deploy: 19a7391

_modules/pysp2/util/particle_properties.html

@@ -414,7 +414,9 @@ <h1>Source code for pysp2.util.particle_properties</h1><div class="highlight"><p
 
     <span class="n">PkHt_ch1</span> <span class="o">=</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkHt_ch1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
     <span class="n">PkHt_ch5</span> <span class="o">=</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkHt_ch5&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
-    <span class="n">width</span> <span class="o">=</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkEnd_ch1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span> <span class="o">-</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkStart_ch1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+    <span class="n">width_ch1</span> <span class="o">=</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkEnd_ch1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span> <span class="o">-</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkStart_ch1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+    <span class="n">width_ch5</span> <span class="o">=</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkEnd_ch5&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span> <span class="o">-</span> <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkStart_ch5&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+    <span class="n">width</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">width_ch1</span><span class="p">),</span><span class="n">width_ch5</span><span class="p">,</span><span class="n">width_ch1</span><span class="p">)</span>
     <span class="n">accepted_incand</span> <span class="o">=</span> <span class="n">width</span> <span class="o">&gt;=</span> <span class="n">Globals</span><span class="o">.</span><span class="n">IncanMinWidth</span>
     <span class="n">accepted_incand</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">accepted_incand</span><span class="p">,</span>
                                      <span class="n">input_ds</span><span class="p">[</span><span class="s1">&#39;PkHt_ch2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span> <span class="o">&gt;=</span> <span class="n">Globals</span><span class="o">.</span><span class="n">IncanMinPeakHt1</span><span class="p">)</span>

_modules/pysp2/util/peak_fit.html

@@ -863,9 +863,10 @@ <h1>Source code for pysp2.util.peak_fit</h1><div class="highlight"><pre>
     <span class="n">num_base_pts_2_avg</span> <span class="o">=</span> <span class="mi">20</span>
     <span class="n">data</span> <span class="o">=</span> <span class="n">my_ds</span><span class="p">[</span><span class="s1">&#39;Data_ch&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">channel</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
     <span class="n">V_maxloc</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-    <span class="n">V_minloc</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-    <span class="n">invert</span> <span class="o">=</span> <span class="n">V_maxloc</span> <span class="o">&lt;</span> <span class="n">V_minloc</span>
-    <span class="n">data</span><span class="p">[</span><span class="n">invert</span><span class="p">,</span> <span class="p">:]</span> <span class="o">=</span> <span class="o">-</span><span class="n">data</span><span class="p">[</span><span class="n">invert</span><span class="p">,</span> <span class="p">:]</span>
+    <span class="c1">#V_minloc = np.argmin(data, axis=1)</span>
+    <span class="c1">#invert = V_maxloc &lt; V_minloc</span>
+    <span class="k">if</span> <span class="n">channel</span><span class="o">==</span><span class="mi">3</span><span class="p">:</span>
+        <span class="n">data</span> <span class="o">=</span> <span class="o">-</span><span class="n">data</span>
     <span class="n">base</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">data</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">:</span><span class="n">num_base_pts_2_avg</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
     <span class="n">V_max</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
     <span class="n">conditions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logical_and</span><span class="o">.</span><span class="n">reduce</span><span class="p">(((</span><span class="n">V_max</span> <span class="o">-</span> <span class="n">base</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">,</span> <span class="n">V_maxloc</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="n">V_maxloc</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">))</span>
@@ -880,7 +881,7 @@ <h1>Source code for pysp2.util.peak_fit</h1><div class="highlight"><pre>
     <span class="n">pos_tile</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">tile</span><span class="p">(</span><span class="n">pos</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="mi">1</span><span class="p">))</span><span class="o">.</span><span class="n">T</span>
     <span class="n">counting_up</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">data</span> <span class="o">&lt;</span> <span class="mi">5</span><span class="p">,</span> <span class="n">counting_up</span> <span class="o">&lt;=</span> <span class="n">pos_tile</span><span class="p">),</span> <span class="n">counting_up</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
     <span class="n">start</span> <span class="o">=</span> <span class="n">counting_up</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-    <span class="n">fit_coeffs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;base&#39;</span><span class="p">:</span> <span class="n">base</span><span class="p">,</span> <span class="s1">&#39;height&#39;</span><span class="p">:</span> <span class="n">height</span><span class="p">,</span> <span class="s1">&#39;pos&#39;</span><span class="p">:</span> <span class="n">pos</span><span class="p">,</span> <span class="s1">&#39;start&#39;</span><span class="p">:</span> <span class="n">start</span><span class="p">,</span> <span class="s1">&#39;inverted&#39;</span><span class="p">:</span> <span class="n">invert</span><span class="p">}</span>
+    <span class="n">fit_coeffs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;base&#39;</span><span class="p">:</span> <span class="n">base</span><span class="p">,</span> <span class="s1">&#39;height&#39;</span><span class="p">:</span> <span class="n">height</span><span class="p">,</span> <span class="s1">&#39;pos&#39;</span><span class="p">:</span> <span class="n">pos</span><span class="p">,</span> <span class="s1">&#39;start&#39;</span><span class="p">:</span> <span class="n">start</span><span class="p">}</span>
 
     <span class="k">return</span> <span class="n">fit_coeffs</span>
 

_modules/pysp2/vis/plot_wave.html

@@ -424,7 +424,7 @@ <h1>Source code for pysp2.vis.plot_wave</h1><div class="highlight"><pre>
         <span class="n">pos</span> <span class="o">=</span> <span class="n">spectra</span><span class="p">[</span><span class="s1">&#39;FtPos_ch&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">chn</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
         <span class="n">base</span> <span class="o">=</span> <span class="n">spectra</span><span class="p">[</span><span class="s1">&#39;Base_ch&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">chn</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
         <span class="n">width</span> <span class="o">=</span> <span class="n">spectra</span><span class="p">[</span><span class="s1">&#39;PkFWHM_ch&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">chn</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
-        <span class="n">Y</span> <span class="o">=</span> <span class="n">_gaus</span><span class="p">(</span><span class="n">xspace</span><span class="p">,</span> <span class="n">amplitude</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span> <span class="n">width</span><span class="o">/</span><span class="mf">2.</span><span class="p">,</span> <span class="n">base</span><span class="p">)</span>
+        <span class="n">Y</span> <span class="o">=</span> <span class="n">_gaus</span><span class="p">(</span><span class="n">xspace</span><span class="p">,</span> <span class="n">amplitude</span><span class="p">,</span> <span class="n">pos</span><span class="p">,</span> <span class="n">width</span><span class="o">/</span><span class="mf">2.35482</span><span class="p">,</span> <span class="n">base</span><span class="p">)</span>
         <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">xspace</span><span class="p">,</span> <span class="n">Y</span><span class="p">)</span>
         <span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="mf">0.7</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="s1">&#39;Fit Pos = </span><span class="si">%3.2f</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">pos</span><span class="p">,</span>
                 <span class="n">transform</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">transAxes</span><span class="p">)</span>
@@ -494,8 +494,8 @@ <h1>Source code for pysp2.vis.plot_wave</h1><div class="highlight"><pre>
         <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">legends</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
         <span class="k">if</span> <span class="n">i</span><span class="o">==</span><span class="mi">2</span><span class="p">:</span>
             <span class="n">lines</span><span class="o">=</span><span class="n">ax</span><span class="o">.</span><span class="n">get_lines</span><span class="p">()</span>
-            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;PkSplitPos_ch3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">event_index</span><span class="o">=</span><span class="n">record_no</span><span class="p">),</span><span class="mi">0</span><span class="p">,</span><span class="s1">&#39;*&#39;</span><span class="p">,</span><span class="n">markersize</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="n">lines</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">())</span>
-            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;PkSplitPos_ch7&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">event_index</span><span class="o">=</span><span class="n">record_no</span><span class="p">),</span><span class="mi">0</span><span class="p">,</span><span class="s1">&#39;*&#39;</span><span class="p">,</span><span class="n">markersize</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="n">lines</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">())</span>
+            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;PkSplitPos_ch3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">event_index</span><span class="o">=</span><span class="n">record_no</span><span class="p">),</span><span class="mi">0</span><span class="p">,</span><span class="s1">&#39;1&#39;</span><span class="p">,</span><span class="n">markersize</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="n">lines</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">())</span>
+            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;PkSplitPos_ch7&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">event_index</span><span class="o">=</span><span class="n">record_no</span><span class="p">),</span><span class="mi">0</span><span class="p">,</span><span class="s1">&#39;2&#39;</span><span class="p">,</span><span class="n">markersize</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="n">lines</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">())</span>
     <span class="k">return</span> <span class="n">display</span>
 </pre></div>
 

_sources/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:19.474** total execution time for 3 files **from all galleries**:
+**00:19.337** total execution time for 3 files **from all galleries**:
 
 .. container::
 
@@ -33,11 +33,11 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_source_auto_examples_plot_psd.py` (``../../examples/plot_psd.py``)
-     - 00:09.920
+     - 00:09.813
      - 0.0
    * - :ref:`sphx_glr_source_auto_examples_plot_read_sp2b.py` (``../../examples/plot_read_sp2b.py``)
-     - 00:06.703
+     - 00:06.726
      - 0.0
    * - :ref:`sphx_glr_source_auto_examples_plot_hk.py` (``../../examples/plot_hk.py``)
-     - 00:02.851
+     - 00:02.798
      - 0.0

_sources/source/auto_examples/plot_hk.rst.txt

@@ -80,7 +80,7 @@ Example for plotting number of particles in housekeeping data
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.851 seconds)
+   **Total running time of the script:** (0 minutes 2.798 seconds)
 
 
 .. _sphx_glr_download_source_auto_examples_plot_hk.py:

_sources/source/auto_examples/plot_psd.rst.txt

@@ -40,7 +40,7 @@ Example on plotting particle concentration data timeseries
     Processing record 0
     /home/runner/work/PySP2/PySP2/pysp2/util/peak_fit.py:384: OptimizeWarning: Covariance of the parameters could not be estimated
       coeff, var_matrix = curve_fit(_gaus, bins_fit, data_fit, p0=p0, method='lm', maxfev=40, ftol=1e-3)
-    /home/runner/work/PySP2/PySP2/pysp2/util/peak_fit.py:563: OptimizeWarning: Covariance of the parameters could not be estimated
+    /home/runner/work/PySP2/PySP2/pysp2/util/peak_fit.py:564: OptimizeWarning: Covariance of the parameters could not be estimated
       coeff, var_matrix = curve_fit(_gaus, bins_fit, temp1_fit, p0=p0, method='lm', maxfev=50, ftol=1e-3)
     Processing record 1000
     Processing record 2000
@@ -49,7 +49,7 @@ Example on plotting particle concentration data timeseries
     Processing record 5000
     /home/runner/work/PySP2/PySP2/pysp2/util/peak_fit.py:78: RuntimeWarning: Mean of empty slice
       ratio = np.nanmean(
-    5877 records processed in 6.259682655334473 s
+    5877 records processed in 6.273894309997559 s
     /home/runner/work/PySP2/PySP2/pysp2/util/particle_properties.py:38: RuntimeWarning: All-NaN slice encountered
       PkHt_ch0 = np.nanmax(np.stack([input_ds['PkHt_ch0'].values, input_ds['FtAmp_ch0'].values]), axis=0)
     /home/runner/work/PySP2/PySP2/pysp2/util/particle_properties.py:39: RuntimeWarning: All-NaN slice encountered
@@ -86,7 +86,7 @@ Example on plotting particle concentration data timeseries
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 9.920 seconds)
+   **Total running time of the script:** (0 minutes 9.813 seconds)
 
 
 .. _sphx_glr_download_source_auto_examples_plot_psd.py: