import xarray as xr
import numpy as np
import matplotlib.pyplot as plt

# Load the netCDF file
ds = xr.open_dataset('../NC/FD_Char_1961-2020_1yrs_Daily_Reg_New.nc')

# Extract the frq variable and longitude and time coordinates
frq = ds['frq']
lon = ds['lon']
lat = ds['lat']
time = ds['month']

# Define the longitude range to average over
lon1 = 101.125
lon2 = 110.875

# Calculate the longitude indices to average over
lon_indices = np.where((lon >= lon1) & (lon <= lon2))[0]

# Average over the longitude range
frq_mean = frq.isel(longitude=lon_indices).mean(dim='longitude')

# Create a time-latitude cross section plot of the averaged data
fig, ax = plt.subplots()
im = ax.pcolormesh(lat, time, frq_mean.T, cmap='viridis')
ax.set_xlabel('Latitude')
ax.set_ylabel('Time')
ax.set_ylim([time[0], time[-1]])
cbar = fig.colorbar(im, ax=ax)
cbar.set_label('frq')

# Show the plot
plt.show()