Metadata-Version: 1.0
Name: pygeotools
Version: 0.4.0
Summary: Libraries and command-line utilities for geospatial data processing/analysis
Home-page: https://github.com/dshean/pygeotools
Author: David Shean
Author-email: dshean@gmail.com
License: MIT
Description: # pygeotools
        Libraries and command line tools for geospatial data processing/analysis
        
        ## Features
        - Resample/warp rasters to common resolution/extent/projection
        - Many functions to handle rasters with NoData gaps using [NumPy masked arrays](https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html)
        - Point data coordinate transformations, sampling, and interpolation routines (e.g., arrays of xyz points)
        - Common raster filtering operations
        
        ### Libraries [pygeotools/lib](./pygeotools/lib) 
        - geolib - Coordinate transformations, raster to vector, vector to raster
        - malib - NumPy Masked Array operations, DEMStack class
        - warplib - On-the-fly GDAL warp operations for abitrary number of input datasets
        - iolib - File input/output, wrappers for GDAL I/O, masked array write to disk
        - timelib - Time conversions, extract timestamps from filenames, useful for raster time series analysis
        - filtlib - Collection of filters for 2D masked arrays (Gauss, rolling median, high pass, etc.)
        
        ### Command-line utilities (run with no arguments for usage)
        - warptool.py - Warp arbitrary rasters to common res/extent/proj
        - make_stack.py - Create a "stack" of input rasters (a raster time series object) and compute stats
        - clip_raster_by_shp.py - Clip and mask an input raster using a polygon shapefile
        - apply_mask.py - Apply mask from one raster to another
        - filter.py - Apply various filters available in filtlib
        - trim_ndv.py - Remove rows/cols containing only NoData from raster margins
        - replace_ndv.py - Replace NoData value
        - proj_select.py - Automatically determine projection for input lat/lon or raster
        - raster2shp.py - Create polygon shapefile of input raster footprints
        - ogr_merge.sh - Merge shapefiles
        - ...
        
        ## Examples 
        
        ### Warping multiple datasets to common grid, computing difference, writing out
        ```
        from pygeotools.lib import iolib, warplib, malib
        fn1 = 'raster1.tif'
        fn2 = 'raster2.tif'
        ds_list = warplib.memwarp_multi_fn([fn1, fn2], res='max', extent='intersection', t_srs='first', r='cubic')
        r1 = iolib.ds_getma(ds_list[0])
        r2 = iolib.ds_getma(ds_list[1])
        rdiff = r1 - r2
        malib.print_stats(rdiff)
        out_fn = 'raster_diff.tif'
        iolib.writeGTiff(rdiff, out_fn, ds_list[0])
        ```
        or, from the command line... 
        
        Warp all to match raster1.tif projection with common intersection and largest pixel size:
        
        `warptool.py -tr max -te intersection -t_srs first raster1.tif raster2.tif raster3.tif`
        
        Create version of raster1.tif that matches resolution, extent, and projection of raster2.tif:
        
        `warptool.py -tr raster2.tif -te raster2.tif -t_srs raster2.tif raster1.tif`
        
        Reproject and clip to user-defined extent, preserving original resolution of each input raster:
        
        `warptool.py -tr source -te '439090 5285360 458630 5306450' -t_srs EPSG:32610 raster1.tif raster2.tif`
        
        ### Creating a time series "stack" object:
        ```
        from pygeotools.lib import malib
        fn_list = ['20080101_dem.tif', '20090101_dem.tif', '20100101_dem.tif']
        s = malib.DEMStack(fn_list, res='min', extent='union')
        #Stack standard deviation
        s.stack_std
        #Stack linear trend
        s.stack_trend
        ```
        or, from the command line...
        
        `make_stack.py -tr 'min' -te 'union' 20*.tif`
        
        ## Documentation
        
        http://pygeotools.readthedocs.io
        
        ## Installation
        
        Install the latest release from PyPI:
        
            pip install pygeotools 
        
        **Note**: by default, this will deploy executable scripts in /usr/local/bin
        
        ### Building from source
        
        Clone the repository and install:
        
            git clone https://github.com/dshean/pygeotools.git
            pip install -e pygeotools
        
        The -e flag ("editable mode", setuptools "develop mode") will allow you to modify source code and immediately see changes.
        
        ### Core requirements 
        - [GDAL/OGR](http://www.gdal.org/)
        - [NumPy](http://www.numpy.org/)
        - [SciPy](https://www.scipy.org/)
        
        ### Optional requirements (needed for some functionality) 
        - [matplotlib](http://matplotlib.org/)
        - [NASA Ames Stereo Pipeline (ASP)](https://ti.arc.nasa.gov/tech/asr/intelligent-robotics/ngt/stereo/)
        
        ## Disclaimer 
        
        This originated as a personal repo that I am slowly cleaning up and distributing.  There are some useful things that work very well, other things that were hastily written for a one-off task several years ago, and some confusing things that were never finished. 
        
        Contributions, bug reports, and general feedback are all welcome.  My time is limited, I have some bad habits, and I could really use some help.  Thanks in advance.
        
        This was all originally developed for Python 2.X, but should now also work with Python 3.X thanks to [@dlilien](https://github.com/dlilien)
        
        Some of this functionality now exists in the excellent, mature, well-supported [rasterio](https://github.com/mapbox/rasterio).  Eventually, I will integrate rasterio API calls where appropriate.
        
        ## License
        
        This project is licensed under the terms of the MIT License.
        
        
Platform: UNKNOWN
