:orphan:

Demo scripts
============



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    <div class="sphx-glr-thumbnails">

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Online Bayesian linear regression
=================================



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    <div class="sphx-glr-thumbcontainer" tooltip="The code below uses an online algorithm to estimate the linear receptive field of a simple cell recorded from an anesthetized cat, as described in &quot;Touryan, Jon and Felsen, Gidon and Dan, Yang (2005). Spatial structure of complex cell receptive fields measured with natural images. Neuron 45 (5), 781-791.&quot;">

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  .. image:: /auto_examples/onlineBayesianLinearRegression/images/thumb/sphx_glr_plotOnlineBayesianLinearRegressionSimpleCell_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_onlineBayesianLinearRegression_plotOnlineBayesianLinearRegressionSimpleCell.py`

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      <div class="sphx-glr-thumbnail-title">Anesthetized cat V1 simple cell</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The code below uses an online algorithm to estimate the posterior of the weighs of a linear regression model using simulate data.">

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  .. image:: /auto_examples/onlineBayesianLinearRegression/images/thumb/sphx_glr_plotOnlineBayesianLinearRegressionSimulatedData_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_onlineBayesianLinearRegression_plotOnlineBayesianLinearRegressionSimulatedData.py`

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      <div class="sphx-glr-thumbnail-title">Simulated data</div>
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Tracking
========



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    <div class="sphx-glr-thumbcontainer" tooltip="The code below samples from a Discrete Wiener Process Acceleration (DWPA) model.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotSimulatedTrajectoryDWPA_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotSimulatedTrajectoryDWPA.py`

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      <div class="sphx-glr-thumbnail-title">Sampling from a Discrete Wiener Process Acceleration Model</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="The code below performs online Kalman filtering of a trajectory of the mouse shown on the left image below, as it forages in the arena shown on the right image below. Click on the images to see their larger versions.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotOnlineFilterFWGMouseTrajectory_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotOnlineFilterFWGMouseTrajectory.py`

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      <div class="sphx-glr-thumbnail-title">Online filtering of a foraging mouse trajectory</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The code below performs online Kalman filtering of a simulated mouse trajectory.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotBatchFilterSimulatedTrajectoryDWPA_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotBatchFilterSimulatedTrajectoryDWPA.py`

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      <div class="sphx-glr-thumbnail-title">Offline filtering of a simulated mouse trajectory</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="The code below performs online Kalman smoothing of a simulated mouse trajectory.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotBatchSmoothSimulatedTrajectoryDWPA_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotBatchSmoothSimulatedTrajectoryDWPA.py`

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      <div class="sphx-glr-thumbnail-title">Offline smoothing of a simulated mouse trajectory</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="The code below compares the expectation maximization (EM) and gradient ascent algorithm for tracking a simulated mouse.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotEMvsGAcomparisonSimulated_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotEMvsGAcomparisonSimulated.py`

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      <div class="sphx-glr-thumbnail-title">Comparison between EM and gradient ascent for tracking a simulated mouse</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="The code below compares the expectation maximization (EM) and gradient ascent algorithm for tracking a foraging mouse.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotEMvsGAcomparisonForagingMouse_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotEMvsGAcomparisonForagingMouse.py`

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      <div class="sphx-glr-thumbnail-title">Comparison between EM and gradient ascent for tracking a foraging mouse</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The code below performs Kalman filtering and smoothing of a trajectory of the mouse shown on the left image below, as it forages in the arena shown on the right image below, with manual and learned parameters. Click on the images to see their larger versions.">

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  .. image:: /auto_examples/tracking/images/thumb/sphx_glr_plotFilterFWGMouseTrajectoryManualVsLearnedParams_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_tracking_plotFilterFWGMouseTrajectoryManualVsLearnedParams.py`

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      <div class="sphx-glr-thumbnail-title">Filtering of a foraging mouse trajectory with manual vs learned parameters</div>
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.. toctree::
   :hidden:
   :includehidden:


   /auto_examples/onlineBayesianLinearRegression/index.rst
   /auto_examples/tracking/index.rst


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  .. container:: sphx-glr-footer sphx-glr-footer-gallery

    .. 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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 .. rst-class:: sphx-glr-signature

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