Get values in specific cells from xarray

[jc-barreto]

I was wondering if is possible to get the pixel values from xarray plot that match a specific line. I need the air values from the NetCDF volume along the blue line.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import xarray as xr
import rioxarray as rxr
from scipy.optimize import curve_fit



data = xr.tutorial.load_dataset("air_temperature")

n_cells = data['air']['time'].values.shape[0]
print(n_cells)
n_seccao = np.linspace(0,n_cells-1,6,endpoint=True,dtype=int)
print(n_seccao)
n_rows = int(np.ceil((len(n_seccao)/2)))
print(n_rows)

def match_function(x,A,B):
    return A*x

x_min = data['air']['lon'].values.min()
x_max = data['air']['lon'].values.max()

x_fit = np.linspace(x_min,x_max,50)
y= match_function(x_fit,0.2,20)

fig, axs = plt.subplots(nrows=n_rows, ncols=2,figsize=(12,15))

for i, ax in enumerate(fig.axes):

    lat = data['air']['lat'][i].values
    sec = data.air.isel(time=n_seccao[i])
    p2, = ax.plot(x_fit,y,'o',color='blue',label='Function')
    sec.plot(ax=ax, cbar_kwargs={"label": "Air",'location': 'top' })

    ax.set_title('X= {:.2f} e cel= {:.0f}'.format(lat,n_seccao[i]))
    ax.set_xlabel('Y[m]')
    ax.set_ylabel('Z[m]')
    fig.tight_layout()
    fig.subplots_adjust(wspace=0.7)

[rabernat]

It sounds like you're looking for advanced interpolation.

[jc-barreto]

Exactly! Thank you!