correlate_2D

Correlate time series on regular meshes

Python and Dependencies

The code needs the python packages netcdf4 and progressbar

If you know what you are doing, just make sure the aforementioned dependencies are installed. Otherwise do yourself a favor and download the Anaconda (https://store.continuum.io/cshop/anaconda/) Python distribution. It is a free scientific Python distribution bundling almost all necessary modules with a convenient installer (does not require root access!). Once installed assert that pip and conda point to the Anaconda installation folder (you may need to open a new terminal after installing Anaconda).

$ conda install -c netcdf4 progressbar pip

Usage

$ python correlate_2d.py -h

usage: correlate_2d.py [-h] [-o OUTPUT_FILE_NAME] [-v VARIABLE]
                       [-m MAX_LENGTH] [-d DEPTH_LAYER] [-k]
                       input_file_name

Calculate spatial correlation length in a 2D time series

positional arguments:
  input_file_name       NetCDF input file name. Should follow BLABLA convention

optional arguments:
  -h, --help            show this help message and exit
  -o OUTPUT_FILE_NAME, --output_file_name OUTPUT_FILE_NAME
                        Output file name. Default is input_file_name_corr.nc
  -v VARIABLE, --variable VARIABLE
                        Variable to calculate correlation on
  -m MAX_LENGTH, --max_length MAX_LENGTH
                        Maximum correlation length. 
                        Only elements with a distance smaller max_length are 
                        correlated. Smaller max_length speed up the calculation
  -d DEPTH_LAYER, --depth_layer DEPTH_LAYER
                        Depth layer to correlate. 
  -k, --keep_original   Keep original variable in output file?