vvmtools.analyze.create_nc_output

vvmtools.analyze.create_nc_output(filename, dim_data_dict, data_dict, var_dims_dict, attributes=None)

Creates a NetCDF file with multiple 1D and 2D data arrays and user-defined attributes using xarray.

Parameters:

• filename (str) – The name of the output NetCDF file.

• dim_data_dict (dict) – Dictionary of dimension data, where each key is a dimension name and the value is the data for that dimension.

• data_dict (dict) – Dictionary of data arrays, with each key representing a variable name and the value being the data array.

• var_dims_dict (dict) – Dictionary specifying the dimensions for each variable. Each key is a variable name, and each value is a tuple of dimension names, e.g., (“dim1”,) or (“dim1”, “dim2”).

• attributes (dict, optional) – Optional. A dictionary of attributes for each variable, where each key is a variable name and the value is a dictionary containing metadata such as units and description.

Examples

save data to NetCDF file using create_nc_output.

import numpy as np
import vvmtools
nz, nt = 50, 721
dim_data_dict = {
    "time": (np.arange(nt)*np.timedelta64(2,'m')+np.datetime64('2024-01-01 05:00:00')).astype('datetime64[s]'),
    "height": np.arange(nz)*0.04
}
data_dict = {
    "th": np.random.rand(nt, nz),
    "enstrophy": np.random.rand(nt, nz),
    "tke": np.random.rand(nt, nz)
}
var_dims_dict = {
    "th": ("time", "height"),
    "enstrophy": ("time", "height"),
    "tke": ("time", "height")
}
attributes = {
    "th": {"units": "K", "description": "x-y mean potential temperature (t,z)"},
    "enstrophy": {"units": "1/(s^2)", "description": "x-y mean enstrophy (t,z)"},
    "tke": {"units": "(m^2)/(s^2)", "description": "x-y mean turbulent kinetic energy (t,z)"},
    "time": {"description": "Local Time"},  # Removed 'units' for time
    "height": {"units": "m", "description": "Height in grid center"},
}

# Example of creating a NetCDF file with flexible dimensions
vvmtools.analyze.create_nc_output("sample_xarray.nc", dim_data_dict, data_dict, var_dims_dict, attributes)

Read NetCDF file from xarray

import xarray as xr

# Extract dimension
ds = xr.open_dataset("sample_xarray.nc")
z = ds.coords["height"].values
t = ds.coords["time"].values

# Extract data
tke = ds["tke"]