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generated first sphinx instance and adapted code doctsrings for automated api...

generated first sphinx instance and adapted code doctsrings for automated api generation for disaggregation module as a first test
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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line.
SPHINXOPTS =
SPHINXBUILD = sphinx-build
SPHINXPROJ = flex_extract
SOURCEDIR = source
BUILDDIR = build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
\ No newline at end of file
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 02e87e48403e699e19326e64e41ebe7d
tags: 645f666f9bcd5a90fca523b33c5a78b7
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<div class="section" id="module-disaggregation">
<span id="auto-generated-documentation"></span><h1>Auto Generated Documentation<a class="headerlink" href="#module-disaggregation" title="Permalink to this headline"></a></h1>
<dl class="function">
<dt id="disaggregation.IA3">
<code class="descclassname">disaggregation.</code><code class="descname">IA3</code><span class="sig-paren">(</span><em>g</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/disaggregation.html#IA3"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#disaggregation.IA3" title="Permalink to this definition"></a></dt>
<dd><p>Interpolation with a non-negative geometric mean based algorithm.</p>
<p>The original grid is reconstructed by adding two sampling points in each
data series interval. This subgrid is used to keep all information during
the interpolation within the associated interval. Additionally, an advanced
monotonicity filter is applied to improve the monotonicity properties of
the series.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>Copyright 2017
Sabine Hittmeir, Anne Philipp, Petra Seibert</p>
<p class="last">This work is licensed under the Creative Commons Attribution 4.0
International License. To view a copy of this license, visit
<a class="reference external" href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</a> or send a letter to
Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</p>
</div>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>g</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code>) – Complete data series that will be interpolated having
the dimension of the original raw series.</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><strong>f</strong> – The interpolated data series with additional subgrid points.
Its dimension is equal to the length of the input data series
times three.</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><code class="xref py py-obj docutils literal notranslate"><span class="pre">list</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code></td>
</tr>
</tbody>
</table>
<p class="rubric">References</p>
<p>For more information see article:
Hittmeir, S.; Philipp, A.; Seibert, P. (2017): A conservative
interpolation scheme for extensive quantities with application to the
Lagrangian particle dispersion model FLEXPART.,
Geoscientific Model Development</p>
</dd></dl>
<dl class="function">
<dt id="disaggregation.dapoly">
<code class="descclassname">disaggregation.</code><code class="descname">dapoly</code><span class="sig-paren">(</span><em>alist</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/disaggregation.html#dapoly"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#disaggregation.dapoly" title="Permalink to this definition"></a></dt>
<dd><p>Cubic polynomial interpolation of deaccumulated fluxes.</p>
<p>Interpolation of deaccumulated fluxes of an ECMWF model FG field
using a cubic polynomial solution which conserves the integrals
of the fluxes within each timespan.
Disaggregation is done for 4 accumluated timespans which
generates a new, disaggregated value which is output at the
central point of the 4 accumulation timespans.
This new point is used for linear interpolation of the complete
timeseries afterwards.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>alist</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code>) – List of 4 timespans as 2-dimensional, horizontal fields.
E.g. [[array_t1], [array_t2], [array_t3], [array_t4]]</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><strong>nfield</strong> – Interpolated flux at central point of accumulation timespan.</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code></td>
</tr>
</tbody>
</table>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<dl class="last docutils">
<dt>March 2000 <span class="classifier-delimiter">:</span> <span class="classifier">P. JAMES</span></dt>
<dd>Original author</dd>
<dt>June 2003 <span class="classifier-delimiter">:</span> <span class="classifier">A. BECK</span></dt>
<dd>Adaptations</dd>
<dt>November 2015 <span class="classifier-delimiter">:</span> <span class="classifier">Leopold Haimberger (University of Vienna)</span></dt>
<dd>Migration from Fortran to Python</dd>
</dl>
</div>
</dd></dl>
<dl class="function">
<dt id="disaggregation.darain">
<code class="descclassname">disaggregation.</code><code class="descname">darain</code><span class="sig-paren">(</span><em>alist</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/disaggregation.html#darain"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#disaggregation.darain" title="Permalink to this definition"></a></dt>
<dd><p>Linear interpolation of deaccumulated fluxes.</p>
<p>Interpolation of deaccumulated fluxes of an ECMWF model FG rainfall
field using a modified linear solution which conserves the integrals
of the fluxes within each timespan.
Disaggregation is done for 4 accumluated timespans which generates
a new, disaggregated value which is output at the central point
of the 4 accumulation timespans. This new point is used for linear
interpolation of the complete timeseries afterwards.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>alist</strong> (<code class="xref py py-obj docutils literal notranslate"><span class="pre">list</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code>) – List of 4 timespans as 2-dimensional, horizontal fields.
E.g. [[array_t1], [array_t2], [array_t3], [array_t4]]</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><strong>nfield</strong> – Interpolated flux at central point of accumulation timespan.</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">float</span></code></td>
</tr>
</tbody>
</table>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<dl class="last docutils">
<dt>March 2000 <span class="classifier-delimiter">:</span> <span class="classifier">P. JAMES</span></dt>
<dd>Original author</dd>
<dt>June 2003 <span class="classifier-delimiter">:</span> <span class="classifier">A. BECK</span></dt>
<dd>Adaptations</dd>
<dt>November 2015 <span class="classifier-delimiter">:</span> <span class="classifier">Leopold Haimberger (University of Vienna)</span></dt>
<dd>Migration from Fortran to Python</dd>
</dl>
</div>
</dd></dl>
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