<h3 dir="auto">Bug report</h3>
<p dir="auto"><strong>Bug summary</strong></p>
<p dir="auto">When interpolating a 2D heatmap on Windows, I get colored artifacts drawn over the 'bad' points. I am using LogNorm for normalization. I suspect it has something to do with the masked values caused by having 0s in a LogNorm. I set then to white with set_bad() function. On Linux, the interpolation looks entirely different (the white areas are not interpolated) and no artifacts can be seen.</p>
<p dir="auto">I've also tried different interpolating methods, all of them seem to create artifacts, except for nearest.</p>
<p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/1119915/33780953-87285a06-dc07-11e7-8b87-fd72132b6836.png"><img src="https://user-images.githubusercontent.com/1119915/33780953-87285a06-dc07-11e7-8b87-fd72132b6836.png" alt="image" style="max-width: 100%;"></a></p>
<p dir="auto">Zooming in creates more artifacts:<br>
<a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/1119915/33780974-982d253e-dc07-11e7-90c9-9c2a9bed356a.png"><img src="https://user-images.githubusercontent.com/1119915/33780974-982d253e-dc07-11e7-90c9-9c2a9bed356a.png" alt="image" style="max-width: 100%;"></a></p>
<p dir="auto">Zooming in to one of these artifacts, reveals this:<br>
<a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/1119915/33780980-a4db3ea6-dc07-11e7-8dc6-067746dbbc06.png"><img src="https://user-images.githubusercontent.com/1119915/33780980-a4db3ea6-dc07-11e7-8dc6-067746dbbc06.png" alt="image" style="max-width: 100%;"></a></p>
<p dir="auto"><strong>Code for reproduction</strong></p>

<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import matplotlib.pyplot as plt
import matplotlib.colors

heatmap = [[0] * 32 for _ in range(128)]
cnt = 0
last = 1
for lvl in range(127):
    if lvl % 20 &lt; 10:
        for i in range(32):
            heatmap[lvl][i] = 40
    else:
        for i in range(32):
            heatmap[lvl][i] = 0
jet = plt.get_cmap('jet')
jet.set_bad('white', 1)

plt.imshow(heatmap, origin='lower', interpolation='gaussian', aspect='auto', cmap=jet,
                 norm=matplotlib.colors.LogNorm())
plt.show()"><pre class="notranslate"><span class="pl-k">import</span> <span class="pl-s1">matplotlib</span>.<span class="pl-s1">pyplot</span> <span class="pl-k">as</span> <span class="pl-s1">plt</span>
<span class="pl-k">import</span> <span class="pl-s1">matplotlib</span>.<span class="pl-s1">colors</span>

<span class="pl-s1">heatmap</span> <span class="pl-c1">=</span> [[<span class="pl-c1">0</span>] <span class="pl-c1">*</span> <span class="pl-c1">32</span> <span class="pl-k">for</span> <span class="pl-s1">_</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">128</span>)]
<span class="pl-s1">cnt</span> <span class="pl-c1">=</span> <span class="pl-c1">0</span>
<span class="pl-s1">last</span> <span class="pl-c1">=</span> <span class="pl-c1">1</span>
<span class="pl-k">for</span> <span class="pl-s1">lvl</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">127</span>):
    <span class="pl-k">if</span> <span class="pl-s1">lvl</span> <span class="pl-c1">%</span> <span class="pl-c1">20</span> <span class="pl-c1">&lt;</span> <span class="pl-c1">10</span>:
        <span class="pl-k">for</span> <span class="pl-s1">i</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">32</span>):
            <span class="pl-s1">heatmap</span>[<span class="pl-s1">lvl</span>][<span class="pl-s1">i</span>] <span class="pl-c1">=</span> <span class="pl-c1">40</span>
    <span class="pl-k">else</span>:
        <span class="pl-k">for</span> <span class="pl-s1">i</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">32</span>):
            <span class="pl-s1">heatmap</span>[<span class="pl-s1">lvl</span>][<span class="pl-s1">i</span>] <span class="pl-c1">=</span> <span class="pl-c1">0</span>
<span class="pl-s1">jet</span> <span class="pl-c1">=</span> <span class="pl-s1">plt</span>.<span class="pl-en">get_cmap</span>(<span class="pl-s">'jet'</span>)
<span class="pl-s1">jet</span>.<span class="pl-en">set_bad</span>(<span class="pl-s">'white'</span>, <span class="pl-c1">1</span>)

<span class="pl-s1">plt</span>.<span class="pl-en">imshow</span>(<span class="pl-s1">heatmap</span>, <span class="pl-s1">origin</span><span class="pl-c1">=</span><span class="pl-s">'lower'</span>, <span class="pl-s1">interpolation</span><span class="pl-c1">=</span><span class="pl-s">'gaussian'</span>, <span class="pl-s1">aspect</span><span class="pl-c1">=</span><span class="pl-s">'auto'</span>, <span class="pl-s1">cmap</span><span class="pl-c1">=</span><span class="pl-s1">jet</span>,
                 <span class="pl-s1">norm</span><span class="pl-c1">=</span><span class="pl-s1">matplotlib</span>.<span class="pl-s1">colors</span>.<span class="pl-v">LogNorm</span>())
<span class="pl-s1">plt</span>.<span class="pl-en">show</span>()</pre></div>
<p dir="auto"><strong>Matplotlib version</strong></p>

<ul dir="auto">
<li>Operating system: Windows</li>
<li>Matplotlib version: 2.1.0</li>
<li>Matplotlib backend (<code class="notranslate">print(matplotlib.get_backend())</code>): TkAgg</li>
<li>Python version: 3.6</li>
<li>Jupyter version (if applicable):</li>
<li>Other libraries:</li>
</ul>
<h3 dir="auto">Bug report</h3>
<p dir="auto"><strong>Bug summary</strong></p>
<p dir="auto">I am using Matplotlib with Basemap to create heatmaps of data.<br>
A change introduced between version 2.0.0 and 2.0.1 caused my code to:</p>
<ul dir="auto">
<li>Produce a different result</li>
<li>Run significantly slower</li>
</ul>
<p dir="auto">The problem still seems to exist in 2.0.2.</p>
<p dir="auto">I also ran some profiling to have a look at the differences, and the increase in time seems to be in the <code class="notranslate">resample</code> function (from 0.473s total time to 19.042s total time)</p>
<p dir="auto"><strong>Code for reproduction</strong></p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import csv
import time

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mpl_toolkits.basemap import Basemap


def create_basemap():
    m = Basemap(projection='cyl', llcrnrlat=-90, urcrnrlat=90,
                llcrnrlon=-180, urcrnrlon=180, resolution='c')
    m.drawmapboundary(fill_color='#b4d0d0')
    m.drawcoastlines(linewidth=0.25, color=&quot;#ffffff&quot;)
    m.fillcontinents(color=&quot;grey&quot;, lake_color='#b4d0d0')

    m.drawparallels(np.arange(-90., 91., 30.), linewidth=&quot;0.25&quot;, color=&quot;#333333&quot;)
    m.drawmeridians(np.arange(-180., 181., 60.), linewidth=&quot;0.25&quot;, color=&quot;#555555&quot;)
    return m


def create_heatmap(positions):
    heatmap = np.zeros((180, 360))
    extents = [[-90, 90], [-180, 180]]

    lats, lons = map(list, zip(*positions))

    subheatmap, xedges, yedges = np.histogram2d(lats, lons, bins=[180, 360], range=extents)
    extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
    heatmap = np.add(heatmap, subheatmap)

    fig = plt.figure()
    m = create_basemap()

    cmap = cm.jet
    cmap.set_bad(alpha=0.0)

    im = m.imshow(heatmap, cmap=cmap, interpolation='bicubic', extent=extent, origin='lower', alpha=1.0, norm=matplotlib.colors.LogNorm(), vmin=1, vmax=2, zorder=100)
    cb = fig.colorbar(im, shrink=0.5, format=&quot;%d&quot;)

    plt.title(&quot;Test&quot;)
    plt.savefig(&quot;test.png&quot;, dpi=500, bbox_inches='tight', pad_inches=0.1)
    plt.close()


positions = [(50, i) for i in range(50)]
start = time.time()
create_heatmap(positions)
print &quot;Runtime: {0}&quot;.format(time.time() - start)"><pre class="notranslate"><span class="pl-k">import</span> <span class="pl-s1">csv</span>
<span class="pl-k">import</span> <span class="pl-s1">time</span>

<span class="pl-k">import</span> <span class="pl-s1">numpy</span> <span class="pl-k">as</span> <span class="pl-s1">np</span>
<span class="pl-k">import</span> <span class="pl-s1">matplotlib</span>
<span class="pl-k">import</span> <span class="pl-s1">matplotlib</span>.<span class="pl-s1">pyplot</span> <span class="pl-k">as</span> <span class="pl-s1">plt</span>
<span class="pl-k">import</span> <span class="pl-s1">matplotlib</span>.<span class="pl-s1">cm</span> <span class="pl-k">as</span> <span class="pl-s1">cm</span>
<span class="pl-k">from</span> <span class="pl-s1">mpl_toolkits</span>.<span class="pl-s1">basemap</span> <span class="pl-k">import</span> <span class="pl-v">Basemap</span>


<span class="pl-k">def</span> <span class="pl-en">create_basemap</span>():
    <span class="pl-s1">m</span> <span class="pl-c1">=</span> <span class="pl-v">Basemap</span>(<span class="pl-s1">projection</span><span class="pl-c1">=</span><span class="pl-s">'cyl'</span>, <span class="pl-s1">llcrnrlat</span><span class="pl-c1">=</span><span class="pl-c1">-</span><span class="pl-c1">90</span>, <span class="pl-s1">urcrnrlat</span><span class="pl-c1">=</span><span class="pl-c1">90</span>,
                <span class="pl-s1">llcrnrlon</span><span class="pl-c1">=</span><span class="pl-c1">-</span><span class="pl-c1">180</span>, <span class="pl-s1">urcrnrlon</span><span class="pl-c1">=</span><span class="pl-c1">180</span>, <span class="pl-s1">resolution</span><span class="pl-c1">=</span><span class="pl-s">'c'</span>)
    <span class="pl-s1">m</span>.<span class="pl-en">drawmapboundary</span>(<span class="pl-s1">fill_color</span><span class="pl-c1">=</span><span class="pl-s">'#b4d0d0'</span>)
    <span class="pl-s1">m</span>.<span class="pl-en">drawcoastlines</span>(<span class="pl-s1">linewidth</span><span class="pl-c1">=</span><span class="pl-c1">0.25</span>, <span class="pl-s1">color</span><span class="pl-c1">=</span><span class="pl-s">"#ffffff"</span>)
    <span class="pl-s1">m</span>.<span class="pl-en">fillcontinents</span>(<span class="pl-s1">color</span><span class="pl-c1">=</span><span class="pl-s">"grey"</span>, <span class="pl-s1">lake_color</span><span class="pl-c1">=</span><span class="pl-s">'#b4d0d0'</span>)

    <span class="pl-s1">m</span>.<span class="pl-en">drawparallels</span>(<span class="pl-s1">np</span>.<span class="pl-en">arange</span>(<span class="pl-c1">-</span><span class="pl-c1">90.</span>, <span class="pl-c1">91.</span>, <span class="pl-c1">30.</span>), <span class="pl-s1">linewidth</span><span class="pl-c1">=</span><span class="pl-s">"0.25"</span>, <span class="pl-s1">color</span><span class="pl-c1">=</span><span class="pl-s">"#333333"</span>)
    <span class="pl-s1">m</span>.<span class="pl-en">drawmeridians</span>(<span class="pl-s1">np</span>.<span class="pl-en">arange</span>(<span class="pl-c1">-</span><span class="pl-c1">180.</span>, <span class="pl-c1">181.</span>, <span class="pl-c1">60.</span>), <span class="pl-s1">linewidth</span><span class="pl-c1">=</span><span class="pl-s">"0.25"</span>, <span class="pl-s1">color</span><span class="pl-c1">=</span><span class="pl-s">"#555555"</span>)
    <span class="pl-k">return</span> <span class="pl-s1">m</span>


<span class="pl-k">def</span> <span class="pl-en">create_heatmap</span>(<span class="pl-s1">positions</span>):
    <span class="pl-s1">heatmap</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">zeros</span>((<span class="pl-c1">180</span>, <span class="pl-c1">360</span>))
    <span class="pl-s1">extents</span> <span class="pl-c1">=</span> [[<span class="pl-c1">-</span><span class="pl-c1">90</span>, <span class="pl-c1">90</span>], [<span class="pl-c1">-</span><span class="pl-c1">180</span>, <span class="pl-c1">180</span>]]

    <span class="pl-s1">lats</span>, <span class="pl-s1">lons</span> <span class="pl-c1">=</span> <span class="pl-en">map</span>(<span class="pl-s1">list</span>, <span class="pl-en">zip</span>(<span class="pl-c1">*</span><span class="pl-s1">positions</span>))

    <span class="pl-s1">subheatmap</span>, <span class="pl-s1">xedges</span>, <span class="pl-s1">yedges</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">histogram2d</span>(<span class="pl-s1">lats</span>, <span class="pl-s1">lons</span>, <span class="pl-s1">bins</span><span class="pl-c1">=</span>[<span class="pl-c1">180</span>, <span class="pl-c1">360</span>], <span class="pl-s1">range</span><span class="pl-c1">=</span><span class="pl-s1">extents</span>)
    <span class="pl-s1">extent</span> <span class="pl-c1">=</span> [<span class="pl-s1">xedges</span>[<span class="pl-c1">0</span>], <span class="pl-s1">xedges</span>[<span class="pl-c1">-</span><span class="pl-c1">1</span>], <span class="pl-s1">yedges</span>[<span class="pl-c1">0</span>], <span class="pl-s1">yedges</span>[<span class="pl-c1">-</span><span class="pl-c1">1</span>]]
    <span class="pl-s1">heatmap</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">add</span>(<span class="pl-s1">heatmap</span>, <span class="pl-s1">subheatmap</span>)

    <span class="pl-s1">fig</span> <span class="pl-c1">=</span> <span class="pl-s1">plt</span>.<span class="pl-en">figure</span>()
    <span class="pl-s1">m</span> <span class="pl-c1">=</span> <span class="pl-en">create_basemap</span>()

    <span class="pl-s1">cmap</span> <span class="pl-c1">=</span> <span class="pl-s1">cm</span>.<span class="pl-s1">jet</span>
    <span class="pl-s1">cmap</span>.<span class="pl-en">set_bad</span>(<span class="pl-s1">alpha</span><span class="pl-c1">=</span><span class="pl-c1">0.0</span>)

    <span class="pl-s1">im</span> <span class="pl-c1">=</span> <span class="pl-s1">m</span>.<span class="pl-en">imshow</span>(<span class="pl-s1">heatmap</span>, <span class="pl-s1">cmap</span><span class="pl-c1">=</span><span class="pl-s1">cmap</span>, <span class="pl-s1">interpolation</span><span class="pl-c1">=</span><span class="pl-s">'bicubic'</span>, <span class="pl-s1">extent</span><span class="pl-c1">=</span><span class="pl-s1">extent</span>, <span class="pl-s1">origin</span><span class="pl-c1">=</span><span class="pl-s">'lower'</span>, <span class="pl-s1">alpha</span><span class="pl-c1">=</span><span class="pl-c1">1.0</span>, <span class="pl-s1">norm</span><span class="pl-c1">=</span><span class="pl-s1">matplotlib</span>.<span class="pl-s1">colors</span>.<span class="pl-v">LogNorm</span>(), <span class="pl-s1">vmin</span><span class="pl-c1">=</span><span class="pl-c1">1</span>, <span class="pl-s1">vmax</span><span class="pl-c1">=</span><span class="pl-c1">2</span>, <span class="pl-s1">zorder</span><span class="pl-c1">=</span><span class="pl-c1">100</span>)
    <span class="pl-s1">cb</span> <span class="pl-c1">=</span> <span class="pl-s1">fig</span>.<span class="pl-en">colorbar</span>(<span class="pl-s1">im</span>, <span class="pl-s1">shrink</span><span class="pl-c1">=</span><span class="pl-c1">0.5</span>, <span class="pl-s1">format</span><span class="pl-c1">=</span><span class="pl-s">"%d"</span>)

    <span class="pl-s1">plt</span>.<span class="pl-en">title</span>(<span class="pl-s">"Test"</span>)
    <span class="pl-s1">plt</span>.<span class="pl-en">savefig</span>(<span class="pl-s">"test.png"</span>, <span class="pl-s1">dpi</span><span class="pl-c1">=</span><span class="pl-c1">500</span>, <span class="pl-s1">bbox_inches</span><span class="pl-c1">=</span><span class="pl-s">'tight'</span>, <span class="pl-s1">pad_inches</span><span class="pl-c1">=</span><span class="pl-c1">0.1</span>)
    <span class="pl-s1">plt</span>.<span class="pl-en">close</span>()


<span class="pl-s1">positions</span> <span class="pl-c1">=</span> [(<span class="pl-c1">50</span>, <span class="pl-s1">i</span>) <span class="pl-k">for</span> <span class="pl-s1">i</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">50</span>)]
<span class="pl-s1">start</span> <span class="pl-c1">=</span> <span class="pl-s1">time</span>.<span class="pl-en">time</span>()
<span class="pl-en">create_heatmap</span>(<span class="pl-s1">positions</span>)
<span class="pl-k">print</span> <span class="pl-s">"Runtime: {0}"</span>.<span class="pl-en">format</span>(<span class="pl-s1">time</span>.<span class="pl-en">time</span>() <span class="pl-c1">-</span> <span class="pl-s1">start</span>)</pre></div>
<p dir="auto"><strong>Version 2.0.0 outcome</strong></p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="Runtime: 2.31200003624"><pre class="notranslate"><code class="notranslate">Runtime: 2.31200003624
</code></pre></div>
<p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/8438951/28690404-0c940b66-72e7-11e7-8589-de72d04283e2.png"><img src="https://user-images.githubusercontent.com/8438951/28690404-0c940b66-72e7-11e7-8589-de72d04283e2.png" alt="2 0 0" style="max-width: 100%;"></a></p>
<p dir="auto"><code class="notranslate">python -m cProfile --sort=tottime script.py</code>:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="         667764 function calls (659117 primitive calls) in 3.555 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        2    0.702    0.351    0.702    0.351 {matplotlib._png.write_png}
        2    0.473    0.237    0.473    0.237 {matplotlib._image.resample}
        1    0.138    0.138    0.138    0.138 {_tkinter.create}
      890    0.117    0.000    0.117    0.000 {method 'is_valid' of '_geoslib.BaseGeometry' objects}
       15    0.106    0.007    0.632    0.042 __init__.py:1(&lt;module&gt;)
        1    0.090    0.090    0.135    0.135 __init__.py:14(&lt;module&gt;)
      296    0.083    0.000    0.083    0.000 {method 'intersection' of '_geoslib.BaseGeometry' objects}
        2    0.068    0.034    0.681    0.340 image.py:275(_make_image)
    11413    0.055    0.000    0.058    0.000 {numpy.core.multiarray.array}
      300    0.050    0.000    0.072    0.000 {method 'draw_path' of 'matplotlib.backends._backend_agg.RendererAgg' objects}
..."><pre class="notranslate"><code class="notranslate">         667764 function calls (659117 primitive calls) in 3.555 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        2    0.702    0.351    0.702    0.351 {matplotlib._png.write_png}
        2    0.473    0.237    0.473    0.237 {matplotlib._image.resample}
        1    0.138    0.138    0.138    0.138 {_tkinter.create}
      890    0.117    0.000    0.117    0.000 {method 'is_valid' of '_geoslib.BaseGeometry' objects}
       15    0.106    0.007    0.632    0.042 __init__.py:1(&lt;module&gt;)
        1    0.090    0.090    0.135    0.135 __init__.py:14(&lt;module&gt;)
      296    0.083    0.000    0.083    0.000 {method 'intersection' of '_geoslib.BaseGeometry' objects}
        2    0.068    0.034    0.681    0.340 image.py:275(_make_image)
    11413    0.055    0.000    0.058    0.000 {numpy.core.multiarray.array}
      300    0.050    0.000    0.072    0.000 {method 'draw_path' of 'matplotlib.backends._backend_agg.RendererAgg' objects}
...
</code></pre></div>
<p dir="auto"><strong>Version 2.0.1 outcome</strong></p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="Runtime: 21.0169999599"><pre class="notranslate"><code class="notranslate">Runtime: 21.0169999599
</code></pre></div>
<p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/8438951/28690462-4f7640a2-72e7-11e7-8688-4d9f7c729cf3.png"><img src="https://user-images.githubusercontent.com/8438951/28690462-4f7640a2-72e7-11e7-8688-4d9f7c729cf3.png" alt="2 0 1" style="max-width: 100%;"></a></p>
<p dir="auto"><code class="notranslate">python -m cProfile --sort=tottime script.py</code>:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="         1763720 function calls (1754827 primitive calls) in 23.725 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4   19.042    4.761   19.043    4.761 {matplotlib._image.resample}
        2    0.735    0.367    0.735    0.367 {matplotlib._png.write_png}
        2    0.609    0.304    1.377    0.688 font_manager.py:558(createFontList)
       60    0.138    0.002    0.336    0.006 afm.py:181(_parse_char_metrics)
        1    0.135    0.135    0.135    0.135 {_tkinter.create}
        2    0.133    0.067   19.309    9.655 image.py:275(_make_image)
      890    0.115    0.000    0.115    0.000 {method 'is_valid' of '_geoslib.BaseGeometry' objects}
        1    0.107    0.107    0.159    0.159 __init__.py:14(&lt;module&gt;)
       15    0.106    0.007    0.637    0.042 __init__.py:1(&lt;module&gt;)
      559    0.104    0.000    0.104    0.000 {method 'get_sfnt' of 'matplotlib.ft2font.FT2Font' objects}"><pre class="notranslate"><code class="notranslate">         1763720 function calls (1754827 primitive calls) in 23.725 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4   19.042    4.761   19.043    4.761 {matplotlib._image.resample}
        2    0.735    0.367    0.735    0.367 {matplotlib._png.write_png}
        2    0.609    0.304    1.377    0.688 font_manager.py:558(createFontList)
       60    0.138    0.002    0.336    0.006 afm.py:181(_parse_char_metrics)
        1    0.135    0.135    0.135    0.135 {_tkinter.create}
        2    0.133    0.067   19.309    9.655 image.py:275(_make_image)
      890    0.115    0.000    0.115    0.000 {method 'is_valid' of '_geoslib.BaseGeometry' objects}
        1    0.107    0.107    0.159    0.159 __init__.py:14(&lt;module&gt;)
       15    0.106    0.007    0.637    0.042 __init__.py:1(&lt;module&gt;)
      559    0.104    0.000    0.104    0.000 {method 'get_sfnt' of 'matplotlib.ft2font.FT2Font' objects}
</code></pre></div>
<p dir="auto"><strong>Matplotlib version</strong></p>
<ul dir="auto">
<li>Operating System: Windows 10</li>
<li>Matplotlib Version: 2.0.0/2.0.1 (from pip)</li>
<li>Python Version: 2.7.13</li>
<li>Jupyter Version (if applicable): N/A</li>
<li>Other Libraries: basemap 1.1.0, numpy 1.13.1</li>
</ul>