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Diffstat (limited to 'python/plot.py')
-rw-r--r-- | python/plot.py | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/python/plot.py b/python/plot.py new file mode 100644 index 0000000..b65f8a3 --- /dev/null +++ b/python/plot.py @@ -0,0 +1,35 @@ +# -*- 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') + |