🎉 feat(sample.py) add option to overwrite folder in save

docs/conf.py

@@ -14,23 +14,18 @@
 # -- Path setup --------------------------------------------------------------
 
 import datetime
-import os
 import sys
 import subprocess
-
-# If extensions (or modules to document with autodoc) are in another directory,
-# add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
-#
+from pathlib import Path
 
 sys.path.insert(0, ".")
 sys.path.insert(0, "../")
 
-basedir = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+basedir = Path(__file__).absolute().parent.parent
 sys.path.insert(0, basedir)
-sys.path.insert(0, os.path.join(basedir, "src/plaid"))
-# sys.path.insert(0, os.path.join(basedir, "tests"))
-sys.path.insert(0, os.path.join(basedir, "examples"))
+sys.path.insert(0, basedir / "src" / "plaid")
+# sys.path.insert(0, basedir / "tests")
+sys.path.insert(0, basedir / "examples")
 print(sys.path)
 
 
@@ -278,4 +273,4 @@ def get_git_info():
         return "unknown"
 
 release = get_git_info()
-version = release
+version = release

docs/source/notebooks/bisect.ipynb

@@ -17,7 +17,8 @@
    "outputs": [],
    "source": [
     "# Importing Required Libraries\n",
-    "import os\n",
+    "from typing import Union\n",
+    "from pathlib import Path\n",
     "\n",
     "from plaid.containers.dataset import Dataset\n",
     "from plaid.post.bisect import plot_bisect, prepare_datasets\n",
@@ -30,24 +31,25 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def get_project_root(path: str, index=3) -> str:\n",
+    "def get_project_root(path: Union[str, Path], index: int=3) -> Path:\n",
     "    \"\"\"Find the project root path\n",
     "\n",
     "    Args:\n",
-    "        path (str): Current path of the notebook\n",
+    "        path (Union[str, Path]): Current path of the notebook\n",
     "        index (int, optional): The number of parents to go back. Defaults to 3.\n",
     "\n",
     "    Returns:\n",
-    "        str: The project root path\n",
+    "        Path: The project root path\n",
     "    \"\"\"\n",
+    "    path = Path(path)\n",
     "    if index == 0:\n",
     "        return path\n",
-    "    return get_project_root(os.path.dirname(path), index - 1)\n",
+    "    return get_project_root(path.parent, index - 1)\n",
     "\n",
     "\n",
     "# Setting up Directories\n",
-    "current_directory = os.getcwd()\n",
-    "dataset_directory = os.path.join(get_project_root(current_directory), \"tests\", \"post\")"
+    "current_directory = Path.cwd()\n",
+    "dataset_directory = get_project_root(current_directory) / \"tests\" / \"post\""
    ]
   },
   {
@@ -66,9 +68,9 @@
    "outputs": [],
    "source": [
     "# Load PLAID datasets and problem metadata objects\n",
-    "ref_ds = Dataset(os.path.join(dataset_directory, \"dataset_ref\"))\n",
-    "pred_ds = Dataset(os.path.join(dataset_directory, \"dataset_near_pred\"))\n",
-    "problem = ProblemDefinition(os.path.join(dataset_directory, \"problem_definition\"))\n",
+    "ref_ds = Dataset(dataset_directory / \"dataset_ref\")\n",
+    "pred_ds = Dataset(dataset_directory / \"dataset_near_pred\")\n",
+    "problem = ProblemDefinition(dataset_directory / \"problem_definition\")\n",
     "\n",
     "# Get output scalars from reference and prediction dataset\n",
     "ref_out_scalars, pred_out_scalars, out_scalars_names = prepare_datasets(\n",
@@ -117,9 +119,9 @@
     "print(\"=== Plot with file paths ===\")\n",
     "\n",
     "# Load PLAID datasets and problem metadata from files\n",
-    "ref_path = os.path.join(dataset_directory, \"dataset_ref\")\n",
-    "pred_path = os.path.join(dataset_directory, \"dataset_pred\")\n",
-    "problem_path = os.path.join(dataset_directory, \"problem_definition\")\n",
+    "ref_path = dataset_directory / \"dataset_ref\"\n",
+    "pred_path = dataset_directory / \"dataset_pred\"\n",
+    "problem_path = dataset_directory / \"problem_definition\"\n",
     "\n",
     "# Using file paths to generate bisect plot on scalar_2\n",
     "plot_bisect(ref_path, pred_path, problem_path, \"scalar_2\", \"differ_bisect_plot\")"
@@ -143,9 +145,9 @@
     "print(\"=== Plot with PLAID objects ===\")\n",
     "\n",
     "# Load PLAID datasets and problem metadata objects\n",
-    "ref_path = Dataset(os.path.join(dataset_directory, \"dataset_ref\"))\n",
-    "pred_path = Dataset(os.path.join(dataset_directory, \"dataset_ref\"))\n",
-    "problem_path = ProblemDefinition(os.path.join(dataset_directory, \"problem_definition\"))\n",
+    "ref_path = Dataset(dataset_directory / \"dataset_ref\")\n",
+    "pred_path = Dataset(dataset_directory / \"dataset_pred\")\n",
+    "problem_path = ProblemDefinition(dataset_directory / \"problem_definition\")\n",
     "\n",
     "# Using PLAID objects to generate bisect plot on scalar_2\n",
     "plot_bisect(ref_path, pred_path, problem_path, \"scalar_2\", \"equal_bisect_plot\")"
@@ -169,9 +171,9 @@
     "print(\"=== Mix with scalar index and verbose ===\")\n",
     "\n",
     "# Mix\n",
-    "ref_path = os.path.join(dataset_directory, \"dataset_ref\")\n",
-    "pred_path = os.path.join(dataset_directory, \"dataset_near_pred\")\n",
-    "problem_path = ProblemDefinition(os.path.join(dataset_directory, \"problem_definition\"))\n",
+    "ref_path = dataset_directory / \"dataset_ref\"\n",
+    "pred_path = dataset_directory / \"dataset_near_pred\"\n",
+    "problem_path = ProblemDefinition(dataset_directory / \"problem_definition\")\n",
     "\n",
     "# Using scalar index and verbose option to generate bisect plot\n",
     "scalar_index = 0\n",

docs/source/notebooks/metrics.ipynb

@@ -17,7 +17,8 @@
    "outputs": [],
    "source": [
     "# Importing Required Libraries\n",
-    "import os\n",
+    "from typing import Union\n",
+    "from pathlib import Path\n",
     "\n",
     "from plaid.containers.dataset import Dataset\n",
     "from plaid.post.metrics import compute_metrics, prepare_datasets, pretty_metrics\n",
@@ -30,24 +31,25 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def get_project_root(path: str, index=3) -> str:\n",
+    "def get_project_root(path: Union[str, Path], index=3) -> Path:\n",
     "    \"\"\"Find the project root path\n",
     "\n",
     "    Args:\n",
-    "        path (str): Current path of the notebook\n",
+    "        path (Union[str, Path]): Current path of the notebook\n",
     "        index (int, optional): The number of parents to go back. Defaults to 3.\n",
     "\n",
     "    Returns:\n",
-    "        str: The project root path\n",
+    "        Path: The project root path\n",
     "    \"\"\"\n",
+    "    path = Path(path)\n",
     "    if index == 0:\n",
     "        return path\n",
-    "    return get_project_root(os.path.dirname(path), index - 1)\n",
+    "    return get_project_root(path.parent, index - 1)\n",
     "\n",
     "\n",
     "# Setting up Directories\n",
-    "current_directory = os.getcwd()\n",
-    "dataset_directory = os.path.join(get_project_root(current_directory), \"tests\", \"post\")"
+    "current_directory = Path.cwd()\n",
+    "dataset_directory = current_directory / \"tests\" / \"post\""
    ]
   },
   {
@@ -66,9 +68,9 @@
    "outputs": [],
    "source": [
     "# Load PLAID datasets and problem metadata objects\n",
-    "ref_ds = Dataset(os.path.join(dataset_directory, \"dataset_ref\"))\n",
-    "pred_ds = Dataset(os.path.join(dataset_directory, \"dataset_near_pred\"))\n",
-    "problem = ProblemDefinition(os.path.join(dataset_directory, \"problem_definition\"))\n",
+    "ref_ds = Dataset(dataset_directory / \"dataset_ref\")\n",
+    "pred_ds = Dataset(dataset_directory / \"dataset_near_pred\")\n",
+    "problem = ProblemDefinition(dataset_directory / \"problem_definition\")\n",
     "\n",
     "# Get output scalars from reference and prediction dataset\n",
     "ref_out_scalars, pred_out_scalars, out_scalars_names = prepare_datasets(\n",
@@ -117,9 +119,9 @@
     "print(\"=== Metrics with file paths ===\")\n",
     "\n",
     "# Load PLAID datasets and problem metadata file paths\n",
-    "ref_ds = os.path.join(dataset_directory, \"dataset_ref\")\n",
-    "pred_ds = os.path.join(dataset_directory, \"dataset_near_pred\")\n",
-    "problem = os.path.join(dataset_directory, \"problem_definition\")\n",
+    "ref_ds = dataset_directory / \"dataset_ref\"\n",
+    "pred_ds = dataset_directory / \"dataset_near_pred\"\n",
+    "problem = dataset_directory / \"problem_definition\"\n",
     "\n",
     "# Using file paths to generate metrics\n",
     "metrics = compute_metrics(ref_ds, pred_ds, problem, \"first_metrics\")\n",
@@ -148,9 +150,9 @@
     "print(\"=== Metrics with PLAID objects and verbose ===\")\n",
     "\n",
     "# Load PLAID datasets and problem metadata objects\n",
-    "ref_ds = Dataset(os.path.join(dataset_directory, \"dataset_ref\"))\n",
-    "pred_ds = Dataset(os.path.join(dataset_directory, \"dataset_pred\"))\n",
-    "problem = ProblemDefinition(os.path.join(dataset_directory, \"problem_definition\"))\n",
+    "ref_ds = Dataset(dataset_directory / \"dataset_ref\")\n",
+    "pred_ds = Dataset(dataset_directory / \"dataset_pred\")\n",
+    "problem = ProblemDefinition(dataset_directory / \"problem_definition\")\n",
     "\n",
     "# Pretty print activated with verbose mode\n",
     "metrics = compute_metrics(ref_ds, pred_ds, problem, \"second_metrics\", verbose=True)"

docs/source/notebooks/problem_definition.ipynb

@@ -24,7 +24,7 @@
    "outputs": [],
    "source": [
     "# Import required libraries\n",
-    "import os\n",
+    "from pathlib import Path\n",
     "\n",
     "import numpy as np"
    ]
@@ -229,9 +229,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "test_pth = f\"/tmp/test_safe_to_delete_{np.random.randint(1e10, 1e12)}\"\n",
-    "pb_def_save_fname = os.path.join(test_pth, \"test\")\n",
-    "os.makedirs(test_pth)\n",
+    "test_pth = Path(f\"/tmp/test_safe_to_delete_{np.random.randint(1e10, 1e12)}\")\n",
+    "pb_def_save_fname = test_pth / \"test\"\n",
+    "test_pth.mkdir(parents=True, exist_ok=True)\n",
     "print(f\"saving path: {pb_def_save_fname}\")\n",
     "\n",
     "problem._save_to_dir_(pb_def_save_fname)"

docs/source/notebooks/sample.ipynb

@@ -25,7 +25,7 @@
    "outputs": [],
    "source": [
     "# Import required libraries\n",
-    "import os\n",
+    "from pathlib import Path\n",
     "\n",
     "import numpy as np"
    ]
@@ -255,9 +255,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "path_linked_sample = os.path.join(\n",
-    "    os.getcwd(), \"dataset/samples/sample_000000000/meshes/mesh_000000000.cgns\"\n",
-    ")\n",
+    "path_linked_sample = Path.cwd() / \"dataset/samples/sample_000000000/meshes/mesh_000000000.cgns\"\n",
     "new_sample_mult_mesh.link_tree(\n",
     "    path_linked_sample, linked_sample=sample, linked_time=0.0, time=1.5\n",
     ")\n",
@@ -929,10 +927,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "test_pth = f\"/tmp/test_safe_to_delete_{np.random.randint(1e10, 1e12)}\"\n",
-    "os.makedirs(test_pth)\n",
+    "test_pth = Path(f\"/tmp/test_safe_to_delete_{np.random.randint(1e10, 1e12)}\")\n",
+    "test_pth.mkdir(parents=True, exist_ok=True)\n",
     "\n",
-    "sample_save_fname = os.path.join(test_pth, \"test\")\n",
+    "sample_save_fname = test_pth / \"test\"\n",
     "print(f\"saving path: {sample_save_fname}\")\n",
     "\n",
     "sample.save(sample_save_fname)"
@@ -969,9 +967,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "new_sample_2 = Sample.load_from_dir(os.path.join(test_pth, \"test\"))\n",
+    "new_sample_2 = Sample.load_from_dir(test_pth / \"test\")\n",
     "\n",
-    "show_sample(new_sample)"
+    "show_sample(new_sample_2)"
    ]
   },
   {

examples/containers/dataset_example.py

@@ -15,6 +15,7 @@
 # %%
 # Import required libraries
 import os
+from pathlib import Path
 
 # %%
 # Import necessary libraries and functions
@@ -388,8 +389,8 @@ def dprint(name: str, dictio: dict, end: str = "\n"):
 # ### Save the dataset to a TAR (Tape Archive) file
 
 # %%
-tmpdir = f"/tmp/test_safe_to_delete_{np.random.randint(low=1, high=2_000_000_000)}"
-tmpfile = os.path.join(tmpdir, "test_file.plaid")
+tmpdir = Path(f"/tmp/test_safe_to_delete_{np.random.randint(low=1, high=2_000_000_000)}")
+tmpfile = tmpdir / "test_file.plaid"
 
 print(f"Save dataset in: {tmpfile}")
 dataset.save(tmpfile)

examples/containers/sample_example.py

@@ -14,7 +14,7 @@
 
 # %%
 # Import required libraries
-import os
+from pathlib import Path
 
 # %%
 # Import necessary libraries and functions
@@ -517,10 +517,10 @@ def show_sample(sample: Sample):
 # ### Save Sample to as a file tree
 
 # %%
-test_pth = f"/tmp/test_safe_to_delete_{np.random.randint(low=1, high=2_000_000_000)}"
-os.makedirs(test_pth)
+test_pth = Path(f"/tmp/test_safe_to_delete_{np.random.randint(low=1, high=2_000_000_000)}")
+test_pth.mkdir(parents=True, exist_ok=True)
 
-sample_save_fname = os.path.join(test_pth, "test")
+sample_save_fname = test_pth / "test"
 print(f"saving path: {sample_save_fname}")
 
 sample.save(sample_save_fname)
@@ -537,7 +537,7 @@ def show_sample(sample: Sample):
 # ### Load a Sample from a directory via the Sample class
 
 # %%
-new_sample_2 = Sample.load_from_dir(os.path.join(test_pth, "test"))
+new_sample_2 = Sample.load_from_dir(test_pth / "test")
 
 show_sample(new_sample)