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Fig_SCHISM_hind_Pac.py
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Fig_SCHISM_hind_Pac.py
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#!/usr/bin/python3
import os
import fsspec
import xarray as xr
import numpy as np
import numpy.typing as npt
import typing as T
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import matplotlib.tri as tri
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.patches as patches
import imageio.v2 as imageio
import matplotlib
def dates_range(start_date, end_date):
"""
This function takes the start and end dates and returns
all the dates in between.
"""
dates = []
for i in range(
int(
(
datetime.strptime(end_date, "%Y%m%d")
- datetime.strptime(start_date, "%Y%m%d")
).days
)
+ 1
):
date = datetime.strptime(start_date, "%Y%m%d") + timedelta(days=i)
#dates.append(date.strftime("%m/%d/%y"))
dates.append(date)
return dates
def concat_stofs_pac(date, n, averaged=True):
"""
This function creates climatology (average) files for
STOFS Pacific data based on a start and end dates, e.g.:
clim_stofs_pac("20240801", "20240803")
"""
# dates = dates_range(start_date, end_date)
n=n+1
fs = fsspec.filesystem("s3", anon=True)
try:
ds = xr.open_dataset(
fs.open(
f"s3://noaa-nos-stofs3d-pds/STOFS-3D-Pac-shadow-VIMS/hindcasts/2018/RUN29c/outputs/temperature_{n}.nc"
),
chunks={},
engine='h5netcdf',
drop_variables=['vvel4.5','uvel4.5','vvel_bottom','uvel_bottom','vvel_surface','uvel_surface','salt_bottom','temp_bottom',
'precipitationRate',
'evaporationRate',
'windSpeedX',
'windSpeedY',
'windStressX',
'windStressY',
'dryFlagElement',
'dryFlagSide',
'dryFlagNode',
]
)
# # if averaged==True:
# # ds = ds.mean(dim='time')
# # ds = ds.isel(nSCHISM_vgrid_layers=-1)
print("Model data found for: ", date)
except:
print("No model data found for: ", date)
pass
# ds = xr.concat(ds_all,dim="time",data_vars="all")
# if averaged==True:
# ds = ds.mean(dim='time')
return ds
def split_quads(face_nodes: npt.NDArray[np.int_]) -> npt.NDArray[np.int_]:
"""
https://gist.github.com/pmav99/5ded91f18ef096b080b2ed45598c7d1c
copied from: https://github.com/ec-jrc/Thalassa/blob/master/thalassa/utils.py
"""
if face_nodes.shape[-1] != 4:
return face_nodes
existing_triangles = face_nodes[:, :3]
quad_indexes = np.nonzero(~np.isnan(face_nodes).any(axis=1))
quads = face_nodes[quad_indexes]
quads_first_column = quads[:, 0]
quads_last_two_columns = quads[:, -2:]
new_triangles = np.c_[quads_first_column, quads_last_two_columns]
new_face_nodes = T.cast(
npt.NDArray[np.int_],
np.r_[existing_triangles, new_triangles].astype(int),
)
return new_face_nodes
def fixed_connectivity_tri():
fs = fsspec.filesystem("s3", anon=True)
ds_tri = xr.open_dataset(
fs.open(
"s3://noaa-nos-stofs3d-pds/STOFS-3D-Pac-shadow-VIMS/hindcasts/2018/RUN29c/outputs/out2d_10.nc"#this is tri only
),
chunks={},
engine='h5netcdf',
drop_variables=['dryFlagNode','evaporationRate','precipitationRate','windSpeedX','windSpeedY','windStressX','windStressY','dryFlagElement','dryFlagSide']
)
connect=np.array(ds_tri['SCHISM_hgrid_face_nodes'][:])-1
connect_tri=split_quads(np.array(connect))
x, y = np.array(ds_tri['SCHISM_hgrid_node_x']), np.array(ds_tri['SCHISM_hgrid_node_y'])
depth=np.array(ds_tri.variables['depth'])
return x,y,connect_tri,depth
def plot_stofs_pac(
triangulation,
z,
depth=None,
isobaths=None,
output_dir="",
n=0,
long_name="name of the var",
time_str="time str",
vmin1=None,
vmax1=None,
latmin=None,
latmax=None,
lonmin=None,
lonmax=None,
interv=None):
fig = plt.figure(figsize=(7,10))
ax = fig.add_subplot(111)
ax.set_xlim(lonmin,lonmax)
ax.set_ylim(latmin,latmax)
tp = ax.tripcolor(triangulation, z,shading='gouraud',cmap='jet', vmin=vmin1, vmax=vmax1)#'gouraud' = linearly interp. 'flat'=averaged to tri
div = make_axes_locatable(ax)
cax = div.append_axes("right", size="5%", pad=0.2)
cb = fig.colorbar(tp,
cax=cax,
boundaries=np.arange(vmin1,vmax1,0.25),
extend='both',
# orientation='horizontal',
# location='bottom',
ticks=np.linspace(vmin1,vmax1,len([i for i in np.arange(vmin1,vmax1,1)])+1))#,interv))
cb.set_label(long_name)
ax.set_title(time_str)
ax.set_facecolor('grey')
if depth is not None and isobaths is not None:
depth[np.isnan(depth)] = -9999
ax.tricontour(triangulation, depth, levels=isobaths, linewidths=.5, colors="k")
fig.tight_layout()
fig.savefig(output_dir+'{:04d}.jpeg'.format(n))
# fig.savefig(output_dir+'{:04d}.jpeg'.format(n))
plt.clf()
matplotlib.pyplot.close()
def main(var,start_date,end_date,averaged,output_dir,timestep,isobaths):
if var == 'temperature':
long_name="Sea Surface Temperature (degC)"
dates = dates_range(start_date, end_date)
times = [dd.strftime("%m/%d/%y") for dd in dates]
x,y,connect_tri,depth = fixed_connectivity_tri()
triangulation = tri.Triangulation(x=x, y=y, triangles=connect_tri)
for n, date in enumerate(dates):
ds = concat_stofs_pac(date,n,averaged=averaged)
ds = np.array(ds.variables[var][12,:,-1])
time_str=times[n]
if var == 'temperature':
plot_stofs_pac(triangulation,
ds,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n=n,
long_name=long_name,
time_str=time_str,
vmin1=10,
vmax1=20,
latmin=42,
latmax=47,
lonmin=233,
lonmax=238,
interv=0.5,
)
files = os.listdir(output_dir)
images = []
for file in files:
images.append(imageio.imread(output_dir+file))
# os.remove(output_dir/file)
imageio.mimsave(output_dir+f'{start_date}_{end_date}_{var}.gif',images,loop=0)
if __name__ == '__main__':
# Enter your inputs here:
var = 'temperature'#'elev'#'salt_surface'#'temp_surface'
start_date='20180101'
end_date='20181231'
isobaths=[200,2000]#None
averaged=True #if True it calculates the climatology, if False it will be one file per timestep
output_dir=r"C:\Users\Felicio.Cassalho\Work\Modeling\AK_Project\STOFS_postprocessing\figures\hindcast_Temp_Pac/"
timestep=6 #every X hours
main(var,start_date,end_date,averaged,output_dir,timestep,isobaths)