h0rton.h0_inference.plotting_utils¶
Module Contents¶
Functions¶
gaussian(x, mean, standard_deviation, amplitude) |
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plot_weighted_h0_histogram(all_samples, all_weights, lens_i=0, true_h0=None, include_fit_gaussian=True, save_dir=’.’) |
Plot the histogram of H0 samples, overlaid with a Gaussian fit and truth H0 |
plot_h0_histogram(samples, lens_i=0, true_h0=None, include_fit_gaussian=True, save_dir=’.’) |
Plot the histogram of H0 samples, overlaid with a Gaussian fit and truth H0 |
plot_D_dt_histogram(all_samples, lens_i=0, true_D_dt=None, save_dir=’.’) |
Plot the histogram of D_dt samples, overlaid with a Gaussian fit and truth D_dt |
plot_mcmc_corner(mcmc_samples, truth, col_labels, save_path) |
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plot_forward_modeling_comparisons(model_plot_instance, out_dir) |
Plot the data vs. model comparisons using the Lenstronomy modelPlot tool |
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h0rton.h0_inference.plotting_utils.plot_weighted_h0_histogram(all_samples, all_weights, lens_i=0, true_h0=None, include_fit_gaussian=True, save_dir='.')[source]¶ Plot the histogram of H0 samples, overlaid with a Gaussian fit and truth H0
- all_samples : np.array
- H0 samples
- all_weights : np.array
- H0 weights corresponding to all_samples, possibly including nan values
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h0rton.h0_inference.plotting_utils.plot_h0_histogram(samples, lens_i=0, true_h0=None, include_fit_gaussian=True, save_dir='.')[source]¶ Plot the histogram of H0 samples, overlaid with a Gaussian fit and truth H0
- all_samples : np.array
- H0 samples
- all_weights : np.array
- H0 weights corresponding to all_samples, possibly including nan values
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h0rton.h0_inference.plotting_utils.plot_D_dt_histogram(all_samples, lens_i=0, true_D_dt=None, save_dir='.')[source]¶ Plot the histogram of D_dt samples, overlaid with a Gaussian fit and truth D_dt
- all_samples : np.array
- D_dt MCMC samples
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h0rton.h0_inference.plotting_utils.plot_mcmc_corner(mcmc_samples, truth, col_labels, save_path)[source]¶
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h0rton.h0_inference.plotting_utils.plot_forward_modeling_comparisons(model_plot_instance, out_dir)[source]¶ Plot the data vs. model comparisons using the Lenstronomy modelPlot tool
model_plot_instance : lenstronomy.Plots.model_plot.ModelPlot object out_dir : directory in which the plots will be saved