blob: b65f8a30a2dc87e751f1797fb8bcf711af2ccf72 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
|
# -*- coding: utf-8 -*-
#
# Credits: http://www.aosabook.org/en/matplotlib.html
#
# Aaron LI
# 2016-03-14
#
# Import the FigureCanvas from the backend of your choice
# and attach the Figure artist to it.
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
fig = Figure()
canvas = FigureCanvas(fig)
# Import the numpy library to generate the random numbers.
import numpy as np
x = np.random.randn(10000)
# Now use a figure method to create an Axes artist; the Axes artist is
# added automatically to the figure container fig.axes.
# Here "111" is from the MATLAB convention: create a grid with 1 row and 1
# column, and use the first cell in that grid for the location of the new
# Axes.
ax = fig.add_subplot(111)
# Call the Axes method hist to generate the histogram; hist creates a
# sequence of Rectangle artists for each histogram bar and adds them
# to the Axes container. Here "100" means create 100 bins.
ax.hist(x, 100)
# Decorate the figure with a title and save it.
ax.set_title('Normal distribution with $\mu=0, \sigma=1$')
fig.savefig('matplotlib_histogram.png')
|
