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<h1>Source code for matplotlib.units</h1><div class="highlight"><pre>
<span></span><span class="sd">"""</span>
<span class="sd">The classes here provide support for using custom classes with</span>
<span class="sd">Matplotlib, e.g., those that do not expose the array interface but know</span>
<span class="sd">how to convert themselves to arrays. It also supports classes with</span>
<span class="sd">units and units conversion. Use cases include converters for custom</span>
<span class="sd">objects, e.g., a list of datetime objects, as well as for objects that</span>
<span class="sd">are unit aware. We don't assume any particular units implementation;</span>
<span class="sd">rather a units implementation must provide the register with the Registry</span>
<span class="sd">converter dictionary and a `ConversionInterface`. For example,</span>
<span class="sd">here is a complete implementation which supports plotting with native</span>
<span class="sd">datetime objects::</span>
<span class="sd"> import matplotlib.units as units</span>
<span class="sd"> import matplotlib.dates as dates</span>
<span class="sd"> import matplotlib.ticker as ticker</span>
<span class="sd"> import datetime</span>
<span class="sd"> class DateConverter(units.ConversionInterface):</span>
<span class="sd"> @staticmethod</span>
<span class="sd"> def convert(value, unit, axis):</span>
<span class="sd"> 'Convert a datetime value to a scalar or array'</span>
<span class="sd"> return dates.date2num(value)</span>
<span class="sd"> @staticmethod</span>
<span class="sd"> def axisinfo(unit, axis):</span>
<span class="sd"> 'Return major and minor tick locators and formatters'</span>
<span class="sd"> if unit!='date': return None</span>
<span class="sd"> majloc = dates.AutoDateLocator()</span>
<span class="sd"> majfmt = dates.AutoDateFormatter(majloc)</span>
<span class="sd"> return AxisInfo(majloc=majloc,</span>
<span class="sd"> majfmt=majfmt,</span>
<span class="sd"> label='date')</span>
<span class="sd"> @staticmethod</span>
<span class="sd"> def default_units(x, axis):</span>
<span class="sd"> 'Return the default unit for x or None'</span>
<span class="sd"> return 'date'</span>
<span class="sd"> # Finally we register our object type with the Matplotlib units registry.</span>
<span class="sd"> units.registry[datetime.date] = DateConverter()</span>
<span class="sd">"""</span>
<span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="p">(</span><span class="n">absolute_import</span><span class="p">,</span> <span class="n">division</span><span class="p">,</span> <span class="n">print_function</span><span class="p">,</span>
<span class="n">unicode_literals</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">six</span>
<span class="kn">from</span> <span class="nn">matplotlib.cbook</span> <span class="kn">import</span> <span class="n">iterable</span><span class="p">,</span> <span class="n">is_numlike</span><span class="p">,</span> <span class="n">safe_first_element</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="AxisInfo"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.AxisInfo">[docs]</a><span class="k">class</span> <span class="nc">AxisInfo</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Information to support default axis labeling, tick labeling, and</span>
<span class="sd"> default limits. An instance of this class must be returned by</span>
<span class="sd"> :meth:`ConversionInterface.axisinfo`.</span>
<span class="sd"> """</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">majloc</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">minloc</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">majfmt</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">minfmt</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">default_limits</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> majloc, minloc : Locator, optional</span>
<span class="sd"> Tick locators for the major and minor ticks.</span>
<span class="sd"> majfmt, minfmt : Formatter, optional</span>
<span class="sd"> Tick formatters for the major and minor ticks.</span>
<span class="sd"> label : str, optional</span>
<span class="sd"> The default axis label.</span>
<span class="sd"> default_limits : optional</span>
<span class="sd"> The default min and max limits of the axis if no data has</span>
<span class="sd"> been plotted.</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> If any of the above are ``None``, the axis will simply use the</span>
<span class="sd"> default value.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">majloc</span> <span class="o">=</span> <span class="n">majloc</span>
<span class="bp">self</span><span class="o">.</span><span class="n">minloc</span> <span class="o">=</span> <span class="n">minloc</span>
<span class="bp">self</span><span class="o">.</span><span class="n">majfmt</span> <span class="o">=</span> <span class="n">majfmt</span>
<span class="bp">self</span><span class="o">.</span><span class="n">minfmt</span> <span class="o">=</span> <span class="n">minfmt</span>
<span class="bp">self</span><span class="o">.</span><span class="n">label</span> <span class="o">=</span> <span class="n">label</span>
<span class="bp">self</span><span class="o">.</span><span class="n">default_limits</span> <span class="o">=</span> <span class="n">default_limits</span></div>
<div class="viewcode-block" id="ConversionInterface"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface">[docs]</a><span class="k">class</span> <span class="nc">ConversionInterface</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The minimal interface for a converter to take custom data types (or</span>
<span class="sd"> sequences) and convert them to values Matplotlib can use.</span>
<span class="sd"> """</span>
<div class="viewcode-block" id="ConversionInterface.axisinfo"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.axisinfo">[docs]</a> <span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">axisinfo</span><span class="p">(</span><span class="n">unit</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return an `~units.AxisInfo` instance for the axis with the</span>
<span class="sd"> specified units.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="kc">None</span></div>
<div class="viewcode-block" id="ConversionInterface.default_units"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.default_units">[docs]</a> <span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">default_units</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the default unit for *x* or ``None`` for the given axis.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="kc">None</span></div>
<div class="viewcode-block" id="ConversionInterface.convert"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.convert">[docs]</a> <span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">convert</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">unit</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Convert *obj* using *unit* for the specified *axis*.</span>
<span class="sd"> If *obj* is a sequence, return the converted sequence.</span>
<span class="sd"> The output must be a sequence of scalars that can be used by the numpy</span>
<span class="sd"> array layer.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="n">obj</span></div>
<div class="viewcode-block" id="ConversionInterface.is_numlike"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.is_numlike">[docs]</a> <span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">is_numlike</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The Matplotlib datalim, autoscaling, locators etc work with</span>
<span class="sd"> scalars which are the units converted to floats given the</span>
<span class="sd"> current unit. The converter may be passed these floats, or</span>
<span class="sd"> arrays of them, even when units are set.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">iterable</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="k">for</span> <span class="n">thisx</span> <span class="ow">in</span> <span class="n">x</span><span class="p">:</span>
<span class="k">return</span> <span class="n">is_numlike</span><span class="p">(</span><span class="n">thisx</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">is_numlike</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="Registry"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.Registry">[docs]</a><span class="k">class</span> <span class="nc">Registry</span><span class="p">(</span><span class="nb">dict</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> A register that maps types to conversion interfaces.</span>
<span class="sd"> """</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="nb">dict</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="bp">self</span><span class="o">.</span><span class="n">_cached</span> <span class="o">=</span> <span class="p">{}</span>
<div class="viewcode-block" id="Registry.get_converter"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.Registry.get_converter">[docs]</a> <span class="k">def</span> <span class="nf">get_converter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Get the converter for data that has the same type as *x*. If no</span>
<span class="sd"> converters are registered for *x*, returns ``None``.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="kc">None</span> <span class="c1"># nothing registered</span>
<span class="c1"># DISABLED idx = id(x)</span>
<span class="c1"># DISABLED cached = self._cached.get(idx)</span>
<span class="c1"># DISABLED if cached is not None: return cached</span>
<span class="n">converter</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">classx</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="s1">'__class__'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">classx</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">converter</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">classx</span><span class="p">)</span>
<span class="k">if</span> <span class="n">converter</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="s2">"values"</span><span class="p">):</span>
<span class="c1"># this unpacks pandas series or dataframes...</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">values</span>
<span class="c1"># If x is an array, look inside the array for data with units</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span><span class="p">:</span>
<span class="n">xravel</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="k">try</span><span class="p">:</span>
<span class="c1"># pass the first value of x that is not masked back to</span>
<span class="c1"># get_converter</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">all</span><span class="p">(</span><span class="n">xravel</span><span class="o">.</span><span class="n">mask</span><span class="p">):</span>
<span class="c1"># some elements are not masked</span>
<span class="n">converter</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_converter</span><span class="p">(</span>
<span class="n">xravel</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">xravel</span><span class="o">.</span><span class="n">mask</span><span class="p">)])</span>
<span class="k">return</span> <span class="n">converter</span>
<span class="k">except</span> <span class="ne">AttributeError</span><span class="p">:</span>
<span class="c1"># not a masked_array</span>
<span class="c1"># Make sure we don't recurse forever -- it's possible for</span>
<span class="c1"># ndarray subclasses to continue to return subclasses and</span>
<span class="c1"># not ever return a non-subclass for a single element.</span>
<span class="n">next_item</span> <span class="o">=</span> <span class="n">xravel</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">if</span> <span class="p">(</span><span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">next_item</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">or</span>
<span class="n">next_item</span><span class="o">.</span><span class="n">shape</span> <span class="o">!=</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">):</span>
<span class="n">converter</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_converter</span><span class="p">(</span><span class="n">next_item</span><span class="p">)</span>
<span class="k">return</span> <span class="n">converter</span>
<span class="c1"># If we haven't found a converter yet, try to get the first element</span>
<span class="k">if</span> <span class="n">converter</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">thisx</span> <span class="o">=</span> <span class="n">safe_first_element</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="k">except</span> <span class="p">(</span><span class="ne">TypeError</span><span class="p">,</span> <span class="ne">StopIteration</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="n">classx</span> <span class="ow">and</span> <span class="n">classx</span> <span class="o">!=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">thisx</span><span class="p">,</span> <span class="s1">'__class__'</span><span class="p">,</span> <span class="kc">None</span><span class="p">):</span>
<span class="n">converter</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_converter</span><span class="p">(</span><span class="n">thisx</span><span class="p">)</span>
<span class="k">return</span> <span class="n">converter</span>
<span class="c1"># DISABLED self._cached[idx] = converter</span>
<span class="k">return</span> <span class="n">converter</span></div></div>
<span class="n">registry</span> <span class="o">=</span> <span class="n">Registry</span><span class="p">()</span>
</pre></div>
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