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Documentation updated
This commit is contained in:
fjosw
parent
9e47e26665
commit
ac54a81b50
2 changed files with 114 additions and 5 deletions
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@ -125,6 +125,9 @@
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<li>
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<a class="function" href="#Corr.show">show</a>
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</li>
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<li>
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<a class="function" href="#Corr.spaghetti_plot">spaghetti_plot</a>
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</li>
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<li>
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<a class="function" href="#Corr.dump">dump</a>
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</li>
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@ -1000,7 +1003,34 @@
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<span class="k">else</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'save' has to be a string."</span><span class="p">)</span>
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<span class="k">return</span>
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<span class="k">def</span> <span class="nf">spaghetti_plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">logscale</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
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<span class="sd">"""Produces a spaghetti plot of the correlator suited to monitor exceptional configurations.</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> logscale : bool</span>
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<span class="sd"> Determines whether the scale of the y-axis is logarithmic or standard.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Correlator needs to be projected first."</span><span class="p">)</span>
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<span class="n">mc_names</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">item</span> <span class="k">for</span> <span class="n">sublist</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">mc_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">sublist</span><span class="p">]))</span>
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<span class="n">x0_vals</span> <span class="o">=</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">o</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">T</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span><span class="p">)</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span>
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<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">mc_names</span><span class="p">:</span>
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<span class="n">data</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">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">])</span><span class="o">.</span><span class="n">T</span>
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<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
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<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
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<span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x0_vals</span><span class="p">,</span> <span class="n">dat</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">'-'</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">''</span><span class="p">)</span>
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<span class="k">if</span> <span class="n">logscale</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'$x_0 / a$'</span><span class="p">)</span>
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<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
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<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
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<span class="k">def</span> <span class="nf">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">datatype</span><span class="o">=</span><span class="s2">"json.gz"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
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<span class="sd">"""Dumps the Corr into a file of chosen type</span>
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@ -2113,7 +2143,34 @@
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<span class="k">else</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'save' has to be a string."</span><span class="p">)</span>
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<span class="k">return</span>
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<span class="k">def</span> <span class="nf">spaghetti_plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">logscale</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
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<span class="sd">"""Produces a spaghetti plot of the correlator suited to monitor exceptional configurations.</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> logscale : bool</span>
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<span class="sd"> Determines whether the scale of the y-axis is logarithmic or standard.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Correlator needs to be projected first."</span><span class="p">)</span>
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<span class="n">mc_names</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">item</span> <span class="k">for</span> <span class="n">sublist</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">mc_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">sublist</span><span class="p">]))</span>
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<span class="n">x0_vals</span> <span class="o">=</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">o</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">T</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span><span class="p">)</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span>
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<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">mc_names</span><span class="p">:</span>
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<span class="n">data</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">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">])</span><span class="o">.</span><span class="n">T</span>
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<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
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<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
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<span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x0_vals</span><span class="p">,</span> <span class="n">dat</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">'-'</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">''</span><span class="p">)</span>
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<span class="k">if</span> <span class="n">logscale</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
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<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'$x_0 / a$'</span><span class="p">)</span>
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<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
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<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
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<span class="k">def</span> <span class="nf">dump</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">filename</span><span class="p">,</span> <span class="n">datatype</span><span class="o">=</span><span class="s2">"json.gz"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
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<span class="sd">"""Dumps the Corr into a file of chosen type</span>
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@ -3782,8 +3839,6 @@ apply gamma_method with default parameters to the Corr. Defaults to None</li>
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<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">save</span><span class="p">)</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"'save' has to be a string."</span><span class="p">)</span>
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<span class="k">return</span>
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</pre></div>
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</details>
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@ -3814,6 +3869,60 @@ Apply the gamma method with standard parameters to all correlators and plateau v
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</div>
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</div>
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<div id="Corr.spaghetti_plot" class="classattr">
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<div class="attr function"><a class="headerlink" href="#Corr.spaghetti_plot">#  </a>
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<span class="def">def</span>
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<span class="name">spaghetti_plot</span><span class="signature">(self, logscale=True)</span>:
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</div>
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<details>
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<summary>View Source</summary>
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<div class="pdoc-code codehilite"><pre><span></span> <span class="k">def</span> <span class="nf">spaghetti_plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">logscale</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
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<span class="sd">"""Produces a spaghetti plot of the correlator suited to monitor exceptional configurations.</span>
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<span class="sd"> Parameters</span>
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<span class="sd"> ----------</span>
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<span class="sd"> logscale : bool</span>
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<span class="sd"> Determines whether the scale of the y-axis is logarithmic or standard.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">N</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Correlator needs to be projected first."</span><span class="p">)</span>
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<span class="n">mc_names</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">([</span><span class="n">item</span> <span class="k">for</span> <span class="n">sublist</span> <span class="ow">in</span> <span class="p">[</span><span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">mc_names</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">sublist</span><span class="p">]))</span>
|
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<span class="n">x0_vals</span> <span class="o">=</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">o</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">T</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span><span class="p">)</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span>
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||||
|
||||
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">mc_names</span><span class="p">:</span>
|
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<span class="n">data</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">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">deltas</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">+</span> <span class="n">o</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">r_values</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">content</span> <span class="k">if</span> <span class="n">o</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">])</span><span class="o">.</span><span class="n">T</span>
|
||||
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<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
|
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<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x0_vals</span><span class="p">,</span> <span class="n">dat</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">'-'</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s1">''</span><span class="p">)</span>
|
||||
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||||
<span class="k">if</span> <span class="n">logscale</span> <span class="ow">is</span> <span class="kc">True</span><span class="p">:</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">'log'</span><span class="p">)</span>
|
||||
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||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="sa">r</span><span class="s1">'$x_0 / a$'</span><span class="p">)</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
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</pre></div>
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</details>
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<div class="docstring"><p>Produces a spaghetti plot of the correlator suited to monitor exceptional configurations.</p>
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|
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<h6 id="parameters">Parameters</h6>
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|
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<ul>
|
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<li><strong>logscale</strong> (bool):
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Determines whether the scale of the y-axis is logarithmic or standard.</li>
|
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</ul>
|
||||
</div>
|
||||
|
||||
|
||||
</div>
|
||||
<div id="Corr.dump" class="classattr">
|
||||
<div class="attr function"><a class="headerlink" href="#Corr.dump">#  </a>
|
||||
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Add table
Reference in a new issue