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Posted to commits@climate.apache.org by bu...@apache.org on 2017/04/24 21:37:04 UTC
svn commit: r1011072 [14/17] - in /websites/staging/climate/trunk/content:
./ api/1.1.0/ api/1.1.0/_sources/ api/1.1.0/_sources/config/
api/1.1.0/_sources/data_source/ api/1.1.0/_sources/ocw/
api/1.1.0/_sources/ui-backend/ api/1.1.0/_static/ api/1.1.0/...
Modified: websites/staging/climate/trunk/content/api/current/ocw/evaluation.html
==============================================================================
--- websites/staging/climate/trunk/content/api/current/ocw/evaluation.html (original)
+++ websites/staging/climate/trunk/content/api/current/ocw/evaluation.html Mon Apr 24 21:37:01 2017
@@ -6,7 +6,7 @@
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
- <title>Evaluation Module — Apache Open Climate Workbench 1.1.0 documentation</title>
+ <title>Evaluation Module — Apache Open Climate Workbench 1.2.0 documentation</title>
<link rel="stylesheet" href="../_static/alabaster.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
@@ -14,7 +14,7 @@
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../',
- VERSION: '1.1.0',
+ VERSION: '1.2.0',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true
@@ -23,36 +23,20 @@
<script type="text/javascript" src="../_static/jquery.js"></script>
<script type="text/javascript" src="../_static/underscore.js"></script>
<script type="text/javascript" src="../_static/doctools.js"></script>
- <link rel="top" title="Apache Open Climate Workbench 1.1.0 documentation" href="../index.html" />
+ <link rel="index" title="Index" href="../genindex.html" />
+ <link rel="search" title="Search" href="../search.html" />
+ <link rel="top" title="Apache Open Climate Workbench 1.2.0 documentation" href="../index.html" />
<link rel="next" title="Metrics Module" href="metrics.html" />
<link rel="prev" title="Dataset Processor Module" href="dataset_processor.html" />
+ <link rel="stylesheet" href="../_static/custom.css" type="text/css" />
- <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9">
+
+ <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
</head>
<body role="document">
- <div class="related" role="navigation" aria-label="related navigation">
- <h3>Navigation</h3>
- <ul>
- <li class="right" style="margin-right: 10px">
- <a href="../genindex.html" title="General Index"
- accesskey="I">index</a></li>
- <li class="right" >
- <a href="../http-routingtable.html" title="HTTP Routing Table"
- >routing table</a> |</li>
- <li class="right" >
- <a href="../py-modindex.html" title="Python Module Index"
- >modules</a> |</li>
- <li class="right" >
- <a href="metrics.html" title="Metrics Module"
- accesskey="N">next</a> |</li>
- <li class="right" >
- <a href="dataset_processor.html" title="Dataset Processor Module"
- accesskey="P">previous</a> |</li>
- <li class="nav-item nav-item-0"><a href="../index.html">Apache Open Climate Workbench 1.1.0 documentation</a> »</li>
- </ul>
- </div>
+
<div class="document">
<div class="documentwrapper">
@@ -65,13 +49,13 @@
<dt id="evaluation.Evaluation">
<em class="property">class </em><code class="descclassname">evaluation.</code><code class="descname">Evaluation</code><span class="sig-paren">(</span><em>reference</em>, <em>targets</em>, <em>metrics</em>, <em>subregions=None</em><span class="sig-paren">)</span><a class="headerlink" href="#evaluation.Evaluation" title="Permalink to this definition">¶</a></dt>
<dd><p>Container for running an evaluation</p>
-<p>An <em>Evaluation</em> is the running of one or more metrics on one or more
+<p>An <em>Evaluation</em> is the running of one or more metrics on one or more
target datasets and a (possibly optional) reference dataset. Evaluation
can handle two types of metrics, <code class="docutils literal"><span class="pre">unary</span></code> and <code class="docutils literal"><span class="pre">binary</span></code>. The validity
of an Evaluation is dependent upon the number and type of metrics as well
as the number of datasets.</p>
<p>A <code class="docutils literal"><span class="pre">unary</span></code> metric is a metric that runs over a single dataset. If you add
-a <code class="docutils literal"><span class="pre">unary</span></code> metric to the Evaluation you are only required to add a
+a <code class="docutils literal"><span class="pre">unary</span></code> metric to the Evaluation you are only required to add a
reference dataset or a target dataset. If there are multiple datasets
in the evaluation then the <code class="docutils literal"><span class="pre">unary</span></code> metric is run over all of them.</p>
<p>A <code class="docutils literal"><span class="pre">binary</span></code> metric is a metric that runs over a reference dataset and
@@ -87,11 +71,11 @@ Evaluation.</p>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>reference</strong> (<a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – The reference Dataset for the evaluation.</li>
-<li><strong>targets</strong> (<a class="reference external" href="http://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – A list of one or more target datasets for the
+<li><strong>targets</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – A list of one or more target datasets for the
evaluation.</li>
-<li><strong>metrics</strong> (<a class="reference external" href="http://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a>) – A list of one or more Metric instances to run
+<li><strong>metrics</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a>) – A list of one or more Metric instances to run
in the evaluation.</li>
-<li><strong>subregions</strong> (<a class="reference external" href="http://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Bounds" title="dataset.Bounds"><code class="xref py py-class docutils literal"><span class="pre">dataset.Bounds</span></code></a>) – (Optional) Subregion information to use in the
+<li><strong>subregions</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Bounds" title="dataset.Bounds"><code class="xref py py-class docutils literal"><span class="pre">dataset.Bounds</span></code></a>) – (Optional) Subregion information to use in the
evaluation. A subregion is specified with a Bounds object.</li>
</ul>
</td>
@@ -105,7 +89,7 @@ evaluation. A subregion is specified wit
<dt id="evaluation.Evaluation.add_dataset">
<code class="descname">add_dataset</code><span class="sig-paren">(</span><em>target_dataset</em><span class="sig-paren">)</span><a class="headerlink" href="#evaluation.Evaluation.add_dataset" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a Dataset to the Evaluation.</p>
-<p>A target Dataset is compared against the reference dataset when the
+<p>A target Dataset is compared against the reference dataset when the
Evaluation is run with one or more metrics.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
@@ -113,8 +97,7 @@ Evaluation is run with one or more metri
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>target_dataset</strong> (<a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – The target Dataset to add to the Evaluation.</td>
</tr>
-<tr class="field-even field"><th class="field-name" colspan="2">Raises ValueError:</th></tr>
-<tr class="field-even field"><td> </td><td class="field-body">If a dataset to add isn’t an instance of Dataset.</td>
+<tr class="field-even field"><th class="field-name">Raises:</th><td class="field-body"><strong>ValueError</strong> – If a dataset to add isn’t an instance of Dataset.</td>
</tr>
</tbody>
</table>
@@ -128,11 +111,10 @@ Evaluation is run with one or more metri
<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>target_datasets</strong> (<a class="reference external" href="http://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – The list of datasets that should be added to
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>target_datasets</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a>) – The list of datasets that should be added to
the Evaluation.</td>
</tr>
-<tr class="field-even field"><th class="field-name" colspan="2">Raises ValueError:</th></tr>
-<tr class="field-even field"><td> </td><td class="field-body">If a dataset to add isn’t an instance of Dataset.</td>
+<tr class="field-even field"><th class="field-name">Raises:</th><td class="field-body"><strong>ValueError</strong> – If a dataset to add isn’t an instance of Dataset.</td>
</tr>
</tbody>
</table>
@@ -149,8 +131,7 @@ the Evaluation.</td>
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>metric</strong> (<a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a>) – The metric instance to add to the Evaluation.</td>
</tr>
-<tr class="field-even field"><th class="field-name" colspan="2">Raises ValueError:</th></tr>
-<tr class="field-even field"><td> </td><td class="field-body">If the metric to add isn’t a class that inherits
+<tr class="field-even field"><th class="field-name">Raises:</th><td class="field-body"><strong>ValueError</strong> – If the metric to add isn’t a class that inherits
from metrics.Metric.</td>
</tr>
</tbody>
@@ -166,10 +147,9 @@ from metrics.Metric.</td>
<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>metrics</strong> (<a class="reference external" href="http://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a>) – The list of metric instances to add to the Evaluation.</td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>metrics</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#list" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">list</span></code></a> of <a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a>) – The list of metric instances to add to the Evaluation.</td>
</tr>
-<tr class="field-even field"><th class="field-name" colspan="2">Raises ValueError:</th></tr>
-<tr class="field-even field"><td> </td><td class="field-body">If a metric to add isn’t a class that inherits
+<tr class="field-even field"><th class="field-name">Raises:</th><td class="field-body"><strong>ValueError</strong> – If a metric to add isn’t a class that inherits
from metrics.Metric.</td>
</tr>
</tbody>
@@ -242,13 +222,15 @@ evaluations. The shape of unary_results
<div class="sphinxsidebarwrapper">
<p class="logo"><a href="../index.html">
<img class="logo" src="../_static/ocw-logo-variant-sm-01-01-new.png" alt="Logo"/>
- </a></p>
- <h4>Previous topic</h4>
- <p class="topless"><a href="dataset_processor.html"
- title="previous chapter">Dataset Processor Module</a></p>
- <h4>Next topic</h4>
- <p class="topless"><a href="metrics.html"
- title="next chapter">Metrics Module</a></p>
+ </a></p><div class="relations">
+<h3>Related Topics</h3>
+<ul>
+ <li><a href="../index.html">Documentation overview</a><ul>
+ <li>Previous: <a href="dataset_processor.html" title="previous chapter">Dataset Processor Module</a></li>
+ <li>Next: <a href="metrics.html" title="next chapter">Metrics Module</a></li>
+ </ul></li>
+</ul>
+</div>
<div role="note" aria-label="source link">
<h3>This Page</h3>
<ul class="this-page-menu">
@@ -259,14 +241,11 @@ evaluations. The shape of unary_results
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<form class="search" action="../search.html" method="get">
- <input type="text" name="q" />
- <input type="submit" value="Go" />
+ <div><input type="text" name="q" /></div>
+ <div><input type="submit" value="Go" /></div>
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
- <p class="searchtip" style="font-size: 90%">
- Enter search terms or a module, class or function name.
- </p>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
@@ -277,12 +256,12 @@ evaluations. The shape of unary_results
©2016, Apache Software Foundation.
|
- Powered by <a href="http://sphinx-doc.org/">Sphinx 1.3.1</a>
- & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.4</a>
+ Powered by <a href="http://sphinx-doc.org/">Sphinx 1.4.8</a>
+ & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.9</a>
|
<a href="../_sources/ocw/evaluation.txt"
- rel="nofollow">Page source</a></li>
+ rel="nofollow">Page source</a>
</div>
Modified: websites/staging/climate/trunk/content/api/current/ocw/metrics.html
==============================================================================
--- websites/staging/climate/trunk/content/api/current/ocw/metrics.html (original)
+++ websites/staging/climate/trunk/content/api/current/ocw/metrics.html Mon Apr 24 21:37:01 2017
@@ -6,7 +6,7 @@
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
- <title>Metrics Module — Apache Open Climate Workbench 1.1.0 documentation</title>
+ <title>Metrics Module — Apache Open Climate Workbench 1.2.0 documentation</title>
<link rel="stylesheet" href="../_static/alabaster.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
@@ -14,7 +14,7 @@
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../',
- VERSION: '1.1.0',
+ VERSION: '1.2.0',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true
@@ -23,36 +23,20 @@
<script type="text/javascript" src="../_static/jquery.js"></script>
<script type="text/javascript" src="../_static/underscore.js"></script>
<script type="text/javascript" src="../_static/doctools.js"></script>
- <link rel="top" title="Apache Open Climate Workbench 1.1.0 documentation" href="../index.html" />
+ <link rel="index" title="Index" href="../genindex.html" />
+ <link rel="search" title="Search" href="../search.html" />
+ <link rel="top" title="Apache Open Climate Workbench 1.2.0 documentation" href="../index.html" />
<link rel="next" title="Plotter Module" href="plotter.html" />
<link rel="prev" title="Evaluation Module" href="evaluation.html" />
+ <link rel="stylesheet" href="../_static/custom.css" type="text/css" />
- <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9">
+
+ <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
</head>
<body role="document">
- <div class="related" role="navigation" aria-label="related navigation">
- <h3>Navigation</h3>
- <ul>
- <li class="right" style="margin-right: 10px">
- <a href="../genindex.html" title="General Index"
- accesskey="I">index</a></li>
- <li class="right" >
- <a href="../http-routingtable.html" title="HTTP Routing Table"
- >routing table</a> |</li>
- <li class="right" >
- <a href="../py-modindex.html" title="Python Module Index"
- >modules</a> |</li>
- <li class="right" >
- <a href="plotter.html" title="Plotter Module"
- accesskey="N">next</a> |</li>
- <li class="right" >
- <a href="evaluation.html" title="Evaluation Module"
- accesskey="P">previous</a> |</li>
- <li class="nav-item nav-item-0"><a href="../index.html">Apache Open Climate Workbench 1.1.0 documentation</a> »</li>
- </ul>
- </div>
+
<div class="document">
<div class="documentwrapper">
@@ -91,7 +75,7 @@ reference dataset in this metric run.</l
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The difference between the reference and target datasets.</p>
</td>
</tr>
-<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference external" href="http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.11)"><code class="xref py py-class docutils literal"><span class="pre">numpy.ndarray</span></code></a></p>
+<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference external" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.12)"><code class="xref py py-class docutils literal"><span class="pre">numpy.ndarray</span></code></a></p>
</td>
</tr>
</tbody>
@@ -404,9 +388,9 @@ be run.</td>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>target_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array to be evaluated, as model output</li>
-<li><strong>reference_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array of reference dataset</li>
-<li><strong>average_over_time</strong> (<em>‘bool’</em>) – if True, calculated bias is averaged for the axis=0</li>
+<li><strong>target_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to be evaluated, as model output</li>
+<li><strong>reference_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array of reference dataset</li>
+<li><strong>average_over_time</strong> (<em>'bool'</em>) – if True, calculated bias is averaged for the axis=0</li>
</ul>
</td>
</tr>
@@ -429,8 +413,8 @@ be run.</td>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>target_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array to be evaluated, as model output</li>
-<li><strong>reference_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array of reference dataset</li>
+<li><strong>target_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to be evaluated, as model output</li>
+<li><strong>reference_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array of reference dataset</li>
</ul>
</td>
</tr>
@@ -445,6 +429,30 @@ be run.</td>
</dd></dl>
<dl class="function">
+<dt id="metrics.calc_histogram_overlap">
+<code class="descclassname">metrics.</code><code class="descname">calc_histogram_overlap</code><span class="sig-paren">(</span><em>hist1</em>, <em>hist2</em><span class="sig-paren">)</span><a class="headerlink" href="#metrics.calc_histogram_overlap" title="Permalink to this definition">¶</a></dt>
+<dd><p>from Lee et al. (2014)
+:param hist1: a histogram array
+:type hist1: :class:’numpy.ndarray’
+:param hist2: a histogram array with the same size as hist1
+:type hist2: :class:’numpy.ndarray’</p>
+</dd></dl>
+
+<dl class="function">
+<dt id="metrics.calc_joint_histogram">
+<code class="descclassname">metrics.</code><code class="descname">calc_joint_histogram</code><span class="sig-paren">(</span><em>data_array1</em>, <em>data_array2</em>, <em>bins_for_data1</em>, <em>bins_for_data2</em><span class="sig-paren">)</span><a class="headerlink" href="#metrics.calc_joint_histogram" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate a joint histogram of two variables in data_array1 and data_array2
+:param data_array1: the first variable
+:type data_array1: :class:’numpy.ma.core.MaskedArray’
+:param data_array2: the second variable
+:type data_array2: :class:’numpy.ma.core.MaskedArray’
+:param bins_for_data1: histogram bin edges for data_array1
+:type bins_for_data1: :class:’numpy.ndarray’
+:param bins_for_data2: histogram bin edges for data_array2
+:type bins_for_data2: :class:’numpy.ndarray’</p>
+</dd></dl>
+
+<dl class="function">
<dt id="metrics.calc_rmse">
<code class="descclassname">metrics.</code><code class="descname">calc_rmse</code><span class="sig-paren">(</span><em>target_array</em>, <em>reference_array</em><span class="sig-paren">)</span><a class="headerlink" href="#metrics.calc_rmse" title="Permalink to this definition">¶</a></dt>
<dd><p>Calculate ratio of standard deivations of the two arrays</p>
@@ -453,9 +461,9 @@ be run.</td>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>target_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array to be evaluated, as model output</li>
-<li><strong>reference_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array of reference dataset</li>
-<li><strong>average_over_time</strong> (<em>‘bool’</em>) – if True, calculated bias is averaged for the axis=0</li>
+<li><strong>target_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to be evaluated, as model output</li>
+<li><strong>reference_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array of reference dataset</li>
+<li><strong>average_over_time</strong> (<em>'bool'</em>) – if True, calculated bias is averaged for the axis=0</li>
</ul>
</td>
</tr>
@@ -478,8 +486,8 @@ be run.</td>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array to calculate sample standard deviation</li>
-<li><strong>axis</strong> (<em>‘int’</em>) – Axis along which the sample standard deviation is computed.</li>
+<li><strong>array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to calculate sample standard deviation</li>
+<li><strong>axis</strong> (<em>'int'</em>) – Axis along which the sample standard deviation is computed.</li>
</ul>
</td>
</tr>
@@ -502,9 +510,9 @@ be run.</td>
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
-<li><strong>target_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array to be evaluated, as model output</li>
-<li><strong>reference_array</strong> (<em>:class:’numpy.ma.core.MaskedArray’</em>) – an array of reference dataset</li>
-<li><strong>average_over_time</strong> (<em>‘bool’</em>) – if True, calculated bias is averaged for the axis=0</li>
+<li><strong>target_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to be evaluated, as model output</li>
+<li><strong>reference_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array of reference dataset</li>
+<li><strong>average_over_time</strong> (<em>'bool'</em>) – if True, calculated bias is averaged for the axis=0</li>
</ul>
</td>
</tr>
@@ -518,6 +526,26 @@ be run.</td>
</table>
</dd></dl>
+<dl class="function">
+<dt id="metrics.wet_spell_analysis">
+<code class="descclassname">metrics.</code><code class="descname">wet_spell_analysis</code><span class="sig-paren">(</span><em>reference_array</em>, <em>threshold=0.1</em>, <em>nyear=1</em>, <em>dt=3.0</em><span class="sig-paren">)</span><a class="headerlink" href="#metrics.wet_spell_analysis" title="Permalink to this definition">¶</a></dt>
+<dd><p>Characterize wet spells using sub-daily (hourly) data</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"><ul class="first last simple">
+<li><strong>reference_array</strong> (<em>:class:'numpy.ma.core.MaskedArray'</em>) – an array to be analyzed</li>
+<li><strong>threshold</strong> (<em>'float'</em>) – the minimum amount of rainfall [mm/hour]</li>
+<li><strong>nyear</strong> (<em>'int'</em>) – the number of discontinous periods</li>
+<li><strong>dt</strong> (<em>'float'</em>) – the temporal resolution of reference_array</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
</div>
@@ -528,13 +556,15 @@ be run.</td>
<div class="sphinxsidebarwrapper">
<p class="logo"><a href="../index.html">
<img class="logo" src="../_static/ocw-logo-variant-sm-01-01-new.png" alt="Logo"/>
- </a></p>
- <h4>Previous topic</h4>
- <p class="topless"><a href="evaluation.html"
- title="previous chapter">Evaluation Module</a></p>
- <h4>Next topic</h4>
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- title="next chapter">Plotter Module</a></p>
+ </a></p><div class="relations">
+<h3>Related Topics</h3>
+<ul>
+ <li><a href="../index.html">Documentation overview</a><ul>
+ <li>Previous: <a href="evaluation.html" title="previous chapter">Evaluation Module</a></li>
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<h3>This Page</h3>
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@@ -545,14 +575,11 @@ be run.</td>
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<form class="search" action="../search.html" method="get">
- <input type="text" name="q" />
- <input type="submit" value="Go" />
+ <div><input type="text" name="q" /></div>
+ <div><input type="submit" value="Go" /></div>
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
- <p class="searchtip" style="font-size: 90%">
- Enter search terms or a module, class or function name.
- </p>
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<script type="text/javascript">$('#searchbox').show(0);</script>
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@@ -563,12 +590,12 @@ be run.</td>
©2016, Apache Software Foundation.
|
- Powered by <a href="http://sphinx-doc.org/">Sphinx 1.3.1</a>
- & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.4</a>
+ Powered by <a href="http://sphinx-doc.org/">Sphinx 1.4.8</a>
+ & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.9</a>
|
<a href="../_sources/ocw/metrics.txt"
- rel="nofollow">Page source</a></li>
+ rel="nofollow">Page source</a>
</div>
Modified: websites/staging/climate/trunk/content/api/current/ocw/overview.html
==============================================================================
--- websites/staging/climate/trunk/content/api/current/ocw/overview.html (original)
+++ websites/staging/climate/trunk/content/api/current/ocw/overview.html Mon Apr 24 21:37:01 2017
@@ -6,7 +6,7 @@
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
- <title>Overview — Apache Open Climate Workbench 1.1.0 documentation</title>
+ <title>Overview — Apache Open Climate Workbench 1.2.0 documentation</title>
<link rel="stylesheet" href="../_static/alabaster.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
@@ -14,7 +14,7 @@
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../',
- VERSION: '1.1.0',
+ VERSION: '1.2.0',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true
@@ -23,36 +23,20 @@
<script type="text/javascript" src="../_static/jquery.js"></script>
<script type="text/javascript" src="../_static/underscore.js"></script>
<script type="text/javascript" src="../_static/doctools.js"></script>
- <link rel="top" title="Apache Open Climate Workbench 1.1.0 documentation" href="../index.html" />
+ <link rel="index" title="Index" href="../genindex.html" />
+ <link rel="search" title="Search" href="../search.html" />
+ <link rel="top" title="Apache Open Climate Workbench 1.2.0 documentation" href="../index.html" />
<link rel="next" title="Dataset Module" href="dataset.html" />
<link rel="prev" title="Welcome to Apache Open Climate Workbench’s documentation!" href="../index.html" />
+ <link rel="stylesheet" href="../_static/custom.css" type="text/css" />
- <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9">
+
+ <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
</head>
<body role="document">
- <div class="related" role="navigation" aria-label="related navigation">
- <h3>Navigation</h3>
- <ul>
- <li class="right" style="margin-right: 10px">
- <a href="../genindex.html" title="General Index"
- accesskey="I">index</a></li>
- <li class="right" >
- <a href="../http-routingtable.html" title="HTTP Routing Table"
- >routing table</a> |</li>
- <li class="right" >
- <a href="../py-modindex.html" title="Python Module Index"
- >modules</a> |</li>
- <li class="right" >
- <a href="dataset.html" title="Dataset Module"
- accesskey="N">next</a> |</li>
- <li class="right" >
- <a href="../index.html" title="Welcome to Apache Open Climate Workbench’s documentation!"
- accesskey="P">previous</a> |</li>
- <li class="nav-item nav-item-0"><a href="../index.html">Apache Open Climate Workbench 1.1.0 documentation</a> »</li>
- </ul>
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+
<div class="document">
<div class="documentwrapper">
@@ -71,15 +55,15 @@
</ol>
<div class="section" id="common-data-abstraction">
<h2>Common Data Abstraction<a class="headerlink" href="#common-data-abstraction" title="Permalink to this headline">¶</a></h2>
-<p>The OCW <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> class is the primary data abstraction used throughout OCW. It facilitates the uniform handling of data throughout the toolkit and provides a few useful helper functions such as <a class="reference internal" href="dataset.html#dataset.Dataset.spatial_boundaries" title="dataset.Dataset.spatial_boundaries"><code class="xref py py-func docutils literal"><span class="pre">dataset.Dataset.spatial_boundaries()</span></code></a> and <a class="reference internal" href="dataset.html#dataset.Dataset.time_range" title="dataset.Dataset.time_range"><code class="xref py py-func docutils literal"><span class="pre">dataset.Dataset.time_range()</span></code></a>. Creating a new dataset object is straightforward but generally you will want to use an OCW data source to load the data for you.</p>
+<p>The OCW <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> class is the primary data abstraction used throughout OCW. It facilitates the uniform handling of data throughout the toolkit and provides a few useful helper functions such as <a class="reference internal" href="dataset.html#dataset.Dataset.spatial_boundaries" title="dataset.Dataset.spatial_boundaries"><code class="xref py py-func docutils literal"><span class="pre">dataset.Dataset.spatial_boundaries()</span></code></a> and <a class="reference internal" href="dataset.html#dataset.Dataset.temporal_boundaries" title="dataset.Dataset.temporal_boundaries"><code class="xref py py-func docutils literal"><span class="pre">dataset.Dataset.temporal_boundaries()</span></code></a>. Creating a new dataset object is straightforward but generally you will want to use an OCW data source to load the
data for you.</p>
</div>
<div class="section" id="data-sources">
<h2>Data Sources<a class="headerlink" href="#data-sources" title="Permalink to this headline">¶</a></h2>
-<p>OCW data sources allow users to easily load <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> objects from a number of places. These data sources help with step 1 of an evaluation above. In general the primary file format that is supported is NetCDF. For instance, the <a class="reference internal" href="../data_source/data_sources.html#module-local" title="local"><code class="xref py py-mod docutils literal"><span class="pre">local</span></code></a>, <a class="reference internal" href="../data_source/data_sources.html#module-dap" title="dap"><code class="xref py py-mod docutils literal"><span class="pre">dap</span></code></a> and <a class="reference internal" href="../data_source/data_sources.html#module-esgf" title="esgf"><code class="xref py py-mod docutils literal"><span class="pre">esgf</span></code></a> data sources only support loading
NetCDF files from your local machine, an OpenDAP URL, and the ESGF respectively. Some data sources, such as <a class="reference internal" href="../data_source/data_sources.html#module-rcmed" title="rcmed"><code class="xref py py-mod docutils literal"><span class="pre">rcmed</span></code></a>, point to externally supported data sources. In the case of the RCMED data source, the Regional Climate Model Evaluation Database is run by NASA’s Jet Propulsion Laboratory.</p>
+<p>OCW data sources allow users to easily load <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> objects from a number of places. These data sources help with step 1 of an evaluation above. In general the primary file format that is supported is NetCDF. For instance, the <a class="reference internal" href="../data_source/data_sources.html#module-local" title="local"><code class="xref py py-mod docutils literal"><span class="pre">local</span></code></a>, <code class="xref py py-mod docutils literal"><span class="pre">dap</span></code> and <code class="xref py py-mod docutils literal"><span class="pre">esgf</span></code> data sources only support loading NetCDF files from your local machine, an OpenDAP URL, and the ESGF respectively. Some data sources, such as <a class="reference internal" href="../data_source/data_sources.html#module-rcmed" title
="rcmed"><code class="xref py py-mod docutils literal"><span class="pre">rcmed</span></code></a>, point to externally supported data sources. In the case of the RCMED data source, the Regional Climate Model Evaluation Database is run by NASA’s Jet Propulsion Laboratory.</p>
<p>Adding additional data sources is quite simple. The only API limitation that we have on a data source is that it returns a valid <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> object. Please feel free to send patches for adding more data sources.</p>
<p>A simple example using the <a class="reference internal" href="../data_source/data_sources.html#module-local" title="local"><code class="xref py py-mod docutils literal"><span class="pre">local</span></code></a> data source to load a NetCDF file from your local machine:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.data_source.local</span> <span class="kn">as</span> <span class="nn">local</span>
-<span class="gp">>>> </span><span class="n">ds</span> <span class="o">=</span> <span class="n">local</span><span class="o">.</span><span class="n">load_file</span><span class="p">(</span><span class="s">'/tmp/some_dataset.nc'</span><span class="p">,</span> <span class="s">'SomeVarInTheDataset'</span><span class="p">)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.data_source.local</span> <span class="k">as</span> <span class="nn">local</span>
+<span class="gp">>>> </span><span class="n">ds</span> <span class="o">=</span> <span class="n">local</span><span class="o">.</span><span class="n">load_file</span><span class="p">(</span><span class="s1">'/tmp/some_dataset.nc'</span><span class="p">,</span> <span class="s1">'SomeVarInTheDataset'</span><span class="p">)</span>
</pre></div>
</div>
</div>
@@ -87,17 +71,17 @@
<h2>Dataset Manipulations<a class="headerlink" href="#dataset-manipulations" title="Permalink to this headline">¶</a></h2>
<p>All <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> manipulations are handled by the <a class="reference internal" href="dataset_processor.html#module-dataset_processor" title="dataset_processor"><code class="xref py py-mod docutils literal"><span class="pre">dataset_processor</span></code></a> module. In general, an evaluation will include calls to <a class="reference internal" href="dataset_processor.html#dataset_processor.subset" title="dataset_processor.subset"><code class="xref py py-func docutils literal"><span class="pre">dataset_processor.subset()</span></code></a>, <a class="reference internal" href="dataset_processor.html#dataset_processor.spatial_regrid" title="dataset_processor.spatial_regrid"><code class="xref py py-func docutils literal"><span class="pre">dataset_processor.spatial_regrid()</span></code></a>, and <a class="refe
rence internal" href="dataset_processor.html#dataset_processor.temporal_rebin" title="dataset_processor.temporal_rebin"><code class="xref py py-func docutils literal"><span class="pre">dataset_processor.temporal_rebin()</span></code></a> to ensure that the datasets can actually be compared. <a class="reference internal" href="dataset_processor.html#module-dataset_processor" title="dataset_processor"><code class="xref py py-mod docutils literal"><span class="pre">dataset_processor</span></code></a> functions take a <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> object and some various parameters and return a modified <a class="reference internal" href="dataset.html#dataset.Dataset" title="dataset.Dataset"><code class="xref py py-class docutils literal"><span class="pre">dataset.Dataset</span></code></a> object. The original dataset is never ma
nipulated in the process.</p>
<p>Subsetting is a great way to speed up your processing and keep useless data out of your plots. Notice that we’re using a <a class="reference internal" href="dataset.html#dataset.Bounds" title="dataset.Bounds"><code class="xref py py-class docutils literal"><span class="pre">dataset.Bounds</span></code></a> objec to represent the area of interest:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.dataset_processor</span> <span class="kn">as</span> <span class="nn">dsp</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.dataset_processor</span> <span class="k">as</span> <span class="nn">dsp</span>
<span class="gp">>>> </span><span class="n">new_bounds</span> <span class="o">=</span> <span class="n">Bounds</span><span class="p">(</span><span class="n">min_lat</span><span class="p">,</span> <span class="n">max_lat</span><span class="p">,</span> <span class="n">min_lon</span><span class="p">,</span> <span class="n">max_lon</span><span class="p">,</span> <span class="n">start_time</span><span class="p">,</span> <span class="n">end_time</span><span class="p">)</span>
-<span class="gp">>>> </span><span class="n">knmi_dataset</span> <span class="o">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">subset</span><span class="p">(</span><span class="n">new_bounds</span><span class="p">,</span> <span class="n">knmi_dataset</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">knmi_dataset</span> <span class="o">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">subset</span><span class="p">(</span><span class="n">knmi_dataset</span><span class="p">,</span> <span class="n">new_bounds</span><span class="p">)</span>
</pre></div>
</div>
<p>Temporally re-binning a dataset is great when the time step of the data is too fine grain for the desired use. For instance, perhaps we want to see a yearly trend but we have daily data. We would need to make the following call to adjust our dataset:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">knmi_dataset</span> <span class="o">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">temporal_rebin</span><span class="p">(</span><span class="n">knmi_dataset</span><span class="p">,</span> <span class="n">datetime</span><span class="o">.</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="mi">365</span><span class="p">))</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">knmi_dataset</span> <span class="o">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">temporal_rebin</span><span class="p">(</span><span class="n">knmi_dataset</span><span class="p">,</span> <span class="n">datetime</span><span class="o">.</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="mi">365</span><span class="p">))</span>
</pre></div>
</div>
<p>It is critically necessary for our datasets to be on the same lat/lon grid before we try to compare them. That’s where spatial re-gridding comes in helpful. Here we re-grid our example dataset onto a 1-degree lat/lon grid within the range that we subsetted the dataset previously:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">new_lons</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">min_lon</span><span class="p">,</span> <span class="n">max_lon</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">new_lons</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">min_lon</span><span class="p">,</span> <span class="n">max_lon</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">new_lats</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">min_lat</span><span class="p">,</span> <span class="n">max_lat</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">knmi_dataset</span> <span class="o">=</span> <span class="n">dsp</span><span class="o">.</span><span class="n">spatial_regrid</span><span class="p">(</span><span class="n">knmi_dataset</span><span class="p">,</span> <span class="n">new_lats</span><span class="p">,</span> <span class="n">new_lons</span><span class="p">)</span>
</pre></div>
@@ -106,19 +90,19 @@
<div class="section" id="metrics">
<h2>Metrics<a class="headerlink" href="#metrics" title="Permalink to this headline">¶</a></h2>
<p>Metrics are the backbone of an evaluation. You’ll find a number of (hopefully) useful “default” metrics in the <a class="reference internal" href="metrics.html#module-metrics" title="metrics"><code class="xref py py-mod docutils literal"><span class="pre">metrics</span></code></a> module in the toolkit. In general you won’t be too likely to use a metric outside of an evaluation, however you could run a metric manually if you so desired.:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.metrics</span>
-<span class="gp">>>> </span><span class="c"># Load 2 datasets</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.metrics</span>
+<span class="gp">>>> </span><span class="c1"># Load 2 datasets</span>
<span class="gp">>>> </span><span class="n">bias</span> <span class="o">=</span> <span class="n">ocw</span><span class="o">.</span><span class="n">metrics</span><span class="o">.</span><span class="n">Bias</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="k">print</span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">dataset1</span><span class="p">,</span> <span class="n">dataset2</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="nb">print</span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">dataset1</span><span class="p">,</span> <span class="n">dataset2</span><span class="p">)</span>
</pre></div>
</div>
<p>While this might be exactly what you need to get the job done, it is far more likely that you’ll need to run a number of metrics over a number of datasets. That’s where running an evaluation comes in, but we’ll get to that shortly.</p>
<p>There are two “types” of metrics that the toolkit supports. A unary metric acts on a single dataset and returns a result. A binary metric acts on a target and reference dataset and returns a result. This is helpful to know if you decide that the included metrics aren’t sufficient. We’ve attempted to make adding a new metric as simple as possible. You simply create a new class that inherits from either the unary or binary base classes and override the <cite>run</cite> function. At this point your metric will behave exactly like the included metrics in the toolkit. Below is an example of how one of the included metrics is implemented. If you need further assistance with your own metrics be sure to email the project’s mailing list!:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="k">class</span> <span class="nc">Bias</span><span class="p">(</span><span class="n">BinaryMetric</span><span class="p">):</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">class</span> <span class="nc">Bias</span><span class="p">(</span><span class="n">BinaryMetric</span><span class="p">):</span>
<span class="gp">>>> </span> <span class="sd">'''Calculate the bias between a reference and target dataset.'''</span>
<span class="go">>>></span>
<span class="gp">>>> </span> <span class="k">def</span> <span class="nf">run</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target_dataset</span><span class="p">):</span>
-<span class="gp">>>> </span> <span class="s">'''Calculate the bias between a reference and target dataset.</span>
+<span class="gp">>>> </span> <span class="s1">'''Calculate the bias between a reference and target dataset.</span>
<span class="go">>>></span>
<span class="gp">>>> </span> <span class="o">..</span> <span class="n">note</span><span class="p">::</span>
<span class="gp">>>> </span> <span class="n">Overrides</span> <span class="n">BinaryMetric</span><span class="o">.</span><span class="n">run</span><span class="p">()</span>
@@ -131,18 +115,18 @@
<span class="go">>>></span>
<span class="gp">>>> </span> <span class="p">:</span><span class="n">returns</span><span class="p">:</span> <span class="n">The</span> <span class="n">difference</span> <span class="n">between</span> <span class="n">the</span> <span class="n">reference</span> <span class="ow">and</span> <span class="n">target</span> <span class="n">datasets</span><span class="o">.</span>
<span class="gp">>>> </span> <span class="p">:</span><span class="n">rtype</span><span class="p">:</span> <span class="n">Numpy</span> <span class="n">Array</span>
-<span class="gp">>>> </span> <span class="s">'''</span>
-<span class="gp">>>> </span><span class="s"> return ref_dataset.values - target_dataset.values</span>
+<span class="gp">>>> </span> <span class="s1">'''</span>
+<span class="gp">>>> </span><span class="s1"> return ref_dataset.values - target_dataset.values</span>
</pre></div>
</div>
<p>While this might look a bit scary at first, if we take out all the documentation you’ll see that it’s really extremely simple.:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="c"># Our new Bias metric inherits from the Binary Metric base class</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># Our new Bias metric inherits from the Binary Metric base class</span>
<span class="gp">>>> </span><span class="k">class</span> <span class="nc">Bias</span><span class="p">(</span><span class="n">BinaryMetric</span><span class="p">):</span>
-<span class="gp">>>> </span> <span class="c"># Since our new metric is a binary metric we need to override</span>
-<span class="gp">>>> </span> <span class="c"># the run funtion in the BinaryMetric base class.</span>
+<span class="gp">>>> </span> <span class="c1"># Since our new metric is a binary metric we need to override</span>
+<span class="gp">>>> </span> <span class="c1"># the run funtion in the BinaryMetric base class.</span>
<span class="gp">>>> </span> <span class="k">def</span> <span class="nf">run</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target_dataset</span><span class="p">):</span>
-<span class="gp">>>> </span> <span class="c"># To implement the bias metric we simply return the difference</span>
-<span class="gp">>>> </span> <span class="c"># between the reference and target dataset's values arrays.</span>
+<span class="gp">>>> </span> <span class="c1"># To implement the bias metric we simply return the difference</span>
+<span class="gp">>>> </span> <span class="c1"># between the reference and target dataset's values arrays.</span>
<span class="gp">>>> </span> <span class="k">return</span> <span class="n">ref_dataset</span><span class="o">.</span><span class="n">values</span> <span class="o">-</span> <span class="n">target_dataset</span><span class="o">.</span><span class="n">values</span>
</pre></div>
</div>
@@ -151,66 +135,66 @@
<div class="section" id="handling-an-evaluation">
<h2>Handling an Evaluation<a class="headerlink" href="#handling-an-evaluation" title="Permalink to this headline">¶</a></h2>
<p>We saw above that it is easy enough to run a metric over a few datasets manually. However, when we have a lot of datasets and/or a lot of metrics to run that can become tedious and error prone. This is where the <a class="reference internal" href="evaluation.html#evaluation.Evaluation" title="evaluation.Evaluation"><code class="xref py py-class docutils literal"><span class="pre">evaluation.Evaluation</span></code></a> class comes in handy. It ensures that all the metrics that you choose are run over all combinations of the datasets that you input. Consider the following simple example:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.evaluation</span> <span class="kn">as</span> <span class="nn">eval</span>
-<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.data_source.local</span> <span class="kn">as</span> <span class="nn">local</span>
-<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.metrics</span> <span class="kn">as</span> <span class="nn">metrics</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.evaluation</span> <span class="k">as</span> <span class="nn">eval</span>
+<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.data_source.local</span> <span class="k">as</span> <span class="nn">local</span>
+<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">ocw.metrics</span> <span class="k">as</span> <span class="nn">metrics</span>
<span class="go">>>></span>
-<span class="gp">>>> </span><span class="c"># Load a few datasets</span>
+<span class="gp">>>> </span><span class="c1"># Load a few datasets</span>
<span class="gp">>>> </span><span class="n">ref_dataset</span> <span class="o">=</span> <span class="n">local</span><span class="o">.</span><span class="n">load_file</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">target1</span> <span class="o">=</span> <span class="n">local</span><span class="o">.</span><span class="n">load_file</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">target2</span> <span class="o">=</span> <span class="n">local</span><span class="o">.</span><span class="n">load_file</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">target_datasets</span> <span class="o">=</span> <span class="p">[</span><span class="n">target1</span><span class="p">,</span> <span class="n">target2</span><span class="p">]</span>
<span class="go">>>></span>
-<span class="gp">>>> </span><span class="c"># Do some dataset manipulations here such as subsetting and regridding</span>
+<span class="gp">>>> </span><span class="c1"># Do some dataset manipulations here such as subsetting and regridding</span>
<span class="go">>>></span>
-<span class="gp">>>> </span><span class="c"># Load a few metrics</span>
+<span class="gp">>>> </span><span class="c1"># Load a few metrics</span>
<span class="gp">>>> </span><span class="n">bias</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">Bias</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">tstd</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">TemporalStdDev</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">metrics</span> <span class="o">=</span> <span class="p">[</span><span class="n">bias</span><span class="p">,</span> <span class="n">tstd</span><span class="p">]</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="n">new_eval</span> <span class="o">=</span> <span class="nb">eval</span><span class="o">.</span><span class="n">Evaluation</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target_datasets</span><span class="p">,</span> <span class="n">metrics</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">new_eval</span><span class="o">.</span><span class="n">run</span><span class="p">()</span>
-<span class="gp">>>> </span><span class="k">print</span> <span class="n">new_eval</span><span class="o">.</span><span class="n">results</span>
-<span class="gp">>>> </span><span class="k">print</span> <span class="n">new_eval</span><span class="o">.</span><span class="n">unary_results</span>
+<span class="gp">>>> </span><span class="nb">print</span> <span class="n">new_eval</span><span class="o">.</span><span class="n">results</span>
+<span class="gp">>>> </span><span class="nb">print</span> <span class="n">new_eval</span><span class="o">.</span><span class="n">unary_results</span>
</pre></div>
</div>
<p>First we load all of our datasets and do any manipulations (which we leave out for brevity). Then we load the metrics that we want to run, namely Bias and TemporalStdDev. We then load our evaluation object.:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">new_eval</span> <span class="o">=</span> <span class="nb">eval</span><span class="o">.</span><span class="n">Evaluation</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target_datasets</span><span class="p">,</span> <span class="n">metrics</span><span class="p">)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">new_eval</span> <span class="o">=</span> <span class="nb">eval</span><span class="o">.</span><span class="n">Evaluation</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target_datasets</span><span class="p">,</span> <span class="n">metrics</span><span class="p">)</span>
</pre></div>
</div>
<p>Notice two things about this. First, we’re splitting the datasets into a reference dataset (ref_dataset) and a list of target datasets (target_datasets). Second, one of the metrics that we loaded (<a class="reference internal" href="metrics.html#metrics.TemporalStdDev" title="metrics.TemporalStdDev"><code class="xref py py-class docutils literal"><span class="pre">metrics.TemporalStdDev</span></code></a>) is a unary metric. The reference/target dataset split is necessary to handling binary metrics. When an evaluation is run, all the binary metrics are run against every (reference, target) dataset pair. So the above evaluation could be replaced with the following calls. Of course this wouldn’t handle the unary metric, but we’ll get to that in a second.:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">result1</span> <span class="o">=</span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target1</span><span class="p">)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">result1</span> <span class="o">=</span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">result2</span> <span class="o">=</span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target2</span><span class="p">)</span>
</pre></div>
</div>
<p>Unary metrics are handled slightly differently but they’re still simple. Each unary metric passed into the evaluation is run against <em>every</em> dataset in the evaluation. So we could replace the above evaluation with the following calls:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">unary_result1</span> <span class="o">=</span> <span class="n">tstd</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">unary_result1</span> <span class="o">=</span> <span class="n">tstd</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">unary_result2</span> <span class="o">=</span> <span class="n">tstd</span><span class="p">(</span><span class="n">target1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">unary_result3</span> <span class="o">=</span> <span class="n">tstd</span><span class="p">(</span><span class="n">target2</span><span class="p">)</span>
</pre></div>
</div>
<p>The only other part that we need to explore to fully understand the <code class="xref py py-class docutils literal"><span class="pre">evalution.Evaluation</span></code> class is how the results are stored internally from the run. The <cite>results</cite> list is a multidimensional array holding all the binary metric results and the <cite>unary_results</cite> is a list holding all the unary metric results. To more accurately replace the above evaluation with manual calls we would write the following:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">results</span> <span class="o">=</span> <span class="p">[</span>
-<span class="gp">>>> </span> <span class="c"># Results for target1</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">results</span> <span class="o">=</span> <span class="p">[</span>
+<span class="gp">>>> </span> <span class="c1"># Results for target1</span>
<span class="gp">>>> </span> <span class="p">[</span>
<span class="gp">>>> </span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target1</span><span class="p">)</span>
-<span class="gp">>>> </span> <span class="c"># If there were other binary metrics, the results would be here.</span>
+<span class="gp">>>> </span> <span class="c1"># If there were other binary metrics, the results would be here.</span>
<span class="gp">>>> </span> <span class="p">],</span>
-<span class="gp">>>> </span> <span class="c"># Results for target2</span>
+<span class="gp">>>> </span> <span class="c1"># Results for target2</span>
<span class="gp">>>> </span> <span class="p">[</span>
<span class="gp">>>> </span> <span class="n">bias</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">,</span> <span class="n">target2</span><span class="p">)</span>
-<span class="gp">>>> </span> <span class="c"># If there were other binary metrics, the results would be here.</span>
+<span class="gp">>>> </span> <span class="c1"># If there were other binary metrics, the results would be here.</span>
<span class="gp">>>> </span> <span class="p">]</span>
<span class="gp">>>> </span><span class="p">]</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="n">unary_results</span> <span class="o">=</span> <span class="p">[</span>
-<span class="gp">>>> </span> <span class="c"># Results for TemporalStdDev</span>
+<span class="gp">>>> </span> <span class="c1"># Results for TemporalStdDev</span>
<span class="gp">>>> </span> <span class="p">[</span>
<span class="gp">>>> </span> <span class="n">tstd</span><span class="p">(</span><span class="n">ref_dataset</span><span class="p">),</span>
<span class="gp">>>> </span> <span class="n">tstd</span><span class="p">(</span><span class="n">target1</span><span class="p">),</span>
<span class="gp">>>> </span> <span class="n">tstd</span><span class="p">(</span><span class="n">target2</span><span class="p">)</span>
<span class="gp">>>> </span> <span class="p">]</span>
-<span class="gp">>>> </span> <span class="c"># If there were other unary metrics, the results would be in a list here.</span>
+<span class="gp">>>> </span> <span class="c1"># If there were other unary metrics, the results would be in a list here.</span>
<span class="gp">>>> </span><span class="p">]</span>
</pre></div>
</div>
@@ -218,13 +202,13 @@
<div class="section" id="plotting">
<h2>Plotting<a class="headerlink" href="#plotting" title="Permalink to this headline">¶</a></h2>
<p>Plotting can be fairly complicated business. Luckily we have <a class="reference external" href="https://cwiki.apache.org/confluence/display/CLIMATE/Guide+to+Plotting+API">pretty good documentation</a> on the project wiki that can help you out. There are also fairly simple examples in the project’s example folder with the remainder of the code such as the following:</p>
-<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="c"># Let's grab the values returned for bias.run(ref_dataset, target1)</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="c1"># Let's grab the values returned for bias.run(ref_dataset, target1)</span>
<span class="gp">>>> </span><span class="n">results</span> <span class="o">=</span> <span class="n">bias_evaluation</span><span class="o">.</span><span class="n">results</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="go">>>></span>
-<span class="gp">>>> </span><span class="n">Here</span><span class="s">'s the same lat/lons we used earlier when we were re-gridding</span>
+<span class="gp">>>> </span><span class="n">Here</span><span class="s1">'s the same lat/lons we used earlier when we were re-gridding</span>
<span class="gp">>>> </span><span class="n">lats</span> <span class="o">=</span> <span class="n">new_lats</span>
<span class="gp">>>> </span><span class="n">lons</span> <span class="o">=</span> <span class="n">new_lons</span>
-<span class="gp">>>> </span><span class="n">fname</span> <span class="o">=</span> <span class="s">'My_Test_Plot'</span>
+<span class="gp">>>> </span><span class="n">fname</span> <span class="o">=</span> <span class="s1">'My_Test_Plot'</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="n">plotter</span><span class="o">.</span><span class="n">draw_contour_map</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="n">lats</span><span class="p">,</span> <span class="n">lons</span><span class="p">,</span> <span class="n">fname</span><span class="p">)</span>
</pre></div>
@@ -254,13 +238,15 @@
</ul>
</li>
</ul>
-
- <h4>Previous topic</h4>
- <p class="topless"><a href="../index.html"
- title="previous chapter">Welcome to Apache Open Climate Workbench’s documentation!</a></p>
- <h4>Next topic</h4>
- <p class="topless"><a href="dataset.html"
- title="next chapter">Dataset Module</a></p>
+<div class="relations">
+<h3>Related Topics</h3>
+<ul>
+ <li><a href="../index.html">Documentation overview</a><ul>
+ <li>Previous: <a href="../index.html" title="previous chapter">Welcome to Apache Open Climate Workbench’s documentation!</a></li>
+ <li>Next: <a href="dataset.html" title="next chapter">Dataset Module</a></li>
+ </ul></li>
+</ul>
+</div>
<div role="note" aria-label="source link">
<h3>This Page</h3>
<ul class="this-page-menu">
@@ -271,14 +257,11 @@
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<form class="search" action="../search.html" method="get">
- <input type="text" name="q" />
- <input type="submit" value="Go" />
+ <div><input type="text" name="q" /></div>
+ <div><input type="submit" value="Go" /></div>
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
- <p class="searchtip" style="font-size: 90%">
- Enter search terms or a module, class or function name.
- </p>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
@@ -289,12 +272,12 @@
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- & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.4</a>
+ Powered by <a href="http://sphinx-doc.org/">Sphinx 1.4.8</a>
+ & <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.9</a>
|
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- rel="nofollow">Page source</a></li>
+ rel="nofollow">Page source</a>
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