This library is still under development. Do not expect full functionality, or documentation until release 1.0.0
Warning There will be breaking changes to how DomainMaps are exported starting in 0.5.4. As this is an alpha the concept of saving DomainMaps should never be considered stable.
Supported version of Python: Python 3.8+
The purpose of PyProm is to have a fully scriptable API for loading Raster Data for discovery of Summits, Saddles (cols), Prominence, Peak Parentage and all that good stuff. Anything you might want to be able to manipulate can be manipulated in a scalable, scriptable manner.
pyProm is written in Python, which is a fairly accessible language to most people. My master plan is once a stable, and well documented version can be produced, others can add features as they see fit. The disadvantage of writing such a deeply customizable library in python is it is inherently slower and consumes more memory (appalling so in some instances).
This library is inspired by WinProm, by the late Edward Earl, as well as the number of websites which make use of similiarly derived data, such as LoJ and peakbagger
Fancy pyProm Documentation derived from docstrings can be found on readthedocs.io (this is no longer maintained)
- http://www.surgent.net/highpoints/prominence.html
- http://www.peaklist.org/theory/theory.html
- https://en.m.wikipedia.org/wiki/Topographic_prominence
- SRTM Data #1
- [DEM type data] (http://viewer.nationalmap.gov/basic/#productGroupSearch) Start with Elevation Products (3DEP) - 1/3 arc-second DEM More info
pyProm is most easily installed using uv. You may have to install GDAL developer libraries and update the pyproject.toml file to match GDAL versions in case they are mismatched
- Go to the pyprom folder and execute
uv venv --python 3.14 - Follow venv activation instructions
- run
uv sync --activethis should install the required packages.
- Install pyProm
- Download This
- Extract the zip file
In your favorite Python interpreter on a Unix system (I use
ipythoninLinux):
from pyprom import GDALLoader, KMLFileWriter
from pyprom.domain_map import DomainMap
import logging
logging.basicConfig(level=logging.DEBUG)
# Load your Datamap into your Domain
loader = GDALLoader('YOURPATHHERE/N44W072.hgt')
datamap = loader.to_datamap()
domainmap = DomainMap(datamap)
domainmap.run()
# ^ This will run the Saddle/RunOff/Summit discovery as well as saddle walk and saddle disqualifiers, it'll take a while..
# Find all summits above 4000 feet
_4ks = domainmap.summits.elevationRange(4000)
# Write your fancy list of 4ks to a KML file
mykml = KMLfileWriter('YOURPATHHERE/myfile.kml', features=_4ks')
mykml.writeFile()
# Save your Domain
domainmap.write('YOURPATHHERE/mydomain.dom')
# Load your DomainMap you you don't need to wait forever for analysis.
newDomain = DomainMap.read('YOURPATHHERE/mydomain.dom', data.datamap)
Warning! Cbor data or saved Domains will almost certainly fail to load in future version. There WILL be breaking changes. You've been warned! (twice!)
Download zip from github, or clone.
Go to extraction directory and run pip install -e .
This will work with Python 3.4+
The GDAL (Geo Data Abstration Layer) package for Python must match the version of gdal installed on your system.
gdalinfo --version
You may have to manually install the proper version with pip3. ..or use conda..
Most common fix here: https://gis.stackexchange.com/questions/28966/python-gdal-package-missing-header-file-when-installing-via-pip
Unit tests can be run in two ways:
Your own local env:
make test
Inside a docker container:
make test-docker
Docker tests requires you to have docker installed on your system, and may require privilege escalation. The advantage of running tests in docker is for dependency consistency.
As of 0.5.7 you can run pyprom inside a Docker container!
make pyprom-docker
Will put you inside an ipython instance.