Tools for interpreting and generating new climate data

pip install ocrtools==1.0.0


OCR Tools

Open Climate Research is an ongoing project that aims to facilitate creative experimentation with modeled climate data. OCR Tools aims to be much more than a climate data viewer by enabling non-scientists to utilize a wide range of datasets and providing users with simple feedback conducive to learning. In addition to providing basic analysis functions, OCR Tools includes organizational and creative tools.

Installing / Getting started

Run the following to install:

pip install ocrtools


  • Open a NetCDF dataset with

  • import ocrtools as ocr
    cesm_TS = ocr.load('path/to/cesm_TS_data.nc', var='TS')

    If var is omitted, ocrtools will print out all variables in the dataset and ask you to specify a variable(s) of interest via command line. The dataset is then opened as an Xarray Dataset

  • Create a scope object

    lima_peru = ocr.scope(location='Lima, Peru', yr0=1950, yrf=2000)
    • Location can also be specified by keyword arguments lat_min, lat_max, lon_min, and lon_max; or if none of these are given, location can be specified interactively by selecting areas on a map
  • Subset your data

    lima_TS = ocr.subset(cesm_TS, lima_peru)
  • Select an area on a map and take the spatial average

    from ocrtools import plt
    map_selection = ocr.scope()
    [OCR] Creating new scope object
    Enter yr0: 
    Enter yrf: 
    Select area(s) on map and close the pop-up window
[OCR] Finished writing new scope object
peru_TS = ocr.subset(cesm_TS, map_selection)
peru_avg_TS = ocr.spatial_average(peru_TS)