Jan 2022 Baird Python Update
This commit is contained in:
Alexander Rey
parent
531a5fa026
commit
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# Default ignored files
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/shelf/
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/workspace.xml
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# Datasource local storage ignored files
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/dataSources/
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/dataSources.local.xml
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# Editor-based HTTP Client requests
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/httpRequests/
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<?xml version="1.0" encoding="UTF-8"?>
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<module type="PYTHON_MODULE" version="4">
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<component name="NewModuleRootManager">
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<content url="file://$MODULE_DIR$" />
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<orderEntry type="inheritedJdk" />
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<orderEntry type="sourceFolder" forTests="false" />
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</component>
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</module>
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<component name="InspectionProjectProfileManager">
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<profile version="1.0">
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<option name="myName" value="Project Default" />
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<inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
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<option name="ignoredIdentifiers">
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<list>
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<option value="bool.*" />
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<option value="geopandas.io.file" />
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</list>
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</option>
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</inspection_tool>
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</profile>
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</component>
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<component name="InspectionProjectProfileManager">
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<settings>
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<option name="USE_PROJECT_PROFILE" value="false" />
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<version value="1.0" />
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</settings>
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</component>
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (D3DFM)" project-jdk-type="Python SDK" />
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</project>
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="ProjectModuleManager">
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<modules>
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<module fileurl="file://$PROJECT_DIR$/.idea/EWR_D3D.iml" filepath="$PROJECT_DIR$/.idea/EWR_D3D.iml" />
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</modules>
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</component>
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</project>
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="VcsDirectoryMappings">
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<mapping directory="$PROJECT_DIR$/.." vcs="Git" />
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</component>
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</project>
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="PySciProjectComponent">
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<option name="PY_SCI_VIEW" value="true" />
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<option name="PY_SCI_VIEW_SUGGESTED" value="true" />
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</component>
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</project>
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<content url="file://$MODULE_DIR$">
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<excludeFolder url="file://$MODULE_DIR$/data" />
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</content>
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<orderEntry type="jdk" jdkName="Python 3.8 (BairdBase)" jdkType="Python SDK" />
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<orderEntry type="jdk" jdkName="Python 3.8 (geopandas_forge_mustique)" jdkType="Python SDK" />
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<orderEntry type="sourceFolder" forTests="false" />
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</component>
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<component name="PyDocumentationSettings">
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@ -1,4 +1,4 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (BairdBase)" project-jdk-type="Python SDK" />
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (geopandas_forge_mustique)" project-jdk-type="Python SDK" />
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</project>
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#%% Script to read in GFS data at a specific point
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# Author: Alexander Rey
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# November 18, 2021
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#%% Project Setup
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import os
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import sys
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import pandas as pd
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import numpy as np
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import matplotlib.pyplot as plt
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from xarray.backends import NetCDF4DataStore
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import xarray as xr
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from datetime import datetime, timedelta
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from netCDF4 import num2date
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from metpy.units import units
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from siphon.catalog import TDSCatalog
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#%% Helper function for finding proper time variable
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def find_time_var(var, time_basename='time'):
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for coord_name in var.coords:
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if coord_name.startswith(time_basename):
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return var.coords[coord_name]
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raise ValueError('No time variable found for ' + var.name)
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#%% GFS Import
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# List hours to download
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hours = [0, 6, 12, 18]
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# List variables to download
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var = ['Temperature_surface', 'Wind_speed_gust_surface',
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'u-component_of_wind_height_above_ground', 'v-component_of_wind_height_above_ground']
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# Precipitation variable
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var_precp = ['Total_precipitation_surface_6_Hour_Accumulation']
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# Setup lists for data
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temp_1d = []
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gust_1d = []
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wndu_1d = []
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wndv_1d = []
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prep_1d = []
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time_1d = []
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# Set times to download
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startdate = datetime(year=2021, month=10, day=1, hour=0, minute=0, second=0)
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enddate = datetime(year=2021, month=10, day=7, hour=0, minute=0, second=0)
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date_list = pd.date_range(startdate, enddate, freq='6H')
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# Loop through dates
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for date in date_list:
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# Base URL for 0.5 degree GFS data
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best_gfs = TDSCatalog('https://www.ncei.noaa.gov/thredds/catalog/model-gfs-g4-anl-files/' +
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date.strftime('%Y%m') + '/' + date.strftime('%Y%m%d') + '/' + 'catalog.xml')
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# Generate URLs for specific grib file
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best_ds = best_gfs.datasets['gfs_4_'+date.strftime('%Y%m%d_%H%M')+'_000.grb2']
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best_ds_precp = best_gfs.datasets['gfs_4_'+date.strftime('%Y%m%d_%H%M')+'_006.grb2']
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# Format the query parameters
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ncss = best_ds.subset()
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query = ncss.query()
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ncss_precp = best_ds_precp.subset()
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query_precp = ncss_precp.query()
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# Extract data from specific point
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query.lonlat_point(-75.6972, 45.4215).time(date)
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query.accept('netcdf')
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query.variables(var[0], var[1], var[2], var[3])
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query.vertical_level(0) #10 m
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data = ncss.get_data(query)
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data = xr.open_dataset(NetCDF4DataStore(data), drop_variables='height_above_ground4')
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query_precp.lonlat_point(-75.6972, 45.4215).time(date + timedelta(hours=6))
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query_precp.accept('netcdf')
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query_precp.variables(var_precp[0])
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query_precp.vertical_level(0) #10 m
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data_precp = ncss_precp.get_data(query_precp)
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data_precp = xr.open_dataset(NetCDF4DataStore(data_precp))
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temp_3d = data[var[0]]
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gust_3d = data[var[1]]
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wndu_3d = data[var[2]]
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wndv_3d = data[var[3]]
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prep_3d = data_precp[var_precp[0]]
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# Read the individual point (with units) and append to the list
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temp_1d.append(temp_3d.metpy.unit_array.squeeze())
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gust_1d.append(gust_3d.metpy.unit_array.squeeze())
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wndu_1d.append(wndu_3d.metpy.unit_array.squeeze())
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wndv_1d.append(wndv_3d.metpy.unit_array.squeeze())
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prep_1d.append(prep_3d.metpy.unit_array.squeeze())
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time_1d.append(find_time_var(temp_3d))
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#%% Create a new figure
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fig = plt.figure(figsize=(15, 12))
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fig.patch.set_facecolor('white')
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plt.plot([i.values[0] for i in time_1d], [i.m.item(0) for i in temp_1d])
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plt.show()
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#%% Project Setup
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import os
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import pandas as pd
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import geopandas as gp
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from scipy.signal import argrelextrema
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import numpy as np
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import math
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from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar, AnchoredDirectionArrows
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import matplotlib.pyplot as plt
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import matplotlib.font_manager as fm
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import matplotlib as mpl
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import cartopy.crs as ccrs
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import contextily as ctx
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import cmocean.cm as cmo
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from shapely.geometry import Point, LineString
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from xarray.backends import NetCDF4DataStore
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import xarray as xr
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from datetime import datetime, timedelta
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from netCDF4 import num2date
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from metpy.units import units
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import matplotlib.pyplot as plt
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import cartopy.crs as ccrs
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import cartopy.feature as cfeature
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from metpy.plots import ctables
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from siphon.catalog import TDSCatalog
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#%% Helper function for finding proper time variable
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def find_time_var(var, time_basename='time'):
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for coord_name in var.coords:
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if coord_name.startswith(time_basename):
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return var.coords[coord_name]
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raise ValueError('No time variable found for ' + var.name)
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#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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importPaths = ['C:/Users/arey/files/Projects/West Coast/Pre_Construction/Great House/',
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'C:/Users/arey/files/Projects/West Coast/Pre_Construction/Greensleeves/',
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'C:/Users/arey/files/Projects/West Coast/Pre_Construction/Old Queens Fort/',
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'C:/Users/arey/files/Projects/West Coast/Construction/Great House/',
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'C:/Users/arey/files/Projects/West Coast/Construction/Greensleeves/',
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'C:/Users/arey/files/Projects/West Coast/Construction/Old Queens Fort/',
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'C:/Users/arey/files/Projects/West Coast/Post_Construction/Great House/',
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'C:/Users/arey/files/Projects/West Coast/Post_Construction/Greensleeves/',
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'C:/Users/arey/files/Projects/West Coast/Post_Construction/Old Queens Fort/',
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'C:/Users/arey/files/Projects/West Coast/Monitoring_Nov/Great House/',
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'C:/Users/arey/files/Projects/West Coast/Monitoring_Nov/Greensleeves/',
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'C:/Users/arey/files/Projects/West Coast/Monitoring_Nov/Old Queens Fort/']
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siteNames = ['Great House',
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'Greensleeves',
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'Old Queens Fort',
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'Great House',
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'Greensleeves',
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'Old Queens Fort',
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'Great House',
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'Greensleeves',
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'Old Queens Fort',
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'Great House',
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'Greensleeves',
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'Old Queens Fort']
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timeLabels= ['Before Construction',
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'Before Construction',
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'Before Construction',
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'During Construction',
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'During Construction',
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'During Construction',
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'After Construction',
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'After Construction',
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'After Construction',
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'Monitoring',
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'Monitoring',
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'Monitoring']
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wave_bts_file = [
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/holetown_mid_15m',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/holetown_mid_15m',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/spawnee_mid_27m.bts',
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'T:/Alexander/WestCoast/Barbados Nowcast 2021-09-15 to 2021-11-15/holetown_mid_15m',
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None,
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None,
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None]
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for s in range(9,13):
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## Define master import path
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importPath = importPaths[s]
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siteName = siteNames[s]
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timeLabel = timeLabels[s]
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importFiles = os.listdir(importPath)
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# Initialize import variables
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RBR_File = None
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JFE_File = None
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GPS_File = None
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for i in range(0, len(importFiles)):
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if '.xlsx' in importFiles[i] and 'Summary' not in importFiles[i]:
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RBR_File = importFiles[i]
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elif '_A.csv' in importFiles[i] and 'Summary' not in importFiles[i]:
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JFE_File = importFiles[i]
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elif '.csv' in importFiles[i] and 'Summary' not in importFiles[i]:
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GPS_File = importFiles[i]
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#%% RBR Import Data
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if RBR_File is not None:
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RBR_Obs = pd.read_excel(importPath + RBR_File,
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sheet_name='Data', skiprows=0, header=1)
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#%% JFE Import Data
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if JFE_File is not None:
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JFE_Obs = pd.read_csv(importPath + JFE_File, skiprows=30)
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#%% GPS Import Data
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if GPS_File is not None:
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GPS = pd.read_csv(importPath + GPS_File,
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header=None, names=['Index', 'Date1', 'Time1', 'Date2', 'Time2', 'Northing', 'North', 'Easting', 'East', 'Var1', 'Var2'])
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#convert GPS data to geodataframe
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GPS_gdf = gp.GeoDataFrame(GPS, geometry=gp.points_from_xy(-GPS.Easting, GPS.Northing, crs="EPSG:4326"))
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GPS_gdf['DateTime'] = pd.to_datetime(GPS_gdf['Date2'].astype(str) + ' ' + GPS_gdf['Time2'].astype(str))
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GPS_gdf.set_index('DateTime', inplace=True)
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# Convert to UTM
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GPS_gdf.geometry = GPS_gdf.geometry.to_crs("EPSG:32621")
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else:
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# Synthesize GPS data for great house
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GPS_gdf = gp.read_file('C:/Users/arey/files/Projects/West Coast/GreatHousePath_R3.shp')
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GPS_gdf['DateTime'] = pd.date_range(pd.to_datetime(RBR_Obs['Time'].iloc[0]),
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pd.to_datetime(RBR_Obs['Time'].iloc[-1]),
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periods=len(GPS_gdf)).values
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GPS_gdf.set_index('DateTime', inplace=True)
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#%% Read in site shapefile
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siteShp = gp.read_file('C:/Users/arey/files/Projects/West Coast/SitePolygons.shp')
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siteShp.geometry = siteShp.geometry.to_crs("EPSG:32621")
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#%% Merge GPS to RBR
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# Process RBR into datetime
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if RBR_File is not None:
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RBR_Obs['DateTime'] = pd.to_datetime(RBR_Obs['Time'])
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RBR_Obs.set_index('DateTime', inplace=True)
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# Merge with GPS as dataframe
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RBR_Obs_geo = pd.merge_asof(RBR_Obs, GPS_gdf,
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left_index=True, right_index=True, direction='nearest', tolerance=pd.Timedelta('300s'))
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RBR_Obs_geo = gp.GeoDataFrame(RBR_Obs_geo, geometry=RBR_Obs_geo.geometry, crs="EPSG:32621")
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#%% Merge GPS to JFE
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if JFE_File is not None:
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# Process JFE into datetime
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JFE_Obs['DateTime'] = pd.to_datetime(JFE_Obs['Date'])
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JFE_Obs.set_index('DateTime', inplace=True)
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# Merge with GPS as dataframe
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JFE_Obs_geo = pd.merge_asof(JFE_Obs, GPS_gdf, left_index=True, right_index=True, direction='nearest', tolerance=pd.Timedelta('60s'))
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JFE_Obs_geo = gp.GeoDataFrame(JFE_Obs_geo, geometry=JFE_Obs_geo.geometry, crs="EPSG:32621")
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#%% Find and setup key plotting details
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# Shaded Water
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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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# Sat water
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# mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckekcw3pn08am19qmqbhtq8sb/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
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if siteName == 'Great House':
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axXlim = (213210.7529575412, 213562.64172686986)
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axYlim = (1464769.2243017585, 1465135.2219089477)
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GFS_Lon = -59.6441
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GFS_Lat = 13.2372
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RBR_Obs_geo['inArea'] = RBR_Obs_geo.within(siteShp.iloc[2, 1])
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elif siteName == 'Greensleeves':
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axXlim = (213269.99233348924, 213648.1643157148)
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# axYlim = (1463378.1020314451, 1463843.5442048472)
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axYlim = (1463378.1020314451, 1463950.5442048472)
|
||||
GFS_Lon = -59.6428
|
||||
GFS_Lat = 13.2289
|
||||
RBR_Obs_geo['inArea'] = RBR_Obs_geo.within(siteShp.iloc[1, 1])
|
||||
elif siteName == 'Old Queens Fort':
|
||||
axXlim = (213368.59866770002, 213745.6997016811)
|
||||
axYlim = (1460192.707288096, 1460672.371780407)
|
||||
GFS_Lon = -59.6419
|
||||
GFS_Lat = 13.1960
|
||||
RBR_Obs_geo['inArea'] = RBR_Obs_geo.within(siteShp.iloc[0, 1])
|
||||
|
||||
|
||||
# Set min and max times using conductivity
|
||||
# if JFE_File is None:
|
||||
if RBR_Obs_geo['inArea'].any():
|
||||
# First and last times from area in shapefile
|
||||
minTime = RBR_Obs_geo[RBR_Obs_geo['inArea']==True].iloc[0, 0]
|
||||
maxTime = RBR_Obs_geo[RBR_Obs_geo['inArea']==True].iloc[-1, 0]
|
||||
else:
|
||||
# First and last times if no GPS data
|
||||
minTime = RBR_Obs_geo.iloc[20, 0]
|
||||
maxTime = RBR_Obs_geo.iloc[-20, 0]
|
||||
# else:
|
||||
# minTime = (RBR_Obs['Conductivity ']>5).idxmax()
|
||||
# minTime = minTime + timedelta(seconds=30)
|
||||
# maxTime = ((RBR_Obs['Conductivity ']<5) & (RBR_Obs['Time']>minTime)).idxmax()
|
||||
# maxTime = maxTime - timedelta(seconds=30)
|
||||
# obsPeriod = maxTime-minTime
|
||||
#
|
||||
# if (obsPeriod.seconds<180) | (maxTime<minTime):
|
||||
# minTime = ((RBR_Obs['Conductivity ']>5) & (RBR_Obs['Time']>(minTime+timedelta(seconds=180)))).idxmax()
|
||||
# minTime = minTime + timedelta(seconds=30)
|
||||
# maxTime = ((RBR_Obs['Conductivity ']<5) & (RBR_Obs['Time']>minTime)).idxmax()
|
||||
# maxTime = maxTime - timedelta(seconds=30)
|
||||
|
||||
metDate = minTime - timedelta(
|
||||
hours = minTime.hour % 6,
|
||||
minutes=minTime.minute,
|
||||
seconds=minTime.second,
|
||||
microseconds=minTime.microsecond)
|
||||
|
||||
|
||||
#%% GFS Met Import
|
||||
var = ['Temperature_surface', 'Wind_speed_gust_surface',
|
||||
'u-component_of_wind_height_above_ground', 'v-component_of_wind_height_above_ground']
|
||||
var_precp = ['Total_precipitation_surface_6_Hour_Accumulation']
|
||||
|
||||
temp_1d = []
|
||||
gust_1d = []
|
||||
wndu_1d = []
|
||||
wndv_1d = []
|
||||
prep_1d = []
|
||||
time_1d = []
|
||||
|
||||
# Set times to download
|
||||
startdate = metDate - timedelta(hours=18)
|
||||
enddate = metDate + timedelta(hours=6)
|
||||
date_list = pd.date_range(startdate, enddate, freq='6H')
|
||||
|
||||
# Loop through dates
|
||||
for date in date_list:
|
||||
# Base URL for 0.5 degree GFS data
|
||||
best_gfs = TDSCatalog('https://www.ncei.noaa.gov/thredds/catalog/model-gfs-g4-anl-files/' +
|
||||
date.strftime('%Y%m') + '/' + date.strftime('%Y%m%d') + '/' + 'catalog.xml')
|
||||
|
||||
# Generate URLs for specific grib file
|
||||
best_ds = best_gfs.datasets['gfs_4_'+date.strftime('%Y%m%d_%H%M')+'_000.grb2']
|
||||
best_ds_precp = best_gfs.datasets['gfs_4_'+date.strftime('%Y%m%d_%H%M')+'_006.grb2']
|
||||
|
||||
# Format the query parameters
|
||||
ncss = best_ds.subset()
|
||||
query = ncss.query()
|
||||
|
||||
ncss_precp = best_ds_precp.subset()
|
||||
query_precp = ncss_precp.query()
|
||||
|
||||
# Extract data from specific point
|
||||
query.lonlat_point(GFS_Lon, GFS_Lat).time(date)
|
||||
query.accept('netcdf')
|
||||
query.variables(var[0], var[1], var[2], var[3])
|
||||
query.vertical_level(10)
|
||||
|
||||
data = ncss.get_data(query)
|
||||
data = xr.open_dataset(NetCDF4DataStore(data), drop_variables='height_above_ground4')
|
||||
|
||||
query_precp.lonlat_point(GFS_Lon, GFS_Lat).time(date + timedelta(hours=6))
|
||||
query_precp.accept('netcdf')
|
||||
query_precp.variables(var_precp[0])
|
||||
|
||||
|
||||
data_precp = ncss_precp.get_data(query_precp)
|
||||
data_precp = xr.open_dataset(NetCDF4DataStore(data_precp))
|
||||
|
||||
temp_3d = data[var[0]]
|
||||
gust_3d = data[var[1]]
|
||||
wndu_3d = data[var[2]]
|
||||
wndv_3d = data[var[3]]
|
||||
prep_3d = data_precp[var_precp[0]]
|
||||
|
||||
# Read the individual point (with units) and append to the list
|
||||
temp_1d.append(temp_3d.metpy.unit_array.squeeze())
|
||||
gust_1d.append(gust_3d.metpy.unit_array.squeeze())
|
||||
wndu_1d.append(wndu_3d.metpy.unit_array.squeeze())
|
||||
wndv_1d.append(wndv_3d.metpy.unit_array.squeeze())
|
||||
prep_1d.append(prep_3d.metpy.unit_array.squeeze())
|
||||
time_1d.append(find_time_var(temp_3d))
|
||||
|
||||
#%% Process Met Data
|
||||
# 24h Precipitation Total
|
||||
# Time weighted average of last two points for everything else
|
||||
|
||||
met_prep = prep_1d[0] + prep_1d[1] + prep_1d[2] + prep_1d[3]
|
||||
|
||||
timeWeight1 = minTime-metDate
|
||||
timeWeight2 = (metDate+timedelta(hours=6))-minTime
|
||||
|
||||
timeWeight1 = timeWeight1.seconds/21600
|
||||
timeWeight2 = timeWeight2.seconds/21600
|
||||
|
||||
met_gust = gust_1d[3] * timeWeight1 + gust_1d[4] * timeWeight2
|
||||
met_temp = temp_1d[3] * timeWeight1 + temp_1d[4] * timeWeight2
|
||||
met_wind = math.sqrt((wndv_1d[3].m.item(0) * timeWeight1 + wndv_1d[4].m.item(0)* timeWeight2) ** 2 +
|
||||
(wndu_1d[3].m.item(0) * timeWeight1 + wndu_1d[4].m.item(0)* timeWeight2) **2 )
|
||||
met_wdir = math.degrees(math.atan2(
|
||||
wndv_1d[3].m.item(0) * timeWeight1 + wndv_1d[4].m.item(0)* timeWeight2,
|
||||
wndu_1d[3].m.item(0) * timeWeight1 + wndu_1d[4].m.item(0)* timeWeight2)) % 360
|
||||
|
||||
#%% Read in wave conditions from BTS file
|
||||
if wave_bts_file[s] is not None:
|
||||
if siteName == 'Great House':
|
||||
wave_bts = pd.read_csv(wave_bts_file[s],
|
||||
names=['date', 'time', 'HM0', 'TP', 'TM', 'MWD', 'DPK', 'HSWL', 'TSWL', 'DPSWL', 'HSEA', 'TSEA', 'DPSEA'],
|
||||
header=0, skiprows=22, delim_whitespace=True)
|
||||
wave_bts['datetime'] = pd.to_datetime(wave_bts['date'] + ' ' + wave_bts['time'])
|
||||
wave_bts.set_index('datetime', inplace=True)
|
||||
|
||||
|
||||
met_hmo = wave_bts.iloc[wave_bts.index.get_loc(minTime, method='nearest'), :].HM0
|
||||
met_tp = wave_bts.iloc[wave_bts.index.get_loc(minTime, method='nearest'), :].TP
|
||||
met_mwd = wave_bts.iloc[wave_bts.index.get_loc(minTime, method='nearest'), :].MWD
|
||||
else:
|
||||
met_hmo = -999
|
||||
met_tp = -999
|
||||
met_mwd = -999
|
||||
|
||||
|
||||
#%% Plot time series for Geo data
|
||||
fontprops = fm.FontProperties(size=25)
|
||||
|
||||
if JFE_File is None:
|
||||
fig, axesTMP = plt.subplots(nrows=1, ncols=1, figsize=(19, 5), constrained_layout=True)
|
||||
|
||||
RBRparam = ['Turbidity ']
|
||||
RBRparamName = ['Turbidity [NTU]']
|
||||
RBRparmCmap = [cmo.turbid]
|
||||
RBRparamMin = [0.0]
|
||||
RBRparamMax = [60.0]
|
||||
|
||||
dataTable = np.zeros([9, 4])
|
||||
roundIDX = [1, 1, 0, 1, 1, 1, 1, 1]
|
||||
axes = []
|
||||
axes.append(axesTMP)
|
||||
else:
|
||||
fig, axes = plt.subplots(nrows=7, ncols=1, figsize=(19, 25), constrained_layout=True)
|
||||
dataTable = np.zeros([15, 4])
|
||||
roundIDX = [1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1]
|
||||
|
||||
RBRparam = ['Depth ', 'Salinity ', 'Dissolved O₂ saturation ', 'Temperature ']
|
||||
RBRparamName = ['Depth [m]', 'Salinity [PSU]', 'Dissolved O₂ saturation [%]', 'Temperature [degC]']
|
||||
RBRparmCmap = [cmo.deep, 'cividis', cmo.dense, cmo.thermal]
|
||||
RBRparamMin = [0.0, 34.0, 32.5, 29.0]
|
||||
RBRparamMax = [1.0, 36.0, 34.0, 31.0]
|
||||
|
||||
JFEparam = ['Turb. -M[FTU]', 'Chl-Flu.[ppb]', 'Chl-a[ug/l]']
|
||||
JFEparamName = ['Turbidity [FTU]', 'Chl-Flu. [ppb]', 'Chl-a [ug/l]']
|
||||
JFEparamMin = [0.0, 0.0, 0.0]
|
||||
JFEparamMax = [20.0, 1.0, 1.0]
|
||||
|
||||
|
||||
fig.patch.set_facecolor('white')
|
||||
# fig.tight_layout(pad=1.05)
|
||||
|
||||
fontprops = fm.FontProperties(size=25)
|
||||
|
||||
dataTable[0, 0] = met_temp.m.item(0)-272.15
|
||||
dataTable[1, 0] = met_wind
|
||||
dataTable[2, 0] = met_wdir
|
||||
dataTable[3, 0] = met_prep.m.item(0)
|
||||
dataTable[4, 0] = met_hmo
|
||||
dataTable[5, 0] = met_tp
|
||||
dataTable[6, 0] = met_mwd
|
||||
|
||||
ilocs_max = []
|
||||
ilocs_max_pts = []
|
||||
RBR_mask = []
|
||||
JFE_mask = []
|
||||
|
||||
for paramIDX, param in enumerate(RBRparam):
|
||||
RBR_Obs_geo.loc[minTime:maxTime, param].plot(
|
||||
ax=axes[paramIDX], label='1 Second Observations', color='lightgrey') # Note the space in the col name
|
||||
|
||||
# Create mask for RBR data based on time and parameter minimum
|
||||
RBR_mask.append(((RBR_Obs_geo.index>minTime) &
|
||||
(RBR_Obs_geo.index<maxTime) &
|
||||
(RBR_Obs_geo[param]>RBRparamMin[paramIDX])))
|
||||
|
||||
RBR_smoothed = RBR_Obs_geo.loc[RBR_mask[paramIDX], param].rolling(
|
||||
60, win_type='nuttall',center=True).mean()
|
||||
|
||||
RBR_smoothed.plot(
|
||||
ax=axes[paramIDX], label='1 Minute Average', color='black',
|
||||
linewidth=3)
|
||||
|
||||
# Find the local maximums for Turbidity
|
||||
if param == 'Turbidity ':
|
||||
ilocs_max.append(argrelextrema(RBR_smoothed.values,
|
||||
np.greater_equal, order=40, mode='wrap')[0])
|
||||
|
||||
# Add start and end points?
|
||||
# ilocs_max = np.insert(ilocs_max, 0, 10)
|
||||
# ilocs_max[-1] = len(RBR_smoothed.values)-10
|
||||
ilocs_max_pts.append(RBR_smoothed.iloc[ilocs_max[paramIDX]].index.values)
|
||||
|
||||
# Add labels if GPS data is available
|
||||
if GPS_File is not None:
|
||||
axes[paramIDX].scatter(RBR_smoothed.iloc[
|
||||
ilocs_max[paramIDX]].index, np.ones(len(ilocs_max[paramIDX])) * 30, 75,
|
||||
color='blue')
|
||||
for a in range(0, len(ilocs_max[paramIDX])):
|
||||
axes[paramIDX].annotate(str(a+1), (ilocs_max_pts[paramIDX][a], 30), fontsize=30)
|
||||
else:
|
||||
ilocs_max.append(None)
|
||||
ilocs_max_pts.append(None)
|
||||
|
||||
# dataTable[paramIDX+7, 0] = RBR_Obs_geo.loc[minTime:maxTime, param].mean(skipna=True)
|
||||
# dataTable[paramIDX+7, 1] = RBR_Obs_geo.loc[minTime:maxTime, param].std(skipna=True)
|
||||
# dataTable[paramIDX+7, 2] = max(RBR_Obs_geo.loc[minTime:maxTime, param].min(skipna=True), 0)
|
||||
# dataTable[paramIDX+7, 3] = RBR_Obs_geo.loc[minTime:maxTime, param].max(skipna=True)
|
||||
dataTable[paramIDX+7, 0] = RBR_smoothed.mean(skipna=True)
|
||||
dataTable[paramIDX+7, 1] = RBR_smoothed.std(skipna=True)
|
||||
dataTable[paramIDX+7, 2] = max(RBR_smoothed.min(skipna=True), 0)
|
||||
dataTable[paramIDX+7, 3] = RBR_smoothed.max(skipna=True)
|
||||
|
||||
axes[paramIDX].set_ylabel(RBRparamName[paramIDX])
|
||||
axes[paramIDX].set_title('RBR: ' + RBRparamName[paramIDX])
|
||||
axes[paramIDX].set_xlabel('')
|
||||
axes[paramIDX].set_ylim(RBRparamMin[paramIDX], RBRparamMax[paramIDX])
|
||||
axes[paramIDX].legend(loc='upper right')
|
||||
|
||||
if JFE_File is not None:
|
||||
for paramIDX, param in enumerate(JFEparam):
|
||||
JFE_Obs_geo.loc[minTime:maxTime, param].plot(
|
||||
ax=axes[paramIDX+4], label='15 Second Observations', color='lightgrey')
|
||||
|
||||
JFE_mask.append(((JFE_Obs_geo.index > minTime) &
|
||||
(JFE_Obs_geo.index < maxTime) &
|
||||
(JFE_Obs_geo[param] > JFEparamMin[paramIDX])))
|
||||
|
||||
JFE_smoothed = JFE_Obs_geo.loc[JFE_mask[paramIDX], param].rolling(
|
||||
20, win_type='nuttall', center=True).mean()
|
||||
|
||||
JFE_smoothed.plot(
|
||||
ax=axes[paramIDX+4], label='1 Minute Average', color='black',
|
||||
linewidth=3)
|
||||
|
||||
|
||||
# Find the local maximums for Turbidity
|
||||
if param == 'Turb. -M[FTU]':
|
||||
ilocs_max.append(argrelextrema(JFE_smoothed.values,
|
||||
np.greater_equal, order=60, mode='wrap')[0])
|
||||
|
||||
# Add start and end points?
|
||||
# ilocs_max = np.insert(ilocs_max, 0, 10)
|
||||
# ilocs_max[-1] = len(RBR_smoothed.values)-10
|
||||
ilocs_max_pts.append(JFE_smoothed.iloc[ilocs_max[paramIDX+4]].index.values)
|
||||
|
||||
# Add labels if GPS data is available
|
||||
if GPS_File is not None:
|
||||
axes[paramIDX+4].scatter(JFE_smoothed.iloc[
|
||||
ilocs_max[paramIDX+4]].index, np.ones(len(ilocs_max[paramIDX+4])) * 10, 75,
|
||||
color='blue')
|
||||
for a in range(0, len(ilocs_max[paramIDX+4])):
|
||||
axes[paramIDX+4].annotate(str(a + 1), (ilocs_max_pts[paramIDX+4][a], 10), fontsize=30)
|
||||
else:
|
||||
ilocs_max.append(None)
|
||||
ilocs_max_pts.append(None)
|
||||
|
||||
# dataTable[paramIDX+4+7, 0] = JFE_Obs_geo.loc[minTime:maxTime, param].mean(skipna=True)
|
||||
# dataTable[paramIDX+4+7, 1] = JFE_Obs_geo.loc[minTime:maxTime, param].std(skipna=True)
|
||||
# dataTable[paramIDX+4+7, 2] = max(JFE_Obs_geo.loc[minTime:maxTime, param].min(skipna=True), 0)
|
||||
# dataTable[paramIDX+4+7, 3] = JFE_Obs_geo.loc[minTime:maxTime, param].max(skipna=True) dataTable[paramIDX+4+7, 0] = JFE_Obs_geo.loc[minTime:maxTime, param].mean(skipna=True)
|
||||
|
||||
dataTable[paramIDX+4+7, 0] = JFE_smoothed.mean(skipna=True)
|
||||
dataTable[paramIDX+4+7, 1] = JFE_smoothed.std(skipna=True)
|
||||
dataTable[paramIDX+4+7, 2] = max(JFE_smoothed.min(skipna=True), 0)
|
||||
dataTable[paramIDX+4+7, 3] = JFE_smoothed.max(skipna=True)
|
||||
|
||||
axes[paramIDX+4].set_ylabel(JFEparamName[paramIDX])
|
||||
axes[paramIDX+4].set_title('JFE: ' + JFEparamName[paramIDX])
|
||||
axes[paramIDX+4].set_xlabel('')
|
||||
|
||||
axes[paramIDX+4].set_ylim(JFEparamMin[paramIDX], JFEparamMax[paramIDX])
|
||||
axes[paramIDX+4].legend(loc='upper right')
|
||||
|
||||
axes[paramIDX+4].set_xlabel(minTime.strftime('%B %#d, %Y'))
|
||||
else:
|
||||
axes[paramIDX].set_xlabel(minTime.strftime('%B %#d, %Y'))
|
||||
|
||||
# Formate Data Table
|
||||
dataTableFormat_mean = []
|
||||
dataTableFormat_maxmin = []
|
||||
for d in range(0, len(roundIDX)):
|
||||
dataTableFormat_mean.append(round(dataTable[d, 0], roundIDX[d]))
|
||||
if dataTable[d, 3] == 0:
|
||||
dataTableFormat_maxmin.append('--')
|
||||
else:
|
||||
dataTableFormat_maxmin.append(str(round(dataTable[d, 2], roundIDX[d])) + ' / ' + str(round(dataTable[d, 3], roundIDX[d])))
|
||||
|
||||
|
||||
dfOut = pd.DataFrame(dataTable[:, :])
|
||||
dfOutFormat = pd.DataFrame([dataTableFormat_mean, dataTableFormat_maxmin]).transpose()
|
||||
|
||||
# Change the column names
|
||||
dfOut.columns =['Mean', 'Standard Deviation', 'Min', 'Max']
|
||||
dfOutFormat.columns = [np.array([minTime.strftime('%B %#d, %Y'), minTime.strftime('%B %#d, %Y')]),
|
||||
np.array(['Mean', 'Min / Max'])]
|
||||
# Change the row indexes
|
||||
if JFE_File is not None:
|
||||
dfOut.iloc[14, 0] = minTime.strftime('%B %#d, %Y')
|
||||
rowNames = ['Air Temperature [degC]', 'Wind Speed [m/s]', 'Wind Direction [deg]', '24h Precipitation [mm]',
|
||||
'Significant Wave Height Offshore [m]' ,'Peak Wave Period Offshore [s]',
|
||||
'Mean Wave Direction Offshore [deg]', 'Depth [m]', 'Salinity [PSU]',
|
||||
'Dissolved O₂ saturation [%]', 'Temperature [degC]',
|
||||
'Turbidity [FTU]', 'Chl-Flu. [ppb]', 'Chl-a [ug/l]', 'Observation Date']
|
||||
dfOut.index = rowNames
|
||||
dfOutFormat.index = rowNames[0:-1]
|
||||
else:
|
||||
dfOut.iloc[8, 0] = minTime.strftime('%B %#d, %Y')
|
||||
rowNames = ['Air Temperature [degC]', 'Wind Speed [m/s]', 'Wind Direction [deg]', '24h Precipitation [mm]',
|
||||
'Significant Wave Height Offshore [m]' ,'Peak Wave Period Offshore [s]',
|
||||
'Mean Wave Direction Offshore [deg]',
|
||||
'Turbidity [NTU]', 'Observation Date']
|
||||
dfOut.index = rowNames
|
||||
dfOutFormat.index = rowNames[0:-1]
|
||||
|
||||
|
||||
fig.suptitle(siteName + ', ' +minTime.strftime('%B %#d, %Y') + ' (' + timeLabel + ')', fontsize=30)
|
||||
|
||||
plt.show()
|
||||
dfOut.to_excel(importPath + '/Summary_Stats_' + siteName + '.xlsx')
|
||||
dfOutFormat.to_excel(importPath + '/Summary_StatsFormat_' + siteName + '.xlsx')
|
||||
|
||||
dfOut.to_csv(importPath + '/Summary_Stats_' + siteName + '.csv')
|
||||
|
||||
fig.savefig(importPath + '/Figures/SummaryTimeSeries_' + siteName + '.pdf',
|
||||
bbox_inches='tight')
|
||||
fig.savefig(importPath + '/Figures/SummaryTimeSeries_' + siteName + '.png',
|
||||
bbox_inches='tight', dpi=500)
|
||||
|
||||
|
||||
#%% Plot Maps
|
||||
if JFE_File is None:
|
||||
# Only Turbidity Data
|
||||
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(9, 9), constrained_layout=True)
|
||||
ax = []
|
||||
ax.append(axes)
|
||||
else:
|
||||
fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(19, 25), constrained_layout=True)
|
||||
ax = axes.flat
|
||||
|
||||
fig.patch.set_facecolor('white')
|
||||
# fig.tight_layout(pad=1.05)
|
||||
|
||||
fontprops = fm.FontProperties(size=25)
|
||||
x, y, arrow_length = 0.95, 0.93, 0.20
|
||||
plt.rcParams.update({'font.size': 22})
|
||||
|
||||
axXlimTT = (RBR_Obs_geo.loc[minTime:maxTime].geometry.x.min()-100,
|
||||
RBR_Obs_geo.loc[minTime:maxTime].geometry.x.max()+100)
|
||||
axYlimTT = (RBR_Obs_geo.loc[minTime:maxTime].geometry.y.min()-100,
|
||||
RBR_Obs_geo.loc[minTime:maxTime].geometry.y.max()+100)
|
||||
|
||||
plt.setp(axes, xlim=axXlim, ylim=axYlim)
|
||||
# plt.setp(axes, xlim=axXlimTT, ylim=axYlimTT)
|
||||
|
||||
# Plot the RBR observations
|
||||
# Salinity
|
||||
for paramIDX, param in enumerate(RBRparam):
|
||||
if RBR_File is not None:
|
||||
|
||||
# Draw thick black line to show approx path
|
||||
if GPS_File is None:
|
||||
ax[paramIDX].scatter(RBR_Obs_geo.loc[minTime:maxTime].geometry.x,
|
||||
RBR_Obs_geo.loc[minTime:maxTime].geometry.y,
|
||||
150, marker='o', color='black', label='Approximate Path')
|
||||
plt.legend(loc='upper left')
|
||||
|
||||
RBR_Obs_geo.loc[minTime:maxTime].plot(
|
||||
column=param, ax=ax[paramIDX], vmin=RBRparamMin[paramIDX], vmax=RBRparamMax[paramIDX],
|
||||
legend=True, legend_kwds={'label': RBRparamName[paramIDX]},
|
||||
cmap=RBRparmCmap[paramIDX], markersize=20)
|
||||
|
||||
|
||||
ctx.add_basemap(ax[paramIDX], source=mapbox, crs='EPSG:32621')
|
||||
|
||||
# Add time labels
|
||||
# plt.scatter(RBR_Obs_geo.loc[RBR_mask].iloc[
|
||||
# ilocs_max, :].geometry.x,
|
||||
# RBR_Obs_geo.loc[RBR_mask].iloc[
|
||||
# ilocs_max, :].geometry.y, 75, marker='o', color='black')
|
||||
|
||||
if (not RBR_Obs_geo.geometry.isnull().all()) & (GPS_File is not None) & (param == 'Turbidity '):
|
||||
for a in range(0, len(ilocs_max[paramIDX])):
|
||||
ax[paramIDX].annotate(str(a + 1), (RBR_Obs_geo.loc[RBR_mask[paramIDX]].iloc[
|
||||
ilocs_max[paramIDX][a], :].geometry.x,
|
||||
RBR_Obs_geo.loc[RBR_mask[paramIDX]].iloc[
|
||||
ilocs_max[paramIDX][a], :].geometry.y), fontsize=30)
|
||||
|
||||
ax[paramIDX].set_title(RBRparamName[paramIDX])
|
||||
# ax[paramIDX].set_ylabel('UTM 21N [m]')
|
||||
# ax[paramIDX].set_xlabel('UTM 21N [m]')
|
||||
ax[paramIDX].locator_params(axis='y', nbins=3)
|
||||
ax[paramIDX].ticklabel_format(useOffset=False, style='plain', axis='both')
|
||||
|
||||
ax[paramIDX].get_xaxis().set_ticks([])
|
||||
ax[paramIDX].get_yaxis().set_ticks([])
|
||||
|
||||
#Add scale-bar
|
||||
scalebar = AnchoredSizeBar(ax[paramIDX].transData,
|
||||
100, '100 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
ax[paramIDX].add_artist(scalebar)
|
||||
ax[paramIDX].annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
|
||||
arrowprops=dict(facecolor='black', width=6, headwidth=30),
|
||||
ha='center', va='center', fontsize=35,
|
||||
xycoords=ax[paramIDX].transAxes)
|
||||
|
||||
# Plot Plot JFE Points
|
||||
JFEparam = ['Turb. -M[FTU]', 'Chl-Flu.[ppb]']
|
||||
JFEparamName = ['Turbidity [FTU]', 'Chl-Flu. [ppb]']
|
||||
JFEparamCmp = [cmo.turbid, cmo.algae]
|
||||
JFEparamMin = [0.0, 0.0]
|
||||
JFEparamMax = [10.0, 1.0]
|
||||
if JFE_File is not None:
|
||||
for paramIDX, param in enumerate(JFEparam):
|
||||
if JFE_File is not None:
|
||||
JFE_Obs_geo.loc[minTime:maxTime].plot(
|
||||
column=param, ax=ax[paramIDX+4], vmin=JFEparamMin[paramIDX], vmax=JFEparamMax[paramIDX],
|
||||
legend=True, legend_kwds={'label': JFEparamName[paramIDX]},
|
||||
cmap=JFEparamCmp[paramIDX], markersize=20) # Note the space in the col name
|
||||
ctx.add_basemap(ax[paramIDX+4], source=mapbox, crs='EPSG:32621')
|
||||
|
||||
# Add time labels
|
||||
if (not JFE_Obs_geo.geometry.isnull().all()) & (GPS_File is not None) & (param == 'Turb. -M[FTU]'):
|
||||
for a in range(0, len(ilocs_max[paramIDX+4])):
|
||||
ax[paramIDX+4].annotate(str(a + 1), (JFE_Obs_geo.loc[JFE_mask[paramIDX]].iloc[
|
||||
ilocs_max[paramIDX+4][a], :].geometry.x,
|
||||
JFE_Obs_geo.loc[JFE_mask[paramIDX]].iloc[
|
||||
ilocs_max[paramIDX+4][a], :].geometry.y), fontsize=30)
|
||||
|
||||
ax[paramIDX+4].set_title(JFEparamName[paramIDX])
|
||||
# ax[paramIDX+4].set_ylabel('UTM 21N [m]')
|
||||
# ax[paramIDX+4].set_xlabel('UTM 21N [m]')
|
||||
ax[paramIDX+4].locator_params(axis='y', nbins=3)
|
||||
ax[paramIDX+4].ticklabel_format(useOffset=False, style='plain', axis='both')
|
||||
ax[paramIDX+4].get_xaxis().set_ticks([])
|
||||
ax[paramIDX+4].get_yaxis().set_ticks([])
|
||||
|
||||
#Add scale-bar
|
||||
scalebar = AnchoredSizeBar(ax[paramIDX+4].transData,
|
||||
100, '100 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
ax[paramIDX+4].add_artist(scalebar)
|
||||
ax[paramIDX+4].annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
|
||||
arrowprops=dict(facecolor='black', width=6, headwidth=30),
|
||||
ha='center', va='center', fontsize=25,
|
||||
xycoords=ax[paramIDX+4].transAxes)
|
||||
|
||||
fig.suptitle(siteName + ', ' + minTime.strftime('%b %#d, %Y') + ' (' + timeLabel + ')', fontsize=30)
|
||||
plt.show()
|
||||
|
||||
if not os.path.exists(importPath + '/Figures'):
|
||||
os.mkdir(importPath + '/Figures')
|
||||
|
||||
fig.savefig(importPath + '/Figures/SummaryMap_' + siteName + '.pdf',
|
||||
bbox_inches='tight')
|
||||
|
||||
fig.savefig(importPath + '/Figures/SummaryMap_' + siteName + '.png',
|
||||
bbox_inches='tight', dpi=500)
|
||||
|
||||
#%% Summary Sheet
|
||||
plotIDXsLoop = []
|
||||
plotIDXsLoop.append([0, 3, 6, 9])
|
||||
plotIDXsLoop.append([1, 4, 7, 10])
|
||||
plotIDXsLoop.append([2, 5, 8, 11])
|
||||
|
||||
for i in range(0, 3):
|
||||
summTable = None
|
||||
plotIDXs = plotIDXsLoop[i]
|
||||
|
||||
for s, plotIDX in enumerate(plotIDXs):
|
||||
## Define master import path
|
||||
importPath = importPaths[plotIDX]
|
||||
siteName = siteNames[plotIDX]
|
||||
|
||||
obsStatsIN = pd.read_excel(importPath + '/Summary_StatsFormat_' + siteName + '.xlsx', header=[0,1], index_col=0)
|
||||
if any((plotIDX == 9, plotIDX == 10, plotIDX == 11)):
|
||||
obsStatsIN.rename({'Turbidity [NTU]': 'Turbidity [FTU]'}, inplace=True)
|
||||
|
||||
if s == 0:
|
||||
summTable = obsStatsIN
|
||||
else:
|
||||
summTable = summTable.join(obsStatsIN)
|
||||
|
||||
# Remove -999 with nan
|
||||
summTable.replace(-999, np.nan, inplace=True)
|
||||
|
||||
summTable.to_excel('//srv-ott3.baird.com/Projects/13033.201 Great House - Coastal Structures/05_Analyses/01_WQ Monitoring/CombinedStats/Summary_StatsMerge_' + siteName + '.xlsx')
|
||||
|
||||
|
||||
#%% Summary Plot
|
||||
|
||||
plotvars = ['Air Temperature [degC]', 'Wind Speed [m/s]', 'Wind Direction [deg]', '24h Precipitation [mm]',
|
||||
'Significant Wave Height [m]', 'Salinity [PSU]',
|
||||
'Dissolved O₂ [%]', 'Temperature [degC]',
|
||||
'Turbidity [FTU]', 'Chl-Flu. [ppb]']
|
||||
|
||||
|
||||
plotIDXsLoop = []
|
||||
plotIDXsLoop.append([0, 3, 6, 9])
|
||||
plotIDXsLoop.append([1, 4, 7, 10])
|
||||
plotIDXsLoop.append([2, 5, 8, 11])
|
||||
|
||||
for i in range(0, 3):
|
||||
summTable = None
|
||||
plotIDXs = plotIDXsLoop[i]
|
||||
plotDates = []
|
||||
plotTable = np.empty([10, len(plotIDXs)])
|
||||
|
||||
for s, plotIDX in enumerate(plotIDXs):
|
||||
## Define master import path
|
||||
importPath = importPaths[plotIDX]
|
||||
siteName = siteNames[plotIDX]
|
||||
|
||||
obsStatsIN = pd.read_excel(importPath + '/Summary_Stats_' + siteName + '.xlsx')
|
||||
if any((plotIDX == 9, plotIDX == 10, plotIDX == 11)):
|
||||
plotTable[0:3, s] = obsStatsIN.iloc[0:3, 1]
|
||||
plotTable[8, s] = obsStatsIN.iloc[7, 1]
|
||||
plotDates.append(datetime.strptime(obsStatsIN.iloc[8, 1], '%B %d, %Y'))
|
||||
else:
|
||||
plotTable[:, s] = obsStatsIN.iloc[[0, 1, 2, 3, 4, 8, 9, 10, 11, 12], 1]
|
||||
plotDates.append(datetime.strptime(obsStatsIN.iloc[14, 1], '%B %d, %Y'))
|
||||
|
||||
|
||||
fig, axes = plt.subplots(nrows=5, ncols=2, figsize=(19, 25), sharex=True)
|
||||
fig.patch.set_facecolor('white')
|
||||
fig.tight_layout(pad=3)
|
||||
ax = axes.flat
|
||||
|
||||
# Repalce zero with nan
|
||||
plotTable[plotTable < 0.00001] = np.nan
|
||||
|
||||
for v in range(0, 10):
|
||||
ax[v].scatter(plotDates, plotTable[v, :], 250)
|
||||
ax[v].set_ylabel(plotvars[v])
|
||||
|
||||
fig.suptitle(siteName, fontsize=35)
|
||||
plt.gcf().autofmt_xdate()
|
||||
plt.gcf().align_ylabels()
|
||||
plt.show()
|
||||
|
||||
fig.savefig('//srv-ott3.baird.com/Projects/13033.201 Great House - Coastal Structures/05_Analyses/01_WQ Monitoring/CombinedStats/' + siteName + '.pdf',
|
||||
bbox_inches='tight')
|
||||
fig.savefig('//srv-ott3.baird.com/Projects/13033.201 Great House - Coastal Structures/05_Analyses/01_WQ Monitoring/CombinedStats/' + siteName + '.png',
|
||||
bbox_inches='tight', dpi=500)
|
||||
|
|
@ -22,7 +22,7 @@ import os
|
|||
from shapely.geometry import Point
|
||||
|
||||
import pickle
|
||||
# %% read in data
|
||||
# %% Read in data
|
||||
dataPath = '//srv-ott3/Projects/11934.201 Newtown Creek TPP – Privileged and Confidential/05_Analyses/07 ADCP/NC_CurrentMeter_All_Phase1_all_data_2012_05_20/'
|
||||
|
||||
df = pd.read_excel('//srv-ott3/Projects/11934.201 Newtown Creek TPP – Privileged and Confidential/03_Data/02_Physical/05 Currents/NC_CurrentMeter_All_Phase1_all_data_2013_07_16/NC_CurrentMeter_All_Phase1_all_mobile_2013_05_02.xlsx',
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -0,0 +1,8 @@
|
|||
# Default ignored files
|
||||
/shelf/
|
||||
/workspace.xml
|
||||
# Editor-based HTTP Client requests
|
||||
/httpRequests/
|
||||
# Datasource local storage ignored files
|
||||
/dataSources/
|
||||
/dataSources.local.xml
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<module type="PYTHON_MODULE" version="4">
|
||||
<component name="NewModuleRootManager">
|
||||
<content url="file://$MODULE_DIR$" />
|
||||
<orderEntry type="jdk" jdkName="Python 3.8 (geopandas_forge)" jdkType="Python SDK" />
|
||||
<orderEntry type="sourceFolder" forTests="false" />
|
||||
</component>
|
||||
<component name="PyDocumentationSettings">
|
||||
<option name="renderExternalDocumentation" value="true" />
|
||||
</component>
|
||||
</module>
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
<component name="InspectionProjectProfileManager">
|
||||
<profile version="1.0">
|
||||
<option name="myName" value="Project Default" />
|
||||
<inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
|
||||
<option name="ignoredIdentifiers">
|
||||
<list>
|
||||
<option value="bool.*" />
|
||||
<option value="geopandas.io.file" />
|
||||
</list>
|
||||
</option>
|
||||
</inspection_tool>
|
||||
</profile>
|
||||
</component>
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
<component name="InspectionProjectProfileManager">
|
||||
<settings>
|
||||
<option name="USE_PROJECT_PROFILE" value="false" />
|
||||
<version value="1.0" />
|
||||
</settings>
|
||||
</component>
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (geopandas_forge)" project-jdk-type="Python SDK" />
|
||||
</project>
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="ProjectModuleManager">
|
||||
<modules>
|
||||
<module fileurl="file://$PROJECT_DIR$/.idea/SouthShore.iml" filepath="$PROJECT_DIR$/.idea/SouthShore.iml" />
|
||||
</modules>
|
||||
</component>
|
||||
</project>
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="PySciProjectComponent">
|
||||
<option name="PY_SCI_VIEW" value="true" />
|
||||
<option name="PY_SCI_VIEW_SUGGESTED" value="true" />
|
||||
</component>
|
||||
</project>
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="VcsDirectoryMappings">
|
||||
<mapping directory="$PROJECT_DIR$/.." vcs="Git" />
|
||||
</component>
|
||||
</project>
|
||||
|
|
@ -0,0 +1,43 @@
|
|||
## Wave transmission through a Breakwater
|
||||
# Author: AJMR
|
||||
# December 14, 2021
|
||||
|
||||
#%% Setup Project
|
||||
from mikeio import Dfs0
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
|
||||
#%% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models", "13632.101.W.zzAJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "ModelLog")
|
||||
#%% Read in Point Sh
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
|
||||
#%% Read Model Results
|
||||
modelPlot = [8]
|
||||
# MIKEds = [None] * (max(modelPlot)+1)
|
||||
|
||||
for i in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][i],
|
||||
runLog['Run Name'][i] + '.sw - Result Files','BreakPts.dfs0'))
|
||||
|
||||
dfsIN_read = dfsIN.read()
|
||||
|
||||
A = dfsIN_read.to_dataframe()
|
||||
|
||||
MIKEnp = np.empty((dfsIN_read.n_timesteps, dfsIN_read.shape[1], dfsIN_read.n_items-1))
|
||||
MIKEname = []
|
||||
|
||||
for j in range(0, dfsIN_read.n_items-1):
|
||||
MIKEname.append(dfsIN_read.items[j].name)
|
||||
|
||||
MIKEnp[:, :, j] = dfsIN_read[j]
|
||||
|
||||
MIKEds = pd.DataFrame(np.squeeze(MIKEnp[1:, :, :]), columns=MIKEname)
|
||||
|
||||
|
|
@ -0,0 +1,242 @@
|
|||
## Wave transmission through a Breakwater
|
||||
# Author: AJMR
|
||||
# December 14, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfs0, Dfs1
|
||||
from mikeio.eum import ItemInfo, EUMUnit, EUMType
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.zzAJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "ModelLog")
|
||||
|
||||
# %% Read in Point Sh
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
|
||||
# %% Read in Breakwater crest
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = [8]
|
||||
|
||||
for i in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][i],
|
||||
runLog['Run Name'][i] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
|
||||
dfsIN_read = dfsIN.read()
|
||||
|
||||
MIKEds = dfsIN_read.to_dataframe()
|
||||
|
||||
# %% Merge with dataframe
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds.shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds.shape[1]):
|
||||
paramName = MIKEds.columns.values[i][MIKEds.columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
# MIKEds_dict[paramName] = []
|
||||
# MIKEid_dict[paramName] = []
|
||||
tmpFID = int(MIKEds.columns.values[i][1:MIKEds.columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds.columns.values[i][5:MIKEds.columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds.iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds.index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakwaterPTS_times.rename(columns={'index_right': 'index_right_old'}, inplace=True)
|
||||
|
||||
# %% Conversion
|
||||
breakwaterPTS_times['transmitted'] = np.full([breakwaterPTS_times.shape[0], 1], np.nan)
|
||||
gamma = 1.2
|
||||
|
||||
transmit_paramA = 0.81 * gamma
|
||||
transmit_paramB = 0.45 * gamma - 0.3 * gamma * \
|
||||
(breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) / \
|
||||
breakwaterPTS_times['Sign. Wave Height']
|
||||
|
||||
# Identify different overtopping regimes
|
||||
breakMask_A = (breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) / \
|
||||
breakwaterPTS_times['Sign. Wave Height'] >= 1.2
|
||||
breakMask_B = (((breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) /
|
||||
breakwaterPTS_times['Sign. Wave Height'] < 1.2) &
|
||||
(transmit_paramA < transmit_paramB))
|
||||
breakMask_C = (((breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) /
|
||||
breakwaterPTS_times['Sign. Wave Height'] < 1.2) &
|
||||
(transmit_paramA > transmit_paramB))
|
||||
|
||||
# breakMask_B = (breakwaterPTS_times['Crest']-breakwaterPTS_times['Surface elevation'])/ \
|
||||
# breakwaterPTS_times['Sign. Wave Height']<=-1.2
|
||||
|
||||
# breakMask_C = (((breakwaterPTS_times['Crest']-breakwaterPTS_times['Surface elevation'])/
|
||||
# breakwaterPTS_times['Sign. Wave Height']>=-1.2) &
|
||||
# ((breakwaterPTS_times['Crest']-breakwaterPTS_times['Surface elevation'])/
|
||||
# breakwaterPTS_times['Sign. Wave Height']<1.2))
|
||||
|
||||
|
||||
# breakwaterPTS_times['transmitted'][breakMask_A] = breakwaterPTS_times['Sign. Wave Height'][breakMask_A]* 0.1
|
||||
# breakwaterPTS_times['transmitted'][breakMask_B] = breakwaterPTS_times['Sign. Wave Height'][breakMask_B]* 0.82
|
||||
# breakwaterPTS_times['transmitted'][breakMask_C] = breakwaterPTS_times['Sign. Wave Height'][breakMask_C]* \
|
||||
# (0.46-0.3*(breakwaterPTS_times['Crest'][breakMask_C]
|
||||
# -breakwaterPTS_times['Surface elevation'][breakMask_C])/
|
||||
# breakwaterPTS_times['Sign. Wave Height'][breakMask_C])
|
||||
|
||||
|
||||
# Updated approach
|
||||
breakwaterPTS_times['transmitted'][breakMask_A] = breakwaterPTS_times['Sign. Wave Height'][breakMask_A] * 0.09 * gamma
|
||||
breakwaterPTS_times['transmitted'][breakMask_B] = breakwaterPTS_times['Sign. Wave Height'][breakMask_B] *\
|
||||
transmit_paramA
|
||||
breakwaterPTS_times['transmitted'][breakMask_C] = breakwaterPTS_times['Sign. Wave Height'][breakMask_C] * \
|
||||
transmit_paramB[breakMask_C]
|
||||
|
||||
# %% Merge with breakwater transformed waves
|
||||
breakwaterPTS_end = breakwaterPTS_times['Time'] == breakwaterPTS_times['Time'].max()
|
||||
# innerBound_gdf = innerBound_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end,:])
|
||||
# %% Read Inner Boundary Points North
|
||||
innerBoundNorth = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_North.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundNorth.sort_values(by=['x'], inplace=True)
|
||||
innerBoundNorth_gdf = gp.GeoDataFrame(innerBoundNorth, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundNorth.x, innerBoundNorth.y))
|
||||
innerBoundNorth_gdf = innerBoundNorth_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
# %% Read Inner Boundary Points Mid
|
||||
innerBoundMid = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_Mid.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundMid.sort_values(by=['x'], inplace=True)
|
||||
innerBoundMid_gdf = gp.GeoDataFrame(innerBoundMid, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundMid.x, innerBoundMid.y))
|
||||
innerBoundMid_gdf = innerBoundMid_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
# %% Read Inner Boundary Points North
|
||||
innerBoundSouth = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_South.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundSouth.sort_values(by=['x'], inplace=True)
|
||||
innerBoundSouth_gdf = gp.GeoDataFrame(innerBoundSouth, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundSouth.x, innerBoundSouth.y))
|
||||
innerBoundSouth_gdf = innerBoundSouth_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
|
||||
# %% Save as DFS1
|
||||
boundDataNorth = pd.DataFrame(
|
||||
innerBoundNorth_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataNorth.set_index('Time', inplace=True)
|
||||
boundDataNorth.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][modelPlot[0]] + 'ProdInnerNorth1.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataNorth['Significant wave height'], boundDataNorth['Significant wave height'])),
|
||||
np.array((boundDataNorth['Peak wave period'], boundDataNorth['Peak wave period'])),
|
||||
np.array((boundDataNorth['Mean wave direction'], boundDataNorth['Mean wave direction'])),
|
||||
np.ones((2, boundDataNorth.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
datetimes=None,
|
||||
items=items,
|
||||
title=None)
|
||||
|
||||
|
||||
# %% Save as DFS1- Mid
|
||||
boundDataMid = pd.DataFrame(
|
||||
innerBoundMid_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataMid.set_index('Time', inplace=True)
|
||||
boundDataMid.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][modelPlot[0]] + 'ProdInnerMid.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataMid['Significant wave height'], boundDataMid['Significant wave height'])),
|
||||
np.array((boundDataMid['Peak wave period'], boundDataMid['Peak wave period'])),
|
||||
np.array((boundDataMid['Mean wave direction'], boundDataMid['Mean wave direction'])),
|
||||
np.ones((2, boundDataMid.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
items=items)
|
||||
|
||||
# %% Save as DFS1- South
|
||||
boundDataSouth = pd.DataFrame(
|
||||
innerBoundSouth_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataSouth.set_index('Time', inplace=True)
|
||||
boundDataSouth.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][modelPlot[0]] + 'ProdInnerSouth.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataSouth['Significant wave height'], boundDataSouth['Significant wave height'])),
|
||||
np.array((boundDataSouth['Peak wave period'], boundDataSouth['Peak wave period'])),
|
||||
np.array((boundDataSouth['Mean wave direction'], boundDataSouth['Mean wave direction'])),
|
||||
np.ones((2, boundDataSouth.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
items=items)
|
||||
|
||||
|
||||
# %% Test Plot
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||
|
||||
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(9, 9), constrained_layout=True)
|
||||
|
||||
breakwaterPTS_merge.plot(ax=axes, column='Sign. Wave Height', cmap='viridis')
|
||||
# breakwaterPTS_merge.plot(ax=axes, column='Crest', cmap='viridis', legend=True)
|
||||
innerBound_gdf.plot(ax=axes, column='transmitted', cmap='viridis')
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,225 @@
|
|||
## Wave transmission through a Breakwater
|
||||
# Author: AJMR
|
||||
# December 14, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfs0, Dfs1
|
||||
from mikeio.eum import ItemInfo, EUMUnit, EUMType
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "ModelLog")
|
||||
|
||||
# %% Read in Point Sh
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
|
||||
# %% Read in Breakwater crest
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(12, 20)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
|
||||
dfsIN_read = dfsIN.read()
|
||||
|
||||
MIKEds = dfsIN_read.to_dataframe()
|
||||
|
||||
# %% Merge with dataframe
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds.shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds.shape[1]):
|
||||
paramName = MIKEds.columns.values[i][MIKEds.columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
# MIKEds_dict[paramName] = []
|
||||
# MIKEid_dict[paramName] = []
|
||||
tmpFID = int(MIKEds.columns.values[i][1:MIKEds.columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds.columns.values[i][5:MIKEds.columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds.iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds.index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakwaterPTS_times.rename(columns={'index_right': 'index_right_old'}, inplace=True)
|
||||
|
||||
# %% Conversion
|
||||
breakwaterPTS_times['transmitted'] = np.full([breakwaterPTS_times.shape[0], 1], np.nan)
|
||||
gamma = 1.2
|
||||
|
||||
transmit_paramA = 0.81 * gamma
|
||||
transmit_paramB = 0.45 * gamma - 0.3 * gamma * \
|
||||
(breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) / \
|
||||
breakwaterPTS_times['Sign. Wave Height']
|
||||
|
||||
# Identify different overtopping regimes
|
||||
breakMask_A = (breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) / \
|
||||
breakwaterPTS_times['Sign. Wave Height'] >= 1.2
|
||||
breakMask_B = (((breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) /
|
||||
breakwaterPTS_times['Sign. Wave Height'] < 1.2) &
|
||||
(transmit_paramA < transmit_paramB))
|
||||
breakMask_C = (((breakwaterPTS_times['Crest'] - breakwaterPTS_times['Surface elevation']) /
|
||||
breakwaterPTS_times['Sign. Wave Height'] < 1.2) &
|
||||
(transmit_paramA > transmit_paramB))
|
||||
|
||||
# Updated approach
|
||||
breakwaterPTS_times['transmitted'][breakMask_A] = breakwaterPTS_times['Sign. Wave Height'][breakMask_A] * 0.09 * gamma
|
||||
breakwaterPTS_times['transmitted'][breakMask_B] = breakwaterPTS_times['Sign. Wave Height'][breakMask_B] *\
|
||||
transmit_paramA
|
||||
breakwaterPTS_times['transmitted'][breakMask_C] = breakwaterPTS_times['Sign. Wave Height'][breakMask_C] * \
|
||||
transmit_paramB[breakMask_C]
|
||||
|
||||
# %% Merge with breakwater transformed waves
|
||||
breakwaterPTS_end = breakwaterPTS_times['Time'] == breakwaterPTS_times['Time'].max()
|
||||
|
||||
# %% Read Inner Boundary Points North
|
||||
innerBoundNorth = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_North.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundNorth.sort_values(by=['x'], inplace=True)
|
||||
innerBoundNorth_gdf = gp.GeoDataFrame(innerBoundNorth, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundNorth.x, innerBoundNorth.y))
|
||||
innerBoundNorth_gdf = innerBoundNorth_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
# %% Read Inner Boundary Points Mid
|
||||
innerBoundMid = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_Mid.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundMid.sort_values(by=['x'], inplace=True)
|
||||
innerBoundMid_gdf = gp.GeoDataFrame(innerBoundMid, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundMid.x, innerBoundMid.y))
|
||||
innerBoundMid_gdf = innerBoundMid_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
# %% Read Inner Boundary Points North
|
||||
innerBoundSouth = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/InnerBound_South.txt',
|
||||
delimiter='\s+', header=None, names=['x', 'y'])
|
||||
innerBoundSouth.sort_values(by=['x'], inplace=True)
|
||||
innerBoundSouth_gdf = gp.GeoDataFrame(innerBoundSouth, crs='EPSG:32616',
|
||||
geometry=gp.points_from_xy(innerBoundSouth.x, innerBoundSouth.y))
|
||||
innerBoundSouth_gdf = innerBoundSouth_gdf.sjoin_nearest(breakwaterPTS_times.loc[breakwaterPTS_end, :])
|
||||
|
||||
# %% Save as DFS1
|
||||
boundDataNorth = pd.DataFrame(
|
||||
innerBoundNorth_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataNorth.set_index('Time', inplace=True)
|
||||
boundDataNorth.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][m] + 'ProdInnerNorth1.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataNorth['Significant wave height'], boundDataNorth['Significant wave height'])),
|
||||
np.array((boundDataNorth['Peak wave period'], boundDataNorth['Peak wave period'])),
|
||||
np.array((boundDataNorth['Mean wave direction'], boundDataNorth['Mean wave direction'])),
|
||||
np.ones((2, boundDataNorth.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
datetimes=None,
|
||||
items=items,
|
||||
title=None)
|
||||
|
||||
|
||||
# %% Save as DFS1- Mid
|
||||
boundDataMid = pd.DataFrame(
|
||||
innerBoundMid_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataMid.set_index('Time', inplace=True)
|
||||
boundDataMid.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][m] + 'ProdInnerMid.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataMid['Significant wave height'], boundDataMid['Significant wave height'])),
|
||||
np.array((boundDataMid['Peak wave period'], boundDataMid['Peak wave period'])),
|
||||
np.array((boundDataMid['Mean wave direction'], boundDataMid['Mean wave direction'])),
|
||||
np.ones((2, boundDataMid.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
items=items)
|
||||
|
||||
# %% Save as DFS1- South
|
||||
boundDataSouth = pd.DataFrame(
|
||||
innerBoundSouth_gdf.loc[:, ['Time', 'transmitted', 'Peak Wave Period', 'Mean Wave Direction']])
|
||||
boundDataSouth.set_index('Time', inplace=True)
|
||||
boundDataSouth.rename(columns={'transmitted': 'Significant wave height', 'Peak Wave Period': 'Peak wave period',
|
||||
'Mean Wave Direction': 'Mean wave direction'},
|
||||
inplace=True)
|
||||
|
||||
dfsfilename = '//oak-spillway.baird.com/F/13632.101 South Shore Breakwater/SetupFiles/InnerBounds/' + \
|
||||
runLog['Run Name'][m] + 'ProdInnerSouth.dfs1'
|
||||
|
||||
items = [ItemInfo("Significant wave height", EUMType.Significant_wave_height, EUMUnit.meter),
|
||||
ItemInfo("Peak wave period", EUMType.Wave_period, EUMUnit.second),
|
||||
ItemInfo("Mean wave direction", EUMType.Mean_Wave_Direction, EUMUnit.degree),
|
||||
ItemInfo("Directional Standard Deviation, n", EUMType.Directional_Standard_Deviation, EUMUnit.degree)]
|
||||
|
||||
dfs = Dfs1()
|
||||
dfs.write(filename=dfsfilename,
|
||||
data=[np.array((boundDataSouth['Significant wave height'], boundDataSouth['Significant wave height'])),
|
||||
np.array((boundDataSouth['Peak wave period'], boundDataSouth['Peak wave period'])),
|
||||
np.array((boundDataSouth['Mean wave direction'], boundDataSouth['Mean wave direction'])),
|
||||
np.ones((2, boundDataSouth.shape[0])) * 23.28],
|
||||
start_time=breakwaterPTS_times['Time'].min(),
|
||||
dt=86400,
|
||||
items=items)
|
||||
|
||||
|
||||
# %% Test Plot
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
||||
|
||||
fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(9, 9), constrained_layout=True)
|
||||
|
||||
breakwaterPTS_merge.plot(ax=axes, column='Sign. Wave Height', cmap='viridis')
|
||||
# breakwaterPTS_merge.plot(ax=axes, column='Crest', cmap='viridis', legend=True)
|
||||
innerBound_gdf.plot(ax=axes, column='transmitted', cmap='viridis')
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,221 @@
|
|||
## Plotting Mike21 SW results for SouthShore
|
||||
# Author: AJMR
|
||||
# December 22, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfsu, Mesh, Dfs2, Dfs0
|
||||
from mikeio.eum import ItemInfo, EUMUnit, EUMType
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar, AnchoredDirectionArrows
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "ModelLog")
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(28, 29)
|
||||
hmo_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'ResultsMap.dfsu').as_posix())
|
||||
|
||||
# Read Mesh for first model
|
||||
mikeMeshIN = dfsIN.to_shapely()
|
||||
|
||||
# Convert to list of polygons
|
||||
mikeMeshIN_list = [p for p in mikeMeshIN]
|
||||
|
||||
ds = dfsIN.read()
|
||||
hm0 = ds["Sign. Wave Height"][1]
|
||||
|
||||
# Add to list
|
||||
hmo_list[m] = gp.GeoDataFrame(hm0, geometry=mikeMeshIN_list)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del mikeMeshIN
|
||||
del mikeMeshIN_list
|
||||
del hm0
|
||||
|
||||
# %% Plotting
|
||||
# Shaded Water
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/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)
|
||||
|
||||
for m in modelPlot:
|
||||
fig, axes = plt.subplots(figsize=(6, 6))
|
||||
|
||||
# centroids = hmo_list[m].representative_point()
|
||||
# hmo_plot = gp.GeoDataFrame.set_geometry(hmo_list[m], centroids)
|
||||
# hmo_plot = hmo_plot.set_crs(crs='EPSG:32616')
|
||||
# hmo_plot = hmo_plot.to_crs(epsg=4326)
|
||||
# hmo_list[m].plot(ax=axes, column=0, antialiased=False, scheme='equal_interval', k=12, cmap='turbo',
|
||||
# legend=True, legend_kwds={'fmt': "{:.2f}"})
|
||||
|
||||
dfsIN.plot(hm0, plot_type='contourf', show_mesh=False, cmap='turbo', ax=axes, levels=12, label='HM0 [m]')
|
||||
|
||||
# axes2 = gplt.polyplot(hmo_list[m], projection=gcrs.AlbersEqualArea)
|
||||
# gplt.kdeplot(hmo_plot, cmap='turbo', shade=True, ax=axes)
|
||||
# hmo_plot.plot(ax=axes, column=0, antialiased=False)
|
||||
|
||||
|
||||
# # Add in scale bar and North Arrow
|
||||
# scalebar = AnchoredSizeBar(axes.transData,
|
||||
# 500, '500 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
# axes.add_artist(scalebar)
|
||||
|
||||
axes.annotate('N', xy=(x, y), xytext=(x, y - arrow_length),
|
||||
arrowprops=dict(facecolor='black', width=6, headwidth=20),
|
||||
ha='center', va='center', fontsize=15,
|
||||
xycoords=axes.transAxes)
|
||||
|
||||
axes.set_xlim(left=427800, right=431000)
|
||||
axes.set_ylim(bottom=4758000, top=4762000)
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
plt.suptitle(runLog['Short Description'][m])
|
||||
axes.title.set_text('Significant Wave Height (m)')
|
||||
axes.titlesize = 'small'
|
||||
axes.set_xlabel('Easting [m]')
|
||||
axes.set_ylabel('Northing [m]')
|
||||
|
||||
plt.show()
|
||||
|
||||
fig.savefig(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Images/Production/' +
|
||||
runLog['Short Description'][m] + '_HM0.png', bbox_inches='tight')
|
||||
|
||||
# %% Read time series
|
||||
MIKEds_list = [None] * (max(modelPlot) + 1)
|
||||
MIKEdsT_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
dfsIN_read = dfsIN.read()
|
||||
MIKEds_list[m] = dfsIN_read.to_dataframe()
|
||||
|
||||
dfsTIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'TransectPTS.dfs0').as_posix())
|
||||
dfsTIN_read = dfsTIN.read()
|
||||
MIKEdsT_list[m] = dfsTIN_read.to_dataframe()
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del dfsIN_read
|
||||
del dfsIN
|
||||
del dfsTIN_read
|
||||
del dfsTIN
|
||||
|
||||
# %% Read in Toe and Crest Shapefiles
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Merge with data
|
||||
breakPointsOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimesOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds_list[m].shape[1]):
|
||||
paramName = MIKEds_list[m].columns.values[i][MIKEds_list[m].columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpFID = int(MIKEds_list[m].columns.values[i][1:MIKEds_list[m].columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds_list[m].columns.values[i][5:MIKEds_list[m].columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimesOut[m] = breakwaterPTS_times
|
||||
|
||||
# %% Read in Breakwater Transect Points Sh
|
||||
breakwaterT = pd.read_csv("C:/Users/arey/files/Projects/SouthShore/Bathy/BreakTransectPTS_Names.csv", sep='\t')
|
||||
|
||||
breakwaterT_PTS = gp.GeoDataFrame(breakwaterT, geometry=gp.points_from_xy(breakwaterT.X, breakwaterT.Y),
|
||||
crs='EPSG:32616')
|
||||
|
||||
# %% Merge with data
|
||||
breakPoints_TOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimes_TOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEdsT_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterT_PTS
|
||||
|
||||
for i in range(0, MIKEdsT_list[m].shape[1]):
|
||||
paramName = MIKEdsT_list[m].columns.values[i][MIKEdsT_list[m].columns.values[i].find(':', 5, -1) + 2:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpName = MIKEdsT_list[m].columns.values[i][0:MIKEdsT_list[m].columns.values[i].find(':', 1)]
|
||||
|
||||
breakwaterPTS_merge.loc[(breakwaterPTS_merge.Name == tmpName),
|
||||
paramName] = MIKEdsT_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEdsT_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimes_TOut[m] = breakwaterPTS_times
|
||||
|
||||
|
||||
#%% Format and save
|
||||
|
||||
for m in modelPlot:
|
||||
saveTmp = breakTimesOut[m].copy()
|
||||
saveTmp['X'] = saveTmp.geometry.x
|
||||
saveTmp['Y'] = saveTmp.geometry.y
|
||||
saveTmp.drop(['vertex_par', 'vertex_p_1', 'angle', 'geometry', 'index_right',
|
||||
'breakCrest_x', 'breakCrest_y', 'Length'], axis=1, inplace=True)
|
||||
saveTmp.sort_values(by=['FID', 'vertex_ind'], inplace=True, ignore_index=True)
|
||||
|
||||
# Reorder columns
|
||||
colNames = saveTmp.columns.values
|
||||
saveTmp = saveTmp[['X', 'Y', *colNames[0:-2]]]
|
||||
saveTmpT = saveTmp.transpose(copy=True)
|
||||
|
||||
# Transect points
|
||||
saveTmp2 = breakTimes_TOut[m].copy()
|
||||
saveTmp2.drop(['geometry'], axis=1, inplace=True)
|
||||
saveTmp2T = saveTmp2.transpose(copy=True)
|
||||
|
||||
|
||||
saveTmpT.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Toe' + runLog['Short Description'][m] + '.csv')
|
||||
|
||||
saveTmp2T.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Transect' + runLog['Short Description'][m] + '.csv')
|
||||
|
|
@ -0,0 +1,220 @@
|
|||
## Plotting Mike21 SW results for SouthShore
|
||||
# Author: AJMR
|
||||
# December 22, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfsu, Mesh, Dfs2, Dfs0
|
||||
from mikeio.eum import ItemInfo, EUMUnit, EUMType
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar, AnchoredDirectionArrows
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "StormRuns")
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(0, 4)
|
||||
hmo_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'ResultsMap.dfsu').as_posix())
|
||||
|
||||
# Read Mesh for first model
|
||||
mikeMeshIN = dfsIN.to_shapely()
|
||||
|
||||
# Convert to list of polygons
|
||||
mikeMeshIN_list = [p for p in mikeMeshIN]
|
||||
|
||||
ds = dfsIN.read()
|
||||
hm0 = ds["Sign. Wave Height"]
|
||||
|
||||
# Add to list
|
||||
hmo_list[m] = gp.GeoDataFrame(hm0, geometry=mikeMeshIN_list)
|
||||
|
||||
print(m)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del mikeMeshIN
|
||||
del mikeMeshIN_list
|
||||
del hm0
|
||||
|
||||
# %% Plotting
|
||||
# Shaded Water
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/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)
|
||||
|
||||
for m in modelPlot:
|
||||
fig, axes = plt.subplots(figsize=(6, 6))
|
||||
|
||||
plt.xlim([427800, 431000])
|
||||
plt.ylim([4758000, 4762000])
|
||||
|
||||
hmo_list[m].plot(ax=axes, column=0, antialiased=False, scheme='equal_interval', k=7, cmap='turbo',
|
||||
legend=True, legend_kwds={'fmt': "{:.2f}"}, vmax=6, vmin=0)
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
plt.suptitle(runLog['Short Description'][m])
|
||||
axes.title.set_text('Significant Wave Height (m)')
|
||||
axes.titlesize = 'small'
|
||||
axes.set_xlabel('Easting [m]')
|
||||
axes.set_ylabel('Northing [m]')
|
||||
|
||||
# # Add in scale bar and North Arrow
|
||||
# scalebar = AnchoredSizeBar(axes.transData,
|
||||
# 500, '500 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
# axes.add_artist(scalebar)
|
||||
|
||||
axes.annotate('N', xy=(x, y), xytext=(x, y - arrow_length),
|
||||
arrowprops=dict(facecolor='black', width=6, headwidth=20),
|
||||
ha='center', va='center', fontsize=15,
|
||||
xycoords=axes.transAxes)
|
||||
|
||||
plt.show()
|
||||
|
||||
fig.savefig(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Images/Production/' +
|
||||
runLog['Short Description'][m] + '_HM0.png', bbox_inches='tight')
|
||||
|
||||
# %% Read time series
|
||||
MIKEds_list = [None] * (max(modelPlot) + 1)
|
||||
MIKEdsT_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m],
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
dfsIN_read = dfsIN.read()
|
||||
MIKEds_list[m] = dfsIN_read.to_dataframe()
|
||||
|
||||
dfsTIN = Dfs0(pl.Path(runLog['Run Location'][m],
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'TransectPTS.dfs0').as_posix())
|
||||
dfsTIN_read = dfsTIN.read()
|
||||
MIKEdsT_list[m] = dfsTIN_read.to_dataframe()
|
||||
|
||||
print(m)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del dfsIN_read
|
||||
del dfsIN
|
||||
del dfsTIN_read
|
||||
del dfsTIN
|
||||
|
||||
# %% Read in Toe and Crest Shapefiles
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Merge with data
|
||||
breakPointsOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimesOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds_list[m].shape[1]):
|
||||
paramName = MIKEds_list[m].columns.values[i][MIKEds_list[m].columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpFID = int(MIKEds_list[m].columns.values[i][1:MIKEds_list[m].columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds_list[m].columns.values[i][5:MIKEds_list[m].columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
print(i)
|
||||
|
||||
print(m)
|
||||
|
||||
breakPointsOut[m] = breakwaterPTS_merge
|
||||
breakTimesOut[m] = breakwaterPTS_times
|
||||
|
||||
# %% Read in Breakwater Transect Points Sh
|
||||
breakwaterT = pd.read_csv("C:/Users/arey/files/Projects/SouthShore/Bathy/BreakTransectPTS_Names.csv", sep='\t')
|
||||
|
||||
breakwaterT_PTS = gp.GeoDataFrame(breakwaterT, geometry=gp.points_from_xy(breakwaterT.X, breakwaterT.Y),
|
||||
crs='EPSG:32616')
|
||||
|
||||
# %% Merge with data
|
||||
breakPoints_TOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimes_TOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEdsT_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterT_PTS
|
||||
|
||||
for i in range(0, MIKEdsT_list[m].shape[1]):
|
||||
paramName = MIKEdsT_list[m].columns.values[i][MIKEdsT_list[m].columns.values[i].find(':', 5, -1) + 2:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpName = MIKEdsT_list[m].columns.values[i][0:MIKEdsT_list[m].columns.values[i].find(':', 1)]
|
||||
|
||||
breakwaterPTS_merge.loc[(breakwaterPTS_merge.Name == tmpName),
|
||||
paramName] = MIKEdsT_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEdsT_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakPoints_TOut[m] = breakwaterPTS_merge
|
||||
breakTimes_TOut[m] = breakwaterPTS_times
|
||||
|
||||
|
||||
#%% Format and save
|
||||
|
||||
for m in modelPlot:
|
||||
saveTmp = breakPointsOut[m].copy()
|
||||
saveTmp['X'] = saveTmp.geometry.x
|
||||
saveTmp['Y'] = saveTmp.geometry.y
|
||||
saveTmp.drop(['vertex_par', 'vertex_p_1', 'angle', 'geometry', 'index_right',
|
||||
'breakCrest_x', 'breakCrest_y', 'Length'], axis=1, inplace=True)
|
||||
saveTmp.sort_values(by=['FID', 'vertex_ind'], inplace=True, ignore_index=True)
|
||||
|
||||
# Reorder columns
|
||||
colNames = saveTmp.columns.values
|
||||
saveTmp = saveTmp[['X', 'Y', *colNames[0:-2]]]
|
||||
saveTmpT = saveTmp.transpose(copy=True)
|
||||
|
||||
# Transect points
|
||||
saveTmp2 = breakPoints_TOut[m].copy()
|
||||
saveTmp2.drop(['geometry'], axis=1, inplace=True)
|
||||
saveTmp2T = saveTmp2.transpose(copy=True)
|
||||
|
||||
|
||||
saveTmpT.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Toe' + runLog['Short Description'][m] + '.csv')
|
||||
|
||||
saveTmp2T.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Transect' + runLog['Short Description'][m] + '.csv')
|
||||
|
|
@ -0,0 +1,269 @@
|
|||
## Plotting Mike21 SW results for SouthShore
|
||||
# Author: AJMR
|
||||
# December 22, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfsu, Mesh, Dfs2, Dfs0
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "HD")
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(2, 6)
|
||||
|
||||
curSpeed_list = [None] * (max(modelPlot) + 1)
|
||||
curElm_list = [None] * (max(modelPlot) + 1)
|
||||
curU_list = [None] * (max(modelPlot) + 1)
|
||||
curV_list = [None] * (max(modelPlot) + 1)
|
||||
dfs_list = [None] * (max(modelPlot) + 1)
|
||||
ds_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfsu(pl.Path(runLog['Run Location'][m],
|
||||
runLog['Run Name'][m] + '.m21fm - Result Files', 'FullDomain.dfsu').as_posix())
|
||||
|
||||
dfs_list[m] = dfsIN
|
||||
ds_list[m] = dfs_list[m].read()
|
||||
curSpeed_list[m] = ds_list[m]["Current speed"][-1]
|
||||
curU_list[m] = ds_list[m]["U velocity"][-1]
|
||||
curV_list[m] = ds_list[m]["V velocity"][-1]
|
||||
curElm_list[m] = dfs_list[m].element_coordinates
|
||||
|
||||
# # Read Mesh for first model
|
||||
# mikeMeshIN = dfsIN.to_shapely()
|
||||
# # Convert to list of polygons
|
||||
# mikeMeshIN_list = [p for p in mikeMeshIN]
|
||||
|
||||
# Add to list
|
||||
# hmo_list[m] = gp.GeoDataFrame(hm0, geometry=mikeMeshIN_list)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
# del mikeMeshIN
|
||||
# del mikeMeshIN_list
|
||||
del dfsIN
|
||||
|
||||
# %% Plotting
|
||||
# Shaded Water
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/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)
|
||||
modelPlot = range(2, 6)
|
||||
|
||||
vmin = 0
|
||||
vmax = 1
|
||||
scale = 1 #5
|
||||
|
||||
for m in modelPlot:
|
||||
if m < 4:
|
||||
vmax = 5
|
||||
qmax = 4
|
||||
qfac = 1.5
|
||||
scale = 250
|
||||
else:
|
||||
vmax = 1
|
||||
qmax = 10
|
||||
qfac = 10
|
||||
scale = 250
|
||||
fig, axes = plt.subplots(figsize=(8, 8))
|
||||
|
||||
# Convert to feet and ignore missing
|
||||
cur_plot = curSpeed_list[m]*3.28084
|
||||
cur_nan = np.isnan(cur_plot)
|
||||
|
||||
axDHI = dfs_list[m].plot(cur_plot[~cur_nan], plot_type='contourf', show_mesh=False, cmap='viridis', ax=axes, levels=11,
|
||||
vmin=vmin, vmax=vmax, label='Current Speed (ft/s)',
|
||||
elements=dfs_list[m].element_ids[~cur_nan])
|
||||
|
||||
# Plot arrows on overset grid
|
||||
overGrid = dfs_list[m].get_overset_grid(dx=50)
|
||||
interpolant = dfs_list[m].get_2d_interpolant(overGrid.xy, n_nearest=1)
|
||||
|
||||
# Interpolate velocity at last time step by selecting time from dataset
|
||||
overGrid_Cur = dfs_list[m].interp2d(ds_list[m][ds_list[m].time[-1]:], *interpolant, shape=(overGrid.ny, overGrid.nx))
|
||||
|
||||
overGrid_U = overGrid_Cur["U velocity"][-1]
|
||||
overGrid_V = overGrid_Cur["V velocity"][-1]
|
||||
|
||||
# Normalize velocity above limit
|
||||
overGrid_U_Scale = overGrid_U*3.28084
|
||||
overGrid_V_Scale = overGrid_V*3.28084
|
||||
|
||||
r = np.power(np.add(np.power(overGrid_U_Scale * qfac, 2), np.power(overGrid_V_Scale * qfac, 2)), 0.5)
|
||||
curPlotMask = np.sqrt((overGrid_U_Scale * qfac) ** 2 + (overGrid_V_Scale * qfac) ** 2) > qmax
|
||||
|
||||
overGrid_U_Plot = np.zeros(overGrid_U_Scale.shape)
|
||||
overGrid_V_Plot = np.zeros(overGrid_V_Scale.shape)
|
||||
|
||||
# Scale arrows:
|
||||
# Arrows above qmax are scaled to qfac, multiplied by qmax, since the scaling factor (r) sets the magnitude to 1
|
||||
# Arrows below qmax are scaled by qface
|
||||
overGrid_U_Plot[curPlotMask] = ((overGrid_U_Scale[curPlotMask] * qfac)/r[curPlotMask]) * qmax
|
||||
overGrid_V_Plot[curPlotMask] = ((overGrid_V_Scale[curPlotMask] * qfac)/r[curPlotMask]) * qmax
|
||||
overGrid_U_Plot[~curPlotMask] = (overGrid_U_Scale[~curPlotMask])*qfac
|
||||
overGrid_V_Plot[~curPlotMask] = (overGrid_V_Scale[~curPlotMask])*qfac
|
||||
|
||||
qv = axDHI.quiver(overGrid.x, overGrid.y, overGrid_U_Plot, overGrid_V_Plot, scale=scale, color='k') #200
|
||||
|
||||
# # Add in scale bar and North Arrow
|
||||
# scalebar = AnchoredSizeBar(axes.transData,
|
||||
# 500, '500 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
# axes.add_artist(scalebar)
|
||||
|
||||
# axes.annotate('N', xy=(x, y), xytext=(x, y - arrow_length),
|
||||
# arrowprops=dict(facecolor='black', width=6, headwidth=20),
|
||||
# ha='center', va='center', fontsize=15,
|
||||
# xycoords=axes.transAxes)
|
||||
|
||||
axes.set_xlim(left=427800, right=431000)
|
||||
axes.set_ylim(bottom=4758000, top=4762000)
|
||||
# axes.set_xlim(left=428000, right=430500)
|
||||
# axes.set_ylim(bottom=4758750, top=4761000)
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
# axes.title.set_text(runLog['Short Description'][m])
|
||||
# axes.titlesize = 'x-large'
|
||||
fig.suptitle(runLog['Short Description'][m], fontsize=18)
|
||||
axes.set_xlabel('Easting [m]')
|
||||
axes.set_ylabel('Northing [m]')
|
||||
|
||||
plt.show()
|
||||
|
||||
fig.savefig(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/04_MIKE21_HD/Images/Production/' +
|
||||
runLog['Short Description'][m] + '_RevB_Current.png', bbox_inches='tight', dpi=300)
|
||||
|
||||
# %% Read time series
|
||||
MIKEds_list = [None] * (max(modelPlot) + 1)
|
||||
MIKEdsT_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
dfsIN_read = dfsIN.read()
|
||||
MIKEds_list[m] = dfsIN_read.to_dataframe()
|
||||
|
||||
dfsTIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'TransectPTS.dfs0').as_posix())
|
||||
dfsTIN_read = dfsTIN.read()
|
||||
MIKEdsT_list[m] = dfsTIN_read.to_dataframe()
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del dfsIN_read
|
||||
del dfsIN
|
||||
del dfsTIN_read
|
||||
del dfsTIN
|
||||
|
||||
# %% Read in Toe and Crest Shapefiles
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Merge with data
|
||||
breakPointsOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimesOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds_list[m].shape[1]):
|
||||
paramName = MIKEds_list[m].columns.values[i][MIKEds_list[m].columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpFID = int(MIKEds_list[m].columns.values[i][1:MIKEds_list[m].columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds_list[m].columns.values[i][5:MIKEds_list[m].columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimesOut[m] = breakwaterPTS_times
|
||||
|
||||
# %% Read in Breakwater Transect Points Sh
|
||||
breakwaterT = pd.read_csv("C:/Users/arey/files/Projects/SouthShore/Bathy/BreakTransectPTS_Names.csv", sep='\t')
|
||||
|
||||
breakwaterT_PTS = gp.GeoDataFrame(breakwaterT, geometry=gp.points_from_xy(breakwaterT.X, breakwaterT.Y),
|
||||
crs='EPSG:32616')
|
||||
|
||||
# %% Merge with data
|
||||
breakPoints_TOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimes_TOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEdsT_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterT_PTS
|
||||
|
||||
for i in range(0, MIKEdsT_list[m].shape[1]):
|
||||
paramName = MIKEdsT_list[m].columns.values[i][MIKEdsT_list[m].columns.values[i].find(':', 5, -1) + 2:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpName = MIKEdsT_list[m].columns.values[i][0:MIKEdsT_list[m].columns.values[i].find(':', 1)]
|
||||
|
||||
breakwaterPTS_merge.loc[(breakwaterPTS_merge.Name == tmpName),
|
||||
paramName] = MIKEdsT_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEdsT_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimes_TOut[m] = breakwaterPTS_times
|
||||
|
||||
|
||||
#%% Format and save
|
||||
|
||||
for m in modelPlot:
|
||||
saveTmp = breakTimesOut[m].copy()
|
||||
saveTmp['X'] = saveTmp.geometry.x
|
||||
saveTmp['Y'] = saveTmp.geometry.y
|
||||
saveTmp.drop(['vertex_par', 'vertex_p_1', 'angle', 'geometry', 'index_right',
|
||||
'breakCrest_x', 'breakCrest_y', 'Length'], axis=1, inplace=True)
|
||||
saveTmp.sort_values(by=['FID', 'vertex_ind'], inplace=True, ignore_index=True)
|
||||
|
||||
# Reorder columns
|
||||
colNames = saveTmp.columns.values
|
||||
saveTmp = saveTmp[['X', 'Y', *colNames[0:-2]]]
|
||||
saveTmpT = saveTmp.transpose(copy=True)
|
||||
|
||||
# Transect points
|
||||
saveTmp2 = breakTimes_TOut[m].copy()
|
||||
saveTmp2.drop(['geometry'], axis=1, inplace=True)
|
||||
saveTmp2T = saveTmp2.transpose(copy=True)
|
||||
|
||||
|
||||
saveTmpT.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Toe' + runLog['Short Description'][m] + '.csv')
|
||||
|
||||
saveTmp2T.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Transect' + runLog['Short Description'][m] + '.csv')
|
||||
|
|
@ -0,0 +1,259 @@
|
|||
## Plotting Mike21 SW results for SouthShore
|
||||
# Author: AJMR
|
||||
# December 22, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfsu, Mesh, Dfs2, Dfs0
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "HD")
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(2, 6)
|
||||
|
||||
curSpeed_list = [None] * (max(modelPlot) + 1)
|
||||
curElm_list = [None] * (max(modelPlot) + 1)
|
||||
curU_list = [None] * (max(modelPlot) + 1)
|
||||
curV_list = [None] * (max(modelPlot) + 1)
|
||||
dfs_list = [None] * (max(modelPlot) + 1)
|
||||
ds_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfsu(pl.Path(runLog['Run Location'][m],
|
||||
runLog['Run Name'][m] + '.m21fm - Result Files', 'FullDomain.dfsu').as_posix())
|
||||
|
||||
dfs_list[m] = dfsIN
|
||||
ds_list[m] = dfs_list[m].read()
|
||||
curSpeed_list[m] = ds_list[m]["Current speed"][-1]
|
||||
curU_list[m] = ds_list[m]["U velocity"][-1]
|
||||
curV_list[m] = ds_list[m]["V velocity"][-1]
|
||||
curElm_list[m] = dfs_list[m].element_coordinates
|
||||
|
||||
# # Read Mesh for first model
|
||||
# mikeMeshIN = dfsIN.to_shapely()
|
||||
# # Convert to list of polygons
|
||||
# mikeMeshIN_list = [p for p in mikeMeshIN]
|
||||
|
||||
# Add to list
|
||||
# hmo_list[m] = gp.GeoDataFrame(hm0, geometry=mikeMeshIN_list)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
# del mikeMeshIN
|
||||
# del mikeMeshIN_list
|
||||
del dfsIN
|
||||
|
||||
# %% Plotting
|
||||
# Shaded Water
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/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)
|
||||
modelPlot = range(2, 6)
|
||||
|
||||
vmin = 0
|
||||
vmax = 1
|
||||
scale = 1 #5
|
||||
|
||||
for m in modelPlot:
|
||||
if m < 4:
|
||||
vmax = 5
|
||||
qmax = 4
|
||||
scale = 50
|
||||
amin = 1
|
||||
else:
|
||||
vmax = 1
|
||||
qmax = 0.25
|
||||
scale = 75
|
||||
amin = 3
|
||||
|
||||
fig, axes = plt.subplots(figsize=(8, 8))
|
||||
|
||||
# Convert to feet and ignore missing
|
||||
cur_plot = curSpeed_list[m]*3.28084
|
||||
cur_nan = np.isnan(cur_plot)
|
||||
|
||||
axDHI = dfs_list[m].plot(cur_plot[~cur_nan], plot_type='contourf', show_mesh=False, cmap='viridis', ax=axes, levels=11,
|
||||
vmin=vmin, vmax=vmax, label='Current Speed (ft/s)',
|
||||
elements=dfs_list[m].element_ids[~cur_nan])
|
||||
|
||||
# Plot arrows on overset grid
|
||||
overGrid = dfs_list[m].get_overset_grid(dx=50)
|
||||
interpolant = dfs_list[m].get_2d_interpolant(overGrid.xy, n_nearest=1)
|
||||
|
||||
# Interpolate velocity at last time step by selecting time from dataset
|
||||
overGrid_Cur = dfs_list[m].interp2d(ds_list[m][ds_list[m].time[-1]:], *interpolant, shape=(overGrid.ny, overGrid.nx))
|
||||
|
||||
overGrid_U = overGrid_Cur["U velocity"][-1]
|
||||
overGrid_V = overGrid_Cur["V velocity"][-1]
|
||||
|
||||
# Normalize velocity above limit
|
||||
overGrid_U_Scale = overGrid_U*3.28084
|
||||
overGrid_V_Scale = overGrid_V*3.28084
|
||||
|
||||
r = np.power(np.add(np.power(overGrid_U_Scale, 2), np.power(overGrid_V_Scale, 2)), 0.5)
|
||||
curPlotMask = np.sqrt((overGrid_U_Scale) ** 2 + (overGrid_V_Scale) ** 2) > qmax
|
||||
|
||||
overGrid_U_Plot = np.zeros(overGrid_U_Scale.shape)
|
||||
overGrid_V_Plot = np.zeros(overGrid_V_Scale.shape)
|
||||
|
||||
# Normalize arrows to 1
|
||||
overGrid_U_Plot = overGrid_U_Scale / r
|
||||
overGrid_V_Plot = overGrid_V_Scale / r
|
||||
|
||||
# Scale arrows below qmax
|
||||
overGrid_U_Plot[~curPlotMask] = overGrid_U_Plot[~curPlotMask] * (r[~curPlotMask] / qmax)
|
||||
overGrid_V_Plot[~curPlotMask] = overGrid_V_Plot[~curPlotMask] * (r[~curPlotMask] / qmax)
|
||||
|
||||
qv = axDHI.quiver(overGrid.x, overGrid.y, overGrid_U_Plot, overGrid_V_Plot, scale=scale,
|
||||
color='k', headlength=3.5, headwidth=3.5, headaxislength=3.5, width=0.0015, minlength=amin) #200
|
||||
|
||||
axes.set_xlim(left=427800, right=431000)
|
||||
axes.set_ylim(bottom=4758000, top=4762000)
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
# axes.title.set_text(runLog['Short Description'][m])
|
||||
# axes.titlesize = 'x-large'
|
||||
fig.suptitle(runLog['Short Description'][m], fontsize=18)
|
||||
axes.set_xlabel('Easting [m]')
|
||||
axes.set_ylabel('Northing [m]')
|
||||
|
||||
plt.show()
|
||||
|
||||
fig.savefig(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/04_MIKE21_HD/Images/Production/' +
|
||||
runLog['Short Description'][m] + '_RevC_Current.png', bbox_inches='tight', dpi=300)
|
||||
|
||||
# %% Read time series
|
||||
MIKEds_list = [None] * (max(modelPlot) + 1)
|
||||
MIKEdsT_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
dfsIN_read = dfsIN.read()
|
||||
MIKEds_list[m] = dfsIN_read.to_dataframe()
|
||||
|
||||
dfsTIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'TransectPTS.dfs0').as_posix())
|
||||
dfsTIN_read = dfsTIN.read()
|
||||
MIKEdsT_list[m] = dfsTIN_read.to_dataframe()
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del dfsIN_read
|
||||
del dfsIN
|
||||
del dfsTIN_read
|
||||
del dfsTIN
|
||||
|
||||
# %% Read in Toe and Crest Shapefiles
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Merge with data
|
||||
breakPointsOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimesOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds_list[m].shape[1]):
|
||||
paramName = MIKEds_list[m].columns.values[i][MIKEds_list[m].columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpFID = int(MIKEds_list[m].columns.values[i][1:MIKEds_list[m].columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds_list[m].columns.values[i][5:MIKEds_list[m].columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimesOut[m] = breakwaterPTS_times
|
||||
|
||||
# %% Read in Breakwater Transect Points Sh
|
||||
breakwaterT = pd.read_csv("C:/Users/arey/files/Projects/SouthShore/Bathy/BreakTransectPTS_Names.csv", sep='\t')
|
||||
|
||||
breakwaterT_PTS = gp.GeoDataFrame(breakwaterT, geometry=gp.points_from_xy(breakwaterT.X, breakwaterT.Y),
|
||||
crs='EPSG:32616')
|
||||
|
||||
# %% Merge with data
|
||||
breakPoints_TOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimes_TOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEdsT_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterT_PTS
|
||||
|
||||
for i in range(0, MIKEdsT_list[m].shape[1]):
|
||||
paramName = MIKEdsT_list[m].columns.values[i][MIKEdsT_list[m].columns.values[i].find(':', 5, -1) + 2:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpName = MIKEdsT_list[m].columns.values[i][0:MIKEdsT_list[m].columns.values[i].find(':', 1)]
|
||||
|
||||
breakwaterPTS_merge.loc[(breakwaterPTS_merge.Name == tmpName),
|
||||
paramName] = MIKEdsT_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEdsT_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimes_TOut[m] = breakwaterPTS_times
|
||||
|
||||
|
||||
#%% Format and save
|
||||
|
||||
for m in modelPlot:
|
||||
saveTmp = breakTimesOut[m].copy()
|
||||
saveTmp['X'] = saveTmp.geometry.x
|
||||
saveTmp['Y'] = saveTmp.geometry.y
|
||||
saveTmp.drop(['vertex_par', 'vertex_p_1', 'angle', 'geometry', 'index_right',
|
||||
'breakCrest_x', 'breakCrest_y', 'Length'], axis=1, inplace=True)
|
||||
saveTmp.sort_values(by=['FID', 'vertex_ind'], inplace=True, ignore_index=True)
|
||||
|
||||
# Reorder columns
|
||||
colNames = saveTmp.columns.values
|
||||
saveTmp = saveTmp[['X', 'Y', *colNames[0:-2]]]
|
||||
saveTmpT = saveTmp.transpose(copy=True)
|
||||
|
||||
# Transect points
|
||||
saveTmp2 = breakTimes_TOut[m].copy()
|
||||
saveTmp2.drop(['geometry'], axis=1, inplace=True)
|
||||
saveTmp2T = saveTmp2.transpose(copy=True)
|
||||
|
||||
|
||||
saveTmpT.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Toe' + runLog['Short Description'][m] + '.csv')
|
||||
|
||||
saveTmp2T.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Transect' + runLog['Short Description'][m] + '.csv')
|
||||
|
|
@ -0,0 +1,216 @@
|
|||
## Plotting Mike21 SW results for SouthShore
|
||||
# Author: AJMR
|
||||
# December 22, 2021
|
||||
|
||||
# %% Setup Project
|
||||
from mikeio import Dfsu, Mesh, Dfs2, Dfs0
|
||||
from mikeio.eum import ItemInfo, EUMUnit, EUMType
|
||||
|
||||
import pandas as pd
|
||||
import pathlib as pl
|
||||
import numpy as np
|
||||
import geopandas as gp
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import contextily as ctx
|
||||
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar, AnchoredDirectionArrows
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
# %% Read Model Log
|
||||
|
||||
pth = pl.Path("//srv-mad3.baird.com/", "Projects", "13632.101 South Shore Breakwater", "06_Models",
|
||||
"13632.101.W.AJMR.Rev0_ModelLog.xlsx")
|
||||
runLog = pd.read_excel(pth.as_posix(), "ModelLog")
|
||||
|
||||
# %% Read Model Results
|
||||
modelPlot = range(20, 29)
|
||||
hmo_list = [None] * (max(modelPlot) + 1)
|
||||
dfs_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'ResultsMap.dfsu').as_posix())
|
||||
dfs_list[m] = dfsIN
|
||||
|
||||
ds = dfsIN.read()
|
||||
hmo_list[m] = ds["Sign. Wave Height"][1]
|
||||
|
||||
# # Read Mesh for first model
|
||||
# mikeMeshIN = dfsIN.to_shapely()
|
||||
# # Convert to list of polygons
|
||||
# mikeMeshIN_list = [p for p in mikeMeshIN]
|
||||
|
||||
# Add to list
|
||||
# hmo_list[m] = gp.GeoDataFrame(hm0, geometry=mikeMeshIN_list)
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
# del mikeMeshIN
|
||||
# del mikeMeshIN_list
|
||||
del dfsIN
|
||||
|
||||
# %% Plotting
|
||||
# Shaded Water
|
||||
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckemxgtk51fgp19nybfmdcb1e/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)
|
||||
modelPlot = range(28, 29)
|
||||
for m in modelPlot:
|
||||
fig, axes = plt.subplots(figsize=(8, 8))
|
||||
|
||||
# Convert to feet and ignore missing
|
||||
hm0_plot = hmo_list[m]*3.28084
|
||||
hm0_nan = np.isnan(hm0_plot)
|
||||
|
||||
dfs_list[m].plot(hm0_plot[~hm0_nan], plot_type='contourf', show_mesh=False, cmap='turbo', ax=axes, levels=21,
|
||||
vmin=0, vmax=20, label='Spectral significant wave height (ft)',
|
||||
elements=dfs_list[m].element_ids[~hm0_nan])
|
||||
|
||||
# # Add in scale bar and North Arrow
|
||||
# scalebar = AnchoredSizeBar(axes.transData,
|
||||
# 500, '500 m', 'lower right', pad=0.5, size_vertical=10, fontproperties=fontprops)
|
||||
# axes.add_artist(scalebar)
|
||||
|
||||
# axes.annotate('N', xy=(x, y), xytext=(x, y - arrow_length),
|
||||
# arrowprops=dict(facecolor='black', width=6, headwidth=20),
|
||||
# ha='center', va='center', fontsize=15,
|
||||
# xycoords=axes.transAxes)
|
||||
|
||||
axes.set_xlim(left=427800, right=431000)
|
||||
axes.set_ylim(bottom=4758000, top=4762000)
|
||||
|
||||
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32616')
|
||||
# axes.title.set_text(runLog['Short Description'][m])
|
||||
# axes.titlesize = 'x-large'
|
||||
fig.suptitle(runLog['Short Description'][m], fontsize=18)
|
||||
axes.set_xlabel('Easting [m]')
|
||||
axes.set_ylabel('Northing [m]')
|
||||
|
||||
plt.show()
|
||||
|
||||
fig.savefig(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Images/Production/' +
|
||||
runLog['Short Description'][m] + '_HM0.png', bbox_inches='tight', dpi=300)
|
||||
|
||||
# %% Read time series
|
||||
MIKEds_list = [None] * (max(modelPlot) + 1)
|
||||
MIKEdsT_list = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
dfsIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'BreakPts.dfs0').as_posix())
|
||||
dfsIN_read = dfsIN.read()
|
||||
MIKEds_list[m] = dfsIN_read.to_dataframe()
|
||||
|
||||
dfsTIN = Dfs0(pl.Path(runLog['Run Location'][m], str(runLog['Number'][m]) + '_' +
|
||||
runLog['Run Name'][m] + '.sw - Result Files', 'TransectPTS.dfs0').as_posix())
|
||||
dfsTIN_read = dfsTIN.read()
|
||||
MIKEdsT_list[m] = dfsTIN_read.to_dataframe()
|
||||
|
||||
# Cleanup unnecessary variables
|
||||
del dfsIN_read
|
||||
del dfsIN
|
||||
del dfsTIN_read
|
||||
del dfsTIN
|
||||
|
||||
# %% Read in Toe and Crest Shapefiles
|
||||
breakwaterPTS = gp.read_file("//srv-mad3.baird.com/Projects/"
|
||||
"13632.101 South Shore Breakwater/08_CADD/Outgoing/"
|
||||
"20211211_Toe Extents (to Alexander)/"
|
||||
"20211211_Toe_Extents_NAD83_WISStatePlaneSZn_USFt_Lines_OffshoreClipSimple_10m_vertexUTM.shp")
|
||||
breakCrest = pd.read_csv(
|
||||
'//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/08_CADD/Outgoing/20211214_Crest Points (to Alexander)/20211214_Crest_Points_m.csv',
|
||||
header=None, names=['x', 'y', 'z'])
|
||||
breakCrest_gdf = gp.GeoDataFrame(breakCrest, crs='EPSG:32154',
|
||||
geometry=gp.points_from_xy(breakCrest.x, breakCrest.y))
|
||||
breakCrest_gdf.to_crs('EPSG:32616', inplace=True)
|
||||
|
||||
breakwaterPTS_Crest = breakwaterPTS.sjoin_nearest(breakCrest_gdf)
|
||||
breakwaterPTS_Crest.rename(columns={'x': 'breakCrest_x', 'y': 'breakCrest_y', 'z': 'Crest'}, inplace=True)
|
||||
|
||||
# %% Merge with data
|
||||
breakPointsOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimesOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEds_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterPTS_Crest
|
||||
|
||||
for i in range(0, MIKEds_list[m].shape[1]):
|
||||
paramName = MIKEds_list[m].columns.values[i][MIKEds_list[m].columns.values[i].find('"', 5, -1) + 3:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpFID = int(MIKEds_list[m].columns.values[i][1:MIKEds_list[m].columns.values[i].find('"', 1)])
|
||||
tmpIND = int(MIKEds_list[m].columns.values[i][5:MIKEds_list[m].columns.values[i].find('"', 5)])
|
||||
|
||||
breakwaterPTS_merge.loc[((breakwaterPTS_merge.FID == tmpFID) &
|
||||
(breakwaterPTS_merge.vertex_ind == tmpIND)),
|
||||
paramName] = MIKEds_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEds_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimesOut[m] = breakwaterPTS_times
|
||||
|
||||
# %% Read in Breakwater Transect Points Sh
|
||||
breakwaterT = pd.read_csv("C:/Users/arey/files/Projects/SouthShore/Bathy/BreakTransectPTS_Names.csv", sep='\t')
|
||||
|
||||
breakwaterT_PTS = gp.GeoDataFrame(breakwaterT, geometry=gp.points_from_xy(breakwaterT.X, breakwaterT.Y),
|
||||
crs='EPSG:32616')
|
||||
|
||||
# %% Merge with data
|
||||
breakPoints_TOut = [None] * (max(modelPlot) + 1)
|
||||
breakTimes_TOut = [None] * (max(modelPlot) + 1)
|
||||
|
||||
for m in modelPlot:
|
||||
breakwaterPTS_times = None
|
||||
|
||||
for t in range(0, MIKEdsT_list[m].shape[0]):
|
||||
breakwaterPTS_merge = None
|
||||
breakwaterPTS_merge = breakwaterT_PTS
|
||||
|
||||
for i in range(0, MIKEdsT_list[m].shape[1]):
|
||||
paramName = MIKEdsT_list[m].columns.values[i][MIKEdsT_list[m].columns.values[i].find(':', 5, -1) + 2:]
|
||||
if paramName not in breakwaterPTS_merge.columns:
|
||||
breakwaterPTS_merge[paramName] = np.full([breakwaterPTS_merge.shape[0], 1], np.nan)
|
||||
tmpName = MIKEdsT_list[m].columns.values[i][0:MIKEdsT_list[m].columns.values[i].find(':', 1)]
|
||||
|
||||
breakwaterPTS_merge.loc[(breakwaterPTS_merge.Name == tmpName),
|
||||
paramName] = MIKEdsT_list[m].iloc[t, i]
|
||||
|
||||
breakwaterPTS_merge['Time'] = MIKEdsT_list[m].index[t]
|
||||
|
||||
breakwaterPTS_times = pd.concat([breakwaterPTS_times, breakwaterPTS_merge], ignore_index=True)
|
||||
|
||||
breakTimes_TOut[m] = breakwaterPTS_times
|
||||
|
||||
|
||||
#%% Format and save
|
||||
|
||||
for m in modelPlot:
|
||||
saveTmp = breakTimesOut[m].copy()
|
||||
saveTmp['X'] = saveTmp.geometry.x
|
||||
saveTmp['Y'] = saveTmp.geometry.y
|
||||
saveTmp.drop(['vertex_par', 'vertex_p_1', 'angle', 'geometry', 'index_right',
|
||||
'breakCrest_x', 'breakCrest_y', 'Length'], axis=1, inplace=True)
|
||||
saveTmp.sort_values(by=['FID', 'vertex_ind'], inplace=True, ignore_index=True)
|
||||
|
||||
# Reorder columns
|
||||
colNames = saveTmp.columns.values
|
||||
saveTmp = saveTmp[['X', 'Y', *colNames[0:-2]]]
|
||||
saveTmpT = saveTmp.transpose(copy=True)
|
||||
|
||||
# Transect points
|
||||
saveTmp2 = breakTimes_TOut[m].copy()
|
||||
saveTmp2.drop(['geometry'], axis=1, inplace=True)
|
||||
saveTmp2T = saveTmp2.transpose(copy=True)
|
||||
|
||||
|
||||
saveTmpT.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Toe' + runLog['Short Description'][m] + '.csv')
|
||||
|
||||
saveTmp2T.to_csv('//srv-mad3.baird.com/Projects/13632.101 South Shore Breakwater/06_Models/02_Mike21SW/Results/' +
|
||||
'Transect' + runLog['Short Description'][m] + '.csv')
|
||||
Loading…
Reference in New Issue