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Geobricks library to correlate two raster and create statistics and scatter charts.

Project description

Geobricks Raster Correlation

The library provides an easy way correlate raster of the same size. It returns a json containing statistical outputs and frequencies information to be directly used with Highcharts JS library.

# Installation

## Dependencies

The library has different dependencies (see also requirements.txt) click, watchdog, flask, flask-cors, numpy, scipy, pysal, brewer2mpl, rasterio, GeobricksCommon.

## On Ubuntu

sudo add-apt-repository ppa:ubuntugis/ppa
sudo apt-get update
sudo apt-get install python-numpy libgdal1h gdal-bin libgdal-dev

In case of compiling errors for numpy
sudo apt-get install libblas3gf libc6 libgcc1 libgfortran3 liblapack3gf libstdc++6 build-essential gfortran python-all-dev libatlas-base-dev python-dev

In case of compiling errors for scipy
sudo apt-get install libblas-dev liblapack-dev

## Installation

The library is distributed through PyPi and can be installed by typing the following command in the console:
pip install GeobricksRasterCorrelation

**N.B.** Due to a well known PyPi issue it's not possible to install scipy and pysal through or requirements.txt

In order to install pysal run the following command
pip install pysal

# Examples

## Library usage

from geobricks_raster_correlation.core.raster_correlation_core import get_correlation

raster_path1 = "path_to_raster1.tif"
raster_path2 = "path_to_raster2.tif"
# Number of bins to be applied to the scatter chart
bins = 300
corr = get_correlation(raster_path1, raster_path2, bins)
print corr

The returned json:

* corr['stats'] contains the statistics: slope, p_value, std_err, intercept, r_value
* corr['series'] contains the output series that can be used directly as an Highcharts input.

Project details

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