Difference between revisions of "Plots With PyVista"
From Planets
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| − | <syntaxhighlight lang="python" | + | <syntaxhighlight lang="python"> |
| + | import pyvista as pv | ||
| + | import numpy as np | ||
| + | from netCDF4 import Dataset | ||
| + | # import all the required libraries (netcdf4, pyvista) | ||
</syntaxhighlight> | </syntaxhighlight> | ||
| + | <syntaxhighlight lang="python"> | ||
| + | #FIRST WE GET THE DATA FROM THE GCM SIMULATION | ||
| − | <syntaxhighlight lang="python" | + | # 4D GRID VARIABLES |
| + | nc1 = Dataset('diagfi.nc') | ||
| + | |||
| + | Time_GCM=nc1.variables['Time'][:] | ||
| + | lat_GCM=nc1.variables['latitude'][:] | ||
| + | lon_GCM=nc1.variables['longitude'][:] | ||
| + | alt_GCM=nc1.variables['altitude'][:] | ||
| + | aire_GCM=nc1.variables['aire'][:][:] | ||
| + | |||
| + | resolution_lon_GCM = abs(lon_GCM[1]-lon_GCM[0]) | ||
| + | resolution_lat_GCM = abs(lat_GCM[1]-lat_GCM[0]) | ||
| + | |||
| + | # 2D VARIABLES | ||
| + | tsurf1=nc1.variables['tsurf'][:][:][:] | ||
| + | OLR1=nc1.variables['OLR'][:][:][:] | ||
| + | h2o_ice_col1=nc1.variables['h2o_ice_col'][:][:][:] | ||
| + | |||
| + | # 3D VARIABLES | ||
| + | u1=nc1.variables['u'][:][:][:][:] | ||
| + | v1=nc1.variables['v'][:][:][:][:] | ||
| + | w1=nc1.variables['w'][:][:][:][:] | ||
| + | ice1=nc1.variables['h2o_ice'][:][:][:][:] | ||
| + | temp1=nc1.variables['temp'][:][:][:][:] | ||
| + | </syntaxhighlight> | ||
| + | |||
| + | |||
| + | |||
| + | <syntaxhighlight lang="python"> | ||
</syntaxhighlight> | </syntaxhighlight> | ||
| + | <syntaxhighlight lang="python"> | ||
| + | </syntaxhighlight> | ||
| + | <syntaxhighlight lang="python"> | ||
| + | </syntaxhighlight> | ||
| − | <syntaxhighlight lang="python" | + | <syntaxhighlight lang="python"> |
</syntaxhighlight> | </syntaxhighlight> | ||
Revision as of 09:19, 4 September 2022
We provide here a tutorial on how to make pretty visuals from GCM simulations. Do not hesitate to send us your best visuals so that we can enrich our GCM plot gallery.
import pyvista as pv
import numpy as np
from netCDF4 import Dataset
# import all the required libraries (netcdf4, pyvista)
#FIRST WE GET THE DATA FROM THE GCM SIMULATION
# 4D GRID VARIABLES
nc1 = Dataset('diagfi.nc')
Time_GCM=nc1.variables['Time'][:]
lat_GCM=nc1.variables['latitude'][:]
lon_GCM=nc1.variables['longitude'][:]
alt_GCM=nc1.variables['altitude'][:]
aire_GCM=nc1.variables['aire'][:][:]
resolution_lon_GCM = abs(lon_GCM[1]-lon_GCM[0])
resolution_lat_GCM = abs(lat_GCM[1]-lat_GCM[0])
# 2D VARIABLES
tsurf1=nc1.variables['tsurf'][:][:][:]
OLR1=nc1.variables['OLR'][:][:][:]
h2o_ice_col1=nc1.variables['h2o_ice_col'][:][:][:]
# 3D VARIABLES
u1=nc1.variables['u'][:][:][:][:]
v1=nc1.variables['v'][:][:][:][:]
w1=nc1.variables['w'][:][:][:][:]
ice1=nc1.variables['h2o_ice'][:][:][:][:]
temp1=nc1.variables['temp'][:][:][:][:]
