.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/parameters/temporal_parameters.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_parameters_temporal_parameters.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_parameters_temporal_parameters.py:


.. _example_temporal_parameters:

Temporal parameters calculation
===============================

This example illustrates how temporal parameters can be calculated for each stride  by
the :class:`~gaitmap.parameters.TemporalParameterCalculation`.

.. GENERATED FROM PYTHON SOURCE LINES 12-16

Getting stride list
--------------------------

For this we need stride event list that can be obtained from event detection method.

.. GENERATED FROM PYTHON SOURCE LINES 16-21

.. code-block:: default

    from gaitmap.example_data import get_healthy_example_stride_events
    from gaitmap.parameters import TemporalParameterCalculation

    stride_list = get_healthy_example_stride_events()








.. GENERATED FROM PYTHON SOURCE LINES 22-26

Creating TemporalParameterCalculation object
--------------------------------------------
We need this object for calculating the temporal parameters.
Temporal parameters are calculated based on ic and tc events

.. GENERATED FROM PYTHON SOURCE LINES 26-30

.. code-block:: default


    p = TemporalParameterCalculation()
    p = p.calculate(stride_event_list=stride_list, sampling_rate_hz=204.8)








.. GENERATED FROM PYTHON SOURCE LINES 31-36

Inspecting the results
----------------------
The main output is the `parameters_`, which contains the temporal parameters for each stride in format of data frame
in case of single sensor or dictionary of data frames for multiple sensors.
As our passed stride_list here consists of two sensors, the output will be a dictionary.

.. GENERATED FROM PYTHON SOURCE LINES 36-38

.. code-block:: default

    p.parameters_["left_sensor"]






.. raw:: html

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    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>stride_time</th>
          <th>swing_time</th>
          <th>stance_time</th>
        </tr>
        <tr>
          <th>s_id</th>
          <th></th>
          <th></th>
          <th></th>
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          <th>8</th>
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          <td>0.732422</td>
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        <tr>
          <th>9</th>
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        <tr>
          <th>10</th>
          <td>1.103516</td>
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          <td>0.751953</td>
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        <tr>
          <th>11</th>
          <td>1.098633</td>
          <td>0.361328</td>
          <td>0.737305</td>
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        <tr>
          <th>12</th>
          <td>1.152344</td>
          <td>0.371094</td>
          <td>0.781250</td>
        </tr>
        <tr>
          <th>13</th>
          <td>2.275391</td>
          <td>1.499023</td>
          <td>0.776367</td>
        </tr>
        <tr>
          <th>14</th>
          <td>1.162109</td>
          <td>0.380859</td>
          <td>0.781250</td>
        </tr>
        <tr>
          <th>15</th>
          <td>1.098633</td>
          <td>0.356445</td>
          <td>0.742188</td>
        </tr>
        <tr>
          <th>16</th>
          <td>1.069336</td>
          <td>0.356445</td>
          <td>0.712891</td>
        </tr>
        <tr>
          <th>17</th>
          <td>1.083984</td>
          <td>0.361328</td>
          <td>0.722656</td>
        </tr>
        <tr>
          <th>18</th>
          <td>1.059570</td>
          <td>0.351562</td>
          <td>0.708008</td>
        </tr>
        <tr>
          <th>19</th>
          <td>1.079102</td>
          <td>0.351562</td>
          <td>0.727539</td>
        </tr>
        <tr>
          <th>20</th>
          <td>1.088867</td>
          <td>0.351562</td>
          <td>0.737305</td>
        </tr>
        <tr>
          <th>21</th>
          <td>1.088867</td>
          <td>0.346680</td>
          <td>0.742188</td>
        </tr>
        <tr>
          <th>22</th>
          <td>1.103516</td>
          <td>0.361328</td>
          <td>0.742188</td>
        </tr>
        <tr>
          <th>23</th>
          <td>1.108398</td>
          <td>0.380859</td>
          <td>0.727539</td>
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          <th>24</th>
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          <th>25</th>
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          <th>26</th>
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          <th>27</th>
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          <td>0.761719</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 39-40

`parameters_pretty_` is another version of `parameters_` but using human readable column names that indicate units.

.. GENERATED FROM PYTHON SOURCE LINES 40-41

.. code-block:: default

    p.parameters_pretty_["left_sensor"]





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
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          <th>stance time [s]</th>
        </tr>
        <tr>
          <th>stride id</th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
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        <tr>
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.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.603 seconds)

**Estimated memory usage:**  9 MB


.. _sphx_glr_download_auto_examples_parameters_temporal_parameters.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


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

      :download:`Download Python source code: temporal_parameters.py <temporal_parameters.py>`

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

      :download:`Download Jupyter notebook: temporal_parameters.ipynb <temporal_parameters.ipynb>`


.. only:: html

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

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