ocrtools 0.1.1

Tools for interpreting and generating new climate data

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

Examples

• 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)
peru_avg_TS['TS'].plot()
plt.show()