gcpy.examples.working_with_files.concatenate_files

This Python script concatenates several individual netCDF files into a single netCDF file using xarray.

Examples

1. Copy this file to a different folder and navigate to that folder.

2. In your copy, edit the file names for your use case.

3. Run the following commands:

$ conda activate gcpy_env
(gcpy_env) $ ./concatentate_files.py

Notes

If you have several individual files with one variable per file, you should consider concatenating them into a single file. This is often more efficient, as opening each netCDF file incurs computational overhead. It is usually faster to read data from a file with multiple variables than to having to open several files with one variable each.

Functions

find_files_in_dir(path, substrs)	Returns a list of all files in a directory that match one or more substrings.
main()	Main program.
replace_nans_with_zeroes(dset[, verbose])	Replaces NaN values with zeroes for each variable within an an xarray Dataset.

gcpy.examples.working_with_files.concatenate_files.find_files_in_dir(path, substrs)

Returns a list of all files in a directory that match one or more substrings.

Parameters:

• path (str) – Path to the directory in which to search for files.

• substrs (list of str) – List of substrings used in the search for files.

Returns:

file_list – List of files in the directory (specified by path) that match all substrings (specified in substrs).

Return type:

list of str

gcpy.examples.working_with_files.concatenate_files.replace_nans_with_zeroes(dset, verbose=True)

Replaces NaN values with zeroes for each variable within an an xarray Dataset.

Parameters:

• dset (xarray Dataset) – The input dataset, containing one or more data variables.

• verbose (bool, optional) – Set this switch to print out the variable name, as well as the min and max of the variable. This will illustrate the replacement of NaNs with zeroes.

gcpy.examples.working_with_files.concatenate_files.main()

Main program.