4. RS CVn Stars Corner Plots

4.1. Notebook setup

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import emcee
import corner
import warnings
warnings.filterwarnings('ignore')

4.2. Download data

Unzip the contents into a folder named data in the same level as the notebooks folder. The directory structure should end up looking like the following:

thermal-gs
├── data
│   ├── HR1099_chain.h5
│   ├── HR1099_lmfit_params.txt
│   ├── thermal-gs.mplstyle
│   ├── UXArietis_chain.h5
│   ├── UXArietis_lmfit_params.txt
│   ├── ...
├── figures
│   ├── HR1099_corner.pdf
│   ├── HR1099_corner.png
│   ├── UXArietis_corner.pdf
│   ├── UXArietis_corner.png
│   ├── ...
├── notebooks
│   ├── rs-cvn_corner-plots.ipynb
│   ├── ...
.
.
.

4.3. Load

HR_sampler = emcee.backends.HDFBackend('../data/HR1099_chain.h5')
HR_samples = HR_sampler.get_chain(flat=True)
HR_samples /= np.array([1, 1, 1, 1, np.pi/180])
HR_lmfit_params = np.loadtxt('../data/HR1099_lmfit_params.txt')
HR_lmfit_params /= np.array([1, 1, 1, 1, np.pi/180])

UX_sampler = emcee.backends.HDFBackend('../data/UXArietis_chain.h5')
UX_samples = UX_sampler.get_chain(flat=True)
UX_samples /= np.array([1, 1, 1, 1, np.pi/180])
UX_lmfit_params = np.loadtxt('../data/UXArietis_lmfit_params.txt')
UX_lmfit_params /= np.array([1, 1, 1, 1, np.pi/180])

plt.style.use('../data/thermal-gs.mplstyle')

4.4. Plot

fig = plt.figure(figsize=(8, 4))
subfigs = fig.subfigures(1, 2, hspace=0, wspace=0)
plt_labels = ['$L$', '$\delta$', '$n_e$', '$B$', '$\phi$']

# HR 1099
thin = 10000
median_values = np.median(HR_samples[::thin, :], axis=0)
cmap = mpl.cm.get_cmap('Blues')
cmap.set_under(color='w')

cornerFig = corner.corner(HR_samples[::thin, :],color='black',top_ticks=True,quiet=True, show_titles=True,use_math_text=True,
labels=plt_labels,plot_datapoints=False, title_quantiles=[0.16, 0.5, 0.84], label_kwargs={"fontsize":8}, 
title_kwargs={"fontsize":7}, max_n_ticks=4, bins=25, title_fmt='3.3g', plot_density=False, fill_contours=True,
levels=(0.393, 0.865, 0.989), hist_kwargs={'linewidth':0.75, 'color':cmap(0.75)}, fig=subfigs[0], 
contour_kwargs={'linewidths':0.5, 'colors':'black'}, labelpad=0.05,
contourf_kwargs={'colors':(cmap(-1), cmap(0.25), cmap(0.75), cmap(0.999)), 'alpha':0.75})
corner.overplot_lines(cornerFig, HR_lmfit_params, color='C0', label='Least squares', lw=1)
corner.overplot_points(cornerFig, np.array([HR_lmfit_params]), color='C0', marker='s', ms=3)
corner.overplot_lines(cornerFig, median_values, color='black', label='Median', lw=1)
corner.overplot_points(cornerFig, np.array([median_values]), color='black', marker='s', ms=3)

for axis in cornerFig.axes:
    for side in ['top','bottom','left','right']:
        axis.spines[side].set_linewidth(1)
    axis.tick_params(axis='both', which='major', labelsize=6, length=3)

# UX Arietis
thin = 10
median_values = np.median(UX_samples[::thin, :], axis=0)
cmap = mpl.cm.get_cmap('Greens')
cmap.set_under(color='w')

cornerFig = corner.corner(UX_samples[::thin, :],color='black',top_ticks=True,quiet=True, show_titles=True,use_math_text=True,
labels=plt_labels,plot_datapoints=False, title_quantiles=[0.16, 0.5, 0.84], label_kwargs={"fontsize":8}, 
title_kwargs={"fontsize":7}, max_n_ticks=4, bins=25, title_fmt='3.3g', plot_density=False, fill_contours=True,
levels=(0.393, 0.865, 0.989), hist_kwargs={'linewidth':0.75, 'color':cmap(0.75)}, fig=subfigs[1], 
contour_kwargs={'linewidths':0.5, 'colors':'black'}, labelpad=0.05,
contourf_kwargs={'colors':(cmap(-1), cmap(0.25), cmap(0.75), cmap(0.999)), 'alpha':0.75})
corner.overplot_lines(cornerFig, UX_lmfit_params, color='C0', label='Least squares', lw=1)
corner.overplot_points(cornerFig, np.array([UX_lmfit_params]), color='C0', marker='s', ms=3)
corner.overplot_lines(cornerFig, median_values, color='black', label='Median', lw=1)
corner.overplot_points(cornerFig, np.array([median_values]), color='black', marker='s', ms=3)

for axis in cornerFig.axes:
    for side in ['top','bottom','left','right']:
        axis.spines[side].set_linewidth(1)
    axis.tick_params(axis='both', which='major', labelsize=6, length=3)

handles,labels = cornerFig.gca().get_legend_handles_labels()
by_label = dict(zip(labels, handles))
cornerFig.legend(by_label.values(), by_label.keys(), fontsize=10, loc='upper right')
subfigs[0].text(0.40, -0.05, '(a) HR 1099', fontsize=12)
subfigs[1].text(0.40, -0.05, '(b) UX Arietis', fontsize=12)

cornerFig.set_facecolor('white')
plt.savefig('../figures/rs-cvn_corner-plots.png', bbox_inches='tight')
plt.savefig('../figures/rs-cvn_corner-plots.pdf', bbox_inches='tight')
plt.show()