"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)