v0.0.5 (#21)

.gitignore

@@ -86,4 +86,7 @@ __pycache__/
 *.coverage
 
 # old notebooks
-notebooks/deprecated/
+notebooks/deprecated/
+
+# data output from nbs
+notebooks/out/

CHANGELOG.md

@@ -6,6 +6,20 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [PEP 440](https://www.python.org/dev/peps/pep-0440/)
 and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.0.5] - 2025-01-18
+
+### Added
+* Added `rio_tools` for merging float arrays (including burst data such as the computed metric)
+    * can be used to average over overlapping areas
+    * average using the distance from exterior mask (mask that touches one of the four edges)
+    * exterior mask can also be dilated to avoid problematic boundary pixels
+    * categorical merging of data
+* Added `nd_tools` for getting exterior mask and distance from such mask (wrappers around `scipy.ndimage`)
+* A notebook for applying the transformer metric to a large area of interest
+
+### Removed
+* Removed torch.compile from transformer model loading
+
 ## [0.0.4] - 2025-01-18
 
 ### Fixed

README.md

@@ -41,6 +41,14 @@ mamba install -c conda-forge distmetrics
 
 You can also use `pip`, although this doesn't ensure proper dependencies are installed.
 
+### GPU support
+
+To get the best performance of pytorch, you need to ensure pytorch recognizes the GPU.
+Using `conda-forge` distributions, you may require you to ensure that `cudatoolkit` is installed (this is the additional library in `environment_gpu.yml`).
+For our servers, we needed to install `cudatoolkit>=11.8` to get pytorch to recognize the GPU.
+There are certain libraries that may downgrade `pytorch` to use CPU only (you can check this by looking at the distribution of pytorch before installing the library).
+There may be different distributions of pytorch and cuda drivers that are compatible, but providing detailed instructions is beyond the scope of these instructions.
+
 
 ### For development
 
@@ -61,7 +69,7 @@ get_device() # should be `cuda` if GPU is available or `mps` if using mac M chip
 
 # References
 
-<a id=1>[1]</a> H. Hardiman Mostow et al., "Deep Self-Supervised Disturbance Mapping with Sentinel-1 OPERA RTC Synthetic Aperture Radar", [arXiv](https://arxiv.org/abs/2409.15568).
+<a id=1>[1]</a> H. Hardiman Mostow et al., "Deep Self-Supervised Disturbance Mapping with Sentinel-1 OPERA RTC Synthetic Aperture Radar", [https://arxiv.org/abs/2501.09129](https://arxiv.org/abs/2501.09129).
 
 <a id=2>[2]</a> O. L. Stephenson et al., "Deep Learning-Based Damage Mapping With InSAR Coherence Time Series," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022, Art no. 5207917, doi: 10.1109/TGRS.2021.3084209. https://arxiv.org/abs/2105.11544 
 
@@ -71,4 +79,4 @@ get_device() # should be `cuda` if GPU is available or `mps` if using mac M chip
 
 <a id=5>[5]</a> Sarem Seitz, "Probabalistic Cusum for Change Point Detection", https://web.archive.org/web/20240817203837/https://sarem-seitz.com/posts/probabilistic-cusum-for-change-point-detection/, Accessed September 2024.
 
-<a id=6>[6]</a> Tartakovsky, Alexander, Igor Nikiforov, and Michele Basseville. Sequential analysis: Hypothesis testing and changepoint detection. CRC press, 2014.
+<a id=6>[6]</a> Tartakovsky, Alexander, Igor Nikiforov, and Michele Basseville. Sequential analysis: Hypothesis testing and changepoint detection. CRC press, 2014.

environment.yml

@@ -4,6 +4,7 @@ dependencies:
  - asf_search
  - astropy
  - backoff
+ - dem_stitcher
  - dill
  - einops
  - flake8

environment_gpu.yml

@@ -0,0 +1,36 @@
+name: distmetrics
+dependencies:
+ - python>=3.10
+ - asf_search
+ - astropy
+ - backoff
+ - dem_stitcher
+ - dill
+ - einops
+ - flake8
+ - flake8-blind-except
+ - flake8-builtins
+ - flake8-import-order
+ - gdal
+ - geopandas
+ - jupyterlab
+ - matplotlib
+ - mpire
+ - multiprocess
+ - numpy
+ - pandas
+ - pydantic
+ - pytest
+ - pytest-cov
+ - pytorch
+ - rasterio
+ - requests
+ - ruff
+ - scikit-image
+ - scipy
+ - setuptools
+ - setuptools_scm
+ - shapely
+ - tqdm
+ - pip
+ - cudatoolkit>=11.8