33 lines
749 B
Python
33 lines
749 B
Python
import numpy as np
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from netCDF4 import Dataset
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# Load the NetCDF file
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file_path = 'data/MERRA2_400.inst6_3d_ana_Np.20120101.nc4'
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ncfile = Dataset(file_path, 'r')
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# Check the available variables in the file
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print(ncfile.variables.keys())
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U = ncfile.variables['T'][:]
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# Check the shape of the variable (it should be 3D)
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print("Shape of U:", U.shape)
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# Compute the mean of the variable across all axes (for all elements in U)
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U_mean = np.mean(U)
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U_sum = np.sum(U)
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# Print the mean
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print("Mean of U:", U_mean)
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print("Sum of U:", U_sum)
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masked_count = np.ma.count_masked(U)
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print("Number of masked values in U:", masked_count)
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nan_count = np.isnan(U).sum()
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print("Number of NaN values in U:", nan_count)
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# Close the NetCDF file
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ncfile.close()
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