Metadata-Version: 2.1
Name: ocrtools
Version: 0.1.2
Summary: Tools for interpreting and generating new climate data
Home-page: https://github.com/andreschang/ocr-tools
Author: Andres Chang
Author-email: andresdanielchang@gmail.com
License: MIT
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:
        ```python
        pip install ocrtools
        ```
        
        ## Examples
        
        - Open a NetCDF dataset with 
        
        - ``` python
          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
        
          ``` python
          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
        
          ```python
          lima_TS = ocr.subset(cesm_TS, lima_peru)
          ```
        
        - Select an area on a map and take the spatial average
        
          ```python
          from ocrtools import plt
          map_selection = ocr.scope()
          ```
        
          ```shell
          [OCR] Creating new scope object
          Enter yr0: 
          Enter yrf: 
          Select area(s) on map and close the pop-up window
          ```
          
          <img src="http://andreschang.com/unlinked/tk_selector_screenshot.png" width=70%/>
        
        ```shell
        [OCR] Finished writing new scope object
        ```
        
        ```python
        peru_TS = ocr.subset(cesm_TS, map_selection)
        peru_avg_TS = ocr.spatial_average(peru_TS)
        peru_avg_TS['TS'].plot()
        plt.show()
        ```
        
        
Platform: UNKNOWN
Requires-Python: >=3.0
Description-Content-Type: text/markdown
