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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">io</span> <span class="kn">import</span> <span class="n">BytesIO</span>
<span class="kn">import</span> <span class="nn">math</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span>
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
<span class="kn">import</span> <span class="nn">urllib.parse</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="kn">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.backend_bases</span> <span class="kn">import</span> <span class="n">FigureCanvasBase</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="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="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">matplotlib.transforms</span> <span class="kn">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">'antialiased'</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"># this will use nearest or Hanning...</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_scalar_alpha</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="nb">round</span><span class="p">(</span><span class="n">l</span><span class="p">),</span> <span class="nb">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">_resample</span><span class="p">(</span>
<span class="n">image_obj</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">out_shape</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">resample</span><span class="o">=</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="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Convenience wrapper around `._image.resample` to resample *data* to</span>
<span class="sd"> *out_shape* (with a third dimension if *data* is RGBA) that takes care of</span>
<span class="sd"> allocating the output array and fetching the relevant properties from the</span>
<span class="sd"> Image object *image_obj*.</span>
<span class="sd"> """</span>
<span class="c1"># decide if we need to apply anti-aliasing if the data is upsampled:</span>
<span class="c1"># compare the number of displayed pixels to the number of</span>
<span class="c1"># the data pixels.</span>
<span class="n">interpolation</span> <span class="o">=</span> <span class="n">image_obj</span><span class="o">.</span><span class="n">get_interpolation</span><span class="p">()</span>
<span class="k">if</span> <span class="n">interpolation</span> <span class="o">==</span> <span class="s1">'antialiased'</span><span class="p">:</span>
<span class="c1"># don't antialias if upsampling by an integer number or</span>
<span class="c1"># if zooming in more than a factor of 3</span>
<span class="n">pos</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="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</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">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="n">disp</span> <span class="o">=</span> <span class="n">transform</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">pos</span><span class="p">)</span>
<span class="n">dispx</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">disp</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]))</span>
<span class="n">dispy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">disp</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]))</span>
<span class="k">if</span> <span class="p">((</span><span class="n">dispx</span> <span class="o">></span> <span class="mi">3</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="ow">or</span>
<span class="n">dispx</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="ow">or</span>
<span class="n">dispx</span> <span class="o">==</span> <span class="mi">2</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="ow">and</span>
<span class="p">(</span><span class="n">dispy</span> <span class="o">></span> <span class="mi">3</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="ow">or</span>
<span class="n">dispy</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="ow">or</span>
<span class="n">dispy</span> <span class="o">==</span> <span class="mi">2</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="n">interpolation</span> <span class="o">=</span> <span class="s1">'nearest'</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">interpolation</span> <span class="o">=</span> <span class="s1">'hanning'</span>
<span class="n">out</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_shape</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">2</span><span class="p">:],</span> <span class="n">data</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="c1"># 2D->2D, 3D->3D.</span>
<span class="k">if</span> <span class="n">resample</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">resample</span> <span class="o">=</span> <span class="n">image_obj</span><span class="o">.</span><span class="n">get_resample</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">out</span><span class="p">,</span> <span class="n">transform</span><span class="p">,</span>
<span class="n">_interpd_</span><span class="p">[</span><span class="n">interpolation</span><span class="p">],</span>
<span class="n">resample</span><span class="p">,</span>
<span class="n">alpha</span><span class="p">,</span>
<span class="n">image_obj</span><span class="o">.</span><span class="n">get_filternorm</span><span class="p">(),</span>
<span class="n">image_obj</span><span class="o">.</span><span class="n">get_filterrad</span><span class="p">())</span>
<span class="k">return</span> <span class="n">out</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="sd">"""</span>
<span class="sd"> Base class for images.</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">zorder</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">def</span> <span class="fm">__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="kc">True</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="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="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">"""Return the size of the image as tuple (numrows, numcols)."""</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 all backends.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> alpha : float</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">alpha</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span>
<span class="n">alpha</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">alpha</span><span class="p">)</span>
<span class="k">if</span> <span class="n">alpha</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="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s1">'alpha must be a float, two-dimensional '</span>
<span class="s1">'array, or None'</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_alpha</span> <span class="o">=</span> <span class="n">alpha</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pchanged</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>
<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">_get_scalar_alpha</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Get a scalar alpha value to be applied to the artist as a whole.</span>
<span class="sd"> If the alpha value is a matrix, the method returns 1.0 because pixels</span>
<span class="sd"> have individual alpha values (see `~._ImageBase._make_image` for</span>
<span class="sd"> details). If the alpha value is a scalar, the method returns said value</span>
<span class="sd"> to be applied to the artist as a whole because pixels do not have</span>
<span class="sd"> individual alpha values.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="mf">1.0</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_alpha</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">ndim</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_alpha</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span> \
<span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">_alpha</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 colormap the image *A* from the given *in_bbox*</span>
<span class="sd"> (in data space), to the given *out_bbox* (in pixel space) clipped to</span>
<span class="sd"> the given *clip_bbox* (also in pixel space), and magnified by the</span>
<span class="sd"> *magnification* factor.</span>
<span class="sd"> *A* may be a greyscale image (M, N) with a dtype of float32, float64,</span>
<span class="sd"> float128, uint16 or uint8, or an (M, N, 4) RGBA image with a dtype of</span>
<span class="sd"> float32, float64, float128, 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 be</span>
<span class="sd"> rounded to the nearest pixel boundary. This makes the images align</span>
<span class="sd"> correctly with the axes. It should not be used if exact scaling is</span>
<span class="sd"> needed, such as for `FigureImage`.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> image : (M, N, 4) uint8 array</span>
<span class="sd"> The RGBA image, resampled unless *unsampled* is True.</span>
<span class="sd"> x, y : float</span>
<span class="sd"> The upper left corner where the image should be drawn, in pixel</span>
<span class="sd"> space.</span>
<span class="sd"> trans : Affine2D</span>
<span class="sd"> The affine transformation from image to pixel 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="p">(</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="c1"># So that the image is aligned with the edge of the axes, we want to</span>
<span class="c1"># round up the output width to the next integer. This also means</span>
<span class="c1"># scaling the transform slightly to account for the 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="n">math</span><span class="o">.</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="n">math</span><span class="o">.</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="n">out_shape</span> <span class="o">=</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="k">if</span> <span class="ow">not</span> <span class="n">unsampled</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</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="ow">or</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="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">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Invalid shape </span><span class="si">{</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2"> for image data"</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"># 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="c1"># Cast to float64</span>
<span class="k">if</span> <span class="n">A</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">not</span> <span class="ow">in</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">float16</span><span class="p">):</span>
<span class="k">if</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">float64</span><span class="p">:</span>
<span class="n">cbook</span><span class="o">.</span><span class="n">_warn_external</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">"Casting input data from '</span><span class="si">{</span><span class="n">A</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">' to "</span>
<span class="sa">f</span><span class="s2">"'float64' for imshow"</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">float64</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="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">if</span> <span class="n">da</span> <span class="o">></span> <span class="mf">1e8</span> <span class="k">else</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="c1"># Always copy, and don't allow array subtypes.</span>
<span class="n">A_scaled</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">A</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="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="bp">self</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">autoscale_None</span><span class="p">(</span><span class="n">A</span><span class="p">)</span>
<span class="n">dv</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">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">fact</span> <span class="o">=</span> <span class="mf">1e7</span> <span class="k">if</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="mf">1e4</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="n">fact</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="n">fact</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">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">out</span><span class="o">=</span><span class="n">A_scaled</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"># item to avoid errors</span>
<span class="n">a_min</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">scaled_dtype</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
<span class="n">a_max</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">scaled_dtype</span><span class="p">)</span><span class="o">.</span><span class="n">item</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="c1"># resample the input data to the correct resolution and shape</span>
<span class="n">A_resampled</span> <span class="o">=</span> <span class="n">_resample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">A_scaled</span><span class="p">,</span> <span class="n">out_shape</span><span class="p">,</span> <span class="n">t</span><span class="p">)</span>
<span class="c1"># done with A_scaled now, remove from namespace 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="p">(</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">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="c1"># nontrivial mask</span>
<span class="k">else</span> <span class="n">np</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">A</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="c1"># we always have to interpolate the mask to account for</span>
<span class="c1"># non-affine transformations</span>
<span class="n">out_alpha</span> <span class="o">=</span> <span class="n">_resample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mask</span><span class="p">,</span> <span class="n">out_shape</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">resample</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># done with the mask now, delete from namespace to be sure!</span>
<span class="k">del</span> <span class="n">mask</span>
<span class="c1"># Agg updates out_alpha in place. If the pixel has no image</span>
<span class="c1"># data it will not be updated (and still be 0 as we initialized</span>
<span class="c1"># it), if input data that would go into that output pixel than</span>
<span class="c1"># it will be `nan`, if all the input data for a pixel is good</span>
<span class="c1"># it will be 1, and if there is _some_ good data in that output</span>
<span class="c1"># pixel it will be between [0, 1] (such as a rotated image).</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_alpha</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"># Apply the pixel-by-pixel alpha values if present</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="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">np</span><span class="o">.</span><span class="n">ndim</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
<span class="n">out_alpha</span> <span class="o">*=</span> <span class="n">_resample</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="n">out_shape</span><span class="p">,</span>
<span class="n">t</span><span class="p">,</span> <span class="n">resample</span><span class="o">=</span><span class="kc">True</span><span class="p">)</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="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="n">alpha</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_scalar_alpha</span><span class="p">()</span>
<span class="n">output_alpha</span> <span class="o">=</span> <span class="n">_resample</span><span class="p">(</span> <span class="c1"># resample alpha channel</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">A</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="n">out_shape</span><span class="p">,</span> <span class="n">t</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="n">output</span> <span class="o">=</span> <span class="n">_resample</span><span class="p">(</span> <span class="c1"># resample rgb channels</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">_rgb_to_rgba</span><span class="p">(</span><span class="n">A</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="p">:</span><span class="mi">3</span><span class="p">]),</span> <span class="n">out_shape</span><span class="p">,</span> <span class="n">t</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="n">output</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">output_alpha</span> <span class="c1"># recombine rgb and alpha</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_scalar_alpha</span><span class="p">()</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">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="sd">"""</span>
<span class="sd"> Normalize, rescale, and colormap this image's data for rendering using</span>
<span class="sd"> *renderer*, with the given *magnification*.</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"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> image : (M, N, 4) uint8 array</span>
<span class="sd"> The RGBA image, resampled unless *unsampled* is True.</span>
<span class="sd"> x, y : float</span>
<span class="sd"> The upper left corner where the image should be drawn, in pixel</span>
<span class="sd"> space.</span>
<span class="sd"> trans : Affine2D</span>
<span class="sd"> The affine transformation from image to pixel space.</span>
<span class="sd"> """</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</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 whether 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">@martist</span><span class="o">.</span><span class="n">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_scalar_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="n">inside</span><span class="p">,</span> <span class="n">info</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_default_contains</span><span class="p">(</span><span class="n">mouseevent</span><span class="p">)</span>
<span class="k">if</span> <span class="n">inside</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="n">inside</span><span class="p">,</span> <span class="n">info</span>
<span class="c1"># 1) This doesn't work for figimage; but figimage also needs a fix</span>
<span class="c1"># below (as the check cannot use x/ydata and extents).</span>
<span class="c1"># 2) As long as the check below uses x/ydata, we need to test axes</span>
<span class="c1"># identity instead of `self.axes.contains(event)` because even if</span>
<span class="c1"># axes overlap, x/ydata is only valid for event.inaxes anyways.</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">mouseevent</span><span class="o">.</span><span class="n">inaxes</span><span class="p">:</span>
<span class="k">return</span> <span class="kc">False</span><span class="p">,</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="kn">from</span> <span class="nn">matplotlib</span> <span class="kn">import</span> <span class="n">_png</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="k">with</span> <span class="n">cbook</span><span class="o">.</span><span class="n">open_file_cm</span><span class="p">(</span><span class="n">fname</span><span class="p">,</span> <span class="s2">"wb"</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</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">file</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"> Note that this function does *not* update the normalization used.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> A : array-like or `PIL.Image.Image`</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="k">pass</span>
<span class="k">else</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">Image</span><span class="o">.</span><span class="n">Image</span><span class="p">):</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="c1"># Needed e.g. to apply png palette.</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 of dtype </span><span class="si">{}</span><span class="s2"> cannot be converted to "</span>
<span class="s2">"float"</span><span class="o">.</span><span class="n">format</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="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 shape </span><span class="si">{}</span><span class="s2"> for image data"</span>
<span class="o">.</span><span class="n">format</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">shape</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"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> A : array-like</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 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 'antialiased', 'nearest', 'bilinear', 'bicubic', 'spline16',</span>
<span class="sd"> 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',</span>
<span class="sd"> 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos',</span>
<span class="sd"> 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"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> s : {'antialiased', 'nearest', 'bilinear', 'bicubic', 'spline16',</span>
<span class="sd">'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom', \</span>
<span class="sd">'gaussian', 'bessel', 'mitchell', '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="n">cbook</span><span class="o">.</span><span class="n">_check_in_list</span><span class="p">(</span><span class="n">_interpd_</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="n">s</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">"""Return whether the image can be composited with its neighbors."""</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 image resampling is used.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> v : bool or None</span>
<span class="sd"> If None, use :rc:`image.resample` = True.</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 whether image resampling is used."""</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 normalizes the weights.</span>
<span class="sd"> See help for `~.Axes.imshow`.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> filternorm : bool</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_filternorm</span> <span class="o">=</span> <span class="nb">bool</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">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 whether the resize filter normalizes the weights."""</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"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> filterrad : 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="sd">"""</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> ax : `~.axes.Axes`</span>
<span class="sd"> The axes the image will belong to.</span>
<span class="sd"> cmap : str or `~matplotlib.colors.Colormap`, default: :rc:`image.cmap`</span>
<span class="sd"> The Colormap instance or registered colormap name used to map scalar</span>
<span class="sd"> data to colors.</span>
<span class="sd"> norm : `~matplotlib.colors.Normalize`</span>
<span class="sd"> Maps luminance to 0-1.</span>
<span class="sd"> interpolation : str, default: :rc:`image.interpolation`</span>
<span class="sd"> Supported values are 'none', 'antialiased', 'nearest', 'bilinear',</span>
<span class="sd"> 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite',</span>
<span class="sd"> 'kaiser', 'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell',</span>
<span class="sd"> 'sinc', 'lanczos'.</span>
<span class="sd"> origin : {'upper', 'lower'}, default: :rc:`image.origin`</span>
<span class="sd"> Place the [0, 0] index of the array in the upper left or lower left</span>
<span class="sd"> corner of the axes. The convention 'upper' is typically used for</span>
<span class="sd"> matrices and images.</span>
<span class="sd"> extent : tuple, optional</span>
<span class="sd"> The 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"> filternorm : bool, default: True</span>
<span class="sd"> A parameter for the antigrain image resize filter</span>
<span class="sd"> (see the antigrain documentation).</span>
<span class="sd"> If filternorm is set, the filter normalizes integer values and corrects</span>
<span class="sd"> the rounding errors. It doesn't do anything with the source floating</span>
<span class="sd"> point values, it corrects only integers according to the rule of 1.0</span>
<span class="sd"> which means that any sum of pixel weights must be equal to 1.0. So,</span>
<span class="sd"> the filter function must produce a graph of the proper shape.</span>
<span class="sd"> filterrad : float > 0, default: 4</span>
<span class="sd"> The filter radius for filters that have a radius parameter, i.e. when</span>
<span class="sd"> interpolation is one of: 'sinc', 'lanczos' or 'blackman'.</span>
<span class="sd"> resample : bool, default: False</span>
<span class="sd"> When True, use a full resampling method. When False, only resample when</span>
<span class="sd"> the output image is larger than the input image.</span>
<span class="sd"> **kwargs : `.Artist` properties</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="fm">__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="fm">__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>