analysis API Reference¶

Top-level functions for propagator.

This contains main functions use propagate and accumlate catchment properties in a larger watershed.

3. Geosyntec Consultants, 2015.

Released under the BSD 3-clause license (see LICENSE file for more info)

Written by Paul Hobson (phobson@geosyntec.com)

propagator.analysis.trace_upstream(*args, **kwargs)¶

Recursively traces an upstream path of subcatchments through a watetershed.

Parameters:

subcatchment_array : numpy.recarry A record array of all of the subcatchments in the watershed. This array must have a “downstrea ID” column in which each subcatchment identifies as single, downstream neighbor. subcatchment_ID : str The ID of the downstream catchment from which the trace originates. id_col : str, optional The name of the column that specifies the current subcatchment. ds_col : str, optional The name of the column that identifies the downstream subcatchment. downstream : list, optional A list of already known downstream catchments in the trace. Warning This is only used in the recursive calls to this function. You should never provide this value.

Returns:

upstream : numpy.recarry A record array of all of the upstream subcatchments. This will have the same schema as subcatchment_array

propagator.analysis.find_bottoms(*args, **kwargs)¶

Finds the lowest, non-ocean subcatchments in a watershed.

Parameters:	subcatchment_array : numpy.recarry A record array of all of the subcatchments in the watershed. This array must have a “downstrea ID” column in which each subcatchment identifies as single, downstream neighbor. bottom_ID : str, optional The subcatchment ID of the pseudo-catchments in the Ocean. ds_col : str, optional The name of the column that identifies the downstream subcatchment.
Returns:	bottoms : numpy.recarry A record array of all of subcatchments that drain into the ocean.

propagator.analysis.find_tops(*args, **kwargs)¶

Finds the the subcatchments in a watershed that do not accept any upstrea tributary flow.

Parameters:

subcatchment_array : numpy.recarry A record array of all of the subcatchments in the watershed. This array must have a “downstrea ID” column in which each subcatchment identifies as single, downstream neighbor. subcatchment_ID : str The ID of the downstream catchment from which the trace originates. id_col : str, optional The name of the column that specifies the current subcatchment. ds_col : str, optional The name of the column that identifies the downstream subcatchment.

Returns:

top : numpy.recarry A record array of all of the upper most subcatchments.

propagator.analysis.propagate_scores(*args, **kwargs)¶

Propagate values into upstream subcatchments through a watershed.

Parameters:

subcatchment_array : numpy.recarry A record array of all of the subcatchments in the watershed. This array must have a “downstrea ID” column in which each subcatchment identifies as single, downstream neighbor. id_col : str, optional The name of the column that specifies the current subcatchment. ds_col : str, optional The name of the column that identifies the downstream subcatchment. value_column : str Name of a representative water quality column that can be used to indicate if the given subcatchment has or has not been populated with water quality data. ignored_value : float, optional The values representing unpopulated records in the array of subcatchment and water quality data. bottom_ID : str, optional The subcatchment ID of the pseudo-catchments in the Ocean.

Returns:

propagated : numpy.recarry A copy of subcatchment_array with all of the water quality records populated.

propagator.analysis.preprocess_wq(*args, **kwargs)¶

Preprocess the water quality data to have to averaged score for each subcatchment.

Parameters:

monitoring_locations : str Path to the feature class containing the monitoring locations and their water quality scores. subcatchments : str Path to the feature class containing the subcatchment boundaries. id_col : str, ds_col Name of the column in subcatchments that contains the (ds = downstream) subcatchment IDs. output_path : str Path of the new feature class where the preprocessed data should be saved. value_columns : list of str A list of the names of the fields containing water quality scores that need to be analyzed. aggfxn : callable, optional A function, lambda, or class method that reduces arrays into scalar values. By default, this is numpy.mean. ignored_value : int, optional The values in monitoring_locations that should be ignored. Given the default input datasets, zero has been chosen to signal that a value is missing. cleanup : bool, optional Toggles the deletion of temporary files.

Returns:

array : numpy.recarray A numpy record array of the subcatchments with their aggregated water quality scores.

propagator.analysis.split_streams(*args, **kwargs)¶

propagator.analysis.prepare_data(*args, **kwargs)¶

Assigns water quality ranking from monitoring locations to the subcatchments. If multiple monitoring locations are present in one subcatchment, water quality rankings are aggregated prior to assignment.

Parameters:

mon_locations : str File path to the monitoring locations feature class. subcatchments : str File path to the subcatchments feature class. subcatch_id_col : str Field name of the subcatchment ID column in subcatchments. sort_id: str Arbituary field name for sorting purpose. Default value is ‘FID’ header_fields : list List of header field names to be retained in the output feature class. wq_fields : list List of water quality field names to be analyzed outputfile : str Filename where the output should be saved.

Returns:

subcatchment_wq : arcpy.Layer A subcatchment class that inherited water quality rankings from respective monitoring locations.