"linewidth": 1.5,
"color": "springgreen",
"linestyle": "--"
}
FONTSIZE = 14
model_name = "blue_sedgwick_shen_final"
xkey = "rec_phys_offset_alpha"
ykey = "logmstar_a"
zkey_noprior = "likelihood_kde_3d"
zkey = "posterior_kde_3d"
xlabel = r"$\beta$"
ylabel = r"$\alpha$"
grid = ParameterGrid(model_name)
df = grid.load_metrics()
metrics = grid.get_best_metrics(metric=zkey)
x = df[xkey].values
y = df[ykey].values
znoprior = df[zkey_noprior].values
z = df[zkey].values
xrange = x.min(), 0.675
yrange = -1.675, -1.225
# xrange = x.min(), x.max()
# yrange = y.min(), y.max()
fig = plt.figure(figsize=(7, 7))
spec = GridSpec(ncols=10, nrows=10, figure=fig)
ax0 = fig.add_subplot(spec[3:10, 0:7])
model_name = "blue_sedgwick_shen_highkink"
model_type = "udgsizes.model.sm_size.Model"
config = get_config()
config["grid"][model_type]["parameters"]["rec_phys_offset"]["alpha"][
"max"] = 0.6
config["grid"][model_type]["parameters"]["rec_phys_offset"]["alpha"][
"step"] = 0.05
config["grid"][model_type]["parameters"]["logmstar"]["a"]["min"] = -1.50
config["grid"][model_type]["parameters"]["logmstar"]["a"]["max"] = -1.45
config["grid"][model_type]["parameters"]["logmstar"]["a"]["step"] = 0.05
metrics_ignore = ["kstest_2d"] # Takes too long for whole grid
n_samples = 500
burnin = 250
grid = ParameterGrid(model_name, config=config)
if CHECK_INITIAL_VALUES:
grid.check_initial_values()
if SAMPLE:
grid.sample(overwrite=True, n_samples=n_samples, burnin=burnin)
grid.evaluate(metrics_ignore=metrics_ignore)
dfm = grid.load_metrics()
if MAKEPLOTS:
grid.summary_plot()
plt.show(block=False)