added updated validation notebooks

.gitattributes

@@ -1 +1,2 @@
 processed_data/merged_basin_groups/region_polygons.zip filter=lfs diff=lfs merge=lfs -text
+input_data/adjusted_region_polygons.zip filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -5,16 +5,24 @@ references/
 input_data/*.vrt
 input_data/DEM/
 input_data/AK_*/
-processed_dem/
 input_data/NHN_INDEX*/
+input_data/DAYMET/
 input_data/region_polygons/
+input_data/region_bounds/
 input_data/BasinATLAS/
-optimization/
-validation/tmp/
-
+input_data/adjusted_region_polygons/
 input_data/NHN_data/*
+input_data/HYSETS_data/*
 input_data/NALCMS/*
 input_data/GLHYMPS/*
+input_data/*.geojson
+
+optimization/
+validation/tmp/
+validation/data/
+validation/ss/
+processed_dem/
+
 processed_data/basin_attributes/
 processed_data/DAYMET/
 processed_data/BCUB_files/
@@ -24,9 +32,11 @@ processed_data/derived_basins/
 processed_data/processed_dem/
 processed_data/*.vrt
 processed_data/*.py
+processed_data/*.geojson
 results/
 superseded/
 *.qgz
+upload_dataverse_files.py
 
 __pycache__/
-.ipynb_checkpoints/
+.ipynb_checkpoints/

get_hysets_attributes.py

@@ -0,0 +1,54 @@
+import pandas as pd
+import numpy as np
+import geopandas as gpd
+import psycopg2
+
+columns = [
+    'official_id', 'watershed_id', 'name', 'centroid_lat_deg_n', 'centroid_lon_deg_e', 
+    'drainage_area_km2', 'drainage_area_gsim_km2', 'flag_gsim_boundaries', 'flag_artificial_boundaries', 
+    'elevation_m', 'slope_deg', 'gravelius', 'perimeter', 'flag_shape_extraction', 'aspect_deg', 'flag_terrain_extraction', 
+    'land_use_forest_frac_2010', 'land_use_grass_frac_2010', 'land_use_wetland_frac_2010', 
+    'land_use_water_frac_2010', 'land_use_urban_frac_2010', 'land_use_shrubs_frac_2010', 
+    'land_use_crops_frac_2010', 'land_use_snow_ice_frac_2010', 'flag_land_use_extraction', 
+    'logk_ice_x100', 'porosity_x100', 'flag_subsoil_extraction', 'year_from', 'year_to', 
+    'record_length', 'agency', 'status', 'updated_official_basin', 'in_bcub', 
+    'prcp', 'srad', 'swe', 'tmax', 'tmin', 'vp', 
+    'high_prcp_freq', 'high_prcp_duration', 'low_prcp_freq', 'low_prcp_duration'
+]
+
+def get_hysets_attributes(columns, conn):
+    """
+    Get hysets attributes by hysets_id
+    :param hysets_id: int
+    :param conn: psycopg2 connection
+    :return: pd.DataFrame
+    """
+    # Get hysets attributes
+    if columns is None:
+        query = f"""
+        SELECT * FROM basins_schema.hysets_basins
+        WHERE in_bcub = True
+        LIMIT 10;
+        """
+        hysets_attributes = gpd.read_postgis(query, conn, geom_col='centroid')
+    else:
+        column_string = ', '.join(columns)
+        query = f"""
+        SELECT {column_string} FROM basins_schema.hysets_basins
+        WHERE in_bcub = True
+        ORDER BY official_id;
+        """
+        hysets_attributes = pd.read_sql_query(query, conn)
+    return hysets_attributes
+
+conn_info = {   
+    'dbname': 'basins',
+    'user': 'postgres',
+    'password': 'pgpass',
+    'host': 'localhost',
+    'port': '5432'
+}
+conn = psycopg2.connect(**conn_info)
+
+df = get_hysets_attributes(columns, conn)
+df.to_csv('BCUB_HYSETS_properties_with_climate.csv', index=False)

img/region_edge_detail.pgw

@@ -0,0 +1,6 @@
+102.93548597422287116
+0
+0
+-102.93548597422287116
+1158699.56954298727214336
+1110379.6146800983697176