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January 6, 2016 10:50
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Updating Histogram with Matplotlib
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from __future__ import division | |
import matplotlib.pyplot as plt | |
import matplotlib.gridspec as gridspec | |
import random | |
import math | |
def lognormal_cdf(x, m, s): | |
x1 = x[0] | |
x2 = x[1] | |
inner1 = (math.log(x1) - m)/(s*math.sqrt(2)) | |
inner2 = (math.log(x2) - m)/(s*math.sqrt(2)) | |
cdf1 = 0.5 + 0.5*math.erf(inner1) | |
cdf2 = 0.5 + 0.5*math.erf(inner2) | |
return cdf2-cdf1 | |
m = 1.5 | |
s = 0.6 | |
samplesize = 200 | |
xlim = 20 | |
ylim = 40 | |
frac = 10 | |
axticks = [(1/frac)*i for i in range(1, 30*frac + 1)] | |
axticks_shift1 = axticks[:-1] | |
axticks_shift2 = axticks[1:] | |
axticks_tuples = zip(axticks_shift1, axticks_shift2) | |
lognormdistplots = [lognormal_cdf(i, m, s)*(samplesize*frac) for i in axticks_tuples] | |
bins = range(31) | |
lognormrandoms = [random.lognormvariate(m, s) for i in range(samplesize)] | |
plt.ion() | |
fig = plt.figure() | |
ax = fig.gca() | |
plt.plot(axticks[1:], lognormdistplots, c='firebrick', linewidth=3) | |
plt.ylim([0, ylim]) | |
plt.xlim([0, xlim]) | |
plt.show() | |
# plt.savefig('giftest/img_1000') | |
wait = raw_input('Begin.') | |
for i in range(samplesize): | |
plt.cla() | |
plt.plot(axticks[1:], lognormdistplots, c='firebrick', linewidth=3) | |
ax.axvline(lognormrandoms[i], color='peru') | |
plt.hist(lognormrandoms[:i+1], bins=bins, color='goldenrod') | |
plt.ylim([0, ylim]) | |
plt.xlim([0, xlim]) | |
ax.text(15, 30, str(round(lognormrandoms[i], 3)), fontsize=20) | |
fig.canvas.draw() | |
# name = str(1) + str(0)*(3-len(str(i+1))) + str(i+1) | |
# plt.savefig('giftest/img_' + name) | |
plt.plot(axticks[1:], lognormdistplots, c='firebrick', linewidth=3) | |
plt.hist(lognormrandoms, bins=bins, color='goldenrod') | |
wait = raw_input('End.') | |
plt.show() |
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Take a look at tqdm:
That's just two one line changes:
import tqdm
for i in tqdm.tqdm(range(samplesize)):