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Fig_STOFS_Pac.py
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Fig_STOFS_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
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(start_date, end_date, 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)
ds_all=[]
for date in dates:
print(date)
try:
fs = fsspec.filesystem("s3", anon=True)
ds1 = xr.open_dataset(
fs.open(
f"s3://noaa-nos-stofs3d-pds/STOFS-3D-Pac/para/stofs_3d_pac.{date.strftime('%Y%m%d')}/stofs_3d_pac.t12z.field2d_n001_012.nc"#this is tri only
),
chunks={},
engine='h5netcdf',
drop_variables=['vvel4.5',
'uvel4.5',
'vvel_bottom',
'uvel_bottom',
'vvel_surface',
'uvel_surface',
'salt_bottom',
'temp_bottom',
# 'depth',
]
)
ds2 = xr.open_dataset(
fs.open(
f"s3://noaa-nos-stofs3d-pds/STOFS-3D-Pac/para/stofs_3d_pac.{date.strftime('%Y%m%d')}/stofs_3d_pac.t12z.field2d_n013_024.nc"#this is tri only
),
chunks={},
engine='h5netcdf',
drop_variables=['vvel4.5',
'uvel4.5',
'vvel_bottom',
'uvel_bottom',
'vvel_surface',
'uvel_surface',
'salt_bottom',
'temp_bottom',
# 'depth',
]
)
ds = xr.concat([ds1,ds2],dim="time",data_vars="all")
if averaged==True:
ds = ds.mean(dim='time')
ds_all.append(ds)
except:
ds = xr.open_dataset(
fs.open(
f"s3://noaa-nos-stofs3d-pds/STOFS-3D-Pac/para/stofs_3d_pac.{date.strftime('%Y%m%d')}/stofs_3d_pac.t12z.n001_024.field2d.nc"#this is tri only
),
chunks={},
engine='h5netcdf',
drop_variables=['vvel4.5',
'uvel4.5',
'vvel_bottom',
'uvel_bottom',
'vvel_surface',
'uvel_surface',
'salt_bottom',
'temp_bottom',
# 'depth'
]
)
if averaged==True:
ds = ds.mean(dim='time')
ds_all.append(ds)
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/para/stofs_3d_pac.20241001/stofs_3d_pac.t12z.fields.out2d_n001_012.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'])
return x,y,connect_tri
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,
latmin2=None,
latmax2=None,
lonmin2=None,
lonmax2=None,
vmin2=None,
vmax2=None,
latmin3=None,
latmax3=None,
lonmin3=None,
lonmax3=None,
vmin3=None,
vmax3=None,
interv=None):
fig = plt.figure(figsize=(10,9))
ax = fig.add_subplot(212)
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, extend='both',boundaries=np.arange(vmin1,vmax1,interv))
cb.set_label(long_name)
rect1 = patches.Rectangle((lonmin2, latmin2), lonmax2-lonmin2, latmax2-latmin2, linewidth=1, edgecolor='k', facecolor='none')
rect2 = patches.Rectangle((lonmin3, latmin3), lonmax3-lonmin3, latmax3-latmin3, linewidth=1, edgecolor='k', facecolor='none')
ax.add_patch(rect1)
ax.add_patch(rect2)
ax.set_title(time_str)
ax.set_facecolor('grey')
ax2 = fig.add_subplot(221)
ax2.set_xlim(lonmin2,lonmax2)
ax2.set_ylim(latmin2,latmax2)
tp2 = ax2.tripcolor(triangulation, z,shading='gouraud',cmap='jet', vmin=vmin2, vmax=vmax2)
div2 = make_axes_locatable(ax2)
cax2 = div2.append_axes("right", size="5%", pad=0.2)
cb2 = fig.colorbar(tp2, cax=cax2, extend='both',boundaries=np.arange(vmin2,vmax2,interv))
ax2.set_facecolor('grey')
ax3 = fig.add_subplot(222)
ax3.set_xlim(lonmin3,lonmax3)
ax3.set_ylim(latmin3,latmax3)
tp3 = ax3.tripcolor(triangulation, z,shading='gouraud',cmap='jet', vmin=vmin3, vmax=vmax3)
div3 = make_axes_locatable(ax3)
cax3 = div3.append_axes("right", size="5%", pad=0.2)
cb3 = fig.colorbar(tp3, cax=cax3, extend='both',boundaries=np.arange(vmin3,vmax3,interv))
ax3.set_facecolor('grey')
if depth is not None and isobaths is not None:
depth[np.isnan(depth)] = -9999
ax2.tricontour(triangulation, depth, levels=isobaths, linewidths=.75, colors="k")
ax3.tricontour(triangulation, depth, levels=isobaths, linewidths=.75, colors="k")
fig.tight_layout()
if isinstance(n, str):
fig.savefig(output_dir+'{}.jpeg'.format(n))
else:
fig.savefig(output_dir+'{:04d}.jpeg'.format(n))
# fig.savefig(output_dir+'{:04d}.jpeg'.format(n))
plt.clf()
def main(var,start_date,end_date,averaged,output_dir,timestep,isobaths):
ds = concat_stofs_pac(start_date,end_date,averaged=averaged)
if var == 'temp_surface':
long_name="Sea Surface Temperature (degC)"
if var == 'salt_surface':
long_name="Sea Surface Salinity (psu)"
if var == 'elev':
long_name="Sea Surface Height (m)"
if averaged==False:
times=[str(tt).split('.')[0] for tt in np.array(ds['time'][:])]
else:
times=f"average from {start_date} to {end_date}"
if isobaths is not None and averaged == False:
depth=np.array(ds.variables['depth'][0])
if isobaths is not None and averaged == True:
depth=np.array(ds.variables['depth'])
else:
depth=None
ds = np.array(ds.variables[var])
print("here is depth:",depth)
x,y,connect_tri = fixed_connectivity_tri()
triangulation = tri.Triangulation(x=x, y=y, triangles=connect_tri)
if averaged==False:
for n in range(0, len(ds), timestep):
print(n)
z = ds[n]
time_str=times[n]
if var == 'temp_surface':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n=n,
long_name=long_name,
time_str=time_str,
vmin1=0,
vmax1=32,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=5,
vmax2=15,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=10,
vmax3=20,
interv=0.5,
)
if var == 'salt_surface':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n=n,
long_name=long_name,
time_str=time_str,
vmin1=30,
vmax1=37,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=28,
vmax2=34.5,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=27,
vmax3=33.5,
interv=0.5,
)
if var == 'elev':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n=n,
long_name=long_name,
time_str=time_str,
vmin1=-2.0,
vmax1=2.0,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=-1,#5,
vmax2=1,#15,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=-1.5,
vmax3=1.5,
interv=0.1,
)
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)
else:
z=ds
if var == 'temp_surface':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n="average_temp_surface",
long_name=long_name,
time_str=times,
vmin1=0,
vmax1=32,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=5,
vmax2=15,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=10,
vmax3=20,
interv=0.5,
)
if var == 'salt_surface':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n="average_salt_surface",
long_name=long_name,
time_str=times,
vmin1=30,
vmax1=37,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=28,
vmax2=34.5,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=27,
vmax3=33.5,
interv=0.5,
)
if var == 'elev':
plot_stofs_pac(triangulation,
z,
depth=depth,
isobaths=isobaths,
output_dir=output_dir,
n="average_height_surface",
long_name=long_name,
time_str=times,
vmin1=-2.0,
vmax1=2.0,
latmin2=45,
latmax2=67,
lonmin2=170,
lonmax2=200,
vmin2=-1,#5,
vmax2=1,#15,
latmin3=42,
latmax3=47,
lonmin3=233,
lonmax3=238,
vmin3=-1.5,
vmax3=1.5,
interv=0.1,
)
if __name__ == '__main__':
# Enter your inputs here:
var = 'temp_surface'#'elev'#'salt_surface'#'temp_surface'
start_date='20240801'
end_date='20240801'
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\2024_08_sst/"
timestep=6 #every X hours
main(var,start_date,end_date,averaged,output_dir,timestep,isobaths)