ecoscope.analysis.ecograph
==========================

.. py:module:: ecoscope.analysis.ecograph








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

.. py:data:: InterpolationOption

.. py:class:: Ecograph(trajectory, resolution = 15, radius = 2, cutoff = None, tortuosity_length = 3)

   A class that analyzes movement tracking data using Network Theory.

   :param trajectory: Trajectory dataframe
   :type trajectory: ecoscope.Trajectory
   :param resolution: Pixel size, in meters
   :type resolution: float
   :param radius: Radius to compute Collective Influence (Default : 2)
   :type radius: int
   :param cutoff: Cutoff to compute an approximation of betweenness index if the standard algorithm is
                  too slow. Can be useful for very large graphs (Default : None)
   :type cutoff: int
   :param tortuosity_length: The number of steps used to compute the two tortuosity metrics (Default : 3 steps)
   :type tortuosity_length: int


   .. py:attribute:: graphs
      :type:  dict[str, networkx.Graph]


   .. py:attribute:: trajectory


   .. py:attribute:: resolution


   .. py:attribute:: utm_crs


   .. py:attribute:: features
      :value: ['dot_product', 'speed', 'step_length', 'sin_time', 'cos_time', 'weight', 'degree',...



   .. py:attribute:: xmin


   .. py:attribute:: ymin


   .. py:attribute:: xmax


   .. py:attribute:: ymax


   .. py:attribute:: transform


   .. py:attribute:: inverse_transform


   .. py:attribute:: n_rows


   .. py:attribute:: n_cols


   .. py:method:: to_csv(output_path)

      Saves the features of all nodes in a CSV file

      :param output_path: Output path for the CSV file
      :type output_path: str, Pathlike



   .. py:method:: to_geotiff(feature, output_path, individual = 'all', interpolation = None, transform = None)

      Saves a specific node feature as a GeoTIFF

      :param feature: Feature of interest
      :type feature: str
      :param output_path: Output path for the GeoTIFF file
      :type output_path: str, Pathlike
      :param individual: The individual for which we want to output the node feature (Default : "all")
      :type individual: str
      :param interpolation: Whether to interpolate the feature for each step in the trajectory (Default : None). If
                            provided, has to be one of those four types of interpolation : "mean", "median", "max"
                            or "min"
      :type interpolation: str or None
      :param transform: A feature transform method (Default : None)
      :type transform: sklearn.base.TransformerMixin or None



   .. py:method:: _get_ecograph(gdf, radius, cutoff, tortuosity_length)


   .. py:method:: _update_node(G, node_id, attributes)
      :staticmethod:



   .. py:method:: _get_day_night_value(day_night_value)
      :staticmethod:



   .. py:method:: _initialize_node(G, node_id, attributes, empty = False)
      :staticmethod:



   .. py:method:: _get_dot_product(x, y, z, w)
      :staticmethod:



   .. py:method:: _get_tortuosities(lines, time_delta)


   .. py:method:: _compute_network_metrics(G, radius, cutoff)


   .. py:method:: _compute_degree(G)
      :staticmethod:



   .. py:method:: _compute_collective_influence(G, radius)


   .. py:method:: _get_collective_influence(G, start, radius)
      :staticmethod:



   .. py:method:: _compute_betweenness(G, cutoff)
      :staticmethod:



   .. py:method:: _get_feature_mosaic(feature, interpolation = None)


   .. py:method:: _get_feature_map(feature, individual, interpolation = None)


   .. py:method:: _get_regular_feature_map(feature, individual)


   .. py:method:: _get_interpolated_feature_map(feature, individual, interpolation)


.. py:function:: get_feature_gdf(input_path)

   Convert a GeoTIFF feature map into a GeoDataFrame

   :param input_path: Input path for the GeoTIFF file
   :type input_path: str, Pathlike