phargogh

Compilation issue with clang 14 on ARM64

To reproduce:

• Use an ARM64 computer (tested on M1 mac and on Raspberry Pi model 4B)

  • On Raspberry pi, I used Raspbian:bookworm
  • On M1 mac, I used docker run --rm -ti -v $(pwd):/demo -w /demo debian:bookworm /bin/bash (which shares the local directory into the container, assumes you are running this from the cloned gist)

• On your computer of choice, run apt update && apt install -y build-essential clang-13 clang

• Observe gcc produces correct results: gcc ./min-repro-sample.c && ./a.out

phargogh

Is it faster to return None as a mask?

While reading through the InVEST utils source code, I noticed that our nodata masking function returns a boolean array of zeros rather than just False, and it made me wonder if the memory allocation for this array was slower than simply returning False and letting the numpy array broadcasting handle the distribution of that single value across all of the comparison array values.

In my tests here (see test-nodata-timings.py), the runtime is dominated by random array generation rather than indexing, but there does appear to be a

phargogh

# # Install Zsh on Sherlock
# Installs Zsh with Oh-My-Zsh without root privileges 
# on Stanford's Sherlock (https://sherlock.stanford.edu) for use in tmux
#
# ## Instructions
# 1) bash install_zsh.sh
# 2) edit .zshrc (add the path to your Zsh binary to the PATH variable, etc.)
# 3) add `set-option -g default-shell <path to zsh>/bin/zsh` to `~/.tmux.conf`
# 4) also see comments for potential further notes
#

phargogh

#!/bin/bash

# This script runs within iterm2 to print images to the commandline and
# ask whether there's text that should be translated.
#
# Developed to run within the context of the InVEST user's guide,
# executing this from within the source/ directory.

NO_TRANSLATE_FILE=images_that_should_not_be_translated.txt
YES_TRANSLATE_FILE=images_that_SHOULD_be_translated.txt

phargogh

import numpy
from osgeo import gdal
from osgeo import osr

# Taken from Examples section of https://wiki.gcube-system.org/gcube/ISO_19115:2003/19139
METADATA = """\
<fileIdentifier>
	<gco:CharacterString>33462e78-e5ab-11c3-737d-b3a61366d028</gco:CharacterString>
</fileIdentifier>
<language>

phargogh

Can HRA Reclassification Percentages be Derived from pygeoprocessing.zonal_statistics outputs?

Background

Among its outputs, HRA produces a raster where the calculated floating-point risk score is reclassified into the following classifications:

1. 0 representing no risk
2. 1 representing low risk
3. 2 representing medium risk

phargogh

import math
import sys

import numpy
from osgeo import gdal


def make_ones_kernel(radius_in_pixels):
    side_length = radius_in_pixels * 2
    if side_length % 2 == 0:

phargogh

import numpy
import pygeoprocessing
from osgeo import gdal

FLOAT32_NODATA = float(numpy.finfo(numpy.float32).min)


def _convert_to_from_density(source_raster_path, target_raster_path,
                             direction='to_density'):
    """Convert a raster to/from counts/pixel and counts/unit area.

phargogh

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.

phargogh

import logging
import os

import pygeoprocessing
import pygeoprocessing.routing
from osgeo import gdal

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