.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/parameters/spatial_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_spatial_parameters.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_parameters_spatial_parameters.py:


.. _example_spatial_parameters:

Spatial parameters calculation
==============================

This example illustrates illustrates how spatial parameters can be calculated for each stride  by
the :class:`~gaitmap.parameters.SpatialParameterCalculation`.
The used implementation is based on the work of Kanzler et al [1]_ and Rampp et al [2]_.

.. [1] Kanzler, C. M., Barth, J., Rampp, A., Schlarb, H., Rott, F., Klucken, J., Eskofier, B. M. (2015, August).
       Inertial sensor based and shoe size independent gait analysis including heel and toe clearance estimation.
       In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
       (pp. 5424-5427). IEEE.
.. [2] Rampp, A., Barth, J., Schülein, S., Gaßmann, K. G., Klucken, J., & Eskofier, B. M. (2014).
       Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients.
       IEEE transactions on biomedical engineering, 62(4), 1089-1097.

.. GENERATED FROM PYTHON SOURCE LINES 21-26

Getting input data
------------------

For this we need stride event list obtained from event detection method, position and orientation list
obtained from trajectory reconstruction.

.. GENERATED FROM PYTHON SOURCE LINES 26-37

.. code-block:: default

    from gaitmap.example_data import (
        get_healthy_example_orientation,
        get_healthy_example_position,
        get_healthy_example_stride_events,
    )
    from gaitmap.parameters import SpatialParameterCalculation

    stride_list = get_healthy_example_stride_events()
    positions = get_healthy_example_position()
    orientations = get_healthy_example_orientation()








.. GENERATED FROM PYTHON SOURCE LINES 38-43

Preparing the data
------------------
Orientation and position are sampled at 100 Hz as they are derived from mocap data.
The stride list is aligned with the IMU samples (204.8 Hz).
Therefore, we need to convert the sampling rate for the stride list to be compatible with position and orientation.

.. GENERATED FROM PYTHON SOURCE LINES 43-50

.. code-block:: default


    converted_stride_list = {}
    for sensor, strides in stride_list.items():
        converted_stride_list[sensor] = strides.set_index("s_id").mul(100 / 204.8).round().astype("Int64")

    stride_list = converted_stride_list








.. GENERATED FROM PYTHON SOURCE LINES 51-54

Creating SpatialParameterCalculation object
-------------------------------------------
We need this object for calculating the spatial parameters.

.. GENERATED FROM PYTHON SOURCE LINES 54-58

.. code-block:: default


    p = SpatialParameterCalculation()
    p = p.calculate(stride_event_list=stride_list, positions=positions, orientations=orientations, sampling_rate_hz=100)








.. GENERATED FROM PYTHON SOURCE LINES 59-64

Inspecting the results
----------------------
The main output is the `parameters_`, which contains the spatial 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 64-66

.. code-block:: default

    p.parameters_["left_sensor"]






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>arc_length</th>
          <th>gait_velocity</th>
          <th>ic_angle</th>
          <th>max_lateral_excursion</th>
          <th>max_orientation_change</th>
          <th>max_sensor_lift</th>
          <th>stride_length</th>
          <th>tc_angle</th>
          <th>turning_angle</th>
        </tr>
        <tr>
          <th>s_id</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1.551336</td>
          <td>1.304694</td>
          <td>31.341649</td>
          <td>0.037907</td>
          <td>90.273736</td>
          <td>0.230113</td>
          <td>1.396022</td>
          <td>-57.449568</td>
          <td>-0.847536</td>
        </tr>
        <tr>
          <th>1</th>
          <td>1.557407</td>
          <td>1.306463</td>
          <td>30.217489</td>
          <td>0.052585</td>
          <td>90.508119</td>
          <td>0.230177</td>
          <td>1.397916</td>
          <td>-57.779914</td>
          <td>2.431839</td>
        </tr>
        <tr>
          <th>2</th>
          <td>1.581696</td>
          <td>1.327713</td>
          <td>33.364893</td>
          <td>0.038355</td>
          <td>93.115220</td>
          <td>0.227605</td>
          <td>1.420653</td>
          <td>-57.884926</td>
          <td>-1.068458</td>
        </tr>
        <tr>
          <th>3</th>
          <td>1.581874</td>
          <td>1.322211</td>
          <td>32.826192</td>
          <td>0.052619</td>
          <td>94.994063</td>
          <td>0.231756</td>
          <td>1.414765</td>
          <td>-60.605447</td>
          <td>1.418711</td>
        </tr>
        <tr>
          <th>4</th>
          <td>1.588506</td>
          <td>1.35719</td>
          <td>31.644281</td>
          <td>0.053196</td>
          <td>88.928298</td>
          <td>0.228316</td>
          <td>1.425050</td>
          <td>-52.730850</td>
          <td>-0.696435</td>
        </tr>
        <tr>
          <th>5</th>
          <td>1.601673</td>
          <td>1.369327</td>
          <td>32.093232</td>
          <td>0.045197</td>
          <td>90.860257</td>
          <td>0.231185</td>
          <td>1.437793</td>
          <td>-56.677996</td>
          <td>1.148086</td>
        </tr>
        <tr>
          <th>6</th>
          <td>1.603018</td>
          <td>1.377332</td>
          <td>31.653487</td>
          <td>0.047548</td>
          <td>90.547222</td>
          <td>0.233719</td>
          <td>1.446199</td>
          <td>-55.699391</td>
          <td>-0.751054</td>
        </tr>
        <tr>
          <th>7</th>
          <td>1.613106</td>
          <td>1.349747</td>
          <td>33.056158</td>
          <td>0.066245</td>
          <td>89.254958</td>
          <td>0.233695</td>
          <td>1.444230</td>
          <td>-55.125864</td>
          <td>2.367373</td>
        </tr>
        <tr>
          <th>8</th>
          <td>1.582760</td>
          <td>1.31039</td>
          <td>30.680655</td>
          <td>0.038741</td>
          <td>90.028285</td>
          <td>0.232082</td>
          <td>1.415221</td>
          <td>-51.563416</td>
          <td>0.118047</td>
        </tr>
        <tr>
          <th>9</th>
          <td>1.537512</td>
          <td>1.276349</td>
          <td>32.483550</td>
          <td>0.042677</td>
          <td>89.327811</td>
          <td>0.227329</td>
          <td>1.378457</td>
          <td>-55.372066</td>
          <td>-1.148422</td>
        </tr>
        <tr>
          <th>10</th>
          <td>1.484822</td>
          <td>1.207296</td>
          <td>31.927522</td>
          <td>0.026986</td>
          <td>88.742457</td>
          <td>0.221525</td>
          <td>1.328025</td>
          <td>-56.814935</td>
          <td>-4.841572</td>
        </tr>
        <tr>
          <th>11</th>
          <td>1.488537</td>
          <td>1.198343</td>
          <td>31.833930</td>
          <td>0.047310</td>
          <td>85.481615</td>
          <td>0.221396</td>
          <td>1.318177</td>
          <td>-50.893184</td>
          <td>-0.330903</td>
        </tr>
        <tr>
          <th>12</th>
          <td>1.478344</td>
          <td>1.12722</td>
          <td>32.054301</td>
          <td>0.052482</td>
          <td>84.449672</td>
          <td>0.223780</td>
          <td>1.296303</td>
          <td>-44.846466</td>
          <td>-1.154617</td>
        </tr>
        <tr>
          <th>13</th>
          <td>1.697819</td>
          <td>0.205299</td>
          <td>-26.177910</td>
          <td>0.602695</td>
          <td>45.951556</td>
          <td>0.150593</td>
          <td>0.468082</td>
          <td>-25.935349</td>
          <td>-166.322326</td>
        </tr>
        <tr>
          <th>14</th>
          <td>1.541493</td>
          <td>1.192787</td>
          <td>-31.241248</td>
          <td>0.014819</td>
          <td>95.155874</td>
          <td>0.229849</td>
          <td>1.383633</td>
          <td>59.688229</td>
          <td>-11.755454</td>
        </tr>
        <tr>
          <th>15</th>
          <td>1.546868</td>
          <td>1.255387</td>
          <td>-32.130055</td>
          <td>0.049132</td>
          <td>88.663217</td>
          <td>0.221836</td>
          <td>1.380925</td>
          <td>48.587683</td>
          <td>-3.250563</td>
        </tr>
        <tr>
          <th>16</th>
          <td>1.562865</td>
          <td>1.312509</td>
          <td>-32.943188</td>
          <td>0.016744</td>
          <td>92.130044</td>
          <td>0.221109</td>
          <td>1.404385</td>
          <td>51.039403</td>
          <td>4.254341</td>
        </tr>
        <tr>
          <th>17</th>
          <td>1.609458</td>
          <td>1.330787</td>
          <td>-32.892909</td>
          <td>0.059461</td>
          <td>90.338997</td>
          <td>0.231328</td>
          <td>1.437250</td>
          <td>51.148763</td>
          <td>3.190712</td>
        </tr>
        <tr>
          <th>18</th>
          <td>1.573855</td>
          <td>1.324743</td>
          <td>-33.098392</td>
          <td>0.013983</td>
          <td>92.811379</td>
          <td>0.226108</td>
          <td>1.404228</td>
          <td>57.248321</td>
          <td>-1.209358</td>
        </tr>
        <tr>
          <th>19</th>
          <td>1.572994</td>
          <td>1.302716</td>
          <td>-33.639738</td>
          <td>0.033045</td>
          <td>90.556265</td>
          <td>0.222304</td>
          <td>1.406933</td>
          <td>56.007658</td>
          <td>-0.000964</td>
        </tr>
        <tr>
          <th>20</th>
          <td>1.511498</td>
          <td>1.228517</td>
          <td>-32.214021</td>
          <td>0.036579</td>
          <td>90.045474</td>
          <td>0.220584</td>
          <td>1.339083</td>
          <td>54.792416</td>
          <td>-0.255400</td>
        </tr>
        <tr>
          <th>21</th>
          <td>1.539912</td>
          <td>1.25378</td>
          <td>-33.367350</td>
          <td>0.039426</td>
          <td>92.697716</td>
          <td>0.220686</td>
          <td>1.366620</td>
          <td>54.989109</td>
          <td>-1.828305</td>
        </tr>
        <tr>
          <th>22</th>
          <td>1.502812</td>
          <td>1.212846</td>
          <td>-30.780993</td>
          <td>0.036905</td>
          <td>87.325563</td>
          <td>0.228289</td>
          <td>1.334131</td>
          <td>50.147141</td>
          <td>0.409310</td>
        </tr>
        <tr>
          <th>23</th>
          <td>1.504343</td>
          <td>1.206246</td>
          <td>-31.148819</td>
          <td>0.025703</td>
          <td>88.297088</td>
          <td>0.225588</td>
          <td>1.338933</td>
          <td>53.209872</td>
          <td>2.333753</td>
        </tr>
        <tr>
          <th>24</th>
          <td>1.512405</td>
          <td>1.21277</td>
          <td>-31.993676</td>
          <td>0.039298</td>
          <td>89.074205</td>
          <td>0.220820</td>
          <td>1.346174</td>
          <td>55.071943</td>
          <td>-1.863167</td>
        </tr>
        <tr>
          <th>25</th>
          <td>1.502292</td>
          <td>1.193141</td>
          <td>-32.192790</td>
          <td>0.051573</td>
          <td>88.076743</td>
          <td>0.222772</td>
          <td>1.336317</td>
          <td>48.825681</td>
          <td>1.659710</td>
        </tr>
        <tr>
          <th>26</th>
          <td>1.456642</td>
          <td>1.149952</td>
          <td>-31.964229</td>
          <td>0.028782</td>
          <td>87.303691</td>
          <td>0.220247</td>
          <td>1.299446</td>
          <td>54.532540</td>
          <td>-2.987568</td>
        </tr>
        <tr>
          <th>27</th>
          <td>1.316825</td>
          <td>1.028979</td>
          <td>-30.933646</td>
          <td>0.041233</td>
          <td>79.972601</td>
          <td>0.211285</td>
          <td>1.162746</td>
          <td>42.210693</td>
          <td>-10.672308</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 67-68

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

.. GENERATED FROM PYTHON SOURCE LINES 68-69

.. 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 {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>arc length [m]</th>
          <th>gait velocity [m/s]</th>
          <th>ic angle [deg]</th>
          <th>max. lateral excursion [m]</th>
          <th>max. orientation change [deg]</th>
          <th>max. sensor lift [m]</th>
          <th>stride length [m]</th>
          <th>tc angle [deg]</th>
          <th>turning angle [deg]</th>
        </tr>
        <tr>
          <th>stride id</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1.551336</td>
          <td>1.304694</td>
          <td>31.341649</td>
          <td>0.037907</td>
          <td>90.273736</td>
          <td>0.230113</td>
          <td>1.396022</td>
          <td>-57.449568</td>
          <td>-0.847536</td>
        </tr>
        <tr>
          <th>1</th>
          <td>1.557407</td>
          <td>1.306463</td>
          <td>30.217489</td>
          <td>0.052585</td>
          <td>90.508119</td>
          <td>0.230177</td>
          <td>1.397916</td>
          <td>-57.779914</td>
          <td>2.431839</td>
        </tr>
        <tr>
          <th>2</th>
          <td>1.581696</td>
          <td>1.327713</td>
          <td>33.364893</td>
          <td>0.038355</td>
          <td>93.115220</td>
          <td>0.227605</td>
          <td>1.420653</td>
          <td>-57.884926</td>
          <td>-1.068458</td>
        </tr>
        <tr>
          <th>3</th>
          <td>1.581874</td>
          <td>1.322211</td>
          <td>32.826192</td>
          <td>0.052619</td>
          <td>94.994063</td>
          <td>0.231756</td>
          <td>1.414765</td>
          <td>-60.605447</td>
          <td>1.418711</td>
        </tr>
        <tr>
          <th>4</th>
          <td>1.588506</td>
          <td>1.35719</td>
          <td>31.644281</td>
          <td>0.053196</td>
          <td>88.928298</td>
          <td>0.228316</td>
          <td>1.425050</td>
          <td>-52.730850</td>
          <td>-0.696435</td>
        </tr>
        <tr>
          <th>5</th>
          <td>1.601673</td>
          <td>1.369327</td>
          <td>32.093232</td>
          <td>0.045197</td>
          <td>90.860257</td>
          <td>0.231185</td>
          <td>1.437793</td>
          <td>-56.677996</td>
          <td>1.148086</td>
        </tr>
        <tr>
          <th>6</th>
          <td>1.603018</td>
          <td>1.377332</td>
          <td>31.653487</td>
          <td>0.047548</td>
          <td>90.547222</td>
          <td>0.233719</td>
          <td>1.446199</td>
          <td>-55.699391</td>
          <td>-0.751054</td>
        </tr>
        <tr>
          <th>7</th>
          <td>1.613106</td>
          <td>1.349747</td>
          <td>33.056158</td>
          <td>0.066245</td>
          <td>89.254958</td>
          <td>0.233695</td>
          <td>1.444230</td>
          <td>-55.125864</td>
          <td>2.367373</td>
        </tr>
        <tr>
          <th>8</th>
          <td>1.582760</td>
          <td>1.31039</td>
          <td>30.680655</td>
          <td>0.038741</td>
          <td>90.028285</td>
          <td>0.232082</td>
          <td>1.415221</td>
          <td>-51.563416</td>
          <td>0.118047</td>
        </tr>
        <tr>
          <th>9</th>
          <td>1.537512</td>
          <td>1.276349</td>
          <td>32.483550</td>
          <td>0.042677</td>
          <td>89.327811</td>
          <td>0.227329</td>
          <td>1.378457</td>
          <td>-55.372066</td>
          <td>-1.148422</td>
        </tr>
        <tr>
          <th>10</th>
          <td>1.484822</td>
          <td>1.207296</td>
          <td>31.927522</td>
          <td>0.026986</td>
          <td>88.742457</td>
          <td>0.221525</td>
          <td>1.328025</td>
          <td>-56.814935</td>
          <td>-4.841572</td>
        </tr>
        <tr>
          <th>11</th>
          <td>1.488537</td>
          <td>1.198343</td>
          <td>31.833930</td>
          <td>0.047310</td>
          <td>85.481615</td>
          <td>0.221396</td>
          <td>1.318177</td>
          <td>-50.893184</td>
          <td>-0.330903</td>
        </tr>
        <tr>
          <th>12</th>
          <td>1.478344</td>
          <td>1.12722</td>
          <td>32.054301</td>
          <td>0.052482</td>
          <td>84.449672</td>
          <td>0.223780</td>
          <td>1.296303</td>
          <td>-44.846466</td>
          <td>-1.154617</td>
        </tr>
        <tr>
          <th>13</th>
          <td>1.697819</td>
          <td>0.205299</td>
          <td>-26.177910</td>
          <td>0.602695</td>
          <td>45.951556</td>
          <td>0.150593</td>
          <td>0.468082</td>
          <td>-25.935349</td>
          <td>-166.322326</td>
        </tr>
        <tr>
          <th>14</th>
          <td>1.541493</td>
          <td>1.192787</td>
          <td>-31.241248</td>
          <td>0.014819</td>
          <td>95.155874</td>
          <td>0.229849</td>
          <td>1.383633</td>
          <td>59.688229</td>
          <td>-11.755454</td>
        </tr>
        <tr>
          <th>15</th>
          <td>1.546868</td>
          <td>1.255387</td>
          <td>-32.130055</td>
          <td>0.049132</td>
          <td>88.663217</td>
          <td>0.221836</td>
          <td>1.380925</td>
          <td>48.587683</td>
          <td>-3.250563</td>
        </tr>
        <tr>
          <th>16</th>
          <td>1.562865</td>
          <td>1.312509</td>
          <td>-32.943188</td>
          <td>0.016744</td>
          <td>92.130044</td>
          <td>0.221109</td>
          <td>1.404385</td>
          <td>51.039403</td>
          <td>4.254341</td>
        </tr>
        <tr>
          <th>17</th>
          <td>1.609458</td>
          <td>1.330787</td>
          <td>-32.892909</td>
          <td>0.059461</td>
          <td>90.338997</td>
          <td>0.231328</td>
          <td>1.437250</td>
          <td>51.148763</td>
          <td>3.190712</td>
        </tr>
        <tr>
          <th>18</th>
          <td>1.573855</td>
          <td>1.324743</td>
          <td>-33.098392</td>
          <td>0.013983</td>
          <td>92.811379</td>
          <td>0.226108</td>
          <td>1.404228</td>
          <td>57.248321</td>
          <td>-1.209358</td>
        </tr>
        <tr>
          <th>19</th>
          <td>1.572994</td>
          <td>1.302716</td>
          <td>-33.639738</td>
          <td>0.033045</td>
          <td>90.556265</td>
          <td>0.222304</td>
          <td>1.406933</td>
          <td>56.007658</td>
          <td>-0.000964</td>
        </tr>
        <tr>
          <th>20</th>
          <td>1.511498</td>
          <td>1.228517</td>
          <td>-32.214021</td>
          <td>0.036579</td>
          <td>90.045474</td>
          <td>0.220584</td>
          <td>1.339083</td>
          <td>54.792416</td>
          <td>-0.255400</td>
        </tr>
        <tr>
          <th>21</th>
          <td>1.539912</td>
          <td>1.25378</td>
          <td>-33.367350</td>
          <td>0.039426</td>
          <td>92.697716</td>
          <td>0.220686</td>
          <td>1.366620</td>
          <td>54.989109</td>
          <td>-1.828305</td>
        </tr>
        <tr>
          <th>22</th>
          <td>1.502812</td>
          <td>1.212846</td>
          <td>-30.780993</td>
          <td>0.036905</td>
          <td>87.325563</td>
          <td>0.228289</td>
          <td>1.334131</td>
          <td>50.147141</td>
          <td>0.409310</td>
        </tr>
        <tr>
          <th>23</th>
          <td>1.504343</td>
          <td>1.206246</td>
          <td>-31.148819</td>
          <td>0.025703</td>
          <td>88.297088</td>
          <td>0.225588</td>
          <td>1.338933</td>
          <td>53.209872</td>
          <td>2.333753</td>
        </tr>
        <tr>
          <th>24</th>
          <td>1.512405</td>
          <td>1.21277</td>
          <td>-31.993676</td>
          <td>0.039298</td>
          <td>89.074205</td>
          <td>0.220820</td>
          <td>1.346174</td>
          <td>55.071943</td>
          <td>-1.863167</td>
        </tr>
        <tr>
          <th>25</th>
          <td>1.502292</td>
          <td>1.193141</td>
          <td>-32.192790</td>
          <td>0.051573</td>
          <td>88.076743</td>
          <td>0.222772</td>
          <td>1.336317</td>
          <td>48.825681</td>
          <td>1.659710</td>
        </tr>
        <tr>
          <th>26</th>
          <td>1.456642</td>
          <td>1.149952</td>
          <td>-31.964229</td>
          <td>0.028782</td>
          <td>87.303691</td>
          <td>0.220247</td>
          <td>1.299446</td>
          <td>54.532540</td>
          <td>-2.987568</td>
        </tr>
        <tr>
          <th>27</th>
          <td>1.316825</td>
          <td>1.028979</td>
          <td>-30.933646</td>
          <td>0.041233</td>
          <td>79.972601</td>
          <td>0.211285</td>
          <td>1.162746</td>
          <td>42.210693</td>
          <td>-10.672308</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  1.946 seconds)

**Estimated memory usage:**  9 MB


.. _sphx_glr_download_auto_examples_parameters_spatial_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: spatial_parameters.py <spatial_parameters.py>`

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

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


.. only:: html

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

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