formatting with black

hydropop/streamflow/selecting_gages.py

@@ -1,39 +1,39 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Mon Sep 12 14:45:03 2022
-
-@author: 318596
-"""
 import geopandas as gpd
 from VotE import config
+
 config.vote_db()
 from VotE.streamflow import export_streamflow as es
 import os
 
 
-path_bounding_box = r"X:\Research\CIMMID\Data\Hydropop Layers\Finals\toronto_coarse\roi.gpkg" # shapefile of ROI
+path_bounding_box = r"X:\Research\CIMMID\Data\Hydropop Layers\Finals\toronto_coarse\roi.gpkg"  # shapefile of ROI
 bb = gpd.read_file(path_bounding_box)
-gage_params = {'within' : bb.geometry.values[0],
-               'max_drainarea_km2' : 10000,
-               'fraction_valid' : .9,
-               'vote_snapped' : True,
-               'end_date': '2000-01-01',
-               'min_span_years' : 10
-              }
+gage_params = {
+    "within": bb.geometry.values[0],
+    "max_drainarea_km2": 10000,
+    "fraction_valid": 0.9,
+    "vote_snapped": True,
+    "end_date": "2000-01-01",
+    "min_span_years": 10,
+}
 gage_ids = es.gage_selector(gage_params)
 gages = es.get_gages(gage_ids)
 
 # Export the gages and their watersheds (two files)
-keepkeys = [k for k in gages.keys() if 'geom' not in k]
-keepkeys = [k for k in keepkeys if 'chunk' not in k]
-keepkeys.remove('id_duplicates')
-gage_locs = gpd.GeoDataFrame(data=gages[keepkeys], geometry=gages['mapped_geom'], crs=gages.crs)
-basins = gpd.GeoDataFrame(data=gages[keepkeys], geometry=gages['basin_geom_vote'], crs=gages.crs)
+keepkeys = [k for k in gages.keys() if "geom" not in k]
+keepkeys = [k for k in keepkeys if "chunk" not in k]
+keepkeys.remove("id_duplicates")
+gage_locs = gpd.GeoDataFrame(
+    data=gages[keepkeys], geometry=gages["mapped_geom"], crs=gages.crs
+)
+basins = gpd.GeoDataFrame(
+    data=gages[keepkeys], geometry=gages["basin_geom_vote"], crs=gages.crs
+)
 
-gage_locs['start_date'] = gage_locs['start_date'].astype(str)
-gage_locs['end_date'] = gage_locs['end_date'].astype(str)
-basins['start_date'] = basins['start_date'].astype(str)
-basins['end_date'] = basins['end_date'].astype(str)
+gage_locs["start_date"] = gage_locs["start_date"].astype(str)
+gage_locs["end_date"] = gage_locs["end_date"].astype(str)
+basins["start_date"] = basins["start_date"].astype(str)
+basins["end_date"] = basins["end_date"].astype(str)
 
 # gage_locs.to_file(r'X:\Research\CIMMID\Data\Hydropop Layers\Finals\na_10k\gage_selection\na_10k_gages.gpkg', driver='GPKG')
 # basins.to_file(r'X:\Research\CIMMID\Data\Hydropop Layers\Finals\na_10k\gage_selection\na_10k_basins.gpkg', driver='GPKG')
@@ -43,15 +43,23 @@
 # current_gages = gpd.read_file(current_gages)
 # gages = es.get_gages(current_gages['id_gage'].values.tolist())
 
-gage_locs.to_file(r'X:\Research\CIMMID\Data\Watersheds\Toronto\initial_gages.gpkg', driver='GPKG')
-basins.to_file(r'X:\Research\CIMMID\Data\Watersheds\Toronto\initial_basins.gpkg', driver='GPKG')
+gage_locs.to_file(
+    r"X:\Research\CIMMID\Data\Watersheds\Toronto\initial_gages.gpkg", driver="GPKG"
+)
+basins.to_file(
+    r"X:\Research\CIMMID\Data\Watersheds\Toronto\initial_basins.gpkg", driver="GPKG"
+)
 
 """ Download streamflow data """
-for id_gage in basins['id_gage'].values:
+for id_gage in basins["id_gage"].values:
     print(id_gage)
-    df = es.get_streamflow_timeseries([int(id_gage)], start_date='1981-01-01', expand=True, trim=True)
-    df.drop('id_gage', inplace=True, axis=1)
-    df.sort_values(by='date', inplace=True)
-    path_out = os.path.join(r'X:\Research\CIMMID\Data\Hydropop Layers\Finals\na_10k\streamflow', str(id_gage) + '.csv')
+    df = es.get_streamflow_timeseries(
+        [int(id_gage)], start_date="1981-01-01", expand=True, trim=True
+    )
+    df.drop("id_gage", inplace=True, axis=1)
+    df.sort_values(by="date", inplace=True)
+    path_out = os.path.join(
+        r"X:\Research\CIMMID\Data\Hydropop Layers\Finals\na_10k\streamflow",
+        str(id_gage) + ".csv",
+    )
     df.to_csv(path_out, index=False)
-