import matplotlib.pyplot as plt
import numpy as np

fields = [
    "q_850",
]

data_ref = {
    "q_850": 1.125651E-03,
    "t_850": 1.151291E+00,
    "u_850": 1.916980E+00,
    "v_850": 1.840032E+00,
    "z_500": 1.075307E+02,
    "10u": 1.342692E+00,
    "10v": 1.363811E+00,
    "2t": 1.289473E+00,
}
# data_exp = {
#     "q_850": 1.147168E-03,
#     "t_850": 1.205859E+00,
#     "u_850": 1.968734E+00,
#     "v_850": 1.891413E+00,
#     "z_500": 1.216451E+02,
#     "10u": 1.214067,
#     "10v": 1.243045,
#     "2t": 1.068439E+00,
# }
data_exp = {
    "q_850": 1.122758E-03,
    "t_850": 1.146472E+00,
    "u_850": 1.918213E+00 ,
    "v_850": 1.836079E+00,
    "z_500": 1.096801E+02,
    "10u": 1.342595,
    "10v": 1.361598,
    "2t": 1.287225,
}



leg = []
vals = []
for k, v in data_ref.items():
    leg += [k]
    vals += [data_exp[k] / v]
vals = np.array(vals) - 1.0

cmap = plt.get_cmap("bwr")
vals_centered = 1.0 - ((vals / (vals / 0.5).min()) + 0.5)
colors = [cmap(v) for v in vals_centered]

fig = plt.figure(figsize=(10, 7), dpi=300)
ax = plt.gca()

ax.barh(np.arange(len(vals)), vals, color=colors, align="center", edgecolor="black", linewidth=0.5)
ax.set_yticks(np.arange(len(vals)), labels=leg)
ax.invert_yaxis()  # labels read top-to-bottom
ax.set_xlabel("Relative RMSE: experiment / reference")

plt.savefig("era5_no_adaln.png")