ecoscope.base#

Submodules#

Package Contents#

class ecoscope.base.ProximityProfile[source]#
spatial_features: list[SpatialFeature]#
class ecoscope.base.RelocsCoordinateFilter[source]#

Filter parameters for filtering get_fixes based on X/Y coordinate ranges or specific coordinate values

min_x: float = -180.0#
max_x: float = 180.0#
min_y: float = -90.0#
max_y: float = 90.0#
filter_point_coords: list[list[float]] | geopandas.GeoSeries | None = None#
__post_init__()[source]#
class ecoscope.base.RelocsDateRangeFilter[source]#

Filter parameters for filtering based on a datetime range

start: datetime.datetime#
end: datetime.datetime#
class ecoscope.base.RelocsDistFilter[source]#

Filter based on the distance between consecutive fixes. Fixes are filtered to the range [min_dist_km, max_dist_km].

min_dist_km: float = 0.0#
max_dist_km: float#
temporal_order: str = 'ASC'#
class ecoscope.base.RelocsSpeedFilter[source]#

Filter parameters for filtering based on the speed needed to move from one fix to the next

max_speed_kmhr: float#
temporal_order: str = 'ASC'#
ecoscope.base.RelocsFilterType#
class ecoscope.base.SpatialFeature[source]#

A spatial geometry with an associated name and unique ID. Becomes a useful construct in several movdata calculations

name: str = ''#
unique_id: Any#
geometry: Any = None#
class ecoscope.base.TrajSegFilter[source]#

Class filtering a set of trajectory segment segments

min_length_meters: float = 0.0#
max_length_meters: float#
min_time_secs: float = 0.0#
max_time_secs: float#
min_speed_kmhr: float = 0.0#
max_speed_kmhr: float#
class ecoscope.base.StraightTrackProperties(gdf)[source]#
Parameters:

gdf (geopandas.GeoDataFrame)

gdf#
property start_fixes#
property end_fixes#
property inverse_transformation#
property heading#
property dist_meters#
property nsd#
property timespan_seconds#
property speed_kmhr#
ecoscope.base.BoundingBox#
ecoscope.base.create_meshgrid(aoi, in_crs, out_crs, xlen=1000, ylen=1000, return_intersecting_only=True, align_to_existing=None)[source]#

Create a grid covering aoi.

Parameters:

  • aoi (shapely.geometry.base.BaseGeometry) – The area of interest. Should be in a UTM CRS.

  • in_crs (value) – Coordinate Reference System of input aoi. Can be anything accepted by pyproj.CRS.from_user_input(). Geometry is automatically converted to UTM CRS as an intermediate for computation.

  • out_crs (value) – Coordinate Reference System of output gs. Can be anything accepted by pyproj.CRS.from_user_input(). Geometry is automatically converted to UTM CRS as an intermediate for computation.

  • xlen (int, optional) – The width of a grid cell in meters.

  • ylen (int, optional) – The height of a grid cell in meters.

  • return_intersecting_only (bool, optional) – Whether to return only grid cells intersecting with the aoi.

  • align_to_existing (geopandas.GeoSeries or geopandas.GeoDataFrame, optional) – If provided, attempts to align created grid to start of existing grid. Requires a CRS and valid geometry.

Returns:

gs – Grid of boxes. CRS is converted to out_crs.

Return type:

geopandas.GeoSeries

ecoscope.base.groupby_intervals(df, col, intervals)[source]#
Parameters:

  • df (pd.DataFrame) – Data to group

  • col (str) – Name of column to group on

  • intervals (pd.IntervalIndex) – Intervals to group on

Return type:

pd.core.groupby.DataFrameGroupBy

ecoscope.base.hex_to_rgba(input)[source]#
Parameters:

input (str)

Return type:

tuple

ecoscope.base.color_tuple_to_css(color)[source]#
Parameters:

color (Tuple[int, int, int, int])

Return type:

str

class ecoscope.base.EcoDataFrame(gdf)[source]#

EcoDataFrame wraps geopandas.GeoDataFrame to provide customizations and allow for simpler extension.

Parameters:

gdf (geopandas.GeoDataFrame)

gdf#
classmethod from_file(filename, **kwargs)[source]#
classmethod from_features(features, **kwargs)[source]#
reset_filter(inplace=False)[source]#
remove_filtered(inplace=False)[source]#