scipy spatial regridding

reg_sci.py

from scipy.interpolate import griddata
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr


file = "your_ncfile.nc"
dset = xr.open_dataset(file)


start_lat,end_lat = 10,15 # setting an start and end lon/lat points
start_lon,end_lon = 65,75 

""" Creating data arrays"""
n_dset = dset.sel(lat = slice(start_lat,end_lat),lon = slice(start_lon,end_lon)) #subsetting the netcdf using xarrray.sel
y = n_dset.lat.values  # latitude values (1D array) change variable name according to what in dataset
x = n_dset.lon.values # latitude values (1D array)
vals = n_dset.rh2.values[0,0,:,:] # ndarray(here Iam taking lat/lon so indexed to 2D array)


xm,ym = np.meshgrid(x,y) # Creating complete set of lon (x), lat (y) points
xf = xm.flatten() # creating 1 D array of all lon points
yf = ym.flatten() # creating 1D array of all lat points
valsf = vals.flatten() # corresponding 1 D array of values

""" Creating an new lat lon grid on 0.1 degree resolution"""

xx = np.arange(start_lon+1,end_lon,0.2) # Creating new lon list
yy =  np.arange(start_lat+1,end_lat,0.2) # creating new lat list


""" (x,y) are the initial (lon,lat) points  then the new lat and lon points are reshaped accoridng to the axis"""

n_vals = griddata((xf,yf),valsf,(xx[None,:],yy[:,None]),method="linear")

"""simply visualising using plt.contourf"""

plt.contourf(x,y,vals)
#plt.contourf(xx,yy,n_vals)