621 lines
24 KiB
Python
621 lines
24 KiB
Python
## Plotting Mike21 SW results for SouthShore
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# Author: AJMR
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# December 22, 2021
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# %% Setup Project
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from mikeio import Dfsu, Mesh, Dfs2, Dfs0, Dfs1
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import pandas as pd
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import pathlib as pl
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import numpy as np
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import geopandas as gp
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import datetime as datetime
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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import time
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import matplotlib.animation as animation
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import contextily as ctx
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import matplotlib.font_manager as fm
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# %% Read Model Log
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pth = pl.Path("//srv-ott3.baird.com/", "Projects", "13539.101 L'Ansecoy Bay, Mustique", "06_Models",
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"Model Log Mustique.xlsx")
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runLog = pd.read_excel(pth.as_posix(), "ModelLog")
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# %% Read Map Model Results
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modelPlot = [8, 10, 11, 12, 13, 14]
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modelPlot = [15, 16, 17]
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dfs_list = [None] * (max(modelPlot) + 1)
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ds_list = [None] * (max(modelPlot) + 1)
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for m in modelPlot:
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dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], 'fullDomain3D.dfsu').as_posix())
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dfs_list[m] = dfsIN
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ds_list[m] = dfs_list[m].read()
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# %% Read Model Results at point
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modelPlot = [4, 10, 12, 13]
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dfs2d_list = [None] * (max(modelPlot) + 1)
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dfs3d_list = [None] * (max(modelPlot) + 1)
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z_list = [None] * (max(modelPlot) + 1)
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z_profile_list = [None] * (max(modelPlot) + 1)
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elm_list = [None] * (max(modelPlot) + 1)
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elm_df_list = [None] * (max(modelPlot) + 1)
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elm2d_list = [None] * (max(modelPlot) + 1)
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elm2d_df_list = [None] * (max(modelPlot) + 1)
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readPointsName = pd.read_csv("//srv-ott3.baird.com/Projects/13539.101 L'Ansecoy Bay, Mustique/03_Data/03_Field/01_September 2021 trip/Dataset locations_RevF.csv",
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delimiter=",")
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readPoints = pd.read_csv("//srv-ott3.baird.com/Projects/13539.101 L'Ansecoy Bay, Mustique/03_Data/03_Field/01_September 2021 trip/Dataset locations_RevF.csv",
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delimiter=",").iloc[0:, 2:-2].values
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for m in modelPlot:
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dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], 'fullDomain2D.dfsu').as_posix())
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dfs2d_list[m] = dfsIN
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# Read Map
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# ds_list[m] = dfs_list[m].read()
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# curU_list[m] = ds_list[m]["Depth averaged U velocity"]
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# curV_list[m] = ds_list[m]["Depth averaged V velocity"]
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# curElm_list[m] = dfs_list[m].element_coordinates
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# wl_list[m] = ds_list[m]["Surface elevation"]
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# z_list[m] = ds_list[m]["Z coordinate"]
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## Read specific points in 2D
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# Find nearest elements
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elem_ids = dfs2d_list[m].find_nearest_elements(readPoints[:, 0], readPoints[:, 1])
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# Read in data from nearest elements
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elm2d_list[m] = dfs2d_list[m].read(elements=elem_ids)
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# Convert to Pandas DataFrame
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elm2d_df_list[m] = [None] * readPoints.shape[0]
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for p in range(0, readPoints.shape[0]):
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elm2d_df_list[m][p] = elm2d_list[m].isel(idx=p).to_dataframe()
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## Read specific points 3D
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# Setup MIKE object
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dfsIN = Dfsu(pl.Path(runLog['Run Location'][m], 'fullDomain3D.dfsu').as_posix())
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dfs3d_list[m] = dfsIN
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# Find nearest elements
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elem_ids = dfs3d_list[m].find_nearest_profile_elements(readPoints[:, 0], readPoints[:, 1])
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# Read from elements- flatten 2d element array (xy and z) to 1d for reading
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elm_list[m] = dfs3d_list[m].read(elements=elem_ids.flatten().astype(int))
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elm_df_list[m] = [None] * readPoints.shape[0]
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z_profile_list[m] = [None] * readPoints.shape[0]
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# Convert to Pandas DataFrame
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# Loop through points, selecting corresponding depths
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for p in range(0, readPoints.shape[0]):
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z_profile_list[m][p] = dfs3d_list[m].element_coordinates[elem_ids[p, :].astype(int), 2]
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# Convert to Pandas and add zidx
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for z in range(0, z_profile_list[m][p].shape[0]):
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df_tmp = elm_list[m].isel(idx=p * 5 + z).to_dataframe()
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df_tmp['Z'] = z_profile_list[m][p][z]
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df_tmp['Z_IDX'] = z
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if z == 0:
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elm_df_list[m][p] = df_tmp
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else:
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elm_df_list[m][p] = elm_df_list[m][p].append(df_tmp)
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del df_tmp
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# %% Import RBR data
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rbr_path = "C:/Users/arey/files/Projects/Mustique/041279_20211203_1541Ruskin.xlsx"
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rbr_pd = pd.read_excel(rbr_path, sheet_name='Wave', parse_dates=True, header=1, index_col=0)
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rbr_pd['WL'] = rbr_pd['Depth'] - rbr_pd['Depth'].mean() - 0.2
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# Correct time zone
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rbr_pd.index = rbr_pd.index + datetime.timedelta(hours=4)
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# %% Import Nortek Eco data
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eco_path_1 = "//srv-ott3/Projects/13539.101 L'Ansecoy Bay, Mustique/03_Data/03_Field/01_September 2021 trip/02_Nortek ECO/Eco61_20210910184606.csv"
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eco_path_2 = "//srv-ott3/Projects/13539.101 L'Ansecoy Bay, Mustique/03_Data/03_Field/01_September 2021 trip/02_Nortek ECO/Eco214_20210902120703.csv"
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eco1_pd = pd.read_csv(eco_path_1, sep=',', header=[28], index_col=0,
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parse_dates=False)
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eco2_pd = pd.read_csv(eco_path_2, sep=',', header=[28], index_col=0,
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parse_dates=False)
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# Drop first row
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eco1_pd.drop(eco1_pd.index[0], inplace=True)
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eco2_pd.drop(eco2_pd.index[0], inplace=True)
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eco1_pd.index = pd.to_datetime(eco1_pd.index, format='%m/%d/%Y %I:%M:%S %p')
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eco2_pd.index = pd.to_datetime(eco2_pd.index, format='%m/%d/%Y %I:%M:%S %p')
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# Set water level to zero
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eco1_pd['WL'] = eco1_pd['Depth'].astype(float) - eco1_pd['Depth'].astype(float).mean(skipna=True) + 0.2
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eco2_pd['WL'] = eco2_pd['Depth'].astype(float) - eco2_pd['Depth'].astype(float).mean(skipna=True) + 0.2
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# Correct time zone
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eco1_pd.index = eco1_pd.index + datetime.timedelta(hours=4)
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eco2_pd.index = eco2_pd.index + datetime.timedelta(hours=4)
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# %% Read in boundary conditions
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ds_wl = []
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dfs1 = Dfs1("//oak-spillway.baird.com/D/13539.101 L'Ansecoy Bay, Mustique/MIKE3/02_Bounds/NCOM2_EastBound.dfs1")
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ds_wl.append(dfs1.read())
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dfs1 = Dfs1("//oak-spillway.baird.com/D/13539.101 L'Ansecoy Bay, Mustique/MIKE3/02_Bounds/NCOM2_NorthBound.dfs1")
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ds_wl.append(dfs1.read())
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dfs1 = Dfs1("//oak-spillway.baird.com/D/13539.101 L'Ansecoy Bay, Mustique/MIKE3/02_Bounds/NCOM2_SouthBound.dfs1")
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ds_wl.append(dfs1.read())
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dfs1 = Dfs1("//oak-spillway.baird.com/D/13539.101 L'Ansecoy Bay, Mustique/MIKE3/02_Bounds/NCOM2_WestBound.dfs1")
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ds_wl.append(dfs1.read())
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# %% Plot Water Level at a point
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fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(8, 8), sharex=True)
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plotstart = '2021-10-01 00:00:00'
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plotend = '2021-10-15 00:00:00'
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# plotstart = '2021-10-05 00:00:00'
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# plotend = '2021-10-07 00:00:00'
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modelPlot = [13]
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for m in modelPlot:
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for sub, p in enumerate([5, 9, 6]):
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if p == 9:
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rbr_pd['WL'].plot(ax=axes[sub], color='k', label='Nearshore East Obervations')
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elif p == 5:
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eco1_pd['WL'].plot(ax=axes[sub], color='k', label='Offshore Obervations')
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elif p == 6:
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eco2_pd['WL'].plot(ax=axes[sub], color='k', label='Nearshore West Obervations')
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elm2d_df_list[m][p].plot(y='Surface elevation', ax=axes[sub], label='Model')
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axes[sub].legend(loc="upper left")
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axes[sub].set_xlim(pd.Timestamp(plotstart), pd.Timestamp(plotend))
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axes[sub].set_ylim(-1.0, 1.0)
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axes[sub].set_ylabel('Water Level (m)')
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axes[sub].set_xlabel('Date')
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plt.show()
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fig.savefig('//srv-ott3.baird.com/Projects/13539.101 L\'Ansecoy Bay, Mustique/06_Models/01_MIKE3/00_Figures/' +
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'/wl_TS_RevB.png', bbox_inches='tight')
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# %% Velocity point U and V
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# Z_IDX = 4
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# ecoVar1 = 'Upper speed U'
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# ecoVar2 = 'Upper speed V'
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# ecoVar3 = 'Upper speed'
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# ecoVar4 = 'Upper direction'
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# plotstart = '2021-09-14 00:00:00'
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# # plotend = '2021-09-16 00:00:00'
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# plotend = '2021-10-03 00:00:00'
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plotstart = '2021-10-01 00:00:00'
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# plotend = '2021-09-16 00:00:00'
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plotend = '2021-10-21 00:00:00'
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# plotstart = '2021-10-05 00:00:00'
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# plotend = '2021-10-07 00:00:00'
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Z_IDX = 2
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ecoVar1 = 'Middle speed U'
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ecoVar2 = 'Middle speed V'
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ecoVar3 = 'Middle speed'
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ecoVar4 = 'Middle direction'
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# Z_IDX = 1
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# ecoVar1 = 'Lower speed U'
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# ecoVar2 = 'Lower speed V'
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# ecoVar3 = 'Lower speed'
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# ecoVar4 = 'Lower direction'
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fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(8, 4), sharex=True)
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modelPlot = [13]
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for m in modelPlot:
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eco1_pd[ecoVar1] = eco1_pd[ecoVar3].astype(float) * \
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np.sin(np.radians(eco1_pd[ecoVar4].astype(float).to_numpy()))
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eco1_pd[ecoVar1].astype(float).plot(ax=axes[0], color='k', label='Observations')
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elm_df_list[m][3].loc[elm_df_list[m][5]['Z_IDX'] == Z_IDX, :].plot(
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y='U velocity', ax=axes[0], label='Model')
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axes[0].set_ylim(-0.5, 0.5)
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axes[0].set_xlim(pd.Timestamp(plotstart), pd.Timestamp(plotend))
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axes[0].set_ylabel('Nearshore U (m/s)')
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axes[0].legend(bbox_to_anchor=(0.90, 1), loc="upper left")
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eco1_pd[ecoVar2] = eco1_pd[ecoVar3].astype(float) * \
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np.cos(np.radians(eco1_pd[ecoVar4].astype(float).to_numpy()))
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eco1_pd[ecoVar2].astype(float).plot(ax=axes[1], color='k', label='Observations')
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elm_df_list[m][5].loc[elm_df_list[m][5]['Z_IDX'] == Z_IDX, :].plot(
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y='V velocity', ax=axes[1], label='Model')
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axes[1].set_ylim(-0.5, 0.5)
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axes[1].set_xlim(pd.Timestamp(plotstart), pd.Timestamp(plotend))
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axes[1].set_ylabel('Nearshore V (m/s)')
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axes[1].legend(bbox_to_anchor=(0.90, 1), loc="upper left")
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# eco2_pd[ecoVar1] = eco2_pd[ecoVar3].astype(float) * \
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# np.sin(np.radians(eco2_pd[ecoVar4].astype(float).to_numpy()))
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# eco2_pd[ecoVar1].astype(float).plot(ax=axes[2], color='k', label='Observations')
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# elm_df_list[m][6].loc[elm_df_list[m][6]['Z_IDX'] == Z_IDX, :].plot(
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# y='U velocity', ax=axes[2], label='Model')
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# axes[2].set_ylim(-1.5, 1.5)
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# axes[2].set_xlim(pd.Timestamp(plotstart), pd.Timestamp(plotend))
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# axes[2].set_ylabel('Offshore U (m/s)')
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# axes[2].legend(bbox_to_anchor=(0.90, 1), loc="upper left")
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#
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# eco2_pd[ecoVar2] = eco2_pd[ecoVar3].astype(float) * \
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# np.cos(np.radians(eco2_pd[ecoVar4].astype(float).to_numpy()))
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# eco2_pd[ecoVar2].astype(float).plot(ax=axes[3], color='k', label='Observations')
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# elm_df_list[m][5].loc[elm_df_list[m][6]['Z_IDX'] == Z_IDX, :].plot(
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# y='V velocity', ax=axes[3], label='Model')
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#
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# axes[3].set_ylim(-1.00, 1.00)
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# axes[3].set_xlim(pd.Timestamp(plotstart), pd.Timestamp(plotend))
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# axes[3].set_ylabel('Offshore V (m/s)')
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# axes[3].legend(bbox_to_anchor=(0.90, 1), loc="upper left")
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axes[1].set_xlabel('Date')
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plt.show()
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fig.savefig('//srv-ott3.baird.com/Projects/13539.101 L\'Ansecoy Bay, Mustique/06_Models/01_MIKE3/00_Figures/' +
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'/uVel_TS_RevC.png', bbox_inches='tight')
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# %% Subplot Map Plotting
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mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckex9vtri0o6619p55sl5qiyv/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
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x, y, arrow_length = 0.93, 0.95, 0.12
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fontprops = fm.FontProperties(size=12)
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modelPlot = [15, 16, 17]
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tStepsPlot = np.zeros((5, 6))
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tStepsPlot[0, :] = range(110, 116)
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tStepsPlot[1, :] = range(158, 164)
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tStepsPlot[2, :] = range(206, 212)
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tStepsPlot[3, :] = range(255, 261)
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tStepsPlot[4, :] = range(138, 144)
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for m in modelPlot:
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vmax = 34.0
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vmin = 33.7
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cmap = 'inferno'
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if m == 8 or m == 17:
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disPlot = 7
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elif m == 11 or m == 15:
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disPlot = 13
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elif m == 14 or m == 16:
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disPlot = 8
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for a in range(0, 5):
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fig, axes = plt.subplots(nrows=2, ncols=3, sharey=True, sharex=True, figsize=(16, 9))
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ax = axes.flatten()
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for t in range(0, 6):
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# Plot salinity
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# Select salinity data at selected time step
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plotDat = ds_list[m]['Salinity'][int(tStepsPlot[a, t]), :]
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# Identify nan values
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plot_nan = np.isnan(plotDat)
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# Add additional nan values to show bed
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plot_nan = plot_nan | (plotDat < 33.725)
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# Plot all selected values at a given later and not nan
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axDHI = dfs_list[m].plot(plotDat[(dfs_list[m].layer_ids == 0) & (~plot_nan)], plot_type='contourf',
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show_mesh=False, cmap=cmap, ax=ax[t], add_colorbar=False,
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vmin=vmin, vmax=vmax,
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elements=dfs_list[m].element_ids[(dfs_list[m].layer_ids == 0) & (~plot_nan)])
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# Add discharge point
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ax[t].scatter(readPoints[disPlot, 0], readPoints[disPlot, 1], marker='^', color='r', s=20)
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# ax[t].set_xlim(left=696680.7, right=698252.7)
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# ax[t].set_ylim(bottom=1425547.5, top=1426681.8)
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ax[t].set_xlim(left=696508.3, right=698252.7)
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ax[t].set_ylim(bottom=1425267.0, top=1426681.8)
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ctx.add_basemap(ax[t], source=mapbox, crs='EPSG:32620')
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ax[t].title.set_text(str(ds_list[m].time[int(tStepsPlot[a, t])]))
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ax[t].xaxis.set_major_locator(plt.MaxNLocator(4))
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# axes.titlesize = 'x-large'
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# fig.suptitle(runLog['Short Description'][m], fontsize=18)
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# ax[t].set_xlabel('Easting [m]')
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# ax[t].set_ylabel('Northing [m]')
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fig.subplots_adjust(right=0.8)
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cmap = mpl.cm.inferno
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norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
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cax = plt.axes([0.85, 0.2, 0.05, 0.6])
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cb1 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
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norm=norm,
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orientation='vertical')
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cb1.set_label('Salinity (PSU)')
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plt.show()
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fig.savefig('//srv-ott3.baird.com/Projects/13539.101 L\'Ansecoy Bay, Mustique/06_Models/01_MIKE3/00_Figures/' +
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'/Plume_6_Plot_' + runLog['Run'][m][0:-20] +'_Alt' + str(a) + '.png', bbox_inches='tight')
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# %% Map Plotting
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mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckex9vtri0o6619p55sl5qiyv/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
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x, y, arrow_length = 0.93, 0.95, 0.12
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fontprops = fm.FontProperties(size=12)
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modelPlot = range(8, 9)
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for m in modelPlot:
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vmax = 34.2
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vmin = 34
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fig, axes = plt.subplots(figsize=(8, 8))
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# Plot salinity
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# Select salinity data at last time step
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plotDat = ds_list[m]['Salinity'][-1, :]
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# Identify nan values
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plot_nan = np.isnan(plotDat)
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|
|
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# Add additional nan values to show bed
|
|
plot_nan = plot_nan | (plotDat<34.05)
|
|
|
|
# Plot all selected values at a given later and not nan
|
|
axDHI = dfs_list[m].plot(plotDat[(dfs_list[m].layer_ids == 1) & (~plot_nan)], plot_type='contourf',
|
|
show_mesh=False, cmap='inferno', ax=axes,
|
|
vmin=vmin, vmax=vmax, label='Salinity (PSU)',
|
|
elements=dfs_list[m].element_ids[(dfs_list[m].layer_ids == 1) & (~plot_nan)])
|
|
|
|
|
|
axes.set_xlim(left=696680.7, right=698252.7)
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axes.set_ylim(bottom=1425547.5, top=1426681.8)
|
|
|
|
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32620')
|
|
# 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()
|
|
|
|
|
|
# %% Animated map
|
|
plt.rcParams['animation.ffmpeg_path'] = 'C:/Users/arey/Local/ffmpeg-2022-02-14-git-59c647bcf3-full_build/bin/ffmpeg.exe'
|
|
|
|
mapbox = 'https://api.mapbox.com/styles/v1/alexander0042/ckex9vtri0o6619p55sl5qiyv/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1IjoiYWxleGFuZGVyMDA0MiIsImEiOiJjazVmdG4zbncwMHY4M2VrcThwZGUzZDFhIn0.w6oDHoo1eCeRlSBpwzwVtw'
|
|
x, y, arrow_length = 0.93, 0.95, 0.12
|
|
fontprops = fm.FontProperties(size=12)
|
|
|
|
# Set model to plot
|
|
modelPlot = [15, 16, 17]
|
|
m = 16
|
|
|
|
# m = 11
|
|
vmax = 34.0
|
|
vmin = 33.7
|
|
cmap = 'inferno'
|
|
|
|
metadata = dict(title='Movie Test', artist='Matplotlib',
|
|
comment='Movie support')
|
|
writer = animation.FFMpegWriter(fps=2, metadata=metadata, codec='h264')
|
|
fig, axes = plt.subplots(figsize=(8, 8))
|
|
|
|
writer.setup(fig, 'C:/Users/arey/files/Projects/Mustique/' +
|
|
runLog['Run'][m][0:-20] + 'Intake.mp4')
|
|
|
|
# Animation function
|
|
for i in np.arange(1, 384, 1): #384
|
|
if m == 8 or m == 17:
|
|
disPlot = 7
|
|
elif m == 11 or m == 15:
|
|
disPlot = 13
|
|
elif m == 14 or m == 16:
|
|
disPlot = 8
|
|
|
|
# fig, axes = plt.subplots(figsize=(8, 8))
|
|
axes.cla()
|
|
|
|
# Plot salinity
|
|
# Select salinity data at last time step
|
|
plotDat = ds_list[m]['Salinity'][i, :]
|
|
# Identify nan values
|
|
plot_nan = np.isnan(plotDat)
|
|
|
|
# Add additional nan values to show bed
|
|
plot_nan = plot_nan | (plotDat<33.725)
|
|
|
|
# Plot all selected values at a given later and not nan
|
|
axDHI = dfs_list[m].plot(plotDat[(dfs_list[m].layer_ids == 0) & (~plot_nan)], plot_type='contourf',
|
|
show_mesh=False, cmap='inferno', ax=axes, add_colorbar=False,
|
|
vmin=vmin, vmax=vmax, label='Salinity (PSU)', levels=24,
|
|
elements=dfs_list[m].element_ids[(dfs_list[m].layer_ids == 0) & (~plot_nan)])
|
|
|
|
axes.scatter(readPoints[disPlot, 0], readPoints[disPlot, 1], marker='^', color='r', s=20)
|
|
# axes.set_xlim(left=696680.7, right=698252.7)
|
|
# axes.set_ylim(bottom=1425547.5, top=1426681.8)
|
|
axes.set_xlim(left=696508.3, right=698252.7)
|
|
axes.set_ylim(bottom=1425267.0, top=1426681.8)
|
|
|
|
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32620')
|
|
axes.set_xlabel('Easting [m]')
|
|
axes.set_ylabel('Northing [m]')
|
|
|
|
axes.title.set_text(str(ds_list[m].time[i]))
|
|
|
|
if i == 1:
|
|
fig.subplots_adjust(right=0.8)
|
|
cmap = mpl.cm.inferno
|
|
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
|
|
cax = plt.axes([0.82, 0.25, 0.04, 0.5])
|
|
cb1 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
|
|
norm=norm,
|
|
orientation='vertical')
|
|
cb1.set_label('Salinity (PSU)')
|
|
|
|
|
|
writer.grab_frame()
|
|
# plt.show()
|
|
print(i)
|
|
|
|
writer.finish()
|
|
|
|
|
|
# %% Plot Bathymetry
|
|
|
|
fig, axes = plt.subplots(figsize=(8, 8))
|
|
# Convert to feet and ignore missing
|
|
axDHI = dfs_list[m].plot(bed_plot[~bed_nan], plot_type='contourf', show_mesh=False, cmap='magma_r', ax=axes, levels=9,
|
|
vmin=-80, vmax=0, label='Bed Elevation (ft)',
|
|
elements=dfs_list[m].element_ids[~bed_nan])
|
|
|
|
axes.set_xlim(left=427800, right=431000)
|
|
axes.set_ylim(bottom=4758000, top=4762500)
|
|
|
|
ctx.add_basemap(axes, source=mapbox, crs='EPSG:32620')
|
|
|
|
fig.suptitle('Bed Elevation', fontsize=18)
|
|
axes.set_xlabel('Easting [m]')
|
|
axes.set_ylabel('Northing [m]')
|
|
|
|
plt.show()
|
|
|
|
# fig.savefig(
|
|
# '//srv-mad3/Projects/13632.101 South Shore Breakwater/10_Reports&Pres/13632.101.R3 Ph I BOD/Support files/' +
|
|
# 'Bed_Elevation.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')
|