All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to PEP 440 and uses Semantic Versioning.
- Removed ability to pass [0, 0, 0, 0] as bounds
- Added
mypy
tostatic-analysis
- The
static-analysis
Github Actions workflow now usesruff
rather thanflake8
for linting.
- A new
--use-gslc-prefix
option has been added to theback_projection
andtime_series
workflows:- This option causes
back_projection
to upload the GSLC outputs to aGSLC_granules/
subprefix located within the S3 bucket and prefix given by the--bucket
and--bucket-prefix
options. - This option causes
time_series
to download the GSLC inputs from theGSLC_granules/
subprefix located within the bucket and prefix given by the--bucket
and--bucket-prefix
options.
- This option causes
- Releases and test deployments now trigger a Docker build for the GPU container, rather than the CPU container.
- Fixed the parsing for the
--bounds
option fortime_series
.
- New
time_series
workflow for time series processing of GSLC stacks.
- The
back_projection
workflow now accepts an optional--bounds
parameter to specify the DEM extent - The back-projection product now includes the elevation.dem.rsc file.
- Renamed project to HyP3 SRG to reflect that it's a HyP3 plugin for the Stanford Radar Group (SRG) SAR Processor.
- Orbit files are now retrieved using
fetch_for_scene
froms1_orbits
. - ESA Credentials are no longer needed.
back_project
granules parameter so that it can accept a string of space-delimited granule names.
- Main Dockerfile so that workflow matches changes introduced by fixing GPU workflow.
- Main Dockerfile to use a multi-stage build, mirroring Dockerfile.gpu.
scripts/ubuntu_setup.sh
for setting up a GPU-based Ubuntu EC2 AMI.scripts/amazon_linux_setup.sh
for setting up a GPU-based Amazon Linux 2023 EC2 AMI.
- Refactored
scripts/build_proc.sh
to combine GPU compilation steps. - Final product zip archive is now always created.
Dockerfile.gpu
so that outputs will contain actual data.
- Support for GPU accelerated processing using CUDA.
- Compilation of the
back-processing
code to the Dockerfile. - CPU-based workflow for back-projecting level-0 Sentinel-1 data
- Compilation script now uses libfftw3f library installed using
apt
instead of locally compiled version.
- Created a fresh version of the repository using hyp3-cookiecutter.
- All the files associated with the pre-2021 work, except the .git folder.
- All pre-2021 work on the repository.
- Initial version of repository.