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<h1>Source code for matplotlib.image</h1><div class="highlight"><pre>
<span></span><span class="sd">"""</span>
<span class="sd">The image module supports basic image loading, rescaling and display</span>
<span class="sd">operations.</span>
<span class="sd">"""</span>
<span class="kn">from</span> <span class="nn">__future__</span> <span class="k">import</span> <span class="p">(</span><span class="n">absolute_import</span><span class="p">,</span> <span class="n">division</span><span class="p">,</span> <span class="n">print_function</span><span class="p">,</span>
<span class="n">unicode_literals</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">six</span>
<span class="kn">from</span> <span class="nn">six.moves.urllib.parse</span> <span class="k">import</span> <span class="n">urlparse</span>
<span class="kn">from</span> <span class="nn">six.moves.urllib.request</span> <span class="k">import</span> <span class="n">urlopen</span>
<span class="kn">from</span> <span class="nn">io</span> <span class="k">import</span> <span class="n">BytesIO</span>
<span class="kn">from</span> <span class="nn">math</span> <span class="k">import</span> <span class="n">ceil</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="k">import</span> <span class="n">rcParams</span>
<span class="kn">import</span> <span class="nn">matplotlib.artist</span> <span class="k">as</span> <span class="nn">martist</span>
<span class="kn">from</span> <span class="nn">matplotlib.artist</span> <span class="k">import</span> <span class="n">allow_rasterization</span>
<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">mcolors</span>
<span class="kn">import</span> <span class="nn">matplotlib.cm</span> <span class="k">as</span> <span class="nn">cm</span>
<span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="k">as</span> <span class="nn">cbook</span>
<span class="c1"># For clarity, names from _image are given explicitly in this module:</span>
<span class="kn">import</span> <span class="nn">matplotlib._image</span> <span class="k">as</span> <span class="nn">_image</span>
<span class="kn">import</span> <span class="nn">matplotlib._png</span> <span class="k">as</span> <span class="nn">_png</span>
<span class="c1"># For user convenience, the names from _image are also imported into</span>
<span class="c1"># the image namespace:</span>
<span class="kn">from</span> <span class="nn">matplotlib._image</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">matplotlib.transforms</span> <span class="k">import</span> <span class="p">(</span><span class="n">Affine2D</span><span class="p">,</span> <span class="n">BboxBase</span><span class="p">,</span> <span class="n">Bbox</span><span class="p">,</span> <span class="n">BboxTransform</span><span class="p">,</span>
<span class="n">IdentityTransform</span><span class="p">,</span> <span class="n">TransformedBbox</span><span class="p">)</span>
<span class="n">_log</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
<span class="c1"># map interpolation strings to module constants</span>
<span class="n">_interpd_</span> <span class="o">=</span> <span class="p">{</span>
<span class="s1">'none'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">NEAREST</span><span class="p">,</span> <span class="c1"># fall back to nearest when not supported</span>
<span class="s1">'nearest'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">NEAREST</span><span class="p">,</span>
<span class="s1">'bilinear'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">BILINEAR</span><span class="p">,</span>
<span class="s1">'bicubic'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">BICUBIC</span><span class="p">,</span>
<span class="s1">'spline16'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">SPLINE16</span><span class="p">,</span>
<span class="s1">'spline36'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">SPLINE36</span><span class="p">,</span>
<span class="s1">'hanning'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">HANNING</span><span class="p">,</span>
<span class="s1">'hamming'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">HAMMING</span><span class="p">,</span>
<span class="s1">'hermite'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">HERMITE</span><span class="p">,</span>
<span class="s1">'kaiser'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">KAISER</span><span class="p">,</span>
<span class="s1">'quadric'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">QUADRIC</span><span class="p">,</span>
<span class="s1">'catrom'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">CATROM</span><span class="p">,</span>
<span class="s1">'gaussian'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">GAUSSIAN</span><span class="p">,</span>
<span class="s1">'bessel'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">BESSEL</span><span class="p">,</span>
<span class="s1">'mitchell'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">MITCHELL</span><span class="p">,</span>
<span class="s1">'sinc'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">SINC</span><span class="p">,</span>
<span class="s1">'lanczos'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">LANCZOS</span><span class="p">,</span>
<span class="s1">'blackman'</span><span class="p">:</span> <span class="n">_image</span><span class="o">.</span><span class="n">BLACKMAN</span><span class="p">,</span>
<span class="p">}</span>
<span class="n">interpolations_names</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">_interpd_</span><span class="p">)</span>
<div class="viewcode-block" id="composite_images"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.composite_images">[docs]</a><span class="k">def</span> <span class="nf">composite_images</span><span class="p">(</span><span class="n">images</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="n">magnification</span><span class="o">=</span><span class="mf">1.0</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Composite a number of RGBA images into one. The images are</span>
<span class="sd"> composited in the order in which they appear in the `images` list.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> images : list of Images</span>
<span class="sd"> Each must have a `make_image` method. For each image,</span>
<span class="sd"> `can_composite` should return `True`, though this is not</span>
<span class="sd"> enforced by this function. Each image must have a purely</span>
<span class="sd"> affine transformation with no shear.</span>
<span class="sd"> renderer : RendererBase instance</span>
<span class="sd"> magnification : float</span>
<span class="sd"> The additional magnification to apply for the renderer in use.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> tuple : image, offset_x, offset_y</span>
<span class="sd"> Returns the tuple:</span>
<span class="sd"> - image: A numpy array of the same type as the input images.</span>
<span class="sd"> - offset_x, offset_y: The offset of the image (left, bottom)</span>
<span class="sd"> in the output figure.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">images</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">),</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span>
<span class="n">parts</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">bboxes</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">image</span> <span class="ow">in</span> <span class="n">images</span><span class="p">:</span>
<span class="n">data</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">trans</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">make_image</span><span class="p">(</span><span class="n">renderer</span><span class="p">,</span> <span class="n">magnification</span><span class="p">)</span>
<span class="k">if</span> <span class="n">data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">x</span> <span class="o">*=</span> <span class="n">magnification</span>
<span class="n">y</span> <span class="o">*=</span> <span class="n">magnification</span>
<span class="n">parts</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">data</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">image</span><span class="o">.</span><span class="n">get_alpha</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">1.0</span><span class="p">))</span>
<span class="n">bboxes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="n">Bbox</span><span class="p">([[</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">],</span> <span class="p">[</span><span class="n">x</span> <span class="o">+</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">y</span> <span class="o">+</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]]]))</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">parts</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">),</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span>
<span class="n">bbox</span> <span class="o">=</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">union</span><span class="p">(</span><span class="n">bboxes</span><span class="p">)</span>
<span class="n">output</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span>
<span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">bbox</span><span class="o">.</span><span class="n">height</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">bbox</span><span class="o">.</span><span class="n">width</span><span class="p">),</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="k">for</span> <span class="n">data</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">alpha</span> <span class="ow">in</span> <span class="n">parts</span><span class="p">:</span>
<span class="n">trans</span> <span class="o">=</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">translate</span><span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">bbox</span><span class="o">.</span><span class="n">x0</span><span class="p">,</span> <span class="n">y</span> <span class="o">-</span> <span class="n">bbox</span><span class="o">.</span><span class="n">y0</span><span class="p">)</span>
<span class="n">_image</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span> <span class="n">trans</span><span class="p">,</span> <span class="n">_image</span><span class="o">.</span><span class="n">NEAREST</span><span class="p">,</span>
<span class="n">resample</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="n">alpha</span><span class="p">)</span>
<span class="k">return</span> <span class="n">output</span><span class="p">,</span> <span class="n">bbox</span><span class="o">.</span><span class="n">x0</span> <span class="o">/</span> <span class="n">magnification</span><span class="p">,</span> <span class="n">bbox</span><span class="o">.</span><span class="n">y0</span> <span class="o">/</span> <span class="n">magnification</span></div>
<span class="k">def</span> <span class="nf">_draw_list_compositing_images</span><span class="p">(</span>
<span class="n">renderer</span><span class="p">,</span> <span class="n">parent</span><span class="p">,</span> <span class="n">artists</span><span class="p">,</span> <span class="n">suppress_composite</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Draw a sorted list of artists, compositing images into a single</span>
<span class="sd"> image where possible.</span>
<span class="sd"> For internal matplotlib use only: It is here to reduce duplication</span>
<span class="sd"> between `Figure.draw` and `Axes.draw`, but otherwise should not be</span>
<span class="sd"> generally useful.</span>
<span class="sd"> """</span>
<span class="n">has_images</span> <span class="o">=</span> <span class="nb">any</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">_ImageBase</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">artists</span><span class="p">)</span>
<span class="c1"># override the renderer default if suppressComposite is not None</span>
<span class="n">not_composite</span> <span class="o">=</span> <span class="p">(</span><span class="n">suppress_composite</span> <span class="k">if</span> <span class="n">suppress_composite</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">else</span> <span class="n">renderer</span><span class="o">.</span><span class="n">option_image_nocomposite</span><span class="p">())</span>
<span class="k">if</span> <span class="n">not_composite</span> <span class="ow">or</span> <span class="ow">not</span> <span class="n">has_images</span><span class="p">:</span>
<span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">artists</span><span class="p">:</span>
<span class="n">a</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="n">renderer</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Composite any adjacent images together</span>
<span class="n">image_group</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">mag</span> <span class="o">=</span> <span class="n">renderer</span><span class="o">.</span><span class="n">get_image_magnification</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">flush_images</span><span class="p">():</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">image_group</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">image_group</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="n">renderer</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">image_group</span><span class="p">)</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
<span class="n">data</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="n">composite_images</span><span class="p">(</span><span class="n">image_group</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="n">mag</span><span class="p">)</span>
<span class="k">if</span> <span class="n">data</span><span class="o">.</span><span class="n">size</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">gc</span> <span class="o">=</span> <span class="n">renderer</span><span class="o">.</span><span class="n">new_gc</span><span class="p">()</span>
<span class="n">gc</span><span class="o">.</span><span class="n">set_clip_rectangle</span><span class="p">(</span><span class="n">parent</span><span class="o">.</span><span class="n">bbox</span><span class="p">)</span>
<span class="n">gc</span><span class="o">.</span><span class="n">set_clip_path</span><span class="p">(</span><span class="n">parent</span><span class="o">.</span><span class="n">get_clip_path</span><span class="p">())</span>
<span class="n">renderer</span><span class="o">.</span><span class="n">draw_image</span><span class="p">(</span><span class="n">gc</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">l</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">b</span><span class="p">),</span> <span class="n">data</span><span class="p">)</span>
<span class="n">gc</span><span class="o">.</span><span class="n">restore</span><span class="p">()</span>
<span class="k">del</span> <span class="n">image_group</span><span class="p">[:]</span>
<span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">artists</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">_ImageBase</span><span class="p">)</span> <span class="ow">and</span> <span class="n">a</span><span class="o">.</span><span class="n">can_composite</span><span class="p">():</span>
<span class="n">image_group</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">flush_images</span><span class="p">()</span>
<span class="n">a</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="n">renderer</span><span class="p">)</span>
<span class="n">flush_images</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">_rgb_to_rgba</span><span class="p">(</span><span class="n">A</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Convert an RGB image to RGBA, as required by the image resample C++</span>
<span class="sd"> extension.</span>
<span class="sd"> """</span>
<span class="n">rgba</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">A</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="n">rgba</span><span class="p">[:,</span> <span class="p">:,</span> <span class="p">:</span><span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">A</span>
<span class="k">if</span> <span class="n">rgba</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">:</span>
<span class="n">rgba</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="mi">255</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">rgba</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
<span class="k">return</span> <span class="n">rgba</span>
<span class="k">class</span> <span class="nc">_ImageBase</span><span class="p">(</span><span class="n">martist</span><span class="o">.</span><span class="n">Artist</span><span class="p">,</span> <span class="n">cm</span><span class="o">.</span><span class="n">ScalarMappable</span><span class="p">):</span>
<span class="n">zorder</span> <span class="o">=</span> <span class="mi">0</span>
<span class="nd">@property</span>
<span class="nd">@cbook</span><span class="o">.</span><span class="n">deprecated</span><span class="p">(</span><span class="s2">"2.1"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_interpd</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">_interpd_</span>
<span class="nd">@property</span>
<span class="nd">@cbook</span><span class="o">.</span><span class="n">deprecated</span><span class="p">(</span><span class="s2">"2.1"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_interpdr</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="p">{</span><span class="n">v</span><span class="p">:</span> <span class="n">k</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">six</span><span class="o">.</span><span class="n">iteritems</span><span class="p">(</span><span class="n">_interpd_</span><span class="p">)}</span>
<span class="nd">@property</span>
<span class="nd">@cbook</span><span class="o">.</span><span class="n">deprecated</span><span class="p">(</span><span class="s2">"2.1"</span><span class="p">,</span> <span class="n">alternative</span><span class="o">=</span><span class="s2">"mpl.image.interpolation_names"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">iterpnames</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">interpolations_names</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"AxesImage(</span><span class="si">%g</span><span class="s2">,</span><span class="si">%g</span><span class="s2">;</span><span class="si">%g</span><span class="s2">x</span><span class="si">%g</span><span class="s2">)"</span> <span class="o">%</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">bbox</span><span class="o">.</span><span class="n">bounds</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span>
<span class="n">cmap</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">interpolation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">origin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">filternorm</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">filterrad</span><span class="o">=</span><span class="mf">4.0</span><span class="p">,</span>
<span class="n">resample</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span>
<span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> interpolation and cmap default to their rc settings</span>
<span class="sd"> cmap is a colors.Colormap instance</span>
<span class="sd"> norm is a colors.Normalize instance to map luminance to 0-1</span>
<span class="sd"> extent is data axes (left, right, bottom, top) for making image plots</span>
<span class="sd"> registered with data plots. Default is to label the pixel</span>
<span class="sd"> centers with the zero-based row and column indices.</span>
<span class="sd"> Additional kwargs are matplotlib.artist properties</span>
<span class="sd"> """</span>
<span class="n">martist</span><span class="o">.</span><span class="n">Artist</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="n">cm</span><span class="o">.</span><span class="n">ScalarMappable</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">norm</span><span class="p">,</span> <span class="n">cmap</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_mouseover</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">if</span> <span class="n">origin</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">origin</span> <span class="o">=</span> <span class="n">rcParams</span><span class="p">[</span><span class="s1">'image.origin'</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">origin</span> <span class="o">=</span> <span class="n">origin</span>
<span class="bp">self</span><span class="o">.</span><span class="n">set_filternorm</span><span class="p">(</span><span class="n">filternorm</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">set_filterrad</span><span class="p">(</span><span class="n">filterrad</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">set_interpolation</span><span class="p">(</span><span class="n">interpolation</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">set_resample</span><span class="p">(</span><span class="n">resample</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="n">ax</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">state</span> <span class="o">=</span> <span class="nb">super</span><span class="p">(</span><span class="n">_ImageBase</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">()</span>
<span class="c1"># We can't pickle the C Image cached object.</span>
<span class="n">state</span><span class="p">[</span><span class="s1">'_imcache'</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">return</span> <span class="n">state</span>
<span class="k">def</span> <span class="nf">get_size</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Get the numrows, numcols of the input image"""</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">'You must first set the image array'</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">shape</span><span class="p">[:</span><span class="mi">2</span><span class="p">]</span>
<span class="k">def</span> <span class="nf">set_alpha</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">alpha</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the alpha value used for blending - not supported on</span>
<span class="sd"> all backends</span>
<span class="sd"> ACCEPTS: float</span>
<span class="sd"> """</span>
<span class="n">martist</span><span class="o">.</span><span class="n">Artist</span><span class="o">.</span><span class="n">set_alpha</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">alpha</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">def</span> <span class="nf">changed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Call this whenever the mappable is changed so observers can</span>
<span class="sd"> update state</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_rgbacache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">cm</span><span class="o">.</span><span class="n">ScalarMappable</span><span class="o">.</span><span class="n">changed</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_make_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">A</span><span class="p">,</span> <span class="n">in_bbox</span><span class="p">,</span> <span class="n">out_bbox</span><span class="p">,</span> <span class="n">clip_bbox</span><span class="p">,</span> <span class="n">magnification</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span>
<span class="n">unsampled</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">round_to_pixel_border</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Normalize, rescale and color the image `A` from the given</span>
<span class="sd"> in_bbox (in data space), to the given out_bbox (in pixel</span>
<span class="sd"> space) clipped to the given clip_bbox (also in pixel space),</span>
<span class="sd"> and magnified by the magnification factor.</span>
<span class="sd"> `A` may be a greyscale image (MxN) with a dtype of `float32`,</span>
<span class="sd"> `float64`, `uint16` or `uint8`, or an RGBA image (MxNx4) with</span>
<span class="sd"> a dtype of `float32`, `float64`, or `uint8`.</span>
<span class="sd"> If `unsampled` is True, the image will not be scaled, but an</span>
<span class="sd"> appropriate affine transformation will be returned instead.</span>
<span class="sd"> If `round_to_pixel_border` is True, the output image size will</span>
<span class="sd"> be rounded to the nearest pixel boundary. This makes the</span>
<span class="sd"> images align correctly with the axes. It should not be used</span>
<span class="sd"> in cases where you want exact scaling, however, such as</span>
<span class="sd"> FigureImage.</span>
<span class="sd"> Returns the resulting (image, x, y, trans), where (x, y) is</span>
<span class="sd"> the upper left corner of the result in pixel space, and</span>
<span class="sd"> `trans` is the affine transformation from the image to pixel</span>
<span class="sd"> space.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">A</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">'You must first set the image '</span>
<span class="s1">'array or the image attribute'</span><span class="p">)</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">"_make_image must get a non-empty image. "</span>
<span class="s2">"Your Artist's draw method must filter before "</span>
<span class="s2">"this method is called."</span><span class="p">)</span>
<span class="n">clipped_bbox</span> <span class="o">=</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">out_bbox</span><span class="p">,</span> <span class="n">clip_bbox</span><span class="p">)</span>
<span class="k">if</span> <span class="n">clipped_bbox</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="kc">None</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="kc">None</span>
<span class="n">out_width_base</span> <span class="o">=</span> <span class="n">clipped_bbox</span><span class="o">.</span><span class="n">width</span> <span class="o">*</span> <span class="n">magnification</span>
<span class="n">out_height_base</span> <span class="o">=</span> <span class="n">clipped_bbox</span><span class="o">.</span><span class="n">height</span> <span class="o">*</span> <span class="n">magnification</span>
<span class="k">if</span> <span class="n">out_width_base</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">out_height_base</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="kc">None</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="kc">None</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">origin</span> <span class="o">==</span> <span class="s1">'upper'</span><span class="p">:</span>
<span class="c1"># Flip the input image using a transform. This avoids the</span>
<span class="c1"># problem with flipping the array, which results in a copy</span>
<span class="c1"># when it is converted to contiguous in the C wrapper</span>
<span class="n">t0</span> <span class="o">=</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">translate</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="o">-</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">scale</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">t0</span> <span class="o">=</span> <span class="n">IdentityTransform</span><span class="p">()</span>
<span class="n">t0</span> <span class="o">+=</span> <span class="p">(</span>
<span class="n">Affine2D</span><span class="p">()</span>
<span class="o">.</span><span class="n">scale</span><span class="p">(</span>
<span class="n">in_bbox</span><span class="o">.</span><span class="n">width</span> <span class="o">/</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span>
<span class="n">in_bbox</span><span class="o">.</span><span class="n">height</span> <span class="o">/</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="o">.</span><span class="n">translate</span><span class="p">(</span><span class="n">in_bbox</span><span class="o">.</span><span class="n">x0</span><span class="p">,</span> <span class="n">in_bbox</span><span class="o">.</span><span class="n">y0</span><span class="p">)</span>
<span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">())</span>
<span class="n">t</span> <span class="o">=</span> <span class="p">(</span><span class="n">t0</span>
<span class="o">+</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">translate</span><span class="p">(</span>
<span class="o">-</span><span class="n">clipped_bbox</span><span class="o">.</span><span class="n">x0</span><span class="p">,</span>
<span class="o">-</span><span class="n">clipped_bbox</span><span class="o">.</span><span class="n">y0</span><span class="p">)</span>
<span class="o">.</span><span class="n">scale</span><span class="p">(</span><span class="n">magnification</span><span class="p">,</span> <span class="n">magnification</span><span class="p">))</span>
<span class="c1"># So that the image is aligned with the edge of the axes, we want</span>
<span class="c1"># to round up the output width to the next integer. This also</span>
<span class="c1"># means scaling the transform just slightly to account for the</span>
<span class="c1"># extra subpixel.</span>
<span class="k">if</span> <span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">is_affine</span> <span class="ow">and</span> <span class="n">round_to_pixel_border</span> <span class="ow">and</span>
<span class="p">(</span><span class="n">out_width_base</span> <span class="o">%</span> <span class="mf">1.0</span> <span class="o">!=</span> <span class="mf">0.0</span> <span class="ow">or</span> <span class="n">out_height_base</span> <span class="o">%</span> <span class="mf">1.0</span> <span class="o">!=</span> <span class="mf">0.0</span><span class="p">)):</span>
<span class="n">out_width</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">ceil</span><span class="p">(</span><span class="n">out_width_base</span><span class="p">))</span>
<span class="n">out_height</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">ceil</span><span class="p">(</span><span class="n">out_height_base</span><span class="p">))</span>
<span class="n">extra_width</span> <span class="o">=</span> <span class="p">(</span><span class="n">out_width</span> <span class="o">-</span> <span class="n">out_width_base</span><span class="p">)</span> <span class="o">/</span> <span class="n">out_width_base</span>
<span class="n">extra_height</span> <span class="o">=</span> <span class="p">(</span><span class="n">out_height</span> <span class="o">-</span> <span class="n">out_height_base</span><span class="p">)</span> <span class="o">/</span> <span class="n">out_height_base</span>
<span class="n">t</span> <span class="o">+=</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">scale</span><span class="p">(</span><span class="mf">1.0</span> <span class="o">+</span> <span class="n">extra_width</span><span class="p">,</span> <span class="mf">1.0</span> <span class="o">+</span> <span class="n">extra_height</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">out_width</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">out_width_base</span><span class="p">)</span>
<span class="n">out_height</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">out_height_base</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">unsampled</span><span class="p">:</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">ndim</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Invalid dimensions, got </span><span class="si">{}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="c1"># if we are a 2D array, then we are running through the</span>
<span class="c1"># norm + colormap transformation. However, in general the</span>
<span class="c1"># input data is not going to match the size on the screen so we</span>
<span class="c1"># have to resample to the correct number of pixels</span>
<span class="c1"># need to</span>
<span class="c1"># TODO slice input array first</span>
<span class="n">inp_dtype</span> <span class="o">=</span> <span class="n">A</span><span class="o">.</span><span class="n">dtype</span>
<span class="n">a_min</span> <span class="o">=</span> <span class="n">A</span><span class="o">.</span><span class="n">min</span><span class="p">()</span>
<span class="n">a_max</span> <span class="o">=</span> <span class="n">A</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
<span class="c1"># figure out the type we should scale to. For floats,</span>
<span class="c1"># leave as is. For integers cast to an appropriate-sized</span>
<span class="c1"># float. Small integers get smaller floats in an attempt</span>
<span class="c1"># to keep the memory footprint reasonable.</span>
<span class="k">if</span> <span class="n">a_min</span> <span class="ow">is</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked</span><span class="p">:</span>
<span class="c1"># all masked, so values don't matter</span>
<span class="n">a_min</span><span class="p">,</span> <span class="n">a_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">inp_dtype</span><span class="o">.</span><span class="n">kind</span> <span class="o">==</span> <span class="s1">'f'</span><span class="p">:</span>
<span class="n">scaled_dtype</span> <span class="o">=</span> <span class="n">A</span><span class="o">.</span><span class="n">dtype</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># probably an integer of some type.</span>
<span class="n">da</span> <span class="o">=</span> <span class="n">a_max</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span> <span class="o">-</span> <span class="n">a_min</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)</span>
<span class="k">if</span> <span class="n">da</span> <span class="o">></span> <span class="mf">1e8</span><span class="p">:</span>
<span class="c1"># give more breathing room if a big dynamic range</span>
<span class="n">scaled_dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">scaled_dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span>
<span class="c1"># scale the input data to [.1, .9]. The Agg</span>
<span class="c1"># interpolators clip to [0, 1] internally, use a</span>
<span class="c1"># smaller input scale to identify which of the</span>
<span class="c1"># interpolated points need to be should be flagged as</span>
<span class="c1"># over / under.</span>
<span class="c1"># This may introduce numeric instabilities in very broadly</span>
<span class="c1"># scaled data</span>
<span class="n">A_scaled</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">scaled_dtype</span><span class="p">)</span>
<span class="n">A_scaled</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">A</span>
<span class="c1"># clip scaled data around norm if necessary.</span>
<span class="c1"># This is necessary for big numbers at the edge of</span>
<span class="c1"># float64's ability to represent changes. Applying</span>
<span class="c1"># a norm first would be good, but ruins the interpolation</span>
<span class="c1"># of over numbers.</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">vmin</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">vmax</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">dv</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">vmax</span><span class="p">)</span> <span class="o">-</span>
<span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">vmin</span><span class="p">))</span>
<span class="n">vmid</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">vmin</span> <span class="o">+</span> <span class="n">dv</span> <span class="o">/</span> <span class="mi">2</span>
<span class="n">newmin</span> <span class="o">=</span> <span class="n">vmid</span> <span class="o">-</span> <span class="n">dv</span> <span class="o">*</span> <span class="mf">1.e7</span>
<span class="k">if</span> <span class="n">newmin</span> <span class="o"><</span> <span class="n">a_min</span><span class="p">:</span>
<span class="n">newmin</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">a_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="n">newmin</span><span class="p">)</span>
<span class="n">newmax</span> <span class="o">=</span> <span class="n">vmid</span> <span class="o">+</span> <span class="n">dv</span> <span class="o">*</span> <span class="mf">1.e7</span>
<span class="k">if</span> <span class="n">newmax</span> <span class="o">></span> <span class="n">a_max</span><span class="p">:</span>
<span class="n">newmax</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">a_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="n">newmax</span><span class="p">)</span>
<span class="k">if</span> <span class="n">newmax</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">or</span> <span class="n">newmin</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">A_scaled</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">A_scaled</span><span class="p">,</span> <span class="n">newmin</span><span class="p">,</span> <span class="n">newmax</span><span class="p">)</span>
<span class="n">A_scaled</span> <span class="o">-=</span> <span class="n">a_min</span>
<span class="c1"># a_min and a_max might be ndarray subclasses so use</span>
<span class="c1"># asscalar to ensure they are scalars to avoid errors</span>
<span class="n">a_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asscalar</span><span class="p">(</span><span class="n">a_min</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">scaled_dtype</span><span class="p">))</span>
<span class="n">a_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asscalar</span><span class="p">(</span><span class="n">a_max</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">scaled_dtype</span><span class="p">))</span>
<span class="k">if</span> <span class="n">a_min</span> <span class="o">!=</span> <span class="n">a_max</span><span class="p">:</span>
<span class="n">A_scaled</span> <span class="o">/=</span> <span class="p">((</span><span class="n">a_max</span> <span class="o">-</span> <span class="n">a_min</span><span class="p">)</span> <span class="o">/</span> <span class="mf">0.8</span><span class="p">)</span>
<span class="n">A_scaled</span> <span class="o">+=</span> <span class="mf">0.1</span>
<span class="n">A_resampled</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">out_height</span><span class="p">,</span> <span class="n">out_width</span><span class="p">),</span>
<span class="n">dtype</span><span class="o">=</span><span class="n">A_scaled</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="c1"># resample the input data to the correct resolution and shape</span>
<span class="n">_image</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">A_scaled</span><span class="p">,</span> <span class="n">A_resampled</span><span class="p">,</span>
<span class="n">t</span><span class="p">,</span>
<span class="n">_interpd_</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">get_interpolation</span><span class="p">()],</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_resample</span><span class="p">(),</span> <span class="mf">1.0</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_filternorm</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_filterrad</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">)</span>
<span class="c1"># we are done with A_scaled now, remove from namespace</span>
<span class="c1"># to be sure!</span>
<span class="k">del</span> <span class="n">A_scaled</span>
<span class="c1"># un-scale the resampled data to approximately the</span>
<span class="c1"># original range things that interpolated to above /</span>
<span class="c1"># below the original min/max will still be above /</span>
<span class="c1"># below, but possibly clipped in the case of higher order</span>
<span class="c1"># interpolation + drastically changing data.</span>
<span class="n">A_resampled</span> <span class="o">-=</span> <span class="mf">0.1</span>
<span class="k">if</span> <span class="n">a_min</span> <span class="o">!=</span> <span class="n">a_max</span><span class="p">:</span>
<span class="n">A_resampled</span> <span class="o">*=</span> <span class="p">((</span><span class="n">a_max</span> <span class="o">-</span> <span class="n">a_min</span><span class="p">)</span> <span class="o">/</span> <span class="mf">0.8</span><span class="p">)</span>
<span class="n">A_resampled</span> <span class="o">+=</span> <span class="n">a_min</span>
<span class="c1"># if using NoNorm, cast back to the original datatype</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="p">,</span> <span class="n">mcolors</span><span class="o">.</span><span class="n">NoNorm</span><span class="p">):</span>
<span class="n">A_resampled</span> <span class="o">=</span> <span class="n">A_resampled</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="n">mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">mask</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">:</span>
<span class="c1"># this is the case of a nontrivial mask</span>
<span class="n">mask</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">mask</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">),</span>
<span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">(</span><span class="mi">1</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">mask</span><span class="p">[:]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="c1"># we always have to interpolate the mask to account for</span>
<span class="c1"># non-affine transformations</span>
<span class="n">out_mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">out_height</span><span class="p">,</span> <span class="n">out_width</span><span class="p">),</span>
<span class="n">dtype</span><span class="o">=</span><span class="n">mask</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="n">_image</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="n">out_mask</span><span class="p">,</span>
<span class="n">t</span><span class="p">,</span>
<span class="n">_interpd_</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">get_interpolation</span><span class="p">()],</span>
<span class="kc">True</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_filternorm</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_filterrad</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">)</span>
<span class="c1"># we are done with the mask, delete from namespace to be sure!</span>
<span class="k">del</span> <span class="n">mask</span>
<span class="c1"># Agg updates the out_mask in place. If the pixel has</span>
<span class="c1"># no image data it will not be updated (and still be 0</span>
<span class="c1"># as we initialized it), if input data that would go</span>
<span class="c1"># into that output pixel than it will be `nan`, if all</span>
<span class="c1"># the input data for a pixel is good it will be 1, and</span>
<span class="c1"># if there is _some_ good data in that output pixel it</span>
<span class="c1"># will be between [0, 1] (such as a rotated image).</span>
<span class="n">out_alpha</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">out_mask</span><span class="p">)</span>
<span class="n">out_mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">out_mask</span><span class="p">)</span>
<span class="n">out_alpha</span><span class="p">[</span><span class="n">out_mask</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="c1"># mask and run through the norm</span>
<span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked_array</span><span class="p">(</span><span class="n">A_resampled</span><span class="p">,</span> <span class="n">out_mask</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Always convert to RGBA, even if only RGB input</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span>
<span class="n">A</span> <span class="o">=</span> <span class="n">_rgb_to_rgba</span><span class="p">(</span><span class="n">A</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">!=</span> <span class="mi">4</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Invalid dimensions, got </span><span class="si">%s</span><span class="s2">"</span> <span class="o">%</span> <span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">,))</span>
<span class="n">output</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">out_height</span><span class="p">,</span> <span class="n">out_width</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">A</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="n">alpha</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_alpha</span><span class="p">()</span>
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">alpha</span> <span class="o">=</span> <span class="mf">1.0</span>
<span class="n">_image</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
<span class="n">A</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">_interpd_</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">get_interpolation</span><span class="p">()],</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_resample</span><span class="p">(),</span> <span class="n">alpha</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_filternorm</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_filterrad</span><span class="p">()</span> <span class="ow">or</span> <span class="mf">0.0</span><span class="p">)</span>
<span class="c1"># at this point output is either a 2D array of normed data</span>
<span class="c1"># (of int or float)</span>
<span class="c1"># or an RGBA array of re-sampled input</span>
<span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_rgba</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="nb">bytes</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="c1"># output is now a correctly sized RGBA array of uint8</span>
<span class="c1"># Apply alpha *after* if the input was greyscale without a mask</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="n">alpha</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_alpha</span><span class="p">()</span>
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">alpha</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">alpha_channel</span> <span class="o">=</span> <span class="n">output</span><span class="p">[:,</span> <span class="p">:,</span> <span class="mi">3</span><span class="p">]</span>
<span class="n">alpha_channel</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span>
<span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">alpha_channel</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span> <span class="o">*</span> <span class="n">out_alpha</span> <span class="o">*</span> <span class="n">alpha</span><span class="p">,</span>
<span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_rgba</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="nb">bytes</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">2</span><span class="p">))</span>
<span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span>
<span class="c1"># Subset the input image to only the part that will be</span>
<span class="c1"># displayed</span>
<span class="n">subset</span> <span class="o">=</span> <span class="n">TransformedBbox</span><span class="p">(</span>
<span class="n">clip_bbox</span><span class="p">,</span> <span class="n">t0</span><span class="o">.</span><span class="n">frozen</span><span class="p">()</span><span class="o">.</span><span class="n">inverted</span><span class="p">())</span><span class="o">.</span><span class="n">frozen</span><span class="p">()</span>
<span class="n">output</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span>
<span class="nb">int</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">ymin</span><span class="p">,</span> <span class="mi">0</span><span class="p">)):</span>
<span class="nb">int</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">ymax</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])),</span>
<span class="nb">int</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">xmin</span><span class="p">,</span> <span class="mi">0</span><span class="p">)):</span>
<span class="nb">int</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">xmax</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]))]</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">translate</span><span class="p">(</span>
<span class="nb">int</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">xmin</span><span class="p">,</span> <span class="mi">0</span><span class="p">)),</span> <span class="nb">int</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">subset</span><span class="o">.</span><span class="n">ymin</span><span class="p">,</span> <span class="mi">0</span><span class="p">)))</span> <span class="o">+</span> <span class="n">t</span>
<span class="k">return</span> <span class="n">output</span><span class="p">,</span> <span class="n">clipped_bbox</span><span class="o">.</span><span class="n">x0</span><span class="p">,</span> <span class="n">clipped_bbox</span><span class="o">.</span><span class="n">y0</span><span class="p">,</span> <span class="n">t</span>
<span class="k">def</span> <span class="nf">make_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="n">magnification</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">unsampled</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s1">'The make_image method must be overridden.'</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_draw_unsampled_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="n">gc</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> draw unsampled image. The renderer should support a draw_image method</span>
<span class="sd"> with scale parameter.</span>
<span class="sd"> """</span>
<span class="n">im</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">trans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">make_image</span><span class="p">(</span><span class="n">renderer</span><span class="p">,</span> <span class="n">unsampled</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">if</span> <span class="n">im</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span>
<span class="n">trans</span> <span class="o">=</span> <span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">scale</span><span class="p">(</span><span class="n">im</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">im</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="n">trans</span>
<span class="n">renderer</span><span class="o">.</span><span class="n">draw_image</span><span class="p">(</span><span class="n">gc</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">im</span><span class="p">,</span> <span class="n">trans</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_check_unsampled_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> return True if the image is better to be drawn unsampled.</span>
<span class="sd"> The derived class needs to override it.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="kc">False</span>
<span class="nd">@allow_rasterization</span>
<span class="k">def</span> <span class="nf">draw</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="c1"># if not visible, declare victory and return</span>
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_visible</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">return</span>
<span class="c1"># for empty images, there is nothing to draw!</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_array</span><span class="p">()</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">return</span>
<span class="c1"># actually render the image.</span>
<span class="n">gc</span> <span class="o">=</span> <span class="n">renderer</span><span class="o">.</span><span class="n">new_gc</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_set_gc_clip</span><span class="p">(</span><span class="n">gc</span><span class="p">)</span>
<span class="n">gc</span><span class="o">.</span><span class="n">set_alpha</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_alpha</span><span class="p">())</span>
<span class="n">gc</span><span class="o">.</span><span class="n">set_url</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_url</span><span class="p">())</span>
<span class="n">gc</span><span class="o">.</span><span class="n">set_gid</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_gid</span><span class="p">())</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_check_unsampled_image</span><span class="p">(</span><span class="n">renderer</span><span class="p">)</span> <span class="ow">and</span>
<span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()</span><span class="o">.</span><span class="n">is_affine</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_draw_unsampled_image</span><span class="p">(</span><span class="n">renderer</span><span class="p">,</span> <span class="n">gc</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">im</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">trans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">make_image</span><span class="p">(</span>
<span class="n">renderer</span><span class="p">,</span> <span class="n">renderer</span><span class="o">.</span><span class="n">get_image_magnification</span><span class="p">())</span>
<span class="k">if</span> <span class="n">im</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">renderer</span><span class="o">.</span><span class="n">draw_image</span><span class="p">(</span><span class="n">gc</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">im</span><span class="p">)</span>
<span class="n">gc</span><span class="o">.</span><span class="n">restore</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">def</span> <span class="nf">contains</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mouseevent</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Test whether the mouse event occurred within the image.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">callable</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_contains</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_contains</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mouseevent</span><span class="p">)</span>
<span class="c1"># TODO: make sure this is consistent with patch and patch</span>
<span class="c1"># collection on nonlinear transformed coordinates.</span>
<span class="c1"># TODO: consider returning image coordinates (shouldn't</span>
<span class="c1"># be too difficult given that the image is rectilinear</span>
<span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">mouseevent</span><span class="o">.</span><span class="n">xdata</span><span class="p">,</span> <span class="n">mouseevent</span><span class="o">.</span><span class="n">ydata</span>
<span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_extent</span><span class="p">()</span>
<span class="k">if</span> <span class="n">xmin</span> <span class="o">></span> <span class="n">xmax</span><span class="p">:</span>
<span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span> <span class="o">=</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">xmin</span>
<span class="k">if</span> <span class="n">ymin</span> <span class="o">></span> <span class="n">ymax</span><span class="p">:</span>
<span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <span class="n">ymax</span><span class="p">,</span> <span class="n">ymin</span>
<span class="k">if</span> <span class="n">x</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">y</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">inside</span> <span class="o">=</span> <span class="p">(</span><span class="n">xmin</span> <span class="o"><=</span> <span class="n">x</span> <span class="o"><=</span> <span class="n">xmax</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span><span class="n">ymin</span> <span class="o"><=</span> <span class="n">y</span> <span class="o"><=</span> <span class="n">ymax</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">inside</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">return</span> <span class="n">inside</span><span class="p">,</span> <span class="p">{}</span>
<span class="k">def</span> <span class="nf">write_png</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fname</span><span class="p">):</span>
<span class="sd">"""Write the image to png file with fname"""</span>
<span class="n">im</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_rgba</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="p">[::</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">origin</span> <span class="o">==</span> <span class="s1">'lower'</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="p">,</span>
<span class="nb">bytes</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">_png</span><span class="o">.</span><span class="n">write_png</span><span class="p">(</span><span class="n">im</span><span class="p">,</span> <span class="n">fname</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">set_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">A</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the image array.</span>
<span class="sd"> ACCEPTS: numpy/PIL Image A</span>
<span class="sd"> Note that this function does *not* update the normalization used.</span>
<span class="sd"> """</span>
<span class="c1"># check if data is PIL Image without importing Image</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="s1">'getpixel'</span><span class="p">):</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">mode</span> <span class="o">==</span> <span class="s1">'L'</span><span class="p">:</span>
<span class="c1"># greyscale image, but our logic assumes rgba:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="o">=</span> <span class="n">pil_to_array</span><span class="p">(</span><span class="n">A</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">'RGBA'</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="o">=</span> <span class="n">pil_to_array</span><span class="p">(</span><span class="n">A</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="o">=</span> <span class="n">cbook</span><span class="o">.</span><span class="n">safe_masked_invalid</span><span class="p">(</span><span class="n">A</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">dtype</span> <span class="o">!=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint8</span> <span class="ow">and</span>
<span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">can_cast</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="s2">"same_kind"</span><span class="p">)):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">"Image data cannot be converted to float"</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">2</span>
<span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">3</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">"Invalid dimensions for image data"</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span>
<span class="c1"># If the input data has values outside the valid range (after</span>
<span class="c1"># normalisation), we issue a warning and then clip X to the bounds</span>
<span class="c1"># - otherwise casting wraps extreme values, hiding outliers and</span>
<span class="c1"># making reliable interpretation impossible.</span>
<span class="n">high</span> <span class="o">=</span> <span class="mi">255</span> <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">integer</span><span class="p">)</span> <span class="k">else</span> <span class="mi">1</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">min</span><span class="p">()</span> <span class="o"><</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">high</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">max</span><span class="p">():</span>
<span class="n">_log</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span>
<span class="s1">'Clipping input data to the valid range for imshow with '</span>
<span class="s1">'RGB data ([0..1] for floats or [0..255] for integers).'</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">high</span><span class="p">)</span>
<span class="c1"># Cast unsupported integer types to uint8</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">dtype</span> <span class="o">!=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint8</span> <span class="ow">and</span> <span class="n">np</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">np</span><span class="o">.</span><span class="n">integer</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imcache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_rgbacache</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">set_array</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">A</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Retained for backwards compatibility - use set_data instead</span>
<span class="sd"> ACCEPTS: numpy array A or PIL Image</span>
<span class="sd"> """</span>
<span class="c1"># This also needs to be here to override the inherited</span>
<span class="c1"># cm.ScalarMappable.set_array method so it is not invoked</span>
<span class="c1"># by mistake.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">set_data</span><span class="p">(</span><span class="n">A</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">get_interpolation</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the interpolation method the image uses when resizing.</span>
<span class="sd"> One of 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36',</span>
<span class="sd"> 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom',</span>
<span class="sd"> 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos', or 'none'.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_interpolation</span>
<span class="k">def</span> <span class="nf">set_interpolation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">s</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the interpolation method the image uses when resizing.</span>
<span class="sd"> if None, use a value from rc setting. If 'none', the image is</span>
<span class="sd"> shown as is without interpolating. 'none' is only supported in</span>
<span class="sd"> agg, ps and pdf backends and will fall back to 'nearest' mode</span>
<span class="sd"> for other backends.</span>
<span class="sd"> .. ACCEPTS: ['nearest' | 'bilinear' | 'bicubic' | 'spline16' |</span>
<span class="sd"> 'spline36' | 'hanning' | 'hamming' | 'hermite' | 'kaiser' |</span>
<span class="sd"> 'quadric' | 'catrom' | 'gaussian' | 'bessel' | 'mitchell' |</span>
<span class="sd"> 'sinc' | 'lanczos' | 'none' ]</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">s</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">rcParams</span><span class="p">[</span><span class="s1">'image.interpolation'</span><span class="p">]</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span>
<span class="k">if</span> <span class="n">s</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">_interpd_</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'Illegal interpolation string'</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_interpolation</span> <span class="o">=</span> <span class="n">s</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">can_composite</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Returns `True` if the image can be composited with its neighbors.</span>
<span class="sd"> """</span>
<span class="n">trans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()</span>
<span class="k">return</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_interpolation</span> <span class="o">!=</span> <span class="s1">'none'</span> <span class="ow">and</span>
<span class="n">trans</span><span class="o">.</span><span class="n">is_affine</span> <span class="ow">and</span>
<span class="n">trans</span><span class="o">.</span><span class="n">is_separable</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">set_resample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set whether or not image resampling is used.</span>
<span class="sd"> ACCEPTS: True|False</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">v</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">v</span> <span class="o">=</span> <span class="n">rcParams</span><span class="p">[</span><span class="s1">'image.resample'</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_resample</span> <span class="o">=</span> <span class="n">v</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">get_resample</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Return the image resample boolean."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_resample</span>
<span class="k">def</span> <span class="nf">set_filternorm</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filternorm</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set whether the resize filter norms the weights -- see</span>
<span class="sd"> help for imshow</span>
<span class="sd"> ACCEPTS: 0 or 1</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">filternorm</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_filternorm</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_filternorm</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">get_filternorm</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Return the filternorm setting."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_filternorm</span>
<span class="k">def</span> <span class="nf">set_filterrad</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filterrad</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the resize filter radius only applicable to some</span>
<span class="sd"> interpolation schemes -- see help for imshow</span>
<span class="sd"> ACCEPTS: positive float</span>
<span class="sd"> """</span>
<span class="n">r</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">filterrad</span><span class="p">)</span>
<span class="k">if</span> <span class="n">r</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"The filter radius must be a positive number"</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_filterrad</span> <span class="o">=</span> <span class="n">r</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">get_filterrad</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Return the filterrad setting."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_filterrad</span>
<div class="viewcode-block" id="AxesImage"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage">[docs]</a><span class="k">class</span> <span class="nc">AxesImage</span><span class="p">(</span><span class="n">_ImageBase</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"AxesImage(</span><span class="si">%g</span><span class="s2">,</span><span class="si">%g</span><span class="s2">;</span><span class="si">%g</span><span class="s2">x</span><span class="si">%g</span><span class="s2">)"</span> <span class="o">%</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">bbox</span><span class="o">.</span><span class="n">bounds</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span>
<span class="n">cmap</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">norm</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">interpolation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">origin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">extent</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">filternorm</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">filterrad</span><span class="o">=</span><span class="mf">4.0</span><span class="p">,</span>
<span class="n">resample</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span>
<span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> interpolation and cmap default to their rc settings</span>
<span class="sd"> cmap is a colors.Colormap instance</span>
<span class="sd"> norm is a colors.Normalize instance to map luminance to 0-1</span>
<span class="sd"> extent is data axes (left, right, bottom, top) for making image plots</span>
<span class="sd"> registered with data plots. Default is to label the pixel</span>
<span class="sd"> centers with the zero-based row and column indices.</span>
<span class="sd"> Additional kwargs are matplotlib.artist properties</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_extent</span> <span class="o">=</span> <span class="n">extent</span>
<span class="nb">super</span><span class="p">(</span><span class="n">AxesImage</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
<span class="n">ax</span><span class="p">,</span>
<span class="n">cmap</span><span class="o">=</span><span class="n">cmap</span><span class="p">,</span>
<span class="n">norm</span><span class="o">=</span><span class="n">norm</span><span class="p">,</span>
<span class="n">interpolation</span><span class="o">=</span><span class="n">interpolation</span><span class="p">,</span>
<span class="n">origin</span><span class="o">=</span><span class="n">origin</span><span class="p">,</span>
<span class="n">filternorm</span><span class="o">=</span><span class="n">filternorm</span><span class="p">,</span>
<span class="n">filterrad</span><span class="o">=</span><span class="n">filterrad</span><span class="p">,</span>
<span class="n">resample</span><span class="o">=</span><span class="n">resample</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span>
<span class="p">)</span>
<div class="viewcode-block" id="AxesImage.get_window_extent"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage.get_window_extent">[docs]</a> <span class="k">def</span> <span class="nf">get_window_extent</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="n">x0</span><span class="p">,</span> <span class="n">x1</span><span class="p">,</span> <span class="n">y0</span><span class="p">,</span> <span class="n">y1</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extent</span>
<span class="n">bbox</span> <span class="o">=</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">from_extents</span><span class="p">([</span><span class="n">x0</span><span class="p">,</span> <span class="n">y0</span><span class="p">,</span> <span class="n">x1</span><span class="p">,</span> <span class="n">y1</span><span class="p">])</span>
<span class="k">return</span> <span class="n">bbox</span><span class="o">.</span><span class="n">transformed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">transData</span><span class="p">)</span></div>
<div class="viewcode-block" id="AxesImage.make_image"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage.make_image">[docs]</a> <span class="k">def</span> <span class="nf">make_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">,</span> <span class="n">magnification</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">unsampled</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
<span class="n">trans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()</span>
<span class="c1"># image is created in the canvas coordinate.</span>
<span class="n">x1</span><span class="p">,</span> <span class="n">x2</span><span class="p">,</span> <span class="n">y1</span><span class="p">,</span> <span class="n">y2</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_extent</span><span class="p">()</span>
<span class="n">bbox</span> <span class="o">=</span> <span class="n">Bbox</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="n">x1</span><span class="p">,</span> <span class="n">y1</span><span class="p">],</span> <span class="p">[</span><span class="n">x2</span><span class="p">,</span> <span class="n">y2</span><span class="p">]]))</span>
<span class="n">transformed_bbox</span> <span class="o">=</span> <span class="n">TransformedBbox</span><span class="p">(</span><span class="n">bbox</span><span class="p">,</span> <span class="n">trans</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_make_image</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_A</span><span class="p">,</span> <span class="n">bbox</span><span class="p">,</span> <span class="n">transformed_bbox</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">bbox</span><span class="p">,</span> <span class="n">magnification</span><span class="p">,</span>
<span class="n">unsampled</span><span class="o">=</span><span class="n">unsampled</span><span class="p">)</span></div>
<span class="k">def</span> <span class="nf">_check_unsampled_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">renderer</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return whether the image would be better drawn unsampled.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_interpolation</span><span class="p">()</span> <span class="o">==</span> <span class="s2">"none"</span>
<span class="ow">and</span> <span class="n">renderer</span><span class="o">.</span><span class="n">option_scale_image</span><span class="p">())</span>
<div class="viewcode-block" id="AxesImage.set_extent"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage.set_extent">[docs]</a> <span class="k">def</span> <span class="nf">set_extent</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">extent</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> extent is data axes (left, right, bottom, top) for making image plots</span>
<span class="sd"> This updates ax.dataLim, and, if autoscaling, sets viewLim</span>
<span class="sd"> to tightly fit the image, regardless of dataLim. Autoscaling</span>
<span class="sd"> state is not changed, so following this with ax.autoscale_view</span>
<span class="sd"> will redo the autoscaling in accord with dataLim.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_extent</span> <span class="o">=</span> <span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <span class="n">extent</span>
<span class="n">corners</span> <span class="o">=</span> <span class="p">(</span><span class="n">xmin</span><span class="p">,</span> <span class="n">ymin</span><span class="p">),</span> <span class="p">(</span><span class="n">xmax</span><span class="p">,</span> <span class="n">ymax</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">update_datalim</span><span class="p">(</span><span class="n">corners</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sticky_edges</span><span class="o">.</span><span class="n">x</span><span class="p">[:]</span> <span class="o">=</span> <span class="p">[</span><span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sticky_edges</span><span class="o">.</span><span class="n">y</span><span class="p">[:]</span> <span class="o">=</span> <span class="p">[</span><span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span><span class="p">]</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">_autoscaleXon</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">((</span><span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span><span class="p">),</span> <span class="n">auto</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">_autoscaleYon</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">((</span><span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span><span class="p">),</span> <span class="n">auto</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">stale</span> <span class="o">=</span> <span class="kc">True</span></div>
<div class="viewcode-block" id="AxesImage.get_extent"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage.get_extent">[docs]</a> <span class="k">def</span> <span class="nf">get_extent</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Get the image extent: left, right, bottom, top"""</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extent</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extent</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">sz</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_size</span><span class="p">()</span>
<span class="n">numrows</span><span class="p">,</span> <span class="n">numcols</span> <span class="o">=</span> <span class="n">sz</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">origin</span> <span class="o">==</span> <span class="s1">'upper'</span><span class="p">:</span>
<span class="k">return</span> <span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">numcols</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">numrows</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.5</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">numcols</span><span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">numrows</span><span class="o">-</span><span class="mf">0.5</span><span class="p">)</span></div>
<div class="viewcode-block" id="AxesImage.get_cursor_data"><a class="viewcode-back" href="../../api/image_api.html#matplotlib.image.AxesImage.get_cursor_data">[docs]</a> <span class="k">def</span> <span class="nf">get_cursor_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">event</span><span class="p">):</span>
<span class="sd">"""Get the cursor data for a given event"""</span>
<span class="n">xmin</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_extent</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">origin</span> <span class="o">==</span> <span class="s1">'upper'</span><span class="p">:</span>