90 lines
1.8 KiB
Python
90 lines
1.8 KiB
Python
import plotstyle_plt
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from scipy.stats import norm
|
|
from plot_functions import xlabel, ylabel
|
|
from IPython import embed
|
|
|
|
# Analysis settings:
|
|
mode = ['thresh_lp', 'full', 'short', 'field'][0]
|
|
thresh_path = f'../data/inv/{mode}/thresholds.npz'
|
|
save_path = f'../figures/fig_kernel_sd_perc_{mode}_appendix.pdf'
|
|
|
|
# Plot settings:
|
|
fig_kwargs = dict(
|
|
figsize=(32/2.54, 15/2.54),
|
|
nrows=1,
|
|
ncols=1,
|
|
gridspec_kw=dict(
|
|
wspace=0,
|
|
hspace=0,
|
|
left=0.09,
|
|
right=0.99,
|
|
bottom=0.11,
|
|
top=0.98,
|
|
)
|
|
)
|
|
line_kwargs = dict(
|
|
c='black',
|
|
lw=1,
|
|
alpha=0.5,
|
|
)
|
|
fit_kwargs = dict(
|
|
c='red',
|
|
lw=3,
|
|
ls='--',
|
|
)
|
|
grid_line_kwargs = dict(
|
|
visible=True,
|
|
which='major',
|
|
axis='both',
|
|
color='k',
|
|
lw=0.5,
|
|
)
|
|
xlab = '$\\Theta_i\\,[\\text{multiples of }\\sigma_{c_i}]$'
|
|
ylab = '$\\mu_{f_i}\\,\\approx\\,P\\,(c_i > \\Theta_i)$'
|
|
xlab_kwargs = dict(
|
|
y=0,
|
|
fontsize=20,
|
|
ha='center',
|
|
va='bottom',
|
|
)
|
|
ylab_kwargs = dict(
|
|
x=0,
|
|
fontsize=20,
|
|
ha='center',
|
|
va='top',
|
|
)
|
|
xloc = 1
|
|
yloc = 0.25
|
|
|
|
# Load threshold data:
|
|
data = dict(np.load(thresh_path))
|
|
factors = data['factors']
|
|
perc = data['percs']
|
|
|
|
# Get Gaussian CDF for reference:
|
|
fit = norm.cdf(factors, loc=0, scale=1)[::-1]
|
|
|
|
# Prepare graph:
|
|
fig, ax = plt.subplots(**fig_kwargs)
|
|
ax.grid(**grid_line_kwargs)
|
|
ax.set_xlim(factors[0], factors[-1])
|
|
ax.set_ylim(-0.01, 1.01)
|
|
ax.xaxis.set_major_locator(plt.MultipleLocator(xloc))
|
|
ax.yaxis.set_major_locator(plt.MultipleLocator(yloc))
|
|
ylabel(ax, ylab, transform=fig.transFigure, **ylab_kwargs)
|
|
xlabel(ax, xlab, transform=fig.transFigure, **xlab_kwargs)
|
|
|
|
# Plotting:
|
|
ax.plot(factors, perc, **line_kwargs)
|
|
ax.plot(factors, fit, **fit_kwargs)
|
|
|
|
# Save figure:
|
|
fig.savefig(save_path)
|
|
|
|
plt.show()
|
|
print('Done.')
|
|
|
|
|