diff --git a/.gitignore b/.gitignore index 535818f5..0714c5a2 100644 --- a/.gitignore +++ b/.gitignore @@ -30,10 +30,12 @@ pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ +cover/ .coverage .cache nosetests.xml coverage.xml +cover/ # Translations *.mo @@ -56,11 +58,32 @@ docs/_build/ #mac .DS_Store *~ -__MACOSX/ #pycharm .idea/* -# ipython notebook stuff -.ipynb_checkpoints/ -*.npy +#Dolphin browser files +.directory/ +.directory + +#Binary data files +*.volume +*.am +*.tiff +*.tif +*.dat +*.DAT +*.zip +*.tar.gz +*.tar +*.SPE +*.setup +*.volume +*.dcm +data/ + +#generated documntation files +doc/resource/api/generated/ + +#iPython Notebook checkpoints +.ipynb_checkpoints diff --git a/demos/tomography/end-to-end/NSLS-II Segmentation workflow design.ipynb b/demos/tomography/end-to-end/NSLS-II Segmentation workflow design.ipynb new file mode 100644 index 00000000..54e84dc8 --- /dev/null +++ b/demos/tomography/end-to-end/NSLS-II Segmentation workflow design.ipynb @@ -0,0 +1,1463 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NSLS-II: Image segmentation workflow example" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook serves as a general illustration of the steps and tools required in order to segment three-dimensional image data sets for quantitative analysis. \n", + "\n", + "The demonstration steps through a sample segmentation workflow, specific to x-ray tomography, and is broken down into each of the intermediate steps required: from \"raw\" collected image to quantified values and parameters." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sample Dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The sample data sets consist of micro-CT volumes collected using a single glass bead packed column.\n", + "\n", + "The final quantified product in this demonstration includes:\n", + "- Solid volume (total volume of the beads)\n", + "- Measured porosity\n", + "- Surface area\n", + "- Curvature\n", + "- Solid grain size distribution (comparison of the volume and surface area of the individual beads in the column section)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Global Dependencies:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The major python packages that are utilized in order to provide image processing functionality, quantification, and visualization include:\n", + "+ Reconstruction\n", + " - tomopy\n", + "+ Registration\n", + " - SimpleITK\n", + "+ Analysis:\n", + " - Numpy\n", + " - Scikit-Image\n", + " - Scikit-Xray\n", + " \n", + "+ Visualization:\n", + " - Summary Tables\n", + " - Pandas\n", + " - Two-dimensional Visualization\n", + " - Xray-vision\n", + " - Matplotlib\n", + " - Pyqtgraph\n", + " - Three-dimensional Visualization\n", + " - VTK\n", + " - MayaVI\n", + " - Pyqtgraph\n", + "\n", + "These packages are imported here for common use throughout the demonstration.\n", + "\n", + "An equivalent and parallel demonstration, using VisTrails, is provided to illustrate how to conduct the same operations using the VisTrails workflow and provanance manager." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**In the current implementation both mayavi and xray-vision must be imported first, in order to prevent conflicts with default settings associated with direct import of matplotlib.**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:traits.has_traits:DEPRECATED: traits.has_traits.wrapped_class, 'the 'implements' class advisor has been deprecated. Use the 'provides' class decorator.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "********************************************************************************\n", + "WARNING: Imported VTK version (6.2) does not match the one used\n", + " to build the TVTK classes (5.1). This may cause problems.\n", + " Please rebuild TVTK.\n", + "********************************************************************************\n", + "\n" + ] + } + ], + "source": [ + "import sip\n", + "sip.setapi('QString', 2)\n", + "import mayavi.mlab as mlab\n", + "from xray_vision.mpl_plotting.img_proc_tools import plot_multiple_dsets\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# File I/O\n", + "#from skxray import io\n", + "from vttools.to_wrap.image.io import read_tiff\n", + "#import pims\n", + "import tifffile" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Tomographic reconstruction\n", + "import tomopy" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Image segmentation, analysis and quantification\n", + "import numpy as np\n", + "#import scipy as sp\n", + "import skxray\n", + "import skimage" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One particularly nice feature of iPython Notebook is the ability to have graphical results be plotted inline with the text and code that comprise this demonstration. In order to enable inline plotting using matplotlib\n", + "\n", + "```python\n", + "%matplotlib inline\n", + "```\n", + "\n", + "is included as a 'magic' function prior to the import string for matplotlib." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Plotting and visualization tools\n", + "%matplotlib inline\n", + "import matplotlib\n", + "matplotlib.rcParams[\"backend\"] = \"Qt4Agg\"\n", + "import matplotlib.pyplot as plt\n", + "import pyqtgraph as pqg\n", + "import vtk\n", + "import cv2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Reconstruction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add reconstruction information and example here" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "USING TOMOPY" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### List of camera files associated with the data sets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note there are three .SPE camera files associated with each data set. The data was collected as part of a biofilm growth experiment conducted in collaboration with Dorthe Wildenschild. Imaging was conducted at the Advanced Photon Source, Argonne National Laboratory, Sector 13, BM-D.\n", + "\n", + "The data was collected in March of 2012." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "path_cam_files = \"../data/mCT/camera_files/\"\n", + "cam_fname_abv = ['biofilm_abv_cam_1.SPE', 'biofilm_abv_cam_2.SPE', 'biofilm_abv_cam_3.SPE']\n", + "cam_fname_blw = ['biofilm_blw_cam_1.SPE', 'biofilm_blw_cam_2.SPE', 'biofilm_blw_cam_3.SPE']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load raw camera (SPE) data for reconstruction" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "ERROR:tomopy.io.reader:unknown file extension\n", + "ERROR:tomopy.io.reader:unknown file extension\n", + "ERROR:tomopy.io.reader:unknown file extension\n", + "ERROR:tomopy.io.reader:unknown file extension\n", + "ERROR:tomopy.io.reader:unknown file extension\n", + "ERROR:tomopy.io.reader:unknown file extension\n" + ] + } + ], + "source": [ + "camfile_abv = []\n", + "camfile_blw = []\n", + "cam_lst = [camfile_abv, camfile_blw]\n", + "for index, dset_list in enumerate([cam_fname_abv, cam_fname_blw]):\n", + " for fname in dset_list:\n", + " cam_lst[index].append(tomopy.read_aps_13bm(path_cam_files + fname, 'spe'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "2" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(cam_lst)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(cam_lst[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "10" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(cam_lst[0][2])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "tmp" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function read_spe in module tomopy.io.reader:\n", + "\n", + "read_spe(fname, slc=None)\n", + " Read data from spe file.\n", + " \n", + " Parameters\n", + " ----------\n", + " fname : str\n", + " String defining the path or file name.\n", + " slc : {sequence, int}\n", + " Range of values for slicing data.\n", + " ((start_1, end_1, step_1), ... , (start_N, end_N, step_N))\n", + " defines slicing parameters for each axis of the data matrix.\n", + " \n", + " Returns\n", + " -------\n", + " ndarray\n", + " Data.\n", + "\n" + ] + } + ], + "source": [ + "help(tomopy.read_spe)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function read_aps_13bm in module tomopy.io.exchange:\n", + "\n", + "read_aps_13bm(fname, format, proj=None, sino=None)\n", + " Read APS 13-BM standard data format.\n", + " \n", + " Parameters\n", + " ----------\n", + " fname : str\n", + " Path to hdf5 file.\n", + " \n", + " format : str\n", + " Data format. 'spe' or 'netcdf4'\n", + " \n", + " proj : {sequence, int}, optional\n", + " Specify projections to read. (start, end, step)\n", + " \n", + " sino : {sequence, int}, optional\n", + " Specify sinograms to read. (start, end, step)\n", + " \n", + " Returns\n", + " -------\n", + " ndarray\n", + " 3D tomographic data.\n", + "\n" + ] + } + ], + "source": [ + "help(tomopy.read_aps_13bm)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function find_center in module tomopy.recon.rotation:\n", + "\n", + "find_center(tomo, theta, ind=None, emission=True, init=None, tol=0.5, mask=True, ratio=1.0)\n", + " Find rotation axis location.\n", + " \n", + " The function exploits systematic artifacts in reconstructed images\n", + " due to shifts in the rotation center. It uses image entropy\n", + " as the error metric and ''Nelder-Mead'' routine (of the scipy\n", + " optimization module) as the optimizer :cite:`Donath:06`.\n", + " \n", + " Parameters\n", + " ----------\n", + " tomo : ndarray\n", + " 3D tomographic data.\n", + " theta : array\n", + " Projection angles in radian.\n", + " ind : int, optional\n", + " Index of the slice to be used for reconstruction.\n", + " emission : bool, optional\n", + " Determines whether data is emission or transmission type.\n", + " init : float\n", + " Initial guess for the center.\n", + " tol : scalar\n", + " Desired sub-pixel accuracy.\n", + " mask : bool, optional\n", + " If ``True``, apply a circular mask to the reconstructed image to\n", + " limit the analysis into a circular region.\n", + " ratio : float, optional\n", + " The ratio of the radius of the circular mask to the edge of the\n", + " reconstructed image.\n", + " \n", + " Returns\n", + " -------\n", + " float\n", + " Rotation axis location.\n", + "\n" + ] + } + ], + "source": [ + "help(tomopy.find_center)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "recon_abv = tomopy.find_center" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "4095" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "camfile_abv\n", + "np.amax(camfile_abv[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 1: Import Above and Below Edge volumes:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: PIMS" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#vol_abv = pims.TiffStack(fname_abv)\n", + "#vol_blw = pims.TiffStack(fname_blw)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains functions and tools for reading, writing and converting common image processing files and file types." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ls" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_path = \"../data/\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#fname_abv_tiff = data_path + \"uCT/NSLS_shale_smpl-2_AbvFe.tiff\"\n", + "fname_blw_tiff = data_path + \"uCT/NSLS_shale_smpl-2_BlwFe.tiff\"\n", + "fname_abv = data_path + \"mCT/biofilm_33pcntBa__A_recon.volume\"\n", + "fname_blw = data_path + \"mCT/biofilm_33pcntBa__B_recon.volume\"\n", + "fname_bdpack = data_path + \"mCT/dry_beadpack_A_recon.volume\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ls ../data/uCT/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pwd" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [ + "tst = read_tiff(fname_blw_tiff)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "fnames = [fname_abv, fname_blw, fname_bdpack]\n", + "#for index, var in enumerate(fnames):\n", + "# print index\n", + "# print var\n", + "header_abv, vol_abv = io.net_cdf_io.load_netCDF(fname_abv)\n", + "header_blw, vol_blw = io.net_cdf_io.load_netCDF(fname_blw)\n", + "header_dry, vol_dry = io.net_cdf_io.load_netCDF(fname_bdpack)\n", + "\n", + "print \"Array Max Value: \" + str(np.max(vol_abv))\n", + "print \"Array Min Value: \" + str(np.min(vol_abv))\n", + "#print header_dict_abv\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sample netCDF header\n", + "The header in these netCDF files retains important information pertinent to not only the data set, but also to how the data set was collected.\n", + "\n", + "### Header Example:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [ + "print header_blw" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Select how many of the available volumes to load\n", + "num_vols = 3 # Length of the data list, dummy.\n", + "axis = \"XY\"\n", + "height = None\n", + "num_columns = None\n", + "#Input Lists\n", + "sample_data = [vol_abv, vol_blw, vol_dry]\n", + "plot_titles = [\"Bead pack sample: above Ba edge\", \"Bead pack sample: below Ba edge\", \"Bead pack sample: Dry column\"]\n", + "#Error: If other than XY selected and data is only 2D array, then raise error pointing this out.\n", + "plot_multiple_dsets (sample_data, 450, plot_titles, \"YZ\", num_columns=1)\n", + "\n", + " # if plot_titles=None:\n", + " # for -- create for loop to generate list of str with (Dataset # 'index': 'dset variable name')\n", + "#for x in range(num_vols):\n", + "# plt.figure(figsize = (5,(5.25*num_vols)))\n", + "# num_rows = num_vols\n", + "# num_columns = 1\n", + "# plt.subplot(((num_rows * 10 + num_columns) * 10 + (x+1)))\n", + "# plt.imshow(sample_data[x][:,450,:], cmap=plt.cm.gray)\n", + "# plt.title(plot_titles[x])\n", + "#plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "def auto_plot (num_figs, num_rows, num_cols, src_data_list, title_list=None, indi_figSize = None, display_slc=None):\n", + " if indi_figSize == None:\n", + " figsize = 5\n", + " else:\n", + " figsize = indi_figSize\n", + " \n", + " plt.figure(figsize = ((figsize*num_cols),(figsize*num_rows)))\n", + " for x in range(len(src_data_list)):\n", + " sample_data = src_data_list[x]\n", + " if len(sample_data.shape) == 2:\n", + " slc = sample_data[x][:,:]\n", + " elif len(sample_data.shape) == 3 and display_slc == None:\n", + " slc = sample_data[x][int(sample_data.shape[0]/2),:,:]\n", + " elif len(sample_data.shape) == 3 and display_slc != None:\n", + " slc = sample_data[x][int(display_slc),:,:]\n", + " plt.subplot(((num_rows * 10 + num_columns) * 10 + (x+1)))\n", + " plt.imshow(slc, cmap=plt.cm.gray)\n", + " plt.title(title_list[x])\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 2: Volume transformation to correct alignment" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Source Packages: vttools.to_wrap.image.transformation.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains tools for basic spatial transformation of image volumes" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "The tools currently included in this module are:\n", + " + swap_axes\n", + " + flip_axis\n", + " + crop_volume\n", + " + rotate_volume" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from vttools.to_wrap.image import transformation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The z-axis orientation for all three of the volumes loaded as part of this demonstration is flipped. A problem that isn't necessarily an issue unless spatial orientation is important in the data analysis (e.g. when looking at sequential tiles in a single experimental sample, or when looking at spatial changes in a material over the course of an experiment). As a result, the data sets need to be flipped along the z-axis." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "len(sample_data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "corrected_src_data = []\n", + "for x in sample_data:\n", + " xForm_vol = transformation.flip_axis(x, \"Flip Z\")\n", + " corrected_src_data.append(xForm_vol)\n", + "num_rows=3\n", + "num_cols=2\n", + "plt.figure(figsize = ((5*num_cols),(5*num_rows)))\n", + "for x in range(len(corrected_src_data)):\n", + " plt.subplot(((num_rows * 10 + (num_cols)) * 10 + 2*x+1))\n", + " plt.subplot(320+(x*2+1))\n", + " plt.imshow(sample_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Original grayscale data')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + 2*x+2))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 3: Histogram analysis of trial volume" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This module consists of a collection of functions specific to histogram visualization and analysis. A variety of options are included for both displaying and saving histogram data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: histops.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from vttools.to_wrap.image import histogram\n", + "from xray_vision.mpl_plotting.img_proc_tools import plot_histogram" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "num_cols = 2\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "num_bins = 1500\n", + "pdf_hist = False\n", + "plt.figure(figsize = ((5.5*num_cols),(5*num_rows)))\n", + "plot_yscale = 'linear'\n", + "for x in range(len(corrected_src_data)):\n", + " hist, bin_edges, bin_avg = histogram.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " \n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " plt.subplot(((num_rows * 10 + (num_cols)) * 10 + 2*x+1))\n", + " plt.subplot(320+(x*2+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + 2*x+2))\n", + " #plot_histogram(hist, bin_edges, plot_min, plot_max, plot_yscale)\n", + "plt.show()\n", + "print np.amin(hist)\n", + "print np.amax(hist)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 4: Thresholding for trial volume segmentation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: threshops.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains tools for thresholding image data." + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Currently a number of tools are available for both manual and automatic thresholding.\n", + "\n", + "Manual:\n", + " Manual thresholding requires that threshold intensities be identified and explicitly stated\n", + " within the thresholding function call. The result will consist of a binary representation of \n", + " the original data set where all voxels, originally assinged an intensity value within the\n", + " specified boundary are assigned a value of 1 (True), and all voxels with intensity values\n", + " outside the specified bounds are assigned a value of 0 (False).\n", + " \n", + " Options for manual thresholding:\n", + " + Global thresholding [requires only one threshold value be specified]:\n", + " *thresh_globalGT() -- Greater than the specified value\n", + " *thresh_globalLT() -- Less than the specified value \n", + " + Bounded thresholding [requires two threshold values be specified]:\n", + " *thresh_bounded() -- Identifies all voxels with intensities within bounded region.\n", + " This method is useful for isolating specific peaks, or materials, within a single\n", + " data set -- termed multi-thresholding.\n", + "Automatic: \n", + " Options for automatic thresholding:\n", + " + Adaptive thresholding:\n", + " *thresh_adapt()\n", + " + Otsu method:\n", + " *thresh_otsu()\n", + " + Yen method:\n", + " *thresh_yen()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import threshops" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Manual thresholding demonstration\n", + "thresh_value = 1000\n", + "\n", + "solid_matrix = []\n", + "\n", + "for x in range(len(corrected_src_data)):\n", + " manual_result = threshops.thresh_globalGT(corrected_src_data[x], thresh_value)\n", + " solid_matrix.append(manual_result)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Plotting manual thresholding results\n", + "num_cols = 3\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "plt.figure(figsize = ((5.5*num_cols),(6*num_rows)))\n", + "for x in range(len(corrected_src_data)):\n", + " hist, bin_edges, bin_avg = histops.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " thresh_coords_x = [thresh_value, thresh_value]\n", + " thresh_coords_y = [np.amin(hist), np.amax(hist)]\n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+2))\n", + " histops.hist_plot(hist, bin_edges, plot_min, plot_max, plot_yscale, 'No')\n", + " plt.plot(thresh_coords_x, thresh_coords_y, color='r')\n", + " plt.annotate('threshold marker', \n", + " xy=(thresh_value, (np.amax(hist)*0.7)), \n", + " xytext=((thresh_value+750), np.amax(hist)*0.95),\n", + " arrowprops=dict(facecolor='red', shrink=0.05)\n", + " )\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+3))\n", + " plt.imshow(solid_matrix[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from thresholding')\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Automatic thresholding demonstration\n", + "auto_adapt_solid = []\n", + "auto_otsu_solid = []\n", + "auto_yen_solid = []\n", + "\n", + "\n", + "for x in range(len(corrected_src_data)):\n", + " \n", + " adapt_block_size = 250\n", + " adapt_thresh = threshops.thresh_adapt(corrected_src_data[x], adapt_block_size)\n", + " auto_adapt_solid.append(adapt_thresh)\n", + " \n", + " otsu_thresh_trial, otsu_T_value = threshops.thresh_otsu(corrected_src_data[x])\n", + " auto_otsu_solid.append(otsu_thresh_trial)\n", + " \n", + " yen_thresh_trial, yen_T_value = threshops.thresh_yen(corrected_src_data[x])\n", + " auto_yen_solid.append(yen_thresh_trial)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "plt.imshow(solid_matrix[0][:,250,:], cmap=plt.cm.gray)\n", + "plt.show()\n", + "for x in range(num_vols):\n", + " print x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Plotting automatic thresholding results\n", + "num_cols = 6\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "plt.figure(figsize = ((5.5*num_cols),(6*num_rows)))\n", + "for x in range(num_vols):\n", + " hist, bin_edges, bin_avg = histops.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " \n", + " thresh_type_labels = ['manual', 'Otsu', 'Yen']\n", + " label_offsets = [0.95, 0.8, 0.6]\n", + " thresh_coords_x = [[thresh_value, thresh_value], \n", + " [otsu_T_value, otsu_T_value], \n", + " [yen_T_value, yen_T_value]]\n", + " thresh_coords_y = [np.amin(hist), np.amax(hist)]\n", + " color_set_ = ['r', 'g', 'b']\n", + " \n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+2))\n", + " histops.hist_plot(hist, bin_edges, plot_min, plot_max, plot_yscale, 'No')\n", + " for y in range(len(thresh_type_labels)):\n", + " plt.plot(thresh_coords_x[y], thresh_coords_y, color=color_set_[y])\n", + " plt.annotate(thresh_type_labels[y], \n", + " xy=(thresh_coords_x[y][0], (np.amax(hist)*0.7)),\n", + " xytext=((thresh_coords_x[y][0]+750), np.amax(hist)*label_offsets[y]), \n", + " arrowprops=dict(facecolor=color_set_[y], shrink=0.05))\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+3))\n", + " plt.imshow(solid_matrix[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from manual thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+4))\n", + " \n", + " plt.imshow(auto_adapt_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Adaptive thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+5))\n", + " plt.imshow(auto_otsu_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Otsu thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+6))\n", + " plt.imshow(auto_yen_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Yen thresholding')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Adaptive thresholding: Block size evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ad_block_size = [5, 10, 20, 50, 100, 250]\n", + "num_cols = 6\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "ad_test = []\n", + "plt.figure(figsize = (((5.5*num_cols),(6*num_rows))))\n", + "for x in range(len(corrected_src_data)):\n", + " for y in range(len(ad_block_size)):\n", + " tmp_binary = threshops.thresh_adapt(corrected_src_data[x], ad_block_size[y])\n", + " ad_test.append(tmp_binary)\n", + " if y == 0:\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " plt.title(\"Original Data\")\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+y+1))\n", + " plt.imshow(ad_test[y][:,250,:])\n", + " plt.title(\"Adaptive threshold: Block size = \" + str(ad_block_size[y]))\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 5: Isolate pore space" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: mathops.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import mathops\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pore_space = []\n", + "\n", + "for x in range(len(solid_matrix)):\n", + " tmp_pore = np.logical_not(solid_matrix[x])\n", + " pore_space.append(tmp_pore)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 6: Generate exterior mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: synth_drawing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import synth_drawing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "exterior_mask=synth_drawing.draw_cylinder(corrected_src_data[0], None, 325, None, None, 'YES')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Masked volume demonstration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "mask_demo=synth_drawing.draw_cylinder(corrected_src_data[0], \n", + " radius=325, \n", + " value = 2000, \n", + " draw_exterior='YES', \n", + " apply_mask='yes')\n", + "\n", + "plt.imshow(mask_demo[50,:,:])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Isolated phase presentation:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Glass beads: solid_matrix[0]\n", + "#Pore space: pore_space[0]\n", + "#exterior: exterior_mask\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "plt.figure(figsize = (15,4.5))\n", + "plt.subplot(131)\n", + "plt.imshow(solid_matrix[0][50,:,:])\n", + "plt.subplot(132)\n", + "plt.imshow(pore_space[0][50,:,:])\n", + "plt.subplot(133)\n", + "plt.imshow(exterior_mask[50,:,:])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 7: Merge materials and label" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import filterops as fltr\n", + "import morphology as morph\n", + "import scipy.ndimage.measurements as measure\n", + "import mathops\n", + "\n", + "def logical_sub(src_data1, \n", + " src_data2):\n", + " temp = np.logical_not(np.logical_and(src_data1, \n", + " src_data2))\n", + " output = np.logical_and(src_data1, \n", + " temp)\n", + " return output\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#rough quantification\n", + "labels_rough = (exterior_mask) + (pore_space[0]) + (solid_matrix[0]*3)\n", + "glass_bead_corrected = 3*(logical_sub(solid_matrix[0], exterior_mask))\n", + "pore_space_corrected = 2*(logical_sub(pore_space[0], exterior_mask))\n", + "\n", + "#Merge volume:\n", + "label_field = (exterior_mask + 2*pore_space_corrected + 3*glass_bead_corrected)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "label_field_int = label_field.astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "plt.imshow(label_field_int[50,:,:], cmap=plt.cm.gray)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import imgQuant\n", + "\n", + "measures, vol_rec = imgQuant.Q_VOL(label_field_int)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "bead_vol = measures['Material_4']['volume']['value']\n", + "pore_sp_vol = measures['Material_1']['volume']['value']\n", + "\n", + "bead_vol_corrected = float(bead_vol) * 9.5**3\n", + "pore_sp_vol_corrected = float(pore_sp_vol) * 9.5**3\n", + "print \"Measured bead volume (um^3): \" + str(bead_vol_corrected)\n", + "print \"Measured pore space (um^3): \" + str(pore_sp_vol_corrected)\n", + "porosity = pore_sp_vol/(bead_vol+pore_sp_vol)\n", + "print \"Measured column section porosity is: \" + str(porosity)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Volume confirmation:\n", + "total_vol = bead_vol_corrected" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [ + "!gist \"NSLS-II Segmentation workflow design.ipynb\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/end-to-end/download_data.py b/demos/tomography/end-to-end/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/end-to-end/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/end-to-end/ipTools_DryScan_SegDemo.ipynb b/demos/tomography/end-to-end/ipTools_DryScan_SegDemo.ipynb new file mode 100644 index 00000000..602e0a85 --- /dev/null +++ b/demos/tomography/end-to-end/ipTools_DryScan_SegDemo.ipynb @@ -0,0 +1,1638 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "Link: https://www.dropbox.com/sh/3jzjcqkagbhjl68/AACo2xfhg-3HqHjzCBvVeRFGa?dl=0" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NSLS-II ipTools: Software Tool Demonstration" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "This notebook serves as a practical demonstration of the segmentation and quantification tools available in the image processing toolset compiled as a part of our LDRD.\n", + "\n", + "The demonstration steps through a sample segmentation workflow, and is broken down based on the toolbox modules that are included in our image processing functional library." + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Sample Dataset:\n", + "\n", + "The sample data sets consist of tiled micro-CT volumes collected using a single glass bead packed column." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Global Dependencies:" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "The major python packages that are planned to be included at the most basic level of the proposed NSLS-II python-based functional library consist of:\n", + " \n", + " + Numpy\n", + " + Scipy\n", + " + Matplotlib\n", + "\n", + "These packages are imported here for common use throughout the demonstration.\n", + "\n", + "The modules being developed as a part of our LDRD are loaded individually as they are utilized throughout this demonstration." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import scipy as sp\n", + "#import cv2\n", + "#import mayavi.mlab as mlab\n", + "from skxray.io.net_cdf_io import load_netCDF" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "One particularly nice feature of iPython Notebook is the ability to have graphical results be plotted inline with the text and code that comprise this demonstration. The command in this cell enables that inline functionality." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 1: Import trial volume: Dry scan of a glass bead-packed column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: fileops.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains all functions and tools for reading, writing and converting common image processing files and file types." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from vttools.vtmods.io import ReadTiff" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "SyntaxError", + "evalue": "invalid syntax (, line 1)", + "output_type": "error", + "traceback": [ + "\u001b[1;36m File \u001b[1;32m\"\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m ReadTiff.\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "ReadTiff." + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Explicit definition of the source files used in this demonstration, including path to the containing directory, and the range of file names available for use in this segmentation demonstration." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "path_parentDir = '/home/giltis/Dropbox/BNL_Docs/Alt_File_Formats/3D_RAW/Shewanella_col_4/'\n", + "src_path3D = path_parentDir\n", + "src_file3D_base = 'Shewanella_col_4_dry_'\n", + "vol_ID_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G']\n", + "src_file_suffix = '_recon.volume'" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Each of the volumes was collected at the APS, Sector 13, GSECARS. The native file format of that beamline is netCDF.\n", + "\n", + "A number of common CT file types are currently accessible using both read and write options. The file I/O module currently allows for loading of the following file types:\n", + "READ:\n", + " + netCDF -- COMMAND: load_netCDF\n", + " + TIFF -- COMMAND: load_tif\n", + " + Raw -- COMMAND: load_RAW\n", + " + HDF5 -- COMMAND: open_H5_file\n", + "\n", + "WRITE:\n", + " + TIFF -- COMMAND: save_data_Tiff" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Successfully loaded: Shewanella_col_4_dry_A_recon.volume\n", + "Volume max value: OrderedDict([(u'title', u'Shewanella Column #4'), (u'operator', u'Iltis'), (u'camera', u'CoolSnap, Nikon macro, 15mm tube'), (u'sample', u'glass beads'), (u'image_type', u'RECONSTRUCTED'), (u'energy', 25.570999), (u'dark_current', 99.0), (u'center', 345.36374), (u'x_pixel_size', 9.7600002), (u'y_pixel_size', 9.7600002), (u'z_pixel_size', 0.0), (u'angles', array([ 0. , 0.25, 0.5 , 0.75, 1. , 1.25, 1.5 ,\n", + " 1.75, 2. , 2.25, 2.5 , 2.75, 3. , 3.25,\n", + " 3.5 , 3.75, 4. , 4.25, 4.5 , 4.75, 5. ,\n", + " 5.25, 5.5 , 5.75, 6. , 6.25, 6.5 , 6.75,\n", + " 7. , 7.25, 7.5 , 7.75, 8. , 8.25, 8.5 ,\n", + " 8.75, 9. , 9.25, 9.5 , 9.75, 10. , 10.25,\n", + " 10.5 , 10.75, 11. , 11.25, 11.5 , 11.75, 12. ,\n", + " 12.25, 12.5 , 12.75, 13. , 13.25, 13.5 , 13.75,\n", + " 14. , 14.25, 14.5 , 14.75, 15. , 15.25, 15.5 ,\n", + " 15.75, 16. , 16.25, 16.5 , 16.75, 17. , 17.25,\n", + " 17.5 , 17.75, 18. , 18.25, 18.5 , 18.75, 19. ,\n", + " 19.25, 19.5 , 19.75, 20. , 20.25, 20.5 , 20.75,\n", + " 21. , 21.25, 21.5 , 21.75, 22. , 22.25, 22.5 ,\n", + " 22.75, 23. , 23.25, 23.5 , 23.75, 24. , 24.25,\n", + " 24.5 , 24.75, 25. , 25.25, 25.5 , 25.75, 26. ,\n", + " 26.25, 26.5 , 26.75, 27. , 27.25, 27.5 , 27.75,\n", + " 28. , 28.25, 28.5 , 28.75, 29. , 29.25, 29.5 ,\n", + " 29.75, 30. , 30.25, 30.5 , 30.75, 31. , 31.25,\n", + " 31.5 , 31.75, 32. , 32.25, 32.5 , 32.75, 33. ,\n", + " 33.25, 33.5 , 33.75, 34. , 34.25, 34.5 , 34.75,\n", + " 35. , 35.25, 35.5 , 35.75, 36. , 36.25, 36.5 ,\n", + " 36.75, 37. , 37.25, 37.5 , 37.75, 38. , 38.25,\n", + " 38.5 , 38.75, 39. , 39.25, 39.5 , 39.75, 40. ,\n", + " 40.25, 40.5 , 40.75, 41. , 41.25, 41.5 , 41.75,\n", + " 42. , 42.25, 42.5 , 42.75, 43. , 43.25, 43.5 ,\n", + " 43.75, 44. , 44.25, 44.5 , 44.75, 45. , 45.25,\n", + " 45.5 , 45.75, 46. , 46.25, 46.5 , 46.75, 47. ,\n", + " 47.25, 47.5 , 47.75, 48. , 48.25, 48.5 , 48.75,\n", + " 49. , 49.25, 49.5 , 49.75, 50. , 50.25, 50.5 ,\n", + " 50.75, 51. , 51.25, 51.5 , 51.75, 52. , 52.25,\n", + " 52.5 , 52.75, 53. , 53.25, 53.5 , 53.75, 54. ,\n", + " 54.25, 54.5 , 54.75, 55. , 55.25, 55.5 , 55.75,\n", + " 56. , 56.25, 56.5 , 56.75, 57. , 57.25, 57.5 ,\n", + " 57.75, 58. , 58.25, 58.5 , 58.75, 59. , 59.25,\n", + " 59.5 , 59.75, 60. , 60.25, 60.5 , 60.75, 61. ,\n", + " 61.25, 61.5 , 61.75, 62. , 62.25, 62.5 , 62.75,\n", + " 63. , 63.25, 63.5 , 63.75, 64. , 64.25, 64.5 ,\n", + " 64.75, 65. , 65.25, 65.5 , 65.75, 66. , 66.25,\n", + " 66.5 , 66.75, 67. , 67.25, 67.5 , 67.75, 68. ,\n", + " 68.25, 68.5 , 68.75, 69. , 69.25, 69.5 , 69.75,\n", + " 70. , 70.25, 70.5 , 70.75, 71. , 71.25, 71.5 ,\n", + " 71.75, 72. , 72.25, 72.5 , 72.75, 73. , 73.25,\n", + " 73.5 , 73.75, 74. , 74.25, 74.5 , 74.75, 75. ,\n", + " 75.25, 75.5 , 75.75, 76. , 76.25, 76.5 , 76.75,\n", + " 77. , 77.25, 77.5 , 77.75, 78. , 78.25, 78.5 ,\n", + " 78.75, 79. , 79.25, 79.5 , 79.75, 80. , 80.25,\n", + " 80.5 , 80.75, 81. , 81.25, 81.5 , 81.75, 82. ,\n", + " 82.25, 82.5 , 82.75, 83. , 83.25, 83.5 , 83.75,\n", + " 84. , 84.25, 84.5 , 84.75, 85. , 85.25, 85.5 ,\n", + " 85.75, 86. , 86.25, 86.5 , 86.75, 87. , 87.25,\n", + " 87.5 , 87.75, 88. , 88.25, 88.5 , 88.75, 89. ,\n", + " 89.25, 89.5 , 89.75, 90. , 90.25, 90.5 , 90.75,\n", + " 91. , 91.25, 91.5 , 91.75, 92. , 92.25, 92.5 ,\n", + " 92.75, 93. , 93.25, 93.5 , 93.75, 94. , 94.25,\n", + " 94.5 , 94.75, 95. , 95.25, 95.5 , 95.75, 96. ,\n", + " 96.25, 96.5 , 96.75, 97. , 97.25, 97.5 , 97.75,\n", + " 98. , 98.25, 98.5 , 98.75, 99. , 99.25, 99.5 ,\n", + " 99.75, 100. , 100.25, 100.5 , 100.75, 101. , 101.25,\n", + " 101.5 , 101.75, 102. , 102.25, 102.5 , 102.75, 103. ,\n", + " 103.25, 103.5 , 103.75, 104. , 104.25, 104.5 , 104.75,\n", + " 105. , 105.25, 105.5 , 105.75, 106. , 106.25, 106.5 ,\n", + " 106.75, 107. , 107.25, 107.5 , 107.75, 108. , 108.25,\n", + " 108.5 , 108.75, 109. , 109.25, 109.5 , 109.75, 110. ,\n", + " 110.25, 110.5 , 110.75, 111. , 111.25, 111.5 , 111.75,\n", + " 112. , 112.25, 112.5 , 112.75, 113. , 113.25, 113.5 ,\n", + " 113.75, 114. , 114.25, 114.5 , 114.75, 115. , 115.25,\n", + " 115.5 , 115.75, 116. , 116.25, 116.5 , 116.75, 117. ,\n", + " 117.25, 117.5 , 117.75, 118. , 118.25, 118.5 , 118.75,\n", + " 119. , 119.25, 119.5 , 119.75, 120. , 120.25, 120.5 ,\n", + " 120.75, 121. , 121.25, 121.5 , 121.75, 122. , 122.25,\n", + " 122.5 , 122.75, 123. , 123.25, 123.5 , 123.75, 124. ,\n", + " 124.25, 124.5 , 124.75, 125. , 125.25, 125.5 , 125.75,\n", + " 126. , 126.25, 126.5 , 126.75, 127. , 127.25, 127.5 ,\n", + " 127.75, 128. , 128.25, 128.5 , 128.75, 129. , 129.25,\n", + " 129.5 , 129.75, 130. , 130.25, 130.5 , 130.75, 131. ,\n", + " 131.25, 131.5 , 131.75, 132. , 132.25, 132.5 , 132.75,\n", + " 133. , 133.25, 133.5 , 133.75, 134. , 134.25, 134.5 ,\n", + " 134.75, 135. , 135.25, 135.5 , 135.75, 136. , 136.25,\n", + " 136.5 , 136.75, 137. , 137.25, 137.5 , 137.75, 138. ,\n", + " 138.25, 138.5 , 138.75, 139. , 139.25, 139.5 , 139.75,\n", + " 140. , 140.25, 140.5 , 140.75, 141. , 141.25, 141.5 ,\n", + " 141.75, 142. , 142.25, 142.5 , 142.75, 143. , 143.25,\n", + " 143.5 , 143.75, 144. , 144.25, 144.5 , 144.75, 145. ,\n", + " 145.25, 145.5 , 145.75, 146. , 146.25, 146.5 , 146.75,\n", + " 147. , 147.25, 147.5 , 147.75, 148. , 148.25, 148.5 ,\n", + " 148.75, 149. , 149.25, 149.5 , 149.75, 150. , 150.25,\n", + " 150.5 , 150.75, 151. , 151.25, 151.5 , 151.75, 152. ,\n", + " 152.25, 152.5 , 152.75, 153. , 153.25, 153.5 , 153.75,\n", + " 154. , 154.25, 154.5 , 154.75, 155. , 155.25, 155.5 ,\n", + " 155.75, 156. , 156.25, 156.5 , 156.75, 157. , 157.25,\n", + " 157.5 , 157.75, 158. , 158.25, 158.5 , 158.75, 159. ,\n", + " 159.25, 159.5 , 159.75, 160. , 160.25, 160.5 , 160.75,\n", + " 161. , 161.25, 161.5 , 161.75, 162. , 162.25, 162.5 ,\n", + " 162.75, 163. , 163.25, 163.5 , 163.75, 164. , 164.25,\n", + " 164.5 , 164.75, 165. , 165.25, 165.5 , 165.75, 166. ,\n", + " 166.25, 166.5 , 166.75, 167. , 167.25, 167.5 , 167.75,\n", + " 168. , 168.25, 168.5 , 168.75, 169. , 169.25, 169.5 ,\n", + " 169.75, 170. , 170.25, 170.5 , 170.75, 171. , 171.25,\n", + " 171.5 , 171.75, 172. , 172.25, 172.5 , 172.75, 173. ,\n", + " 173.25, 173.5 , 173.75, 174. , 174.25, 174.5 , 174.75,\n", + " 175. , 175.25, 175.5 , 175.75, 176. , 176.25, 176.5 ,\n", + " 176.75, 177. , 177.25, 177.5 , 177.75, 178. , 178.25,\n", + " 178.5 , 178.75, 179. , 179.25, 179.5 , 179.75], dtype=float32)), ('voxel_size', {'units': '', 'type': , 'value': 9.7600002})])\n", + "Vol Max Check: OrderedDict([(u'title', u'Shewanella Column #4'), (u'operator', u'Iltis'), (u'camera', u'CoolSnap, Nikon macro, 15mm tube'), (u'sample', u'glass beads'), (u'image_type', u'RECONSTRUCTED'), (u'energy', 25.570999), (u'dark_current', 99.0), (u'center', 345.36374), (u'x_pixel_size', 9.7600002), (u'y_pixel_size', 9.7600002), (u'z_pixel_size', 0.0), (u'angles', array([ 0. , 0.25, 0.5 , 0.75, 1. , 1.25, 1.5 ,\n", + " 1.75, 2. , 2.25, 2.5 , 2.75, 3. , 3.25,\n", + " 3.5 , 3.75, 4. , 4.25, 4.5 , 4.75, 5. ,\n", + " 5.25, 5.5 , 5.75, 6. , 6.25, 6.5 , 6.75,\n", + " 7. , 7.25, 7.5 , 7.75, 8. , 8.25, 8.5 ,\n", + " 8.75, 9. , 9.25, 9.5 , 9.75, 10. , 10.25,\n", + " 10.5 , 10.75, 11. , 11.25, 11.5 , 11.75, 12. ,\n", + " 12.25, 12.5 , 12.75, 13. , 13.25, 13.5 , 13.75,\n", + " 14. , 14.25, 14.5 , 14.75, 15. , 15.25, 15.5 ,\n", + " 15.75, 16. , 16.25, 16.5 , 16.75, 17. , 17.25,\n", + " 17.5 , 17.75, 18. , 18.25, 18.5 , 18.75, 19. ,\n", + " 19.25, 19.5 , 19.75, 20. , 20.25, 20.5 , 20.75,\n", + " 21. , 21.25, 21.5 , 21.75, 22. , 22.25, 22.5 ,\n", + " 22.75, 23. , 23.25, 23.5 , 23.75, 24. , 24.25,\n", + " 24.5 , 24.75, 25. , 25.25, 25.5 , 25.75, 26. ,\n", + " 26.25, 26.5 , 26.75, 27. , 27.25, 27.5 , 27.75,\n", + " 28. , 28.25, 28.5 , 28.75, 29. , 29.25, 29.5 ,\n", + " 29.75, 30. , 30.25, 30.5 , 30.75, 31. , 31.25,\n", + " 31.5 , 31.75, 32. , 32.25, 32.5 , 32.75, 33. ,\n", + " 33.25, 33.5 , 33.75, 34. , 34.25, 34.5 , 34.75,\n", + " 35. , 35.25, 35.5 , 35.75, 36. , 36.25, 36.5 ,\n", + " 36.75, 37. , 37.25, 37.5 , 37.75, 38. , 38.25,\n", + " 38.5 , 38.75, 39. , 39.25, 39.5 , 39.75, 40. ,\n", + " 40.25, 40.5 , 40.75, 41. , 41.25, 41.5 , 41.75,\n", + " 42. , 42.25, 42.5 , 42.75, 43. , 43.25, 43.5 ,\n", + " 43.75, 44. , 44.25, 44.5 , 44.75, 45. , 45.25,\n", + " 45.5 , 45.75, 46. , 46.25, 46.5 , 46.75, 47. ,\n", + " 47.25, 47.5 , 47.75, 48. , 48.25, 48.5 , 48.75,\n", + " 49. , 49.25, 49.5 , 49.75, 50. , 50.25, 50.5 ,\n", + " 50.75, 51. , 51.25, 51.5 , 51.75, 52. , 52.25,\n", + " 52.5 , 52.75, 53. , 53.25, 53.5 , 53.75, 54. ,\n", + " 54.25, 54.5 , 54.75, 55. , 55.25, 55.5 , 55.75,\n", + " 56. , 56.25, 56.5 , 56.75, 57. , 57.25, 57.5 ,\n", + " 57.75, 58. , 58.25, 58.5 , 58.75, 59. , 59.25,\n", + " 59.5 , 59.75, 60. , 60.25, 60.5 , 60.75, 61. ,\n", + " 61.25, 61.5 , 61.75, 62. , 62.25, 62.5 , 62.75,\n", + " 63. , 63.25, 63.5 , 63.75, 64. , 64.25, 64.5 ,\n", + " 64.75, 65. , 65.25, 65.5 , 65.75, 66. , 66.25,\n", + " 66.5 , 66.75, 67. , 67.25, 67.5 , 67.75, 68. ,\n", + " 68.25, 68.5 , 68.75, 69. , 69.25, 69.5 , 69.75,\n", + " 70. , 70.25, 70.5 , 70.75, 71. , 71.25, 71.5 ,\n", + " 71.75, 72. , 72.25, 72.5 , 72.75, 73. , 73.25,\n", + " 73.5 , 73.75, 74. , 74.25, 74.5 , 74.75, 75. ,\n", + " 75.25, 75.5 , 75.75, 76. , 76.25, 76.5 , 76.75,\n", + " 77. , 77.25, 77.5 , 77.75, 78. , 78.25, 78.5 ,\n", + " 78.75, 79. , 79.25, 79.5 , 79.75, 80. , 80.25,\n", + " 80.5 , 80.75, 81. , 81.25, 81.5 , 81.75, 82. ,\n", + " 82.25, 82.5 , 82.75, 83. , 83.25, 83.5 , 83.75,\n", + " 84. , 84.25, 84.5 , 84.75, 85. , 85.25, 85.5 ,\n", + " 85.75, 86. , 86.25, 86.5 , 86.75, 87. , 87.25,\n", + " 87.5 , 87.75, 88. , 88.25, 88.5 , 88.75, 89. ,\n", + " 89.25, 89.5 , 89.75, 90. , 90.25, 90.5 , 90.75,\n", + " 91. , 91.25, 91.5 , 91.75, 92. , 92.25, 92.5 ,\n", + " 92.75, 93. , 93.25, 93.5 , 93.75, 94. , 94.25,\n", + " 94.5 , 94.75, 95. , 95.25, 95.5 , 95.75, 96. ,\n", + " 96.25, 96.5 , 96.75, 97. , 97.25, 97.5 , 97.75,\n", + " 98. , 98.25, 98.5 , 98.75, 99. , 99.25, 99.5 ,\n", + " 99.75, 100. , 100.25, 100.5 , 100.75, 101. , 101.25,\n", + " 101.5 , 101.75, 102. , 102.25, 102.5 , 102.75, 103. ,\n", + " 103.25, 103.5 , 103.75, 104. , 104.25, 104.5 , 104.75,\n", + " 105. , 105.25, 105.5 , 105.75, 106. , 106.25, 106.5 ,\n", + " 106.75, 107. , 107.25, 107.5 , 107.75, 108. , 108.25,\n", + " 108.5 , 108.75, 109. , 109.25, 109.5 , 109.75, 110. ,\n", + " 110.25, 110.5 , 110.75, 111. , 111.25, 111.5 , 111.75,\n", + " 112. , 112.25, 112.5 , 112.75, 113. , 113.25, 113.5 ,\n", + " 113.75, 114. , 114.25, 114.5 , 114.75, 115. , 115.25,\n", + " 115.5 , 115.75, 116. , 116.25, 116.5 , 116.75, 117. ,\n", + " 117.25, 117.5 , 117.75, 118. , 118.25, 118.5 , 118.75,\n", + " 119. , 119.25, 119.5 , 119.75, 120. , 120.25, 120.5 ,\n", + " 120.75, 121. , 121.25, 121.5 , 121.75, 122. , 122.25,\n", + " 122.5 , 122.75, 123. , 123.25, 123.5 , 123.75, 124. ,\n", + " 124.25, 124.5 , 124.75, 125. , 125.25, 125.5 , 125.75,\n", + " 126. , 126.25, 126.5 , 126.75, 127. , 127.25, 127.5 ,\n", + " 127.75, 128. , 128.25, 128.5 , 128.75, 129. , 129.25,\n", + " 129.5 , 129.75, 130. , 130.25, 130.5 , 130.75, 131. ,\n", + " 131.25, 131.5 , 131.75, 132. , 132.25, 132.5 , 132.75,\n", + " 133. , 133.25, 133.5 , 133.75, 134. , 134.25, 134.5 ,\n", + " 134.75, 135. , 135.25, 135.5 , 135.75, 136. , 136.25,\n", + " 136.5 , 136.75, 137. , 137.25, 137.5 , 137.75, 138. ,\n", + " 138.25, 138.5 , 138.75, 139. , 139.25, 139.5 , 139.75,\n", + " 140. , 140.25, 140.5 , 140.75, 141. , 141.25, 141.5 ,\n", + " 141.75, 142. , 142.25, 142.5 , 142.75, 143. , 143.25,\n", + " 143.5 , 143.75, 144. , 144.25, 144.5 , 144.75, 145. ,\n", + " 145.25, 145.5 , 145.75, 146. , 146.25, 146.5 , 146.75,\n", + " 147. , 147.25, 147.5 , 147.75, 148. , 148.25, 148.5 ,\n", + " 148.75, 149. , 149.25, 149.5 , 149.75, 150. , 150.25,\n", + " 150.5 , 150.75, 151. , 151.25, 151.5 , 151.75, 152. ,\n", + " 152.25, 152.5 , 152.75, 153. , 153.25, 153.5 , 153.75,\n", + " 154. , 154.25, 154.5 , 154.75, 155. , 155.25, 155.5 ,\n", + " 155.75, 156. , 156.25, 156.5 , 156.75, 157. , 157.25,\n", + " 157.5 , 157.75, 158. , 158.25, 158.5 , 158.75, 159. ,\n", + " 159.25, 159.5 , 159.75, 160. , 160.25, 160.5 , 160.75,\n", + " 161. , 161.25, 161.5 , 161.75, 162. , 162.25, 162.5 ,\n", + " 162.75, 163. , 163.25, 163.5 , 163.75, 164. , 164.25,\n", + " 164.5 , 164.75, 165. , 165.25, 165.5 , 165.75, 166. ,\n", + " 166.25, 166.5 , 166.75, 167. , 167.25, 167.5 , 167.75,\n", + " 168. , 168.25, 168.5 , 168.75, 169. , 169.25, 169.5 ,\n", + " 169.75, 170. , 170.25, 170.5 , 170.75, 171. , 171.25,\n", + " 171.5 , 171.75, 172. , 172.25, 172.5 , 172.75, 173. ,\n", + " 173.25, 173.5 , 173.75, 174. , 174.25, 174.5 , 174.75,\n", + " 175. , 175.25, 175.5 , 175.75, 176. , 176.25, 176.5 ,\n", + " 176.75, 177. , 177.25, 177.5 , 177.75, 178. , 178.25,\n", + " 178.5 , 178.75, 179. , 179.25, 179.5 , 179.75], dtype=float32)), ('voxel_size', {'units': '', 'type': , 'value': 9.7600002})])\n", + "Volume min value: OrderedDict([(u'title', u'Shewanella Column #4'), (u'operator', u'Iltis'), (u'camera', u'CoolSnap, Nikon macro, 15mm tube'), (u'sample', u'glass beads'), (u'image_type', u'RECONSTRUCTED'), (u'energy', 25.570999), (u'dark_current', 99.0), (u'center', 345.36374), (u'x_pixel_size', 9.7600002), (u'y_pixel_size', 9.7600002), (u'z_pixel_size', 0.0), (u'angles', array([ 0. , 0.25, 0.5 , 0.75, 1. , 1.25, 1.5 ,\n", + " 1.75, 2. , 2.25, 2.5 , 2.75, 3. , 3.25,\n", + " 3.5 , 3.75, 4. , 4.25, 4.5 , 4.75, 5. ,\n", + " 5.25, 5.5 , 5.75, 6. , 6.25, 6.5 , 6.75,\n", + " 7. , 7.25, 7.5 , 7.75, 8. , 8.25, 8.5 ,\n", + " 8.75, 9. , 9.25, 9.5 , 9.75, 10. , 10.25,\n", + " 10.5 , 10.75, 11. , 11.25, 11.5 , 11.75, 12. ,\n", + " 12.25, 12.5 , 12.75, 13. , 13.25, 13.5 , 13.75,\n", + " 14. , 14.25, 14.5 , 14.75, 15. , 15.25, 15.5 ,\n", + " 15.75, 16. , 16.25, 16.5 , 16.75, 17. , 17.25,\n", + " 17.5 , 17.75, 18. , 18.25, 18.5 , 18.75, 19. ,\n", + " 19.25, 19.5 , 19.75, 20. , 20.25, 20.5 , 20.75,\n", + " 21. , 21.25, 21.5 , 21.75, 22. , 22.25, 22.5 ,\n", + " 22.75, 23. , 23.25, 23.5 , 23.75, 24. , 24.25,\n", + " 24.5 , 24.75, 25. , 25.25, 25.5 , 25.75, 26. ,\n", + " 26.25, 26.5 , 26.75, 27. , 27.25, 27.5 , 27.75,\n", + " 28. , 28.25, 28.5 , 28.75, 29. , 29.25, 29.5 ,\n", + " 29.75, 30. , 30.25, 30.5 , 30.75, 31. , 31.25,\n", + " 31.5 , 31.75, 32. , 32.25, 32.5 , 32.75, 33. ,\n", + " 33.25, 33.5 , 33.75, 34. , 34.25, 34.5 , 34.75,\n", + " 35. , 35.25, 35.5 , 35.75, 36. , 36.25, 36.5 ,\n", + " 36.75, 37. , 37.25, 37.5 , 37.75, 38. , 38.25,\n", + " 38.5 , 38.75, 39. , 39.25, 39.5 , 39.75, 40. ,\n", + " 40.25, 40.5 , 40.75, 41. , 41.25, 41.5 , 41.75,\n", + " 42. , 42.25, 42.5 , 42.75, 43. , 43.25, 43.5 ,\n", + " 43.75, 44. , 44.25, 44.5 , 44.75, 45. , 45.25,\n", + " 45.5 , 45.75, 46. , 46.25, 46.5 , 46.75, 47. ,\n", + " 47.25, 47.5 , 47.75, 48. , 48.25, 48.5 , 48.75,\n", + " 49. , 49.25, 49.5 , 49.75, 50. , 50.25, 50.5 ,\n", + " 50.75, 51. , 51.25, 51.5 , 51.75, 52. , 52.25,\n", + " 52.5 , 52.75, 53. , 53.25, 53.5 , 53.75, 54. ,\n", + " 54.25, 54.5 , 54.75, 55. , 55.25, 55.5 , 55.75,\n", + " 56. , 56.25, 56.5 , 56.75, 57. , 57.25, 57.5 ,\n", + " 57.75, 58. , 58.25, 58.5 , 58.75, 59. , 59.25,\n", + " 59.5 , 59.75, 60. , 60.25, 60.5 , 60.75, 61. ,\n", + " 61.25, 61.5 , 61.75, 62. , 62.25, 62.5 , 62.75,\n", + " 63. , 63.25, 63.5 , 63.75, 64. , 64.25, 64.5 ,\n", + " 64.75, 65. , 65.25, 65.5 , 65.75, 66. , 66.25,\n", + " 66.5 , 66.75, 67. , 67.25, 67.5 , 67.75, 68. ,\n", + " 68.25, 68.5 , 68.75, 69. , 69.25, 69.5 , 69.75,\n", + " 70. , 70.25, 70.5 , 70.75, 71. , 71.25, 71.5 ,\n", + " 71.75, 72. , 72.25, 72.5 , 72.75, 73. , 73.25,\n", + " 73.5 , 73.75, 74. , 74.25, 74.5 , 74.75, 75. ,\n", + " 75.25, 75.5 , 75.75, 76. , 76.25, 76.5 , 76.75,\n", + " 77. , 77.25, 77.5 , 77.75, 78. , 78.25, 78.5 ,\n", + " 78.75, 79. , 79.25, 79.5 , 79.75, 80. , 80.25,\n", + " 80.5 , 80.75, 81. , 81.25, 81.5 , 81.75, 82. ,\n", + " 82.25, 82.5 , 82.75, 83. , 83.25, 83.5 , 83.75,\n", + " 84. , 84.25, 84.5 , 84.75, 85. , 85.25, 85.5 ,\n", + " 85.75, 86. , 86.25, 86.5 , 86.75, 87. , 87.25,\n", + " 87.5 , 87.75, 88. , 88.25, 88.5 , 88.75, 89. ,\n", + " 89.25, 89.5 , 89.75, 90. , 90.25, 90.5 , 90.75,\n", + " 91. , 91.25, 91.5 , 91.75, 92. , 92.25, 92.5 ,\n", + " 92.75, 93. , 93.25, 93.5 , 93.75, 94. , 94.25,\n", + " 94.5 , 94.75, 95. , 95.25, 95.5 , 95.75, 96. ,\n", + " 96.25, 96.5 , 96.75, 97. , 97.25, 97.5 , 97.75,\n", + " 98. , 98.25, 98.5 , 98.75, 99. , 99.25, 99.5 ,\n", + " 99.75, 100. , 100.25, 100.5 , 100.75, 101. , 101.25,\n", + " 101.5 , 101.75, 102. , 102.25, 102.5 , 102.75, 103. ,\n", + " 103.25, 103.5 , 103.75, 104. , 104.25, 104.5 , 104.75,\n", + " 105. , 105.25, 105.5 , 105.75, 106. , 106.25, 106.5 ,\n", + " 106.75, 107. , 107.25, 107.5 , 107.75, 108. , 108.25,\n", + " 108.5 , 108.75, 109. , 109.25, 109.5 , 109.75, 110. ,\n", + " 110.25, 110.5 , 110.75, 111. , 111.25, 111.5 , 111.75,\n", + " 112. , 112.25, 112.5 , 112.75, 113. , 113.25, 113.5 ,\n", + " 113.75, 114. , 114.25, 114.5 , 114.75, 115. , 115.25,\n", + " 115.5 , 115.75, 116. , 116.25, 116.5 , 116.75, 117. ,\n", + " 117.25, 117.5 , 117.75, 118. , 118.25, 118.5 , 118.75,\n", + " 119. , 119.25, 119.5 , 119.75, 120. , 120.25, 120.5 ,\n", + " 120.75, 121. , 121.25, 121.5 , 121.75, 122. , 122.25,\n", + " 122.5 , 122.75, 123. , 123.25, 123.5 , 123.75, 124. ,\n", + " 124.25, 124.5 , 124.75, 125. , 125.25, 125.5 , 125.75,\n", + " 126. , 126.25, 126.5 , 126.75, 127. , 127.25, 127.5 ,\n", + " 127.75, 128. , 128.25, 128.5 , 128.75, 129. , 129.25,\n", + " 129.5 , 129.75, 130. , 130.25, 130.5 , 130.75, 131. ,\n", + " 131.25, 131.5 , 131.75, 132. , 132.25, 132.5 , 132.75,\n", + " 133. , 133.25, 133.5 , 133.75, 134. , 134.25, 134.5 ,\n", + " 134.75, 135. , 135.25, 135.5 , 135.75, 136. , 136.25,\n", + " 136.5 , 136.75, 137. , 137.25, 137.5 , 137.75, 138. ,\n", + " 138.25, 138.5 , 138.75, 139. , 139.25, 139.5 , 139.75,\n", + " 140. , 140.25, 140.5 , 140.75, 141. , 141.25, 141.5 ,\n", + " 141.75, 142. , 142.25, 142.5 , 142.75, 143. , 143.25,\n", + " 143.5 , 143.75, 144. , 144.25, 144.5 , 144.75, 145. ,\n", + " 145.25, 145.5 , 145.75, 146. , 146.25, 146.5 , 146.75,\n", + " 147. , 147.25, 147.5 , 147.75, 148. , 148.25, 148.5 ,\n", + " 148.75, 149. , 149.25, 149.5 , 149.75, 150. , 150.25,\n", + " 150.5 , 150.75, 151. , 151.25, 151.5 , 151.75, 152. ,\n", + " 152.25, 152.5 , 152.75, 153. , 153.25, 153.5 , 153.75,\n", + " 154. , 154.25, 154.5 , 154.75, 155. , 155.25, 155.5 ,\n", + " 155.75, 156. , 156.25, 156.5 , 156.75, 157. , 157.25,\n", + " 157.5 , 157.75, 158. , 158.25, 158.5 , 158.75, 159. ,\n", + " 159.25, 159.5 , 159.75, 160. , 160.25, 160.5 , 160.75,\n", + " 161. , 161.25, 161.5 , 161.75, 162. , 162.25, 162.5 ,\n", + " 162.75, 163. , 163.25, 163.5 , 163.75, 164. , 164.25,\n", + " 164.5 , 164.75, 165. , 165.25, 165.5 , 165.75, 166. ,\n", + " 166.25, 166.5 , 166.75, 167. , 167.25, 167.5 , 167.75,\n", + " 168. , 168.25, 168.5 , 168.75, 169. , 169.25, 169.5 ,\n", + " 169.75, 170. , 170.25, 170.5 , 170.75, 171. , 171.25,\n", + " 171.5 , 171.75, 172. , 172.25, 172.5 , 172.75, 173. ,\n", + " 173.25, 173.5 , 173.75, 174. , 174.25, 174.5 , 174.75,\n", + " 175. , 175.25, 175.5 , 175.75, 176. , 176.25, 176.5 ,\n", + " 176.75, 177. , 177.25, 177.5 , 177.75, 178. , 178.25,\n", + " 178.5 , 178.75, 179. , 179.25, 179.5 , 179.75], dtype=float32)), ('voxel_size', {'units': '', 'type': , 'value': 9.7600002})])\n", + "Vol Min Check: OrderedDict([(u'title', u'Shewanella Column #4'), (u'operator', u'Iltis'), (u'camera', u'CoolSnap, Nikon macro, 15mm tube'), (u'sample', u'glass beads'), (u'image_type', u'RECONSTRUCTED'), (u'energy', 25.570999), (u'dark_current', 99.0), (u'center', 345.36374), (u'x_pixel_size', 9.7600002), (u'y_pixel_size', 9.7600002), (u'z_pixel_size', 0.0), (u'angles', array([ 0. , 0.25, 0.5 , 0.75, 1. , 1.25, 1.5 ,\n", + " 1.75, 2. , 2.25, 2.5 , 2.75, 3. , 3.25,\n", + " 3.5 , 3.75, 4. , 4.25, 4.5 , 4.75, 5. ,\n", + " 5.25, 5.5 , 5.75, 6. , 6.25, 6.5 , 6.75,\n", + " 7. , 7.25, 7.5 , 7.75, 8. , 8.25, 8.5 ,\n", + " 8.75, 9. , 9.25, 9.5 , 9.75, 10. , 10.25,\n", + " 10.5 , 10.75, 11. , 11.25, 11.5 , 11.75, 12. ,\n", + " 12.25, 12.5 , 12.75, 13. , 13.25, 13.5 , 13.75,\n", + " 14. , 14.25, 14.5 , 14.75, 15. , 15.25, 15.5 ,\n", + " 15.75, 16. , 16.25, 16.5 , 16.75, 17. , 17.25,\n", + " 17.5 , 17.75, 18. , 18.25, 18.5 , 18.75, 19. ,\n", + " 19.25, 19.5 , 19.75, 20. , 20.25, 20.5 , 20.75,\n", + " 21. , 21.25, 21.5 , 21.75, 22. , 22.25, 22.5 ,\n", + " 22.75, 23. , 23.25, 23.5 , 23.75, 24. , 24.25,\n", + " 24.5 , 24.75, 25. , 25.25, 25.5 , 25.75, 26. ,\n", + " 26.25, 26.5 , 26.75, 27. , 27.25, 27.5 , 27.75,\n", + " 28. , 28.25, 28.5 , 28.75, 29. , 29.25, 29.5 ,\n", + " 29.75, 30. , 30.25, 30.5 , 30.75, 31. , 31.25,\n", + " 31.5 , 31.75, 32. , 32.25, 32.5 , 32.75, 33. ,\n", + " 33.25, 33.5 , 33.75, 34. , 34.25, 34.5 , 34.75,\n", + " 35. , 35.25, 35.5 , 35.75, 36. , 36.25, 36.5 ,\n", + " 36.75, 37. , 37.25, 37.5 , 37.75, 38. , 38.25,\n", + " 38.5 , 38.75, 39. , 39.25, 39.5 , 39.75, 40. ,\n", + " 40.25, 40.5 , 40.75, 41. , 41.25, 41.5 , 41.75,\n", + " 42. , 42.25, 42.5 , 42.75, 43. , 43.25, 43.5 ,\n", + " 43.75, 44. , 44.25, 44.5 , 44.75, 45. , 45.25,\n", + " 45.5 , 45.75, 46. , 46.25, 46.5 , 46.75, 47. ,\n", + " 47.25, 47.5 , 47.75, 48. , 48.25, 48.5 , 48.75,\n", + " 49. , 49.25, 49.5 , 49.75, 50. , 50.25, 50.5 ,\n", + " 50.75, 51. , 51.25, 51.5 , 51.75, 52. , 52.25,\n", + " 52.5 , 52.75, 53. , 53.25, 53.5 , 53.75, 54. ,\n", + " 54.25, 54.5 , 54.75, 55. , 55.25, 55.5 , 55.75,\n", + " 56. , 56.25, 56.5 , 56.75, 57. , 57.25, 57.5 ,\n", + " 57.75, 58. , 58.25, 58.5 , 58.75, 59. , 59.25,\n", + " 59.5 , 59.75, 60. , 60.25, 60.5 , 60.75, 61. ,\n", + " 61.25, 61.5 , 61.75, 62. , 62.25, 62.5 , 62.75,\n", + " 63. , 63.25, 63.5 , 63.75, 64. , 64.25, 64.5 ,\n", + " 64.75, 65. , 65.25, 65.5 , 65.75, 66. , 66.25,\n", + " 66.5 , 66.75, 67. , 67.25, 67.5 , 67.75, 68. ,\n", + " 68.25, 68.5 , 68.75, 69. , 69.25, 69.5 , 69.75,\n", + " 70. , 70.25, 70.5 , 70.75, 71. , 71.25, 71.5 ,\n", + " 71.75, 72. , 72.25, 72.5 , 72.75, 73. , 73.25,\n", + " 73.5 , 73.75, 74. , 74.25, 74.5 , 74.75, 75. ,\n", + " 75.25, 75.5 , 75.75, 76. , 76.25, 76.5 , 76.75,\n", + " 77. , 77.25, 77.5 , 77.75, 78. , 78.25, 78.5 ,\n", + " 78.75, 79. , 79.25, 79.5 , 79.75, 80. , 80.25,\n", + " 80.5 , 80.75, 81. , 81.25, 81.5 , 81.75, 82. ,\n", + " 82.25, 82.5 , 82.75, 83. , 83.25, 83.5 , 83.75,\n", + " 84. , 84.25, 84.5 , 84.75, 85. , 85.25, 85.5 ,\n", + " 85.75, 86. , 86.25, 86.5 , 86.75, 87. , 87.25,\n", + " 87.5 , 87.75, 88. , 88.25, 88.5 , 88.75, 89. ,\n", + " 89.25, 89.5 , 89.75, 90. , 90.25, 90.5 , 90.75,\n", + " 91. , 91.25, 91.5 , 91.75, 92. , 92.25, 92.5 ,\n", + " 92.75, 93. , 93.25, 93.5 , 93.75, 94. , 94.25,\n", + " 94.5 , 94.75, 95. , 95.25, 95.5 , 95.75, 96. ,\n", + " 96.25, 96.5 , 96.75, 97. , 97.25, 97.5 , 97.75,\n", + " 98. , 98.25, 98.5 , 98.75, 99. , 99.25, 99.5 ,\n", + " 99.75, 100. , 100.25, 100.5 , 100.75, 101. , 101.25,\n", + " 101.5 , 101.75, 102. , 102.25, 102.5 , 102.75, 103. ,\n", + " 103.25, 103.5 , 103.75, 104. , 104.25, 104.5 , 104.75,\n", + " 105. , 105.25, 105.5 , 105.75, 106. , 106.25, 106.5 ,\n", + " 106.75, 107. , 107.25, 107.5 , 107.75, 108. , 108.25,\n", + " 108.5 , 108.75, 109. , 109.25, 109.5 , 109.75, 110. ,\n", + " 110.25, 110.5 , 110.75, 111. , 111.25, 111.5 , 111.75,\n", + " 112. , 112.25, 112.5 , 112.75, 113. , 113.25, 113.5 ,\n", + " 113.75, 114. , 114.25, 114.5 , 114.75, 115. , 115.25,\n", + " 115.5 , 115.75, 116. , 116.25, 116.5 , 116.75, 117. ,\n", + " 117.25, 117.5 , 117.75, 118. , 118.25, 118.5 , 118.75,\n", + " 119. , 119.25, 119.5 , 119.75, 120. , 120.25, 120.5 ,\n", + " 120.75, 121. , 121.25, 121.5 , 121.75, 122. , 122.25,\n", + " 122.5 , 122.75, 123. , 123.25, 123.5 , 123.75, 124. ,\n", + " 124.25, 124.5 , 124.75, 125. , 125.25, 125.5 , 125.75,\n", + " 126. , 126.25, 126.5 , 126.75, 127. , 127.25, 127.5 ,\n", + " 127.75, 128. , 128.25, 128.5 , 128.75, 129. , 129.25,\n", + " 129.5 , 129.75, 130. , 130.25, 130.5 , 130.75, 131. ,\n", + " 131.25, 131.5 , 131.75, 132. , 132.25, 132.5 , 132.75,\n", + " 133. , 133.25, 133.5 , 133.75, 134. , 134.25, 134.5 ,\n", + " 134.75, 135. , 135.25, 135.5 , 135.75, 136. , 136.25,\n", + " 136.5 , 136.75, 137. , 137.25, 137.5 , 137.75, 138. ,\n", + " 138.25, 138.5 , 138.75, 139. , 139.25, 139.5 , 139.75,\n", + " 140. , 140.25, 140.5 , 140.75, 141. , 141.25, 141.5 ,\n", + " 141.75, 142. , 142.25, 142.5 , 142.75, 143. , 143.25,\n", + " 143.5 , 143.75, 144. , 144.25, 144.5 , 144.75, 145. ,\n", + " 145.25, 145.5 , 145.75, 146. , 146.25, 146.5 , 146.75,\n", + " 147. , 147.25, 147.5 , 147.75, 148. , 148.25, 148.5 ,\n", + " 148.75, 149. , 149.25, 149.5 , 149.75, 150. , 150.25,\n", + " 150.5 , 150.75, 151. , 151.25, 151.5 , 151.75, 152. ,\n", + " 152.25, 152.5 , 152.75, 153. , 153.25, 153.5 , 153.75,\n", + " 154. , 154.25, 154.5 , 154.75, 155. , 155.25, 155.5 ,\n", + " 155.75, 156. , 156.25, 156.5 , 156.75, 157. , 157.25,\n", + " 157.5 , 157.75, 158. , 158.25, 158.5 , 158.75, 159. ,\n", + " 159.25, 159.5 , 159.75, 160. , 160.25, 160.5 , 160.75,\n", + " 161. , 161.25, 161.5 , 161.75, 162. , 162.25, 162.5 ,\n", + " 162.75, 163. , 163.25, 163.5 , 163.75, 164. , 164.25,\n", + " 164.5 , 164.75, 165. , 165.25, 165.5 , 165.75, 166. ,\n", + " 166.25, 166.5 , 166.75, 167. , 167.25, 167.5 , 167.75,\n", + " 168. , 168.25, 168.5 , 168.75, 169. , 169.25, 169.5 ,\n", + " 169.75, 170. , 170.25, 170.5 , 170.75, 171. , 171.25,\n", + " 171.5 , 171.75, 172. , 172.25, 172.5 , 172.75, 173. ,\n", + " 173.25, 173.5 , 173.75, 174. , 174.25, 174.5 , 174.75,\n", + " 175. , 175.25, 175.5 , 175.75, 176. , 176.25, 176.5 ,\n", + " 176.75, 177. , 177.25, 177.5 , 177.75, 178. , 178.25,\n", + " 178.5 , 178.75, 179. , 179.25, 179.5 , 179.75], dtype=float32)), ('voxel_size', {'units': '', 'type': , 'value': 9.7600002})])\n" + ] + }, + { + "ename": "TypeError", + "evalue": "unhashable type", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[0mnum_columns\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 25\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnum_rows\u001b[0m \u001b[1;33m*\u001b[0m \u001b[1;36m10\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mnum_columns\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m*\u001b[0m \u001b[1;36m10\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 26\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m250\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 27\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfile_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 28\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mTypeError\u001b[0m: unhashable type" + ] + } + ], + "source": [ + "#Select how many of the available volumes to load\n", + "num_vols = 1\n", + "sample_data = []\n", + "sample_dict = []\n", + " \n", + "for x in range(num_vols):\n", + " file_name = src_file3D_base + vol_ID_list[x]+src_file_suffix\n", + " file_to_load = path_parentDir + file_name\n", + " \n", + " \n", + " volume, metadata_dict = load_netCDF(file_to_load)\n", + " \n", + " \n", + " sample_data.append(volume)\n", + " sample_dict.append(metadata_dict)\n", + " print \"Successfully loaded: \" + file_name\n", + " print \"Volume max value: \" + str(np.amax(volume))\n", + " print \"Vol Max Check: \" + str(np.amax(sample_data[x]))\n", + " print \"Volume min value: \" + str(np.amin(volume))\n", + " print \"Vol Min Check: \" + str(np.amin(sample_data[x]))\n", + " \n", + " plt.figure(figsize = (5,(5.25*num_vols)))\n", + " num_rows = num_vols\n", + " num_columns = 1\n", + " plt.subplot(((num_rows * 10 + num_columns) * 10 + (x+1)))\n", + " plt.imshow(sample_data[x][:,250,:], cmap=plt.cm.gray)\n", + " plt.title(file_name)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "def auto_plot (num_figs, num_rows, num_cols, src_data_list, title_list=None, indi_figSize = None, display_slc=None):\n", + " if indi_figSize == None:\n", + " figsize = 5\n", + " else:\n", + " figsize = indi_figSize\n", + " \n", + " plt.figure(figsize = ((figsize*num_cols),(figsize*num_rows)))\n", + " for x in range(len(src_data_list)):\n", + " sample_data = src_data_list[x]\n", + " if len(sample_data.shape) == 2:\n", + " slc = sample_data[x][:,:]\n", + " elif len(sample_data.shape) == 3 and display_slc == None:\n", + " slc = sample_data[x][int(sample_data.shape[0]/2),:,:]\n", + " elif len(sample_data.shape) == 3 and display_slc != None:\n", + " slc = sample_data[x][int(display_slc),:,:]\n", + " plt.subplot(((num_rows * 10 + num_columns) * 10 + (x+1)))\n", + " plt.imshow(slc, cmap=plt.cm.gray)\n", + " plt.title(title_list[x])\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 2: Volume transformation to correct alignment" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: transform.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains tools for basic spatial transformation of image volumes" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "The tools currently included in this module are:\n", + " + swap_axes\n", + " + flip_axis\n", + " + crop_volume\n", + " + rotate_volume" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "No module named transform", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mtransform\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mImportError\u001b[0m: No module named transform" + ] + } + ], + "source": [ + "import transform" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "All three of the volumes loaded as part of this demonstration are sequential tiles in a single volume. As the initial cross-sectional images show, the data sets need to be flipped along the z-axis in order to line up sequentially, as would be required in order to merge the data sets into a single volume for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Volume Transformation Operation successful:\n", + "Z-axis flipped successfully.\n" + ] + }, + { + "data": { + "image/png": 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Tnr2lpUUjIyPK5XJqaWlRoVBQNBpVPp/XyMiInHPK5/MqFovK5XLKZrPm7EdG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\n3tnLPPBFfKZWq+ld73qXsb2waLC3sVjMTiPxTCLz91aFYKj2RsKBt/EKhUJ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C7fETQ3XO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gEhJgDFL1lvamqyhCXJxOI8/+joqNrb2zUwMKCpqSl94hOf0JVXXqnR0VFNTdX3fOnv7zdn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\nyCuMLQtLACRovKYLxdGMSjJATSHGH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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "num_cols = 2\n", + "num_rows = 3\n", + "#TODO: Ask tom why this isn't working\n", + "#num_rows = num_vols\n", + "corrected_src_data = []\n", + "for x in range(len(sample_data)):\n", + " xForm_vol = transform.flip_axis(sample_data[x], \"Flip_Z\")\n", + " corrected_src_data.append(xForm_vol)\n", + " \n", + "plt.figure(figsize = ((5*num_cols),(5*num_rows)))\n", + "for x in range(len(corrected_src_data)):\n", + " plt.subplot(((num_rows * 10 + (num_cols)) * 10 + 2*x+1))\n", + " plt.subplot(320+(x*2+1))\n", + " plt.imshow(sample_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Original grayscale data')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + 2*x+2))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 3: Histogram analysis of trial volume" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This module consists of a collection of functions specific to histogram visualization and analysis. A variety of options are included for both displaying and saving histogram data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: histops.py" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import histops" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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bFYJcLBaRTqeFaJVKJWQyGfzXf/0XamtrYbVa4XK5hDh4vV6USiXY7XbYbDaY\nzWaYzWak02kYhoFgMCjty+VyCAQCMJvNiMfjiMfjsFgs8Pv9qK2tRaFQgMPhQEdHhyxQSOwCgQCK\nxaIQ02AwCADw+XxwOBxwuVxCRPlc2TaSPb4HxxxzDHbu3CnEkb/3+XwoFotIJpNIJpNIJBJC5vkM\nM5kMWlpahIwXCgXYbDZEIhEh4Ol0GqVSCdlsFsViUYgl2+Dz+eByuVAqleB0OgEAFRUViEQiSKfT\nZePKYrHIwimdTgOA9A3fPQBob2+XcdjR0YFMJoNsNitkz2q1olgsykLKZrOhU6dOQmg7OjpkXJRK\nJSQSCWkTnwewe7HHvyOVlZVf+O+VhoaGhsaB46ArjVarFffffz8uuugiFItFjB07dr8mmHQ6LURG\nJU0dHR2w2WzIZrOwWq3o6OiQSTeXy8FutwvxojpJ9czlconq5Xa7USwW0dLSAp/PVzZRqypLqVSC\nyWSCx+ORydgwDCEHqjqnKlUkdACEvJF4sv1msxkWiwWZTAZOp1PCZlRseK8OhwPRaBQulwvZbBY2\nmw2nnHIKGhsbsXHjRgQCAbz55ps49dRTRWECIBOx0+kUdchms8nkn8/nRc1LJpNlCqTaT1SLrFYr\nzGYzPB4P4vE4vF4visUiMpmMEA8qpy6XS1Q/h8OBQqEAt9st16UiZrPZkMlkysgS/6NK7HQ6hbDx\nGTkcDmlDS0sLKioq5NlQYSwWi0ilUtLmbDYrxJ7khN9xOBwyvvL5PCwWC0KhEOLxOAqFAgKBACKR\nCGw2m2zTWCgUEI/HRW3t6OiAz+dDoVCAyWQSQkxyWiqVytTNqqoqUTmpnHo8Hni9XlRUVKCtrQ3/\n/Oc/kc/nUVlZKcqkyWRCa2urqINUfkulkix4+Nw6OjqkhmU8HofT6URHR4cQRj4PKvXAnsUX+5xk\nzmw2o62tTb7LtiSTSRSLRXnfuPCiIkzFkO2h6s93i/1EtZWqL9ueTqfhdDqRSCTkXrigoLrq8XhE\naeb1UqmULAoZZdDQ0NDQOHQ4JMW9L774Ynz44Yf4+OOPceutt+73GBJCTioAZKI3m82oqqqSiatU\nKgkZstvt6NWrFxwOh4QPGT5Tw2KFQgGFQgH19fVCcPL5PDwejyiKnJBdLpcoHJWVlTjllFNQVVUl\nkysnayouHR0dqKmpQSKRgMViEQWI547H46KE8FrZbFYmaLaDkzEJNJUrnu9HP/oRKioq4HA40Nra\ning8joodyDN3AAAgAElEQVSKCthsNpxwwgmieObzeSE4VJxIGPx+P4rFIgqFgoRQSRgrKipQLBZR\nUVGBQqEg5Johv0wmg1QqJbvNcAJn4W+LxYKKigoJyXI/Z5PJhFNOOQXZbBbpdBo1NTWoqKiQtAAS\n31wuJ2qr0+mU50eCYbFYsHXrViEJTqcTXbt2Re/evSUkzzAnSTrJIQkOx5rNZpMUBIfDgd69e6NQ\nKMDr9YoC6PP5hMCSbJtMJiE6hUIB4XAYkUhExis/41hmWzne1JAux2Rrayuam5uxdetWnHrqqTjv\nvPNwyy23oFu3bkJinU4nrFYrAoGALGaoqPI8TqcTFRUVQuRIXJmeQVJutVpFFWS4vKqqCi6XCxUV\nFfJsqMRzoZPL5WTcejweuVZHRwdOPvlkSY0gYbPb7XC73TKOnE4nPB6PKNpsSz6fRzQaFaLvdDqR\nTqfl/TCbzejo6JAFAO+bIXSmObhcLknhsNvtun6hhoaGxiHGISnu/bkXNZnQpUsXCROSWJF0cPKj\nogJAFCOz2YzBgwejurpayCBDkCQM+XwedrtdJiiqYFRGeE1+l+ohJzcAZXmInDh5jNlsluOoYjFk\nxxxBm80mSiKPI6GgcqVO8NlsVnLkqEo5nU6sWrUKCxcuRCaTwQknnICRI0cikUjIMYlEAnV1dUgk\nEkI82Qc2m62sfwBIiNHlckkOGcOD7HPmQvKZRKNRyd3k87Db7YhEIqisrJTcTz5Pkq1YLAan0ynh\ndKpVJCZUONkvLpdL1FK2ad26dZg7d67053XXXSc5kclkUs7FfqNq2N7eLsTJarWKCkjFjSkEHo8H\n4XAYTqdTiFoikRBymcvlZFzxWQIoG0ck/bx/p9OJ9vZ2+Hw+uR5JMsO4VKHVPM98Po9nnnlGQvO8\nz0gkgvPPPx9nn322bEfIPmNfp1IpuVcuorgA4Djg/uBU2fkO8Jkzj5jKMBVB9XdMHeG7xXuiysg8\nZL4nHPsc41x08b65iOG5+J1CoYAnnngCiUQCuVwOoVBI2kX1lsq9qqZ+/PHHX2vyqIt7a2hoHAoc\ntuLeBwqGmTgBkURQ2SNhYYiVEyRVDeaOAZCwMcNszJ/L5/MAditN6uQNQCZOXoeEg+Sjo6MDiURC\nciGdTid27dolZIHfUUNyJJ38bqFQkFBtR0eHqCXpdFrOTYJJEpBOp5HL5eRnKoperxebN28WJQrY\nTaS9Xi+SyaTkfqn9RTWXih9DwVRDSWA8Hg8sFosokA6HA8lkUvJFvV4v3G63XIOkmd8H9pgeqOZF\nIhFRuPjsAoGAEBWqkyRkJLrM6WNb161bh3w+j0wmg969e6OqqkrUO44FjgOqn4VCAZWVlbDZbEJE\nmb7gcDgkH5Gklf2fzWaxbds22O12BAIBaZ/NZpPwqMVikfxIjhUqdA6HA16vV8LDAMRkEwgERBEj\nieUY4Hvg9XrRq1cvbN++XZQ7nqupqQmrV6/G6tWrhTRRkaNpxWKxoKOjA06nUwg19yPnszSZTLJw\nUI0/JPR8/0j0uKBTlWC+ay6XS+7F4XDA7/dLG0j8qbay77gYYC4qFzS8JxLD1tZWtLa2wu/3S9qG\nuqAjiQ+FQmXvuIaGhobGocNhI43MX2OiPwkelQZOTAxJ00VMFSWfz4tSRzJJ9YY5VGazWRQzgtch\niaMix3AcJ1S73Y7Kykph3oVCAcFgUMKe/I/ndDgcZS5cKk8kYiRFVHDcbreoMsxdU89LR3EwGMTF\nF18s7ti5c+eK4kMCAkB+T8U1GAyWnYvkslgsiqrI/MFUKoV0Oi1qKcOCnIhJylViyXsEUJbLGY/H\nRQnj86VjOJlMCtlSQ6F0TfO5MeyfSqWwdetW+Hw+WCwWnHfeeWhrayvL8SPBpjoN7DbTUM2KxWKo\nqKgQMkUjCcOiNP2kUilEo1FxL5PM8R6o5FJ5ZI4liTSJF3Ndqc6lUink83m0t7cLyWZKQF1dneTD\nsu19+vTBgAEDxCBCY1gqlUKPHj3EQERVT3VKkzSRrLW2tspCQiW7dMFTYaeiyUUXcxkBSHiYrnGe\ni4STeYnMl1TbwJB8RUWFvNs05KjOfb4/jCwwb5T/cSHGlAn2eS6XQ1tbmyyidKkdDQ0NjUOLw0oa\n1RCY2WyWyYUTJcNqJBpUSnK5nJTuoJpFBS2VSonyR4WKKiZDvgwzUilJpVIwmUxiUFBz0ujytNls\ncDqdyOVyoroxpMn2My+S5gwSCYZBOYmSlKrto9pKMsXJeevWrTj55JPRqVMn+Hw+rF+/HslkUsgh\nDREkhVRx2Idut1vUOYfDIaTZ5XLJv9le5mUahiG5dAzpq+FqhtjVMi0kQqpSarfb4ff74Xa7Jf/M\nZrOVhXxJOtgXpVIJHo8HVqsVGzZsQC6XQyQSwXnnnQe/3y8qFsktFTSOKeaAckyoxhtVIQQgfUiV\nkM/e7/cLwaEyzHMBEJc5zU1UUKlc0oyy97ggWSXJpKrK50fSzrJNDNdaLBa0tbWhra0NvXv3ln5o\na2uDw+Eoex5U9UjCg8GgjEOPxyNjgaWVuHDis6cpi0YU3kc4HBYllQu6VCol6iMXLzQjcVxxMaeW\nzzIMQ6oS7E02M5kMEokEli1bVlaeiqYtqrIknFRvmZOqoaGhoXHocNhII+v3cQJjaJbuU042DNMa\nhiGkLhaLSTkUlfhRZXQ6nfB6vQD2TOBUtRiCppLDiYeTNokiCS2JAid55oVls1mpYUdDCbBbmWHN\nQNW1nc1mEY/HRYEisVJNQFSpqOKxXE4+n0fv3r1FGZo9e7bkCra3t0ufkuhSzSqVSojH44hGo0Km\nSahUwkfSxpIlFosFsVhMiCuVYFXNSyQS8n01l5RmIPYXaxjyfg3DgMvlkj7kGFBz4oDdxGLFihWi\nIh9//PHIZrMIhUJIp9OifpHk8nnEYjEJfdK9S9OEGv63Wq1C0lR1mYSUYXeLxSJjQyW9at1Q5jRy\nfORyOVGlaSBR63pyTHB8061eUVGBfD6P6upqVFdXS/4nieO//vUvWbxUVFRISR7WNqSbmO+O2WwW\nRzjV4nQ6jUwmI8+CarmaquH1euFyueD3+wHsCfuT1HNx5/V65T1SjSu8PhXLcDgsuYgMc7N/qUhy\nIchFWiQSESWY7yFzItW8R5Z/onKqoaGhoXHocNhIozq5qLlUnKg4sXFCJylLpVLo3LmzJNuTIDG3\nS3VO04nJ0jGc2FQTAydymkOoUDJ8xpysVColYVcAMpEzT45hc6osgUBAiisD2MfgwUma95fP5+F2\nuyXsp5aHiUQiOOOMM4QEtba2YuHChQgGg3C73fB4PNIeuoxJCHg/NDjwulRKWeaFz2DXrl3yfKgO\nejweUduY5+d2uyV0yNBoe3s7zGYzQqGQqLkM4fJ4khSWWAEgSquaw/rRRx8hEomgUCigtrYWxxxz\njIRPAUi4mfUGKysrUVVVJSFo1oSkAYrmHpI4fo+hcRa9Zr5jIBCQ56YaZNi/zPNj/iqPSyaT0v+h\nUEic1TS7OBwOIbo0kVCF5sLopJNOwplnninpDKwi8MEHH5SRQ+Y9sl4j75VjmzUnuUhiygT7jaSU\n+ZdqSSW6n5keQpWeuZ9UnqnKq8eTSDLFgcosXeCqgqoaY/x+P+x2O7Zu3SoqJscEj2eerrqwUhVl\nDQ0NDY1Dh8NGGpkbyImHqkQsFhOTAwkKzQgMTdFkwp9peFDNGip5opOTE5vq6qT7lQYTklkqnADK\n3NecyNX8uWg0KgRUrWFHEwYnRxJGs9kMv98v56VJg6oJiR5Do4FAAE6nE/X19cjlcvD7/Vi8eDE2\nbNggOXNUalSVj8SCbfN6vaLYsPi43++Xe0mn0/D5fHJtNc+TznHW2jOZTJJ7yDBrMBhEqVTCzp07\nxe1MVY6ElSacfD6PUCgkYVCSAj77V155BdlsFrFYDI2NjYjH4xLKJVnI5/Pw+XzybxJUp9OJyspK\nUbSo6FHJZB4rxyHb73a75Rkyp5G5pVSeqSQSJEwkpeyDXC4n+ZLsdzXcqu5QpBZRZ81BADImmG+a\nz+exevVqOJ1OxGIxWViQDKvPh+OWOaY08nCMsA1qAX2Sa/7Msas6sxli5vPlu0AVl/fH8cQFBb/L\nRSL7kOWCuGCzWCxYuXIlAJSV2eE1uJjkGGf/c8GloaGhoXHocNhIIyc4TgyclLmzi7prBEkGFQpO\nPlRL1AmE/+Y2cGrYU3VrktiRVLF+HfMfOQmpZJSGFRaW9vl88Hg88Pl8qKysRCAQkG3T4vE4PB6P\nOG8tlt07fDAEya39qP64XC4hrFRYKioq0NDQIGHm3r17Czlxu93405/+JKSThJakhiomw/c0gzDE\nyzInhmEgGo0CgOSdkVB4PB5kMhkEg0EpKxQMBoVU0Wzj8XiE7LH2IcP2NNPQ8MMcQCpmNDGQNFVX\nV+Ptt98WsmO1WnHyySfLuFC37mOoPZVKSciZahnPyf6MRqMSWgYgChqVUiqL3FWIxIvPnjUN1f5T\nx5vf75f7i8fjokAzD1btA6rbXJxQheZCJZfLobq6GvX19QAgY8fj8WD16tVCLKmAx2IxScHg+OCz\nNZlMop6quYA0JXH7Rob4+R6ohh6mOvB7bCuAslJC7E+2g+82nxdJH/ueRqFIJCJpCtu2bUNzc7Nc\nUy2pxDA/Q/ZcyHFRohbc19DQ0NA4+DhspBGAlANRXcYsp8NJh5O+muO4fv16IVUkfZwAmTDPECDD\nX9zVhJMQC3unUikJWTOvkBOoSi5JOgGIYkTlJp1OIxqNiqGBxJRqkGoMASB5e3SjkhABkP6g6kmD\nhdlsRl1dnZAemhzuv/9+6U/VtMHwJEkzS+uooUJO8qr6CqDsuswvIwknoeL90dVKAqUSCpJ/novP\nsb29Xe6bxJLhxc2bN2PevHnyTP1+v7hpmcfJ65DIU21magAXFcy1o2KtbnVH4sswM/uEbWfYFSh3\n/fJZkagwlM18O9WoodYWpbrGkDCJLXMbAUgJJiqeJMM+n0/OHw6HsXLlSvkeif7eiygA8myp3nO8\nAijbaYbkzmq1yrFq+SWqwAzl01jDRR2vz0UDw9vsc7qtaThiX6r5lMxDff/99+UeaNBi3zDCoBJa\nKvdWq1XvCKOhoaFxiHHYSCOJmFo2hmRJTaxnHiGVJJIOHstdUDixqyFrgsTT5XJJORaen+omJzqW\nIGHYSzUiABAFlJM1Q4lsZyaTEVLAUi2qWYYToclkklIyJGLc/5jnLRQKaG9vF4VMVTl5zXw+j2ef\nfRZ+v7+skLiqPAIQ1ZDlWFhXkbl8DN+yfWxDRUUFgsGgmEAYvqQ66vV6hSTF4/EylzrTAkwmEyor\nKyXMSqd6NpvFrl27hOiWSiXMmjVLVDrDMNDQ0FB2XZowGCK3Wq3w+XxiYmHo0ul0yjNi36XTaVRX\nV4siSKLqdDoRjUZFVaM5heSF5IljgmoZ+4VOYo5BqpPMY1RzZ1mjk+YPKnAAJIUhkUjA7/fje9/7\nHtxutyxkSBTffvtt2eGFY5lFsnk9mmPotFdVdaqdbCtNQhzjVAH5XlAtZ38HAgEhwAxRA5BcXJXo\nsQ1qCH9vRzWvs2nTJmzYsEHc3FxAkcyzD9S0Fm6HyHGuoaGhoXHocNhIo+reVHOpSFg4oTNkR5LD\nSYITJBUnt9tdRraYL8aJn+FGhrcY/lLVSpIaqnx0mwIQwsW8w3Q6LWE1m80mKhxJBIkwk/tJ9Gh4\n2JuEMs8xEAjIpM37ZX6mzWZD165dRXWie3X9+vX485//LKFbkhgSHHVXFt4XSRbL8pCQsD0k19Fo\nVBzJJGpUjJxOp4SM6RRWVTQSGobreX2GJdXr5fN5/OlPfypTw2w2G2pra6UGJOsZ8vcsDUOCTuXM\nbDajtbW1bPceVakMBAKi/lE1I4FnLq1aQofkiISF6pbqCmYpGjUflO55Oq8ZulVd51SB2U9+vx+J\nRAI1NTXyDpDMcmvDlpYWLFmyRIpqOxyOMoc6VXB1IUVCRyV871xMLpBUFzhVVzXfMplMIhaLleUZ\ncgFGdVet08k2qrUz+X6pOZ2JRAJ//etfZa9vLhQACIFUFXHmgfJvBQCtNGpoaGgcYhxW97Sq0HCS\nUdUdteYbAFEbWSiaoUaqMQDENWs2m0XNAVBWboefUYUiaSN55CTLkJkarmb+Gyd9Jvur5yY5IIEi\nKWDIkY5QOr45Iaq7rDDHKxQKSVi5vb1d8jRjsZgorC6XC1u2bMFDDz2EUCgk6hFzy1iiiJM21UoS\nMQBCntQdQVjyhwoZlV8qVVTKWO6GqhCVI4/HI/UCqSwDkPxAEh6v14sZM2YgEolIO2jCqaurEyLC\nvDWmMFDxZb/SxAJA8t+oSvHZ0MDB9AfWKmTbqdDS6U1zjsWye49x9gvbQPczn6PP55PzcdHB/blJ\nmDn2qbLzWTEUXFVVJfmFzGvkmKbZ5x//+IeU6WGf8hyqqsgC9aFQqEx1ZZ1O9jdzYEnkrFarGHk4\nhpmTqBJ4mlhYo5Njnu+D+szpfOf7x3fF5/Nh2bJlUqBerYcJQBZiaqoIyTrfX76DGhoaGhqHDoeN\nNJKo7U1aOGFz+z6G1orFImpqamAYBiKRCMLhsORlcSJj+RC6dknQaPqgYsQQKQA5FoDkWdEEo279\nR1WMW5rt7aRWQ4zc15gGHNWx6/f7xVlNskgyQzVVLUei9ofZbEZ1dbWoN3RCV1RUIBAIoLW1FXfc\ncQcACPlUQ+NUh2geYPtV9yx3CyHJpgpM4sXyL1SoSNL2zrGj65oqo7prSCqVQktLi5Cr++67D7FY\nTPqYZWm8Xi8aGhrKzDRsfzKZFJJFQsLQtLoAYD/TrMPv8HyqW55tJ9lWTSV8llS9mLPIMUujkbpj\niVpHkmkMzPFTC3xToTOZTEgmk/vUQqTaTaWWivqMGTOwfft2MTvl83lZTNG0RZJIBzhzP1XlVB3L\n/E5Hx+79udlnfL6sqbp36SrmyJL0kSDzXVfLLvG947vW1NSElStXyqJF3QWGeblcVHGxwtxl9Vnp\nHWE0NDQ0Di0OG2kk8SJ5U6HuJ6xOwIlEQhSa1atXl7k61VCW6rgk8SGhAFA2mXKSo7rCOnBq6E0N\nJ9N8AUByJ/fec5eKGRVLkle11AqJILAnjMvwGwkk60uSXABAZWWlhOvVItMqyZ46dSrC4bAQGZJA\nhhhJRNlGhj5JWkkiAIjKRsLAHE+SIT4/Os3ZX1S+SFa5/zUXATU1NUilUvjNb34jbWI+qWrEsFqt\noh4zNKyqllS1/H6/3A/Va+57Dewmqmw/xxPPr/aDui0hnznNHyT0KmFk/iSLgJOMk3TTDc3xweur\n40lV/riYonLOIuHsE4aZaQh59dVXUSzu2YqTfc/rUo1LJBKiEJOM8b1h6gK3O2T5Hva5StZJPovF\novQDSx7xnmkQ4n9Uoll+h8+Y6u2cOXNE9eQ4JcFlTUres5qHynHM8ceC/hoaGhoahwaHjTQyR49/\n+FU1Q1V5OAmzpA6wm6ytX79eJnk1tErSp074JAbAnl0s1MnbYrHIPrrM76MCRPWE+WdUJTn50VFt\ns9kQDAblcxbMVkv58DgqfiR+JItU/Rgi5GRutVqlj5jDSQJGFTUajQrZtdvtuPvuu7FgwQLZNo7E\nUg0Vq/XyeK/MGWMpH9ZuVMPODGWSoPH7LJMDQNRTKkMul0t2MKmpqcEbb7yBe++9VwgyFUu2kWFo\nLgJUUkHCoDrPGQ4vlUpyHdY4JClk6SJ1AUHSo44XYM8e5QDEFMJagiRwqkNbzSfkGCNhZ45jRUWF\nLCDU3D46t3lPqjuZ90gjk7prjcvlwpo1a/D666/D6/VKvi5JqlqzkSkOVOPo1ifp5XNW900n8VT3\ntfZ4PAD2FGTnc1PrNnLxQKVcrY5AEst+ffrpp0XpptmG76SaVkASyc/VXZ64sOQiTENDQ0Pj0OCw\nuqfV2nSqi5QKEENgzJ9SQ5GJRAJbt26VYxk65f9J+tRJmIoMw60kZ9xNgzUUAZQ5duleZsiY11FL\n2sRiMQkNcmIslUpSuNrhcJSpjFRCqQqRHDDcBuzOy2NtQJI8GjaooNrt9jIFEIAUt37nnXcwfvx4\nbNu2DX6/X4i6GhqlukqFCNhTYoY5eiqp4b1R/fJ6vULWqFwxL5TFv+kqdzqdaG5uxm233Ya33npL\nyAkJnEpoaAziQoF5dFxcUIVliLNU2rMXOR3iqrEFgKieJNDqAoXu7Ww2KyokxynDqyR6au1GKmPM\nNeW+zLwGxwwXP8yDJflTdzxie1jgPR6Po76+XnI5qXjS1EMH/rJly7BixQr4fD4pc8Rrk2BzbJBo\nqQuRjo4O2WvcbrdL2R2+f2qeJxVq9i/VcyqQXAAxDYT9x4UBr20YBmbNmoW2tray3YU4dtQFHcsy\ncfFHkqiG2fl+a2hoaGgcOhzWOo1UoIA9yg4nGBIHGiaYhK+aZt566y2ZeBnSIklUJyrDMMQ4QQLD\nUCOdxDwHJyoSAW4VB+wx75B8UYEhgQAgZErN5+KkyvwwTpBsD0kI96ZmuZhkMimJ/mqomaYLmoXo\nqmVdv2QyKZNvIBDAM888g8mTJyMcDgtZYV8xxMicMV6P/UAlUa2HyUmbJILhR/YDTSZ0VdfV1SGf\nz+P222/HzJkzhfj4fL59ag06nU74/X4J11KJVA0ryWRSCK8aLqcKpSpXHGfqcyWR4+fM+SRRZA6h\nWksRQFn5nHQ6jba2NiFNJFgMybOuJ5VW5tzyWQGQMch7ZL/RVBKPx1FdXV22KFLza3mfFosF8+bN\nw2uvvYbKysqyHNm9Fwe8d5JaLj5UowlJOcP+THug4xrY415WqxuwjVTIScw5Tmguy+VymDVrFlpa\nWsryOfkOcqHGtnGs8d7Z17xH1SmuoaGhoXHoYD1cF+YkoCp7qlJAsscJgySJu3zk83ls2bJFlCFO\n8FQNOXGTDKg18TghqirV3sSBipSaX5VMJuHxeMRIo6pRJFKcWHkuTtacbEmuOHHz+5wE1bAmiZSq\nPqXTaQlF0j1OFYyGCOb08XdUkP7whz8gnU6jb9++GD58OEKhkKiBbC8nX6qdXq9XQt7MLQT27G3M\nZxMIBETho4nFMAy88cYbeO211+T+VPWU5gs155O78TAlgLlw/D7VVSpziURCVD6SCtVUpBaQJ6mh\n6kZDCceQuvc3iQjLJ5G4qW5gdRGQTqcRDAYRiUTg9XrL8mKZChGNRmG325FMJgFAxgBzIkm0aew6\n9thjsW3bNnkmvH/1vAwvl0olvPbaa8jlcjjvvPPK8hZ5To5rjkuaugh1DNKkxtxJlbRyS0KOX6rC\n6uJBDeFThfT7/fjkk08we/ZsAHsqGhQKBTFg8RpqHi//HjBHlPer5jOqkQoNDQ0NjUODw0Ya1Xwt\nTkg0lnDCUfMUAZSRAmL58uUYNGhQWRkdAELuqMrQpEJiwn+TUFHVymaz8Hq9SCaTokLRUEG3MhVM\nKo8Wi0XICbfaYy1J1QHNOoF+v1/UQKpdNGowrE01ir9nSFktzE3SoKpdbrcbfr9ftqYjiSMRcDqd\nePvtt/HPf/4TDocDF1xwAfr3749gMCjkgsoUSx6RgFZUVJTle7rdbin7wlCl1+vFO++8gwULFiAW\ni8nWiQwfkmywv9k+Tvo8D8cHSSLNGewzunjT6bTkV9LgRILIMcRwKGt4UuGm8YM1Fvl7qqAcl1TM\nGBLlGFQVTK/XK/t7s/QP0xd4DxyDLNFDYk6SyMWG1+vFunXr8O677+KMM84AANkbne1g/5HkUhVf\nuHAhdu7cicsuuwwVFRWIxWKiOJN8k6RxjDNFgO+OqvrxXkhUM5kMotGojCWOy2g0WqaI83i1DNLb\nb7+NuXPnSgoD70V1qFOtzefzUrCc6j5VSfY532P+bWB/amhoaGgcGhw20ghAFAmSL07YKjlh+IuJ\n7pxgSGQWLVqEvn37iorFCUt1HavhL6pJ3FZPVRNpYuGOHcyBZHiSZIbGBpoG1Gtw2zbmbqm7W9Ah\nrKoxfr9fwq6cAFXXKQkHiWw4HJat5bgPMEkj25lIJMpCyQCEVHHvZ4b8ly9fjldffVVIbXV1NXr2\n7Inu3bujqqpKrq2ajEgmI5EIWltb8fHHH2PHjh1CBtX9tLmjDUPMnPhJGBhiZ4iZoUe2h6VquGtM\nOp0WhY41JFVHOMksSRDD/CQUfEZMLaBKTaJCBY9hZXXfcRJBhmJpFKHSSSJJxdxkMsnzVusyqm5q\nNXzLsZXL5dCtWzdEo1HZclHN2VV/5qKHZLmqqgrr16/HvffeiyuuuAKnnnoqkslkmfrMQvRU7VSF\nkffJdpIYcuHCBQhJmmroISGnOquWu3r66aexceNGGavAnjqMXHjx/eL52L8k0xwvDIczrUENq2to\naGhoHDoc1vA0JycqNCwRQkMDJ0OqMAxl8rsM0b777rs499xzZeIFIJMoJzdOYDyGSlNFRQUSiYQY\nC6h8MvyqlgRiuBuAKJBq/h/JDo0AAMRNSuWE5IuhTe4/TeWMhhQ6s1l7r1DYvevIpk2bYLFYZHs4\nkmROmCTMAMryF0lmOOmaTCbU1tYKwWK5Eqqo69evl9zKqqoq+Hw+hEIh+b7dbkevXr1QKpVw5pln\nimJULBYl/MwwsMvlwoYNGzB37lxs27YNu3btkjA11VU1z457j7PWpkooAQjhamlpEWMMQ/MMe1Oh\nYn9wP2eqwXwudDXH43FRs7iIofGG2y1yTNDZXVlZiUwmg3g8Lgoj+0ElUewHEig1BYHpEdlsVvIy\ns9ksYrEYXC4XduzYIW0BIAsMkjiOWfYbjTpmsxmzZ89GQ0MDRo8eDa/Xi0gkImFgvneq4kslnyqj\n2jY1vE/SxoUR0yb4e7X26Pvvv4/nn39+n4UXSaCqBNMsxWvQ5JVIJKS9HMuMSDAkzTGkoaGhoXHo\ncFjD0ww1AhDnKdVCYE/+FQCZpDwej5RNoVKydOlSnH322WUhLzXnkGYWqhiq6kVVRA09MrmeKp46\nQQrI0QQAACAASURBVPI7zCdU3dqqIkMCw9AcS6vwc+bSMfSqEj3m8gF7SvuQzGzZskVMKdyaj2oc\n28OcTwDYsWMHunTpgksvvRSNjY1CLACUlTvi5MtwOk1IzP1kf5hMJiEeNPeQtPCZkIBwlxb2/fDh\nw8Wdu3jxYixZsgSVlZVSf5CkLZ1OS94cFShVfSJpUQk7yTZJlFqWhWYn3jPL1/A5MDWAJITpCDSI\nkFipuamquqduzce6ghyDzFlUw+/xeFwIIvMGSTKZ73riiSdix44dQpj4H8eWql5bLJYykkpF1OVy\nYfv27bjzzjvRp08fXHDBBdI3vCbJOpVFKtZ8pgzl87nyXWBfUeFTneAWiwVr167FwoULZU9vjlmq\ntAyJk8yzhJCqoNJAxr5TUyxIwPm3gcaZA8HWrVsxevRotLS0wGQy4eqrr8b111+PcDiM4cOHY/Pm\nzWhsbMTTTz+NQCAAAJg6dSoeffRRWCwWTJ8+HQMHDgQAvPPOOxgzZgyy2SwuueQS3HffffL3bPTo\n0Vi5ciVCoRCeeuopdO3aFQAwa9Ys3HXXXQCACRMmYPTo0QCAjRs3YsSIEQiHw+jTpw8ef/zxslQc\nja8GkyZNwqRJkw53MzQ0jkgcNvd0Pp9HPB6XGoNUItTtwFRTBieT1tZWUddUcvfMM88I+eLkSYLA\niVUNIVLV5CTGSZkTPMPTnCB5Pm59SILEnEK13AzbRQWFaiJJLidM5sIxN5F5b3RHx2IxeL1e2Gw2\n+Hw+pNPpsiLKak4jsIc0WiwWRCIRnHDCCZg2bRpGjBiB7t27I5fLIRKJIJlMinrJyZbqK3PtzGYz\n2tvbhWAwTMmQJUPUaria5qVoNApgT21A7lVcKBTkWV944YW4//770a9fvzJ10OVyIRgMIhwOo6Oj\nA1u2bCkrFE61kc+Ju7BQzWN/sj2sP8hcUQBobW2V0DWfE9ugpgSQyDMUSsOL6uYlEeSYo2ObDmI1\nPM2akgyZ07TE67J/Odb57OlCZ51DmlxoCuPzoSLIccBn5fF48MEHH+Cee+7BQw89hI8//hgVFRWy\nvzWNR+p7xXxGk8kkTm72B3MjmU9KBdvtduOtt97CxIkTMXfuXCSTSak0oC62OGZ5/2oNUiqIDG+r\n4XEahvjuchGjlk06ENhsNtx777344IMPsGzZMjzwwANYt24dpk2bhgsvvBAfffQRvv3tb2PatGkA\ngLVr1+Kpp57C2rVrMX/+fFx77bXyzl1zzTWYMWMGmpqa0NTUhPnz5wMAZsyYgVAohKamJtx0000Y\nP348ACAcDmPKlClYsWIFVqxYgcmTJyMWiwEAxo8fj1tuuQVNTU0IBoOYMWPGF//DqvFvYdKkSZg8\nefLhboaGxhELk3EYssdNJhNOOOEEMbxQjeGESVMJlSYAEkLz+XzYsWOHKIUMVebzefzsZz9DQ0OD\nECq32y0kgI5pTr4A5Gc6X5mfRYe1Oomq5U4Y1jSZTFKuhwqUmhNH0khXrBpaZCiOfcB8MlXVodLF\nib2pqQkzZ85EVVWVqG8AysLUsVgMdXV1+NnPfibXASChdt6LakSiyYWEVCXDqopDBy/VLgDSTlVF\noglHVXBJ/nkMyRpV4NmzZ2Pjxo2orq4WApFOp3H88cdj0KBBcr9MEVDNMAw1s/4hcz5J3NRwJ8kF\n+4vPh/l6zLlLp9Pw+/2iYNJkw2cGQPqO/cH7owrIcUhCpj5//pt1P9UxxLFVKpUwd+5cbN26VYiU\nGt7mgobPhMRWNYWodUap7tOtXltbixNPPBGnnHIKampqpD/UnYbYVraNhJIK5aZNm7Bu3TqsW7cO\nW7ZsgdfrLVOuWSGBC0D2FZVDAGVtUx3XLJivbnmo9q1a1omLiaampi9siBk8eDCuu+46XHfddVi8\neDE6deqEnTt3YsCAAVi/fj2mTp0Ks9ksxG/QoEGYNGkSunbtigsuuADr1q0DAMyZMweLFi3CH/7w\nBwwaNAiTJ0/GWWedhUKhgLq6OrS2tuLJJ5/EkiVL8NBDDwEAxo0bhwEDBmD48OGoqanBrl27YDab\nsWzZMkyaNElIqPq3Uxt+Dh3UihgaGkcTDvRvy2ELT7NGHMN0JCqcdDlRq2VdODFSFWS+GJWiF198\nEddff70cz20HA4FAWe4TVUQqGGpInBMeFUuqKOouHCSiLPnCfDs1z4okLZfLycSnJvGTePL+1MLT\nKtEkgbHZbNi8eXNZjUVgT0kci8WC5uZmnHfeebjkkksQDoeFfDE0S2WHYUASLxZzZlmhQCBQVkKI\n+yGT2BrG7rqXiURCjBUAhBTw51QqJUqT1+tFIpEQhzqVJBKCq6++Gps2bcIDDzyAuro6JBIJMXV8\n97vfFQMMCQgNRFQBORZU5zd3SOF3Sfb4TNXcOwCSr8hcQxIX/o4hbF6TJJUmLZJA5tdxX3C32432\n9vayWp48byaTkXI1zJVk++nC572w3WpInuocQ8uq+snx7na7JXdVJce5XA5vvfUWFi1aJAs0t9uN\nmpoadO7cWc5LlZttbGpqQltbm6h/bB8XXiq5ZmH6ZDIpYXOHwyEh+lgsVrY7ExVihtxVUk41Wa2b\nyntSi+J/EWzatAmrVq3CWWedhV27dqFTp04AgE6dOmHXrl0AgO3bt+Pss8+W7zQ0NKC5uRk2mw0N\nDQ3yeX19PZqbmwEAzc3NOOaYY+S98/v9aG9vx/bt28u+w3OFw2EEAgG5R/VcGhoaGkcKDhtppJFF\nVbSoHNGBS9WBRI5KCsODDF1ZrVYEAgG0tbVh8eLFOPfcc2US5M4hLEJtsVjEwELVjaFh1WBAdU1t\nIwBJ+CeZo7mF5+IESLWHChiAMpLLiY6hbObZcZIsFouiOFFlfe+99yTUqiqW+XwesVgMw4YNQ58+\nfaQOIK/D8C0Jc1tbGzwej+Q+8vwOh0MIJkOxJAVer1dMKSR7fDZ7GxhINNU8vHg8Lk5lhhnV8Hgq\nlUJdXR1+9atf4fHHH0dLS4t8t729HdXV1WVFzakSMxRN0k4wJ49mD44fknIWgVfvl21Xy7ioDmPV\nqcuanVQp2SZ1L2Y+e5YxUlMZ2G+FQgFtbW0SVt+1axd8Ph/sdjuamppkUcJcSCp9JBd8l9TyTXzW\nzHNsa2uTd4mKHQA5L7Bn8WEymRCNRhGNRsXJTpWc2xgCQHV1tSjc6s5ObJtaAovmHPaLurUiySzb\noRaRV0tvUQHi9Timqbbyvf0iSCaTGDJkCO6777599q1Wc6IPNb6q62hoaGj8uzhspJHJ9larVZyi\nap4ZsGfXCZoiAEieEwsGc8IiaZg3bx569uwp4TYWw1ZVPbXcCbCntiPJJCdPupsZulVDtWwHyQvV\nUTq61b2CeW6fzyf5flSy7Ha7kAtemxMhsGff4w8//BDZbBZ+v1/IDFXPQqGAkSNH4thjj0U0Gi0r\n2sxQtBqq5h7DVD1ZviaVSqG2tlYIG/tJdRNTZc3n88hkMpJ3p7aXJgyG+xmSJmGnChwIBJBKpZBO\npxEKhURBuuGGGzBnzhy89957cDqdeOedd3DhhRdKygHVQBIVqp0Wi0XqLrJ0jOqIJylXcxlJ9hOJ\nBILBoPRrS0sL/H5/GRlRC1ZTtVW3KXQ4HIjFYqioqJCxwe9QOQMgRN9qtcoihO2srq4Wcs/ySsVi\nER6PR1zHPJZEKxwOS6kqbltJElpTU1O2KOKuQ1xoBINBRKNRIXYktg6HQ5TdRCIhfc/wfjweF0V1\n7/HG9nFxF4vFZKtJjhUu5Eh2SUw51hgeV8m2uoMN30W16Dufw4Ggo6MDQ4YMwahRozB48GAAkLB0\nbW0tduzYgZqaGgC7Vb+tW7fKd7dt24aGhgbU19dj27Zt+3zO72zZsgWdO3eWPgiFQqivr8eiRYvk\nO1u3bsUFF1yAyspKRKNReSe3bduG+vr6/bZdNWkMGDAAAwYMOOD71jgwaDOMxtcdixYtKvtbdKA4\n7DmNVEaoKKhKCLAnt8ThcMj+u3Rk8nc8BwApMHzDDTfIJMRjSVSB3coSw7ScmHg95sOxnIvq4iUB\nsdlsiMfjZUWZOZmp5gtuC6c6wlUDA8OzNEhQRWEYlwRl1qxZQkoTiQSA3RNfKpXCd77zHfTp00cm\nYdUcwIkegKhW3JWESi1JOMkNc/HYZyTaDOeyv/Y2k3BCZ1/yHlUSrKqnzE1kjhzJBrBb+Vq6dCle\ne+01eL1eXHPNNUJ2SEjppKXbmk5j3hPVXC4wmIOqqsuqgsjnE41GxWWupiAwdy4QCAgB53e4OKFR\nhgodd6xh6J7jjgRILWPDsWyxWBAOh/HSSy8hHA7Le8GFiZrny7HDcdbQ0IDGxkYEAgFUVlaKu5vP\noLW1tcy0FYvFEA6HEY/HsXnzZkQiEbkfkmYax9hWhvFJ1phrygWB6nTn+Ob3+Y6RQBIkw/yP6Sks\nhM8yThwj/DefKxdX69at+9wwtWEYuPLKKxEKhXDvvffK5z//+c8RCoUwfvx4TJs2DdFoFNOmTcPa\ntWtxxRVXYMWKFWhubsZ3vvMdfPzxxzCZTDjrrLMwffp09OvXD9/97ndx/fXXY9CgQXjwwQfx/vvv\n46GHHsKcOXPw/PPPY86cOQiHw+jbty9WrlwJwzDQp08frFy5EoFAAMOGDcOQIUMwfPhwjBs3Dqef\nfjrGjRu3z99OnW936KCqvrqfNY4mHPE5jQzVMtTJ8KZa3oQlP5gg73A4hAwwNMyQNvOqWLT473//\nO37wgx+gUCgISVNz6ViQmVvIqQWHSc7UMDAnMxICEhKGkakiMYeR6inJIs/Ngt50YDM07Xa7YbVa\nEYlERDFyu91IJpOIxWJoaWlBZWWl5NExxNetWzf07du3LCQOQMLyVNGoxJEgsS6mak5hCRY6l2tr\na+V66t7KzJOk2qcaNEiq+UzpuiXBAfbs6UzjDcPGXDiw1Mq5554LwzAwb948LF26FP3790exWJTF\ngJpyQAJJQqvWDWQOKUsM5XI52UIxGAyipaVFnPccZ6pyyvxJtZQSCT+LyqfTaaTTaSkFo+bN8pmo\n+bFqVQAuXNQQczgcRktLS9kz5HhjziWv161bN7jdbpxwwgno3LmzhFpZt5CheBbNV0tQNTY2CqlO\npVJIJBJYvnw5Nm/ejGg0KuSXBI/hZSq0qlrN0jtUKLkg4KKQ98qtK1ktQDXBkDzzvPwbwaoKvJaa\nOsK0Feb5fh7eeustzJ49G7169ULv3r0B7C6p84tf/ALDhg3DjBkzpOQOAPTs2RPDhg1Dz549YbVa\n8eCDDwq5ePDBBzFmzBhkMhlccsklGDRoEABg7NixGDVqFI477jiEQiHMmTMH/5+9c4+ysyzP/jUz\ne077vGcmmZmEpDkTQoAAMVAOglIIIEWFtAQsTUXrgbWsVl0FV7WVb3Wh/uHqMoosV6sIokVtBZG1\ngiEcNCgQDoEAgRDI+TzHfZ7ZM7P398f0d8/9TsIHWtLpZ997raxMJnu/+3mf53n3cz3XfV33I0lt\nbW360pe+pHe9612SpH/8x3+0sj5f+9rXtHr1an3xi1/UGWecoY985CNv637CCCOMMP67YsqZRs/8\n+RqLUvAEFhbY6dOna8+ePQEgB+BgEarVaiqVSrrqqqt02mmnGSPCwuQ1YYA/UqoYBPhcSpuweMGg\nAAh8m2u1mun5SLf70zv4N/c7uVwIwAxwCSv1ox/9yM4tJuUL4/Q3f/M31p7JJ2f4hdozgYAJABBj\nQJ+yEAMKADWk5gHSvvwN8gF+Rt/JvfIzZXo8wPOsK++j7xsaGvTrX/9aGzdu1Kc//WlLodIP3ojD\nmJL6pdaf113CuJFW5vQfNiywgTCfQ0NDSiaTlu6mnegZmXO+BJJPw3qmDTc2rnjmOGPlmbQnnnhC\nTz75pI0RfVFfP158u1AoqLu7W52dnVq0aJHmzJljukTvoobt8wCN0j+kuEkPYw4ql8vat2+fXn31\nVb3wwgt25CWAl37z7aY/mBe0g9qkzCOebZ5DP7985oD5NGPGjIC0hOfIm494BhsbG/XSSy/9QTNE\nIdN4fCNkGsP43xpv97tlyuo0wkLACrHgY0SAsWCRoBCwL/eCts1rnKg5l0wm9bOf/UyHDh0ygOHN\nG5x2Qn1Cjg/0RaxJnwKSpPEzgP1CDOiDAcK9ywAAkAADvt4eYBUwCdPH5yYSCW3evFlHjhwxMwl9\nVyqVdNlll1nqEgZVkoFQTBkAhYaGBnNG0/eULCHNiHsVUAOARsPpa+zB4KH/BBhKstQs45rL5Qx8\nxGIxSTKWlvQn7l3Sy4DISy+9VPPnz9eDDz5opW+k4Ik3gCq+9KlFOTQ0pMHBQWWzWWMfYcQ4RUWS\nsdown37sYRkZe6QHGGL8uHMmOYw3jGAymVRvb28AmDKPqHUJ0Mxms3r22WetH2BpcSOPjY2pq6tL\n73rXu3TRRRdpyZIldgoM7G2xWDRGlN/T156dlWRmqWq1aunwGTNm6NJLL9Vll12mP/qjP1KtNl6s\nnb5IJBJWP5O2cT988fBcemaZe6ceKRIHxo95BTCkn3mPr24gyUCrB51hhBFGGGEcn3hL0HjDDTeo\ns7NTp5xyiv2uv79fF198sRYtWqRLLrnEzB3SeJpn4cKFWrx4sdavX/+m1+UM6FptvEbgZAchixCL\nBCYMFggAjzTBTFAkmYU/lUrprrvuUn9/v7FEpAVhRTAjUCYEEAgIgJFiUQJMwnwA/nwdOhgen4IG\nhAA+SbMTsFowMC0tLerv79fGjRvNTSuNawJLpZLmzZunZcuW2cJP/T10kYDjRCJhbY5Go+rv7w8c\npwdQpvwRDB2aSsAFEgCAWbFYtPb4/vRnRMfjcetHDBMAFNhbXNwErlj6bnR0VPl8XldddZV27Nih\nJ554Qul0OsBaMV6AaWmcRcUMkkqlNG3aNJsvjCdACjAJu8yGgrGDxU6lUhobGzPwi+wB8FwsFgOb\nobq68ZqV3DfzC9YWUMWc47NfeeUV2+AA5tiYDA8Pa968ebriiit06qmn2jnilMdpbGxUf39/wOTD\n88BZ3ehMmacwqzDnzJdCoaDTTz9dV111lc444wzFYjED44BsNib8DeCjD/znsBlEO+sLpvsUNYCQ\ne2AOod/0bmokE9RVDSOMMMII4/jFW4LGD3/4w0cVmP1dTk54szIYLCKkEEk5+n9z5i8LCgscbBEM\njy8LQuqWxTsajepb3/qWlTUZGRkxrRZOYEm2UMJcsIjC1ME+enDrNZmAIBY8/zeLmWdEAACwqaQ8\nubfW1lb9/Oc/V602caKMZ9bOO+88Y1m9WYgUI6lIjvqDweKUFklWvy8Wixkz6FPwsVjMWFBYSO6x\ntbXVGNuhoSHTnPk0ZzabDTBpgAwYXuYAulJSlZhJABjoLa+88krdd9992rlzZ0BPCgMGkwXLC3Mr\nKVD/kPZ4tmpkZMR0n2j74vG4YrGYbRaYa9Fo9KgSQ+gG0ab6WpG+fJKf54z9hg0bDEzm83lt2bLF\nWGxYeBi+pUuXGjBkY8I8RlqBUQjpBQCXtDildgBfHGXoa4kCLLPZrKLRqC6//HJdcMEFpg31dSn9\n84kpB4ZVks1nXx0As1csFjNmlo0fGxMkA/77wctC/P/DSIYRxu8boVs6jDDeOt4SNJ5//vnKZDKB\n391///1as2aNJGnNmjW67777JEk///nPde2116qxsVFz5szRggULtGnTpmNel0WShZp0NKxUrVaz\n9Bd130iNwgCRDoTpgC0jTYaTORqN6vbbb9f+/ftNXM8CxDVZVCUZY0ZajZ/R//lCwr5ECffCv1tb\nW825ivYO4AnjCDAdGRlRLpcz4PXAAw9YQWiYOF7X3t6uefPmWSkWHNK+zAnpcuphAqC8SxfwJMmc\n4GNjY1a0GwAGK4QT2aeOYcs4cQcDRLFYVCaTsbS219vB6MH+esMQ7CNtAqSOjIxo8eLFOu2003TP\nPfcom80aKOLa/ixlinr71DtsIqwVwBPgRBkZ7ol0uSQrcA4rDgPIH8AtbCMMOulhzyr6kj3JZFIX\nXHCBzasNGzYYSIfhJB27ZMkSLV++XFdddZUWL15sphb6h75lY8ImhH6Xxo0YADuAGXOSVDiAU5Id\ngdja2qp3vetduuKKK0wiALsLyGOeYSaj73i++Fz0t5T96enpsXtl3sH8Ix1h80b9VlhJLwUJQWMY\n/5UIjw8MI4y3jt9L0/j/OjnhWKcdHCtYGGBR/Jc+i4o3J/B/1DVkYST9xmIMSIRN4/rSuNNx586d\ndgIHhZd9AXFJgc+ibT69SOFq0qzcS39/v4GhXC5noIxFDjDg3ad9fX2qq6szJga38ObNm42tKZfL\nGhgYMACwYsUKlctl5fP5QL1KQDA6TXRusGs+pU4KGmaxvb09UIrFax4BXRRL5xowgRQ4b2pqUjwe\nV2trq+kWOdWHU20kGeBg4SfFj76yUCiYGxpGEFf9eeedp1qtph/96EdWQ7FQKBjbR/thH30pJPR8\njAlpT6+J9UYZQKfX0AF+mCP19fXK5XIBTSnglPsEyLMRAqhyLjq1Lp955hnt3r1bkkwWATu7bNky\nrVixQm1tbYF2+7Q2rG59fb3S6bSBV5/eZkx9ityz4uhFAeuUaBoYGFA8HtfSpUv1vve9z8Cl1yCy\nqcKIBAvoNx4AXXTJkcj4aSmAQjIIPPukvT3TC1D0DncYyDDCCCOMMI5f/JeNMJNTtsf6/2OFZ21Y\n+DxA9MDGG0hY9FnsvKuThRxW0JcniUQiikajuuOOO7Ru3TqlUikDVaQ2SYGxyJGuBjgVCoWAyQTm\nA5YFkwlpOZzQpGm9g1WSsWSSjM3ZuHGjNm/erHQ6bQCAtvPvk08+2Qwl9B19SXoXEAnzQ91Bb9RB\nV5nNZs3VDXiiP33pk0qlYvUcKegMqGYcOWqOupOMJWlrWCkAFm30Kdyuri4zDzEGGFFmzpypmTNn\nqlQq6c4771RTU5MdacgJK4Az2FRAPUws9+CZKf872jkyMmJHLPq6jX4+AsK8DAGgB3sGiGKTwbxD\nT1ksFrVr1y4999xzVg+SDYY0vvlasmSJurq6DPAhdeAZ474x9uA49uV/YC15T61Ws9fheJbGZQ6k\nsDECwTI3NzfrpJNO0vLlywM6YTZeMOoAcaQF3l2OJhIA6F3+sLuxWOwouQeaVF9eh41HqGcM452O\nMF0dRhhHx+8FGjk5QdJbnpzwZqcaDA4O6vDhw9q/f7+lf1kASLXC/gG0AGy+vh9AAxaNxYQ0nTd2\nAJ5+85vfaO3atZIUMCl4NorFEHONZ/B8gWnvyGZRJCUMyAUw0VbYKmrecSLLfffdp40bN9oJMQBp\nSVb7LpPJGKBkga6vr1c2mzVTDCwafQKIq1arVhrFt4dUOUyUNzPAdALQOzo6jN0DNJEG54Qbn4L2\nRg+AqDcBAVhgaOlD0uakk6nHWa1WtWzZMtP1rV27Vvl8XrFYzE5kATxi4qE+Ie5nTgjCcMMGBDBP\nepWx5n7pN0rjAMLQDcLaIrvwYKZarQaYVM8wol/F7c3YDw8Pq7OzU0uWLFEmk7Fx4J5SqZT1DXMQ\nxg3mj7nAfGG8YK2RArS1tUmSgVxYPfoRUwv9ctZZZ6m7u9vmKBsLSfZZMPMAaNhiUuV+08NzPrkM\nD+Ysn01g08N99ff3K5vNBgx5YYTxX40wXR1GGEfH7wUar7zySt15552SpDvvvNOO4bryyit1zz33\nqFKpaOfOndq+fbtWrFhxzGu0tbWpu7tb7e3ttnBJspSnZw5IQ8I8eHdmPB63hYuFGoCIvpHFjgWe\ntO/NN9+sRx991E4TkcbBmTeAkDYG/BQKBQNILJT8u6enx4DUZA0bgNTXq6tWq0qn04pEIrr99tv1\nwgsvqKOjQ9LE2cn+NBVJOumkk8xtimPWAySALe8HjAFqAEse1GEQ4n5hfnCXUw5FmjhqkYXb18v0\nBcPRFqITBCj74+IwFwGCPAiFHaYtGIWq1apOOukkVSoVe8+3vvUtHTp0yACrrw/JmGEQISXsgRRz\nDraTdH8ul7O5SbF0X1ibNDTX8iWLAH7cG+CNk3hgASuVir7+9a9bX9N3fGZXV5dmzpxpgBoWW1Kg\n5ifh20EfAvjQaZIiJiZrfBkjwJw0kVFgHkejUZ133nnKZDI2F0hPozvkeoyHN69Iss0YgBdWmGwD\nKXDukdT5ZCNWLBZTPB63zWsYYYQRRhjHJ94SNF577bU655xztG3bNs2aNUt33HGHbr75Zj300ENa\ntGiRHnnkEd18882SgicnXHbZZYGTE4764P/UH7KosKhRNsQbYLzjmDStB44wQN79CWPDz/7UCFiP\nrq4uPfLII/r7v/977dmzR7FYzFKLMGm4j1lwvRbTp2RHR0eNWZEm6v751CEgCWNCNBrVhg0b9E//\n9E/q7e21IwIBnbS3rq5OfX19Ghsb08KFCwNGAEAGejTayuf5WoMsstwH7Bf3SjFmmD7umWtKE2Yc\nXyBcChYG5fhEUsItLS1mAqLYMwyU1xsCwgAP3rUMAwbLPH/+fLt+Op3W3XffrYceesjahe4UdhEA\nRN9KMnczTOfo6KgSiYRisZhtTjxowZiFhtIzd5PZWuYv7nr6DWaVOfjDH/7QjpkkJQ7wa25u1owZ\nMzR9+nRL5wPYJQWKoCN9aGhoUCwWUywWMxMSDmVYVUk2P5gLpIUBkPQ5QJ0x4/+am5s1b948LViw\nwPqP0j9s8GD4eS7pGwwztIPxgYEGcCJLQG7ga4KSmeDZZn6EEUYYYYRx/GLKToRZtGiRsRf+BBYA\nlS9A7Z3G8Xhc/f39VrLDAxtvjIFZA7ywsLC4sfDxPgqFr169Wueee67pvTwAOHTokKZPnx7Qhvl0\noGc8WcB4HZ8H8/Tyyy/rrrvuMhPM2NiYAR7AC+yn14x95jOfsdI4pM9TqZT1balUChTPZnhhx0hn\nsvh7toqTWTg2z4MdHLMwu7CFaEw7OjrMLOHNNslkUrVazU4QgWH0bneYK9g5TC2+L/r6+pRMD80O\njwAAIABJREFUJlUoFDQ6OqqDBw/qgQceMLAK4M5ms/rYxz6m7u5uG3fSy5lMxswV3CPzhdI/XnrA\nPPTgh37wKXy/iWAucj3ADXOcM5TL5bLuuOMOK09DO2DTarWa5s2bp0suucRS6oB/gDbjAxvMv5ln\ngGSYQLS5IyMjKpfLSiQS9swB5qmH6vWkvB+tLM9GPB7Xzp07tW7dOvX09ASeATaFgFmeA2+UAQgz\n1/g9LGi5XFZbW5u1meeAVLXfJErjG9Ht27f/Qbuo/eYsjHc2jkVwhH0dxv+WeLvfLVMKGn2qloCJ\nACzCNLE4xGIx9fb22nvQ7QEsASTSBJviiw6jm8JhzaIKAGBBnzNnji655BItW7ZM1WpVPT09SiaT\nliqGNQSoUmuORZHCz5LMYVwoFPTggw/qmWeesdQ6LKTXFra0tFj6mzbX1dVp3rx5uuaaa5TL5YxZ\naWhoUCqVsgXa11UkDenrW3pgPjmN3tzcrFwuZ2cpMw70EX1L+hKQ45lPf4QffQ/YRCcKe9Tc3Byo\nw0lEIhFLw3ION4CTVPfY2Jhuv/12m08cq4eLff78+bruuusMaGFEgf2jTbQXzSjgCNbNz0vczGgd\nGTPuG+CHVpQ/PGIwqc8884wee+wxm3+kw+nPkZERxWIxXXDBBVq6dKn9ns0LYwhLiAbYb5y4NvOQ\ntqO5ZG6R9vVzLR6Pm4Pdzx1AM+w+73n++ee1fv36wAYPLSj9hNTAn/VOOyTZc8nmhc0amwrAKiyt\nZ41hIMfGxrRt27Y/6IU+BI3HL0LQGMb/5ni73y2R/4a2HPuD/3ORkxQADpQOYTGBjUL/RIpMkrmG\nYbYm6x55PyYXD2CkCU2YP1kmkUhY3b/7779f//Ef/6Hh4WEtWrRI733ve7Vo0SJLJQPmMJt0dnaa\nZi2TyahWq+nQoUN67LHH9NRTTxkjxqJJepN7kGTt5DWesVy4cKEt8IADDA++yDhmFxhU2CwMGvQV\noK1YLNr7AZkAHu9epZYg/+b/AHb0Py5bzyySCoaFAghEIhEbj2q1qoGBgcARj9QB9PUn0Qh6B3Nb\nW5vy+byi0aja2tp0+PBh/d3f/Z2uuuoqnX322da3zA9/IgsGDe4rGo0GirvTNuaS17sODg4GxhTm\nD4AESJOkZDKpu+++2+oSkqoGMOJgpg3d3d22GeFMaOYqaWTYYVLE1GZkHvKcAcRg8nK5nLGk6HwB\nfchFAP70M7pUP451dXVasmSJtm7dql27dgXqUrKRgJGmv3HdM+/Z/DDvfbH0eDxu8xMzFK/3KWyv\n+w0jjDDCCOP4xJSBRu/K9EW6WYxgqWq18VMx/Pm2pHF5vT+txafQWLwAd5hjYAZh0yYzLxhHYGEo\n3/L666/r0KFDymQyisVilnpl0Xrqqae0detWbdmyRf39/XZEXn19vTKZTECHyPUTiYQtqCycuMkB\nLrh9Ozo6AsYY2Dtfbsi7mAFYvl98fUtS9yzMaPlISdPX7MABLTC5OMTL5bLK5bKSyaTdH/2GYcQz\nmwARgBPsIeMCmPVlgOhnQEJ9fb3a29utfiXzxpsrpk+frkceeUS//e1vdeGFF+rd7363isWisbIe\nyBSLRWPJfHkZP18BueVy2V6TSCTMDQ1DC7iBOYvFYnruuee0YcOGALPGSTx+HgMEZ82aZYymT3kD\n+L2G0ksy6MNUKhVIz3tmmA0Fz53XWTY2Nqqvr8+u46sSAPJouzcSdXZ2as+ePZY6pl95vjDg0A7Y\nXlhWxpS5w/PsNyDIMgDhzc3NNpa8N4wwwggjjOMXUwYaSQuSuoJ18yk72Byvq5MUKNPhxfAsplwT\nVgSNIe5p0rssfAR6OU4fuf766zVr1iwDVwAtWDnvRoWNnD9/vlavXq1EIqHDhw9r/fr12rRpkw4e\nPKhZs2apVCqZEzeTyWhwcFBNTU3K5/PGjvo0Y0tLi6UKeR1mFti6WCymYrFo4BZ2yqeH0ZZxzzBo\nHR0dymazpvdDK0dJI/oN1oq+JV2JUx1nNil5TDdcj+PrAPiwSL29veYkRrcHQMNw4121vtRQMpnU\nkSNHDETE43Fls1kz9HAiT6VS0aOPPqoHH3xQK1eu1DnnnGMlhPr6+o46cQeghByCv5lzgKdEIqGe\nnh4lEgkVi0Vj9+iH9vZ2bdmyRT/5yU9UX19vqVZkDgcPHjSTCrU/8/m8ksmkMpmMjZln9pAcFAqF\nQJFuaYJ95D78SUEAP+6BVL831rBJikajpjn1MhFvnplcP3HmzJnavHmz6Tibm5utP2AQ/caFowWZ\n51zLfwcAamFseW5hriXZpsvrjMMII4wwwjg+MWWaxvnz50uSLRCeQWDxg50CVAJ6enp6AvXxACEs\n9lyXBQnGCKAAu+ENBSMjI+ru7tb73vc+nXjiiYpEIhoYGAiwIDBgsHiYN3CDwo7BzNXX1xuQKxaL\n+uUvf6knnnjC0vDewAP49GCYvuLfn/rUpwIlUWAhuR8PZD0ABBiwWPMzKVdSk7B/3gRD/9EGPgvg\nCPuDbMADX5hT7gOgC0PrU88YKAAYbCIw3EgyAIVL/KGHHtKrr75q70Xfxr/5XFhm3PqStGjRIr3/\n/e9XMpm0fmtsbDTXNZsJGDc0pLBgsKy0k/kKkHz00Uf19NNPm6YwFotZmwA4jAG/AzSlUildccUV\n6urqMqbSG788IPRlgnDvt7a2WtFu5haAD6bZO5QrlYo9a4whOkZpQmMKiKMtsLoUtP/pT3+qnp4e\nSRPHVBL8DJPPMYEAVzZrnvlsamrStGnTAkd6SrK57Vl2+nbXrl1/0IxjqGk8fhFqGsP43xz/4zWN\nkiyd6BlDjm+DmWhubrbfc+KET8cWi0VJ4+5gn+bzjmY0UQAddF+lUknDw8NKJBL69Kc/bWCBc4Yl\nGeNGG9GIVatV5fN506zxByBIiZZ8Pm8L9aWXXqqrr75aL730kn784x8ba4j7lfbSNtLZ1I4k/Qlj\nQ2kizo0m9Un7otGoWltbLfXqwZkkAz/caz6ft77xTKNfoCUZMGYhh3FMp9MqFAq26HuGjP6LRqPK\nZrPGQra2tloqH/Di2SX61ReKBpAA1hlzrwH17Bh9gp6vtbVVhw4d0q233qpisagzzjhDa9asMTDr\n5QqAek4DgslNp9PWrzBzmzdv1gMPPGCmKWpgcn6zZ36Z/yMjI0qn0wbWAIS+ggDO50KhENBb0s+S\nbPMgyfoalhFtKM8K8xgXOe3wJY8A6nyO3wygYW1sbFQ0GrVSPt3d3err67P3wdoCNGkXoFOSbQZh\n1dlYeMNVLpezk268k9pvjujbMMIII4wwjl9MGWhkkfeMWzKZtFIgLFKAJrRd6Nf4P1J9pEthywBw\nACDMCYBCFsgbbrhBc+bMMVMAIMMfWUY5HIoXS7LrwRiRdoWhgdXxNRM5raSzs1O33HKLduzYoXvv\nvVc9PT1WDojXw8LAIPq6jwABb4YBbKATo70U64YtBWSSYoXlwdTgj//zJVO8oQM9naSAWWZwcNCY\nPRhWX1yaFLMfM85xhkUeGhqytCYgkrlSLpdt7nC2Nulo2kW7caBjxoEl46xuShVlMhkdPnxYX/3q\nV20TMGfOHM2fP1+dnZ1qbW1VZ2dnIGXa19en3bt3a9++fXrjjTe0Z88emyPValVtbW1WZgcGGWaP\newL0eKc6gWYW4F4oFEwfy2bIs6PcM6AYzSXPBACO8Yelr68fPzebuS4FGWJYauYH4I4xZl7WajVN\nmzZNbW1t9n6eB56hVCplGwqqC/AcwZj6sjzMN78JpD2wvF77CKAPI4wwwgjj+MWUgcb6+nozT5AC\nJIVFcWPYEFgfdJAsDpTggIUiRTfZ2ALQbGlpsQVoyZIluuaaa1QqlQxENjQ0mPMYIOjNB2gjAUXV\natXSgJICJ314EJtKpQKAq1qt6vDhw4rFYvrsZz+rnTt3au3atWpra9PIyIixRqVSyXSdFB5nkeVa\n3mDAvbJw83vMP9I4Mwu4lGRpQQAMesH+/n5jgzCn8LtisWj6RMaRPuHz8vl8wGjitZ8wmvQPukPa\nJo1rImHXfOo8nU4bawegxDCCUQdQAbOMLhKNJGDMG54ikYhmzpypSqWiQqGgjRs32rxEd9rU1GRG\nIF/UHKbQl08izUzNQ3/aC/MJjSq1OwGepGgBRtwPfYhEYGBgQKlUSvF43MA3mw/mG+Dc10ElteyB\nZSKRUC6Xs+fH/x8bE9rCMwoI53SW7u5uJZNJDQwMBNo5Ojpq7WPOUX3A9xepeOp1onvFSQ0whBXl\nvZx+40skhRFGGGGE8c7HlBph0AhS2w4AgLFFkgE3X4qmt7fXQJw0cdatX1B87TxAiyTlcjmtWbNG\nJ598sp0Y45k7z3jgzkQrCYOIsQP2iAXM67N8vToYQc+WAgxyuZymTZumr33ta1q3bp1+9atfWR9N\nZgMBY5gBRkZGTO/lP98DE9oA2yPJAKPXjAKyc7mcle2hVqIv4eId2Rg+aCdgjlNYJgMD76qF0WT8\nASq01bOKMGfRaNQMQ4BdNg5DQ0OmraMMEUADwEX7GB8AaalUMnCfyWTU1dWl5cuXG3iH5erv79fg\n4KByuZxyuZxJK2AFYYj5va97yDyRZBpSwBogj7nL+NIngHI2Q2xMSM8Xi0VjZpmn6E9xUdMPkUjE\nXu9rlHoDENpKPzcA3J6Nr9VqVv4ISYcvgM4zyTPl2UBS1f7ZQq7CvBwbG7N6pTDnzB+/qfNa4DDC\nCCOMMI5fTBlo9DXwYDJYDCRZcV/YFlKmsGgssF635s0j3uFLGq9cLutTn/qUTjjhBFuAYGY8o8mi\njHYQo47XBMJsRKNRWxh97UKKFfs0MW5pTuyQZCnvUqmkD37wgzrjjDP0ve99T5VKRel0WuVy2QAC\nZVxIpfs6hZwCA3iCYfPHAWazWdNB+n6nrdls1lLHuVwuUGvRO21JLQKGvPsZ5qlSqRgb5c0ygEnG\nDUDCZqGurs7YJl9CJ5VKGXsJY+zrcQI+uA4Oda9lBKiVy2Xl83llMhldd911Wrx4sTmuvazBm3gk\nBbSygMX9+/frV7/6lZ5//nlLvwKiOafcmzgAfwAoCo6zAYL5Zm6i6y2Xy2a8SiaTAWA42XDEhsLr\nV5mTaAClcWa8v7/fQCts37Rp0zQ4OGjX85pBNmukuiVZ+hy9Jc7ufD5vYJQNli+bxPcAgNeXe5oM\nJr3mkzHFqe31nGGEEUYYYRy/mDLQyILj06ksGiz2LBT+9ywiyWTSmDvvEPWsIgsSC9EnP/lJtbW1\nBc6TBlySegaokKaTZPpCTkwhVcfiTMFs7zaFJfJOV5y5sKC8hoW/v79fbW1tuvnmm/Wv//qv2rdv\nn9rb2w3ASTLwTD8AYkg3+vqHgF7+7U8AkSYKiXNNGJ5oNGpgDMkAjFwymVQsFtPAwID1FSCLvgF8\n+rQ/6VtAp6+tByiVJly3nHkMCGJsSE97vR3A3TuRAajMi+HhYQ0ODqqzs1PXXHONFixYYEYWzEWw\nykgPfO1Ar8lEN4pWdeXKlfrABz6gbDarJ554Qlu2bNHg4KC1j7HjWvzxjnSkFzjimSNoAzFyYWzy\nBh/uk1I8zDueBz8GsIPUa/RsM9rPvr4+m5cwwt7kBdubzWaPKhN1LMDN/3Ed/9wxr7g/+sL3PYCZ\n+6Rv+JnjH/lOCSOM3zW+/OUvT3UTwgjj/4uYMhEQLBcOXtgOr9fzmjqO6POLFGDJ6668cxkWa3R0\nVDfeeKMxQABGNIi0Jx6PG6sCKPHGFGk8tQiTSTthRnzajnQ7Jh7SbJIMqKFRA4TCqhWLRX3sYx/T\naaedpr6+PlsYvcsUMAdzCBMEw+ZT5TBssIY4tv1JIJxzDUPmmWDAC0XAC4WCfR5MMOl2wBApVW9S\nikajdg/e6YxWEO0lqW8+FxAJu0g/0mflcvkosxCO7kqlosOHD2vOnDn62te+pk984hNWHxJ2C8OF\nNM6e4ogGdEky8MX44ooGKFFk/KKLLtLnP/95fehDH7JrwZpiAPEsmr9/aiQyZvQ9TmLG1Os5AZCk\nz5mTXnNZq9VMdtDZ2Wlj4Wst0jaeR+6btjLPAXw4/2EBKWfEPIX9po99JoGf2RzSTzxXMJmkvn2l\nAA+8yQDwLIRGmDB+37jlllumuglhhPH/RUwZaGQBIQ0MY0X4cis+pQXjBMtDCRUWOVK/3vG7evVq\nSROpQQ9uvKbOawJJzfqiyJTB8SexkCZEhwdQY0GHqWEBhTXyLBOgy5/JWygUdPXVV+u8884zUwyv\nI0UIg+oXYtLR1Cv0JgrAgWee6FvAMPeE65aFHQYT8Ow1caSl+WyOffQsG7pID5QBdoAN2FxfYxMw\n2Nvba/3P9fL5vIF9AHssFjNAnMvlNHfuXH3lK1/RqlWrDDjxGu8M9o5daUI2AAD3GjxvFoEdA9AU\nCgWNjIxozpw5+uxnP6tLL71UHR0dgTGh/f6YPzY9pPUBYZSsYQwGBgZsXNCewiQnEgmTBsDgAuab\nm5ttXLw+ELaOP5PBPkw2P3s9IRuLurq6QIrYP08YeyQZUPZMqyT7GSA4+Vmtr6+3/qANra2t1nek\n9n0qPowwwggjjHc+pgw0oq8CpKCH8uwBIAaWB0bBLzCANs9ioGsrFApauXKlTjzxRNP8Uc4Hpo8F\nmQW7XC4H2EgWTNoK2EG7xWdTNgVAF4vFFI/HrQ4eGk2fiuXeAags4rBE5XJZF198sc4880wNDAxo\nx44dR5X2AUCQogOcUWgcAFEoFOw8Z36G1SRN29AwXoSc1DuglPunT2q1mvL5vPUhwAEwRSklTiwB\nuHgnOqAGoAIYHhkZUTabtc+RZOAM9g8wSpkmwCRsGLX9brzxRq1atUrValX9/f2BueJLFgFG6Fdv\nxKrVakomkwaEYI3z+byxY7DSnu0mHb58+XJ99KMfVUdHh/UzYJ5xrtVqgWMLcR8DmmEnAVAAu1gs\nZkDcayV5BnCrAwJpO6WImNts1phTuJcBdX4zBavtdaXINzCsTNYoAy6Zn15Cwvzx6WVfBQBATT9J\nExtOnl3ma+ieDiOMMMI4vjFl37KwH9I4CCStBTMmyVKVLCiABxZ/wJfXn5GqrK+v14wZM3Tuueeq\nWCwGTqdg8QV0kQanfh7aKdKfsE/VatUWXO9spd2webCCgFCAF9cFIHsmh8W2WCwaYwL79oEPfEBn\nnnmmnnnmGVswef9kdiUSiRir6U/MwQjD/Xsg4tnA5ubmQHFprxekVuKx3Ms+bQhDDJDgLGzYYZ+y\nRScpTTBF3rQCgwtg88caHjlyxFLE3qG9ZMkS3XLLLUqn09ZGD2Z8+pr/A/QBZgA2/qQWgrFm7ABt\nsMSAHlLKDQ0N+vCHP6wrr7zSTncZGRnR4cOHrZyR3yiMjY1ZIW9fmxHGEzkH5ZjoK5jS+vp6G2uv\n/yMlDasqKcDskW7m+l4iQuqfZ44NB/3Q0NCgnp6egEHN1/9kLjBPcrmcvcanyxlL2k5/exYSVz8g\nlGc4NMOEEUYYYRzfmNKtOanpWm3i+De++D1zgICexcgX1maRId2YTqeNcQIwwpA1NjbambqksH3x\naZhNQBRlbuLxuCQFNH6cUENqDP2cpECdPQ8k0CxSJse7cr1eDaDGgnjkyBFde+216u3tNZaQ/4Nx\nQ68IkwPARl8GAPBlaGBA6X8A2PDwsMrlsgqFgqRx8Ip5ArBBG0nXeq2i17T5en7U5xsYGAikdcvl\nspXK8elx+gDQC3AFvA8ODqq1tdXkCQMDA1q1apVWrVplRiPmCW1l/AFDAGzAIpsT5hap0FgsZgYh\nrkepH9hAzjn3GkA+b2hoSCeddJLWrFljp+5QQomTWsrlshl9AJbMXTSnzDc2SdKElo9TVwBhkgI6\nRNhiLznwqW7v6GaOeuOJpIDpSpIBSbSusKAEDK43fDHfAObMZQ8YGQuYRM8yw2ADIr3RKowwwggj\njOMXUwYavTaPBRbBO3UQATue1YJpo0wLbBEaPNjBSy+9VDNnzgykugARkmyB9DXxvG6S9BuLtyRz\n6uKu9SYKakxWq1VbwAA+1WrVgAcLH4wL4JX7hAXCbMECXCwW9f73v1+bNm2ya3Lfk7WhvAeQhokA\nZofrwRSNjo5akWlAEf1bKBSsliDhgZA0cYoIpXEABKQmYeYAuKTs6UOOeWQeADKoCwj4hYWLRCI6\ncOCAisWiYrGYMcmf//zntWjRIjMPsZmQJlgp2samBADJ/QJYPdgeHh429hg9pJc3ANABX5lMxoAc\nDB7gNxaL6ROf+ISl1dPpdKCwN/eZy+UCWsO6ujp7JrzOkPlDP9Nuxoh2An5bW1ttfqG55Tn0JYo8\neIdNRQuJucs77uvr67V//37bdPBen/7mOUSCATMsjYPbQqFg4BRt5+TUOwCTDRxHNMJihxFGGGGE\ncfxiykAjxb19GnVoaChQcJvfscjDYnnAxMLJIgNQWr58uTE/MG/+vFtex+IKuCAdTekSAAvsCEwh\nizNAhMUW7WRra6sSiYSampqsniFtxriB7gz2hXuk1qHX9HG8XTqdtj5i4YxGowa4aR8LLKVVAMMA\nHa/pYzzoV8ATOkyYL8CN1y+SZua1AEVK5gC8JRkYkxQA1zBvXqtKIW+uiUEGQHP48GErn1Sr1fTx\nj3/cWDpSuZ55xTiELs9vRBg7mCt0pxTP9n2MISMSiSgejwfS3fQvIKq5ufkopzv9fd1112nWrFm2\ngQDck/o/cuSIpbbZbOAg91pVDGSUjKImJRsh/tTX19tcl2RaRPqT+U8qmE0O6XFvfOJ5mjZtmqXI\ne3p6TFqBu5pNHX3DnGUeeE0lpYDob19P1Buz2GjRNk4A4p7CCCOMMMI4fjFloNFr1ljUYCRgL3Ax\nk3r2aSjvqPap2XK5rPe+9712LVhDtHEsUk1NTVZEmTRiqVQKpIYpvAx44Pccm+ZF/YAgWKFKpWIn\ng3ijAQsl98E98T4WfV8rEmaooaFBc+fOVW9vbwBg+NNPeH+5XLa0HuyaN5twfYAdTBP6Up92ZaEm\nRQrDypiMjIzYqSgwZR4kSLK0P3pKXz/Qn5oD4PK1KX2ZHWk8Hbl161YDH2vWrFFHR0cA9PLZvg2A\nE9gswIg/wcTLF4aHh60WIeCbNCmsNgwiLCIOdhhuQBrzCWDf3Nys1atXq7293dqG035kZEQ7duzQ\nrl27tHXrVhszACdzzzPZMHje5e31megA2dSwSQHIFgqFo3TFg4OD9owA/Hk+RkdHddddd+k73/mO\nSqWSBgYGrHA9koXh4WG7V56fyQwpfem1of4+YU0BxpHIeCF82GVvpAmNMGG80xHWbwwjjGBMKWiE\n5YAd8xo7SQGmxC8ksE6UovGavkgkolNOOcXq20kT5VNgJGDqML6wYMGwSRMifBgwhPws4PzbMyCj\no6MB0w2v9fo6tFgwRgBnXuvL6HBMH8fdeSarr69PtVrNtGukMT2Q4YxhgOVk048vqzI2NmZnRwPS\nYGlhmnydPBgwgDU6Q65DG7zGEcDGZ3qHtDTh0vXMH6ADzWNDw/jRizt27FA+n9cHP/hBdXd3K5vN\nWlswkbDhAIxgyvHADeDNcXv0GwwaGj6YOSQKAGSczrRZkuldmQeMC457QFVjY6Muv/xy03VGo1Fj\nlfv7+9XX16e5c+fa8YcYvSa7+n3/ekYe0E1tTph9whuXvJt9eHjYSvu0trbaXKbsFJudlStX6mMf\n+5ji8bgOHTpkulUvswAs8zs2QTw7zAGAH+32Zi3kDb4Opz9a1BuTwgjjnYywfmMYYQRjykAj6VEW\nI+8u9u5gXLiSAmCNtHE8Hg+UbjnnnHOMmSMliU4PJi2VShmQIB1HG2CGYH0oZUO6DxDiwQ2uU8+q\nABTRjlEcmxQnCxx1JdGV8ZqWlhZzagNuEomEWlpaFI/HtXXrVrsvTA6TzSK0KZfLWWFzFmpeQxs9\nqwqrMznNDTD0jBz9ApDk2izqaBVzuZwBfG9w8A5s74jP5/N2Ha9tbWho0KZNm1Sr1XT22Wdr8eLF\nGh4eViqVCoBEADqsm2fifPocCQQyCT4jk8kEmGlJBuSLxaJdIxqNGisKaKZv0AG2trYqlUoFUv+U\nGcpkMrrmmmuUSqUCtSGz2awOHjyovXv3Wmqc9CubgKamJsViMRtHnO0YmvwYe2bSn+0sTTCwjFkk\nElF/f79effVVDQ4OGkvNhgpDDUzlwMCAtm/fbilmb9Cib2k3aW5vgmHu+HEDaPI77sdnHzxTHYLG\nMMIII4zjH1MGGmGhvAvUAzxfusTrsVhUJJkrF0AQjUZ19tlnW6kaSQHw4mvoASRYqH27JBnbAaij\nvXy+T6cCrnwaz6fNmpubNTg4aPeDRg29H8wJ6Txp4lg2akHiyi0WiwbsDh06ZOlFn8oeHh5WMpk0\nFqmxsdHOfyY4ag6ADWsFiMcYAyAH7HGfAEffP4BB/zrGhtQt7QMI4EAHzLLwMyb0GeNUqVT00ksv\nafbs2br88ssN3MOaoqnzDnv6C0bRA7tqtWqGI29mggHFZCGNM3OpVMrugWsD6gBfMOGU+aHEDCzZ\nZHd9MpnUaaedZmn/eDyudDqt119/XYVCwVLEsH+Ae6QEsO5IDHz5IzYRlICi3BHlfGD7uS4/t7a2\nas6cOQEJAkCPz2Zcjxw5YnVKy+Wy4vG4gWLmFhpFb2wCMDJPkQgA5mkLWklexxzxmwyY0jDCCCOM\nMI5fTOkxgiwoMAgALRZdQCLOz2QyaQub1yay+KRSKTOZoAuEFWRR4+QVz3pJMtDF4glQQSfIokQh\nYUkBQAVA5H6kiaMQm5ublUqlTC8mTbA1pCa5B9LqLS0tamtrM8bVl88ZHR3V0qVLtWHDBkkKgNZ8\nPm8pcPSXvsQMi/XQ0JABUYI0PAaOarVqjlZALEXL/f0B8n1dRsC3163BKHpDA7KEtrY22zDAegKy\nJBkz+MorryiXy+l973ufcrmcMU2AGtLiuN7RCmIsong5gA4DCXPPG7C8K5q50dfXZ/ed/MH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DGmJA4mCPoUowzgORaL6YEHHtCWLVsCqdxUKmXtBmx69pNUtT8tiEBvyRgNDg6qUCjYBgU9JUW2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GFb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\nmjZtWsHxf9QbBKj4dJUvy7NmzRrt27dP1dX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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "2044516\n" + ] + } + ], + "source": [ + "\n", + "num_cols = 2\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "num_bins = 1500\n", + "pdf_hist = False\n", + "plt.figure(figsize = ((5.5*num_cols),(5*num_rows)))\n", + "plot_yscale = 'linear'\n", + "for x in range(len(corrected_src_data)):\n", + " hist, bin_edges, bin_avg = histops.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " \n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " plt.subplot(((num_rows * 10 + (num_cols)) * 10 + 2*x+1))\n", + " plt.subplot(320+(x*2+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + 2*x+2))\n", + " histops.hist_plot(hist, bin_edges, plot_min, plot_max, plot_yscale, 'No')\n", + "plt.show()\n", + "print np.amin(hist)\n", + "print np.amax(hist)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 4: Thresholding for trial volume segmentation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: threshops.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### This module contains tools for thresholding image data." + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "Currently a number of tools are available for both manual and automatic thresholding.\n", + "\n", + "Manual:\n", + " Manual thresholding requires that threshold intensities be identified and explicitly stated\n", + " within the thresholding function call. The result will consist of a binary representation of \n", + " the original data set where all voxels, originally assinged an intensity value within the\n", + " specified boundary are assigned a value of 1 (True), and all voxels with intensity values\n", + " outside the specified bounds are assigned a value of 0 (False).\n", + " \n", + " Options for manual thresholding:\n", + " + Global thresholding [requires only one threshold value be specified]:\n", + " *thresh_globalGT() -- Greater than the specified value\n", + " *thresh_globalLT() -- Less than the specified value \n", + " + Bounded thresholding [requires two threshold values be specified]:\n", + " *thresh_bounded() -- Identifies all voxels with intensities within bounded region.\n", + " This method is useful for isolating specific peaks, or materials, within a single\n", + " data set -- termed multi-thresholding.\n", + "Automatic: \n", + " Options for automatic thresholding:\n", + " + Adaptive thresholding:\n", + " *thresh_adapt()\n", + " + Otsu method:\n", + " *thresh_otsu()\n", + " + Yen method:\n", + " *thresh_yen()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import threshops" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Thresholding Operation successful:\n", + "Selected Threshold Value: 1000\n", + "Isolated regions in output data set had a measured intensity GREATER THAN the selected threshold value.\n" + ] + } + ], + "source": [ + "#Manual thresholding demonstration\n", + "thresh_value = 1000\n", + "\n", + "solid_matrix = []\n", + "\n", + "for x in range(len(corrected_src_data)):\n", + " manual_result = threshops.thresh_globalGT(corrected_src_data[x], thresh_value)\n", + " solid_matrix.append(manual_result)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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K5s2b8f333yMajcJisUCj0UClUtX6npEjR+Kxxx5DaWkpSktLMXv27DOu/p2L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\n7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5pgrhNWHEk41wOTDGjk2kkSUDuK8RVMPsAZ52LaOb388stqb29XuVzWggULDARRh4yR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efPBBDQ4OamBgQCtXrtTZZ5+tUCik9773vfrhD3/4mvO/XlxzzTX2JwC8QUyXSCbbaz2EaRWn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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Plotting manual thresholding results\n", + "num_cols = 3\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "plt.figure(figsize = ((5.5*num_cols),(6*num_rows)))\n", + "for x in range(len(corrected_src_data)):\n", + " hist, bin_edges, bin_avg = histops.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " thresh_coords_x = [thresh_value, thresh_value]\n", + " thresh_coords_y = [np.amin(hist), np.amax(hist)]\n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+2))\n", + " histops.hist_plot(hist, bin_edges, plot_min, plot_max, plot_yscale, 'No')\n", + " plt.plot(thresh_coords_x, thresh_coords_y, color='r')\n", + " plt.annotate('threshold marker', \n", + " xy=(thresh_value, (np.amax(hist)*0.7)), \n", + " xytext=((thresh_value+750), np.amax(hist)*0.95),\n", + " arrowprops=dict(facecolor='red', shrink=0.05)\n", + " )\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+3))\n", + " plt.imshow(solid_matrix[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from thresholding')\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Thresholding Operation successful:\n", + "Selected Threshold Value: 1164.0\n", + "Isolated regions in output data set had a measured intensity GREATER THAN the selected threshold value.\n", + "Thresholding Operation successful:\n", + "Selected Threshold Value: 1164.0\n", + "Isolated regions in output data set had a measured intensity GREATER THAN the selected threshold value.\n" + ] + } + ], + "source": [ + "#Automatic thresholding demonstration\n", + "auto_adapt_solid = []\n", + "auto_otsu_solid = []\n", + "auto_yen_solid = []\n", + "\n", + "\n", + "for x in range(len(corrected_src_data)):\n", + " \n", + " adapt_block_size = 250\n", + " adapt_thresh = threshops.thresh_adapt(corrected_src_data[x], adapt_block_size)\n", + " auto_adapt_solid.append(adapt_thresh)\n", + " \n", + " otsu_thresh_trial, otsu_T_value = threshops.thresh_otsu(corrected_src_data[x])\n", + " auto_otsu_solid.append(otsu_thresh_trial)\n", + " \n", + " yen_thresh_trial, yen_T_value = threshops.thresh_yen(corrected_src_data[x])\n", + " auto_yen_solid.append(yen_thresh_trial)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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AnnvuOdpSBCU2NpYAIJGRkbSl8E5LEwytTR/MeOrZzp07RyNr2jFv3jxe0rNy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\nBoPBMIP/AzXUgv83XZc1AAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n" + ] + } + ], + "source": [ + "plt.imshow(solid_matrix[0][:,250,:], cmap=plt.cm.gray)\n", + "plt.show()\n", + "for x in range(num_vols):\n", + " print x" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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QmZmZIjc3V3Tr1q3S32WpbjH2NezYJ4QQZrNZxMfHi4EDB4o77rhDuFwuj3Wj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\nSm9uOrAv3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RQBxqyRMbbxeBwFBQXi/otGo+L49Hq9sNvt4m7kOAIHw694PC7b7PF44HQ6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P3973/v1+uXLl06JD7bBeudv/eyqqo2bH+D1XC7l3366ae3+rvhcC/bX9gf3MtWa7tQ9cEH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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Plotting automatic thresholding results\n", + "num_cols = 6\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "plt.figure(figsize = ((5.5*num_cols),(6*num_rows)))\n", + "for x in range(num_vols):\n", + " hist, bin_edges, bin_avg = histops.hist_make(corrected_src_data[x], num_bins, pdf_hist)\n", + " \n", + " thresh_type_labels = ['manual', 'Otsu', 'Yen']\n", + " label_offsets = [0.95, 0.8, 0.6]\n", + " thresh_coords_x = [[thresh_value, thresh_value], \n", + " [otsu_T_value, otsu_T_value], \n", + " [yen_T_value, yen_T_value]]\n", + " thresh_coords_y = [np.amin(hist), np.amax(hist)]\n", + " color_set_ = ['r', 'g', 'b']\n", + " \n", + " plot_min = np.amin(corrected_src_data[x])\n", + " plot_max = np.amax(corrected_src_data[x]) \n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Transformed grayscale data')\n", + " \n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+2))\n", + " histops.hist_plot(hist, bin_edges, plot_min, plot_max, plot_yscale, 'No')\n", + " for y in range(len(thresh_type_labels)):\n", + " plt.plot(thresh_coords_x[y], thresh_coords_y, color=color_set_[y])\n", + " plt.annotate(thresh_type_labels[y], \n", + " xy=(thresh_coords_x[y][0], (np.amax(hist)*0.7)),\n", + " xytext=((thresh_coords_x[y][0]+750), np.amax(hist)*label_offsets[y]), \n", + " arrowprops=dict(facecolor=color_set_[y], shrink=0.05))\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+3))\n", + " plt.imshow(solid_matrix[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from manual thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+4))\n", + " \n", + " plt.imshow(auto_adapt_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Adaptive thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+5))\n", + " plt.imshow(auto_otsu_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Otsu thresholding')\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+6))\n", + " plt.imshow(auto_yen_solid[x][:,250,:], cmap=plt.cm.gray)\n", + " if x == 0:\n", + " plt.title('Binary result from Yen thresholding')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Adaptive thresholding: Block size evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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0Wum8Z4xW+WwN6bRSYruD9GcCoYQyQfG/IaXM4DNW87ASR6kp5zWWE0YQnlxm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\nzH72gI1GhIVoE6wUq8INFtlkhBjVPjCpEe86O+4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3XBckaSpsNzgs3tkg3fWWBF0iR7Rz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\n1lChRLnSXOktKaF0+hkGmhfK1B1mih4Wy5Zhvt7ON1dNRxxS2y6NFEgKr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cO1slEbG1zu\nXc8YrZ11VuhsqRRjPWGB3urar0SsAh2t1U6y5XpYopvPPO8Wba1zixd0le9lN7jD06bKcImPNLXD\nY+7VxQqRjqvmhHnOt11T0Urd6SkTjXRYLRu1tkUL15hknj62aCFWiR/5kz/7oVY2GWKqnvLUs98u\njazXRl9zPen/2KWxXhZarYOFernZC0rEiVPipGpmGCRaqWilNmlphMk+dYGjaoSM6BgnVDPATK+6\nzmgTvOAWP/U7b7nKHg1FO+Q8ix1XXbE415hsq+b2aBDqa7NJjkHqOmCqIQokaWN9qDTSbkuluMYk\nyZZ7wc06WKO64w6JtlyywabbooWjamhqh5U626WRmo6a4wKjTJQjXSsb1XFAiViHRGtgrx2aamWT\n7Zrqbb7NWhpiqhil1mrnfo/Yq4EijXS20iYtPes2UY5JlWekf2psl6a2m6uvGAfFOGiIqWYaoK79\nytSwQxNvGu5T/VRzwq2e08MSl/jIdIN97Fua2u5Cn3jFDaEFhYOOqhEqb/qpA+qYZYD5eisRa5Hz\nDPeGjgr8yY90le8lN6rpiLdcpY4DnjFavN2hRYDyxZdoh5SI1cgu0w220bpzqi8DlXnX3TKfGCJd\nTiXe9bRQmRoKJVmtg60SNLPNxy52VA3HVRerxAnVLJXiTk/5vf+jv1lB35+VOrnYv0w0UjPb7Azx\nLttFRpsgR7of+VMl3nW3TKyD6tqvnXVmS6uSd4dEKxHnRTdrZWOVvHvLVZIUaGGzT1xoiR4Oq6VU\ndKhU5wA1lLnNs2o4GvCusZ26WBHwrpcFrveqMjW8boR8yQHvajry/7F35+FZ1Xf+/x8kYYewQ0jY\nEwJJWMO+GhQVQWRrXautolbbsdZ2Ot+x2npprc58uzjWTrVV1Kp1l0VEVECI7GtYAoGQhH0JEJYQ\nCEuW3x859ykB3KZOvzP297quXAaT3Mu5z3me9+fzXl6+6W1Xe89+cc6oZZoJVupnkKX+3b8qF+NN\n16nvhMOa6mONbjYabban/EBDx93tGRkyq/HuNi9o5rDH3a+ZwxopFqXCIkOr8W620WKU2yvBDOPd\n5Rm/9WOxjptkqgyZ3vZNSfL0tN7VZqnvhANaWWiYyaZ42EOfybsolT5xiflG6GWd/eIu4N0hLUQr\nN9ZML7hVQlAB/C/+rz/4vrNqqRf44EV4N8QSe8U7rqGtkmVYYJ2ebvBa2PEw1OJqvEuWq5miC3g3\ny9VGmK++E1brq6HjNksJz9sk+VLlyJShg+0B7xoqVU8TR+3UXkfbHNJcH6slKtBFrvpO2q5jyLuW\nDtoq2VKDZcqwVbLT6rjOmwZbKkql9kFifqJpWjkQcrWGqmRJG3s87W4jzQ1dOwZbapYxPnKleS7T\n12rbdKrGuwZK3Ozlarw7o7bFhrjOG9V4t0VX7ezyqpsu4N0BrbSzqxrvnvY9J638WvHu4Ycf1kaS\nYRbqYYMFMmTI1NvaoPCnl7s9bbe28nS2Xo/Ak+9dzwYdD3nnjEVdp5fBlqJq7FsPGyw03C1edkQT\n7xmrhw1W6i9Zrg8Cz9LV+njAY5YZJFt3jRTrYYOOtqsQ7VLzQx/qiOf3zV7R0kElGupkmz/6rnZ2\nqqdUnEKJ8gPv5Tra2K2msyrV8IqbZcrQxh6dFEizSbRy0SoMslRLBzV2zDyXSbcGVUmAVfqhKumV\nKUOBRI2C35sVJEC72uz7/hAeA/iLm/SwwTPu0teqoDiphsWG6GED2K2NVfr5yJV2a6uD7Roo0VCJ\ndXr6kSfAxy61V4LFhigUp4cN1uhjprEyZIabjS0d9LrrpVsTbuDDMIs0dcRmKajalP6ZX4R+Yuf6\nbq2RrrcsT7lHkjz3eCpIYM/zgts0V2SG8e70rO06uMdT5gT3v//j3y0NRqAny/WMuy0JEoAJ9ioX\n45hG5rjCv/o3Z9VSKUqSfEc08ZZvSrFZfyv0stYSg2XI9IGr3OJl23XUwwYb9DDRVBulqRCtVD2N\nFCvQSaZLZMgUo8ybrtPJNsVifWCU9nbqpMBZtSwxWJHm2tgjzUYFOqmn1G5tXedNm6SabIpisfZp\nHa43zleEd3u00ck2tc7xUIucD4MtrfZ9Xac0/ozK4L+4yWyjLQwSYBF1sF1zh5SJ8UP/4aR6zqjl\nZbc4o5alBhvlA+3tsEs7nWyTKUOaTT5yhXpK1VBpk1QHtLRfnFPqSLdGSeA//IevKe8uFtvt1N5R\nTazSz/0eVyjOUoMd0USeJK3ts02nCx4vR4r+Vn7q8y0xWFu77NFGPaWmG39BbLfQsIvGdh+54lPX\nsufGdvWUOqS5vlY7q6ZvetsLbgtju6fcY7e2GjputPc1U6SR4s9MOPzOvc4GCc/P0k3+4mrvhd0L\nX1T1g0K8112vhw1SbQp/NtNYP/ZbtZzxpHsNtNwsYyQHXn1fVIMtDT2TL6bNUvS1Kvx3lEp5khzW\n1ETT7NL2c2M7qhJC9Z0w0lwxyrzgVkWa26F9tdhumolu9GoY2yXYY694ifIVBB35VQnZUokKqsV2\nxRrZoqs4+yXJ84y7dFJQLbaLsHu1vuFnfL7+Vt/IiCJ+alsl2ywlvI/9LTo3tjsWTOD6NEXGz0cU\nKWzfKE26LBv0kCjfJy4JX1u2bmFsd0ZtN3jtax3b8fm8o6qb8FBQ5PB5+jzefZoKxRlrpjxJjmps\njPdRlfhu5Jg6TofFeRky1XJWhkwFOjmmcRBHDjPGLCUa2KmdPtYEU03OfunXc76WGPyFeTfRtC/N\nu89Tqpy/+TEGWyLZVmv0uejP8yVV493n6ajGTqhvWuB3e1BLY7wvzn61nTEksMh6wa3u8JwX3CZi\n4/CBq9RTKs0mtZ2xV7ye1smTFDRqVK1l29hth/aaOmy9HtrYY4f2WjroiKbqOqVSlLpOVXtteZIu\nWgx0ruo7eUHS9r+qvRIsOSe++3vz7osowrsUm0UrD4/1Wr0c1lRfq77WvPuqPFUjOnct+3XSm679\nQqOlq9ay//k/8hiky/rM2I6vzkP6f4MS7P3KYjtYapCFhtmjjQ16fCW8+4ubwjzG/xtd3FP1/1lS\ntZ/6ysToanOwwX/CXJcHXXI5QZdhvkGWaeawBHuUBt0zaTY6qKVWDqjljKOayJGio+3mGWm02T5w\nlf5WWGiYGGXqOSlHiqEWy3SJUnV1sMNLvm2oxU6rY7zpFhmqsWPKxFinl9rO6GWtGcbZroNe1vmj\n74q31zKDtHRAri7OqinNRksMlq27/lbaroMZxqkUZYxZVupvomkWGq5AJ4kKnAxGHC43UHfZsqSb\n43IZMs1xuXh7nVbbMgPVcVqUSvWUutKHlhvoHk/J0ttJ9V1qvjZ2G2i5MjE26GGkufaKt1GaFJtt\nlmKAFd4zVqE4zRS5zhummai5Ig2VBCN8U7W1yyapBltqqMUKdAoD5+42EGwo1nPSHgna26GxY7rY\noomjtuhqiMX2i9PHakMtDjagswMPhT943xhX+sgWXcUq9pZr9bdSlnR9rVIozhrpCsXZrKs29jir\npqEWa+KoIs3d7WmF4tR30ir9HNNIHafl6qKVQpWiNHJMW7u94TotHdBAiVjHrdNLd9mWGqxEQ7mS\ntXBQfSfFKVQYbIZn6R0snKp8u45pLCqod9utrRhlhlhig+7KgoqMGlhkqHh7jTFLK4V2amezrkaY\n7w3XaW+n7ToYbIm9EkSp0MxhC4xQz0nzgkqzy81xQEsNlFgj3YjAU/Ma79qtrRINbZJmnstkyjDO\nDE0cFadQmRgjLBClUi/rRKmUKkeqHPWd8Lzb5Es0y9UGWaqD7crEWK2P2z3nHZO0cEicQs0VKRar\nUJzBljqhviaOqu20Fg7ZKM0wC5Wq62rvOaqJQnEmmipKpZ3aGeVD811qr3hHNA02Oa52Sl0H5Hyt\nAjMu5F1H2z3ph5YaZJJ3pMrR2Vb7xbnJq5o5rLX9WjpovZ7SbLRNR5NM1UmBlfprb4dYx80yxkTT\nvGesSd7R0gFbJTuuoV3aVeNdP6su4N1O7bzkFi0cNNfIarzbrY3BlnrKPSHvBlhejXcvucVeCZ/K\nu3FmyJEqS297xetomzX6VOPdW66txrts3a3VS6oco822W5twMXO/f7NXvANailauq836WqWTAguM\ncKdnbdFVU0dC3vWxxhN+pEhzzRS51QummWi20dra5bTacqS62nvec7XBlrrSh9V4N9ZM6/U00zVa\nOmiPBC0dMMxCnWzTXJFFhop13H5xrvWWHjZ4yj2aK/K0uw2zyFadDbRMpgzx9lbj3XjTnVXLxy4N\neXePp+yRYKR5GiqRL8l9nlAoTmPHZMg0zQTUEK3cAS0NtUhKkGhfaJiWDphuvKEWV+PdUIvCTtQ6\nTsmTFBbPnM+7dnY5qEU13o0xywbdxdsrV7J5RtorXpRKY8xSqFU13i03QCPFajqrqy1yJaun1EDL\nve0bDmt2Ud6t09PdnpYh00DLQ9695dogPZohSZ4yMQ5oGV5ntZzVwwbNFSkTI1WOA1p63m0hJ/eK\nN9psqXJC379zeRenULFYQ4PK9gR7bJKmg+1aOCRbN8MtDLsaO9gR8i7ePpukGuVDlWo4pa55Rppo\nmiiVdmn3tePd+azrLK8a6/Zoo4VDisW62SuaKwqTUev1UNtp5WLUd0JTRxzRVFNHtFKoqcOaOhwk\nsXboYLutklWItl1HQy02zcSw4GirZNeYaZd2rvCRuk55zh1aKbRdBx+71AArzHGFZQbJkOkp9wTW\nApfrJttmXVWKkmaTaSb4yJVS5MjVxTIDJduqjlMKtZJsqzdcZ5/4wC+9vsaOedF3XG6uIs1MM9Fw\nC6tVgQ621E7t3W6KP/ieosAb5l5P6hv4iZ6rHjb4d//HDz2pSDOr9VHfCY0d1cEOr7pRoVbKx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Iu+06auSYOIVW66Ov1Z53mz5WW2CEExrIlOHnHhGl0iUy7RfnWXfqY03IuzxJ4uwXb59V+umk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OWxmtY9JCr2tmGa2KGOfcYYr1AL44zF0Xk31jiPurbawuUGbcOiwW4NwrMp6rfZ\nsvzNdzWy66i8G2SWs7yuWGKo+Rf9LRhihnjl9qgvTb7hptmiZejPUd9MVKyusmqB3TTDzTJIhTg1\nHXS9hy3X1V99z7UePYJ3kcXmA34YMqmjXegvOd9Y44w2QbYsQ003xni7NHKaqR5zjZa2+J6/hkWL\nqry73V2KJMmW5RTvhvsfnWvEu+/5q4V6e87F1XgXaZyxgXe3+sMRE8l71XNQTX9wK/6XdzMNlqTI\ns76tSJIs2Z/Iu6Gmh8WPqN7meu2q8e4GD6rxNaix8WWoRILLPe0fLvW0y4P7wzletVJn6fI86lq7\nNdDPvGALd4mJ4pUHq8xExcYaZ5FexhujlgMG+iBkGz7jMhXiwmfecnq144juTVVFE7WRGipVLNFv\n/dxoEzzvIt/3FwVSPOdiw7ytk1WW6xo2elA5sXi7u+xTx11ur/b98CN/ViRJgpIjLJYix45/uFRd\nZebr69uejdVnbukGD6oZqzf3P/7DWOM0sNtsJ4tToZ95YUEmTb5XnSPZVmd53W/9XH17DDLLVKf5\nmbs96UoXe849bnGHO73nJNMNdVBN5eL907fs1sAv/EaW7GA/d5+bDDYznFO0cPl7P1UuXkOlrva4\nyUa62HOhvusY42XLMtY4f/F93/cXj7vab/08WKtHKpYoQYkSCRbppa0NrvSkIkmSFFmlU3jeIfTR\nqPxDxLuqutrj1f79SZMQ44ytVhcX4ftTrbVHfWt0CJOs0YJjtKiIcL8itbHRr/1KlmwH1HJIDTs0\n8a5TjDLJXvU86Uo/c3e4l30sMNw0T7gq2O1XiFPLAQ2VGmO8ddrboK0eltiipSV6uMTEagv5iYq9\n6QxDTT9iAS6a7EbYHEpljd/ZTlYgxQ5NPOnKwLudGlfjXbzy8Bw5wYeW6+oZlwXePeOyYLG6WwP3\nuckNHvxSMpO+DiqRoFRDCUpCbEelk0hDpdLke87Ftmlerb2e6Q1vODPcg6hfJCkK753tNW8409ZY\nnfKPUxTbHY+OtqB6NB0+tjoeHW77GWVX/dX3XOw5p3on9HcqY7skRWo45EIvuMvtYXI3qkUdqWps\nd65XdLYylFqY7WTFEhVIMVf/YIW5QB8jTT5mbPe2YaEvRbHdWOM0VBpiuwQl1eKtqU4LdZC/SFVt\nGwPMOcLt6Xg1zljFEj/BrvjjdTxtrCp7o3vcxsZq79/rZieb7U1nhA3HY43zbc9CYB/VM/O+CJVI\nUNNBj7juY2M7GGym7Zp5wlVudq8iSRIVW6VTmGeKWPdNje34ZN7N19d67QLvfuXX+F/efVELqp+F\nd59Wn4d3x6PItSlBiQZ2V9uQMcmoI2KXccY61TsSFR+Td1XHsnMMsFhP53n5qLzbKlkTO/zInzWw\n23bNAu9a2xT67Je1oHq4It41sstJ3vu3492/u+rbY4/6qLRor8q7Q2po6qOj8u6LyPD+d1UUp3+Z\nOtpY9ovSV8W6b6rO8npwXToeRes7qBZLfh4dbSx7vDp8g/DXVVXHsl8n1fz//gWVpbOzs6WLs1lr\n58bqLVxqoiTFDqnpwtjOxXr2+pbnPeUKw00z2UgzDFHXPgv0cb2H7VPXBm0t0128/SrEKZGgRIKW\nCrVQ6ExTvOJcM5wiXnnMju/voZbXah21tMUWLV1qoilGqBCnrjLvOtUmre0Xr48FWihU00ETXSJd\nngpxWihU3x6NFYmL1f/crLV45eZJ85bTXe9hg830gB9ZqYt6yqzQRR37FGqhu6USFSuQYq1UQ8ww\n18CQBdjQbpu0sUZHS5zgfC97z8l6WeRALGMxRYE69vlQT10td56XrdHRZm3s0sgBtdRQEfs7qbEs\n3URL9dDZSu87SRub1HRQJ6sUSzTJt7S1QQO7rZNipyZW66imQ4o1dkAt7a33kaZaKtTKFts0d6mJ\n9qmrozVedr7OVlkrVVfLLdDXAHO8bZh0eS7wsvXaecJVTvSBpU7Q02J5MtS1zyatHVRTV8tNc5qO\nVnvEdd4xTBzW6uAMb/mTH9urvg8M1NcCLW1RIFWBVG8400eaG+gDB9VSJElnK3W02jBvG2S2QWbL\n198eDeQb4CXne9epulquh6VqqLBVC42UquWgUSZ50QVecKHb3O0jzZxstoX6qG2/JEWa2WGFLm6O\n7eJqaocH/FBezMnKaU8AACAASURBVHK4pUJdrPCEq51mmpW62KyVferoaI1iiZrbJkmxVGs1jN2H\ntVJd6UlxKjMukhR73Bhp5plhKLHr0sgum7U21WlyZWisSF37fGCgWg5KUGKnxrZpbrGezvWqePut\n195BtQzynua2KdXISd6XLs9KXVzuGfe5SZzK3ZHlsf5RqIV6ygwxwwG17VdbQayO71bJulvqHaca\naI6GSrW3Xnvrg0XcWgXfqGL3HB/v2lsXdkpX5V2hFq40wSCz5cqwTHcn+sA67cWpzK48oHbgXY5M\nM5wiToW1Uv3IA0aYooYK7zrFbg1MdInb/K4a7942zApd1HYg8G6Njt5yuos95y1n6GOBTlb50AlO\nNEdt+23Sxk5NzDLEQTVd7XF9LJSvv5W6OKiWAik6W2mFri4xUZl6IYu2oVItFHrd2ZrYYbvmiKvG\nu7rKNFIqIWYtGfGuQIpUa53nZR9ppqaDtsT6UImEYKkY8W6q03S20kSXus6jytQLvHvetxxSQwO7\ntVBosV6edoV4+xVr7BTv2hmzq4t4XZV33S0z2YUOiFeqoa6We9Yl+psbeHepieLwoB8elXfR+Vxk\nkmlOUyHOc/7DO4ZZqodSDQPvDqlhm+TAu6lON9lIMw2xUlcH1VSopQKpelksQ54MeQaZravlsYn0\nVO8Z5DkXy5Ohq+U6W62TVZrYaaM2ajnofC8flXfxsYXeJEU2aW23hoF3g8yOZULv1FKhtVJ1stqf\n/ViG3MC7qU4Pm3Ka2+ZCk8WpHNit0NVaqb7j74aY6XRT7VO3Gu9q22+Z7lKsC7ybYYhmPjLbINs1\nq8a7d51qhiEG+kC8/TZoJ8EuYzwuDg3scYIPZcR4d6HJsRqWnRAXc1OIq8a7POlOMd0TrjLQB2Yb\n5GTvme3kwLs6yvWwROE3lHcR6/7pYt/zN3EqXOR5zW0zzXA/8oADaolXrp31ZhjiTG96xmXeNkwd\n5T4w0I3GBdYtidnsHVLDXvV1sTLYy3ey2kSXWKNjOIarPCFTjrrKUGkHvFYHqdbKk26fugq1tF1z\nL7hQT4u1t94OTazVwVqp6ilTqqGN2jiglkV6qW2/xoo87QpdLbdXfQ3sCX1qh6a2xnasvm2Y2QY5\nwRL/4Tn71NFSoU3aqKFCXwvsU0dNh7S1wV71wgaLzlapocI7hoUNaB2tVi5eOxtsk+wSE73ubN/3\niFINtbXBSp2lKrBED2Jx6UyDXWmCv7lWR6t9pJk6sYm19drbqI0WCq3WURyedJUDamtvnas8qbtl\nZhnsAi9ZqocCKYabZqjpTvKeuQZYo4MlTjDWOHkybNHK+V42Tz8Z8rS0Rd1YXHq210GRxsFVY5BZ\nRsmxXXNPuMoOTU02Urk6NmntZLOt0llDpWFh7pCaytSNXfnKVxwh3ivV6Agruzzp4eePGxN+r0zd\nI9rxCZbYqI1usZgzWmC92uOW6a6rFebqr0INcE4sW5PKTZutbVbTIbUdkKjYq85xtte97mzzpFmk\nl1/6jRmGusREg8y2Tko4vkQlbnGPVgqNMinw7ixveNswB9SyQTvNbLdUdwVSfKSZIkkmulQtBw0w\nx3bNY8+T/50UXa2TktgGth94OGaH394wb+tlsT3qq+WAHZraJlmybbFsskreNbVDL4vMNUCybSa6\nxBAz5BpuiJn2aGCoGerbY7WOhnlHoZZSrf3G8m6tDq7zCP43tpsnzXUecUBtFWq41ESPuSaUionq\n4VG5YWGQ2crUs0z38P4ivbSzXqGWxzyGW91jhCnqfkKdyqqaabBVOku19rjOt64yGfJCbHdIzU/8\nnWgcHqmOclRmXUWLunWVKdQixHYH1dTURzZprYVC53lZWxtjtZBPtFc9zW031WlHxHa9LDZfXz/0\noNed7TqPhLHsQTW1t85HmtqpyVFjuyFmHBHb5UnX3TLvGGaXBG85PcR2xGlvXRhTHk15R7GjPx6V\nqWuNjsfkXYFUqQqUami/2mYa8jGs+3wTwDcfR0ZSnnSTXehks812snrKNLRbnnSpCuRJt1w3V3pS\nhjzQwVr3uNWImGPCXP2t0kmqtaHtfFrF2x+L2aqrsZ1uc7cN2km11matjxnbRVb6dZRboauzveYD\nJ+puqdlOdrL3NFRqtU6Bdd/E2I6P513lWPYFB9SWHptTWa+desq841RTD9v09ln1WXj3WfVZeNfE\nzmq1zD+taqi0EoychRopPWKTxlSnKxevWNIxeXe6qWEsG7kuHYt3NWNuHKtimatbtXCpiVbrqIkd\nlumm5Weo1fl5eVeuzr8l7z6Ndmso/jg59ml1LN59WlV1zUpVEHi3UxNJis00+Ki8+6bGdqq0454W\n23bUzW1f3oLq4WPZL1MR6w4fy36Souf2/1VVHct+Vh0+ll2pq10aBaZVrssckifdDk0t1/VTj2WP\nVyd6X4NY8tfXXVXHsl+98o7Kuxpf/YFUKrInq+FQsKN9zdmmOs3v/VQbG+VJ9we3qGOfB90Qdopn\nyLVKJ9my9DMv1DAb6l0lEqTJl6JAsq3B5vQqT7jBA/Kl+ZVf+4vr5MowxQhN7JCkSIZcv/dTV3lC\nvjTPudj5XjLAHBu10c88GXJDfZUEJc70hhGm2KeO+va4z40GmeUGD2ppi+94TJZsz7jME65yTezf\ncwzQ3VJ50vUzL0z4pcsLg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HGn1A18u37yxKgUr1gn24Jqnlb2aqrcZl0d0tQBza2Xcs4e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350QFDJ9rom0yg2SGEqnBZ1chXolUGVeIC/yfrhz5FhhntDyHtQNdlCrQ22tuUyJVkv0K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70A/c6a8+5w3UdHSFZ4rn6meYpY5oWot3NZ2z3TV0QiPHLDDaFeboIc+j7nOdFw2x3AY9a/Gu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7L12lWcp2bilGpvnQyZfuYeDewNzrm3naWVLc6v7O/ZxE67NZIszzrt7dSksgfYZFNdYozJ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Vk2C/Kcb7L/9utJnaydXZJm+4Q6527vWSSSYabp5f+Kkf+bUJJmsn1//r/3GPl3W0xQST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\nikWaYUJwjdJCQzOmSDPdxNA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Jj3oiiF/X6uND4wyx1BkRqOwQS5IlVbpohVKlS5WuRB1p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jkdFPl90Zj9R1JUzifSKEOD/9zSilK+bFm8m+gsXc3xrJu/lncJdoUa9jN1V9s2O9Q86dS/31Qr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\nLSrwrrwv28xGVRwOfuTq2Gi2T6ODqp2Qd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NdC3UJlMh87oQdUR1kr8x+736Xe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\nuCrWae1eL9ilvt/5up7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2UwMDTNfJ8nJ9rf+S5ujl0/NMLkX93pmKervzKfqsRL3d3V7y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\n2m7wtpvUc1Kcwx7wfNDbq73ttmsvVZ5d2mhjFwQLRan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21oxxTJkYCwy1Tk/t7Qi03a2m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mvgEMontoMt0MsKy6UqCyUJjqttt5aW6esrXtDeFs94wAKDrdbdh0ZZUCF5OsQ8q/TQRL4M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ZJm2c7ROtbHG/+zS1U0N5hptskJkOqW24ydKsDn22dmrqEm+poUQthyUoNNlw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\n/yqctvyvEEIIIYQQQgghhBBCCCGEEEL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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ad_block_size = [5, 10, 20, 50, 100, 250]\n", + "num_cols = 6\n", + "num_rows = 3\n", + "#num_rows = num_vols\n", + "\n", + "ad_test = []\n", + "plt.figure(figsize = (((5.5*num_cols),(6*num_rows))))\n", + "for x in range(len(corrected_src_data)):\n", + " for y in range(len(ad_block_size)):\n", + " tmp_binary = threshops.thresh_adapt(corrected_src_data[x], ad_block_size[y])\n", + " ad_test.append(tmp_binary)\n", + " if y == 0:\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+1))\n", + " plt.imshow(corrected_src_data[x][:,250,:], cmap=plt.cm.gray)\n", + " plt.title(\"Original Data\")\n", + " plt.subplot(((num_rows * 10 + num_cols) * 10 + num_cols*x+y+1))\n", + " plt.imshow(ad_test[y][:,250,:])\n", + " plt.title(\"Adaptive threshold: Block size = \" + str(ad_block_size[y]))\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 5: Isolate pore space" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: mathops.py" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import mathops\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pore_space = []\n", + "\n", + "for x in range(len(solid_matrix)):\n", + " tmp_pore = np.logical_not(solid_matrix[x])\n", + " pore_space.append(tmp_pore)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 6: Generate exterior mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Module: synth_drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import synth_drawing" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "exterior_mask=synth_drawing.draw_cylinder(corrected_src_data[0], None, 325, None, None, 'YES')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Masked volume demonstration" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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7fT7FEQg8Smz8/mR9jkGWTBEwLEZ1ufoaRPeICw6y+cB03iulHwyAwM+i8Etk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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_demo=synth_drawing.draw_cylinder(corrected_src_data[0], \n", + " radius=325, \n", + " value = 2000, \n", + " draw_exterior='YES', \n", + " apply_mask='yes')\n", + "\n", + "plt.imshow(mask_demo[50,:,:])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Isolated phase presentation:" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Glass beads: solid_matrix[0]\n", + "#Pore space: pore_space[0]\n", + "#exterior: exterior_mask\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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Lfxwd4z/kDMf6UuE9MtlNXXrxgWN9Psr/UUwK22lg+ZzD2MoFvO6JRUf8Tgo0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\n5LUf3MATpiMody1Pm44ghG12twzxgye4wXQE5Z7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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize = (15,4.5))\n", + "plt.subplot(131)\n", + "plt.imshow(solid_matrix[0][50,:,:])\n", + "plt.subplot(132)\n", + "plt.imshow(pore_space[0][50,:,:])\n", + "plt.subplot(133)\n", + "plt.imshow(exterior_mask[50,:,:])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 7: Merge materials and label" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import filterops as fltr\n", + "import morphology as morph\n", + "import scipy.ndimage.measurements as measure\n", + "import mathops\n", + "\n", + "def logical_sub(src_data1, \n", + " src_data2):\n", + " temp = np.logical_not(np.logical_and(src_data1, \n", + " src_data2))\n", + " output = np.logical_and(src_data1, \n", + " temp)\n", + " return output\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "only length-1 arrays can be converted to Python scalars", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;31m#Merge volume:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mlabel_field\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexterior_mask\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mpore_space_corrected\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mglass_bead_corrected\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m: only length-1 arrays can be converted to Python scalars" + ] + } + ], + "source": [ + "#rough quantification\n", + "labels_rough = (exterior_mask) + (pore_space[0]) + (solid_matrix[0]*3)\n", + "glass_bead_corrected = 3*(logical_sub(solid_matrix[0], exterior_mask))\n", + "pore_space_corrected = 2*(logical_sub(pore_space[0], exterior_mask))\n", + "\n", + "#Merge volume:\n", + "label_field = (exterior_mask + 2*pore_space_corrected + 3*glass_bead_corrected)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "label_field_int = label_field.astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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4Uqxfv14UP3KdDOQD34w7KeLq6ooFCxbQDsMkjTXi5ZMhalQMFi5ciLy8POTm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\ny9Ofn5+fDw8PD4HCF5fk5GQ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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(label_field_int[50,:,:], cmap=plt.cm.gray)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Phase_0 Measured Volume\n", + "0.0 voxels\n", + "Phase_1 Measured Volume\n", + "79359800.0 voxels\n", + "Phase_2 Measured Volume\n", + "0.0 voxels\n", + "Phase_3 Measured Volume\n", + "0.0 voxels\n", + "Phase_4 Measured Volume\n", + "64278651.0 voxels\n", + "Phase_5 Measured Volume\n", + "0.0 voxels\n", + "Phase_6 Measured Volume\n", + "0.0 voxels\n", + "Phase_7 Measured Volume\n", + "0.0 voxels\n", + "Phase_8 Measured Volume\n", + "0.0 voxels\n", + "{'Material_8': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_8'}, 'Material_0': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_0'}, 'Material_1': {'volume': {'units': 'voxels', 'value': 79359800.0}, 'name': 'Phase_1'}, 'Material_2': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_2'}, 'Material_3': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_3'}, 'Material_4': {'volume': {'units': 'voxels', 'value': 64278651.0}, 'name': 'Phase_4'}, 'Material_5': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_5'}, 'Material_6': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_6'}, 'Material_7': {'volume': {'units': 'voxels', 'value': 0.0}, 'name': 'Phase_7'}}\n", + "[('Phase_8', 0.0, 'voxels') ('Phase_0', 0.0, 'voxels')\n", + " ('Phase_1', 79359800.0, 'voxels') ('Phase_2', 0.0, 'voxels')\n", + " ('Phase_3', 0.0, 'voxels') ('Phase_4', 64278651.0, 'voxels')\n", + " ('Phase_5', 0.0, 'voxels') ('Phase_6', 0.0, 'voxels')\n", + " ('Phase_7', 0.0, 'voxels')]\n" + ] + } + ], + "source": [ + "import imgQuant\n", + "\n", + "measures, vol_rec = imgQuant.Q_VOL(label_field_int)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measured bead volume (um^3): 55110908401.1\n", + "Measured pore space (um^3): 68041108525.0\n", + "Measured column section porosity is: 0.55249690767\n" + ] + } + ], + "source": [ + "\n", + "bead_vol = measures['Material_4']['volume']['value']\n", + "pore_sp_vol = measures['Material_1']['volume']['value']\n", + "\n", + "bead_vol_corrected = float(bead_vol) * 9.5**3\n", + "pore_sp_vol_corrected = float(pore_sp_vol) * 9.5**3\n", + "print \"Measured bead volume (um^3): \" + str(bead_vol_corrected)\n", + "print \"Measured pore space (um^3): \" + str(pore_sp_vol_corrected)\n", + "porosity = pore_sp_vol/(bead_vol+pore_sp_vol)\n", + "print \"Measured column section porosity is: \" + str(porosity)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5427\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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MHj1a6rKTJ0/Gx48fUatWLSVKJD1Vq1bFb7/9pmoxCAQCQa0gSpoUKCoPjKZy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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Volume confirmation:\n", + "total_vol = bead_vol_corrected" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "https://gist.github.com/705ac9a654390e188313\r\n" + ] + } + ], + "source": [ + "!gist ipTools_DryScan_SegDemo.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/end-to-end/shale_seg_demo.ipynb b/demos/tomography/end-to-end/shale_seg_demo.ipynb new file mode 100644 index 00000000..a97f41f4 --- /dev/null +++ b/demos/tomography/end-to-end/shale_seg_demo.ipynb @@ -0,0 +1,364 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Vistrails Segmentation Demo" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/skimage/filter/__init__.py:6: skimage_deprecation: The `skimage.filter` module has been renamed to `skimage.filters`. This placeholder module will be removed in v0.13.\n", + " warn(skimage_deprecation('The `skimage.filter` module has been renamed '\n" + ] + } + ], + "source": [ + "import skxray\n", + "import numpy as np\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "#import tifffile\n", + "from vttools.to_wrap.image import (histogram, filtering, math, logic, morphology, registration, thresholding, transformation)\n", + "import xray_vision as xvis\n", + "from skxray.io.tiff_io import read_tiff, save_tiff" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "file_path = \"/home/giltis/dev/my_src/Demos/demos/tomography/data/uCT/\"\n", + "src_fname = \"NSLS_shale_smpl-1_AbvFe.tiff\"\n", + "src_file_path = file_path+src_fname\n", + "#demo_vol = skxray.io.tiff_io.read_tiff(src_file_path)\n", + "demo_vol = read_tiff(src_file_path)\n", + "demo_vol_crop = demo_vol[:730,200:799,200:799]" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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J53I5q+ID3tFfAAKr2+1arAUPgRAEzgFofvfuXWPRKbDxfV8XFxcaj8e2SfCA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BCsssiHSG6YnlzC7/j42IIBagf3yO23YJOhXYPMKFmw3XIkeiqVUrFYNIQEYsHLkc1mLTBSI9dq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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "slice_select = 350\n", + "plt.imshow(demo_vol_crop[slice_select,:,:], cmap=plt.cm.gray)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Apply Median Filter" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_filter_crop = filtering.median_filter(demo_vol_crop, size=[5,5,5])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_seg_crop = thresholding.thresh_globalGT(vol_filter_crop, 10000).astype(np.int32)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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Xc6/k6Uq0WRGPf1YKRwWUlb7wZmau8VFg3g5+eHiYg4OD4iDZkUk/uc6y53ke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\n1qamaf5+kplOp/Pmw7Y87jqI+ftip9O50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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(vol_seg_crop[slice_select,:,:], cmap=plt.cm.gray)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "dtype('int32')" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol_seg_crop.dtype" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Morphological Closing: Remove noise" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_close_crop = morphology.binary_opening(vol_seg_crop, iterations=5).astype(np.int8)*254" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "254" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol_close_crop.dtype\n", + "np.amax(vol_close_crop)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(vol_close_crop[slice_select,:,:], cmap=plt.cm.gray)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "src_vol_crop_fname = \"032_Shale-E701_AbvFe_gScale_crop.tif\"\n", + "med_fltr_fname = \"032_Shale-E701_AbvFe_mFilter_gScale_crop.tif\"\n", + "seg_vol_fname = \"032_Shale-E701_AbvFe_seg_binary_crop.tif\"\n", + "morph_open_fname = \"032_Shale-E701_AbvFe_seg_binary_open_crop.tif\"\n", + "data_sets = [demo_vol_crop, vol_filter_crop, vol_seg_crop, vol_close_crop]\n", + "data_paths = [src_vol_crop_fname, med_fltr_fname, seg_vol_fname, morph_open_fname]\n", + "for _ in range(len(data_sets)):\n", + " src_file_path = file_path+data_paths[_]\n", + " skxray.io.tiff_io.save_tiff(src_file_path, data_sets[_])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_close_crop.dtype\n", + "vol_close_crop.shape\n", + "#skxray.io.tiff_io.save_tiff(morph_open_fname, vol_close)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_close_crop.dtype\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.mplot3d.art3d import Poly3DCollection\n", + "\n", + "from skimage import measure\n", + "from skimage.draw import ellipsoid\n", + "\n", + "# Generate a level set about zero of two identical ellipsoids in 3D\n", + "ellip_base = ellipsoid(6, 10, 16, levelset=True)\n", + "ellip_double = np.concatenate((ellip_base[:-1, ...],\n", + " ellip_base[2:, ...]), axis=0)\n", + "\n", + "# Use marching cubes to obtain the surface mesh of these ellipsoids\n", + "verts, faces = measure.marching_cubes(ellip_double, 0)\n", + "\n", + "# Display resulting triangular mesh using Matplotlib. This can also be done\n", + "# with mayavi (see skimage.measure.marching_cubes docstring).\n", + "fig = plt.figure(figsize=(10, 12))\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "\n", + "# Fancy indexing: `verts[faces]` to generate a collection of triangles\n", + "mesh = Poly3DCollection(verts[faces])\n", + "ax.add_collection3d(mesh)\n", + "\n", + "ax.set_xlabel(\"x-axis: a = 6 per ellipsoid\")\n", + "ax.set_ylabel(\"y-axis: b = 10\")\n", + "ax.set_zlabel(\"z-axis: c = 16\")\n", + "\n", + "ax.set_xlim(0, 24) # a = 6 (times two for 2nd ellipsoid)\n", + "ax.set_ylim(0, 20) # b = 10\n", + "ax.set_zlim(0, 32) # c = 16\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/file_io/tomo_file_IO.ipynb b/demos/tomography/file_io/tomo_file_IO.ipynb new file mode 100644 index 00000000..a6b7f47d --- /dev/null +++ b/demos/tomography/file_io/tomo_file_IO.ipynb @@ -0,0 +1,103 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# File I/O Examples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Volumetric image data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Key areas of application" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. X-ray tomorgraphy (micro, nano, fluorescence, etc.) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Typical/traditional file types" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. Camera files/\"raw\" data\n", + " - .SPE -- A type of direct output from acquisition cameras\n", + " - .tif/.tiff -- Raw data exported, save, or converted to TIFF for storage before analysis\n", + " \n", + "2. Reconstructed data\n", + " 1. Single/Consolidated (read volumetric) data\n", + " - .netCDF\n", + " - .h5/.hdf5\n", + " - .tif/tiff\n", + " - .am -- AmiraMesh files (e.g. from Avizo)\n", + " 2. Stacks or series of individual images/slices\n", + " - .bmp\n", + " - .jpg\n", + " - .tif/.tiff" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Camera file I/O" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Key packages and tools" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/reconstruction/download_data.py b/demos/tomography/reconstruction/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/reconstruction/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/registration/download_data.py b/demos/tomography/registration/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/registration/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/transformation/crop_volume.ipynb b/demos/tomography/transformation/crop_volume.ipynb new file mode 100644 index 00000000..e49723a0 --- /dev/null +++ b/demos/tomography/transformation/crop_volume.ipynb @@ -0,0 +1,132 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import skxray\n", + "import numpy as np\n", + "import pims" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Warning: These original files are 4 gigs each. Download will take FOREVER" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### @giltis: Write download_data.py which will fetch the source data from dropbox. Then this example continues under the assumption that the data is held locally." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "path_to_data = \"/home/giltis/dev/my_src/Demos/demos/tomography/end-to-end/\"\n", + "fname_abv = \"NSLS_shale_smpl-2_AbvFe.tiff\"\n", + "fname_blw = \"NSLS_shale_smpl-2_BlwFe.tiff\"" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vol_abv = pims.TiffStack(path_to_data+fname_abv)\n", + "vol_blw = pims.TiffStack(path_to_data+fname_blw)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "Frame([[0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]], dtype=int16)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol_abv[500]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "vol_abv = tifffile.imread(path_to_data + fname_abv)\n", + "vol_blw = tifffile.imread(path_to_data + fname_blw)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/transformation/download_data.py b/demos/tomography/transformation/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/transformation/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/vis_3D/Untitled.ipynb b/demos/tomography/vis_3D/Untitled.ipynb new file mode 100644 index 00000000..286dcb3d --- /dev/null +++ b/demos/tomography/vis_3D/Untitled.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/Untitled1.ipynb b/demos/tomography/vis_3D/Untitled1.ipynb new file mode 100644 index 00000000..0d3bf9c5 --- /dev/null +++ b/demos/tomography/vis_3D/Untitled1.ipynb @@ -0,0 +1,47 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import vtk" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from vtk." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/download_data.py b/demos/tomography/vis_3D/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/vis_3D/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/vis_3D/pyqt_vol_viewer-biofilm_demo.ipynb b/demos/tomography/vis_3D/pyqt_vol_viewer-biofilm_demo.ipynb new file mode 100644 index 00000000..78f33e8c --- /dev/null +++ b/demos/tomography/vis_3D/pyqt_vol_viewer-biofilm_demo.ipynb @@ -0,0 +1,546 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#mport vtk\n", + "import numpy as np\n", + "#from skxray.io import vtk_tools, tiff_io\n", + "from skxray.io import tiff_io\n", + "import pims\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from pyqtgraph.Qt import QtCore, QtGui\n", + "import pyqtgraph.opengl as gl" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Demo Data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The three initial data sets included in this example consist of a cropped region of a packed bead column (porous medium) within which biofilm was grown as part of an experiment examining the affect of fluid flow rate (hydraulic loading) on biofilm growth and development." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Segmented data file names\n", + "fnames = ['../data/mCT/demoThresh_Beads1.tif', '../data/mCT/demoThresh_Biofilm1.tif', '../data/mCT/demoThresh_Barium1.tif', '../data/mCT/LabelField.tif']\n", + "\n", + "for index, val in enumerate(['beads', 'biofilm', 'barium', 'label_field']):\n", + " #globals()[val] = pims.TiffStack(fnames[index])\n", + " globals()[val] = tiff_io.read_tiff(fnames[index])\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "255\n", + "85\n", + "[ 85 170 255]\n" + ] + }, + { + "data": { + "text/plain": [ + "(100, 425, 425)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print np.amax(label_field)\n", + "print np.amin(label_field)\n", + "print np.unique(label_field)\n", + "label_field.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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DAwn1LWtZYVM/6GNQUmDQp3YSE9jTe+pb7DAvOdDrtvZNiX0R2aDKG4OJOpiq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\nqZHTkSOFktCziq6aH7rzKGAyYwFbfIKCp3oW0UALtqnbjn1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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "beads[50]\n", + "#label_field[50]\n", + "plt.imshow(beads[50,:,:])\n", + "np.amax(beads)\n", + "np.amin(beads)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "app = QtGui.QApplication([])\n", + "w = gl.GLViewWidget()\n", + "w.opts['distance'] = 200\n", + "w.show()\n", + "w.setWindowTitle('pyqtgraph example: GLVolumeItem')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "g = gl.GLGridItem()\n", + "g.scale(1, 1, 1)\n", + "w.addItem(g)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "## Hydrogen electron probability density\n", + "def psi(i, j, k, offset=(50,50,100)):\n", + " x = i-offset[0]\n", + " y = j-offset[1]\n", + " z = k-offset[2]\n", + " th = np.arctan2(z, (x**2+y**2)**0.5)\n", + " phi = np.arctan2(y, x)\n", + " r = (x**2 + y**2 + z **2)**0.5\n", + " a0 = 2\n", + " #ps = (1./81.) * (2./np.pi)**0.5 * (1./a0)**(3/2) * (6 - r/a0) * (r/a0) * np.exp(-r/(3*a0)) * np.cos(th)\n", + " ps = (1./81.) * 1./(6.*np.pi)**0.5 * (1./a0)**(3/2) * (r/a0)**2 * np.exp(-r/(3*a0)) * (3 * np.cos(th)**2 - 1)\n", + " \n", + " return ps\n", + " \n", + " #return ((1./81.) * (1./np.pi)**0.5 * (1./a0)**(3/2) * (r/a0)**2 * (r/a0) * np.exp(-r/(3*a0)) * np.sin(th) * np.cos(th) * np.exp(2 * 1j * phi))**2 \n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#data = np.fromfunction(psi, (100,100,200))\n", + "#positive = np.log(np.clip(data, 0, data.max())**2)\n", + "#negative = np.log(np.clip(-data, 0, -data.min())**2)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "data = beads" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(101, 426, 426)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "d2=np.empty(data.shape+(4,), dtype=np.ubyte)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(101, 426, 426, 4)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d2.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "d2[...,0] = np.zeros(barium.shape)\n", + "d2[...,1] = barium\n", + "d2[...,2] = beads\n", + "d2[...,3] = biofilm" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "d2[:, 0, 0] = [255,0,0,100]\n", + "d2[0, :, 0] = [0,255,0,100]\n", + "d2[0, 0, :] = [0,0,255,100]" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "v = gl.GLVolumeItem(d2)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "w.addItem(v)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ax = gl.GLAxisItem()\n", + "w.addItem(ax)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " [1, 1, 1, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " ..., \n", + " [[0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " [0, 0, 0, ..., 1, 1, 1],\n", + " ..., \n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0],\n", + " [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "d2[...,2]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ValueError", + "evalue": "could not broadcast input array from shape (4) into shape (101,3)", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0md2\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m255\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mValueError\u001b[0m: could not broadcast input array from shape (4) into shape (101,3)" + ] + } + ], + "source": [ + "d2[:,0,0] = [255,0,0,100]" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'QtGui' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflags\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minteractive\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mQtCore\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'PYQT_VERSION'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mQtGui\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mQApplication\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexec_\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mNameError\u001b[0m: name 'QtGui' is not defined" + ] + } + ], + "source": [ + "\n", + "## Start Qt event loop unless running in interactive mode.\n", + "if __name__ == '__main__':\n", + " import sys\n", + " if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):\n", + " QtGui.QApplication.instance().exec_()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "## build a QApplication before building other widgets\n", + "import pyqtgraph as pg\n", + "pg.mkQApp()\n", + "\n", + "## make a widget for displaying 3D objects\n", + "import pyqtgraph.opengl as gl\n", + "view = gl.GLViewWidget()\n", + "view.show()\n", + "\n", + "## create three grids, add each to the view\n", + "xgrid = gl.GLGridItem()\n", + "ygrid = gl.GLGridItem()\n", + "zgrid = gl.GLGridItem()\n", + "view.addItem(xgrid)\n", + "view.addItem(ygrid)\n", + "view.addItem(zgrid)\n", + "\n", + "## rotate x and y grids to face the correct direction\n", + "xgrid.rotate(90, 0, 1, 0)\n", + "ygrid.rotate(90, 1, 0, 0)\n", + "\n", + "## scale each grid differently\n", + "xgrid.scale(0.2, 0.1, 0.1)\n", + "ygrid.scale(0.2, 0.1, 0.1)\n", + "zgrid.scale(0.1, 0.2, 0.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/skxray_VTK_viewer.ipynb b/demos/tomography/vis_3D/skxray_VTK_viewer.ipynb new file mode 100644 index 00000000..9dac8777 --- /dev/null +++ b/demos/tomography/vis_3D/skxray_VTK_viewer.ipynb @@ -0,0 +1,285 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools\n", + "import pims" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Demo Data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The three initial data sets included in this example consist of a cropped region of a packed bead column (porous medium) within which biofilm was grown as part of an experiment examining the affect of fluid flow rate (hydraulic loading) on biofilm growth and development." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "beads\n", + "biofilm\n", + "barium\n", + "label_field\n" + ] + } + ], + "source": [ + "# Segmented data file names\n", + "fnames = ['demoThresh_Beads1.tif', 'demoThresh_Biofilm1.tif', 'demoThresh_Barium1.tif', 'LabelField.tif']\n", + "\n", + "for index, val in enumerate(['beads', 'biofilm', 'barium', 'label_field']):\n", + " globals()[val] = fnames[index]\n", + " print val" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'demoThresh_Beads1.tif'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "beads" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_matrix = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix[0:35, 0:35, 0:35] = 50\n", + "data_matrix[25:55, 25:55, 25:55] = 100\n", + "data_matrix[45:74, 45:74, 45:74] = 150" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " ..., \n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# An example from scipy cookbook demonstrating the use of numpy arrys in vtk \n", + "\n", + "data_matrix\n", + "\n", + "dataImporter = vtk_tools.np_to_vtk(data_matrix)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# The following two functions describe how the data is stored and the dimensions of the array it is stored in. For this\n", + "# simple case, all axes are of length 75 and begins with the first element. For other data, this is probably not the case.\n", + "# I have to admit however, that I honestly dont know the difference between SetDataExtent() and SetWholeExtent() although\n", + "# VTK complains if not both are used.\n", + "dataImporter.SetDataExtent(0, 74, 0, 74, 0, 74)\n", + "dataImporter.SetWholeExtent(0, 74, 0, 74, 0, 74)\n", + " \n", + "# The following class is used to store transparencyv-values for later retrival. In our case, we want the value 0 to be\n", + "# completly opaque whereas the three different cubes are given different transperancy-values to show how it works.\n", + "alphaChannelFunc = vtk.vtkPiecewiseFunction()\n", + "alphaChannelFunc.AddPoint(0, 0.0)\n", + "alphaChannelFunc.AddPoint(50, 0.05)\n", + "alphaChannelFunc.AddPoint(100, 0.1)\n", + "alphaChannelFunc.AddPoint(150, 0.2)\n", + " \n", + "# This class stores color data and can create color tables from a few color points. For this demo, we want the three cubes\n", + "# to be of the colors red green and blue.\n", + "colorFunc = vtk.vtkColorTransferFunction()\n", + "colorFunc.AddRGBPoint(50, 1.0, 0.0, 0.0)\n", + "colorFunc.AddRGBPoint(100, 0.0, 1.0, 0.0)\n", + "colorFunc.AddRGBPoint(150, 0.0, 0.0, 1.0)\n", + " \n", + "# The preavius two classes stored properties. Because we want to apply these properties to the volume we want to render,\n", + "# we have to store them in a class that stores volume prpoperties.\n", + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(colorFunc)\n", + "volumeProperty.SetScalarOpacity(alphaChannelFunc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(dataImporter, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/skxray_VTK_viewer_demo.ipynb b/demos/tomography/vis_3D/skxray_VTK_viewer_demo.ipynb new file mode 100644 index 00000000..0afd1b49 --- /dev/null +++ b/demos/tomography/vis_3D/skxray_VTK_viewer_demo.ipynb @@ -0,0 +1,157 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "No module named image_proc", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mskxray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mio\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mvtk_tools\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mvttools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_wrap\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimage_proc\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0marithmetic\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marithmetic_expression\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mImportError\u001b[0m: No module named image_proc" + ] + } + ], + "source": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools\n", + "from vttools.to_wrap.image_proc import arithmetic, arithmetic_expression" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_matrix1 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix1[0:35, 0:35, 0:35] = 50\n", + "\n", + "data_matrix2 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix2[25:55, 25:55, 25:55] = 100\n", + "\n", + "data_matrix3 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix3[45:74, 45:74, 45:74] = 150" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Arithmetic example #1\n", + "merge_demo1 = arithmetic('addition', data_matrix1, data_matrix2)\n", + "\n", + "merge_demo1 = arithmetic('addition', merge_demo1, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Arithmetic example 2\n", + "merge_demo2 = arithmetic_expression('A*B+C', data_matrix1, data_matrix2, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Data Conversion from numpy to VTK object\n", + "\n", + "vtkDemo_cube1 = vtk_tools.np_to_vtk(data_matrix2)\n", + "\n", + "vtkDemo_merge1 = vtk_tools.np_to_vtk(merge_demo1)\n", + "\n", + "vtkDemo_merge2 = vtk_tools.np_to_vtk(merge_demo2)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_cube1)\n", + "vtk_tools.vtk_viewer(vtkDemo_cube1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge1)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge2)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge2, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1-Copy1.ipynb b/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1-Copy1.ipynb new file mode 100644 index 00000000..5af6f00b --- /dev/null +++ b/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1-Copy1.ipynb @@ -0,0 +1,919 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools, tiff_io\n", + "import pims\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from vtk.numpy_interface import dataset_adapter as dsa\n", + "\n", + "from vtk.numpy_interface import algorithms as algs \n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "_prism_data = {\n", + " 'red': lambda x: 0.75 * np.sin((x * 20.9 + 0.25) * np.pi) + 0.67,\n", + " 'green': lambda x: 0.75 * np.sin((x * 20.9 - 0.25) * np.pi) + 0.33,\n", + " 'blue': lambda x: -1.1 * np.sin((x * 20.9) * np.pi),\n", + "}\n", + "datad = {'prism': _prism_data}\n", + "\n", + "cm_label = ((0.0, 255.0, 0.0), # 1 -- Lime Green\n", + " (255.0, 223.0, 0.0), # 2 -- Golden yellow\n", + " (135.0, 206.0, 250.0), # 3 -- Sky Blue\n", + " (220.0, 20.0, 60.0), # 4 -- Crimson\n", + " (0.0, 128.0, 0.0), # 5 -- Green\n", + " (255.0, 140.0, 0.0), # 6 -- Dark Orange\n", + " (0.0, 0.0, 255.0), # 7 -- Blue\n", + " (138.0, 43.0, 226.0), # 8 -- Blue Violet\n", + " (46.0, 139.0, 87.0), # 9 -- Sea Green\n", + " (128.0, 0.0, 0.0), # 10 -- Maroon\n", + " (0.0, 128.0, 128.0), # 11 -- Teal\n", + " (160.0, 82.0, 45.0), # 12 -- Sienna \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "val = 0\n", + "red1.20033008589\n", + "green-0.20033008589\n", + "blue-0.0\n", + "val = 1\n", + "red0.329507125195\n", + "green0.998254893141\n", + "blue-0.339918693812\n", + "val = 2\n", + "red0.78732584878\n", + "green-0.410766255446\n", + "blue0.646563777522\n", + "val = 3\n", + "red0.78732584878\n", + "green1.07076625545\n", + "blue-0.889918693812\n", + "val = 4\n", + "red0.329507125195\n", + "green-0.338254893141\n", + "blue1.04616216792\n", + "val = 5\n", + "red1.20033008589\n", + "green0.86033008589\n", + "blue-1.1\n" + ] + } + ], + "source": [ + "val=[0, 1, 2, 3, 4, 5]\n", + "for label_val in val:\n", + " print 'val = ' + str(label_val)\n", + " print 'red' + str(_prism_data['red'](label_val))\n", + " print 'green' + str(_prism_data['green'](label_val))\n", + " print 'blue' + str(_prism_data['blue'](label_val))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + ">" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "datad['prism']['blue']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Demo Data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The three initial data sets included in this example consist of a cropped region of a packed bead column (porous medium) within which biofilm was grown as part of an experiment examining the affect of fluid flow rate (hydraulic loading) on biofilm growth and development." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Segmented data file names\n", + "fnames = ['../data/mCT/demoThresh_Beads1.tif', '../data/mCT/demoThresh_Biofilm1.tif', '../data/mCT/demoThresh_Barium1.tif', '../data/mCT/LabelField.tif']\n", + "\n", + "for index, val in enumerate(['beads', 'biofilm', 'barium', 'label_field']):\n", + " #globals()[val] = pims.TiffStack(fnames[index])\n", + " globals()[val] = tiff_io.read_tiff(fnames[index])\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "255\n", + "85\n", + "[ 85 170 255]\n" + ] + }, + { + "data": { + "text/plain": [ + "(100, 425, 425)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print np.amax(label_field)\n", + "print np.amin(label_field)\n", + "print np.unique(label_field)\n", + "label_field.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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jR7Z/ukcTi/zLNWnfeK3MyDfOfZ3qbnSVJhZuVCx9SfGxAYUWkn3UGcUWCHnV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\nYQYEExMTjf8HjkdJc/CwVZsAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n", + "0\n" + ] + } + ], + "source": [ + "beads[100]\n", + "#label_field[50]\n", + "plt.imshow(beads[50,:,:])\n", + "plt.show()\n", + "print np.amax(beads)\n", + "print np.amin(beads)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol = vtk.vtkImageData()\n", + "vol.SetDimensions(beads.shape[0], beads.shape[1], beads.shape[2])\n", + "vol.SetOrigin(0,0,0)\n", + "vol.SetSpacing(1,1,1)\n", + "\n", + "vtk_data = vtk.util.numpy_support.numpy_to_vtk(beads.ravel(), deep=True)\n", + "\n", + "vol.GetPointData().SetScalars(vtk_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkInformation (0x253a7e0)\n", + " Debug: Off\n", + " Modified Time: 77\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + "\n", + "\n", + "unsigned char\n", + "0.0\n", + "255\n", + "32\n", + "2147483647\n", + "1\n", + "(0, 1)\n", + "1\n", + "0\n" + ] + } + ], + "source": [ + "print vtk_data.GetInformation()\n", + "print vtk_data.GetDataTypeAsString()\n", + "print vtk_data.GetDataTypeMin()\n", + "print vtk_data.GetDataTypeValueMax()\n", + "print vtk_data.GetMaxDiscreteValues()\n", + "print vtk_data.GetNumberOfComponentsMaxValue()\n", + "print vtk_data.GetNumberOfComponentsMinValue()\n", + "print vtk_data.GetValueRange()\n", + "print vtk_data.GetValue(1000)\n", + "print vtk_data.GetValue(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkCellData (0x2acee00)\n", + " Debug: Off\n", + " Modified Time: 56\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n" + ] + } + ], + "source": [ + "print vol.GetCellData()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol.GetDataDimension()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0, 1)\n" + ] + } + ], + "source": [ + "print vtk_data.GetValueRange()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "opacity_xfer_func = vtk.vtkPiecewiseFunction()\n", + "opacity_xfer_func.AddPoint(0, 0.2)\n", + "opacity_xfer_func.AddPoint(1, 0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "color_xfer_func = vtk.vtkColorTransferFunction()\n", + "color_xfer_func.AddRGBPoint(0.0, 0.0, 0.0, 0.0)\n", + "color_xfer_func.AddRGBPoint(1.0, 0.0, 1, 0.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(color_xfer_func)\n", + "volumeProperty.SetScalarOpacity(opacity_xfer_func)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "GetComponent() takes exactly 2 arguments (1 given)", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mvolumeMapper\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetVolumeRayCastFunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcompositFunc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;31m#volumeMapper.SetInputData(vol)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mvolumeMapper\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetInputData\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvtk_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetComponent\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m: GetComponent() takes exactly 2 arguments (1 given)" + ] + } + ], + "source": [ + "compositFunc = vtk.vtkVolumeRayCastCompositeFunction()\n", + "volumeMapper = vtk.vtkVolumeRayCastMapper()\n", + "volumeMapper.SetVolumeRayCastFunction(compositFunc)\n", + "#volumeMapper.SetInputData(vol)\n", + "volumeMapper.SetInputData(vtk_data.Get)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "actorVolume = vtk.vtkVolume()\n", + "actorVolume.SetMapper(volumeMapper)\n", + "actorVolume.SetProperty(volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def createDummyRenderer():\n", + " renderer = vtk.vtkRenderer()\n", + " renderer.SetBackground(0.5,0.5,0.5)\n", + " \n", + " camera = renderer.MakeCamera()\n", + " camera.SetPosition(-256,-256,512)\n", + " camera.SetFocalPoint(0.0, 0.0, 255.0)\n", + " camera.SetViewAngle(30.0)\n", + " camera.SetViewUp(0.46, -0.80, -0.38)\n", + " \n", + " renderer.SetActiveCamera(camera)\n", + " \n", + " return renderer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "renderWindow_tst = vtk.vtkRenderWindow()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "renderer = createDummyRenderer()\n", + "renderer.AddActor(actorVolume)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(vol, volumeProperty, 800,800)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 426, 0, 426, 0, 101)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetDataExtent()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetDataScalarType()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetNumberOfScalarComponents()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(101, 426, 426)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "beads.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dataImporter.SetDataExtent(dataImporter.GetDataExtent())" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "dataImporter.SetWholeExtent(dataImporter.GetWholeExtent())" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "alphaChannelFunc = vtk.vtkPiecewiseFunction()\n", + "alphaChannelFunc.AddPoint(0, 0.0)\n", + "alphaChannelFunc.AddPoint(1, 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# This class stores color data and can create color tables from a few color points. For this demo, we want the three cubes\n", + "# to be of the colors red green and blue.\n", + "colorFunc = vtk.vtkColorTransferFunction()\n", + "colorFunc.AddRGBPoint(1, 1.0, 0.0, 0.0)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(colorFunc)\n", + "volumeProperty.SetScalarOpacity(alphaChannelFunc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(dataImporter, label_field, [0.05, 0.1, 0.2])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(dataImporter, volumeProperty, width=425, height=425)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "global name 'vtkRenderWindow' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mvtk_tools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mipython_vtk_viewer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvolumeProperty\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;32m/home/giltis/dev/my_src/scikit-xray/skxray/io/vtk_tools.pyc\u001b[0m in \u001b[0;36mipython_vtk_viewer\u001b[1;34m(renderer, width, height)\u001b[0m\n\u001b[0;32m 205\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 206\u001b[0m \u001b[1;31m#Create new rendering window\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 207\u001b[1;33m \u001b[0mrenderWindow\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvtkRenderWindow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 208\u001b[0m \u001b[1;31m#Enable off-screen rendering\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 209\u001b[0m \u001b[0mrenderWindow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetOffScreenRendering\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: global name 'vtkRenderWindow' is not defined" + ] + } + ], + "source": [ + "vtk_tools.ipython_vtk_viewer(volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "GetPointDataData", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mdmc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvtk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvtkDiscreteMarchingCubes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mdmc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetInputConnection\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvol\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetPointDataData\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[0mdmc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGenerateValues\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mdmc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mUpdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: GetPointDataData" + ] + } + ], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(vol.GetPointDataData())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "tmp = 5" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.5,0.5,0.5)\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(renderer)\n", + "interactiveRender = vtk.vtkRenderWindowInteractor()\n", + "interactiveRender.SetRenderWindow(renWin)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "renWin.SetSize(600,600)\n", + "\n", + "interactiveRender.Initialize()\n", + "renWin.Render()\n", + "interactiveRender.Start()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "mro", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 889\u001b[0m \u001b[1;31m# lookup registered printer\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 890\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 891\u001b[1;33m \u001b[0mprinter\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlookup\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 892\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 893\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36mlookup\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 382\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msingleton_printers\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mobj_id\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 383\u001b[0m \u001b[1;31m# then lookup by type\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 384\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlookup_by_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_get_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 385\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 386\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mlookup_by_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtyp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36mlookup_by_type\u001b[1;34m(self, typ)\u001b[0m\n\u001b[0;32m 412\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 413\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcls\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mpretty\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_mro\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtyp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 414\u001b[1;33m \u001b[1;32mif\u001b[0m \u001b[0mcls\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype_printers\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_in_deferred_types\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 415\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype_printers\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 416\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: mro" + ] + }, + { + "data": { + "text/plain": [ + "(vtkAlgorithmOutput)0x7fcaa6425788" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetOutputPort()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1.ipynb b/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1.ipynb new file mode 100644 index 00000000..2996c497 --- /dev/null +++ b/demos/tomography/vis_3D/vtk_viewer-biofilm_demo_1.ipynb @@ -0,0 +1,1065 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools, tiff_io\n", + "import pims\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from vtk.numpy_interface import dataset_adapter as dsa\n", + "\n", + "from vtk.numpy_interface import algorithms as algs \n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "_prism_data = {\n", + " 'red': lambda x: 0.75 * np.sin((x * 20.9 + 0.25) * np.pi) + 0.67,\n", + " 'green': lambda x: 0.75 * np.sin((x * 20.9 - 0.25) * np.pi) + 0.33,\n", + " 'blue': lambda x: -1.1 * np.sin((x * 20.9) * np.pi),\n", + "}\n", + "datad = {'prism': _prism_data}\n", + "\n", + "cm_label = ((0.0, 255.0, 0.0), # 1 -- Lime Green\n", + " (255.0, 223.0, 0.0), # 2 -- Golden yellow\n", + " (135.0, 206.0, 250.0), # 3 -- Sky Blue\n", + " (220.0, 20.0, 60.0), # 4 -- Crimson\n", + " (0.0, 128.0, 0.0), # 5 -- Green\n", + " (255.0, 140.0, 0.0), # 6 -- Dark Orange\n", + " (0.0, 0.0, 255.0), # 7 -- Blue\n", + " (138.0, 43.0, 226.0), # 8 -- Blue Violet\n", + " (46.0, 139.0, 87.0), # 9 -- Sea Green\n", + " (128.0, 0.0, 0.0), # 10 -- Maroon\n", + " (0.0, 128.0, 128.0), # 11 -- Teal\n", + " (160.0, 82.0, 45.0), # 12 -- Sienna \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "val = 0\n", + "red1.20033008589\n", + "green-0.20033008589\n", + "blue-0.0\n", + "val = 1\n", + "red0.329507125195\n", + "green0.998254893141\n", + "blue-0.339918693812\n", + "val = 2\n", + "red0.78732584878\n", + "green-0.410766255446\n", + "blue0.646563777522\n", + "val = 3\n", + "red0.78732584878\n", + "green1.07076625545\n", + "blue-0.889918693812\n", + "val = 4\n", + "red0.329507125195\n", + "green-0.338254893141\n", + "blue1.04616216792\n", + "val = 5\n", + "red1.20033008589\n", + "green0.86033008589\n", + "blue-1.1\n" + ] + } + ], + "source": [ + "val=[0, 1, 2, 3, 4, 5]\n", + "for label_val in val:\n", + " print 'val = ' + str(label_val)\n", + " print 'red' + str(_prism_data['red'](label_val))\n", + " print 'green' + str(_prism_data['green'](label_val))\n", + " print 'blue' + str(_prism_data['blue'](label_val))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + ">" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "datad['prism']['blue']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load Demo Data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The three initial data sets included in this example consist of a cropped region of a packed bead column (porous medium) within which biofilm was grown as part of an experiment examining the affect of fluid flow rate (hydraulic loading) on biofilm growth and development." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Segmented data file names\n", + "fnames = ['../data/mCT/demoThresh_Beads1.tif', '../data/mCT/demoThresh_Biofilm1.tif', '../data/mCT/demoThresh_Barium1.tif', '../data/mCT/LabelField.tif']\n", + "\n", + "for index, val in enumerate(['beads', 'biofilm', 'barium', 'label_field']):\n", + " #globals()[val] = pims.TiffStack(fnames[index])\n", + " globals()[val] = tiff_io.read_tiff(fnames[index])\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "255\n", + "85\n", + "[ 85 170 255]\n" + ] + }, + { + "data": { + "text/plain": [ + "(100, 425, 425)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print np.amax(label_field)\n", + "print np.amin(label_field)\n", + "print np.unique(label_field)\n", + "label_field.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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jR7Z/ukcTi/zLNWnfeK3MyDfOfZ3qbnSVJhZuVCx9SfGxAYUWkn3UGcUWCHnV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\nYQYEExMTjf8HjkdJc/CwVZsAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n", + "0\n" + ] + } + ], + "source": [ + "beads[100]\n", + "#label_field[50]\n", + "plt.imshow(beads[50,:,:])\n", + "plt.show()\n", + "print np.amax(beads)\n", + "print np.amin(beads)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Convert label field to VTK object\n", + "dataImporter = vtk_tools.np_to_vtk(label_field)\n", + "#dataImporter = vtk_tools.np_to_vtk(label_field)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkImageData (0x2c02270)\n", + " Debug: Off\n", + " Modified Time: 117\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Information: 0x2d066b0\n", + " Data Released: False\n", + " Global Release Data: Off\n", + " UpdateTime: 0\n", + " Field Data:\n", + " Debug: Off\n", + " Modified Time: 114\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Number Of Points: 0\n", + " Number Of Cells: 0\n", + " Cell Data:\n", + " Debug: Off\n", + " Modified Time: 117\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + " Point Data:\n", + " Debug: Off\n", + " Modified Time: 116\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + " Bounds: \n", + " Xmin,Xmax: (1, -1)\n", + " Ymin,Ymax: (1, -1)\n", + " Zmin,Zmax: (1, -1)\n", + " Compute Time: 135\n", + " Spacing: (1, 1, 1)\n", + " Origin: (0, 0, 0)\n", + " Dimensions: (0, 0, 0)\n", + " Increments: (0, 0, 0)\n", + " Extent: (0, -1, 0, -1, 0, -1)\n", + "\n", + "\n", + "vtkInformation (0x2c57cd0)\n", + " Debug: Off\n", + " Modified Time: 59\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " INPUT_ARRAYS_TO_PROCESS: vtkInformationVector(0x2da52e0)\n", + "\n", + "\n" + ] + } + ], + "source": [ + "print dataImporter.GetOutput()\n", + "print dataImporter.GetInformation()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol = vtk.vtkImageData()\n", + "vol.SetDimensions(beads.shape[0], beads.shape[1], beads.shape[2])\n", + "vol.SetOrigin(0,0,0)\n", + "vol.SetSpacing(1,1,1)\n", + "\n", + "vtk_data = vtk.util.numpy_support.numpy_to_vtk(beads.ravel(), deep=True)\n", + "\n", + "vol.GetPointData().SetScalars(vtk_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkInformation (0x2d8eca0)\n", + " Debug: Off\n", + " Modified Time: 163\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + "\n", + "\n", + "unsigned char\n", + "0.0\n", + "255\n", + "32\n", + "2147483647\n", + "1\n", + "(0, 1)\n", + "1\n", + "0\n" + ] + } + ], + "source": [ + "print vtk_data.GetInformation()\n", + "print vtk_data.GetDataTypeAsString()\n", + "print vtk_data.GetDataTypeMin()\n", + "print vtk_data.GetDataTypeValueMax()\n", + "print vtk_data.GetMaxDiscreteValues()\n", + "print vtk_data.GetNumberOfComponentsMaxValue()\n", + "print vtk_data.GetNumberOfComponentsMinValue()\n", + "print vtk_data.GetValueRange()\n", + "print vtk_data.GetValue(1000)\n", + "print vtk_data.GetValue(10)\n", + "#print vtk_data.GetData()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkCellData (0x2d98eb0)\n", + " Debug: Off\n", + " Modified Time: 142\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n" + ] + } + ], + "source": [ + "print vol.GetCellData()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol.GetDataDimension()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "255\n", + "0\n", + "(0, 1)\n" + ] + } + ], + "source": [ + "print vtk_data.GetDataTypeValueMax()\n", + "print vtk_data.GetDataTypeValueMin()\n", + "print vtk_data.GetValueRange()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "opacity_xfer_func = vtk.vtkPiecewiseFunction()\n", + "opacity_xfer_func.AddPoint(0, 0.2)\n", + "opacity_xfer_func.AddPoint(1, 0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "color_xfer_func = vtk.vtkColorTransferFunction()\n", + "color_xfer_func.AddRGBPoint(0.0, 0.0, 0.0, 0.0)\n", + "color_xfer_func.AddRGBPoint(1.0, 0.0, 1, 0.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(color_xfer_func)\n", + "volumeProperty.SetScalarOpacity(opacity_xfer_func)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#compositFunc = vtk.vtkVolumeRayCastCompositeFunction()\n", + "#volumeMapper = vtk.vtkVolumeRayCastMapper()\n", + "#volumeMapper.SetVolumeRayCastFunction(compositFunc)\n", + "#volumeMapper.SetInputData(vol)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputData(vol)\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.5,0.5,0.5)\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(renderer)\n", + "interactiveRender = vtk.vtkRenderWindowInteractor()\n", + "interactiveRender.SetRenderWindow(renWin)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "renWin.SetSize(600,600)\n", + "\n", + "interactiveRender.Initialize()\n", + "renWin.Render()\n", + "interactiveRender.Start()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "actorVolume = vtk.vtkVolume()\n", + "actorVolume.SetMapper(volumeMapper)\n", + "actorVolume.SetProperty(volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def createDummyRenderer():\n", + " renderer = vtk.vtkRenderer()\n", + " renderer.SetBackground(0.5,0.5,0.5)\n", + " \n", + " camera = renderer.MakeCamera()\n", + " camera.SetPosition(-256,-256,512)\n", + " camera.SetFocalPoint(0.0, 0.0, 255.0)\n", + " camera.SetViewAngle(30.0)\n", + " camera.SetViewUp(0.46, -0.80, -0.38)\n", + " \n", + " renderer.SetActiveCamera(camera)\n", + " \n", + " return renderer\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "renderWindow_tst = vtk.vtkRenderWindow()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "renderer = createDummyRenderer()\n", + "renderer.AddActor(actorVolume)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(vol, volumeProperty, 800,800)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 426, 0, 426, 0, 101)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetDataExtent()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetDataScalarType()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetNumberOfScalarComponents()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(101, 426, 426)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "beads.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dataImporter.SetDataExtent(dataImporter.GetDataExtent())" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "dataImporter.SetWholeExtent(dataImporter.GetWholeExtent())" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "alphaChannelFunc = vtk.vtkPiecewiseFunction()\n", + "alphaChannelFunc.AddPoint(0, 0.0)\n", + "alphaChannelFunc.AddPoint(1, 0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# This class stores color data and can create color tables from a few color points. For this demo, we want the three cubes\n", + "# to be of the colors red green and blue.\n", + "colorFunc = vtk.vtkColorTransferFunction()\n", + "colorFunc.AddRGBPoint(1, 1.0, 0.0, 0.0)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(colorFunc)\n", + "volumeProperty.SetScalarOpacity(alphaChannelFunc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(dataImporter, label_field, [0.05, 0.1, 0.2])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(dataImporter, volumeProperty, width=425, height=425)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "global name 'vtkRenderWindow' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mvtk_tools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mipython_vtk_viewer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvolumeProperty\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;32m/home/giltis/dev/my_src/scikit-xray/skxray/io/vtk_tools.pyc\u001b[0m in \u001b[0;36mipython_vtk_viewer\u001b[1;34m(renderer, width, height)\u001b[0m\n\u001b[0;32m 205\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 206\u001b[0m \u001b[1;31m#Create new rendering window\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 207\u001b[1;33m \u001b[0mrenderWindow\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvtkRenderWindow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 208\u001b[0m \u001b[1;31m#Enable off-screen rendering\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 209\u001b[0m \u001b[0mrenderWindow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetOffScreenRendering\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: global name 'vtkRenderWindow' is not defined" + ] + } + ], + "source": [ + "vtk_tools.ipython_vtk_viewer(volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(dataImporter.GetOutputPort())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "tmp = 5" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.5,0.5,0.5)\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(renderer)\n", + "interactiveRender = vtk.vtkRenderWindowInteractor()\n", + "interactiveRender.SetRenderWindow(renWin)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "renWin.SetSize(600,600)\n", + "\n", + "interactiveRender.Initialize()\n", + "renWin.Render()\n", + "interactiveRender.Start()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "mro", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 889\u001b[0m \u001b[1;31m# lookup registered printer\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 890\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 891\u001b[1;33m \u001b[0mprinter\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlookup\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 892\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 893\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36mlookup\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 382\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msingleton_printers\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mobj_id\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 383\u001b[0m \u001b[1;31m# then lookup by type\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 384\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlookup_by_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_get_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 385\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 386\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mlookup_by_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtyp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/IPython/core/formatters.pyc\u001b[0m in \u001b[0;36mlookup_by_type\u001b[1;34m(self, typ)\u001b[0m\n\u001b[0;32m 412\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 413\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcls\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mpretty\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_mro\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtyp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 414\u001b[1;33m \u001b[1;32mif\u001b[0m \u001b[0mcls\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype_printers\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_in_deferred_types\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 415\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype_printers\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 416\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mAttributeError\u001b[0m: mro" + ] + }, + { + "data": { + "text/plain": [ + "(vtkAlgorithmOutput)0x7fcaa6425788" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetOutputPort()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/vis_3D/vttools_arithmetic_demo.ipynb b/demos/tomography/vis_3D/vttools_arithmetic_demo.ipynb new file mode 100644 index 00000000..7d789a5a --- /dev/null +++ b/demos/tomography/vis_3D/vttools_arithmetic_demo.ipynb @@ -0,0 +1,167 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "No module named image_proc", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mskxray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mio\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mvtk_tools\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mvttools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_wrap\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimage_proc\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0marithmetic\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marithmetic_expression\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mImportError\u001b[0m: No module named image_proc" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import vtk\n", + "import numpy as np\n", + "\n", + "from skxray.io import vtk_tools\n", + "from vttools.to_wrap.image_proc import arithmetic, arithmetic_expression" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_matrix1 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix1[0:35, 0:35, 0:35] = 50\n", + "\n", + "data_matrix2 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix2[25:55, 25:55, 25:55] = 100\n", + "\n", + "data_matrix3 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix3[45:74, 45:74, 45:74] = 150" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Arithmetic example #1\n", + "merge_demo1 = arithmetic('addition', data_matrix1, data_matrix2)\n", + "\n", + "merge_demo1 = arithmetic('addition', merge_demo1, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Arithmetic example 2\n", + "merge_demo2 = arithmetic_expression('A*B+C', data_matrix1, data_matrix2, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Data Conversion from numpy to VTK object\n", + "\n", + "vtkDemo_cube1 = vtk_tools.np_to_vtk(data_matrix2)\n", + "\n", + "vtkDemo_merge1 = vtk_tools.np_to_vtk(merge_demo1)\n", + "\n", + "vtkDemo_merge2 = vtk_tools.np_to_vtk(merge_demo2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_cube1)\n", + "vtk_tools.vtk_viewer(vtkDemo_cube1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge1)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge2)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge2, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/UnstructuredGrid_ex.ipynb b/demos/tomography/visualization/UnstructuredGrid_ex.ipynb new file mode 100644 index 00000000..d2f4acef --- /dev/null +++ b/demos/tomography/visualization/UnstructuredGrid_ex.ipynb @@ -0,0 +1,931 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import os,sys,string\n", + "from vtk import *\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkInformationVector (0x173c620)\n", + " Debug: Off\n", + " Modified Time: 398\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number of Information Objects: 1\n", + " Information Objects:\n", + " vtkInformation(0x173cec0):\n", + " Debug: Off\n", + " Modified Time: 475\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PRODUCER: vtkCompositeDataPipeline(0x1738120) port 0\n", + " CAN_HANDLE_PIECE_REQUEST: 1\n", + " UPDATE_NUMBER_OF_GHOST_LEVELS: 0\n", + " TIME_STEPS: 0 0.111111 0.222222 0.333333 0.444444 0.555556 0.666667 0.777778 0.888889 1\n", + " TIME_RANGE: 0 1\n", + " UPDATE_PIECE_NUMBER: 0\n", + " UPDATE_EXTENT_INITIALIZED: 0\n", + " UPDATE_NUMBER_OF_PIECES: 1\n", + " DATA_OBJECT: vtkUnstructuredGrid(0x13410d0)\n", + "\n", + "\n", + "(0.0, 1.0, 0.0, 1.0, 0.0, 1.0)\n", + "(0.0, 1.0, 0.0, 1.0, 0.0, 1.0)\n", + "vtkUnstructuredGrid (0x13410d0)\n", + " Debug: Off\n", + " Modified Time: 702\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Information: 0x1738730\n", + " Data Released: False\n", + " Global Release Data: Off\n", + " UpdateTime: 707\n", + " Field Data:\n", + " Debug: Off\n", + " Modified Time: 641\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Number Of Points: 8\n", + " Number Of Cells: 1\n", + " Cell Data:\n", + " Debug: Off\n", + " Modified Time: 702\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Cell Value\n", + " Array 1 name = Cell Label\n", + " Array 2 name = Cell X\n", + " Array 3 name = Cell Y\n", + " Array 4 name = Cell Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 1\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 687\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Name: Cell Label\n", + " Data type: idtype\n", + " Size: 1\n", + " MaxId: 0\n", + " NumberOfComponents: 1\n", + " Information: 0\n", + " Name: Cell Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 1\n", + " Size: 1\n", + " MaxId: 0\n", + " LookupTable: (none)\n", + " Array: 0x12a68b0\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + " Point Data:\n", + " Debug: Off\n", + " Modified Time: 676\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 15\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 15\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + " Bounds: \n", + " Xmin,Xmax: (0, 1)\n", + " Ymin,Ymax: (0, 1)\n", + " Zmin,Zmax: (0, 1)\n", + " Compute Time: 719\n", + " Number Of Points: 8\n", + " Point Coordinates: 0x17318c0\n", + " Locator: 0\n", + " Number Of Pieces: 1\n", + " Piece: 0\n", + " Ghost Level: 0\n", + "\n", + "\n" + ] + } + ], + "source": [ + "tse = vtkTimeSourceExample()\n", + "ex = tse.GetExecutive()\n", + "tse.UpdateInformation()\n", + " \n", + "#inspect available time range and time steps\n", + "print ex.GetOutputInformation()\n", + " \n", + "#make it grow because bounds are easy to inspect\n", + "# tse.SetGrowing(1)\n", + " \n", + "ex.SetUpdateTimeStep(0,0.0)\n", + "tse.Update()\n", + "print(tse.GetOutput().GetBounds())\n", + " \n", + "#pick some other time inside the time range\n", + "ex.SetUpdateTimeStep(0,0.5)\n", + "tse.Update()\n", + "print(tse.GetOutput().GetBounds())\n", + " \n", + "grid = tse.GetOutput()\n", + "print grid" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "tri = vtkDataSetTriangleFilter()\n", + "tri.SetInputDataObject(grid)\n", + "tri.SetTetrahedraOnly(1)\n", + "tri.Update()\n", + "output = tri.GetOutput()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "iss = output.GetPointData().SetActiveScalars(\"Point Label\")\n", + "# iss = gridMapper.GetInput().GetCellData().SetActiveScalars(options.scalarName)\n", + "assert(iss>-1)\n", + " \n", + "drange = [0, 1]\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create transfer mapping scalar value to opacity.\n", + "opacityFunction = vtkPiecewiseFunction()\n", + "opacityFunction.AddPoint(drange[0], 0.0)\n", + "opacityFunction.AddPoint(drange[1], 1.0)\n", + " \n", + "# Create transfer mapping scalar value to color.\n", + "colorFunction = vtkColorTransferFunction()\n", + "colorFunction.SetColorSpaceToHSV()\n", + "colorFunction.HSVWrapOff()\n", + "colorFunction.AddRGBPoint(drange[0], 0.0, 0.0, 1.0)\n", + "colorFunction.AddRGBPoint(drange[1], 1.0, 0.0, 0.0)\n", + " \n", + "volumeProperty = vtkVolumeProperty()\n", + "volumeProperty.SetScalarOpacity(opacityFunction)\n", + "volumeProperty.SetColor(colorFunction)\n", + "volumeProperty.ShadeOff()\n", + "volumeProperty.SetInterpolationTypeToLinear()\n", + "# volumeProperty.SetScalarOpacityUnitDistance(options.unit)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeMapper = vtkUnstructuredGridVolumeRayCastMapper()\n", + "# volumeMapper = vtkUnstructuredGridVolumeZSweepMapper()\n", + "# volumeMapper = vtkProjectedTetrahedraMapper()\n", + "# volumeMapper.SetBlendModeToMaximumIntensity()\n", + "volumeMapper.SetInputData(output)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time = 0\n", + "vtkPointData (0x172d400)\n", + " Debug: Off\n", + " Modified Time: 676\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 8\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " 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Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 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idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 8\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n", + "time = 0.8\n", + "vtkPointData (0x172d400)\n", + " Debug: Off\n", + " Modified Time: 676\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 8\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n", + "time = 0.9\n", + "vtkPointData (0x172d400)\n", + " Debug: Off\n", + " Modified Time: 676\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 8\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n", + "time = 1.0\n", + "vtkPointData (0x172d400)\n", + " Debug: Off\n", + " Modified Time: 676\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 5\n", + " Array 0 name = Point Value\n", + " Array 1 name = Point Label\n", + " Array 2 name = Point X\n", + " Array 3 name = Point Y\n", + " Array 4 name = Point Z\n", + " Number Of Components: 5\n", + " Number Of Tuples: 8\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: \n", + " Debug: Off\n", + " Modified Time: 661\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Name: Point Label\n", + " Data type: idtype\n", + " Size: 8\n", + " MaxId: 7\n", + " NumberOfComponents: 1\n", + " Information: 0x28c0810\n", + " Debug: Off\n", + " Modified Time: 5665\n", + " Reference Count: 1\n", + " Registered Events: (none)\n", + " PER_COMPONENT: vtkInformationVector(0x28c0a10)\n", + " Name: Point Label\n", + " Number Of Components: 1\n", + " Number Of Tuples: 8\n", + " Size: 8\n", + " MaxId: 7\n", + " LookupTable: (none)\n", + " Array: 0x1308410\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n" + ] + } + ], + "source": [ + " \n", + "volume = vtkVolume()\n", + "volume.SetMapper(volumeMapper)\n", + "volume.SetProperty(volumeProperty)\n", + " \n", + "# create a rendering window and renderer\n", + "renderer = vtkRenderer()\n", + "renderer.SetBackground(0,0,0)\n", + " \n", + "window = vtkRenderWindow()\n", + "window.SetSize(512,512)\n", + "window.AddRenderer(renderer)\n", + " \n", + "interactor = vtkRenderWindowInteractor()\n", + "interactor.SetRenderWindow(window)\n", + " \n", + "style = vtkInteractorStyleTrackballCamera();\n", + "interactor.SetInteractorStyle(style);\n", + " \n", + "renderer.AddVolume(volume)\n", + " \n", + "scalarBar = vtkScalarBarActor()\n", + "scalarBar.SetLookupTable(colorFunction);\n", + "scalarBar.SetOrientationToVertical();\n", + "scalarBar.SetPosition( 0.85, 0.7 );\n", + "scalarBar.SetPosition2( 0.1, 0.3 );\n", + "propT = vtkTextProperty()\n", + "propL = vtkTextProperty()\n", + "propT.SetFontFamilyToArial()\n", + "propT.ItalicOff()\n", + "propT.BoldOn()\n", + "propL.BoldOff()\n", + "scalarBar.SetTitleTextProperty(propT);\n", + "scalarBar.SetLabelTextProperty(propL);\n", + "scalarBar.SetLabelFormat(\"%5.2f\")\n", + "renderer.AddActor(scalarBar)\n", + " \n", + "# setup the text and add it to the window\n", + "textActor = vtkTextActor()\n", + "textActor.GetTextProperty().SetFontSize(12)\n", + "textActor.SetPosition2(10, 40)\n", + "renderer.AddActor2D(textActor)\n", + "textActor.SetInput(\"time = \")\n", + "textActor.GetTextProperty().SetColor(1.0,1.0,1.0)\n", + " \n", + "renderer.ResetCameraClippingRange()\n", + "renderer.ResetCamera()\n", + " \n", + "counter = 1\n", + "time = 0\n", + "while time<=1:\n", + " print \"time = \", time\n", + " textActor.SetInput(\"time = %g\" % time)\n", + "\n", + " window.Render()\n", + " \n", + " # TODO FIXME if this block is not here than the volume renders wrongly\n", + " renderer.RemoveVolume(volume)\n", + " # del volume\n", + " volume = vtkVolume()\n", + " volume.SetMapper(volumeMapper)\n", + " volume.SetProperty(volumeProperty)\n", + " renderer.AddVolume(volume)\n", + " \n", + " counter = counter + 1\n", + " time = time + 1./10\n", + " ex.SetUpdateTimeStep(0,time)\n", + " tse.Modified()\n", + " #print grid.GetPointData().GetScalars().GetRange()\n", + " print grid.GetPointData()\n", + " # print grid.GetPointData().GetScalars()\n", + " \n", + "# while True:\n", + " # window.Render()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "l" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/VTK_example_2.ipynb b/demos/tomography/visualization/VTK_example_2.ipynb new file mode 100644 index 00000000..a51aac4a --- /dev/null +++ b/demos/tomography/visualization/VTK_example_2.ipynb @@ -0,0 +1,422 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#!/usr/bin/env python\n", + "\n", + "# This example demonstrates the use of the vtkTransformPolyDataFilter\n", + "# to reposition a 3D text string.\n", + "\n", + "import vtk\n", + "from vtk.util.colors import *\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "# Define a Single Cube\n", + "Scalars = vtk.vtkFloatArray()\n", + "Scalars.InsertNextValue(1.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "Scalars.InsertNextValue(1.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "Scalars.InsertNextValue(0.0)\n", + "\n", + "Points = vtk.vtkPoints()\n", + "Points.InsertNextPoint(0, 0, 0)\n", + "Points.InsertNextPoint(1, 0, 0)\n", + "Points.InsertNextPoint(1, 1, 0)\n", + "Points.InsertNextPoint(0, 1, 0)\n", + "Points.InsertNextPoint(0, 0, 1)\n", + "Points.InsertNextPoint(1, 0, 1)\n", + "Points.InsertNextPoint(1, 1, 1)\n", + "Points.InsertNextPoint(0, 1, 1)\n", + "\n", + "Ids = vtk.vtkIdList()\n", + "Ids.InsertNextId(0)\n", + "Ids.InsertNextId(1)\n", + "Ids.InsertNextId(2)\n", + "Ids.InsertNextId(3)\n", + "Ids.InsertNextId(4)\n", + "Ids.InsertNextId(5)\n", + "Ids.InsertNextId(6)\n", + "Ids.InsertNextId(7)\n", + "\n", + "Grid = vtk.vtkUnstructuredGrid()\n", + "Grid.Allocate(10, 10)\n", + "Grid.InsertNextCell(12, Ids)\n", + "Grid.SetPoints(Points)\n", + "Grid.GetPointData().SetScalars(Scalars)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# Find the triangles that lie along the 0.5 contour in this cube.\n", + "Marching = vtk.vtkContourFilter()\n", + "Marching.SetInput(Grid)\n", + "Marching.SetValue(0, 0.5)\n", + "Marching.Update()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Extract the edges of the triangles just found.\n", + "triangleEdges = vtk.vtkExtractEdges()\n", + "triangleEdges.SetInputConnection(Marching.GetOutputPort())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Draw the edges as tubes instead of lines. Also create the associated\n", + "# mapper and actor to display the tubes.\n", + "triangleEdgeTubes = vtk.vtkTubeFilter()\n", + "triangleEdgeTubes.SetInputConnection(triangleEdges.GetOutputPort())\n", + "triangleEdgeTubes.SetRadius(.005)\n", + "triangleEdgeTubes.SetNumberOfSides(6)\n", + "triangleEdgeTubes.UseDefaultNormalOn()\n", + "triangleEdgeTubes.SetDefaultNormal(.577, .577, .577)\n", + "triangleEdgeMapper = vtk.vtkPolyDataMapper()\n", + "triangleEdgeMapper.SetInputConnection(triangleEdgeTubes.GetOutputPort())\n", + "triangleEdgeMapper.ScalarVisibilityOff()\n", + "triangleEdgeActor = vtk.vtkActor()\n", + "triangleEdgeActor.SetMapper(triangleEdgeMapper)\n", + "triangleEdgeActor.GetProperty().SetDiffuseColor(lamp_black)\n", + "triangleEdgeActor.GetProperty().SetSpecular(.4)\n", + "triangleEdgeActor.GetProperty().SetSpecularPower(10)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Shrink the triangles we found earlier. Create the associated mapper\n", + "# and actor. Set the opacity of the shrunken triangles.\n", + "aShrinker = vtk.vtkShrinkPolyData()\n", + "aShrinker.SetShrinkFactor(1)\n", + "aShrinker.SetInputConnection(Marching.GetOutputPort())\n", + "aMapper = vtk.vtkPolyDataMapper()\n", + "aMapper.ScalarVisibilityOff()\n", + "aMapper.SetInputConnection(aShrinker.GetOutputPort())\n", + "Triangles = vtk.vtkActor()\n", + "Triangles.SetMapper(aMapper)\n", + "Triangles.GetProperty().SetDiffuseColor(banana)\n", + "Triangles.GetProperty().SetOpacity(.6)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Draw a cube the same size and at the same position as the one\n", + "# created previously. Extract the edges because we only want to see\n", + "# the outline of the cube. Pass the edges through a vtkTubeFilter so\n", + "# they are displayed as tubes rather than lines.\n", + "CubeModel = vtk.vtkCubeSource()\n", + "CubeModel.SetCenter(.5, .5, .5)\n", + "Edges = vtk.vtkExtractEdges()\n", + "Edges.SetInputConnection(CubeModel.GetOutputPort())\n", + "Tubes = vtk.vtkTubeFilter()\n", + "Tubes.SetInputConnection(Edges.GetOutputPort())\n", + "Tubes.SetRadius(.01)\n", + "Tubes.SetNumberOfSides(6)\n", + "Tubes.UseDefaultNormalOn()\n", + "Tubes.SetDefaultNormal(.577, .577, .577)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create the mapper and actor to display the cube edges.\n", + "TubeMapper = vtk.vtkPolyDataMapper()\n", + "TubeMapper.SetInputConnection(Tubes.GetOutputPort())\n", + "CubeEdges = vtk.vtkActor()\n", + "CubeEdges.SetMapper(TubeMapper)\n", + "CubeEdges.GetProperty().SetDiffuseColor(khaki)\n", + "CubeEdges.GetProperty().SetSpecular(.4)\n", + "CubeEdges.GetProperty().SetSpecularPower(10)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create a sphere to use as a glyph source for vtkGlyph3D.\n", + "Sphere = vtk.vtkSphereSource()\n", + "Sphere.SetRadius(0.04)\n", + "Sphere.SetPhiResolution(20)\n", + "Sphere.SetThetaResolution(20)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Remove the part of the cube with data values below 0.5.\n", + "ThresholdIn = vtk.vtkThresholdPoints()\n", + "ThresholdIn.SetInput(Grid)\n", + "ThresholdIn.ThresholdByUpper(.5)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Display spheres at the vertices remaining in the cube data set after\n", + "# it was passed through vtkThresholdPoints.\n", + "Vertices = vtk.vtkGlyph3D()\n", + "Vertices.SetInputConnection(ThresholdIn.GetOutputPort())\n", + "Vertices.SetSourceConnection(Sphere.GetOutputPort())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create a mapper and actor to display the glyphs.\n", + "SphereMapper = vtk.vtkPolyDataMapper()\n", + "SphereMapper.SetInputConnection(Vertices.GetOutputPort())\n", + "SphereMapper.ScalarVisibilityOff()\n", + "CubeVertices = vtk.vtkActor()\n", + "CubeVertices.SetMapper(SphereMapper)\n", + "CubeVertices.GetProperty().SetDiffuseColor(tomato)\n", + "CubeVertices.GetProperty().SetDiffuseColor(tomato)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Define the text for the label\n", + "caseLabel = vtk.vtkVectorText()\n", + "caseLabel.SetText(\"Case 1\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Set up a transform to move the label to a new position.\n", + "aLabelTransform = vtk.vtkTransform()\n", + "aLabelTransform.Identity()\n", + "aLabelTransform.Translate(-0.2, 0, 1.25)\n", + "aLabelTransform.Scale(.05, .05, .05)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Move the label to a new position.\n", + "labelTransform = vtk.vtkTransformPolyDataFilter()\n", + "labelTransform.SetTransform(aLabelTransform)\n", + "labelTransform.SetInputConnection(caseLabel.GetOutputPort())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create a mapper and actor to display the text.\n", + "labelMapper = vtk.vtkPolyDataMapper()\n", + "labelMapper.SetInputConnection(labelTransform.GetOutputPort())\n", + "\n", + "labelActor = vtk.vtkActor()\n", + "labelActor.SetMapper(labelMapper)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Define the base that the cube sits on. Create its associated mapper\n", + "# and actor. Set the position of the actor.\n", + "baseModel = vtk.vtkCubeSource()\n", + "baseModel.SetXLength(1.5)\n", + "baseModel.SetYLength(.01)\n", + "baseModel.SetZLength(1.5)\n", + "baseMapper = vtk.vtkPolyDataMapper()\n", + "baseMapper.SetInputConnection(baseModel.GetOutputPort())\n", + "base = vtk.vtkActor()\n", + "base.SetMapper(baseMapper)\n", + "base.SetPosition(.5, -0.09, .5)\n", + "\n", + "# Create the Renderer, RenderWindow, and RenderWindowInteractor\n", + "ren = vtk.vtkRenderer()\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(ren)\n", + "renWin.SetSize(640, 480)\n", + "iren = vtk.vtkRenderWindowInteractor()\n", + "iren.SetRenderWindow(renWin)\n", + "\n", + "# Add the actors to the renderer\n", + "ren.AddActor(triangleEdgeActor)\n", + "ren.AddActor(base)\n", + "ren.AddActor(labelActor)\n", + "ren.AddActor(CubeEdges)\n", + "ren.AddActor(CubeVertices)\n", + "ren.AddActor(Triangles)\n", + "\n", + "# Set the background color.\n", + "ren.SetBackground(slate_grey)\n", + "\n", + "# This sets up the right values for case12 of the marching cubes\n", + "# algorithm (routine translated from vtktesting/mccases.tcl).\n", + "def case12(scalars, caselabel, IN, OUT):\n", + " scalars.InsertValue(0, OUT)\n", + " scalars.InsertValue(1, IN)\n", + " scalars.InsertValue(2, OUT)\n", + " scalars.InsertValue(3, IN)\n", + " scalars.InsertValue(4, IN)\n", + " scalars.InsertValue(5, IN)\n", + " scalars.InsertValue(6, OUT)\n", + " scalars.InsertValue(7, OUT)\n", + " if IN == 1:\n", + " caselabel.SetText(\"Case 12 - 00111010\")\n", + " else:\n", + " caselabel.SetText(\"Case 12 - 11000101\")\n", + "\n", + "# Set the scalar values for this case of marching cubes.\n", + "case12(Scalars, caseLabel, 0, 1)\n", + "\n", + "# Force the grid to update.\n", + "Grid.Modified()\n", + "\n", + "# Position the camera.\n", + "ren.ResetCamera()\n", + "ren.GetActiveCamera().Dolly(1.2)\n", + "ren.GetActiveCamera().Azimuth(30)\n", + "ren.GetActiveCamera().Elevation(20)\n", + "ren.ResetCameraClippingRange()\n", + "\n", + "iren.Initialize()\n", + "renWin.Render()\n", + "iren.Start()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/VTK_example_interactive_view.ipynb b/demos/tomography/visualization/VTK_example_interactive_view.ipynb new file mode 100644 index 00000000..190be238 --- /dev/null +++ b/demos/tomography/visualization/VTK_example_interactive_view.ipynb @@ -0,0 +1,277 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# VTK/Examples/Python/vtkWithNumpy" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## From KitwarePublic < VTK‎ | Examples‎ | Python Jump to: navigation, search vtkWithNumpy.py" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# An example from scipy cookbook demonstrating the use of numpy arrys in vtk \n", + " \n", + "import vtk\n", + "import numpy as np \n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# We begin by creating the data we want to render.\n", + "# For this tutorial, we create a 3D-image containing three overlaping cubes.\n", + "# This data can of course easily be replaced by data from a medical CT-scan or anything else three dimensional.\n", + "# The only limit is that the data must be reduced to unsigned 8 bit or 16 bit integers.\n", + "data_matrix = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix[0:35, 0:35, 0:35] = 50\n", + "data_matrix[25:55, 25:55, 25:55] = 100\n", + "data_matrix[45:74, 45:74, 45:74] = 150\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# For VTK to be able to use the data, it must be stored as a VTK-image. This can be done by the vtkImageImport-class which\n", + "# imports raw data and stores it.\n", + "dataImporter = vtk.vtkImageImport()\n", + "# The preaviusly created array is converted to a string of chars and imported.\n", + "data_string = data_matrix.tostring()\n", + "dataImporter.CopyImportVoidPointer(data_string, len(data_string))\n", + "# The type of the newly imported data is set to unsigned char (uint8)\n", + "dataImporter.SetDataScalarTypeToUnsignedChar()\n", + "# Because the data that is imported only contains an intensity value (it isnt RGB-coded or someting similar), the importer\n", + "# must be told this is the case.\n", + "dataImporter.SetNumberOfScalarComponents(1)\n", + "# The following two functions describe how the data is stored and the dimensions of the array it is stored in. For this\n", + "# simple case, all axes are of length 75 and begins with the first element. For other data, this is probably not the case.\n", + "# I have to admit however, that I honestly dont know the difference between SetDataExtent() and SetWholeExtent() although\n", + "# VTK complains if not both are used.\n", + "dataImporter.SetDataExtent(0, 74, 0, 74, 0, 74)\n", + "dataImporter.SetWholeExtent(0, 74, 0, 74, 0, 74)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "3" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The following class is used to store transparencyv-values for later retrival. In our case, we want the value 0 to be\n", + "# completly opaque whereas the three different cubes are given different transperancy-values to show how it works.\n", + "alphaChannelFunc = vtk.vtkPiecewiseFunction()\n", + "alphaChannelFunc.AddPoint(0, 0.0)\n", + "alphaChannelFunc.AddPoint(50, 0.05)\n", + "alphaChannelFunc.AddPoint(100, 0.1)\n", + "alphaChannelFunc.AddPoint(150, 0.2)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "2" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# This class stores color data and can create color tables from a few color points. For this demo, we want the three cubes\n", + "# to be of the colors red green and blue.\n", + "colorFunc = vtk.vtkColorTransferFunction()\n", + "colorFunc.AddRGBPoint(50, 1.0, 0.0, 0.0)\n", + "colorFunc.AddRGBPoint(100, 0.0, 1.0, 0.0)\n", + "colorFunc.AddRGBPoint(150, 0.0, 0.0, 1.0)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# The preavius two classes stored properties. Because we want to apply these properties to the volume we want to render,\n", + "# we have to store them in a class that stores volume prpoperties.\n", + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(colorFunc)\n", + "volumeProperty.SetScalarOpacity(alphaChannelFunc)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# This class describes how the volume is rendered (through ray tracing).\n", + "compositeFunction = vtk.vtkVolumeRayCastCompositeFunction()\n", + "# We can finally create our volume. We also have to specify the data for it, as well as how the data will be rendered.\n", + "volumeMapper = vtk.vtkVolumeRayCastMapper()\n", + "volumeMapper.SetVolumeRayCastFunction(compositeFunction)\n", + "volumeMapper.SetInputConnection(dataImporter.GetOutputPort())\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# The class vtkVolume is used to pair the preaviusly declared volume as well as the properties to be used when rendering that volume.\n", + "volume = vtk.vtkVolume()\n", + "volume.SetMapper(volumeMapper)\n", + "volume.SetProperty(volumeProperty)\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# With almost everything else ready, its time to initialize the renderer and window, as well as creating a method for exiting the application\n", + "renderer = vtk.vtkRenderer()\n", + "renderWin = vtk.vtkRenderWindow()\n", + "renderWin.AddRenderer(renderer)\n", + "renderInteractor = vtk.vtkRenderWindowInteractor()\n", + "renderInteractor.SetRenderWindow(renderWin)\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# We add the volume to the renderer ...\n", + "renderer.AddVolume(volume)\n", + "# ... set background color to white ...\n", + "renderer.SetBackground(0,0,0)\n", + "# ... and set window size.\n", + "renderWin.SetSize(400, 400)\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# A simple function to be called when the user decides to quit the application.\n", + "def exitCheck(obj, event):\n", + " if obj.GetEventPending() != 0:\n", + " obj.SetAbortRender(1)\n", + " \n", + "# Tell the application to use the function as an exit check.\n", + "renderWin.AddObserver(\"AbortCheckEvent\", exitCheck)\n", + " \n", + "renderInteractor.Initialize()\n", + "# Because nothing will be rendered without any input, we order the first render manually before control is handed over to the main-loop.\n", + "renderWin.Render()\n", + "renderInteractor.Start()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/download_data.py b/demos/tomography/visualization/download_data.py new file mode 100644 index 00000000..aaf58f1d --- /dev/null +++ b/demos/tomography/visualization/download_data.py @@ -0,0 +1,57 @@ +""" +Run this file to download and unzip the data files for the +segmentation demonstration. + +If you have already downloaded the file shale_demo_data.zip, no need to +run this script. Just unzip that file and place the data in this +directory. + +In total there are four files included in the .zip. These files include two +tomography data sets, collected above and below the K-shell absorption edge +for iron (Fe), and a .yaml file for each data set. The .yaml files contain +metadata pertinent to the corresponding tomography data set. + +The data sets were collected by Gabriel C. Iltis at the National Synchrotron +Light Source (NSLS), Brookhaven National Laboratory (BNL), in March of 2014. + +""" + +from __future__ import print_function + +import sys +import os +import zipfile +import requests +from clint.textui import progress +import tempfile + +def download_zip(url, path): + r = requests.get(url, stream=True) + temp = tempfile.NamedTemporaryFile(suffix='.zip') + print('Downloading url --> %s\nto --> %s' % (url, temp.name)) + with open(temp.name, 'wb') as f: + total_length = int(r.headers.get('content-length')) + for chunk in progress.bar(r.iter_content(chunk_size=1024), + expected_size=(total_length/1024) + 1): + if chunk: + f.write(chunk) + f.flush() + z = zipfile.ZipFile(temp) + print("extracting to --> %s" % path) + z.extractall(path=path) + +# download to this folder +current_folder = os.sep.join(__file__.split(os.sep)[:-1]) +url = 'https://www.dropbox.com/s/xpxuy9t2e9f4c9i/shale_demo_data.zip?dl=1' + +if os.path.isfile('NSLS_shale_smpl-2_AbvFe.tiff') and os.path.isfile( + 'NSLS_shale_smpl-2_BlwFe.tiff'): + conf = input('data file already exists. Delete? [y/n]') + if conf.upper() == 'Y': + print('deleting existing file.') + os.remove('NSLS_shale_smpl-2_AbvFe.tiff') + os.remove('NSLS_shale_smpl-2_BlwFe.tiff') + else: + sys.exit(1) + +download_zip(url, current_folder) diff --git a/demos/tomography/visualization/npArray_to_VTK.ipynb b/demos/tomography/visualization/npArray_to_VTK.ipynb new file mode 100644 index 00000000..00c2f2af --- /dev/null +++ b/demos/tomography/visualization/npArray_to_VTK.ipynb @@ -0,0 +1,515 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import vtk\n", + "import dicom\n", + "import os\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt, cm\n", + "from IPython.display import Image\n", + "#from skxray.img_proc import histops as hist\n", + "from skxray.io import vtk_tools" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + 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'/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head/vhm.1241.dcm',\n", + " '/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head/vhm.1242.dcm',\n", + " '/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head/vhm.1243.dcm',\n", + " '/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head/vhm.1244.dcm',\n", + " '/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head/vhm.1245.dcm']" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "specimen_list = ['human_male', 'human_female']\n", + "human_male_dsets = ['Head', 'Hip', 'Pelvis', 'Shoulder']\n", + "human_female_dsets = ['Ankle', 'Head', 'Hip', 'Knee', 'Pelvis', 'Shoulder']\n", + "\n", + "img_path = '/home/giltis/dev/my_src/Demos/demos/tomography/data/CT/human_male/Head'\n", + "dcm_file_list = []\n", + "for dirName, subdirList, fileList in os.walk(img_path):\n", + " for filename in fileList:\n", + " if \".dcm\" in filename.lower():\n", + " dcm_file_list.append(os.path.join(dirName, filename))\n", + "dcm_file_list.sort()\n", + "dcm_file_list" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ref_dims = dicom.read_file(dcm_file_list[0])\n", + "pixel_dims = (int(ref_dims.Rows), int(ref_dims.Columns), len(dcm_file_list))\n", + "pixel_spacing = (float(ref_dims.PixelSpacing[0]), float(ref_dims.PixelSpacing[1]), float(ref_dims.SliceThickness))\n", + "\n", + "#Calculate axis dimensions using metadata from the dicom files.\n", + "x_axis = np.arange(0.0, (pixel_dims[0]+1)*pixel_spacing[0], pixel_spacing[0])\n", + "y_axis = np.arange(0.0, (pixel_dims[1]+1)*pixel_spacing[1], pixel_spacing[1])\n", + "z_axis = np.arange(0.0, (pixel_dims[2]+1)*pixel_spacing[2], pixel_spacing[2])\n", + "\n", + "x_dim, y_dim, z_dim = (pixel_dims[0], pixel_dims[1], pixel_dims[2])\n", + "#Create empty array to which image data will be added\n", + "image_array = np.zeros(pixel_dims, dtype=ref_dims.pixel_array.dtype)\n", + "\n", + "#Loop through all dicom files and generate the 3D image array\n", + "for filename in dcm_file_list:\n", + " #read file\n", + " raw_data = dicom.read_file(filename)\n", + " #add file to image array\n", + " image_array[:,:, dcm_file_list.index(filename)] = ref_dims.RescaleSlope * raw_data.pixel_array + ref_dims.RescaleIntercept\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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E5IMi8pG4KR4hhBASYT9BCJkn9IQhhBCya2j3M/kQgK9CswTlHwF8cwjhA9taMEIIITsC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GdnZ/j6668Nbdjf38ff/M3foFqtIpFIYGdnZ4o/3r17F8lkEp1OB7u7u/j5z3+Og4MD3Llz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OtOHr5eGYl9tNGaBRzwVuOWTcqNlstnE0td6aVMSr/F9GIUhJW0aRs+SRVU6K4XAdnmQZ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\nAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Cross sectional orthoslices of the dataset\n", + "plt.figure(figsize=(20,10))\n", + "plt.subplot(131)\n", + "plt.title('XY Plane Cross Section')\n", + "plt.imshow(image_array[:,:,50], cmap=plt.cm.gray)\n", + "\n", + "plt.subplot(132)\n", + "plt.title('XZ Plane Cross Section')\n", + "plt.imshow(image_array[:,250, :], cmap=plt.cm.gray)\n", + "\n", + "plt.subplot(133)\n", + "plt.title('YZ Plane Cross Section')\n", + "plt.imshow(image_array[250, :,:], plt.cm.gray)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(512, 512, 245)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pixel_dims\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dataImporter = vtk.vtkImageImport()\n", + "_NP_TO_VTK_dTYPE_DICT = {\n", + " 'bool' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'character' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'uint8' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'uint16' : dataImporter.SetDataScalarTypeToUnsignedShort(),\n", + " 'uint32' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'uint64' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'int8' : dataImporter.SetDataScalarTypeToShort(),\n", + " 'int16' : dataImporter.SetDataScalarTypeToShort(),\n", + " 'int32' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'int64' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'float32' : dataImporter.SetDataScalarTypeToFloat(),\n", + " 'float64' : dataImporter.SetDataScalarTypeToDouble(),\n", + " }\n", + "_NP_TO_VTK_dTYPE_DICT[str(image_array.dtype)]\n", + "dataImporter.SetNumberOfScalarComponents(1)\n", + "dataImporter.SetDataExtent(0, x_dim-1, 0, y_dim-1, 0, z_dim-1)\n", + "dataImporter.SetWholeExtent(0, x_dim-1, 0, y_dim-1, 0, z_dim-1)\n", + "dataImporter.SetDataSpacing(pixel_spacing[0], pixel_spacing[1], pixel_spacing[2])\n", + "img_string = image_array.tostring()\n", + "dataImporter.CopyImportVoidPointer(img_string, len(img_string))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold_np = vtk.vtkImageThreshold()\n", + "threshold_np.SetInputConnection(dataImporter.GetOutputPort())\n", + "threshold_np.ThresholdByLower(450)\n", + "threshold_np.ReplaceInOn()\n", + "threshold_np.SetInValue(0)\n", + "threshold_np.ReplaceOutOn()\n", + "threshold_np.SetOutValue(1)\n", + "threshold_np.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(threshold_np.GetOutputPort())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.5,0.5,0.5)\n", + "renWin = vtk.RenderWindow()\n", + "renWin.AddRenderer(renderer)\n", + "interactiveRender = vtk.vtkRenderWindowInteractor()\n", + "interactiveRender.SetRenderWindow(renWin)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "renWin.SetSize(600,600)\n", + "\n", + "interactiveRender.Initialize()\n", + "renWin.Render()\n", + "iren.Start()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/skxray_VTK_viewer.ipynb b/demos/tomography/visualization/skxray_VTK_viewer.ipynb new file mode 100644 index 00000000..1e5ca3d7 --- /dev/null +++ b/demos/tomography/visualization/skxray_VTK_viewer.ipynb @@ -0,0 +1,212 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_matrix = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix[0:35, 0:35, 0:35] = 50\n", + "data_matrix[25:55, 25:55, 25:55] = 100\n", + "data_matrix[45:74, 45:74, 45:74] = 150" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " [ 50, 50, 50, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " ..., \n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 150, 150, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]],\n", + "\n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ..., \n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]]], dtype=uint8)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# An example from scipy cookbook demonstrating the use of numpy arrys in vtk \n", + "\n", + "data_matrix\n", + "\n", + "dataImporter = vtk_tools.np_to_vtk(data_matrix)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# The following two functions describe how the data is stored and the dimensions of the array it is stored in. For this\n", + "# simple case, all axes are of length 75 and begins with the first element. For other data, this is probably not the case.\n", + "# I have to admit however, that I honestly dont know the difference between SetDataExtent() and SetWholeExtent() although\n", + "# VTK complains if not both are used.\n", + "dataImporter.SetDataExtent(0, 74, 0, 74, 0, 74)\n", + "dataImporter.SetWholeExtent(0, 74, 0, 74, 0, 74)\n", + " \n", + "# The following class is used to store transparencyv-values for later retrival. In our case, we want the value 0 to be\n", + "# completly opaque whereas the three different cubes are given different transperancy-values to show how it works.\n", + "alphaChannelFunc = vtk.vtkPiecewiseFunction()\n", + "alphaChannelFunc.AddPoint(0, 0.0)\n", + "alphaChannelFunc.AddPoint(50, 0.05)\n", + "alphaChannelFunc.AddPoint(100, 0.1)\n", + "alphaChannelFunc.AddPoint(150, 0.2)\n", + " \n", + "# This class stores color data and can create color tables from a few color points. For this demo, we want the three cubes\n", + "# to be of the colors red green and blue.\n", + "colorFunc = vtk.vtkColorTransferFunction()\n", + "colorFunc.AddRGBPoint(50, 1.0, 0.0, 0.0)\n", + "colorFunc.AddRGBPoint(100, 0.0, 1.0, 0.0)\n", + "colorFunc.AddRGBPoint(150, 0.0, 0.0, 1.0)\n", + " \n", + "# The preavius two classes stored properties. Because we want to apply these properties to the volume we want to render,\n", + "# we have to store them in a class that stores volume prpoperties.\n", + "volumeProperty = vtk.vtkVolumeProperty()\n", + "volumeProperty.SetColor(colorFunc)\n", + "volumeProperty.SetScalarOpacity(alphaChannelFunc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "vtk_tools.vtk_viewer(dataImporter, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/skxray_VTK_viewer_demo.ipynb b/demos/tomography/visualization/skxray_VTK_viewer_demo.ipynb new file mode 100644 index 00000000..caad02a4 --- /dev/null +++ b/demos/tomography/visualization/skxray_VTK_viewer_demo.ipynb @@ -0,0 +1,134 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:cfc74583554fb9a8f95c837d9fe0b0ae920fb502f89e566b0ab2204c00a88a9a" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import vtk\n", + "import numpy as np\n", + "from skxray.io import vtk_tools\n", + "from vttools.to_wrap.image_proc import arithmetic, arithmetic_expression" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 1 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "data_matrix1 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix1[0:35, 0:35, 0:35] = 50\n", + "\n", + "data_matrix2 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix2[25:55, 25:55, 25:55] = 100\n", + "\n", + "data_matrix3 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix3[45:74, 45:74, 45:74] = 150" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 2 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Arithmetic example #1\n", + "merge_demo1 = arithmetic('addition', data_matrix1, data_matrix2)\n", + "\n", + "merge_demo1 = arithmetic('addition', merge_demo1, data_matrix3)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 3 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "#Arithmetic example 2\n", + "merge_demo2 = arithmetic_expression('A*B+C', data_matrix1, data_matrix2, data_matrix3)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 10 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "# Data Conversion from numpy to VTK object\n", + "\n", + "vtkDemo_cube1 = vtk_tools.np_to_vtk(data_matrix2)\n", + "\n", + "vtkDemo_merge1 = vtk_tools.np_to_vtk(merge_demo1)\n", + "\n", + "vtkDemo_merge2 = vtk_tools.np_to_vtk(merge_demo2)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 11 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_cube1)\n", + "vtk_tools.vtk_viewer(vtkDemo_cube1, volumeProperty)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 8 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge1)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge1, volumeProperty)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 9 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge2)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge2, volumeProperty)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 12 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [], + "language": "python", + "metadata": {}, + "outputs": [] + } + ], + "metadata": {} + } + ] +} \ No newline at end of file diff --git a/demos/tomography/visualization/vtkRender_biofilm_example.ipynb b/demos/tomography/visualization/vtkRender_biofilm_example.ipynb new file mode 100644 index 00000000..8dcfb747 --- /dev/null +++ b/demos/tomography/visualization/vtkRender_biofilm_example.ipynb @@ -0,0 +1,249 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import vtk\n", + "import dicom\n", + "import os\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt, cm\n", + "from IPython.display import Image\n", + "from skxray.io.tiff_io import read_tiff" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "u'/home/giltis/dev/my_src/Demos/demos/tomography/visualization'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pwd" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "img_path = '../data/uCT/'\n", + "fname_demo = 'NSLS_shale_smpl-1_AbvFe.tiff'\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load tiff file as numpy array" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "MemoryError", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mMemoryError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdemo_np_array\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mread_tiff\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_path\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mfname_demo\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;32m/home/giltis/dev/my_src/scikit-xray/skxray/io/tiff_io.pyc\u001b[0m in \u001b[0;36mread_tiff\u001b[1;34m(file_name)\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/tifffile-0.6.2-py2.7-linux-x86_64.egg/tifffile/tifffile.pyc\u001b[0m in \u001b[0;36mimread\u001b[1;34m(files, **kwargs)\u001b[0m\n\u001b[0;32m 696\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbasestring\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 697\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mTiffFile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs_file\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mtif\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 698\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mtif\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 699\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 700\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mTiffSequence\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs_seq\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mimseq\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/tifffile-0.6.2-py2.7-linux-x86_64.egg/tifffile/tifffile.pyc\u001b[0m in \u001b[0;36masarray\u001b[1;34m(self, key, series, memmap)\u001b[0m\n\u001b[0;32m 1076\u001b[0m \u001b[0mkeep\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1077\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1078\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mstack_pages\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpages\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmemmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmemmap\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1079\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1080\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mkey\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m/home/giltis/anaconda3/envs/nsls2_dev/lib/python2.7/site-packages/tifffile-0.6.2-py2.7-linux-x86_64.egg/tifffile/tifffile.pyc\u001b[0m in \u001b[0;36mstack_pages\u001b[1;34m(pages, memmap, *args, **kwargs)\u001b[0m\n\u001b[0;32m 3463\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmemmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfh\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3464\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3465\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mempty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3466\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3467\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpage\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpages\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mMemoryError\u001b[0m: " + ] + } + ], + "source": [ + "demo_np_array = read_tiff(img_path+fname_demo)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "reader = vtk.vtkTIFFReader()\n", + "reader.SetFileName(img_path+fname_abv)\n", + "#reader = vtk.vtkDICOMImageReader() \n", + "#reader.SetDirectoryName(img_path)\n", + "reader.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 0, 0, 0, 0, 0)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reader.GetDataExtent()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0, 511, 0, 511, 0, 244)\n", + "[512, 512, 245]\n", + "(1.0, 1.0, 1.0)\n" + ] + } + ], + "source": [ + "_extent = reader.GetDataExtent()\n", + "print _extent\n", + "pixel_dims_vtk = [_extent[1]-_extent[0]+1, _extent[3]-_extent[2]+1, _extent[5]-_extent[4]+1]\n", + "pixel_spacing_vtk = reader.GetPixelSpacing()\n", + "print pixel_dims_vtk\n", + "print pixel_spacing_vtk" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold = vtk.vtkImageThreshold()\n", + "threshold.SetInputConnection(reader.GetOutputPort())\n", + "threshold.ThresholdByLower(450)\n", + "threshold.ReplaceInOn()\n", + "threshold.SetInValue(0)\n", + "threshold.ReplaceOutOn()\n", + "threshold.SetOutValue(1)\n", + "threshold.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(threshold.GetOutputPort())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.5,0.5,0.5)\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(renderer)\n", + "interactiveRender = vtk.vtkRenderWindowInteractor()\n", + "interactiveRender.SetRenderWindow(renWin)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "renWin.SetSize(600,600)\n", + "\n", + "interactiveRender.Initialize()\n", + "renWin.Render()\n", + "interactiveRender.Start()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/vtkRender_example.ipynb b/demos/tomography/visualization/vtkRender_example.ipynb new file mode 100644 index 00000000..96aeeb9f --- /dev/null +++ b/demos/tomography/visualization/vtkRender_example.ipynb @@ -0,0 +1,186 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "No module named matplotlib", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mu'matplotlib inline'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mvtk\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mdicom\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m 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in \u001b[0;36mfind_gui_and_backend\u001b[1;34m(gui, gui_select)\u001b[0m\n\u001b[0;32m 237\u001b[0m \"\"\"\n\u001b[0;32m 238\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 239\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 240\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 241\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mgui\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mgui\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m'auto'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mImportError\u001b[0m: No module named matplotlib" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import vtk\n", + "import dicom\n", + "import os\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt, cm\n", + "from IPython.display import Image\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "u'/home/giltis/dev/my_src/Demos/demos/tomography/visualization'" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pwd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "img_path = '../data/CT/human_male/Head/'" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "reader = vtk.vtkDICOMImageReader()\n", + "reader.SetDirectoryName(img_path)\n", + "reader.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0, 511, 0, 511, 0, 244)\n", + "[512, 512, 245]\n", + "(1.0, 1.0, 1.0)\n" + ] + } + ], + "source": [ + "_extent = reader.GetDataExtent()\n", + "print _extent\n", + "pixel_dims_vtk = [_extent[1]-_extent[0]+1, _extent[3]-_extent[2]+1, _extent[5]-_extent[4]+1]\n", + "pixel_spacing_vtk = reader.GetPixelSpacing()\n", + "print pixel_dims_vtk\n", + "print pixel_spacing_vtk" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold = vtk.vtkImageThreshold()\n", + "threshold.SetInputConnection(reader.GetOutputPort())\n", + "threshold.ThresholdByLower(450)\n", + "threshold.ReplaceInOn()\n", + "threshold.SetInValue(0)\n", + "threshold.ReplaceOutOn()\n", + "threshold.SetOutValue(1)\n", + "threshold.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(threshold.GetOutputPort())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/vtk_VolumeExtract.ipynb b/demos/tomography/visualization/vtk_VolumeExtract.ipynb new file mode 100644 index 00000000..630caf31 --- /dev/null +++ b/demos/tomography/visualization/vtk_VolumeExtract.ipynb @@ -0,0 +1,245 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#VTK Documentation Examples\n", + "#Python PointToCellData\n", + "\n", + "# This example demonstrates the conversion of point data to cell data.\n", + "# The conversion is necessary because we want to threshold data based\n", + "# on cell scalar values.\n", + "\n", + "import vtk\n", + "from vtk.util.misc import vtkGetDataRoot\n", + "#VTK_DATA_ROOT = vtkGetDataRoot()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "VTK_DATA_ROOT='/home/giltis/dev/other_src/vtk/VTK-6.1.0/ExternalData/Testing'\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# Read some data with point data attributes. The data is from a\n", + "# plastic blow molding process (e.g., to make plastic bottles) and\n", + "# consists of two logical components: a mold and a parison. The\n", + "# parison is the hot plastic that is being molded, and the mold is\n", + "# clamped around the parison to form its shape.\n", + "reader = vtk.vtkUnstructuredGridReader()\n", + "reader.SetFileName(VTK_DATA_ROOT + \"/Data/blow.vtk\")\n", + "reader.SetScalarsName(\"thickness9\")\n", + "reader.SetVectorsName(\"displacement9\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# Convert the point data to cell data. The point data is passed\n", + "# through the filter so it can be warped. The vtkThresholdFilter then\n", + "# thresholds based on cell scalar values and extracts a portion of the\n", + "# parison whose cell scalar values lie between 0.25 and 0.75.\n", + "p2c = vtk.vtkPointDataToCellData()\n", + "p2c.SetInputConnection(reader.GetOutputPort())\n", + "p2c.PassPointDataOn()\n", + "warp = vtk.vtkWarpVector()\n", + "warp.SetInputConnection(p2c.GetOutputPort())\n", + "thresh = vtk.vtkThreshold()\n", + "thresh.SetInputConnection(warp.GetOutputPort())\n", + "thresh.ThresholdBetween(0.25, 0.75)\n", + "thresh.SetInputArrayToProcess(1, 0, 0, 0, \"thickness9\")\n", + "#thresh.SetAttributeModeToUseCellData()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# This is used to extract the mold from the parison.\n", + "connect = vtk.vtkConnectivityFilter()\n", + "connect.SetInputConnection(thresh.GetOutputPort())\n", + "connect.SetExtractionModeToSpecifiedRegions()\n", + "connect.AddSpecifiedRegion(0)\n", + "connect.AddSpecifiedRegion(1)\n", + "moldMapper = vtk.vtkDataSetMapper()\n", + "moldMapper.SetInputConnection(reader.GetOutputPort())\n", + "moldMapper.ScalarVisibilityOff()\n", + "moldActor = vtk.vtkActor()\n", + "moldActor.SetMapper(moldMapper)\n", + "moldActor.GetProperty().SetColor(.2, .2, .2)\n", + "moldActor.GetProperty().SetRepresentationToWireframe()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# The threshold filter has been used to extract the parison.\n", + "connect2 = vtk.vtkConnectivityFilter()\n", + "connect2.SetInputConnection(thresh.GetOutputPort())\n", + "parison = vtk.vtkGeometryFilter()\n", + "parison.SetInputConnection(connect2.GetOutputPort())\n", + "normals2 = vtk.vtkPolyDataNormals()\n", + "normals2.SetInputConnection(parison.GetOutputPort())\n", + "normals2.SetFeatureAngle(60)\n", + "lut = vtk.vtkLookupTable()\n", + "lut.SetHueRange(0.0, 0.66667)\n", + "parisonMapper = vtk.vtkPolyDataMapper()\n", + "parisonMapper.SetInputConnection(normals2.GetOutputPort())\n", + "parisonMapper.SetLookupTable(lut)\n", + "parisonMapper.SetScalarRange(0.12, 1.0)\n", + "parisonActor = vtk.vtkActor()\n", + "parisonActor.SetMapper(parisonMapper)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# We generate some contour lines on the parison.\n", + "cf = vtk.vtkContourFilter()\n", + "cf.SetInputConnection(connect2.GetOutputPort())\n", + "cf.SetValue(0, .5)\n", + "contourMapper = vtk.vtkPolyDataMapper()\n", + "contourMapper.SetInputConnection(cf.GetOutputPort())\n", + "contours = vtk.vtkActor()\n", + "contours.SetMapper(contourMapper)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# Create graphics stuff\n", + "ren = vtk.vtkRenderer()\n", + "renWin = vtk.vtkRenderWindow()\n", + "renWin.AddRenderer(ren)\n", + "iren = vtk.vtkRenderWindowInteractor()\n", + "iren.SetRenderWindow(renWin)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "# Add the actors to the renderer, set the background and size\n", + "ren.AddActor(moldActor)\n", + "ren.AddActor(parisonActor)\n", + "ren.AddActor(contours)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "ren.ResetCamera()\n", + "ren.GetActiveCamera().Azimuth(60)\n", + "ren.GetActiveCamera().Roll(-90)\n", + "ren.GetActiveCamera().Dolly(2)\n", + "ren.ResetCameraClippingRange()\n", + "\n", + "ren.SetBackground(1, 1, 1)\n", + "renWin.SetSize(750, 400)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "\n", + "iren.Initialize()\n", + "renWin.Render()\n", + "iren.Start()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/vtk_surfExtraction_and_volRendering.ipynb b/demos/tomography/visualization/vtk_surfExtraction_and_volRendering.ipynb new file mode 100644 index 00000000..001e2ed2 --- /dev/null +++ b/demos/tomography/visualization/vtk_surfExtraction_and_volRendering.ipynb @@ -0,0 +1,1193 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import vtk\n", + "import dicom\n", + "import os\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt, cm\n", + "from IPython.display import Image\n", + "from skxray.io import vtk_tools\n", + "import skxray" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def vtk_show(renderer, width=None, height=None):\n", + " \"\"\"\n", + " Converts a vtkRenderer object into an iPython image\n", + " \n", + " Note: This method generates an external window within which \n", + " rendering actually occurs. The generated image is then returned \n", + " to the ipython session.\n", + " \n", + " Ref: https://pyscience.wordpress.com/2014/09/03/ipython-notebook-vtk/\n", + " \"\"\"\n", + " if width == None:\n", + " width = 400\n", + " if height == None:\n", + " height=300\n", + " \n", + " renderWindow = vtk.vtkRenderWindow() #Create new rendering window\n", + " renderWindow.SetOffScreenRendering(1) #Enable off-screen rendering\n", + " renderWindow.AddRenderer(renderer) #Create instance\n", + " renderWindow.SetSize(width, height) #Set Dims\n", + " renderWindow.Render() #Execute render operation\n", + " \n", + " windowToImageFilter = vtk.vtkWindowToImageFilter() #Create a new vtkWindow -> Image filter object which allows us to read teh data in a vtkWindow and use it as input to the imaging pipeline.\n", + " windowToImageFilter.SetInput(renderWindow) #Add renderWindow to the filter object\n", + " windowToImageFilter.Update() #Update object\n", + " \n", + " writer = vtk.vtkPNGWriter() #Create vtk PNG writer object thereby allowing creation of PNG images of the vtkWindow rendering\n", + " writer.SetWriteToMemory(1) #Setting eq to 1 enables image to be held in memory instead of saving to disk. This is the desired option since the image is meant to be loaded back into the notebook instead of stored on disk\n", + " writer.SetInputConnection(windowToImageFilter.GetOutputPort()) # Link between output (GetOutputPort) of vtkWindowToImageFilter and the PNG writer (SetInputConnection)\n", + " writer.Write()\n", + " data = str(buffer(writer.GetResult()))\n", + " \n", + " return Image(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "specimen_list = ['human_male', 'human_female']\n", + "human_male_dsets = ['Head', 'Hip', 'Pelvis', 'Shoulder']\n", + "human_female_dsets = ['Ankle', 'Head', 'Hip', 'Knee', 'Pelvis', 'Shoulder']\n", + "\n", + "img_path = '../data/CT/human_male/Head/'\n", + "dcm_file_list = []\n", + "for dirName, subdirList, fileList in os.walk(img_path):\n", + " for filename in fileList:\n", + " if \".dcm\" in filename.lower():\n", + " dcm_file_list.append(os.path.join(dirName, filename))\n", + "dcm_file_list.sort()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ref_dims = dicom.read_file(dcm_file_list[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(512, 512, 245)\n" + ] + } + ], + "source": [ + "pixel_dims = (int(ref_dims.Rows), int(ref_dims.Columns), len(dcm_file_list))\n", + "print pixel_dims" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1.0, 1.0, 1.0)\n" + ] + } + ], + "source": [ + "pixel_spacing = (float(ref_dims.PixelSpacing[0]), float(ref_dims.PixelSpacing[1]), float(ref_dims.SliceThickness))\n", + "print pixel_spacing\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Calculate axis dimensions using metadata from the dicom files.\n", + "x_dim = np.arange(0.0, (pixel_dims[0]+1)*pixel_spacing[0], pixel_spacing[0])\n", + "y_dim = np.arange(0.0, (pixel_dims[1]+1)*pixel_spacing[1], pixel_spacing[1])\n", + "z_dim = np.arange(0.0, (pixel_dims[2]+1)*pixel_spacing[2], pixel_spacing[2])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "int16\n", + "int16\n" + ] + } + ], + "source": [ + "#Create empty array to which image data will be added\n", + "image_array = np.zeros(pixel_dims, dtype=ref_dims.pixel_array.dtype)\n", + "\n", + "print ref_dims.pixel_array.dtype\n", + "print image_array.dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Recorded intensity conversion constants:\n", + "Calibration Slope: 1\n", + "Calibration Intercept: -1024\n" + ] + } + ], + "source": [ + "#Hounsfield intensity conversion constants\n", + "print 'Recorded intensity conversion constants:'\n", + "print 'Calibration Slope: ' + str(ref_dims.RescaleSlope)\n", + "print 'Calibration Intercept: ' + str(ref_dims.RescaleIntercept)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Loop through all dicom files and generate the 3D image array\n", + "for filename in dcm_file_list:\n", + " #read file\n", + " raw_data = dicom.read_file(filename)\n", + " #add file to image array\n", + " image_array[:,:, dcm_file_list.index(filename)] = ref_dims.RescaleSlope * raw_data.pixel_array + ref_dims.RescaleIntercept\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Note that the pixel_array object is a pure numpy array containing the actual image data" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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k3NucGDN2PBhbkImV4SpLL1Hd6/V2rJAUEzgpxBBCCCGEEEJITQZhZTGoAMCD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UQi6Pf7OD8/x8XFBaLRKCqVipXXDwKIkUYdoBsettMQNMPBJliDjGabkbBoe7TfvFxbviCn\n2ZbnfRgbFMCXAt8SD8+fP0etVsOPfvQj3Lt3zywBJARabiviz5Y7Sr5/swWJ74Wk65SfAzu8nVyp\nyjHDAwHzN66kjEejEZrNJs7Pz3F2doZms4nhcPjWiVA2ChoXtEXCdlqLRncFEbS+ttURNP5uI1S1\numVZNuPCVq/NIbAZC3yr3JK+O+T7/gzAX3ielwfwf3ue958DkAP0VhPgd7/7HTzvBnB98OABHj9+\nPAfq2lbDSCNPjiVXIMP3IWuDDOdFHXCXUy31UxjDXSO5pchGLqOPy3GuF3h62sNP25NIrrbbbZyc\nnKBYLKJcLptYMfLYVm5HaKczSftCM2xl+6h8nocD/WFXMGl1Ufl0LUjf2HgM0gNh0troNjpCc740\nolNM6O0mLSlfX1/HbDZDJpPB7u4uZrMZXrx4YY6wJfvC933U63XU6/X3Nl+X9O7pfeqJL774woy5\njY0NbGxs3Nq+/z2v5re0WTRdoYEwWn5JYfwVzQYOks0uec/lMifbNj+Sn1wmSnue1yNlmzZHg+Sl\nlIv0fzKZoNls4s2bN6hUKvjd736Hn/70p2g2m1Zgg/LSigjahlSr1dDtdtHv9zEYDMwK21gshlQq\nNXdwh8tu5X0qXwZr+pi+5fO16YIgQIWXJ/vQRRzwkePFBfS4ygoa+5zvZDKJlZUVrK+vY2trC/F4\nHLFYDNVqFUdHRwagyWaz2NnZwdraGs7Pz/H06VNUq9W3DljhPuF0OkW1WsXXX3+NTqeDeDxuTuDT\n6IMAYgDMHTNKg+36+nouyBWf0HJQ2gaqnKxErkGjGTaa0OPl3MWRDgJu5CTSJv1dDCNbWdxI933f\nxFqIx+OoVCr42c9+hocPH+Ljjz9GqVQyJ5cQcENGERfqtFSSAyu8Ppoksu2uZ0fHTsuVL1QPHXHX\nbDbRaDRwdXWFRqOBbrdrQCPutNkcAtlvGoBA96jtPLCYbYxo9/jR4Is8Vxe/trkRND/C1B8k5F0C\nXColGxhkU6K2e0v6bpHv+23P8/4vAP8JgEvv9287Pc/bAkCvI04B3GPZ9n5/TaVPP/3ULFtdWVmh\neozc4R/Gh3M+ShDGdgIElWUjm5yW8l5eo/RaWpnmtjI/qF5XW+6yzUsrlxvxNqOcTuqjYO5kXJ2e\nnqJcLuPevXvY2dkxR1vz7aS2fgzTd7a36FpwQdtvzVjX+kFSGBtFpteu2ewhGwUZ+ndxXnm/Ubky\nWH82m8WDBw9QLBYNAJfJZLCzs2NOxVhbW8NXX32F4+NjExuCz/PNzU3s7u6aFTFffPHFrXhe0rdP\n70NP/Omf/qkVELCRnM9yHgHz4ITNXltkDodNJ2UY/7bFS+T5bAFyNXkpbSypQ/g1+i19My2tBGK0\nsiidzKOVM5vN0Gw28fz5cwPEfPbZZzg8PDSr5WT51F+xWAzxeBzRaBQrKyvY2NhALpfDeDxGv99H\nv9/HdDpFKpXC1tYW8vm8WWFjs0G5nJMvdjX9LvNKn5bbI1pdtj6TfQR8c8ot3ePfsm+18u5Cmp6U\nzziZTJpA/IVCAel0Gr1eD69evUK1WjW+Wi6Xw9bWllk1eXBwgKOjI2Mf8OC85HtOp1M0Gg1cXl6a\nFVCJRML58v2DAWJ4NGx6INoyX9ug14Sfa6C7DM5FQA05gO46WF0OrW2iuyiM0RlUBoETBK7QVrLZ\nbIZnz57h+PjYADLFYnHuyE7pDGkKwCb4udCV16h8GfOFyru+vka328Xl5SVOT09NwEceyFO+Mbc5\naGGeqZZGrozR2sgFogR4NLoNKBPGWdR4IwoaZ2FAG1e/2gSzi2dZ1rt0Dpf07sjzvDKAie/7Lc/z\n0gD+OYD/EcC/B/DfAPifAPzXAP7d77P8ewD/u+d5/wtulpo/BvCLoHo0o4xvl3QZPIzXtwAY13h0\n6ZagtDbj1FW2CxAK4sFWf1h630AnOdJkA8jVrxSE2fd9s7zY9310u10cHR2hWCyaeCLD4dAEX9S2\nyAbJMtc9btABug6TjgVR2Gs2nmxpbfddaTnvQbyEsSFsafhpUq781J+ZTAYPHjzA9va2CcQYi8VQ\nLBaRy+VM7IdqtYrnz5+bk7L4iYb8ZYwWqHtJ3z1633qC2yiu8ayBBAqvb9236QnXfHsfxHmSq/VI\nFvKVIXwVsdYv/KUmT0O/bfIiCGCQsjhM/wHf+CJ8ayj3NQaDgTmwod1uz62M0MrzvJvVtMlk0hx7\nHYlEUCgUsL6+jsFgYGKRtNttdDodFItFpFKpt+q2jS9pP4eV+VwPanpG2t1cz8k6tT7X6uQ8SnL5\nxra2aoCOLS/xRick3r9/H/l8Hs1mE4eHhxiNRmi32xiPx8jn80ilUrh37x7W19dxfHyMZ8+eme1I\nZDPwF+vkhzUaDZycnKDdbptVULSl2UYfDBAD6HE+iMIYSLaHrk3CoAFjM4y1gagNfhvIo92Tk0im\nd/Gjlf0uBD6VI/fCUzvJ+InFYmi323j69CnevHmDvb093L9/35xmQIY15aVnLGMSaH0ghZcmuIm3\n2ezmyOput4tarYZKpYLLy0v0ej0jiDVQSNviJPs0DKDB+ZD9yLdK8LbwfrY9N6qTjvR2gRk2R4CP\nT5lHtlWjME6frCtI4N6FtD5YGtvfWdoG8G+8m4ceAfC/+b7/d57n/RrAv/U8718COMLNCRjwb+IC\n/FsAvwMwAfDf+gETTxp+XD5JIIbPBZuslcbKbcerC3yRc1GuGpR0lzkj67orqOLSS/J+EHHD2ve/\nOUFP6tLJZILRaGSAbc/zjGFVqVTw5s0bfPzxx9jd3TWnJ/EyNaPVZqwGtYXLO27cBjkpYUAUXq7L\nBrHxBnyjh6QsXuS524x4V72Lls35ikQiSCaTePz4Mfb399HtdtFoNHB9fY1kMml4SKfTqFQq+OUv\nf4nLy0tjdPPA/fS5vr5Go9FAr9e7E79L+lboW9ET2jVpS0o702Z3Er1v8CXIXgvyjSi9XCkugRlK\ny/tA80s48QMtJNn6SpOVtvR0n8cLJeJhDjgfpPvb7baJJ+aqi1bBEIDbarUwm82QSqXM6Uuz2Qyt\nVgvpdBrr6+tIJpNz9rgr4Kztv7TXbdfof9D4DdJVYccMz2urS6axlRfGjuL8r6ys4NNPP8Xm5ibG\n4zEuLy/RaDTQ79/E8abTfFOpFO7fv4/V1VW02228ePFibuUTAfNkJ1B/DodDnJ2doVKpwPdvXuqM\nx2Oz9cxGHxQQQ50l943LFQt0nW8lcU1wKkubFGEEpc25XDR/EIUR4NrEcgnL2yoCbQLJOmjbD18t\n0+l08Pz5cxQKBdy/f98E25MIsm2ViKsPuEFIaQkFbzQaOD09xeXlJer1ugFfqDy+moeXZyMbqBFE\nfNmgfD6aI8CP19byUT9PJpO3jgSX5BLWWpogBRhEtjkh65T3NAXvUsLaWAw795b0hyXf978A8I+U\n61cA/pklz98A+JuwdZA+kPNqMpmYFXD05i/I2eWGtzSGtHqpHNs1WZdNP9mCNmp1hjF6ZB2uODla\nXm2u3oVscodkONf7ZCDx50pxYgiooRVPANDtdvHy5UsUi0Xcu3cP9+7dM6ANxQTjTgfVsWgf23SB\nNIblGNPearqeI/HKY4wtQkHjQ/a/jajfg+YBL1sj19imsgmE+eijj3B5eYlms2kCZRaLRZRKJSQS\nCbTbbfzmN7/BmzdvjI7nQBu3MTqdDo6OjtBut528L+kPT+9bT2h2ic355T6G5iRrZYeRj3e1t94l\naQdXEEl7VdOTVIYL5LDZtfKeC0jgJHmQYSt4GdfX1+Yoe06yjkgkglQqhUKhgEQigUgkYkDg8XiM\nVCplnH+KQ0W6iECfIN1tA0K4rggaQ2H9D1kOD3GglSWvy2cvyWbf0D2bjyzbqNkV6XQajx49woMH\nDzCdTnFxcYFarYbr62tz+AnJ+idPnmB/fx+Hh4c4ODjA6ekphsMhALz1XEiPTiYTnJ2dod1uG591\nOByakzVdffxBATEUCIk/HG0rCzcO6O0ZFxbaQ9YcP03AuBxIFxijGZqcZ83osQl4m5Nt408TcBqP\nrnwuChISHIWm/Zb1eh1XV1d4+vQpUqkUMpkMMpkMstks0uk00uk0kskkksmk2ZsZi8UMX9yBIBCF\nlqePx2OMRiN0u12zXLDb7WI8Hs+tcuFbj7gRbhP8fNzYnKygfrQ5WrbfQfcAvPU2QD5vOT5tgA7/\nfVsHSwN1whjqvK5FlK9NqclrYRXVkr6fRHJiPB7D8zwjI/jKCMBuiEvgJcyYDiKSOUGOsa0em14I\ncqBdZfwhSOObywC5rJtvMSGDajqdYjQaYTgcIpVKAQB6vR7S6TRmsxlqtRq+/vprpNNplMtlPHjw\nwOiCZrM5Nw7elUMkl6XbgD3N0NZ0gO/7RteRLpRl8LrD2C6UPyiNRrdZZSjHZhDgFYlEkMlk8PDh\nQ3z66ac4Pj7G0dERPO8meGapVDLLz3u9Hr788kscHBxgMpkAwNzLFbIHPe/mWNKLiwvnSRhL+nAo\nCHC0ATDvCjQJOye+DaK6yUGNRqNqgHOZR/ahlHt89fwiOiqIV+kParKPPy+yBQi419pOPMdiMeTz\neRQKBcRiMWSzWbTbbXz55ZdIp9PodDpIJBLY3d1FNptFNBrFZDIx9fAyJUm/1Ma3zX7nZdv8uiDi\ngJsrPedT2ueuODhhyOVTE0WjUfzJn/wJnjx5gk6ng0ajgU6nA9+/OY6c5uVsNsPq6ioePnyIer2O\nL774wsR6AWBewFGZfEy8fv0al5eXpqzhcGhe0gTRBwXEAN8oZ+k4awPJFc3ZBsLYHGztmm0Aafc0\nQ1/7H8Yo0vgN4o/3kSZEtd+2a1qdtmVbsu/4KhnP8wx40ul03mofgTb8Q8qBnj0pCHq76TpWmisE\njnBKQegSSi7wQv5eZNzYSD6vMMCExo8mRCXoIuvV/gcBea6xorUnyAF5F7Q8LenDJVKytAJCGlrS\nGLKVcRfDW45vW71hQZ5F50gQkPM+t+2FnduaTJL56b40cgmcGY1G6Pf7yOfzSKfTqNfrmE6n5m3Z\nxcUFUqkUotEoSqUSHj16ZHRHp9OZ2wPuAgeCdLyrDzSiccBXP3IifUYvEuLxuPWEEqrPZRjbdITG\nl5b3LuPF5UzIemKxGAqFAh48eID9/X2cn5/j+Ph4TpdFo1Ekk0lcX1/j6OgIL168wGAwMP1JL3/o\n43keRqMRqtUqarWasStardat27Sk7xdJWe+S/9L2CZLNYWXGovwG1ePKa7PtuAyhdNy2DkNcx4UB\nbzT+gsqnb00mcuCI1zedTs0KCapHhr6gLUnFYhGZTAbxeBy9Xg9/+7d/i5OTE6yvr+PRo0eIxWLm\niGQKHEuAOdcX2upBCSJJvUf5qH0A3jqwhKfXfA1tjGr9FNTHWl4Zv1LjhY8d4l/yaNMBpAfK5TKe\nPHkCz/NwdnaGwWBg7lGZ+XweH330EdLpNJ4+fYrj42NUq1Vzqh4H5cm3BIDxeIxarYZqtWpe1lEs\nobA7JD44IIaviuFAizaIeSA+lwNpA2FcoESQIXFbCqrbVq/M5yrHRbQkSxpq2vJp+s8Fs8s45OVx\n45MQZNuzcikLXh7nS0ujCSZ+X/tto7BKdxGBdxuSfEjw0QYcLTouXOmDwBZZf9hyb0tS4S7pwyYa\nY65lyDaD0aUDwpAGhHKSRskiZbtAjiDwRUvr4k3e15wUnsZVj4u0OFq2vFznT6dTjMdjDIdDc7zx\n6enNISmJRMKsgDo/P0cikcDjx49RLBbx6NEj+L6Pw8ND9Pt95xswzaAPapdcmi51GRmoNP749lKu\nH8moj8fjBliSfHGetFhkEsTS2heGbCCZLa3mfGpvf3meRCKBcrmM/f19rK2todls4tWrV+j1elhZ\nWTH9SluaLy4u8OzZMzSbTQDfrHYlO5HHhWm1Wmi324hGo4jH4ya+wJKWBMzLtKCA7MC8Lfyu7BmX\njfYu6ggLgGi60CZDbHrEZSvze7fRGfw5BTn0HEiaTCYmPgz3bzglk0kUi0Wsra0ZAL/VauH8/BzV\nahWe52FzcxO+76PVaqFcLiOfzxv5VKvVVPvTBo647tN1CRhpst/VD9o1qY94f0g9x/tyEf9H01eS\nL83vi8fj2NrawpMnTzAej3F2dmZe2lNfpFIplMtlrK+vI5vN4vT0FL/97W/n9DkPzCtB+aOjI9Rq\nNQyHQwPCuFZKa/TBATGADgZosWLonkuo2Sa/HGhhAJig9EFtsDkCtsnmIhtI4wJqPO+bY9Rkn2kA\nRliHXusLLky07WVBQpn3SVjFpLXZ1Y8auLWoErwN8CKf1yKCVToyGtgon2WQkly0n2/jvGpKSc6N\nMICPFOrLIL0fNrmMY03m3hZAkBQkqyVfYZ3b28ggFx+L1C3T8//aHA0LaMu+4NuJiTS5xnnhW059\n/2a5cjabfYvnwWCAk5MTTKdTPHjwAGtra3jy5AlmsxkqlQq63S76/b4xxDSgTDNOqV66J0914nJY\n9o1sP6UnAAa4AZPoNCi5nFyePCTLln0ldcBtdJQkWzk2Xjg/8n8qlcLGxgbu3buHbDZrYjnQqUgE\nUK2vr2NzcxPD4RAHBwe4uLiYWyELfBOcl7ax9Xo9dLtd88Z6MBjMvRlf0odL3KmX8V/o/iJz5a7z\nymajhyEXry6+ZPlSrmj+CMkSDYDhdXKZI18YLqp3ud6QukfKPE3ejUajt0B3Sjubzcw2pLW1NWSz\nWcMvgf2TyeQtOdxqtdDpdLC7uwvf91EoFNBoNOb44rzafD4XaX6Yq7+kbud9rdnagH4Cli2tVqfL\nbwqaQ/x+LBbD+vo6fvSjH6FQKJhYL4lEAslk0nyvra1hb28Po9EIv/nNb3BxcYFmszkXtoKPO7Iv\nBoMBrq6uUKlUMBwOzSoYfoqWbK+NPkgghh/5K4MwAm87nxoyFyQ0bPckuQSIy9AJCwCEHbQ8r2zj\nokCFaxBqfemiRfsuyIiU5d7WKbHxE6R436XxGpZsbVzU8LXlWYQHG4Aj5w93ElwGgassrUzXda38\nb/M5Lem7Ry6AhTEUYvsAACAASURBVKfRdIVWTti56AI9whpRtvxa+WEAkDDzxmZY2Yww3h4NlAgy\n0G2/pTFIy7H5SRh0nYAI/vYxGo0inU4bw4rKJwPs7OzMOOvlchkff/wxUqmUMaZrtZrZ4hLEK79m\ns0F4X/L8WpnkHNBWXOkchrUrbmPoh0mr6WJXG4PK5X0Vj8exsbGB+/fvI5lMolarIRqNYmNjA9ls\nFqPRCI1GA/l8Hvfu3UMqlcLBwQFev36NXq9nAm+T7iHwCoCJG9ftdg0gQ0E1l/RhE59fGghDtKgt\nHURh5Paidd+Fn7DyQtuSIsEW6ktXXe/Cfpd6m+uMsPpavsRPJpMolUomCDjwjZyj1RWDwQC9Xg/D\n4dDwcHp6ikKhgHK5jO3tbQP6Un7+zcuU/10yNqx8tqW3lW+rT+svW3ukbgrS9ZIXktupVAqbm5vY\n399HsVg0J91OJhOk02nE43Gsr69jY2MD8Xgc7XYbZ2dnePbsmQHKfP/tQO0EyHe7XVQqFbTbbQPA\nDIfDt3aDuPqI0wcJxNDDot/a3jPgm1UX8mhlm1EtUUHNkNSMLZl3UTRNTj6XgaUZYrbfQXVq1/h2\nLldazteiYIusUzPUb2NALsqXJhDlc3iXQM8itGi9NuPcBqCEGT9BCkH7z8EX7Z5LGGtzgP7LOUz3\nbHPY8zzjgC3pwyXpENscYZ5OK0MDImQaTmGc9ruQS3cFObyURpujrrw2Y8zWby7epfEl57RMowXI\nlPKEAjBeX18jnU4jkUiYLUsE4NCKkvF4bJaXT6dTE4uEnPOzszOcnJyg0+nM7e2nOvlqGcmnS+fJ\ndmr/uROj6Sj5zIK2cskxH6Qr3ie5DHPaCrC+vo6VlRUTbL9UKpmA/Z7nYWNjA7u7u0ilUjg+PsbL\nly/RbDYNUEc6iANZ/X4frVYLjUYDzWYTnU5n7rSsJX3YxAN38s9txsYieWwy9bZj0gWC3qZMTc9Q\nOTYAU5PhQXomrI6U5blsRrom+fS8G8A3k8nMbU+i9NFoFNlsFqurq8hkMkYO0+lI2WwW3W7XlHV9\nfY1isYhkMomjoyO0Wi08evQIf/Inf4LNzU3U63VzopJsh+YruvxATa7z/y6fhv+WLzpcfR2GL42/\nML/5Nc/zkE6nkc/nsbq6iq2tLWSzWZyfn+Ps7AwAkM1mUSqVkM/nsbm5iUwmg0qlgoODA9RqNaOv\neQxQDrKOx2O0223U63VcXl5iPB6bFbAEsNl4dNEHCcQANwF24vG41Znk30RhDVS6FhYgCAOC2O5p\nzqqNV+kkB7XFBiQsAjC4JtB32YBZdCJ9l9pyG4M4TB6Xs+ka20GKTpbtmgNB123lLNony9gwSyLS\nZGYY8IDn02Q0lWNzaLU63pez69Jti9RtM/RchltQX2q6dRHiBiStbiAwhBvaZGT1ej2USiVcXl5i\nNBohkUig3+/PBXKPRqO4vr5GrVbDbDbD+vo6CoUCisUi4vG4CdD4+vVrXF1dqU6HDajmPIclbijz\nay7DO6jPXM/ENrYXtQtc9peNJ3k/EokgnU5jZ2cH5XLZBLukt5O0QimRSJg3pdlsFm/evMFXX32F\ni4uLueXkHHCLRCIYjUa4urpCrVZDo9FAt9t9yzFa0odNEjgA/rA24bvQGzY7jtOibeT9xF9Wa/cl\nH7exyV2yJEhuSfCB0kQiEaysrKBcLqPT6ZiVj5QmkUigUCggn88jHo+b+mazGXK5HP7qr/4Kh4eH\nWF1dxf7+PiqVCiKRiIkf8+bNG9TrdaTTafzpn/4pstksqtWqWR2jAUO8TS4bXbY/KDYOpbWVYwPK\n6JoNmJB2um28ar6orD8WiyGTySCXy2FtbQ2rq6tIJBLmRMPT01PMZjPs7OyYFZMrKysYDAZ4/fo1\nTk5OcHx8jPF4bPqX+ocAVgBGD1QqFRMn7Pr6Wo0LJ/Vj0Nj9YIEYojAGaNgy5KCSxoU0xmU6F3IY\nlh/NIJNlaHxpk1nyaSOOmC5C78upoLKDDDuZdlFD3yWgeJogR0IDDYJ4ICG3CIDiuhYE0Mm8QXxq\n48sFxGmCeNFxJcespngWdSaX9GGTbV645KuWl39cFGRAfdsUVva78tIc5oFktbxhgFau37jjLHni\nxA0rGbOF7tOpQs1mE/V6Hfv7+8bQjkQi5o0XrYwhUMf3fVxdXWE4HOL8/Bz7+/soFArI5XJ4/Pgx\nPM8zAV41GSRlnAZQ3IXCyjyNwmy5ua2zabOFFslLQMnKygp2d3fx6NEjpFIp9Pt9dDod9Ho9E2Q5\nmUxifX0dq6uryOVyOD09xZdffomTkxMMBoO5lbwExAA3xnez2USlUkGtVkO/31edoSV92MTtjbvO\nWZtTK8lle9lsrTC28CLXw/LEy5DHT2vblBYhl91us3OD0kidQs+XbG6SJ81m06yYBG5WRmUyGRQK\nBaRSKdNOii81GAzw53/+5/jkk0+wubmJYrGIs7MzvHnzBpVKxcis4+NjfPHFF/in//Sfolwuo1qt\n4s2bN2g0GtYtMIvYyjYfT8tP5Qat1pQ+JL+m+Tgum9/GCxGtVsxms8jlctjc3ESpVEI6nYbneWi3\n26hWqwBuVsEUi0Xs7++b/L1eD69fv8bx8TG63S4Gg4FZEUm8kH7xfR+9Xg/NZhO1Wg1XV1cYDAZz\neuMuehb4wIEYerMlhQJ1LiljG0nEVCM5mLQtS2EFuDbRwk6MoPwup3gRuq0wdZV3F+ckLFCh/Q7i\ngZcvnYsggMJ1bREw5LZ02z61CX9NsGrlagaB5pjY6ggD/NiOnaePa8xz52xJS+LEZb08SlKCLHKc\nhQFi/hgBwEXlsG3OSXlgA5o1uRFWbslTEHl8GN+/CW5Le8W3traws7ODer2ObreLeDxu+PH9b46K\njkajmEwmiEajqFarmM1mZmVMuVzG3t4e+v2+OU2BO/u8PJtcXUSPuNLJscrr0d5a8rF+V+dMyyPt\nH5sD4Hr+5PTcv38fe3t7yOfzJp5Cr9dDvV5HJBIxMRfu3buHXC6H8/Nz/Pa3v8Xx8TEGg8EcsMJX\nw0wmE1xdXeHy8hJXV1cGhAnjJC/pw6R3NRbknLDND9s9Wznviu4CmtiA6LAvK1xl34U3Xo6UT1JX\nEQhQLpfRarXMNnbaHpnL5eZWwwAwW1aj0Sh+8IMf4N69eygUCtjZ2cHq6ioqlQo2NjbQarVMes/z\nsLe3Z2JcnZycmFV5w+Fw7lhlbt9qPgXvn6DTFqVfG8bX5W3VwBsJtNjAQs4XEYF3sVjM9HEymcTG\nxgZKpZIJrN/pdMwqpel0ilKphP39fSQSCaTTaXQ6HROYvVarodfrYTqdGh1AW4bJ97++vsZgMMDl\n5aWxBQgsk7F7bCCSS4cSfdBAzHQ6NcF3OMm91drbG35NDjaeVhuIkjTHUCPbfZeR66pPQykloODi\nxTahNADI1R5XPVy4yIlsq09eD0uu/pX1an2n1cnTLeK0hFEmWnlBQAdPFyQIXX1tK08T3vx30Lh0\n8aTNQ86XC2BxGTKSlvv+l0TkkilBhjJddxmYWpyQd+n4vk/S5FSQrJdpNLmpGXG2fFqdmjHoMlJ5\nEL7hcIhqtYrz83P88Ic/xN7eHl6+fGmcc8o7m80wGo3geTcxYtLpNCKRiIk1Qm/ZVldXsbu7i8Fg\ngDdv3mA8Hht++bN3ATKy/7R2uvpYI5v+spWtkWYLvSuSzg8nel7FYhEPHjzA/fv3MRgM0O12kUgk\nzBHdiUQCKysr2N7exkcffYRisYjj42P88pe/xMnJydx2M14uPefBYIBKpWJOw+JvS5f6YUmcwsrm\nMHMuLAXZ6IvWf5syJNn0oy1N2PoWybNo+RrYYNuyQ20iWZHL5ZBKpTAYDAw4k8/njT6Q5Y5GIxwf\nH2MymaDX6xkwplQq4S//8i8RiURwfHwMAHj06BG2t7eRTqcBANvb28jn82i1Wri6ukK73Ua320Wn\n0wm9Us/mQ2n2NF0Pe2CGrMclwymvC7zg5RAAs7q6ikKhgK2tLbOQIhaLoVarod1uYzwemxOraJXM\n2toahsMhnj9/jouLC5ycnJjA7ARk0UrXWCxm+Li+vka9Xp/bkjoYDN7aluqyA21+iaQPGogBYN5s\nyY/v+3NvijiKGOQAysHHBxoNvDACKyy5Hr68Jnnh94IMq7DACq+T3wvr1NvKDQsSvQ+yCRuXILKB\nXEH0bRh5Np41XvicsN2Xv+UY5+W7HE3pkASBbJw/z/PmFJHkRQNyZPn86NIlLYmPQ81x5mmIbODC\noml4Xd9Vuq3R67oW5CyEARlc38B8zBr+bIGbI6oPDw+xs7ODra0t1Ot1DAYDc/KS53lmDzqAuWXp\ntEx9PB6jXq/D932Uy2U8evQIzWYTV1dXKuCt/ZdAEl3jK2lsbQDwVjrKL8ugvHyLAF+NJPUczx+G\n+BiW5dr40Yx46gs6keTJkyfY2dnBcDhEpVIxDhC9MZ1Op8jn82a7WKVSwd///d+beAD8TTI5VsQL\nna5Ur9cNYKPZR9/lubmkb49sdgsn14uuu9h8Ntvs2x6bLrkmZdoitr8NILgLuXQEyQMpezU9T2kp\nTgltS00kEuruByrv8vISrVYLR0dHyOfzWFlZQTwex6effoof/OAHyOfz2NjYQDKZhOd5yGQySKfT\nKBQKKBQK2NzcNC8OLi8vcXJygsvLS3S73bdW61K9tn6LRqNz8o23TeoQ2RdS9/i+b06ak0CLDJhP\neob0Dtnd/PQxkve5XA4bGxu4d+8eIpEIarUaRqMR+v0+ksmkWaGSTqextraGjY0NFItFTCYTHBwc\noFKp4MWLF+j1euZFK62E4W0gvsfjMa6urvDq1Su0Wi0MBgMTR+x9+HEfPBBDZ74Dbzv8mgDQjEbN\nULEJRm1SvyvhwnmyXbstOLBove9KyWjkAgzeFS1aXlD6IGDhXdG77IPbKEvbcw/qH2nI8Pptc0kD\nFsMYQK6yvw0QbEl/PKSdtkOkgXv0LQ0a+q19f5doUbCdp3UB8Rrdpf2abtZAWP5bM0a5gUz3p9Mp\narUaXrx4gZ/85CfY399Hv9+H53lzsWJisRg8zzP2Qzwex2QymTsI4OrqyhjQ6+vruLq6CtU2Lt+0\nZ+KSW7y9NmfItorX87w5g1iSlLFB8tI1Nnj9rm3gfP6l02lsb2/jwYMHWFtbw8XFhXlbGYlEkMlk\nzCcej6NcLpt+/9nPfoajoyMTyPf6+vqtwLzT6RT9fh+Xl5c4Pj42ARltoOuSlgSEW00cNq+8Fqac\n28jSsPJ6kTHP54kEIVwv6lztlek0oFbWE4ZPqYe5ridZ4Grf9fW1WY0SjUaxsrJiQBV+ihbxxk/K\noyOQe72e4SUWixl5lEgkzPYbCgRfKBSQyWSQTCbNaUyRSAT37t3D/fv38etf/xpff/31XHgN/iwk\nEdDiGqvUBgJreDriM5VKGd03HA6Rz+eRz+cBfPOSgmJ5xeNxE99lOp1iMpnMreahLV7RaBTJZBKp\nVAqlUgnlchnRaBSj0Qi9Xg+NRgOz2cysfEyn08hkMqavhsMh3rx5g7OzM3z11VdzpxpRm+m/XAk5\nmUxwdnaGi4sLNJvNuZg8YcfYonrigwdi5AQJShu2TEJTXQL6XRg0WpqwvGpos0SuebmuyXrXgFta\nmYuAOXc16m1KyeXchwEcbArmXYFgNhBk0bySPy2NC4S05dfKts0J/sxpTLnaxuvW7ocBx2Tblqcl\nLSksyXFqkwPfRcDlfVEYWfC+6nHpCimruEHMQVy6PplMcHh4aPbnl0olE0+E0qXTacRiMYxGI1Nm\nOp2G7/sYDodmiwy9eeMGaBj5r+kO1ykUWlopV+m6tsoGgAGZyDCV9WjXFmmDfF5aWZqcj8fjKBQK\nuH//Pu7duwff9/Hq1SvUajX4/k0wxWQyiXa7DQDI5XLY3t5GJpPB+fk5fvWrX+Hg4MAAMPQMyJmh\nFUGDwQC1Wg2Hh4dotVqBS/2XwMySlvQNaeCLvMaJ5qAmZ7Sy6dtmq2pksz2JJw7Ecpnk2pIzm83Q\narVMnKlUKmXkO28PlcFjimmxxgj4mU6nGI1GGAwG6HQ6mE6neP36tQE9+OlAm5ubKJfLyOVy2Nvb\nM4BEt9tFo9FAu91WT3eLRqOIx+NIpVJIpVJIJpMm3gzxTUHO4/G4AZdGo5HRf/l8HplMBqurq8hm\ns/A8D6PRCMPhEGtrawZ0oa1CFEuNr0ChvqLVLPSiw/NutvsSAEI6lbYfxeNx5HI5lEolA4BlMhlE\no1G02208e/YMlUoFb968MStZuH9K/U7PnviYzWYm0DvVNRwO507Uuy0F5f/ggRgAcychAPY3m9xg\n0+4vQppw4E4oJ5sQk/SuQZBFKCxAtGh5i74ZuA29i367y9uPPxTJMRgWyHEBONqc4fd4HhuAx50l\nG9gj+dXqdAE32hxebklakiS+UkIDEAH3cuuw+iEs4BxE7wrgvW35dwGCb8MLkbYcW0svdawLfO73\n+zg4OECxWMTDhw8xnU5xdnY2Z0zSyhd+rDVtb6T965FIZG5VBa+bbA8XcdAoCIDR9CVvryaD+Usj\nepPLeeIvljhPdM12NLfWv7xOF2+8Horz8uDBA6yurqLf7+P4+BgnJyeIx+NYWVlBIpEwfUSxBFKp\nFC4uLvCrX/0Kr169MoAZd4roQ0Z4pVLB6ekpOp3OMmD7khYmDYxfxEfQ7CDtJeGiZWnX3oU9LYGW\nMACMSzbw44KBeaBcI5e9R9ds8oU/H56X25186wylmUwmqFarePXqFRqNhnHsCUDhW1g0GULl0DYY\nmw4isIADNN1uF7VaDScnJ2bLTrlcRrlcxurqKv7sz/4Mvn8Ti6ZaraJarRpAhlZx5vN5FAoF7O7u\nIpFIwPd9E4ycVpiMx2MMh0NkMhmUy2UDqnAQm/iOx+NIp9NIpVLwfd8EzB2NRma1KK00JDAGgAFQ\n4vG4KW9lZQXD4RAAzAlR5XIZmUwGiUTCHEFN27+Gw6E5ZarVaqFSqeDq6srwr41Heiakm+mZEghf\nr9dRqVTeCuRuG3caLWrPLYGY35PNCKB7fDK6gBItyBN/KLYTXXham1N8FyPbldcFeoRx0O8q3DXe\ntIHsErjvixZxoOTYsCHxMp9WZtjnrIGHQWVJB5J+8zeltr62Gf6asWHjxdZH0kjn+aUzzNPyOeMy\n8LV5x9MsDe8laaQZmUSaIafJS5ch6bp/G16DyCVfbPLONmfD5H2fMlwz/oPKd8kcWQ5tUXn48CHW\n1tbQaDTQ7/fNfR7sL5lMIhKJoNvtGqMykUgYw5xAl8lkosabk+3S7tuenUuH2tqvyWJtPMs6eH9r\n/QdgDqAJq89knbFYDKVSCXt7e9jZ2UEikUCtVjPBEz3vJlYPvQmm7V8bGxvwPA+vXr3CV199hcPD\nw7mjRgHMvQXnIAydSrIIKP+u5u6Svv+kyUL67QIcALvvEVSXy0YMAkJleS6wxdY2/l+uPLF9KI+t\nvdzuk76ZC/iS9iUP1C23a0oQyPdvYodUq1W8fPkSV1dXZnsjnbhHQcSz2azZbsnLpNWGVLfUA7zN\n8iUlj0lG24C63S6q1SqSySSy2SxKpRKKxSKKxaIBXAg4oa20pJfS6TRmsxmm06kJOEwvDFKpFHK5\nHDKZDIrFolnZORqNTFsHgwEAmPg46XTa3L+4uJgbFwQCUT9L+RuNRs2qolgshkQigb29PcxmM7O6\nhlbtTCYTnJyc4Pr6GrVaDcPh0PBD9fNnRoAWkQzeT6uP2u02zs/PTRBk23xcZM6FpSUQ83uipcM2\nRzJIIAShrjZgRZbhepB3Ufg2oUzXghRAmLK/Dfo2QRgX2Z6lRov2j02J8brkth3Jx22fiU35hb0W\ntB0vSFBpQSSlsrcZFrdxft+1I7yk7xdJoE4egUwfMqi0E/dsBqpNL7xLnjVadNzbHPMwFHZe3WYe\nLmIQ8W8XaMHbOZvN0Ov18OrVK+TzeRSLRWxsbJjlyvz4StonL5dA0753Mj7JOOeghqb3bXaDy9mR\nFGaVkOyzIMeMeA7aosRlN/0P0pH8JUAqlTLBGfP5PEajEc7OzkwA5Egkgnw+b46JzWazWFtbw9ra\nGsbjMQ4PD3FwcIDLy0v0ej1MJhMDhPHnQDEKarUaTk9PcXV1pS5Fv62BvaQPi1x2u6YL5JwLmlO3\nGX9SJkniNhal04B3CQhoQIwsn6+ikzKY680g0JjXL9vF07r6SMpTvqqPyyrpuFNd3W4Xl5eX5uhj\nkv++75tjjmk1iYzRInmQvNvsBFdaAhnG47EBE+r1ugFZSCfRNqR0Oo10Oo3BYIBsNmu2z1Kcl2Qy\nadpOAI3neUYe0vYhAkao/ZQXgGl7KpUy8Vd93zcn2MXj8TkwhrYsEVDExxgFTe90OhgOhxiNRiZm\nV7vdhu/7JvguX7nCdS+32Wi1Fcl+ijfTbrfRbrfRbDZRrVZDnT4VRIv6E0sghhFNSkBfBszTAW8b\nbzaHU17n1zSDyyV8eJlh/we1WcsjFYSNOHIcRkm42ibRann9j8UIksY1v86/+e9FnqFNUXIKUugS\n1CAiY1UqUJshagNoNHBI/raNbf7NY7YEOQk2B8vGC+djuS1pSTaSip3Gk9y2pI017vh/WzIsLLji\n4sfmMPB7cl5r8i1MfbyPguarq222/pdpqJwgGUrpKGbIJ598gr29PVxfX5s3fsDNOEgkEsaoJLq+\nvsZ4PDYnX/AAjpJnrW9sYJG8J9stTyaylWGjMHI5TPn0ttO2SlimJccslUphc3MT6+vriMfjqNfr\nJiAvHRWezWaxsrKCtbU1RKNRrK2tIZPJoN1u4+XLl3j58iXq9bp5i8qfFT0HOmb88vISl5eXaDab\nGI/Hgf0T1FdL+vDIZZfQdRtYYQNItDKkPtH4CLI7pfzmKz94uYva80E8ax8qwybbgmy3RUnashwM\nsoFR4/EY3W4X5+fnODk5MXKIvzQkWcdljca7ppPk1iebvpUkZT7Zsf1+H+1228hUAjxopQkBNdFo\nFJlMBqlUColEArFYzATTpbguBJDQ9lqSn1QW9d1gMDA2Eq0GisfjZttnNBo127YoTtdsNsN4PDaA\n0nA4hOd5RmaPRiOMRiOMx2MD8FA99HJDrhrithr5DvSMqT+ur68xHA7RbDbRarXQ6XTQbDbNihqt\njxfxqTmFHbNLIIYRj/As90hLIgDCBmDIdJzCGDraJLYZumEFsotuO8hsyK8kW+CrIMNOpuO/79ru\n2wBYQcIxDD8243VRo/kujp10fKQS4IG7uOF6m/p4XpsjRNeI5JsSPs44/1pdsix+Xd5bgjBLchF/\nqyL3i3O5p60+0P6HpUXnmWsuhK3DZtxrxqmsMyz4o6W1landd8noRWSzZhBLA53aOx6PcXZ2hnK5\njIcPH2Jvb8+spODGN1/RQQF6+WkNNl2g9aurH8K8rZMOh+3ZacCVzRFz6eogHab1N09DAEyhUEA6\nnUY+n8d0OjUrWijmTjabNUvuC4UCSqWSiTFQrVbx9ddf4/Dw0IAq0qbjx5NSTAA6HcOlB8LYJUv6\ncMklczRQm//ncyQsIBP2nmveSefVltYmr6U9J4EcKU/D8BKmnWHs4rBp5VZ83g90PHSlUjGxQ9rt\nttMO5kAvlcf9Sa0fNB8R+EbOcx41GS71Atnb/CUmT8tBiWQyaUATeqFAQAwBKfF4HADmVpTQdeKL\n7HN+jeogHciD39IqGx6cdzQaGcCH9KoMps/Hl2wf8cF9BeKX+mg8HqPZbKLRaKDVaqHf76Pf75ut\nSHwMBM0zbQzYbJCgeb0EYgQFgQqa86qBMfw6n3zagOLlSlrU8belDTO4eH1hjHga+La6NJ40Plyg\nk+a42wb5IiCMq5xF8mi0KKBCacKCQnc1/rS+14xv6nPXEnfNeXGlsbXB5mxJA0GOHzmnJC82J/I2\n82pJHx7J5a2c5Djl120Gl8wfhm4rP8LQomDKXUnqPc3AtPEXRjfJ/uZGqtwqw9PJVZ1SnnQ6HRwd\nHaFYLJq4JbVazSxtBjB3BDMZkbS8mgck1HgNQ2H1g9b+MPlcYIp2j8tmm8635aX/dBoIrXJZW1sz\nq4oo4GI0GjVL7fP5PFZXV1EsFs22JHo2r169wunpKbrd7tzycr4VaTabodPpmOdWrVbRarXmAjCH\ncXQXtTWW9OGQza50BZ7lW1uDypPkAgV4GgmWcPtd01fcAZb8aHJM6kMNiOHptfnmkoma7gjKI+uT\n+TjIIe3FVquFarWKs7MztFotsypD6wP6T7LG5vtx/uWztp2Ix9suZarWL7b2c13I483wdNqHr4wB\nMAds8P6glS/Ur3xrE72YoJcWGr+2XShyHPG0VIdc1SVjEc1mMxP7pVqtotlsmi2rtELH1vechzB0\nGx2xBGIE0WCSHSgnLBGfHDQAJMkHIhG7IIMpCKgIMqyIL1c6G5BkI9fkDxKMUsBrbZWCxkWLGrSa\no38XspVhK9f2zGzPXKvvLmRTTFqfhAE8tDbJuWIzMKRSBuyxDTh/cl8zb4ft/9JwXtKixI0W4G2j\nRpuvfKzLvNIws5E0ZDlpBqg2X1wk9ZFWvu1/WNLmqIsPmwOjyVcXTzbQQJYtnyHl0XieTqeoVqt4\n8+YNstksNjY2EIlEUKlU0Gg0EIlEzHJuMkZp7NBRoJ7nmTePGr+yTptetrWXy0XXeLA5P8SzHJ82\nGa+9qdXy0HVuIMdiMSSTSWQymblTj4hSqZQx/mOxmDlqdXV1FaVSCZlMBrPZDJVKBc+fP8fLly/R\nbDbNEavUDn486fX1NVqtFk5PT41RPhgM1DfHS1rSXcllv9ucaZmW5kvQyWphZLSmszTdJnmyXdfK\nlrLDtU2S8yJ1mZaG/w8bW8Z1n3/kyv5Wq4XDw0NUq1V0u91QRxhzuavpVy5bOegiD6Kg58LHCH9W\nciy4nof2X/N/pL3B5Trfbit1Cx8/tvFu8zPotzzARtPb9M1fcESjUSO7eR0chPF93wQ1Pj09Natf\n+v3+3IrJAI1QmwAAIABJREFURSnMfFtElyyBGIUosjXwNpKskWaoSMfVZvTJa7bypRNMFEY42Pi1\n8RMk3IC3HRQX2UAK2/UgnjndBkj5QxtbQU7YbfLepswwfR22TG74akBjmHLoWZJg1gISawpA8mpT\n5Nr15bakJbnIZuQEgYCUV25n4kZC2LqlQSyNSBsw4ypX+y2vhdVPtvq0cmxlhtFjNuDWxQOlpf3k\nrvw2vijtcDjExcWF2aJUKpXQ7XaNQTibzZBIJJBMJs0KC9pXP51OTVBE2isPzG/ZtYEfso1h7AXb\nNZe+18aUVo6U7bxcOQbpPy3Zp/6ho0uz2aw5aYqOLS2XyygUCvC8b04ZIdAmn88jkUhgNBrh+PgY\nX375pTkVCcDc8aocFJtMJsYYv7i4MEep3sZ+kP24pCXZxoN0JOWJQcA3R+fSUbx8qyMFOU0mk+Yw\nEW3e8VWbtPpAs8M4MKltmdEcYvmt1UkkAZIgeRVks7nSuXyIRUjq8n6/j+PjY+O4h9GH1E4KHMv7\nUZZP/+XWIx7zBMBbwIurL7X+4y9CpE0vfUqpW+m/tg2LA0kSmLHxpfHB+ZH/ZT760JYr7h9wu4qX\nQfFlGo2GOZJ6MpmYo7xdL6BuI99deYLG5BKIUYgesA2FlsJNGne2wU95iLR8tvqkYLMZlC6jzlae\nliaIn0WiStuc8iCj01XebYwnquO2kyxI2CxSlo2kgAyb9y7AjvbbdT+Mk0dtoC0B8r42fjVFpwn6\noLnFlZCtbb7vzyH9S1qSRvKNSZD8CpL5XHZqeoTrD0oj65Mkr9v40UjOOZfMsRmgLnCF88LBEMlX\nmNUzNr54OzSSOpn3s9RJNvlLz63VaqFSqWBzcxO5XA75fB7lctkcn0mBDGOxmDEaKVZMMplEoVDA\naDRCs9mc245g63feh9JQ5+m0sSfftLr6UbbbJfe1vpH9zR0/WtFC4Aud5gHABJccjUZIJBLmCOpM\nJmNWDxEYs7KygkgkgqurK7x+/RpffPEFarWaWV5OfMmTkYbDIYbDIVqtFur1Ovr9/pyztKQl3ZXC\ngg3SZ6AgpRS3ggBJGs90jHA2m0U6nUYymZxbVUcyhuJu0Oo7Anu5L0NxP5LJpAFEE4mEiQViA2Pk\nfCYgh8t0m33s8qMW7UtN3tt07G3qIJvw9PQUZ2dnGA6H/z977xIr2ZJdh+2Tn5v3f29V9at6r/u9\nbpogYYhAG+aEHHAgApYFmzJanpAQQQgSCI80IWBDMMmZBwZJTWh44ImtAS0IkDgyKcCAaUKwDAOy\nabYlE+Bzk0Sjql6/V69u1f3lzZufm7/jQdWK2rnv3vE55+T9VMUCEpl5Tpz4nYgde6/YEeEd87jn\nI4BjpXFcs1aXvK7kiT5SxspTf6wVF/w3nouxM2LqC/nl7zpVdvraB88DH6v5Ry4R5xsR8zpDXxiN\nRs5DcjQa0enpqdtrjMeL52IIoxRYOpGFTMQYABNodSD+wqQipL1E3ui1GVFNCdIMTO2/1nCsBhBL\nRPiEYaw7l6XQyfyErtXtFHUhFfm6kANKCuFym9AUcG4kWM/44uOQbqwh4kv2O543LS5+v6pLYsaH\nDYv04Pd8bVgqGlxR5n1IO/ZTQos/Rm5ofVW6ZltKmhznYogchNXGNn4v9DsVUl7zcddS3DmBwRVP\n3JvNZjQYDGgwGNDDhw/p8ePHVBSF2/AVijg/fQFxYmnNcrl0G/3ytiDHSpnHkOKokSi8rNbzFnwG\nlDWuYxPHXq9HvV6Ptra26PDw0Bl90+nUrc1H/CBZOp0ObW1tORIGp3JgBvTi4oKOjo7ohz/8IT1/\n/pwGgwERvXNX595mWF4+Ho/dpozD4XCFhLH6zn0akzPuBix9grcxvgEp9qWYTCY0GAzo7OzMETHy\n+FyQmfAk29zcdP0C8eDDvWGkRwwAorLX67kTc7hBa+Uf/ROkEAhVLMlEGZGmPFFQi9M3vsj7qWOA\nNd7wuLjdtVgs6Pz8nL744gsaDAbmM0VROCKr0+k4eV+WpTsS+erqyh3pbO19wk9e4mXn4w/3AJHe\nKb4xVVu+pP3Wlhb5xnTN5sQ1PskCgkrue2PpCVwX4rqRbDtoZ/jGJAba/2g0osFg4I6j5kS/XF7m\na4dV9I4UcksiEzEBaOv3rOvaS/Ypy7KRyTQspUpLJ3RN5ikWvLOjc1SBlWbVBh+K15dOqoLfJAET\nS0bx69p7DHX0WMItFlBuLS8STcnHf9yXbV0OJKH7Frgxq62txTc3Wqq244wPC6G+Ka/JDw+r9Ud+\nD8Ykb/fa+OHLi6VQcFiKocyPRiz5wvnKGLPhtw+SdLXChJ6X5SCiFYVPk1Nc0cQSl/Pzc/r4449p\nZ2fH3cPGvETkjt7EZrOtVovG4zG1Wi16/PgxjcdjOj09deF9Y7PUC6RuwduOVWbAImF89cOf5fVU\nluXKMaXdbtd5CR0cHND29jZtbW3RxsYGnZ+fO8+U8XhM3W7XGZTI/9bWljtWFfGPRiN69eoVvXr1\nil6/fk1HR0fOWEUYeMzwmfrFYkGDwYCOj48dEYNTO7SxX2vDTY+hGe8vrH0fuVEKoxD7VJyfn9Ng\nMFg51pcbrogP3i7j8ZjOz89NeWzpUcgfAK+ByWTiNhq3xiiu83MCYmdnhw4PD+nRo0f04MEDd2Sx\n7DOWMe+zWzSyQcubzKcGqedJOcfl+2w2o6+//toZ8JBD/D22Wi3qdrvOuw/XcQzzbDajs7Mzevjw\nIW1tbbkNbqXnC9LnZLxcMsb1VCnfUBY5/so6s2xPWRf8P28zIBgXi8VKnsqydJ6fPF4tP/xdyHva\nUiytPHJJX1EUrg1Pp1MaDAY0Go1oMpnQcDh0m7Gjracg1u6qYrtayESMB+iM/DQEn4FY1XCWcWmC\n1KeEyg6k5SdGmZcKiBRY1nFovjitMmrpyrI00cAlUt5D04iNOxSujnJYVbmEMJTXtLxZA4E2AHNj\nwopLhtfauWwzcoDnz+clSRlVEWqvPJx2nUNbOiL7jU+xkW09hhDBPavvasqdJC+hnEvFKFYZlnni\nSpbMDw+XKrc4AaSNkUjP2vi7LK+vs4eyjeOPiYi2t7fpk08+oaIo6NWrV65+Op0ODYdDN3ZiZu7x\n48f07W9/m8qypNPTU6fES0PEyhPPT+gd+AgWbiTGki/8+sOHD+njjz+m/f19t/8LPFuK4t2yJNQj\nSBp+SgXuz2YzdzT17u4uzWYzOj4+pqdPn9Lz58/dcdR8th955sepLpdvjpw9Ozuj169f09nZGY3H\nYzcjmoJMwmTEQp4+I71BuBHf6XRouVzSeDymi4sLR8ZqtobUaSy5bvXx0HMhnRf5xvMgUrHRNQjR\nxWJBW1tbK8ucpIcDh2aUSz0uZmyR5bSua+MZr7fFYkFnZ2d0dHR0bQNYXkd4hygrPwkI8Zyfn9OL\nFy+o2+3SgwcPnDyEdwsneBAHxgyZb34KEcLw8Zj/x0Qk2h4n0GQb4XWi6dbw1sJJUaPRyHkuQrbz\nsdvSz7nOwNPkZcL4gGd5H5B76mGy4+LiwiRisDcMl/eWbe5DrL3WhN2YiZgAwAQCXMD6lF1Aa4Ay\nrHbNR3RYBFAKtHz6hKamTMekyztmKnkTQkx8VeKtitgOGRPOUsxT8pJyPSa+qkvSrP/SwLOUiNB/\ny1iQYTAYZmSkQlNmAC7f8Ns6jYL/lmFknJqc0JRXHl6T05Lo0BRwPBtaW+7Li3VNC8PDoU9COZPL\nsiyl0Tc2WqQL0pPvU4YB4MaP5/Bsr9ej3d1dZ1C1223a29uj169fU1EUK/ugQElcLpe0s7NDV1dX\n9ODBA/rss8+oKArq9/s0mUyCXnpQWH3u5FIpluFk2aShh+e4lyEIFdzrdDp0eHhIn376Ke3v77ul\nRLjPn9/Y2KD5fE4HBwcrRtp4PKbxeOyWWxRF4eIZDof07Nkz+uEPf0hHR0c0HA5XNmiUyjzyxEmY\no6MjOj4+dsaiVbdVx8NQ3WZ8WPDpOGh7IGE6nQ7N53N3jDpffoJnOSQ5IcNoY4W8r8Ur84+0+LdM\nl4edTCZ0cnJCV1dX1O/36fDwkA4PD2lnZ8ctK5R59EGmrY2HMiy/F5MGnpXj5nQ6pVevXrnljnIs\nhTzDu8ISsNFoROPx2MklEAUvX76k+XxOn332GT1+/Ji63a6Ti3KDZMhOnq7m3chPg+N79HDwvYPw\nnCwvrzvp9cPrCMtJQbKVZenKgbQ42cZ/y03oeXn5O+LjvTYeoT7hTXl5ebmy/A4kOzzLZF/i6cfA\nZ1NqxJy8J9OMHRsyERMBvvGSpjxryoyErzHI53m8KQ3Kum81KplnrRFqjTpmBs0H2ZBjyKabgCWs\nfOGrdngJayD0pc2fi8lfHfC2z4Ut3zyrSlq8LWkb+6a0DUsYcmQiJiMFlsGukRg8rFQ6uKJobbjq\n6z+hDQ+l/NAUcUCbKZOKbKyiod0PlcWntMjTDGQdaulr9a6lKa9rY5Acd6Hs4nhleK9Mp1O3ASaU\nROwDc3Z2RtPp1C3VISK6vLyk4XC4srzpo48+om9+85u0s7PjPDe4x4ecBeXr4qUs5nWjyVH5fjCO\nA9jnodPp0MbGhjvhaXNz0+33gtlgLLsaj8c0Go3oyZMnzisGRAs2BkX4jY0Nly7Swj4TW1tbREQ0\nHA7p+fPn9OzZM3r58qUjqDgJw9833w+Gz5JeXFzQxcWFOxlJa3NNIBMwGRq4LOUz+nxpB/pXr9dz\nMkWzL7TfPv00pU1q8l775mlxEgGeEvBMgLfM/v7+tY2Fffq+Jp9QF9Ljgxvt2rilwSoTH3eGwyEd\nHx9fs3dkPheLhZM1nU7HeV7I8f/q6sqd0jMcDunx48fuJDhO0kmPElkHRVG4jZu15b3ylCotDh+x\nB32YkyBcn+EbBPuICEkuSbs4BNQtTjUCyYVleVhSulgsaDqdOu9I7Pk1m83cu/PpQhbkeCjzxuPj\nz8gwWrwxyERMBLBWjrtMAZqCYynBmgCylHYpPHxKsnwmFjw+GbflBROTTgoBIONLKUcoXJU6SYEm\nPGPypQmpmLJoYbW61pTzOtDaBwZFzUjSnrf+WwM+wPuURpSltLN8VHVGVWjGOW+7XJHRiBreTjVS\nJYa80MYCwKcAWQqD7LvSG8Uax+RzKX1QhvfVk7yvxcXDaGSM/M2fl4Y9v86NJ770pdfr0XK5pOFw\n6IyO2WxG/X6fyrKkw8NDWi6XzhuDiNxx1sPh0Ln0o7184xvfoIcPH9L29rZbPgPFnohWNuTkM4Hc\nJT5m/OQkCDbRxf4t/KSnTqfjyiyJINTLo0ePVpReTrLA6wWeQ51Ox+1/gXfW7Xad90tRvPGO+frr\nr+np06f04sULR8Dw52Rfg5EAI+r09JTOzs6c4TMYDEx5r+lpVhitvWVkSGiyyzrhhssUecKaD9JG\nkPdCkDoT/+ZjmyYveRxyrJnP584bASfUgGQCGSv3N7HyBbsDchCT4Ds7O7S3t0fb29vqxsBWfcg9\nVWRYkCYnJycrG/T6xh3IJeSDj/t8n5z5fE5nZ2fOk+Nb3/oWPXjwwG3iy+te2n58bNImeSxPGJ4X\n+W5lOWS9cN2Bk/7ynqwjXtfyHfByYcyCPQ0CBd84KhzLoXjd8H2NQNZgHJT1J8uZglg7LGYMSclH\nJmIiwZVV/OeVay3d0RRNSzHkL1dTPnzKel3CgT9vKTBa3iR85IQmEEPMaR0y5Tae0wwW3+Djg6w7\nS6DGxKsJUjwfK3za7bZr55IBl3nxCXqeT6vOeBgp4PkmYjIvWplShWZGBocm00KbQmvP8vYsw4fk\nesgoDKUZWzatn6QoNykkSwxSxxo55vL64wSLVFQtI4fLK3iLgBgZj8d0eHjovGXPz8+p0+nQw4cP\naXNzk46OjhwZg7iwMWdZlnRycuJOImm1WrS9ve3kK4wYbpTgaNr5fO6O5cR/bXknV9o3NjZoZ2eH\n9vf3aW9vjzY2NlaUXb4ZIxRdudFhq9Wi8/NzOjg4oEePHtH29rZbggDlne9PgLIi75ubm448WSwW\nbvPRFy9e0PPnz+n4+NjNMMMw5eUCUcgNsfF4TCcnJ3RyckL9ft9568j9YJpUmq02kpERA260o89A\nt4qVrSFYYbXrmsyw8qyFhWyFl8J4PHYecSB25fOSWEAckEcwzsuydMTF1tbWii4sN3eV+eMENves\ngSzBcsvz83PnvcL1ZJ/NBRnG09OI/cVi4Y5Nnkwm9NFHH9GjR48cCS43u8Vvnz1ZFIU7fQ6emHw8\n4ydZcQIMZdLIHM0Wk7oJ9G68H07Qa98IC3nOJxFAoHCPRZBbeGfyPWLcQ9wy36gji5TxIVXm+1DF\nfsxETCSgEHW7XVOYaaSC1lAs8OdlXKH141bclqItw6LDcYHlS0czvnn88remoFclKO4CpGKn1es6\nyqK1Lfz25dMSTqE8yufxv9VqrcxycoQGexmWl0MLx9eeAnxtqxaPTCNv0JtRFZrsiiUWrPYca8hp\n/TVFrlj9Qo5HVnm059ZJamrkrXVP5kne0+pOnkqhxcvrjCufWHrUbrfdKSEgUPb29tzpPAcHB/Tk\nyRMqioJev35N0+l0ZckOvGmm06lzrV4ulyuKc1m+WYqE42WxvGdzc9Mp4lgKgHXyvF2BdMIGi4eH\nh7S7u0u9Xo+KonBKLTdWMP5zbxfEwzcYLYqCHjx44OLmBgsnUuC+32q1aDgcUrfbdQQLjgE/PT2l\n09NTt/YfeeMu8/K9wejD5ownJyd0fn7ujsWWOkxojJJt3NJLMuGSEYsYvUozjlPha8chAt0irK38\nh3RMbojD4JZyViNk5DePz6ofa6wCuQDPuH6/vyJbOPEFovvs7Iz6/b5LAyRGt9u9tumrzKscb/h/\nPs7MZjM6PT11p+Xt7e3Rzs4O7e7u0vb2tvMa0tLh5S/LkiaTCZ2entLLly/p8vLSTQQgPLys+J5E\nqBssFUNa/FlpI3DCBXVwdXXlxh+MFZJ4QV1DhsuJU03n5/YTxiS0I07IW6s0fO3CChvqb5qOZMXl\ney4GmYhJAFdM+DVLWQwZyb50fM9ZZEpsWJkv2UlijWaZBo8zRXEJkT43hZQ8a52U1/W6lDbr/ch8\n+Mg/n4AJxa0twQCLLWdlfXmNUYRDJKJFeslwMSRmRoYGnyy2SAxN4eThUpQB/qymuGh59ZVD/tZI\nCH49pPxKxCo3obCxY5v1X6sb/uEeTdoeBvw9zedz59FRFAVtb2/TgwcPaGdnh1qtFvV6PTo8PHQe\nK/BAwRKefr9Ps9nMedSA1CjL0s1qTqdTZwQQkdtD5dGjR9Rut2kymThiCAr+zs6OW9KEzYA5gURE\n7oSP3d1darVajgCC1wifVS7L0uUfyjoUatwjenNKVK/Xc4QLlhiBHMHmlf1+3ynSOBKWn2CE0y24\nAcfzzg0nADPB/JSM09NTt58Af29NjcGZgMmoCktn1sKFwPUaS4fisitFXocIGEkw8HByokzmwSo7\nJxrwzY9wBiGCTWM54Svzw9OFt12/36dXr17R2dnZtSPuOak7mUxoPp87OYblVIgXk368fHLsh9zS\n9ABeT5eXl+7o8o2NDdrb26ODgwPa3d1d8ZKRdQz9GpuRv3r1ym2ULDe5RZ3w+gRAymA5HMgoeGRx\n+UtEjoCBtxC8ViT5grrQ3okcTzlhxuuQEzmxbVjTr9ZtM8bad5atoiETMYmYz+dOQGgVLY1x2RmJ\ndKUYSo/GtvqEmq+xIg7kFeG5C6D2TAia0PXdT42/aYTyCPgMFAvau2xKcbMIL1/8VQyYWEBg8xkF\ntCfMfmj55UsxNAOVSK8za421r21JMgjKeUZGE7A2KufyWZMdVr9NJWVCBKZPpoXS1+KMIXskQcTD\npcjEGJnrG+tiId8hl0nangLYoHE0GrnNZbmCCa+YTz75xLmgt9ttOjg4oE6nQ5ubm9Tv952L+ubm\nJj18+JAuLy9pOp26GT+eJyjKUMz5HjFQpGEwIA3knXueYMYTezhAHvLfINK18WW5XLplStPplA4P\nD90R06PRiPr9viONYACBXMIGxCBOeFl5/WIMwfjC3wWfUcaxuYPBwG0OOhgM3Iw3byM+Yi2mvdyE\nQp/x/iDWOCNa9T7nG9LyeKwxBmF4uvJaKJ9WHDyN0PM8vLRVpA0jPScAvqQRHhrSBuKEDJcHvJ6g\nX0JGQS7AGwZEi/SG5IQAiBdOQGOLBpDjcnkTyosPnpPX5TMgVCAbz87OaHt72xHrW1tbbv8gyEqQ\n1sPhkC4uLpz3n2+8xXiBNOV7BKnPl+zKNqDpLXIJKp8csJb+StKGk2aybn2oohtosNLxkSfaM7F2\nYgiZiKkANDz+0rTZHCJ9ppE/pzGDgCUseXz8Hk+T50UyjNb+HtYgoN2zvmM6k9WgNXLHauhcEKQg\ndsBMZTx911IQej4l7tTB2coLrwsw5JbiLp8lum74aMaZZUT6lGf+7i3FO5MwGXXAlShN2QmRoynt\nL0QyaKSJJctl+/cpVynKjSRdtA9/Doo4xqMqfbLKeKKF8b0jTrpwZZwbTZeXl07Z3NzcpPPzc+p2\nu24Dye3t7ZWjPonIeaO8evWKvvjiC1cHjx49os3NTXf6EJZ5wmhB2tPplIjI7bMChZ+IVvZlmM/n\n1Ov1nAKP50Gi4D8/gWM6nbrZV8yOIu/ciEId4DQllJWfEAWy6Orqis7Pz92SI3jfyNNIuCHKx3oY\nZjzcZDKhfr9PZ2dnK54/MEjkJqc+XckHOfZqfT8jQwOfbOLQ5DL6OP+kjiFS3vJwqbqrL21JjGj9\ng/dfbtDzfUGsfVqk/cOXo2ACmW9grpEGqMPJZOJI38vLS+clB5kiiQJ+HXYRZCRfosk9frguy+tM\n7j+m2TBaW4BX4WQyofPzc2q3207GyolOud8NJ6/k0h2eB82mQF2g3Fq+tTbBZTbGSIyXfMzk9SdP\nvauqe1SBVnZNX6iikzRpX2QipgLQMTSl03rp3CiVhIYlTC0jVNtESovDUuDlfS2fWhlS7vNvK30J\nSwBohABXLq28aOW0BjX5P9TJtDLzQcaXllYejUi4SQVQqytfOGuHfx6PRpT4BnzrvWv3eT/CNydH\nMQBkZNRBqN1qypb1XGzf8uWFf6zZPU7CyKUnkqCRfVQqivyaJH00AkYzgq3N/Kwy++ophnSxwlnP\nynfIZ6q5oTCfz90RyfAmmc1m9PjxY9rf33ezt1wZJXozg/j48WPa2Nigfr9Pr1+/po2NDXeaEjcY\nsA/LeDx2M7kPHjxw74KfSoTZTpAxmN1EWZA/eJrACwazv5xkwYaYfDNi/MdmwjAQiIhGoxF99NFH\n1Ov16PT0lC4uLmgymdDr16/pq6++ckuR5Bp/3i5R77wdwzCCjjUajej8/JyOj4/p8vLSGUr8SNMQ\nUsJoOlxGRhVYspAb1jCuQ2RMKH5LvmvhLRvDyreP9PGlIccgubSIywC+VJQb97Cz4P23XC5XlinB\nCwaENuQmlnsSvfPg4Doi0uSbvsr8WvqrpRNIEkSG58QTCHBJTsGrkD/DyRIQHpLA5pMdfCzWJj+k\nTs3vyzqS5eT51fZZw9jI60NrK1LONk1sWAiRMLGyP8buxO+YODMRUxFQ0viyHwmtMWvCmSu9suNq\n8UkBwZ/XwIWCNFYtMkPLTxUFxYo7FE5eTyEtuGDzdW6fYp5KgviekYOTzDt/XitrHeEUKwhC7cCK\n24pHI1V8afoEG7/P+4bPSM4kTEZTqEIapMg4i2zk9yThwpVVTXFGeho5wxVOnqZUtmXe+Fp+X9nl\ns9bG2rJeQ3Kuihy0FGhL0ZSAgYR6xnGbV1dXNBwO6fj4mD777DP67LPP6OHDh86tHF4mePbg4IAO\nDg5oOp3SJ598QpeXl3R2duaOepWGRq/Xc6TPxcWF27+A71eAdgBPFaI3LvZE5JZHca9YeNRAQcey\npel06rx58J5BKHF53mq1aGtri5bLpdtkeHNzk46Pj+mrr75yR9cOh8Nryy74b9Q3d2eXy5D4rDbf\nE4YvqaraFkJhYsau1HgzPjxIopoTBzBYIU9Cnt0+uyFGfmokTCi/XPaHyHFJPnDIMYjLAjlWaaf9\nzOdzt4wTe6twT77pdOo+qE/pQWJNSCD/cjyQdlKsDJC2GH+O66QoJydXIJd5W5AECcgafqoc8ghi\nxyJiZL7wzuQz8t3JCQapV0Amg7y36itVroag1bPPJvA9XxVNyf5oIqYoihYR/SkRfVmW5feKonhA\nRP+ciL5DRM+I6JfKsuy/DfsbRPSrRDQnol8ry/KPGsntHQPvBFIQWcIrZKxrRAniBKwG6GvofDCQ\nacrf/H+Msh0jpLR0fXn3QXY6X57rkEcWIWWl73tfWhpWPkP1ZcFnyMl4QmFDedHCy8FNg0zb9+5j\n4pDvBgN3RkZT0OQoh0/GxCoEVtyaO7W2FtsXp8yjpoxakKSLjAff2NCW7zsChRleFHw5aapctuSp\nNCykfOIKo/aMVEJxTXOZ53HDADg/P6eTkxP68ssv6dNPP6XvfOc79PjxY9rc3HREB1desbfLo0eP\n6PDwkIjeeJdAIcaGuDi+Gl4fIFhQj9JwQb3yPJdl6U5Tggs8FGoo/9iHAJtiXl1drew/02q1nJLd\n6XRof3+fHj9+TE+ePKFer0fPnz+nZ8+e0dHREU2nU3dcN9oE6hoGBm/D3ACBUTUej+ns7IyOj4+d\noYrZbpRFIlV/kO0gpT9nZGiQckfKam6w4oh1eLJpe4/4EEu+aHnTnkG6ktQP6bC832lGLb8nf/Ow\nmockPPBw6k+r1XLECk7ugVzmxAu85binkc8zQxJOXF7xcmn2l9QLeNms8QZp8SOc+Tgl8yHTlMSQ\n9m3Js9BYKdPj9QPvIhk/3oEFLbwVznrGBx/hk6qXhcJrNlpdMglI8Yj5NSL6nIj23/7/dSL647Is\n/1FRFP8lEf0GEf16URQ/RUS/RER/jYg+JaI/LoriJ8umcnzHgLWMRP5OwMFdv3zkiXbN11jqkA74\nXUdR5lQ1AAAgAElEQVRBtgxsK0wKYp4L5b9K+ay8pIa3BJLWoS2BaQn/WIQG1lAZ6oaRhEkdkWD1\nidQ9gzIyQtD6bwyaGPLkBoKSEIEiCiMYRvXW1hb1er0VzzFeHp9yZJWVGxggDYbDofuMRiO3Hwjy\ngM1tsREhltZoxI4FXz36SNwQSaWRUZx0KYpiZRZTuoODbMBRzV999RX9xV/8xQohgyOjQYAQvSOk\nut0ubW5uOoMB9QlPkM3NTUds4b1ijxS8V8QLbxcicnu4zGYzR67Aa4YbN0VRuLyhnNhnBkdlYzPg\nra0t2tvbo729Pep2u3R8fEw/+MEP6OnTpyvLkFBH3AACOPnCvWDQlgaDgSO4sOkxTkbipM5No+5Y\nlfFhgMtHTsRw0oCfFsZJmNvIK9Eq0Q9oBqYmSzWCIyRzfeCEMQgVvlGvjI8TLVz+SA+YGNS1C3wE\ng2Zj8WVMRO/GFhDsPE5JpMSkKd9nyC614pbjnWXjyTxaZFIIKX3Bqpf7iCgipiiKT4noF4jovyai\n//zt5b9NRH/97e/fI6L/jd6QM98jon9WluWciJ4VRfFXRPQzRPR/NZftuwfMWKEzyY2eNEihjef5\nfWm88nCWYe0zHHxKeUjhgJCIZTU1aIayT5mOJaFCREeKoNWY4lTBpv2X79IXXiKGoKtDrviercNO\ny7aLdivbvjSOtE0cZV/hAxoRrQzAGRlNQjPseZtN7c8x6XEShq8vx/iCfTKGwyH1+33q9/s0Ho+p\n3W5fI0Bw5LBUbHneNeKXlxUbxsJA5ktGcAwxD48TdbDUBhu8bm1tuaM6+SlsGmnE60N7B77wofpF\nPi3lUcopvgEhl1G4PpvNaDgc0uvXr+kv//IvaW9vjx4+fEiPHj2ihw8f0sHBgTsVA2Xf29tzcSIN\nPmsu94sZDoeurvkGuLIOsWwIZYL3DAgWEDFoF9xbBpsRb25urrS90WhEL168oKdPn9KXX35JFxcX\nzkuF14ncmJd7vRRFseKGz0k83MMJSRcXF+6kpSpknPauY9tHRkYKLNnFZdZyuXTyU9vAOgYpxIIl\n49AX8Z/HXddY1vZViQHihA4HQjaG2NEI9SrguqmVlrzmI6ysPPlID+2ZWPvIZ3/J92+Fs4gWX16s\na5K4qQqLWKojz6WNZ5GPmj4QU57Ucsd6xPwuEf1DIjpg156UZXn0NoMvi6J4/Pb6t4joX7NwX729\n9t4CrCzf7d8yNDVIQckhvWesxtCEIeAjLCQJE8OAyuupjTNl0PHVh6bAh54PpVfl+RCRJOOz3qkl\ngHxkni9M1fcjIduqJvA1wa7d48oCz7d8lgvRTMJkrAMxstSnsKSSwHI/GKnkLxYLGo1GdHFxQefn\n5+70mPF47DwjYHT3ej3a2tpyZAyOyYTngzUbiv4EbxsctwkCZjweu41g0Q95XkEWwdsB+6rAGwNL\nX+BxIckm1IVFSMl9RWTd89lSvmEs98rgy3O0UzUwicKXVEHG8TjxH+FApJyfn9PLly/dO4CH0O7u\nrnsXGxsbTnfY3d2lvb0954mytbVFDx8+dPEjXm6oIA/8lBEsicI1TnahzrF5L8rON6jEZzqdunZ2\ndnZGr169otevX9NgMFCXCSGfqAvuycXbxWw2c/FeXl66uHBM7MXFxTWSJxU+XaYpWDpbxocHa4IN\nKMt3yze5R0wdfSv0rKYTc3mKMJb9wftQDNGhjYFVyBgifZmlLItEVZvH95u/11iSqoqdo+nKPsJE\ney6Uhg/STuPXQ89rpEYI3Mbx6UpV7CofQRVrt1oI1YN1P5RGkIgpiuJvEdFRWZb/tiiKn/flMRTX\n+wwoIbJRcubZanyWMWoZ4xbrbHWaUGfS0tEEUSjNUBzyN/6vizFNQUw+ZFllOjFCKyZOfl2Gs377\nlMLQNf7b8niKHWB8JFLovchZeq2PaPEWxeoSgoyMplCVUKkCriTLjXHhcQEi5OLiggaDgfNIgUs3\n+khRFM5Qn0wmNBgMqNvtOnIGS1RglPPywrCHezjfCBHpyNlcuXyqKApnWAPcjXw6nV5bpqLVMR9/\nOFHi2yeHl4GPqzDqOXnDyQmQRHLvkqIoru13U5alO9VDHs+JMRpkCJYcIU4sGcMeLIgLXii9Xs95\nDm1ubl4jz7rdLvV6Pdrd3b3m3cQJDU5i4H1Op1Pq9/uOWJtMJq5tyffDPXLw4RvlSiMO39jTAW2C\newLAi2owGLi0+bvBkiRtaZNEXb0hJk5fn29Cd8l4fyAJDdl2IAuw3xHfI6RJY1CGkeR+7DhWRZ/1\nIYZgsPQ8LS5rco4jlaiIiTMmfGydxeS3qnEfC4u4sOoutf1oaIpcD6XhK0PKe7KeDRGwsYjxiPk5\nIvpeURS/QERbRLRXFMU/IaKXRVE8KcvyqCiKj4no1dvwXxHRZ+z5T99ee++xXC7dyQdEdoe0jHjL\nqA41vlCDk+lqiGWGQ+k1hRBzaREJULR5HkPsZ1PMsnUvlsDgZF3sc3WgkWixZUgRxjH1r13T3jH/\nxnN8f4SMjCbh64MhhVILbz3DCRgY1zBMsf/LYDBwHjDYj4UTATLPfINUuHlLIkOuv8eYJdfbc6Mb\nZfCdgoM0ZLyoA2kYxBoImhywnuN7vfBntM2PteUzy+XSea2ArAGJJckaSUZo9QS9QO47w0kh/l7w\ngUcNzwf2e+Gb6oIg40t/JKHGj3bFR1tyxT1+eP75GMXLhPqVe79wz5fBYEDD4XBlzxfExY+6xulN\nVaH1saaNAi2tjAwOLl+I3i1NgkcM73NNtCOpP+Ka9ByUdgl/Zl16VCoxodlAvr5s1V9q3cp8ysn1\nWJLIyoNFlGnlrmJrWGGqyD9JKoZ0nKrkivwfIqPqvE/5Liw9TUuzDlkaynOQiCnL8jeJ6DffRvbX\niei/KMvy7xZF8Y+I6O8T0e8Q0d8joj94+8gfEtE/LYrid+nNkqSfIKI/iS7BPcdsNnP7xWiGpNV4\nqzS0GANBQjtFIvSsZrCHnothIy2iKYZwsaDFGRtHjLDiJE8KOSHLrN2rI9hiCbeYfKbc08qvEWBW\n2FCa1sAMzGYz89mMjKYQGlh9RKZFdMo+IMkReAf0+306Pz+nwWDgliHBgNb6Dl8uFJPn2DJrkEtH\nLIJE68epJIyFmHJygwi/4bnB04cc5oTC5uYmEb053WgwGKx4r8BLhnv/SGWaf3AfaYJ0AAmhkVea\nJxBfbsSJFx43J9L4EibpKcS/tTrk+edLsIho5TcIrKJ4cwR1v9+n169f09nZmdsXYz6fX3s/8MLx\nGVqagWKNc1o8VQ3MTPBnxCJEEHCvNO7BGIMUPYvLM8gMn47tu5aSr9j7VQ1cTU/W6iBELMg4qyJG\nb00lcaro8b6xXpsYiEk7hLp1GdKnYgmpqrBsE5+dLttfyFZOQcqpSRK/TUS/XxTFrxLRc3pzUhKV\nZfl5URS/T29OWJoR0T8oP7DRbDabubXdRKszlPxFyplGec8iKjQFw6d0xCjlPJ+xZIsPdTq9RXLw\nzqAJuFihFcpHSGjF1oOMp47Qr/p8zDOcXIqpSy3+kDEVE44PGtZHrh3OyFgnNANa/ubQ5FOoX1j7\nnpRlSdPplC4vL51XAZaHcK8KS4Zp5K5MOwUx/S1EJmvyV8r7VNkTc0+moZEbHL1ejz766CN6+PAh\nPXz4kFqtltuTZzAYUFmWK8uI4J2C/VmKoljZ/Bbl4jIMXiPyHs+rRphoegF+a+ScRgxp9c6h7dGA\nNsfrTcrz5XJJk8mEjo+P6ejoiI6Pj2kymVxboi2XTVUxSDlSSZc8dmSsE1Lf5Bt6SyImpHdrcWu6\nMe/nvmWbTbX9JuKJ0cdT0tNImlB4Se5CPmlxWDaZhpSwoTwiHosE0GwiiwTTyuRrF3Ls8cngVFJN\nu66lbcGqj6rtqGqb1tpRCpKImLIs/xUR/au3v0+J6G8Y4X6LiH4rKSfvGQaDAR0eHq68WMyacUXI\n2uCUK0r8HlfWuFLFn+XKXYjFCynKPL7YZ7RBAtd9DZU/p9UJv+fz7PHFbQmTmI6rGWHIS4zQ48Jd\nM9b4++TXZB40UgnGhBbeqiMZpwyr3efpaXH40uFxamuWpZEg4+UzO/P5nI6Ojq6ll5HRJOqSnz5l\nTJIBfDzA5qz8E3PcaUp+b8IYlX3bF6ZJcDmijT98o11JTHQ6Hdre3qaPPvqIPv74Y9rc3HTPYdNh\nLLOBN0yn03HLlojILWMCWcOPr4aij/fNyROQHVgaJeW4XG5FtCqLuW7Al0TwOKSMRRipP/Bn8FuS\nhZxUmc/nNBqN6Pj4mL766is6Ozuj6XR6bQkc8om8yDGLv0Okq41jN0WmpBgYGR8muDebZhBzbxgs\nTQqdMBTS27R+w+WYT/5paKKda7pp3fjqGscp8VvPaEQHnuf/NdnK71v5DF33lcPSsa34LNJG2iWW\n7UWk7yWZKr9DZfLF2RQ0PcEXdl2o4xGT4QGWKD169OjaEbvSgOYNAb+5u7EGHt4yhvnMG+5rcUBp\n44YuNwr4um2uOGJdOhFd25ixLEunfCIOnq62czvPH/Y+QJn4unGN/ODKHZ9p5IALNK87PiuhAa7d\nFng55awqPz3CFw82gOT5goKPchG9aVNFUbh9ATDDgg0ae73eSpvhSjlf68/zjvv8eTyLNIneGS5E\n5DaaxH2kj5M4kA5c/7l7PC9PWZauneOefB9yE96ieOP2/uLFi6wcZ9wIfMplaADXSEz8lyQM0buZ\nU+wLMxwO3VGn0jC3oCk8mlJ3E/0nZDTgWioZkxJeK7+l5HL5VBSFO4mqKIqVE6m63e7KhrbSEwUe\nMjs7O7S/v087Ozu0tbXl9nPBkiJt/x35XjCO8D1/5H2ef1kuOQ7I+samw3L84htGyzaLeLHvzGKx\noPF4TMfHx3R6ekrn5+cuTowDvJw8L1VhtQGu1zQBzRhYB3mYcX/B9WhNnnBPGL6vV2o70iZFQ+RL\nTN6bRtUxJlWuh1Cljq0xVtZpDAESM16HYD0bW7YYAknGa6Vb9b2mtEOpK1nPN0XOW+8zhCYJ+kzE\nrBEvX76k2WxGe3t7RKR7wvAZLq74wOhGGLkWW2s8+K2F5coJN6gliaMpMVxJ5CQHj1tuBlYUxQoR\nw40RKGf4zcuP/xsbG9fqSjNmpILISSxJKvH0eRwSfHNCbcNKkAOacs8VTE448LX5UuBwIoLXAY+H\nzyqibWxtbbmy8vyA4OD7CKBeeN2AOMEsLzZvhKLA9xTAbA7e63g8XqlbIloh6ziJh/Q6nY4rC68r\njXTTZosQ/ujoKHiiRkZG05CywmcI8t/Wh4iu9Xd4FVxeXtLl5SUNh0O3J4y2hCNWwbstw9GnrKzL\noLUU6FiltSxLGo1G9OzZM0cww6uFHxvN3yMnv2F4LZdL6vf7dHp6Stvb27S3t0d7e3u0vb29cmKV\nXI6G/PKxB/JallGSOPweb2NynMez+M3HETkhI2U8xoLLy0s6PT2l4XDoxpDRaOQIGIzheI6XzSJK\nfO27SluJVZZTlepMxmRwSP2VaHU5EvZI4vqV1D+lPqnpdRwyvDa5ye/zby0+DXUM26qwjG+L+Aj1\nw1B+tL5fh7ypYqBbRENseEtO+uxEGcaaCLDi4fe0MSXmvYTik2WV454v3qZg1WeT6WYiZo1YLpf0\n+vVr2t3ddUdNttttNzMGpQZG6mQyucZwQ2jP53Miuk6KEJFT0jDbJjfTk+Gh3EkShCuFfAM9OaMm\niYxQx+Md3TerGxImKDs35Hl4Hk6eTIF7/AjSyWRCo9FIdVFHWJ4+rzt5HXWtKbAgF66urq7NiHBS\nh5eJk3LS9R17EaA94TdXAGQdQ3lGW+IEDGbckb/lcrmy38FwOHSK9e7uLm1tbV075pXXbavVotFo\nRER0jVSRs66c8MGMEdoYPyoXZXr9+jVlZNw0fAOsJIK18FxWSg84tO3ZbEbj8Zj6/T6dnZ3R5eXl\nSp+IQaxC2dRMjgYpu9elFFmw0tTICG3MKcuSrq6u6OXLl05eYXzF5AJXuLlMg/zjBMRwOKTLy0s6\nPj6mbrfrTmLa3t6m3d3dlaOqefx8sgbgackxgxM5fIyWRIxWF3xvGz6+8jFlOp3SxcWF2zxaEoRc\nV4C3j/Ro5CRT6jvV8i+fX2e75ulphkzGhwu5XI+IVmT6cDh0+3tx/cxn/IZgkaVV0UQ7rlMO331f\nvHXGGKnza/HJ9KsSDPx+TDjrOS0tGUaObykElrSlfGF9edPu+fIbSwyGdLEQfGmFiCGLJNTyGZsf\nokzE3AiePn1KT548oW9961tUFMUKQw7lBa69RO/Wl+PYyrIsqd/v03Q6dUud+JGVRVG49ejSDZjo\njRHOlw5BSeKkAo7kxHNXV1dO0QJhABfk/f192tzcvObxwT0piN4tYUHc2ONgNputrJPFc4AkezDI\ngXTgM4n8CFGEByBgeX6WyzdHao7HY0du4RQM1J30BuFxIA9cQecClX9QXn58KBdweJavn5ezKqhb\nEBV8OYPmMl6WpZul3NnZoe985zvU7Xad+zz3ZoJhAWxvb6/kYTqdUr/fp06nQw8fPqT9/X3qdrs0\nGo1oOBzScrl07RTeNVA+hsMhdbtdV268t83NTdre3l45GQb1gvaCI+D5Uqmrqyv64osvKvS+jIzm\nwfueJnPwm4eX1wAQopPJ5JoHDO+v8sPTvEvGoJYX5DE1r3UV7FAefUY89n0Akc5PaIPMBUnOlxxJ\npR2GF8juq6srFy+fnDk4OKDDw0Pa29ujzc3Na6QOzy8n8DghJAkOTqRw8kgSSESrJA/GLegBl5eX\nbqNifsIR9/7Bf64XyHewjnbqU6qt65qyXTW9JonGjPuL5XJ5zUMZ/WcwGNBoNKLZbKYa/yFYMlWS\nPxo0oqFuP2yyX/vkxG33NUlI8+uaXOb3Q/FyhAz8FOJAe4brJFZbks9o4SwCPWZc18idlEkTX760\n8Ty2TfniTQlTp21mIuaGcHR0RJubm7S7u+uIGAhlbqRCccPa8/F4TB999BH9+I//OL18+ZKm0ykd\nHBw4xWpzc5NarZabWeMK/3Q6db/5rBhfOjKfzx0R0Wq16OrqypEQUBJxWke73aaDgwMaj8d0cnJC\nRO88GjjTLxUxrJWH0d7tdt1yLZ4PqzMjvzLfSBdKLuqEe/vgeU749Ho9+sY3vkHdbpfKsnT7AMj9\nGGQckuCyfnO3U04ugLDgM+KSeOH7qPBvAM/zeLgwWywWNBqNaDQaUVmW9KMf/ci1haJ4s+Sr1+sR\n0TvlvN1uu00mOaGGetrZ2aHpdEpnZ2dE9OZEkd3dXUfWQMmAS/ru7i4VReGILr7MDAQkyk9EjhAC\n6cjfLdEbEuZHP/qRa88ZGbcJSX7imhZO+0a/Rhufz+fuAwO51+u5fg0CXO4Tk2GDE1Z1jQQicu8E\nY+R0Ol1Z/smXLnGiA+8QvzEO8L1e5vO5W4b28uVLJ193dnbcUqaNjY0VEt6afOBp8nGBj/+cROGT\nKCCJxuMxjUYjJ6sxtnPvTUwuaPuOyfrj5I/Mb0z9Z6Ij466Dt28+KXZ1dbXiQQadpq73CuKQk3Y8\nPwA3ZiUJk8eSd1hXvcTIL/m+Uicr6uQ3NX++a1XAZfxdm1S6KWQi5gbx/Plz+vTTT+mb3/zmClmB\nmTXukUJETkkfj8e0vb3tSBCQJ1CEuNCHco+lT7jHw0Ewwx0ZyiXSRBwIs7u767whkD8Y8wD3TkHZ\nuGcJnoMyh/xI5VIThtxwQRyID+XhxITcvBBlBCHQbrdpMpk4LyNp5GiDGFd8fYKCe7YgT1hOxNf4\ny/yh7GgDUtnm9UZEzgNF1lWr1aJPP/3UkSAg9/imynh3k8nELYfDoI4TQ7rdLm1tbRERuSUSW1tb\ntLe3R2VZOkUddYYy4htkCn//SHtzc3NlBpnvJSD34plMJvT555+79pmRcRvgfVKbidQIGakAg2zR\nyBei621fhuXeBjwNfN9lBSY0G8VR1/D2ebn4wGUoVw4x/mByghPLfIkxEa2cbIXfkHNEqycY8c3Y\nOWk0Ho9pMpnQ6empI/H5GAIvHLnnF+Q3X4KMb97eONmOjyRc5EQA4uCetNqMK35DD+DjtPVOfGSL\nj+hMeadNIhNDGRJyQg46NLwcB4MBTSYTJyd83gBW3Bx1+4MVp9anmzTCmx6nqsp6X374NZ83hnx/\n2vuM9TSpkk+epq898DzEthvfu5f3tImm1HZdpy+E8ifvpda/b2xqqi1nIuaG8dVXX9HDhw/po48+\nuuZ6zI1xnErDvTwArtxwAoP/Rzh8y31NuKLE48VSFR5eCm94Lsj7/D/fWJKnD/CBiJMR8j4nc4ho\nZWkSVxKlyxyPEwozz2tRFI5o0NLWhDG/ZimX8rrMk+ZKarly83rDdal48/wSkZcs4qQSEdHu7i7t\n7e1dc0nninRRFLSzs0M7Ozsr7Wp7e3vlGs8Xrws5Gyr3G4Kywr2I+HPf//73V5YEZGTcJHj/44Ql\nJ2MkJLHCl2PC+463cU664CQeubEj9/hLUYwthTKkRFjKh6a0hvIQc78phaZJEoeDT05wD0KA7/+F\nsvCTUbjcx3UYZUTXN60nelMnaBPYp0tbqqRNFuB5fMuJBjk282/ulSnJQQu8ncnxLcUI8SnRNwGr\nv8Q8k/HhgutikOVY0gdvN07C8G+JkCGp9TFfPDyu0DgRurYu8H5npesjNaTuGQurrqXe6qtrn3yL\nkSMy35YtJL+rQiOXfG0yJJP59Sqkj5VHzS4MIVQ/PL6m27dsiynIRMwNoyxL+rM/+zP69NNP6eOP\nP6atrS0qijfu5zgSc29vjz7++GPn6lwUhVP0Op2O8+I4Pz+nXq9HBwcHdHJyQv1+n7a2tujRo0fU\n6/Xo4uKCBoMBjcfjlb1OuDLmc3XnRjnROy8PeDbwpUYgR6A0Qikluq6caXHyzRBBmgwGA+r3+ysK\nLbyBOp2OW2aDGUpuAPHlRYvFgjY2Nq6RM8gL0btNFvmMIyckMLhifxksYeJxwlCT9YmybW9v0+Hh\nIW1sbNB8PnfHfHJvD2ngQfHHEieUG/lE+OVy6Tb6vLy8vEZOYUYW8fR6PdrZ2XF7/QwGAzo5OVkx\nElutFm1tbdHDhw/dUjLs64PZne3tbTdTDCLv7OyMvv76a1cfKAefHZaf6XTq9h4aDAbU6XToT//0\nT1eMlYyM24Jm8KKP8pPFuOzhHgf8P/cqgDcCvCD43jCah14VQxHP1SUpfOn6yOfUuKoiNr6Qom8B\n+8SUZemIZ068cAVPjqsgMfj4IIkN2ba0pW/Sa1bLu5YfHl62LZ5XSbhI4gZl4OkgLa2tSmOmyXZY\nVZFuWgFvuh1n3D9g4hQe7MPhkPr9Pl1cXKxs0quR97HtURt7rOdTyNDbIFxC9zViYB1EfixxYsm6\nmL5vpSHJMVlWjTCIJYTk9SrkgNVmUsrN07XK4auHKgjVt0wrtk2uE5mIuSV8+eWXtFwu6Vvf+hbt\n7+/T1dWVW6ddliU9evTIEQggH7hrMdyQ4bYMsuXg4IB2d3fp6OiITk5OnOLI16RLhYl3Fr75LU+D\nu0fzZVR8xg4bTiJNxM0hNykkopU9VIiIzs/P6eLiwu0JgnDc4BmNRmo94DcnU/jsJZ+RtD5y42H+\nm2+QqJFL+IAw2dnZoe3tbdrc3HT5/vrrr53hpW2uCEUfpAXqZ3Nz0xFP2OQWS4QQn5yFxZIsnNDB\nT+yaTCY0GAzcHkAgVIjeeD3J/WEuLi6oLN8sQ9rb23PkG8gYvMPnz5/TixcvvAJbMuedToe++93v\n0v7+Pg2HQ/r+97+fSZiMWwf3VOAejFxOYIkfloYS6coWPiB1+XM4HUkeUa31H+1+1dnAlFmuVNwU\nCVNl1hGQM2ihesSEhgTeO99HLKQYa0tLrTFFuxcqo0WOyMkYXNPyouVN7pWmGZahOohFFeU8NqyP\nvMrISAE8tHGy2OnpKfX7fRoMBk6nB0J6UUhuWsatFk72w5skXWIQQyhXjTOFLODhtbEvxriPIZq1\n9GS+Q/m1YMn/KgjVoUX+ac/4xl0tn1WIwlhdRv6v0x80sqzq+JGJmFvEixcvaHt7mx49ekT7+/vU\narXcyTWTycTNuHHyYrlcOoLh8PDQ/f7GN75BRVHQ/v6+85x58uTJiuIlBTO/DpKBbyTLjQ98z2Yz\nGgwG146tBPjGhYiHkzpYwy5PCiIit0kxEbm9SIhs4SWNHgyEfFNXTmr49nXg91BungbCaUqr7My8\nvK1WiyaTCZ2fn7v9WIjeDNzY1JbHKwkd/t5A1p2enrrTK3yeLyBxQOAURUH9ft+RLvx9bW1trXir\n7O/vU6/Xc4rExsYGPXnyZCX+zc1Nms1mKycFDIdD2t/fp5/8yZ9cqT+UmxOCPM/b29v05MkT6nQ6\n9Pnnn+flSBl3Atw7gZMwIEJBPmPWE89wrwF4vvDlR1iqxJezyOWbeN4i0CVCyrnvGS3dptG0kVvF\n4NaQOiMmjRuMn9qEh8yHJOZ8M4OxZZIGQEiR9aXD8yWVemncWfFJYisGZVmu9BntvixvTJw8D1UU\n/IyMGGA8uLy8pLOzMzo5OaGLiwuns0m9jiOWfNB0Qzwj5YGG+9T+bzpv2jupIo9TyZ+Y/NQlU6rA\nIhh8BExs2jHlT332JtuLNv7U1W0yEXPLePr0Kc3nc/rkk09WiJbBYOAUfniCEJE5iwa8fv16hWSR\nx0JrCpSPydSUKihNvFNgeQzSwBIXqXBqM3wgk+B9opWLkyUyLxqkUidJGF43vJySkMGzCKPl36rH\nq6urFWILp2WgrnBdKvS8/uWePziK/MGDB9fqhde33IAYx03LNsD33+H3Xr9+vVI3vF55HXHDA4RX\nWb7ZQ0bWoe8dtdtt+vzzz+nly5d0eXmpvtOMjJsGJ2HQ7vmxvliih36Nvof9XWaz2cqHezVyg9an\n4KQoNU0pJD5FX6YfE4dlPDdNztRFrJKokWJ8rNOIDB/BIMcmjXzzERyhek4FLweHJAtDpImErx7m\nUDkAACAASURBVG5DZYtFap4yMuri4uKChsMhnZ+f09nZmTtJkk94EVWTd1IntYh5rd9I0viuIdTX\nU4hchE+p4yrvIyTHfWE1goMT6TFjbmyeEL9Grlch7mRYa3wLlZn/jimjNi5qeb0NXcI3NqeUMRMx\nt4zFYkHPnj2j58+f08/+7M+uEBp89hTLcPheKnzpCfcwgaEAMoQb/XxT1aIoVpYdwcjAzC4ndPie\nJPLaYrGgTqezciw3wkivF+5pgrA4mWlra8sZMSgzJwfa7bZbmsP3hcHSLY0gAtHAjX7eUbDMCu8C\n+UGeET83sPBesF8KF3R4H1tbW+5IcXgace8VGG9Y2oAZcixHw3Ii1Ll8b5LgQZzYxwbECxG5Mm5t\nbTnvGJBC3DAkIrfJHPKCZWY4UhV5Go1GzlsGeeCnMfHBH/v0cKJJbsD87NkzOj4+bqBHZWQ0C/Q5\n6bk3GAxoOBxSWb45lpiTNNjvBeSLXA4Zg6aVC5/SnvJsDGIJ89i4UpRfLRwfi6rmRSr5msKpkWs+\n5dWX55hyxcJK16dscyNBK1OIIPSlaz0j45XjdUbGXcTR0RGdnZ3R5eXlyomSQB0yW5tE5Pe133Lf\np9j0bgu3lSdN5vDrRGnktnzPsZMkPtnoS1+7Z6Up2422jFrm3ddu5dhgkRFV2z4Po01u+BATVuY1\nNv51EP3FbXWAoijunjS4ZWxsbNBP/MRPUK/XW9mrBUa3TzhYpypxYYzn+ekb0gOFEzxa5+EkAP7z\n/OD+crmk/f192tjYcIZJv993RBMv49XVFY1GI5rNZm4zWb7fC5bLgBiSpzrIE544AcA7MV9WA4MJ\nJA2e4R5EvA74xrLIuzTAUDa4o2KPE9SpFHIgfBAHr0dsCIwlYNyjBHFpJ1G1221HtvB2w48pxWw9\n30wZ77zdbruTlLDvy/b2NvV6PZrNZm4DaGzkC6KItyG+Tw0/0pzvs4NnptMpPX361HngZKyiLMu7\n5TLwAaEoivIXf/EXXTtG/x4Oh3RyckJHR0fOcxFkOPZeQh/TjNiUMVcqVTFETkz8MURMaj41AyFU\n5lA+YoxwbRZSIxGsTWb5Mxp4eLlETQvDy8wJPJmuHM9lPuRYbeVNU57l/RBpIhXdWANCxuO7prUR\nnxHBn5d5C+UpNXxdvJ2wyLL6A0RRFOW3v/1td/AC97T2EZGxso1PwvHwMm5p/GpjRYpBf5OoOj40\ngRAJQlSPvLeeL8tyRa/XZK+8Z6VhtTMp/+XYIuOwbD5tfJPx8vFWlpuHrVKXse0zZdzy1XcV+MYu\nwBonskfMHcJ0OqUf/vCH9NM//dO0tbXl1p3CwwDLluDhAEMe3gb8dA6EB6xOBg8beEvA20Yy6nww\ngFGPTsfT5RvH9no92tzcJCJyRjwUUxzHubGxQZubm7S7u+s2r4Rxw415eHTAI4boDYGBpTooC/LK\nPYSI3s0QwNMGJ5UgPyhbp9Ohsixpc3PT1fFkMnFG2Gw2o/F4TETk9oHhS3LghbS9vU0PHjxwhAjf\naBj1ivgwg4I9J/jmwMgf3jt25+fXcZwq30QZGyjLU1jwLOoTGzB3u90VMoYP7Mvlkk5PT+ny8pLK\nsqT9/X3XPnEcLxHR9vb2yvNIi7clvsxjNpvR119/nUmYjDsLbV+Y8XjsiFJskH11deVkBJePdVBF\nQUhRVrSwdRXPlHwgnK+cdUgAIKQMc1kXus7vy7xb8ct9Y0JKaYg88ZFA/PmYZ0PwpaORXVZYnq+Y\nsqdAe7+3aVRmfHg4Pz+n8XjsJresicxUSKIW0PoJ71eSiAnl5bb7S4wc1cI2BUmKWKhKWFljkCbr\ntTQ0stwHi4TW6lEby6y8hdK0wlYhYayxJZSHlPj5d5W8ybRTSTQX3211wCJ7xJjodDr0+PFj+qmf\n+ilHvsCIx2/NE4STCvx0Bx5OGsZEuhDUvE1kGA4ZHzwmNjY23Ca6fAmMxvTjOZ4H/u3bbJcPPFj2\nI08hAUmwsbFxbV8Vebws6o8LQE7uaEq677/GFvNvlB355PXB45Cb3fJ84KQmeLvwOpCbSWoDtLZ8\nSyuPNCqIaGW5HNLhafLwZfnG4+cHP/iBW96VoUNjzzNuBkVRlL/8y79MROQI2NFoRJeXl3RxcUH9\nfp9Go9EKuUrkdwWvoijwZ0OKSRNEzDp0ghiiJCUPMTNfmicKl3varJ0Whte53IiZP2ftnyIVaE3x\njikrz4NVJvyXadZpF5ZC7gtvhUl5t7734ktDXtfyFUKqcp49Yj5cFEVRdrvdFb06tU/L52L2hdFk\nmEbCaOndZYTy3TQR44vPR8Rr4WJkUGj89aUXIuit/MXAkpdWmrHlqELCaHlYl24iEVOPoTqxnn2r\nK2aPmPuA+XxOL168oE6nQ9/+9rev7VECw5roXYPgJyvxRgIPCRA4MO452SAJHW6sY5kRh2+tPScv\ncDQr8gHvG+4xwQ11vqcNJz5wdDf2K4EyjLi4Yor9YvipRXKzTZA1+CBOeJ0QrZJA0jMFdaCRMrwu\n5ebCfJCVJznx+pMElFzWw9+/NBJ6vd4KKYe6Qb3KAY2TQPjIMvCNSHEd9Yj88KPGQQjx98wxHo/p\nz//8z/PJSBl3HvBmw9Hz/X6fLi4uaDQarewRBdQlSTLuBmKVfUlk8/GrrsFgGXXayXMIL9PVSJk6\nedHQpIIcU2frNMoyMqqgDsEuIfXCWBJF0wkz0mCR2lqY0DXf85ZM9hF5VQijWFR5Xitb06hLLt0X\nZCLmDuOLL76gk5MTevLkycp17qnCyQDuhQDvDrlbu+aFwr+hTPJ9SEDm8E4h9y2R94jeGfLwSuH7\nJvD8871b+FIf7oEiBRSIGb4mV25krM1U8s15sQwJm9Jy7xlJmiBuePVwwgTQiAfUJ+oQ9Yh4+MbE\ncuaR1y/KxNNCenw/IewBg+N0QaKAGMGeLiC18C745rk8H3JGhucL8WFJ23Q6dcdqSy8B1Ol0OqXj\n4+PsBZNxL4D+gY3Ih8MhjUYjt4QwpBykKA8+D4D7iFgD3Sr3bSFW+fPNIEqkEHQx9ebzQpFjtc9w\nCBl7PkOhqfekEUgx8JUxpi1VfV8ZGRIpsjqmbWmEKr8n08L990GvSiUhmk7bR6po4fk9Te7ADtIm\nbDSPpqqkCM9T7Fga44GjhdPao7RftHD3Ta5qeebXYsmxULkzEXPHMRwO6enTp245DZGfpa3T2C0F\nLlUwhARZbOO1GONYt7DYQTG2zmR8oeck622Vv4qxouUrViBqZYitLyuMVVaebl6GlHHfgCOqLy8v\nV/Zc4h5qscbrTaCO/OdypE6eNSWwaSUsRb7z9KuMERo4EW+VjaetycZQnvFszDNaOqnw5Y/X37ra\nd9Pt46Zw34yLjOYhZUkqqcxlLyYRuTezL118y7CWEX3XcdsTEFX08xAsL0YtbY3c8RECkhiQz4UQ\nal++MdMaQ632n0JO1MVNtCOr3rV+6EMmYu4ByrKkq6ura8twLGgNgXdYqZTWUUit/Pria6oDagJT\nlitEQPB4UvKVUmc3PbCkvk+E1XZRr5sHvAN+GlVGxn3BxcWFW4qETXr5vks+pPafuscrAzHeEFVk\n0ToIGnmP34/xePDlKzWvvni0OtPI7ia9K7j8tPJnKcUginzEeUo+UyYsZBq+GUUrL+uATPM+ztBm\n3H3EyCbrGW0fRF9f4QSMtkfNTRq+VRGbL58e3aQ8kXLLSrdKOjE2R2h8togPiyBvQr76JnVD8t2K\n77YJNyBmIiWVUE1FJmLuEaD882U3WqfVOorWkXydywLSswaImFm/FEUsZjZAxm2dUhGazdNIKhk2\npaNZ7yaFBPIx4b48pZJKGtNdBZII48voMjLuGwaDAQ0Gg5Xj5LGskMvVJsiTppXmGMK+ynNV0tXk\ncV2ExpjYPMXE1zSqkmGanI4lFSyCyzIwrDqLGZObaFu+OmpKeb9tIyDj/YBsqzGTnBoxyMeBkE4o\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lvnsW8aOVBwSUtjRIG7/gYaKF52NerHdOrIJfxSNGLjXLyPBBLk0Koar33fsOTY6u05C3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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Cross sectional orthoslices of the dataset\n", + "plt.figure(figsize=(20,10))\n", + "plt.subplot(131)\n", + "plt.title('XY Plane Cross Section')\n", + "plt.imshow(image_array[:,:,50], cmap=plt.cm.gray)\n", + "\n", + "plt.subplot(132)\n", + "plt.title('XZ Plane Cross Section')\n", + "plt.imshow(image_array[:,250, :], cmap=plt.cm.gray)\n", + "\n", + "plt.subplot(133)\n", + "plt.title('YZ Plane Cross Section')\n", + "plt.imshow(image_array[250, :,:], plt.cm.gray)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image constants: array dimensions -- (512, 512, 245)\n", + "Image constants: data type -- int16\n", + "Image constants: max value -- 3617\n", + "Image constants: min value -- -1024\n" + ] + } + ], + "source": [ + "print 'Image constants: array dimensions -- ' + str(image_array.shape)\n", + "print 'Image constants: data type -- ' + str(image_array.dtype)\n", + "print 'Image constants: max value -- ' + str(np.amax(image_array))\n", + "print 'Image constants: min value -- ' + str(np.amin(image_array))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1000\n", + "1000\n" + ] + }, + { + "data": { + "image/png": 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BpJTDvB42AEdGfT7cr4sbK09iGIYRHylbnkREjkI1jxP850zgbeB84GPgJWCwc+6tOM9n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\nmFhK19/EH/A5fHVwN246yta/G3/wH5zeLwJuxR0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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from skxray.core.image import hist_make\n", + "bin_count, bin_edges, bin_avg = hist_make(image_array, 1000)\n", + "print len(bin_count)\n", + "print len(bin_avg)\n", + "plt.plot(bin_avg, bin_count, 'ro')\n", + "plt.yscale('log')\n", + "plt.title('Histogram Plot: Human Head Demonstration Data')\n", + "plt.xlabel('Pixel Intensity (HU)')\n", + "plt.ylabel('Count')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Object Conversion: Numpy array to VTK object" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dataImporter = vtk.vtkImageImport()\n", + "_NP_TO_VTK_dTYPE_DICT = {\n", + " 'bool' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'character' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'uint8' : dataImporter.SetDataScalarTypeToUnsignedChar(),\n", + " 'uint16' : dataImporter.SetDataScalarTypeToUnsignedShort(),\n", + " 'uint32' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'uint64' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'int8' : dataImporter.SetDataScalarTypeToShort(),\n", + " 'int16' : dataImporter.SetDataScalarTypeToShort(),\n", + " 'int32' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'int64' : dataImporter.SetDataScalarTypeToInt(),\n", + " 'float32' : dataImporter.SetDataScalarTypeToFloat(),\n", + " 'float64' : dataImporter.SetDataScalarTypeToDouble(),\n", + " }\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#vtk_data = vtk_tools.np_to_vtk(image_array, pixel_spacing)\n", + "from vtk.util.numpy_support import *" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol = vtk.vtkImageData()\n", + "vol.SetDimensions(image_array.shape[0], image_array.shape[1], image_array.shape[2])\n", + "vol.SetOrigin(0,0,0)\n", + "vol.SetSpacing(1,1,1)\n", + "\n", + "vtk_data = numpy_to_vtk(image_array.ravel(), deep=True)\n", + "\n", + "vol.GetPointData().SetScalars(vtk_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "no overloads of AddPoint() take 0 arguments", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mopacity_xfer_func\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvtk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvtkPiecewiseFunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mopacity_xfer_func\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAddPoint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m: no overloads of AddPoint() take 0 arguments" + ] + } + ], + "source": [ + "opacity_xfer_func = vtk.vtkPiecewiseFunction()\n", + "opacity_xfer_func.AddPoint()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "-32768" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vtk_data.GetDataTypeValueMin()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "z_dim, y_dim, x_dim = image_array.shape\n", + "_NP_TO_VTK_dTYPE_DICT[str(image_array.dtype)]\n", + "#help(dataImporter.SetInput)\n", + "#dataImporter.SetInput(vtk_data)\n", + "#dataImporter.SetDataScalarTypeToShort()\n", + "dataImporter.SetNumberOfScalarComponents(1)\n", + "dataImporter.SetDataExtent(0, x_dim-1, 0, y_dim-1, 0, z_dim-1)\n", + "dataImporter.SetWholeExtent(0, x_dim-1, 0, y_dim-1, 0, z_dim-1)\n", + "dataImporter.SetDataSpacing(pixel_spacing[0], pixel_spacing[1], pixel_spacing[2])\n", + "img_string = image_array.tostring()\n", + "dataImporter.CopyImportVoidPointer(img_string, len(img_string))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(vtkAlgorithmOutput)0x7fe7fd1d6410" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataImporter.GetOutputPort()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold_np = vtk.vtkImageThreshold()\n", + "threshold_np.SetInputDataObject(vol)\n", + "threshold_np.ThresholdByLower(450)\n", + "threshold_np.ReplaceInOn()\n", + "threshold_np.SetInValue(0)\n", + "threshold_np.ReplaceOutOn()\n", + "threshold_np.SetOutValue(1)\n", + "threshold_np.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "TypeError", + "evalue": "SetScalarType() takes exactly 2 arguments (1 given)", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mimg_object\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetSpacing\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpixel_spacing\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mimg_object\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetDimensions\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpixel_dims\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mimg_object\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSetScalarType\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvtk_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetDataType\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 6\u001b[0m \u001b[0mhelp\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_object\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetArrayPointer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[0mimg_object\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetArrayPointer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvtk_data\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m512\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m512\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m245\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mTypeError\u001b[0m: SetScalarType() takes exactly 2 arguments (1 given)" + ] + } + ], + "source": [ + "img_object = vtk.vtkImageData()\n", + "img_object.SetOrigin(0,0,0)\n", + "img_object.SetSpacing(pixel_spacing)\n", + "img_object.SetDimensions(pixel_dims)\n", + "img_object.SetScalarType(vtk_data.GetDataType())\n", + "help(img_object.GetArrayPointer)\n", + "img_object.GetArrayPointer(vtk_data, [512, 512, 245])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on built-in function GetAttributes:\n", + "\n", + "GetAttributes(...)\n", + " V.GetAttributes(int) -> vtkDataSetAttributes\n", + " C++: virtual vtkDataSetAttributes *GetAttributes(int type)\n", + " \n", + " Returns the attributes of the data object of the specified\n", + " attribute type. The type may be: POINT - Defined in vtkDataSet\n", + " subclasses. CELL - Defined in vtkDataSet subclasses. VERTEX -\n", + " Defined in vtkGraph subclasses. EDGE - Defined in vtkGraph\n", + " subclasses. ROW - Defined in vtkTable. The other attribute\n", + " type, FIELD, will return NULL since field data is stored as a\n", + " vtkFieldData instance, not a vtkDataSetAttributes instance. To\n", + " retrieve field data, use GetAttributesAsFieldData.\n", + "\n" + ] + } + ], + "source": [ + "help(img_object.GetAttributes)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'short'" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "img_object.GetScalarTypeAsString()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "array = img_object.GetPointData()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkPointData (0x40d2120)\n", + " Debug: Off\n", + " Modified Time: 14\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n" + ] + } + ], + "source": [ + "print array" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on built-in function GetAttributes:\n", + "\n", + "GetAttributes(...)\n", + " V.GetAttributes(int) -> vtkDataSetAttributes\n", + " C++: virtual vtkDataSetAttributes *GetAttributes(int type)\n", + " \n", + " Returns the attributes of the data object of the specified\n", + " attribute type. The type may be: POINT - Defined in vtkDataSet\n", + " subclasses. CELL - Defined in vtkDataSet subclasses. VERTEX -\n", + " Defined in vtkGraph subclasses. EDGE - Defined in vtkGraph\n", + " subclasses. ROW - Defined in vtkTable. The other attribute\n", + " type, FIELD, will return NULL since field data is stored as a\n", + " vtkFieldData instance, not a vtkDataSetAttributes instance. To\n", + " retrieve field data, use GetAttributesAsFieldData.\n", + "\n" + ] + } + ], + "source": [ + "help(img_object.GetAttributes)\n", + "tmp = img_object.GetAttributes(img_object.POINT)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vtkPointData (0x40d2120)\n", + " Debug: Off\n", + " Modified Time: 14\n", + " Reference Count: 2\n", + " Registered Events: (none)\n", + " Number Of Arrays: 0\n", + " Number Of Components: 0\n", + " Number Of Tuples: 0\n", + " Copy Tuple Flags: ( 1 1 1 1 1 0 1 1 )\n", + " Interpolate Flags: ( 1 1 1 1 1 0 0 1 )\n", + " Pass Through Flags: ( 1 1 1 1 1 1 1 1 )\n", + " Scalars: (none)\n", + " Vectors: (none)\n", + " Normals: (none)\n", + " TCoords: (none)\n", + " Tensors: (none)\n", + " GlobalIds: (none)\n", + " PedigreeIds: (none)\n", + " EdgeFlag: (none)\n", + "\n", + "\n" + ] + } + ], + "source": [ + "print tmp" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold_np = vtk.vtkImageThreshold()\n", + "threshold_np.SetInputConnection(vtk_data.GetOutputPort())\n", + "threshold_np.ThresholdByLower(450)\n", + "threshold_np.ReplaceInOn()\n", + "threshold_np.SetInValue(0)\n", + "threshold_np.ReplaceOutOn()\n", + "threshold_np.SetOutValue(1)\n", + "threshold_np.Update()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### File compilation directly using VTK. For comparison of data types and error checking to see why my converted data fails." + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "../data/CT/human_male/Head/\n" + ] + } + ], + "source": [ + "reader = vtk.vtkDICOMImageReader()\n", + "reader.SetDirectoryName(img_path)\n", + "reader.Update()\n", + "print img_path" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(0, 511, 0, 511, 0, 244)" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "_extent = reader.GetDataExtent()\n", + "_extent" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pixel_dims_vtk = [_extent[1]-_extent[0]+1, _extent[3]-_extent[2]+1, _extent[5]-_extent[4]+1]\n", + "pixel_spacing_vtk = reader.GetPixelSpacing()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[512, 512, 245]\n", + "(1.0, 1.0, 1.0)\n" + ] + } + ], + "source": [ + "print pixel_dims_vtk\n", + "print pixel_spacing_vtk" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on vtkobject object:\n", + "\n", + "class vtkobject(object)\n", + " | Use help(x.__class__) to get full documentation.\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | __delattr__(...)\n", + " | x.__delattr__('name') <==> del x.name\n", + " | \n", + " | __getattribute__(...)\n", + " | x.__getattribute__('name') <==> x.name\n", + " | \n", + " | __repr__(...)\n", + " | x.__repr__() <==> repr(x)\n", + " | \n", + " | __setattr__(...)\n", + " | x.__setattr__('name', value) <==> x.name = value\n", + " | \n", + " | __str__(...)\n", + " | x.__str__() <==> str(x)\n", + "\n" + ] + } + ], + "source": [ + "help(reader.GetOutput())" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "tmp = reader.GetOutput()" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on vtkobject object:\n", + "\n", + "class vtkobject(object)\n", + " | Use help(x.__class__) to get full documentation.\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | __delattr__(...)\n", + " | x.__delattr__('name') <==> del x.name\n", + " | \n", + " | __getattribute__(...)\n", + " | x.__getattribute__('name') <==> x.name\n", + " | \n", + " | __repr__(...)\n", + " | x.__repr__() <==> repr(x)\n", + " | \n", + " | __setattr__(...)\n", + " | x.__setattr__('name', value) <==> x.name = value\n", + " | \n", + " | __str__(...)\n", + " | x.__str__() <==> str(x)\n", + "\n" + ] + } + ], + "source": [ + "help(tmp)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on built-in function GetDimensions:\n", + "\n", + "GetDimensions(...)\n", + " V.GetDimensions() -> (int, int, int)\n", + " C++: virtual int *GetDimensions()\n", + " V.GetDimensions([int, int, int])\n", + " C++: virtual void GetDimensions(int dims[3])\n", + " \n", + " Get dimensions of this structured points dataset. It is the\n", + " number of points on each axis. Dimensions are computed from\n", + " Extents during this call.\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "(512, 512, 245)" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "help(tmp.GetDimensions)\n", + "tmp.GetDimensions()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(512, 512, 245)" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vol.GetDimensions()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on vtkobject object:\n", + "\n", + "class vtkobject(object)\n", + " | Use help(x.__class__) to get full documentation.\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | __delattr__(...)\n", + " | x.__delattr__('name') <==> del x.name\n", + " | \n", + " | __getattribute__(...)\n", + " | x.__getattribute__('name') <==> x.name\n", + " | \n", + " | __repr__(...)\n", + " | x.__repr__() <==> repr(x)\n", + " | \n", + " | __setattr__(...)\n", + " | x.__setattr__('name', value) <==> x.name = value\n", + " | \n", + " | __str__(...)\n", + " | x.__str__() <==> str(x)\n", + "\n" + ] + } + ], + "source": [ + "help(vol)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reader.GetInput\n" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "threshold = vtk.vtkImageThreshold()\n", + "threshold.SetInputConnection(reader.GetOutputPort())\n", + "#threshold.SetInputData(vol)\n", + "threshold.ThresholdByLower(450)\n", + "threshold.ReplaceInOn()\n", + "threshold.SetInValue(0)\n", + "threshold.ReplaceOutOn()\n", + "threshold.SetOutValue(1)\n", + "threshold.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dmc = vtk.vtkDiscreteMarchingCubes()\n", + "dmc.SetInputConnection(threshold_np.GetOutputPort())\n", + "dmc.GenerateValues(1,1,1)\n", + "dmc.Update()" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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BPKcGtPxhAgt6UsExyUKK0y8XnilnQb/30yd8QHMeSn3pBDF+zJIzs2NWCzxZ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\nJGDIMpGYZ40pdtELkDv7SgPupgDAj69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k1E+RyjGjSRUQgR79IwacG4xolBW6mwMxnHmO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\nnWQ4xim1oqGjyU7AxJsIFk6u0dnIfJbf8pFkeCqkqNNWiY+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V3otWxLJnQoxYKPjWmmWB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\nHWC6hvO0F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+ "text/plain": [ + "" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mapper = vtk.vtkPolyDataMapper()\n", + "mapper.SetInputConnection(dmc.GetOutputPort())\n", + "\n", + "actor = vtk.vtkActor()\n", + "actor.SetMapper(mapper)\n", + "renderer = vtk.vtkRenderer()\n", + "renderer.AddActor(actor)\n", + "renderer.SetBackground(0.7,0.7,0.7)\n", + "\n", + "camera = renderer.MakeCamera()\n", + "camera.SetPosition(-500.0, 245.5, 122.0)\n", + "camera.SetFocalPoint(301.0, 245.5, 122.0)\n", + "camera.SetViewAngle(30.0)\n", + "camera.SetRoll(-90.0)\n", + "renderer.SetActiveCamera(camera)\n", + "vtk_show(renderer, 600, 600)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "filename = 'tmp_file.stl'" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "path = '/home/giltis/data/'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "filename = path+filename" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/giltis/data/tmp_file.stl'" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filename" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/vtk_visualization.ipynb b/demos/tomography/visualization/vtk_visualization.ipynb new file mode 100644 index 00000000..158f8192 --- /dev/null +++ b/demos/tomography/visualization/vtk_visualization.ipynb @@ -0,0 +1,129 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import vtk\n", + "from IPython.display import Image\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def vtk_show(renderer, width=None, height=None):\n", + " \"\"\"\n", + " Converts a vtkRenderer object into an iPython image\n", + " \n", + " Note: This method generates an external window within which \n", + " rendering actually occurs. The generated image is then returned \n", + " to the ipython session.\n", + " \n", + " Ref: https://pyscience.wordpress.com/2014/09/03/ipython-notebook-vtk/\n", + " \"\"\"\n", + " if width == None:\n", + " width = 400\n", + " if height == None:\n", + " height=300\n", + " \n", + " renderWindow = vtk.vtkRenderWindow() #Create new rendering window\n", + " renderWindow.SetOffScreenRendering(1) #Enable off-screen rendering\n", + " renderWindow.AddRenderer(renderer) #Create instance\n", + " renderWindow.SetSize(width, height) #Set Dims\n", + " renderWindow.Render() #Execute render operation\n", + " \n", + " windowToImageFilter = vtk.vtkWindowToImageFilter() #Create a new vtkWindow -> Image filter object which allows us to read teh data in a vtkWindow and use it as input to the imaging pipeline.\n", + " windowToImageFilter.SetInput(renderWindow) #Add renderWindow to the filter object\n", + " windowToImageFilter.Update() #Update object\n", + " \n", + " writer = vtk.vtkPNGWriter() #Create vtk PNG writer object thereby allowing creation of PNG images of the vtkWindow rendering\n", + " writer.SetWriteToMemory(1) #Setting eq to 1 enables image to be held in memory instead of saving to disk. This is the desired option since the image is meant to be loaded back into the notebook instead of stored on disk\n", + " writer.SetInputConnection(windowToImageFilter.GetOutputPort()) # Link between output (GetOutputPort) of vtkWindowToImageFilter and the PNG writer (SetInputConnection)\n", + " writer.Write()\n", + " data = str(buffer(writer.GetResult()))\n", + " \n", + " return Image(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Rendering Example: A Red Ball\n", + "VtkSourceSphere = vtk.vtkSphereSource() #Create a sphere represented by polygons\n", + "VtkSourceSphere.SetCenter(0.0, 0.0, 0.0) #Define sphere center location\n", + "VtkSourceSphere.SetRadius(10.0) #Define radius of sphere\n", + "VtkSourceSphere.SetPhiResolution(360) #Define # of points to include in the latitudinal direction\n", + "VtkSourceSphere.SetThetaResolution(360) #Define # of points to include in the longitudinal direction\n", + "\n", + "VtkMapperSphere = vtk.vtkPolyDataMapper() #Maps polygonal data to graphics primatives\n", + "VtkMapperSphere.SetInputConnection(VtkSourceSphere.GetOutputPort()) #Connect output port of the sphere source to the input port of the mapper\n", + "\n", + "VtkActorSphere = vtk.vtkActor() #The actor represents the object or entity in the rendering scene\n", + "VtkActorSphere.SetMapper(VtkMapperSphere) # The mapper is connected to the actor in order to connect the sphere object to the actor that will represent it in the rendered image\n", + "VtkActorSphere.GetProperty().SetColor(1.0, 0.0, 0.0) #SetColor follows the RGB catalogue and each value can range from 0.0 to 1.0. Here the sphere color is being set to RED.\n", + "\n", + "VtkRenderer = vtk.vtkRenderer() #Create a new rendering object\n", + "VtkRenderer.SetBackground(0.5, 0.5, 0.5) #The background color is set to white (1.0, 1.0, 1.0). Conversely, black is (0.0, 0.0, 0.0), again following the RGB catalogue.\n", + "VtkRenderer.AddActor(VtkActorSphere) #Now the actor that is representing the sphere is connected to the renderer in order to generate the image.\n", + "\n", + "vtk_show(VtkRenderer) #Execute and display the rendered result in the ipython notebook." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/demos/tomography/visualization/vttools_arithmetic_demo.ipynb b/demos/tomography/visualization/vttools_arithmetic_demo.ipynb new file mode 100644 index 00000000..f0437d61 --- /dev/null +++ b/demos/tomography/visualization/vttools_arithmetic_demo.ipynb @@ -0,0 +1,179 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "No module named image_proc", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mskxray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mio\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mvtk_tools\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mvttools\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_wrap\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimage_proc\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0marithmetic\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marithmetic_expression\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;31mImportError\u001b[0m: No module named image_proc" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "import vtk\n", + "import numpy as np\n", + "\n", + "from skxray.io import vtk_tools\n", + "from vttools.to_wrap.image_proc import arithmetic, arithmetic_expression" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "data_matrix1 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix1[0:35, 0:35, 0:35] = 50\n", + "\n", + "data_matrix2 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix2[25:55, 25:55, 25:55] = 100\n", + "\n", + "data_matrix3 = np.zeros([75, 75, 75], dtype='uint8')\n", + "data_matrix3[45:74, 45:74, 45:74] = 150" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'arithmetic' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m#Arithmetic example #1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmerge_demo1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0marithmetic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'addition'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata_matrix1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata_matrix2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mmerge_demo1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0marithmetic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'addition'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmerge_demo1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata_matrix3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: name 'arithmetic' is not defined" + ] + } + ], + "source": [ + "#Arithmetic example #1\n", + "merge_demo1 = arithmetic('addition', data_matrix1, data_matrix2)\n", + "\n", + "merge_demo1 = arithmetic('addition', merge_demo1, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#Arithmetic example 2\n", + "merge_demo2 = arithmetic_expression('A*B+C', data_matrix1, data_matrix2, data_matrix3)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Data Conversion from numpy to VTK object\n", + "\n", + "vtkDemo_cube1 = vtk_tools.np_to_vtk(data_matrix2)\n", + "\n", + "vtkDemo_merge1 = vtk_tools.np_to_vtk(merge_demo1)\n", + "\n", + "vtkDemo_merge2 = vtk_tools.np_to_vtk(merge_demo2)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_cube1)\n", + "vtk_tools.vtk_viewer(vtkDemo_cube1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge1)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge1, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "volumeProperty = vtk_tools.vtk_vis_props(vtkDemo_merge2)\n", + "vtk_tools.vtk_viewer(vtkDemo_merge2, volumeProperty)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}