ax.plot(x, y, "bo", markersize=3, alpha=0.4)
ax.set_xlabel(k1)
ax.set_ylabel(k2)
plt.show(block=False)
if __name__ == "__main__":
metric = "log_likelihood_kde_3d"
# metric = "posterior"
# metric = "posterior_ks"
grid = ParameterGrid("blue_sedgwick_shen_final")
df = grid.load_best_sample(metric=metric)
dfo = load_sample()
cond = df["selected_jig"].values == 1
df = df[cond].reset_index(drop=True)
# pdf = TransformedGaussianPDF(df, makeplots=MAKEPLOTS)
pdf = TransformedKDE(df, makeplots=MAKEPLOTS)
pvals = pdf.evaluate(dfo)
print(np.log(pvals).sum())
# if MAKEPLOTS:
# pdf.summary_plot(dfo=dfo)
return result
if __name__ == "__main__":
model_name = "blue_final"
metric = "poisson_likelihood_2d"
confs = None
config = get_config()
image_dir = os.path.join(config["directories"]["data"], "images")
image_filename = os.path.join(image_dir, f"model_fit_{model_name}.png")
grid = ParameterGrid(model_name)
dfm = grid.load_best_sample(metric=metric)
dfo = load_sample()
keys = "uae_obs_jig", "rec_obs_jig"
range = {k: r for k, r in zip(keys, RANGE)}
dfs = grid.load_confident_samples(q=Q)
dfbest = grid.load_best_sample()
confs = get_confidence_intervals(dfs, dfbest, keys, range=range, bins=BINS1D)
fig = plt.figure(figsize=FIGSIZE)
spec = gridspec.GridSpec(ncols=10, nrows=2, figure=fig, hspace=0.35, wspace=1.6)
ax1 = fig.add_subplot(spec[:, :4])
ax2 = fig.add_subplot(spec[0, 4:])
ax3 = fig.add_subplot(spec[1, 4:])
"colour_obs": r"$(g-r)$"
}
OBSKEYS = {
"uae_obs_jig": "mueff_av",
"rec_obs_jig": "rec_arcsec",
"colour_obs": "g_r"
}
# TODO: Add KS values to graphs
# TODO: Make into grid method / plotting utils
if __name__ == "__main__":
grid = ParameterGrid(MODEL_NAME)
df = grid.load_best_sample(apply_prior=True, select=True)
df = df[df["selected_jig"].values == 1].reset_index(drop=True)
dfo = load_sample(select=True)
fig = plt.figure(figsize=(FIGHEIGHT * len(PAR_NAMES), FIGHEIGHT * 1.2))
for i, par_name in enumerate(PAR_NAMES):
ax = plt.subplot(1, len(PAR_NAMES), i + 1)
values = df[par_name].values
ax.hist(values, color="k", alpha=0.4, **HISTKWARGS)
if par_name in OBSKEYS:
values_obs = dfo[OBSKEYS[par_name]].values
rng = values.min(), values.max()