Tools for interpreting and generating new climate data
Project description
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
objectlima_peru = ocr.scope(location='Lima, Peru', yr0=1950, yrf=2000)
- Location can also be specified by keyword arguments
lat_min
,lat_max
,lon_min
, andlon_max
; or if none of these are given, location can be specified interactively by selecting areas on a map
- Location can also be specified by keyword arguments
-
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()
Project details
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