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Quick Reference

Released:

Tools for interpreting and generating new climate data

Project description

# OCR ToolsOpen 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:`pythonpip install ocrtools`

## Examples

• Open a NetCDF dataset with

• ` pythonimport ocrtools as ocrcesm_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

  ` pythonlima_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

  `pythonlima_TS = ocr.subset(cesm_TS, lima_peru)`

• Select an area on a map and take the spatial average

  `pythonfrom ocrtools import pltmap_selection = ocr.scope()`

  `shell[OCR] Creating new scope objectEnter yr0:Enter yrf:Select area(s) on map and close the pop-up window`

`shell[OCR] Finished writing new scope object`

`pythonperu_TS = ocr.subset(cesm_TS, map_selection)peru_avg_TS = ocr.spatial_average(peru_TS)peru_avg_TS['TS'].plot()plt.show()`

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