ecoscope.relocations
====================

.. py:module:: ecoscope.relocations




Module Contents
---------------

.. py:class:: Relocations(gdf)

   Bases: :py:obj:`ecoscope.base.EcoDataFrame`


   Relocation is a model for a set of fixes from a given subject.
   Because fixes are temporal, they can be ordered asc or desc. The additional_data dict can contain info
   specific to the subject and relocations: name, type, region, sex etc. These values are applicable to all
   fixes in the relocations array. If they vary, then they should be put into each fix's additional_data dict.


   .. py:method:: from_gdf(gdf, groupby_col = None, time_col = 'fixtime', uuid_col = None, copy = True)
      :classmethod:


      :param gdf: Observations data
      :type gdf: GeoDataFrame
      :param groupby_col: Name of `gdf` column of identities to treat as separate individuals. Usually `subject_id`. Default is
                          treating the gdf as being of a single individual.
      :type groupby_col: str, optional
      :param time_col: Name of `gdf` column containing relocation times. Default is 'fixtime'.
      :type time_col: str, optional
      :param uuid_col: Name of `gdf` column of row identities. Used as index. Default is existing index.
      :type uuid_col: str, optional
      :param copy: Whether or not to copy the `gdf`. Defaults to `True`.
      :type copy: bool, optional



   .. py:method:: _apply_speedfilter(df, fix_filter)
      :staticmethod:



   .. py:method:: _apply_distfilter(df, fix_filter)
      :staticmethod:



   .. py:method:: apply_reloc_filter(fix_filter = None, inplace = False)

      Apply a given filter by marking the fix junk_status based on the conditions of a filter



   .. py:property:: distance_from_centroid


   .. py:property:: cluster_radius

      The cluster radius is the largest distance between a point in the relocationss and the
      centroid of the relocationss


   .. py:property:: cluster_std_dev

      The cluster standard deviation is the standard deviation of the radii from the centroid
      to each point making up the cluster


   .. py:method:: threshold_point_count(threshold_dist)

      Counts the number of points in the cluster that are within a threshold distance of the geographic centre



   .. py:method:: apply_threshold_filter(threshold_dist_meters = float('Inf'))