Final Baird Commit
This commit is contained in:
Alexander Rey
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## Process EWR Hg Data into a surface
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# AJMR: September 2022
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#%% Setup
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import pandas as pd
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import geopandas as gp
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import gpxpy
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import gpxpy.gpx
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import numpy as np
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import matplotlib.pyplot as plt
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import contextily as ctx
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import datetime
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import scipy as sp
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from scipy.interpolate import griddata
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from shapely import geometry, ops
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#%% Read in centerline shapefile
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river_centerline = gp.read_file('//srv-ott3.baird.com/Projects/12828.101 English Wabigoon River/03_Data/02_Physical/16_Waterline/Centerline_for_Modelling_UTMZ15.shp')
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river_centerlineExploded = river_centerline.explode(ignore_index=True)
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river_centerlineExploded.reset_index(inplace=True)
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tempMulti = river_centerlineExploded.iloc[[5,0,1,2,3,4,6,7,9], 4]
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# Put the sub-line coordinates into a list of sublists
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outcoords = [list(i.coords) for i in tempMulti]
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# Flatten the list of sublists and use it to make a new line
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river_centerline_merge = geometry.LineString([i for sublist in outcoords for i in sublist])
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river_centerline_merge_gpd = gp.GeoSeries(river_centerline_merge)
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river_centerline_merge_gpd2 =\
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gp.GeoDataFrame(geometry=gp.points_from_xy(
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river_centerline_merge.xy[0], river_centerline_merge.xy[1], crs="EPSG:32615"))
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# Add distance along centerline
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river_centerline_merge_gpd2['DistanceFromPrevious'] = river_centerline_merge_gpd2.distance(river_centerline_merge_gpd2.shift(1))
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river_centerline_merge_gpd2['RiverKM'] = river_centerline_merge_gpd2['DistanceFromPrevious'].cumsum()
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river_centerline_merge_gpd2.iloc[0, 1] = 0
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river_centerline_merge_gpd2.iloc[0, 2] = 0
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#%% Read in combined dataset
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# obs_IN = pd.read_csv("//srv-ott3.baird.com/Projects/12828.101 English Wabigoon River/05_Analyses/02_Data Analysis/output/combined dataset-SGJ.csv")
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# obs_IN = pd.read_csv("//srv-ott3.baird.com/Projects/12828.101 English Wabigoon River/05_Analyses/02_Data Analysis/combined dataset.csv")
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# obs_IN = pd.read_csv("C:/Users/arey/Downloads/ExportDownloads_EwrrpDataExport_rharris_2023-05-12_104911/EwrrpDataExport_rharris_2023-05-12_104911.txt", sep='\t', encoding='UTF-16 LE')
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df = pd.read_csv(r"P:\12828.101 English Wabigoon River\03_Data\02_Physical\30_Site Sampling Database\EwrrpDataExport_rharris_2022-08-23_102403_Results.txt", sep = '\t', encoding='UTF-16 LE')
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locations = pd.read_csv(r"P:\12828.101 English Wabigoon River\03_Data\02_Physical\30_Site Sampling Database\EwrrpDataExport_rharris_2022-08-23_102403_Sites.txt", sep = '\t', encoding='UTF-16 LE')
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samples = pd.read_csv(r"P:\12828.101 English Wabigoon River\03_Data\02_Physical\30_Site Sampling Database\EwrrpDataExport_rharris_2022-08-23_102403_Samples.txt", sep = '\t', encoding='UTF-16 LE')
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#%% Merge locations and results
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obs_IN = pd.merge(left=df, right=locations, left_on= 'Samplesiteid', right_on= 'Id', how = 'left') # 1096 locations w/Hg
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obs_IN = pd.merge(left=obs_IN, right=samples, left_on= 'Sampleid', right_on= 'Id', how = 'left') # 1096 locations w/Hg
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# Add Datetime
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obs_IN['Sampledate'] = pd.to_datetime(obs_IN.Sampledate)
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#%% Process combined datsaset
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# Convert to geodataframe
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obs_gdf = gp.GeoDataFrame(obs_IN, geometry=gp.points_from_xy(
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obs_IN.loc[:, 'Longitude'], obs_IN.loc[:, 'Latitude'], crs="EPSG:4326")).to_crs(crs="EPSG:32615")
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# Add centerline and reset index
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obs_gdf = gp.sjoin_nearest(river_centerline_merge_gpd2, obs_gdf, how='right', max_distance=250).reset_index()
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# Sediment Hg GeoDataFrame where media is Sediment
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obsMask = (((obs_gdf.Media == 'SED') | (obs_gdf.Media == 'SOIL')) &
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((obs_gdf.Parameter == 'Mercury') | (obs_gdf.Parameter == 'Mercury (Hg) Total')
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| (obs_gdf.Parameter == 'Total Mercury') | (obs_gdf.Parameter == 'Mercury (Hg)')) &
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(obs_gdf.Sampledate > datetime.datetime(2000, 1, 1)) & obs_gdf.RiverKM.notna() &
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((obs_gdf.TopDepth == 0) | (obs_gdf.TopDepth.isna())))
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# obsMask = (((obs_gdf.Media_x == 'SED') | (obs_gdf.Media_x == 'SOIL')) &
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# ((obs_gdf.Parameter == 'Mercury') | (obs_gdf.Parameter == 'Mercury (Hg) Total')
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# | (obs_gdf.Parameter == 'Total Mercury') | (obs_gdf.Parameter == 'Mercury (Hg)')) &
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# (obs_gdf.DateTime > datetime.datetime(2000, 1, 1)) & obs_gdf.RiverKM.notna())
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obs_HgSed = obs_gdf.loc[obsMask, :].copy()
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# Adjust Units
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obs_HgSed.loc[obs_HgSed.Unit == 'NG/G', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'NG/G', 'Samplevalue']
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obs_HgSed.loc[obs_HgSed.Unit == 'ng/g', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'ng/g', 'Samplevalue']
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obs_HgSed.loc[obs_HgSed.Unit == 'UG/G', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'UG/G', 'Samplevalue'] * 1000
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obs_HgSed.loc[obs_HgSed.Unit == 'ug/g', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'ug/g', 'Samplevalue'] * 1000
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obs_HgSed.loc[obs_HgSed.Unit == 'MG/KG', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'MG/KG', 'Samplevalue'] * 0.001
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obs_HgSed.loc[obs_HgSed.Unit == 'mg/kg', 'Sample_NG/G'] = obs_HgSed.loc[obs_HgSed.Unit == 'mg/kg', 'Samplevalue'] * 0.001
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# Save subset of columns as a shapefile
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obs_HgSed.loc[:, ['Sample_NG/G', 'Sampledate_x', 'RiverKM', 'Latitude', 'Longitude', 'geometry',
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'Surveyname','Sitecode','Parameter']].to_file(
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'C:/Users/arey/files/Projects/Grassy Narrows/Wood English-Wabigoon Export_alldata_2017-current/BairdDB_HgSed.shp')
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#%% Extract Hg data from surface water samples
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# Water Hg GeoDataFrame where media is SurfaceWater (SW)
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obsMask = (((obs_gdf.Media == 'SW')) &
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((obs_gdf.Parameter == 'Mercury') | (obs_gdf.Parameter == 'Mercury (Hg)-Total')
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| (obs_gdf.Parameter == 'Total Mercury') | (obs_gdf.Parameter == 'Mercury (Hg)')) &
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(obs_gdf.Sampledate > datetime.datetime(2000, 1, 1)) & obs_gdf.RiverKM.notna())
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obs_HgWater = obs_gdf.loc[obsMask, :].copy()
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# Adjust Units
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obs_HgWater.loc[obs_HgWater.Unit == 'NG/L', 'Samplevalue'] = obs_HgWater.Samplevalue
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obs_HgWater.loc[obs_HgWater.Unit == 'ng/L', 'Samplevalue'] = obs_HgWater.Samplevalue
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obs_HgWater.loc[obs_HgWater.Unit == 'UG/L', 'Samplevalue'] = obs_HgWater.Samplevalue * 1000
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obs_HgWater.loc[obs_HgWater.Unit == 'ug/L', 'Samplevalue'] = obs_HgWater.Samplevalue * 1000
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obs_HgWater.loc[obs_HgWater.Unit == 'MG/L', 'Samplevalue'] = obs_HgWater.Samplevalue * 1000000
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obs_HgWater.loc[obs_HgWater.Unit == 'mg/L', 'Samplevalue'] = obs_HgWater.Samplevalue * 1000000
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# Drop where no result
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obs_HgWater = obs_HgWater.dropna(subset=['Samplevalue'])
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# Save subset of columns as a shapefile
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obs_HgWater.loc[:, ['Samplevalue', 'Sampledate', 'RiverKM', 'geometry',
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'Contributor', 'Sitecode', 'Parameter']].to_file(
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'C:/Users/arey/files/Projects/Grassy Narrows/Wood English-Wabigoon Export_alldata_2017-current/BairdDB_HgWater_RevB.shp')
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#%% River Profile Plotting
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fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(6, 6))
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axes.scatter(obs_HgSed.RiverKM, obs_HgSed.Samplevalue)
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axes.scatter(obs_HgSed.RiverKM, obs_HgSed.Samplevalue)
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axes.set_ylim(0, 20000)
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axes.set_xlim(0, 100000)
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axes.set_xlabel('Distance Along River [m]')
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axes.set_ylabel('Surface Sediment Hg [ng/g]')
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plt.show()
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fig.savefig('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/Hg_SurfaceProfile.png',
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bbox_inches='tight', dpi=300)
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#%% Plot Vertical Profiles
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fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(7, 7))
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obs_HgSed.plot.scatter('RiverKM', 'TopDepth_x', 12, 'Sample_NG/G',
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ax=axes, vmax=20000, cmap='viridis')
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axes.invert_yaxis()
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axes.set_xlabel('Distance Along River [m]')
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axes.set_ylabel('Sample Depth [cm]')
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axes.set_xlim([0, 100000])
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# Get colorbar axis to set a legend
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cax = fig.get_axes()[1]
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#and we can modify it, i.e.:
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cax.set_ylabel('Sediment Hg (ng/g)')
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plt.show()
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fig.savefig('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/Hg_Vertical.png',
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bbox_inches='tight', dpi=300)
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#%% Hg Map Plotting
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mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
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fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(10, 7))
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fig.patch.set_facecolor('white')
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# Full system limits
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# axes.set_xlim(350000, 520000)
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# axes.set_ylim(5510000, 5580000)
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# # Clay Lake Limits
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# axes.set_xlim(466418, 515846)
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# axes.set_ylim(5513437, 5545362)
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# Dryden Limits
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axes.set_xlim(497697, 515846)
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axes.set_ylim(5513437, 5525166)
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# Add Basemap
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ctx.add_basemap(axes, source=mapbox, crs='EPSG:32615')
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# Plot Hg At surface
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obs_HgSed.plot(ax=axes, column='Samplevalue', legend=True,
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vmin=0, vmax=5000, markersize=2, cmap='viridis',
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legend_kwds={'label': 'Surface Sediment Hg (ng/g)'})
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plt.show()
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fig.savefig('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/SurfaceHgMap.png',
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bbox_inches='tight', dpi=300)
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#%% Interpolate Hg
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bathy_xyz = pd.read_csv('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/Bed_Level.xyz',
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names=['x', 'y', 'z'], header=0, delim_whitespace=True)
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rough_xyz = pd.read_csv('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/Roughness.xyz',
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names=['x', 'y', 'z'], header=0, delim_whitespace=True)
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HgInterp = griddata(np.array([dataOUTmax.geometry.x, dataOUTmax.geometry.y]).T,
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np.array(dataOUTmax.Samplevalue).T, np.array([bathy_xyz.x, bathy_xyz.y]).T,
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method='nearest')
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HgInterpOut = np.vstack((bathy_xyz.x, bathy_xyz.y, HgInterp))
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HgInterpOut = np.transpose(HgInterpOut)
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# Set Wetlands to zero
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# Interpolate Roughness
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RoughInterp = sp.interpolate.griddata(np.transpose(np.array([rough_xyz.x, rough_xyz.y])), rough_xyz.z, np.transpose(np.array([bathy_xyz.x, bathy_xyz.y])),
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method='nearest')
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HgInterpOut[RoughInterp==0.05, 2] = 0
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np.savetxt('C:/Users/arey/files/Projects/Grassy Narrows/LocalData/SurfaceInterFiltDB.xyz',
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HgInterpOut, delimiter=" ")
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#%% Hg Interp Plotting
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mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
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fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(10, 7))
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fig.patch.set_facecolor('white')
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# Clay Lake Limits
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axes.set_xlim(466418, 515846)
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axes.set_ylim(5513437, 5545362)
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# Add Basemap
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ctx.add_basemap(axes, source=mapbox, crs='EPSG:32615')
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# Plot Hg
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axes.scatter(HgInterpOut[:, 0], HgInterpOut[:, 1], 5, HgInterpOut[:, 2],
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vmin=0, vmax=5000)
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plt.show()
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@ -0,0 +1,464 @@
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"""
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@author: AJMR
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Plotting and animation script for NTC sediment tests
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April 17, 2023
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"""
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import os
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import pandas as pd
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import geopandas as gpd
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import netCDF4 as nc
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import math
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import numpy as np
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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from scipy.interpolate import LinearNDInterpolator, interp1d
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import matplotlib.animation as animation
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import dfm_tools as dfmt
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# Geotiff
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import cartopy.crs as ccrs
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import contextily as ctx
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import pathlib as pl
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from shapely.geometry import Point, MultiPoint
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import alphashape
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import rioxarray
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import xarray as xr
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import cartopy.crs as ccrs
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import contextily as ctx
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from dfm_tools.regulargrid import scatter_to_regulargrid
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from pathlib import Path
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# Colormaps
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import cm_xml_to_matplotlib as cm
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#%% Read Model Log
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runLog = pd.read_excel('C:/Users/arey/files/Projects/Newtown/Model Log NTC.xlsx', 'ModelLog')
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dataPath = "FlowFM/dflowfm/output/FlowFM_map.nc"
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histPath = "FlowFM/dflowfm/output/FlowFM_his.nc"
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#%% Import Model results for static images
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# Define which models to import
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modelPlot = [144]
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d3dfm_DataArray = [None] * (max(modelPlot)+1)
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sedMass = [None] * (max(modelPlot)+1) # Available Mass of Sediment
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erodeSed = [None] * (max(modelPlot)+1) # Erosion and deposition
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initialBed = [None] * (max(modelPlot)+1) # Erosion and deposition
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modelCRS = [None] * (max(modelPlot)+1) # Model CRS
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sedConc = [None] * (max(modelPlot)+1) # Model CRS
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for i in modelPlot:
|
||||||
|
file_nc_map = Path(runLog['Run Location'][i]) / dataPath
|
||||||
|
|
||||||
|
# Open Map file as xarrray Dataset
|
||||||
|
d3dfm_DataArray[i] = dfmt.open_partitioned_dataset(file_nc_map.as_posix())
|
||||||
|
|
||||||
|
# Get Var info
|
||||||
|
vars_pd = dfmt.get_ncvarproperties(d3dfm_DataArray[i])
|
||||||
|
|
||||||
|
# Get last timestep
|
||||||
|
tStep = d3dfm_DataArray[i].time[-1].values
|
||||||
|
|
||||||
|
# Import sand sediment class
|
||||||
|
sedMass[i] = d3dfm_DataArray[i].mesh2d_bodsed[-1, :, 2].compute()
|
||||||
|
initialBed[i]= d3dfm_DataArray[i].mesh2d_s1[0, :] - d3dfm_DataArray[i].mesh2d_waterdepth[0, :]
|
||||||
|
finalBed = d3dfm_DataArray[i].mesh2d_s1[-1, :] - d3dfm_DataArray[i].mesh2d_waterdepth[-1, :]
|
||||||
|
|
||||||
|
erodeSed[i] = finalBed - initialBed[i]
|
||||||
|
erodeSed[i] = erodeSed[i].compute()
|
||||||
|
initialBed[i] = initialBed[i].compute()
|
||||||
|
|
||||||
|
# Import concentration of sediment 2 at timestep 95 and layer 10
|
||||||
|
sedConc[i] = d3dfm_DataArray[i].mesh2d_sedfrac_concentration[94, 2, :, 9].compute()
|
||||||
|
|
||||||
|
modelCRS[i] = vars_pd['EPSG_code']['projected_coordinate_system']
|
||||||
|
|
||||||
|
#%% Define axis limits
|
||||||
|
axLim_Xmin = []
|
||||||
|
axLim_Xmax = []
|
||||||
|
|
||||||
|
axLim_Ymin = []
|
||||||
|
axLim_Ymax = []
|
||||||
|
|
||||||
|
# Set axis limits
|
||||||
|
# Full domain
|
||||||
|
axLim_Xmin.append(298500)
|
||||||
|
axLim_Xmax.append(306800)
|
||||||
|
|
||||||
|
axLim_Ymin.append(58500)
|
||||||
|
axLim_Ymax.append(68000)
|
||||||
|
|
||||||
|
# Zoom North River
|
||||||
|
axLim_Xmin.append(303500)
|
||||||
|
axLim_Xmax.append(305500)
|
||||||
|
|
||||||
|
axLim_Ymin.append(66000)
|
||||||
|
axLim_Ymax.append(68000)
|
||||||
|
|
||||||
|
# Zoom Tribs
|
||||||
|
axLim_Xmin.append(305500)
|
||||||
|
axLim_Xmax.append(306800)
|
||||||
|
|
||||||
|
axLim_Ymin.append(60000)
|
||||||
|
axLim_Ymax.append(62500)
|
||||||
|
|
||||||
|
# Zoom far trib
|
||||||
|
axLim_Xmin.append(305800)
|
||||||
|
axLim_Xmax.append(305900)
|
||||||
|
|
||||||
|
axLim_Ymin.append(60150)
|
||||||
|
axLim_Ymax.append(60400)
|
||||||
|
|
||||||
|
|
||||||
|
#%% Plot using DFM functions
|
||||||
|
|
||||||
|
for i in modelPlot:
|
||||||
|
# Create figure
|
||||||
|
fig, axesFig = plt.subplots(1, 4, figsize=(8, 2))
|
||||||
|
|
||||||
|
axes = axesFig.flatten()
|
||||||
|
|
||||||
|
# Loop through axis and plot with different limits
|
||||||
|
for subIDX in range(0, 4):
|
||||||
|
|
||||||
|
# # Plot Sediment Mass
|
||||||
|
# smp = sedMass[i].ugrid.plot(ax=axes[subIDX], edgecolors='face', cmap='turbo',
|
||||||
|
# vmin=0, vmax=2000, add_colorbar=False)
|
||||||
|
|
||||||
|
# # Plot Erosion
|
||||||
|
# smp = erodeSed[i].ugrid.plot(ax=axes[subIDX], edgecolors='face', cmap='coolwarm',
|
||||||
|
# vmin=-1, vmax=1, add_colorbar=False)
|
||||||
|
|
||||||
|
# Plot Bed
|
||||||
|
smp = initialBed[i].ugrid.plot(ax=axes[subIDX], edgecolors='face', cmap='nipy_spectral',
|
||||||
|
vmin=-25, vmax=0, add_colorbar=False)
|
||||||
|
|
||||||
|
|
||||||
|
# Set axis labels
|
||||||
|
axes[subIDX].set_xlabel('')
|
||||||
|
axes[subIDX].set_ylabel('')
|
||||||
|
axes[subIDX].set_title('')
|
||||||
|
axes[subIDX].set_xticks([])
|
||||||
|
axes[subIDX].set_yticks([])
|
||||||
|
|
||||||
|
axes[subIDX].set_xlim(axLim_Xmin[subIDX], axLim_Xmax[subIDX])
|
||||||
|
axes[subIDX].set_ylim(axLim_Ymin[subIDX], axLim_Ymax[subIDX])
|
||||||
|
|
||||||
|
# Add basemap
|
||||||
|
# ctx.add_basemap(ax=axes, source=ctx.providers.Esri.WorldImagery, crs=modelCRS[i], attribution=False)
|
||||||
|
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||||
|
ctx.add_basemap(axes[subIDX], source=mapbox, crs=modelCRS[i])
|
||||||
|
|
||||||
|
|
||||||
|
# cbar = plt.colorbar(smp, ax=axesFig.ravel().tolist(), label='Sand Mass [kg/m2]')
|
||||||
|
# cbar = plt.colorbar(smp, ax=axesFig.ravel().tolist(), label='Erosion/ deposition [m]')
|
||||||
|
cbar = plt.colorbar(smp, ax=axesFig.ravel().tolist(), label='Initial Bed [mNAVD88]')
|
||||||
|
|
||||||
|
plt.show()
|
||||||
|
|
||||||
|
# fig.savefig('C:/Users/arey/files/Projects/Newtown/SedFigs2/SedMass_' + runLog['Run'][i] + '.png',
|
||||||
|
# bbox_inches='tight', dpi=300)
|
||||||
|
|
||||||
|
# fig.savefig('C:/Users/arey/files/Projects/Newtown/SedFigs2/ErodeDep_' + runLog['Run'][i] + '.png',
|
||||||
|
# bbox_inches='tight', dpi=300)
|
||||||
|
|
||||||
|
# fig.savefig('C:/Users/arey/files/Projects/Newtown/SedFigs2/InitialBed_' + runLog['Run'][i] + '.png',
|
||||||
|
# bbox_inches='tight', dpi=300)
|
||||||
|
|
||||||
|
#%% Plot using DFM functions
|
||||||
|
#Cmap Path
|
||||||
|
cmap_path = 'C:/Users/arey/Repo/MATLAB_Q/Downloads/KeyColormaps/'
|
||||||
|
|
||||||
|
for i in modelPlot:
|
||||||
|
fig, axes = plt.subplots(nrows=1, ncols=1, subplot_kw={'projection': ccrs.epsg(32118)}, figsize=(6, 6))
|
||||||
|
fig.patch.set_facecolor('white')
|
||||||
|
|
||||||
|
fig.tight_layout(pad=3.0)
|
||||||
|
|
||||||
|
# Load cmaps
|
||||||
|
cmap = 'AJMR_Sed5_RevE.xml'
|
||||||
|
plotcmap = cm.make_cmap(cmap_path + cmap)
|
||||||
|
|
||||||
|
pc = plot_netmapdata(ugrid_all[i].verts, values=modelMaxShear[i][0, :],
|
||||||
|
ax=axes, linewidth=0.5, cmap=plotcmap)
|
||||||
|
|
||||||
|
axes.set_xlim(305900, 306400)
|
||||||
|
axes.set_ylim(61500, 62200)
|
||||||
|
|
||||||
|
# axes.quiver(modelX[i], modelX[i], U[i], V[i], color='w', scale=1.00)
|
||||||
|
|
||||||
|
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||||
|
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32118')
|
||||||
|
|
||||||
|
extent = axes.get_extent()
|
||||||
|
axes.set_xticks(np.linspace(extent[0], extent[1], 4))
|
||||||
|
axes.set_yticks(np.linspace(extent[2], extent[3], 4))
|
||||||
|
|
||||||
|
pc.set_clim([0, 0.145])
|
||||||
|
cbarTicks = [0, 0.0378, 0.063, 0.0826, 0.11, 0.145]
|
||||||
|
cbar = fig.colorbar(pc, ax=axes, shrink=0.95,
|
||||||
|
ticks=cbarTicks)
|
||||||
|
cbar.set_label('Total Max Shear Stress [N/m^2]')
|
||||||
|
|
||||||
|
# Add label on colorbar
|
||||||
|
cbar.ax.text(0.08, (cbarTicks[0]+cbarTicks[1])/2, 'CLAY', ha='center', va='center',
|
||||||
|
rotation=90, fontweight='bold')
|
||||||
|
cbar.ax.text(0.08, (cbarTicks[1]+cbarTicks[2])/2, 'FSILT', ha='center', va='center',
|
||||||
|
rotation=90, fontweight='bold')
|
||||||
|
cbar.ax.text(0.08, (cbarTicks[2]+cbarTicks[3])/2, 'MSILT', ha='center', va='center',
|
||||||
|
rotation=90, fontweight='bold')
|
||||||
|
cbar.ax.text(0.08, (cbarTicks[3]+cbarTicks[4])/2, 'CSILT', ha='center', va='center',
|
||||||
|
rotation=90, fontweight='bold')
|
||||||
|
cbar.ax.text(0.08, (cbarTicks[4]+cbarTicks[5])/2, 'FSAND', ha='center', va='center',
|
||||||
|
rotation=90, fontweight='bold')
|
||||||
|
|
||||||
|
plt.show()
|
||||||
|
|
||||||
|
fig.savefig('C:/Users/arey/files/Projects/Newtown/SedFigs/Shear_Class_' + runLog['Run'][i] + '.png',
|
||||||
|
bbox_inches='tight', dpi=300)
|
||||||
|
|
||||||
|
#%% Import Model results for animations
|
||||||
|
|
||||||
|
# modelPlot = [20, 22]
|
||||||
|
# modelPlot = [18, 20, 21, 22]
|
||||||
|
# modelPlot = [18, 21]
|
||||||
|
modelPlot = [25, 26]
|
||||||
|
|
||||||
|
modelSedConc = [None] * (max(modelPlot)+1)
|
||||||
|
modelMaxShear_animate = [None] * (max(modelPlot)+1)
|
||||||
|
ugrid_all = [None] * (max(modelPlot)+1)
|
||||||
|
tSteps = [None] * (max(modelPlot)+1)
|
||||||
|
|
||||||
|
for i in modelPlot:
|
||||||
|
file_nc_map = Path(runLog['Run Location'][i]) / dataPath
|
||||||
|
|
||||||
|
# Get Var info
|
||||||
|
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc_map.as_posix())
|
||||||
|
|
||||||
|
# Import
|
||||||
|
tSteps[i] = get_timesfromnc(file_nc=file_nc_map.as_posix(), varname='time')
|
||||||
|
|
||||||
|
ugrid_all[i] = get_netdata(file_nc=file_nc_map.as_posix())
|
||||||
|
modelSedConc[i] = get_ncmodeldata(file_nc=file_nc_map.as_posix(), varname='mesh2d_sedfrac_concentration',
|
||||||
|
timestep='all', station=0, layer=0) #timestep='all' OR timestep=range(0, 30)
|
||||||
|
modelMaxShear_animate[i] = get_ncmodeldata(file_nc=file_nc_map.as_posix(), varname='mesh2d_tausmax',
|
||||||
|
timestep='all')
|
||||||
|
|
||||||
|
|
||||||
|
# %% Import water levels from hist
|
||||||
|
modelHistWL = [None] * (max(modelPlot)+1)
|
||||||
|
modelHistTime = [None] * (max(modelPlot)+1)
|
||||||
|
# tSteps = [None] * (max(modelPlot)+1)
|
||||||
|
|
||||||
|
for i in modelPlot:
|
||||||
|
file_nc_hist = Path(runLog['Run Location'][i]) / histPath
|
||||||
|
|
||||||
|
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc_hist.as_posix())
|
||||||
|
|
||||||
|
# Get station names
|
||||||
|
histStations = get_hisstationlist(file_nc=file_nc_hist.as_posix(), varname='waterlevel')
|
||||||
|
|
||||||
|
# Import
|
||||||
|
modelHistTime[i] = get_timesfromnc(file_nc=file_nc_hist.as_posix(), varname='time')
|
||||||
|
modelHistWL[i] = get_ncmodeldata(file_nc=file_nc_hist.as_posix(), varname='waterlevel',
|
||||||
|
timestep='all', station=1)
|
||||||
|
|
||||||
|
|
||||||
|
#%% Sediment animations
|
||||||
|
plt.rcParams['animation.ffmpeg_path'] = \
|
||||||
|
'C:/Users/arey/Local/ffmpeg-2022-02-14-git-59c647bcf3-full_build/bin/ffmpeg.exe'
|
||||||
|
|
||||||
|
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckex9vtri0o6619p55sl5qiyv/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||||
|
x, y, arrow_length = 0.93, 0.95, 0.12
|
||||||
|
# fontprops = fm.FontProperties(size=12)
|
||||||
|
|
||||||
|
# Set model to plot
|
||||||
|
# modelPlot = [20, 22]
|
||||||
|
# modelPlot = [18, 20, 21, 22]
|
||||||
|
modelPlot = [25, 26]
|
||||||
|
cmap_path = 'C:/Users/arey/Repo/MATLAB_Q/Downloads/KeyColormaps/'
|
||||||
|
|
||||||
|
for m in modelPlot:
|
||||||
|
vmax = 0.75
|
||||||
|
vmin = 0
|
||||||
|
# vmax = 0.145
|
||||||
|
# vmin = 0
|
||||||
|
|
||||||
|
cbarTicks = [0, 0.0378, 0.063, 0.0826, 0.11, 0.145]
|
||||||
|
|
||||||
|
cmapName = 'turbo'
|
||||||
|
cmap = mpl.cm.turbo
|
||||||
|
# cmapName = 'AJMR_Sed5_RevE.xml'
|
||||||
|
# cmap = cm.make_cmap(cmap_path + cmapName)
|
||||||
|
|
||||||
|
|
||||||
|
# Zoom limits
|
||||||
|
# xLimits = [305900, 306500]
|
||||||
|
# yLimits = [61400, 62200]
|
||||||
|
|
||||||
|
# Wide Limits
|
||||||
|
xLimits = [302719.4, 306934.2]
|
||||||
|
yLimits = [60263.7, 64194.8]
|
||||||
|
|
||||||
|
# Setup Video
|
||||||
|
metadata = dict(title='NTC Sediment Animation', artist='Matplotlib',
|
||||||
|
comment='AJMR June 28, 2022')
|
||||||
|
writer = animation.FFMpegWriter(fps=2, metadata=metadata, codec='h264', bitrate=5000)
|
||||||
|
fig, axes = plt.subplots(figsize=(6, 6))
|
||||||
|
|
||||||
|
writer.setup(fig, '//srv-ott3/Projects/11934.201 Newtown Creek TPP – Privileged and Confidential/' +
|
||||||
|
'06_Models/04_Delft3D/Figures/SedConc/HQ3_Wide_RevC_Long_Sed_Cond_'
|
||||||
|
+ runLog['Run'][m] + '.mp4')
|
||||||
|
|
||||||
|
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||||
|
|
||||||
|
for i in np.arange(1, len(modelSedConc[m])-1, 1): #289
|
||||||
|
# Clear axes for video
|
||||||
|
axes.cla()
|
||||||
|
|
||||||
|
# Create new figure for stills
|
||||||
|
# fig, axes = plt.subplots(figsize=(6, 6))
|
||||||
|
|
||||||
|
# Clear inset WL Plot
|
||||||
|
# if i > 1:
|
||||||
|
# axin1.cla()
|
||||||
|
|
||||||
|
# Plot sediment
|
||||||
|
pc = plot_netmapdata(ugrid_all[m].verts, values=modelSedConc[m][i, 0, :, 0],
|
||||||
|
ax=axes, cmap=cmapName,
|
||||||
|
antialiaseds=False)
|
||||||
|
|
||||||
|
# Plot shear
|
||||||
|
# pc = plot_netmapdata(ugrid_all[m].verts, values=modelMaxShear_animate[m][i,:],
|
||||||
|
# ax=axes, cmap=cmap,
|
||||||
|
# antialiaseds=False)
|
||||||
|
|
||||||
|
# Set map limits
|
||||||
|
axes.set_xlim(xLimits[0], xLimits[1])
|
||||||
|
axes.set_ylim(yLimits[0], yLimits[1])
|
||||||
|
|
||||||
|
# Add basemap
|
||||||
|
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32118')
|
||||||
|
|
||||||
|
# Set map ticks
|
||||||
|
axes.set_xticks(np.linspace(xLimits[0], xLimits[1], 4))
|
||||||
|
axes.set_yticks(np.linspace(yLimits[0], yLimits[1], 4))
|
||||||
|
|
||||||
|
# Color Limits
|
||||||
|
pc.set_clim([vmin, vmax])
|
||||||
|
|
||||||
|
# Add title
|
||||||
|
axes.title.set_text('Bottom Sediment Concentration at: ' + tSteps[m][i].strftime("%Y/%m/%d %H:%M"))
|
||||||
|
# axes.title.set_text('Total Max Shear Stress at: ' + str(tSteps[m][i]))
|
||||||
|
|
||||||
|
# Add inset wl plot
|
||||||
|
axin1 = axes.inset_axes([0.1, 0.1, 0.4, 0.15])
|
||||||
|
axin1.plot(modelHistTime[m], modelHistWL[m])
|
||||||
|
# Add current point
|
||||||
|
# Find closest time
|
||||||
|
abs_deltas_from_target_date = np.absolute(modelHistTime[m] - tSteps[m][i])
|
||||||
|
axin1.scatter(modelHistTime[m][np.argmin(abs_deltas_from_target_date)], modelHistWL[m][np.argmin(abs_deltas_from_target_date)], 10, 'r')
|
||||||
|
|
||||||
|
# axin1.set_xticks([modelHistTime[m][0], modelHistTime[m][len(modelHistTime[m])-1]])
|
||||||
|
axin1.set_xticks([])
|
||||||
|
axin1.set_yticks([])
|
||||||
|
|
||||||
|
plt.setp(axin1.get_xticklabels(), backgroundcolor="white")
|
||||||
|
plt.setp(axin1.get_yticklabels(), backgroundcolor="white")
|
||||||
|
|
||||||
|
if i == 1: #i < 1000
|
||||||
|
fig.subplots_adjust(right=0.8)
|
||||||
|
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
|
||||||
|
|
||||||
|
# Create colorbar axis
|
||||||
|
# cax = plt.axes([0.82, 0.25, 0.04, 0.5])
|
||||||
|
cax = plt.axes([0.85, 0.15, 0.04, 0.7])
|
||||||
|
|
||||||
|
# Add colorbar with designated tick marks
|
||||||
|
# cb1 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
|
||||||
|
# norm=norm,
|
||||||
|
# orientation='vertical',
|
||||||
|
# ticks=cbarTicks)
|
||||||
|
|
||||||
|
# Add colorbar without designated tick marks
|
||||||
|
cb1 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
|
||||||
|
norm=norm,
|
||||||
|
orientation='vertical')
|
||||||
|
|
||||||
|
# Colorbar lavel
|
||||||
|
cb1.set_label('Sediment Concentration [$kg/m^3$]')
|
||||||
|
# cb1.set_label('Total Max Shear Stress [N/m^2]')
|
||||||
|
|
||||||
|
# Add label on colorbar
|
||||||
|
# cb1.ax.text(0.08, (cbarTicks[0] + cbarTicks[1]) / 2, 'CLAY', ha='center', va='center',
|
||||||
|
# rotation=90, fontweight='bold')
|
||||||
|
# cb1.ax.text(0.08, (cbarTicks[1] + cbarTicks[2]) / 2, 'FSILT', ha='center', va='center',
|
||||||
|
# rotation=90, fontweight='bold')
|
||||||
|
# cb1.ax.text(0.08, (cbarTicks[2] + cbarTicks[3]) / 2, 'MSILT', ha='center', va='center',
|
||||||
|
# rotation=90, fontweight='bold')
|
||||||
|
# cb1.ax.text(0.08, (cbarTicks[3] + cbarTicks[4]) / 2, 'CSILT', ha='center', va='center',
|
||||||
|
# rotation=90, fontweight='bold')
|
||||||
|
# cb1.ax.text(0.08, (cbarTicks[4] + cbarTicks[5]) / 2, 'FSAND', ha='center', va='center',
|
||||||
|
# rotation=90, fontweight='bold')
|
||||||
|
|
||||||
|
|
||||||
|
# Change label font size for only the primary axis
|
||||||
|
for item in ([axes.xaxis.label, axes.yaxis.label] +
|
||||||
|
axes.get_xticklabels() + axes.get_yticklabels()):
|
||||||
|
item.set_fontsize(4)
|
||||||
|
|
||||||
|
|
||||||
|
# Save video frame
|
||||||
|
writer.grab_frame()
|
||||||
|
plt.show()
|
||||||
|
print(i)
|
||||||
|
|
||||||
|
# Save stills
|
||||||
|
fig.savefig('//srv-ott3/Projects/11934.201 Newtown Creek TPP – Privileged and Confidential/' +
|
||||||
|
'06_Models/04_Delft3D/Figures/SedConc/Wide_RevC_SedConc_' +
|
||||||
|
runLog['Run'][m] + '_Frame_' + str(i) + '.png',
|
||||||
|
bbox_inches='tight', dpi=300)
|
||||||
|
# fig.savefig('//srv-ott3/Projects/11934.201 Newtown Creek TPP – Privileged and Confidential/' +
|
||||||
|
# '06_Models/04_Delft3D/Figures/ShearStress/Wide_ShearStress_' +
|
||||||
|
# runLog['Run'][m] + '_Frame_' + str(i) + '.png',
|
||||||
|
# bbox_inches='tight', dpi=300)
|
||||||
|
|
||||||
|
# Save video
|
||||||
|
writer.finish()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
#%% Save Sediment Geotiff
|
||||||
|
|
||||||
|
# Create mask within bounds
|
||||||
|
boundSelect = 2
|
||||||
|
croppedGridMask = (d3dfm_DataArray[i].mesh2d_face_x >= axLim_Xmin[boundSelect]) &\
|
||||||
|
(d3dfm_DataArray[i].mesh2d_face_x <= axLim_Xmax[boundSelect]) &\
|
||||||
|
(d3dfm_DataArray[i].mesh2d_face_y >= axLim_Ymin[boundSelect]) &\
|
||||||
|
(d3dfm_DataArray[i].mesh2d_face_y <= axLim_Ymax[boundSelect])
|
||||||
|
croppedGridMask = croppedGridMask.compute()
|
||||||
|
|
||||||
|
# Step through time steps
|
||||||
|
for sedTstep in range(105, 120):
|
||||||
|
# Rasterize sediment concentration within bounds
|
||||||
|
sedConcTif = dfmt.rasterize_ugrid(d3dfm_DataArray[i]['mesh2d_sedfrac_concentration'].isel(
|
||||||
|
time=sedTstep, mesh2d_nLayers=4, nSedSus=0).where(croppedGridMask, drop=True).to_dataset(),
|
||||||
|
resolution=2)
|
||||||
|
|
||||||
|
# Add CRS
|
||||||
|
sedConcTif.rio.write_crs("epsg:32118", inplace=True)
|
||||||
|
sedConcTif.rio.to_raster('C:/Users/arey/files/Projects/Newtown/SedFigs2/GeoTiff_RevB_'
|
||||||
|
+ 'Sed_Conc4_Time_' + str(sedTstep) + '.tif')
|
||||||
|
|
@ -0,0 +1,8 @@
|
||||||
|
<?xml version="1.0" encoding="UTF-8"?>
|
||||||
|
<module type="PYTHON_MODULE" version="4">
|
||||||
|
<component name="NewModuleRootManager">
|
||||||
|
<content url="file://$MODULE_DIR$" />
|
||||||
|
<orderEntry type="inheritedJdk" />
|
||||||
|
<orderEntry type="sourceFolder" forTests="false" />
|
||||||
|
</component>
|
||||||
|
</module>
|
||||||
Loading…
Reference in New Issue