Connor Manning connormanning

Scripting writers.greyhound

These instructions assume that node.js is installed installed natively. PDAL/Entwine/Greyhound pieces are done via Docker.

Index Autzen with Entwine

Assuming ~/entwine is the storage location for Entwine-indexed data:

docker run -it -v ~/entwine:/opt/data connormanning/entwine build \
 -i http://entwine.io/sample-data/autzen.laz \

Houston LiDAR

Links to source data files for Houston LiDAR data - viewable with Potree and Plasio.

See https://twitter.com/howardbutler/status/9029370196592353

First, save the run.cpp file somewhere.

$ docker run -it \
  -v <your-entwine-data-directory>:/opt/data/ \
  -v <wherever-you-put-that-c++-file>:/opt/test/ \
  --entrypoint=bash connormanning/entwine

root@ff99e5b49bf0:/# cd /opt/test/
root@ff99e5b49bf0:/opt/test# g++ -std=c++11 -I /usr/include/jsoncpp/ run.cpp -lentwine -ljsoncpp -o dump

Create config directory and create a config file

sudo mkdir /etc/systemd/system/docker.service.d/
sudo nano /etc/systemd/system/docker.service.d/custom.conf

Contents of that file should be:

[Service]
ExecStart=

	var Promise = require('bluebird');
	var request = require('request-promise');
	var argv = require('minimist')(process.argv.slice(2));

	if (!argv.r \|\| argv.h) {
	console.log('\nGREYHOUND DENSITY SAMPLER');
	console.log('--------');
	console.log(
	'This script queries randomly selected areas of a resource to\n' +
	'estimate the density of a dataset. Only queries containing\n' +

	import numpy as np

	def normalize(i, o):
	o['Red'] = i['Red'] >> 8;
	o['Green'] = i['Green'] >> 8;
	o['Blue'] = i['Blue'] >> 8;
	return True

	$ time docker run -it --rm connormanning/entwine infer https://storage.googleapis.com/stratmap10_50cm_bexar/stratmap10-50cm_2998104c.laz -v
	Curl config:
	timeout: 5s
	followRedirect: true
	verifyPeer: true
	caBundle: (default)
	caInfo: (default)
	Inferring from: https://storage.googleapis.com/stratmap10_50cm_bexar/stratmap10-50cm_2998104c.laz
	Temp path: tmp
	Threads: 4

	var PointCloudBounds = function(serverInfo) {
	var bounds = serverInfo.bounds;
	var preScale = serverInfo.scale \|\| [1, 1, 1];
	var preOffset = serverInfo.offset \|\| [0, 0, 0];

	console.log('From:', serverInfo);

	if (!preScale.length) preScale = [preScale, preScale, preScale];

	bounds = bounds.map((v, i) => v * preScale[i % 3] + preOffset[i % 3]);