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Merge pull request #6957 from phobson/partial-update-pylab-examples
DOC: clearing out some instances of using pylab in the docs
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‎doc/faq/installing_faq.rst‎

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@@ -23,9 +23,10 @@ complexities. Open up a UNIX shell or a DOS command prompt and cd into a
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directory containing a minimal example in a file. Something like
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:file:`simple_plot.py` for example::
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from pylab import *
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plot([1,2,3])
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show()
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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ax.plot([1,2,3])
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plt.show()
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and run it with::
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‎doc/pyplots/boxplot_demo.py‎

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@@ -4,62 +4,60 @@
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# Example boxplot code
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#
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from pylab import *
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import numpy as np
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import matplotlib.pyplot as plt
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# fake up some data
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spread= rand(50) * 100
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center = ones(25) * 50
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flier_high = rand(10) * 100 + 100
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flier_low = rand(10) * -100
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data =concatenate((spread, center, flier_high, flier_low), 0)
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# basic plot
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boxplot(data)
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#savefig('box1')
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# notched plot
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figure()
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boxplot(data,1)
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#savefig('box2')
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# change outlier point symbols
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figure()
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boxplot(data,0,'gD')
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#savefig('box3')
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# don't show outlier points
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figure()
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boxplot(data,0,'')
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#savefig('box4')
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np.random.seed(0)
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# horizontal boxes
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figure()
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boxplot(data,0,'rs',0)
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#savefig('box5')
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# change whisker length
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figure()
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boxplot(data,0,'rs',0,0.75)
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#savefig('box6')
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# fake up some data
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spread = np.random.rand(50) * 100
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center = np.ones(25) * 50
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flier_high = np.random.rand(10) * 100 + 100
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flier_low = np.random.rand(10) * -100
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data = np.concatenate((spread, center, flier_high, flier_low), 0)
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fig1, ax1 = plt.subplots()
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ax1.set_title('Basic Plot')
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ax1.boxplot(data)
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fig2, ax2 = plt.subplots()
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ax2.set_title('Notched boxes')
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ax2.boxplot(data, notch=True)
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green_diamond = dict(markerfacecolor='g', marker='D')
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fig3, ax3 = plt.subplots()
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ax3.set_title('Changed Outlier Symbols')
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ax3.boxplot(data, flierprops=green_diamond)
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fig4, ax4 = plt.subplots()
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ax4.set_title('Hide Outlier Points')
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ax4.boxplot(data, showfliers=False)
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red_square = dict(markerfacecolor='r', marker='s')
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fig5, ax5 = plt.subplots()
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ax5.set_title('Horizontal Boxes')
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ax5.boxplot(data, vert=False, flierprops=red_square)
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fig6, ax6 = plt.subplots()
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ax6.set_title('Shorter Whisker Length')
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ax6.boxplot(data, flierprops=red_square, vert=False, whis=0.75)
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# fake up some more data
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spread= rand(50) * 100
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center = ones(25) * 40
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flier_high = rand(10) * 100 + 100
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flier_low = rand(10) * -100
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d2 = concatenate( (spread, center, flier_high, flier_low), 0 )
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spread = np.random.rand(50) * 100
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center = np.ones(25) * 40
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flier_high = np.random.rand(10) * 100 + 100
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flier_low = np.random.rand(10) * -100
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d2 = np.concatenate((spread, center, flier_high, flier_low), 0)
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data.shape = (-1, 1)
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d2.shape = (-1, 1)
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#data = concatenate( (data, d2), 1 )
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# Making a 2-D array only works if all the columns are the
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# same length. If they are not, then use a list instead.
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# This is actually more efficient because boxplot converts
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# a 2-D array into a list of vectors internally anyway.
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data = [data, d2, d2[::2,0]]
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# multiple box plots on one figure
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figure()
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boxplot(data)
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#savefig('box7')
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show()
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fig7, ax7 = plt.subplots()
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ax7.set_title('Multiple Samples with Different sizes')
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ax7.boxplot(data)
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plt.show()

‎doc/pyplots/whats_new_98_4_fill_between.py‎

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@@ -1,17 +1,16 @@
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#!/usr/bin/env python
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import matplotlib.mlab as mlab
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from pylab import figure, show
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import matplotlib.pyplot as plt
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import numpy as np
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x = np.arange(0.0, 2, 0.01)
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y1 = np.sin(2*np.pi*x)
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y2 = 1.2*np.sin(4*np.pi*x)
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fig = figure()
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ax = fig.add_subplot(111)
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fig, ax = plt.subplots()
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ax.plot(x, y1, x, y2, color='black')
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ax.fill_between(x, y1, y2, where=y2>y1, facecolor='green')
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ax.fill_between(x, y1, y2, where=y2<=y1, facecolor='red')
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ax.set_title('fill between where')
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show()
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plt.show()

‎doc/pyplots/whats_new_99_mplot3d.py‎

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@@ -1,17 +1,18 @@
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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib import cm
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import pylab
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import random
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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from mpl_toolkits.mplot3d import Axes3D
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fig = pylab.figure()
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ax = Axes3D(fig)
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X = np.arange(-5, 5, 0.25)
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Y = np.arange(-5, 5, 0.25)
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X, Y = np.meshgrid(X, Y)
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R = np.sqrt(X**2 + Y**2)
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Z = np.sin(R)
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ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet)
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pylab.show()
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fig = plt.figure()
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ax = Axes3D(fig)
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ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.viridis)
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plt.show()

‎examples/api/colorbar_only.py‎

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@@ -2,11 +2,11 @@
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Make a colorbar as a separate figure.
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'''
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from matplotlib import pyplot
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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# Make a figure and axes with dimensions as desired.
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fig = pyplot.figure(figsize=(8, 3))
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fig = plt.figure(figsize=(8, 3))
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ax1 = fig.add_axes([0.05, 0.80, 0.9, 0.15])
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ax2 = fig.add_axes([0.05, 0.475, 0.9, 0.15])
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ax3 = fig.add_axes([0.05, 0.15, 0.9, 0.15])
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orientation='horizontal')
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cb3.set_label('Custom extension lengths, some other units')
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pyplot.show()
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plt.show()

‎examples/units/units_scatter.py‎

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@@ -9,28 +9,25 @@
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arrays.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from basic_units import secs, hertz, minutes
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from matplotlib.pylab import figure, show
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# create masked array
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data = (1, 2, 3, 4, 5, 6, 7, 8)
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mask = (1, 0, 1, 0, 0, 0, 1, 0)
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xsecs = secs * np.ma.MaskedArray(data, mask, float)
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xsecs = secs*np.ma.MaskedArray((1, 2, 3, 4, 5, 6, 7, 8), (1, 0, 1, 0, 0, 0, 1, 0), np.float)
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#xsecs = secs*np.arange(1,10.)
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fig = figure()
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ax1 = fig.add_subplot(3, 1, 1)
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fig, (ax1, ax2, ax3) = plt.subplots(nrows=3, sharex=True)
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ax1.scatter(xsecs, xsecs)
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#ax1.set_ylabel('seconds')
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ax1.yaxis.set_units(secs)
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ax1.axis([0, 10, 0, 10])
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ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
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ax2.scatter(xsecs, xsecs, yunits=hertz)
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ax2.axis([0, 10, 0, 1])
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ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
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ax3.scatter(xsecs, xsecs, yunits=hertz)
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ax3.yaxis.set_units(minutes)
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ax3.axis([0, 10, 0, 1])
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show()
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fig.tight_layout()
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plt.show()

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