Releases: earth-chris/elapid
v1.0.1
v1.0.0
This tag marks release of the 1.0 software, commensurate with the expected publication of the JOSS manuscript 🎉
Some minor edits from the previous release:
- adds .partial_dependence_plot() and .permutation_importance() methods as a class mixin for elapid models
- fixed some bugs regarding how model scoring was evaluated
v0.3.20
- Updated the
nearest_point_distance()
function to support computing the average distance to all neighbors, and set this as the default fordistance_weights()
. The distance weight function is now a point density weighting function by default, but still configurable. - Fixed a bug in recent geopandas versions related to imperfectly matching CRS objects
v0.3.19
- Added new sample data with a full
geometetry
attribute. - Added methods to download sample data from an https server
- Fixed a bug in
ela.annotate()
wheredrop_na=True
wasn't properly handling strangely indexed geodataframes - Fixed another annotate bug to drop
nan
values in addition to dropping raster nodata - Updated web documentation to match contemporary python api settings
v0.3.18
- Added the
BufferedLeaveOneOut
cross-validation strategy - Fixed some feature transformer class attribute errors
- Refactored class attributes to become instance attributes, which fixed a bug where some model attributes were not being saved/restored by
ela.save_object()
andela.load_object()
- Set
glmnet
as an optional dependency, which can be installed withpip install elapid[glmnet]
instead of the previously baroque install method.
v0.3.17
Fixes a bug introduced in 0.3.16
where the nodata
argument to ela.geo.sample_raster()
only handled rasters with existing nodata values. It ignored this option for rasters without default nodata values. That's fixed here. Fool on me for pushing a release too quickly! (but this is critically needed for a downstream package).
v0.3.16
Minor update to add a new keyword for raster sampling, ela.geo.sample_raster(nodata={ndval})
, to specify custom nodata values to ignore in addition to the nodata value specified in the raster metadata.
v0.3.15
- added the
EnsembleModel()
class for merging multi-model predictions for general inference and performance evaluation and also to simplify applying an ensemble to raster data. - Improved class hygiene by refactoring mixins and declaring class-level variables for estimators and transformers.
- Added a progress bar to point annotation.
- Simplified and clarified docstrings.
v0.3.14
Added the train_test_split
module, which contains:
checkerboard_split()
for train/test splittingGeographicKFold()
for cross-validation train/test splitting
Updated docs, tests to match.
v0.3.13b
This is the first GH package release, designed for testing the pypi publish package action. I expect this version to be fairly close to what is to come in 1.0.0, as most new features and bugs on the roadmap have been worked out.