James Douglass phargogh

To use this:

	import numpy
	import pygeoprocessing
	from osgeo import gdal


	def convert_taudem_flow_dir_to_pygeoprocessing(
	taudem_flow_dir_raster_path, target_flow_dir_raster_path):
	source_nodata = pygeoprocessing.get_raster_info(
	taudem_flow_dir_raster_path)['nodata'][0]
	dest_nodata = 128 # Matches pygeoprocessing-produced flow dir nodata.

	import logging
	import os

	import pygeoprocessing
	import pygeoprocessing.routing
	from osgeo import gdal

	logging.basicConfig(level=logging.INFO)
	LOGGER = logging.getLogger(__name__)

	import matplotlib.pyplot as plt
	import numpy

	BUFFER_DIST = 500
	DISTANCE = numpy.arange(BUFFER_DIST+100)
	NONE = (DISTANCE < BUFFER_DIST)
	LINEAR = numpy.maximum(1 - (DISTANCE / BUFFER_DIST), 0)
	EXPONENTIAL = numpy.exp(-DISTANCE / BUFFER_DIST) * NONE
	OLD_HRA_EXPONENTIAL = (1 - numpy.exp((numpy.log(1e-6) / DISTANCE))) * NONE

	import logging
	import os
	import pprint

	import numpy
	import pygeoprocessing
	import pygeoprocessing.routing
	from natcap.invest import datastack
	from natcap.invest.seasonal_water_yield import seasonal_water_yield
	from osgeo import gdal

	import os
	import shutil

	import numpy
	import pygeoprocessing
	import pygeoprocessing.routing
	from osgeo import gdal


	def doit(dem_path, flow_dir_weights, watershed_source_vector, workspace):

	import logging
	import os
	import os.path

	import numpy
	import pygeoprocessing
	from osgeo import gdal
	from osgeo import osr

	logging.basicConfig(level=logging.WARNING)

	This gist reflects what I understand to be the workflow for Dyna-CLUE,
	in the interest of getting the core algorithm down on paper.

	This is based on :
	* Verburg & Overmars (2009): https://link.springer.com/article/10.1007%2Fs10980-009-9355-7
	* The CLUE Manual: http://environmentalgeography.nl/files/data/public/cluemanual
	* The provided source code for CLUE: http://www.environmentalgeography.nl/files/data/public/dyna_clue
	* The IEEM Dyna-CLUE manual: https://publications.iadb.org/publications/english/document/The-Integrated-Economic-Environmental-Modeling-IEEM-Platform-IEEM-Platform-Technical-Guides-User-Guide-for-the-IEEM-enhanced-Land-Use-Land-Cover-Change-Model-Dyna-CLUE.pdf

	#!/bin/bash
	curl https://pypi.org/pypi/numpy/json \| jq '..\|.filename?' \| grep \.whl \| grep 310

	.PHONY: all clean

	WITHREADLINE := withreadline.txt
	WITHOUTREADLINE := withoutreadline.txt
	WITHOUTREADLINEBYLINE := withoutreadlinebyline.txt
	SAMPLE := sample.txt

	all: $(WITHREADLINE) $(WITHOUTREADLINE) $(WITHOUTREADLINEBYLINE)

	clean: