Having a simple mechanism to display distributions and descriptive statistics for phenotype information of a subset of subjects
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# Imports
import brainbox as bb
from matplotlib import pyplot as plt
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x = np.arange(100)
dist = 0.06
ticks = True
border = False
title = True
f = plt.figure(figsize=(6,6))
ax = f.add_subplot(111)
if not ticks:
ax.set_xticks([])
ax.set_yticks([])
if not border:
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.spines["bottom"].set_visible(False)
lt = bb.visuOps.add_subplot_axes(ax, [0, 0.5+dist/2, 0.5-dist/(2-title), 0.5-dist/(2-title)])
lt.set_title('left top')
if not ticks:
lt.set_xticks([])
lt.set_yticks([])
if not border:
lt.spines["top"].set_visible(False)
lt.spines["right"].set_visible(False)
lt.spines["left"].set_visible(False)
lt.spines["bottom"].set_visible(False)
lt.plot(x, np.sin((x)))
lb = bb.visuOps.add_subplot_axes(ax, [0, 0, 0.5-dist/(2-title), 0.5-dist/(2-title)])
lb.set_title('left bottom')
if not ticks:
lb.set_xticks([])
lb.set_yticks([])
if not border:
lb.spines["top"].set_visible(False)
lb.spines["right"].set_visible(False)
lb.spines["left"].set_visible(False)
lb.spines["bottom"].set_visible(False)
lb.plot(x, np.tan((x)))
rt = bb.visuOps.add_subplot_axes(ax, [0.5+dist/2, 0, 0.5-dist/(2-title), 0.5-dist/(2-title)])
rt.set_title('right top')
if not border:
rt.set_xticks([])
rt.set_yticks([])
if not border:
rt.spines["top"].set_visible(False)
rt.spines["right"].set_visible(False)
rt.spines["left"].set_visible(False)
rt.spines["bottom"].set_visible(False)
rt.plot(x, np.cos((x)))
rb = bb.visuOps.add_subplot_axes(ax, [0.5+dist/2, 0.5+dist/2, 0.5-dist/(2-title), 0.5-dist/(2-title)])
rb.set_title('right bottom')
if not ticks:
rb.set_xticks([])
rb.set_yticks([])
if not border:
rb.spines["top"].set_visible(False)
rb.spines["right"].set_visible(False)
rb.spines["left"].set_visible(False)
rb.spines["bottom"].set_visible(False)
rb.plot(x, x)
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