ecoscope ======== .. py:module:: ecoscope Submodules ---------- .. toctree:: :maxdepth: 1 /autoapi/ecoscope/_version/index /autoapi/ecoscope/analysis/index /autoapi/ecoscope/base/index /autoapi/ecoscope/io/index /autoapi/ecoscope/mapping/index /autoapi/ecoscope/plotting/index /autoapi/ecoscope/relocations/index /autoapi/ecoscope/trajectory/index Package 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')) .. py:function:: init(silent=False, force=False) Initializes the environment with ecoscope-specific customizations. :param silent: Removes console output :type silent: bool, optional :param force: Ignores `__initialized` :type force: bool, optional