I would like
(1) to create some distance between the title of the plot and the title of the subplots (at present the title of one of the subplots overlaps the title of the plot).
(2) the scientific notion of the axis to be displayed as 10 to the power of x rather than 1lx like in the figure below.
(3) to choose the number of ticks on the x and y axis of the subplots, by entering the number of ticks as an argument into the function. (In this example the y axis has too many ticks).
(4) create some distance between xlab & the x-values, and ylab & the y-values
The code and figure are below
from __future__ import division
import math
import numpy as np
import matplotlib.pyplot as plt
def distribution_histogram(data):
rows_columns = int(math.sqrt(len(data)))
fig, ax = plt.subplots(nrows=rows_columns, ncols=rows_columns, sharey=True, tight_layout=True)
axs = ax.flatten()
subtitle_symbol = r'$\alpha$'
for i in xrange(len(data)):
d = data[i]
bins = len(d) / 10
axs[i].hist(d, bins=bins)
subtitle = subtitle_symbol + ' = '+ str(i)
axs[i].set_title('%s' % subtitle)
axs[i].ticklabel_format(style='sci', scilimits=(1,1), useOffset=True, useLocale=True, useMathText=True)
title = 'Distribution of something'
plt.suptitle('%s' % title)
plt.tight_layout()
fig.text(0.5, 0.0, 'xlab', ha='center')
fig.text(0.0, 0.5, 'ylab', va='center', rotation='vertical')
plt.savefig('%s.png' % 'distribution_file_name', bbox_inches='tight')
data = []
a = range(1,11)
a = a * 100
for i in xrange(9):
d = np.random.uniform(0,a[i],100)
data.append(d)
distribution_histogram(data)
