James Douglass phargogh

The three files here are for developing the InVEST download link auto-updating functionality.

The file invest-current_version.json is there in case it's easier to only update the download links.

The file invest-all-links.json is there in case it's easier to update all of the hyperlinks in one go.

The file invest-all-links-nid.json is the same as invest-all-links.json, just with the drupal Node ID included for easier reference.

	Conclusions:

	* On the Colombia DEM (15030 x 20631 pixels) and the Gura DEM (1939 x 603 pixels) the
	delineateit implementation reliably runs in 1/3 the time of the proposed
	`_ManagedRaster`-based pour points implementation.

	# Related to the discussion at https://community.naturalcapitalproject.org/t/coastal-blue-carbon-zero-net-c-sequestration-in-disturbed-blue-carbon-habitats/1398/9
	# Note that this is intended to simply recreate the math used in the CBC model,
	# which is just a Riemann Sum of the emissions equation. It would be far
	# faster (and should be more numerically correct) to simply use the fundamental
	# theorem of calculus and evaluate the function directly for each transition period.

	# d = 0.0001997
	d = 0.00020075

	# found_emissions = 0.0000133733

	import time
	import math
	import collections

	PRIMES = set((2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199))

	def standard_factored_form(n):
	print(f"Factoring {n}")
	remainder = n
	factors = collections.defaultdict(int)

	# Usage: python model_stats.py <path to model stats GeoJSON
	import sys
	import collections

	from osgeo import ogr

	ALIASES = {
	'natcap.invest.blue_carbon.blue_carbon_preprocessor': 'CBC-preprocessor',
	'natcap.invest.coastal_blue_carbon.preprocessor': 'CBC-preprocessor',
	'natcap.invest.coastal_blue_carbon.coastal_blue_carbon': 'CBC',

	#!/bin/sh
	# jq -r prints the 'raw' value.
	curl https://api.github.com/repos/natcap/invest.users-guide/commits/master \| jq -r .sha

	# encoding=UTF-8
	"""time-mfd-aspect.py

	Time MFD mean aspect ratio generation routine over 100 runs.

	Requires:
	- pygeoprocessing==1.9.2
	- git+https://github.com/phargogh/invest.git@8ac2575#egg=natcap.invest
	"""

	import sys

	def doit():
	packed_flow_dir = int(sys.argv[1])

	weights = [(packed_flow_dir >> 4*i) & 0xF for i in range(8)]
	weights = [str(w).rjust(2, ' ') for w in weights]

	print(weights)

	REPO_DIR=$(pwd)/repos
	OUT_DIR=$(pwd)/bundles
	mkdir -p $OUT_DIR $REPO_DIR

	for sshrepo in `cat repos.txt`
	do
	REPONAME=$(echo $sshrepo \| cut -d '/' -f 5-)
	TARGETDIR=$REPO_DIR/$REPONAME
	hg clone $sshrepo --noupdate $TARGETDIR
	pushd $OUT_DIR