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==================
Examples
==================

Here you can find some examples of how to use the library.


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1 | Single-Set Analysis
=======================



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    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates Extended EOF (EEOF) analysis on xarray tutorial data. EEOF analysis, ...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_eeof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_eeof.py`

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      <div class="sphx-glr-thumbnail-title">Extented EOF analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="EOF analysis in T-mode maximises the spatial variance.">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_eof-tmode_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_eof-tmode.py`

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      <div class="sphx-glr-thumbnail-title">EOF analysis (T-mode)</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="We demonstrate how to execute a Complex EOF (or Hilbert EOF) analysis [1]_ [2]_ [3]_. This meth...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_complex_eof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_complex_eof.py`

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      <div class="sphx-glr-thumbnail-title">Complex/Hilbert EOF analysis</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="EOF analysis in S-mode maximises the temporal variance.">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_eof-smode_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_eof-smode.py`

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      <div class="sphx-glr-thumbnail-title">EOF analysis (S-mode)</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This tutorial illustrates the application of Extended EOF (EEOF) analysis to isolate and remove...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_eeof_trend_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_eeof_trend.py`

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      <div class="sphx-glr-thumbnail-title">Removing nonlinear trends with EEOF analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Multivariate EOF analysis.">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_multivariate-eof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_multivariate-eof.py`

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      <div class="sphx-glr-thumbnail-title">Multivariate EOF analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Multivariate EOF analysis with additional Varimax rotation.">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_mreof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_mreof.py`

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      <div class="sphx-glr-thumbnail-title">Varimax-rotated Multivariate EOF analysis</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="EOF (Empirical Orthogonal Function) analysis is commonly used in climate science, interpreting ...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_rotated_eof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_rotated_eof.py`

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      <div class="sphx-glr-thumbnail-title">Rotated EOF analysis</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Weighted EOF analysis (in S-mode) maximises the temporal variance considering each gridpoint wi...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_weighted-eof_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_weighted-eof.py`

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      <div class="sphx-glr-thumbnail-title">Weighted EOF analysis</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="TIn this demonstration, we&#x27;ll apply GWPCA to a dataset detailing the chemical compositions of s...">

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  .. image:: /auto_examples/1single/images/thumb/sphx_glr_plot_gwpca_thumb.png
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  :ref:`sphx_glr_auto_examples_1single_plot_gwpca.py`

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      <div class="sphx-glr-thumbnail-title">Geographically weighted PCA</div>
    </div>


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    </div>

2 | Multi-Set Analysis
========================



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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, we&#x27;re going to perform a Canonical Correlation Analysis (CCA) on three dataset...">

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  .. image:: /auto_examples/2multi/images/thumb/sphx_glr_plot_cca_thumb.png
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  :ref:`sphx_glr_auto_examples_2multi_plot_cca.py`

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      <div class="sphx-glr-thumbnail-title">Canonical Correlation Analysis</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Maximum Covariance Analysis (MCA) between two data sets.">

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  .. image:: /auto_examples/2multi/images/thumb/sphx_glr_plot_mca_thumb.png
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  :ref:`sphx_glr_auto_examples_2multi_plot_mca.py`

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      <div class="sphx-glr-thumbnail-title">Maximum Covariance Analysis</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Rotated Maximum Covariance Analysis (MCA) between two data sets.">

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  .. image:: /auto_examples/2multi/images/thumb/sphx_glr_plot_rotated_mca_thumb.png
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  :ref:`sphx_glr_auto_examples_2multi_plot_rotated_mca.py`

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      <div class="sphx-glr-thumbnail-title">Rotated Maximum Covariance Analysis</div>
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    </div>

3 | Validation
===============


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    <div class="sphx-glr-thumbcontainer" tooltip="Test the significance of individual modes and obtain confidence intervals for both EOFs and PCs...">

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  .. image:: /auto_examples/3validation/images/thumb/sphx_glr_plot_bootstrap_thumb.png
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  :ref:`sphx_glr_auto_examples_3validation_plot_bootstrap.py`

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      <div class="sphx-glr-thumbnail-title">Significance testing of EOF analysis via bootstrap</div>
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.. toctree::
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   :includehidden:


   /auto_examples/1single/index.rst
   /auto_examples/2multi/index.rst
   /auto_examples/3validation/index.rst


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    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download all examples in Python source code: auto_examples_python.zip </auto_examples/auto_examples_python.zip>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download all examples in Jupyter notebooks: auto_examples_jupyter.zip </auto_examples/auto_examples_jupyter.zip>`


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    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_