46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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from plotstyle import *
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# data:
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rng = np.random.RandomState(981)
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data = rng.randn(100)
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xs = np.sort(data)
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cdf = np.arange(len(xs))/float(len(xs))
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# Gauss:
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dx = 0.01
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xx = np.arange(-4.0, 4.0, dx)
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gauss = np.exp(-0.5*xx*xx)/np.sqrt(2.0*np.pi)
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gausscdf = np.cumsum(gauss)*dx
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# plot:
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fig, ax = plt.subplots(figsize=cm_size(figure_width, 1.2*figure_height))
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ax.set_xlabel('x')
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ax.set_xlim(-3.2, 3.2)
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ax.set_xticks(np.arange(-3.0, 3.1, 1.0))
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ax.set_ylabel('F(x)')
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ax.set_ylim(-0.05, 1.05)
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ax.set_yticks(np.arange(0.0, 1.1, 0.2))
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med = xs[cdf>=0.5][0]
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ax.plot([-3.2, med, med], [0.5, 0.5, 0.0], zorder=-5, **lsSpine)
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ax.text(-2.8, 0.55, 'F=0.5')
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ax.text(0.15, 0.25, 'median at %.2f' % med)
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q3 = xs[cdf>=0.75][0]
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ax.plot([-3.2, q3, q3], [0.75, 0.75, 0.0], zorder=-5, **lsSpine)
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ax.text(-2.8, 0.8, 'F=0.75')
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ax.text(0.8, 0.5, '3. quartile at %.2f' % q3)
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p = cdf[xs>=-1.0][0]
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ax.plot([-3.2, -1.0, -1.0], [p, p, 0.0], zorder=-5, **lsSpine)
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ax.text(-2.8, 0.2, 'F=%.2f' % p)
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ax.text(-0.9, 0.05, '-1')
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ax.plot(xx, gausscdf, zorder=-1, **lsAm)
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ax.plot(xs, cdf, zorder=-1, **lsB)
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ax.plot([-3.2, 3.2], [1.0, 1.0], zorder=-10, **lsGrid)
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fig.savefig('cumulative.pdf')
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