introduction
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Matplotlib is probable the single most used python package for 2d-graphics
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it provides both a very quick way to visualize data from python and publication-quality figures in many formats
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IPython and the pylab mode
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IPython is an enhanced interactive python shell that has lots of intersting features including named inputs and outputs, access to shell commands, improved debugging and many more
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it is central to the scientific-computing workflow in python for its use in combination with Matplotlib
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pylab
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pylab provides a procedural interface to the matplotlib object-oriented plotting library
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it is modeled closely after Matlab
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the majority of plotting commands in pylab have Matlab analogs with similar arguments
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simple plot
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get the data for the sine and cosine functions
import numpy as np X = np.linspace(-np.pi, np.pi, 256, endpoint=True) C, S = np.cos(X), np.sin(X)-
X is now a numpy array with 256 values ranging from -pi to +pi (included)
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C is the cosine (256 values)
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S is the sine (256 values)
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to run the example you can type them in an ipython interactive session
$ ipython --pylab -
you can also download each of the example and run
$ python example.py -
plotting with default settings
import pylab as pl import numpy as np X = np.linspace(-np.pi, np.pi, 256, endpoint=True) C, S = np.cos(X), np.sin(X) pl.plot(X, C) pl.plot(X, S) pl.show() -
instantiating defaults
import pylab as pl import numpy as np # Create a figure of size 8x6 inches, 80 dots per inch pl.figure(figsize=(8, 6), dpi=80) # Create a new subplot from a grid of 1x1 pl.subplot(1, 1, 1) X = np.linspace(-np.pi, np.pi, 256, endpoint=True) C, S = np.cos(X), np.sin(X) # Plot cosine with a blue continuous line of width 1 (pixels) pl.plot(X, C, color="blue", linewidth=1.0, linestyle="-") # Plot sine with a green continuous line of width 1 (pixels) pl.plot(X, S, color="green", linewidth=1.0, linestyle="-") # Set x limits pl.xlim(-4.0, 4.0) # Set x ticks pl.xticks(np.linspace(-4, 4, 9, endpoint=True)) # Set y limits pl.ylim(-1.0, 1.0) # Set y ticks pl.yticks(np.linspace(-1, 1, 5, endpoint=True)) # Save figure using 72 dots per inch # savefig("exercice_2.png", dpi=72) # Show result on screen pl.show() -
changing colors and line widths
pl.figure(figsize=(10, 6), dpi=80) pl.plot(X, C, color="blue", linewidth=2.5, linestyle="-") pl.plot(X, S, color="red", linewidth=2.5, linestyle="-") -
setting limits
pl.xlim(X.min() * 1.1, X.max() * 1.1) pl.ylim(C.min() * 1.1, C.max() * 1.1) -
setting ticks
pl.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi]) pl.yticks([-1, 0, +1]) -
setting tick labels
pl.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) pl.yticks([-1, 0, +1], [r'$-1$', r'$0$', r'$+1$']) -
moving spines
ax = pl.gca() # gca stands for 'get current axis' ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.spines['bottom'].set_position(('data',0)) ax.yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) -
adding a legend
pl.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine") pl.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine") pl.legend(loc='upper left') -
annotate some point
t = 2 * np.pi / 3 pl.plot([t, t], [0, np.cos(t)], color='blue', linewidth=2.5, linestyle="--") pl.scatter([t, ], [np.cos(t), ], 50, color='blue') pl.annotate(r'$sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$', xy=(t, np.sin(t)), xycoords='data', xytext=(+10, +30), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) pl.plot([t, t],[0, np.sin(t)], color='red', linewidth=2.5, linestyle="--") pl.scatter([t, ],[np.sin(t), ], 50, color='red') pl.annotate(r'$cos(\frac{2\pi}{3})=-\frac{1}{2}$', xy=(t, np.cos(t)), xycoords='data', xytext=(-90, -50), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) -
devil is in the details
for label in ax.get_xticklabels() + ax.get_yticklabels(): label.set_fontsize(16) label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65))
figures, subplots, axes and ticks
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figures
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a figure is the windows in the gui that has “Figure #” as title
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numdefault1number of figure -
figsizedefaultfigure.figsizefigure size in inches (width, height) -
dpidefaultfigure.dpiresolution in dots per inch -
facecolordefaultfigure.facecolorcolor of the drawing background -
edgecolordefaultfigure.edgecolorcolor of edge around the drawing background -
frameondefaultTruedraw figure frame or not
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subplots
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two
+------------------+ | | | subplot(2, 1, 1) | | | +------------------+ +------------------+ | | | subplot(2, 1, 2) | | | +------------------+ -
two
+------------------+ +------------------+ | | | | | | | | | | | | | subplot(1, 2, 1) | | subplot(1, 2, 2) | | | | | | | | | | | | | +------------------+ +------------------+ -
four
+------------------+ +------------------+ | | | | | | | | | | | | | subplot(2, 2, 1) | | subplot(2, 2, 2) | | | | | | | | | | | | | +------------------+ +------------------+ +------------------+ +------------------+ | | | | | | | | | | | | | subplot(2, 2, 3) | | subplot(2, 2, 4) | | | | | | | | | | | | | +------------------+ +------------------+
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axes
+---------------------------------------+ | | | | | | | axes([0.1, 0.1, .8, .8]) | | | | | | | | | | +------------------------+ | | | | | | | | | | |axes([0.2, 0.2, .3, .3])| | | | | | | | | | | +------------------------+ | +---------------------------------------+ -
ticks
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tick locators control the position of the ticks
ax = pl.gca() ax.xaxis.set_major_locator(eval(locator)) -
there are several locator for different kind of requirements
NullLocator() ============================================================ MultipleLocator() =====|=====|=====|=====|=====|=====|=====|=====|=====|=====| 0 1 2 3 4 5 6 7 8 9 10 FixedLocator([0, 2, 8, 9, 10]) ===========|===================================|=====|=====| 0 2 8 9 10 IndexLocator(3, 1) =====|=================|=================|=================| 1 4 7 10 LinearLocator(5) ==============|==============|==============|==============| .0 2.5 5.0 7.5 10. LogLocator(2, [1.0]) =====|=====|===========|=======================|============ 1 2 4 8 AutoLocator() ===========|===========|===========|===========|===========| 0 2 4 6 8 10
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