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Merge remote-tracking branch 'matplotlib/v2.x'
Conflicts: .mailmap - Kept version on master
2 parents 4e21b9a + 2cec8c2 commit 2d7c5ad

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‎doc/_templates/citing.html

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@@ -29,6 +29,7 @@ <h1>Citing matplotlib</h1>
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<h2>DOIs</h2>
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<dl>
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<dt>v1.5.2</dt><dd><a href="http://dx.doi.org/10.5281/zenodo.56926"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.56926.svg" alt="10.5281/zenodo.56926"></a></dd>
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<dt>v1.5.1</dt><dd><a href="http://dx.doi.org/10.5281/zenodo.44579"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.44579.svg" alt="10.5281/zenodo.44579"></a></dd>
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<dt>v1.5.0</dt><dd><a href="http://dx.doi.org/10.5281/zenodo.32914"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.32914.svg" alt="10.5281/zenodo.32914"></a></dd>
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<dt>v1.4.3</dt><dd><a href="http://dx.doi.org/10.5281/zenodo.15423"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.15423.svg" alt="10.5281/zenodo.15423"></a></dd>

‎doc/conf.py

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('axisartist', 'axisartist toolkit'),
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('units', 'units'),
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('widgets', 'widgets'),
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('misc', 'Miscellaneous examples'),
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]
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‎examples/misc/image_thumbnail.py

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# -*- noplot -*-
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"""
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You can use matplotlib to generate thumbnails from existing images.
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matplotlib natively supports PNG files on the input side, and other

‎examples/misc/longshort.py

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csv file, computing the daily returns, appending the results to the
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record arrays, joining on date
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"""
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import urllib
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from six.moves import urllib
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.mlab as mlab
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# grab the price data off yahoo
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u1 = urllib.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=AAPL&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
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u2 = urllib.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=GOOG&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
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u1 = urllib.request.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=AAPL&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
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u2 = urllib.request.urlretrieve('http://ichart.finance.yahoo.com/table.csv?s=GOOG&d=9&e=14&f=2008&g=d&a=8&b=7&c=1984&ignore=.csv')
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# load the CSV files into record arrays
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r1 = mlab.csv2rec(file(u1[0]))
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r2 = mlab.csv2rec(file(u2[0]))
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r1 = mlab.csv2rec(open(u1[0]))
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r2 = mlab.csv2rec(open(u2[0]))
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# compute the daily returns and add these columns to the arrays
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gains1 = np.zeros_like(r1.adj_close)

‎examples/misc/multiprocess.py

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# -*- noplot -*-
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# Demo of using multiprocessing for generating data in one process and plotting
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# in another.
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# Written by Robert Cimrman

‎examples/misc/rc_traits.py

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# -*- noplot -*-
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# Here is some example code showing how to define some representative
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# rc properties and construct a matplotlib artist using traits.
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# matplotlib does not ship with enthought.traits, so you will need to

‎lib/matplotlib/axes/_axes.py

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'dotted': ':'
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}
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zorder = mlines.Line2D.zorder
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zdelta = 0.1
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# box properties
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if patch_artist:
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final_boxprops = dict(
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color=rcParams['boxplot.boxprops.color'],
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)
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final_boxprops['zorder'] = zorder
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if boxprops is not None:
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final_boxprops.update(boxprops)
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color=rcParams['boxplot.capprops.color'],
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)
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final_capprops['zorder'] = zorder
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if capprops is not None:
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final_capprops.update(capprops)
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final_whiskerprops['zorder'] = zorder
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if whiskerprops is not None:
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final_whiskerprops.update(whiskerprops)
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markersize=rcParams['boxplot.flierprops.markersize'],
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)
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final_flierprops['zorder'] = zorder
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# flier (outlier) properties
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if flierprops is not None:
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final_flierprops.update(flierprops)
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linewidth=rcParams['boxplot.medianprops.linewidth'],
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color=rcParams['boxplot.medianprops.color'],
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)
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final_medianprops['zorder'] = zorder + zdelta
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if medianprops is not None:
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final_medianprops.update(medianprops)
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markeredgecolor=rcParams['boxplot.meanprops.markeredgecolor'],
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markersize=rcParams['boxplot.meanprops.markersize'],
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)
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final_meanprops['zorder'] = zorder + zdelta
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if meanprops is not None:
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final_meanprops.update(meanprops)
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def to_vc(xs, ys):
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# convert arguments to verts and codes
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verts = []
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#codes = []
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for xi, yi in zip(xs, ys):
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verts.append((xi, yi))
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verts.append((0, 0)) # ignored

‎lib/matplotlib/mlab.py

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@@ -2385,8 +2385,10 @@ def rec_append_fields(rec, names, arrs, dtypes=None):
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dtypes = dtypes * len(arrs)
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else:
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raise ValueError("dtypes must be None, a single dtype or a list")
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newdtype = np.dtype(rec.dtype.descr + list(zip(names, dtypes)))
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old_dtypes = rec.dtype.descr
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if six.PY2:
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old_dtypes = [(name.encode('utf-8'), dt) for name, dt in old_dtypes]
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newdtype = np.dtype(old_dtypes + list(zip(names, dtypes)))
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newrec = np.recarray(rec.shape, dtype=newdtype)
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for field in rec.dtype.fields:
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newrec[field] = rec[field]
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if desc[0] not in key]
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r2desc = [(mapped_r2field(desc[0]), desc[1]) for desc in r2.dtype.descr
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if desc[0] not in key]
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newdtype = np.dtype(keydesc + r1desc + r2desc)
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all_dtypes = keydesc + r1desc + r2desc
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if six.PY2:
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all_dtypes = [(name.encode('utf-8'), dt) for name, dt in all_dtypes]
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newdtype = np.dtype(all_dtypes)
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newrec = np.recarray((common_len + left_len + right_len,), dtype=newdtype)
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if defaults is not None:

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