Added multi-thresh simulation to "full" and "short" (currently running).

Added complete "rect-lp" analysis except figure.
Added multiple appendix figs.
Overhauled normalization options across all condense scripts.

Co-authored-by: Copilot <copilot@github.com>

python/fig_kernel_sd_perc_appendix.py

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+import plotstyle_plt
+import numpy as np
+import matplotlib.pyplot as plt
+from thunderhopper.modeltools import load_data
+from thunderhopper.filetools import search_files, crop_paths
+from plot_functions import xlabel, ylabel
+from IPython import embed
+
+# Analysis settings:
+mode = ['thresh_lp', 'full', 'short', 'field'][3]
+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, 16/2.54),
+    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(
+    color='black',
+    lw=1,
+    alpha=0.5,
+)
+xlab = '$\\text{multiple of }\\sigma_{k_i}$'
+ylab = '$P\\,(c_i > \\Theta_i)$'
+xlab_kwargs = dict(
+    y=0,
+    fontsize=20,
+    ha='center',
+    va='bottom',
+)
+ylab_kwargs = dict(
+    x=0,
+    fontsize=20,
+    ha='center',
+    va='top',
+)
+
+# Load threshold data:
+data = dict(np.load(thresh_path))
+factors = data['factors']
+perc = data['percs']
+
+# Prepare graph:
+fig, ax = plt.subplots(**fig_kwargs)
+ax.set_xlim(factors[0], factors[-1])
+ax.set_ylim(0, 1)
+ylabel(ax, ylab, transform=fig.transFigure, **ylab_kwargs)
+xlabel(ax, xlab, transform=fig.transFigure, **xlab_kwargs)
+
+# Plotting:
+ax.plot(factors, perc, **line_kwargs)
+
+# Save figure:
+fig.savefig(save_path)
+
+plt.show()
+print('Done.')
+
+