1.1.1

installation

• Set minimum python version to 3.10, include py312 in test suite, replace deprecated pkg_resources with importlib.metadata [#73]
• Set minimum tensorflow version to 2.16.1 [#73]
• Pre-trained neural networks updated for compatibility with Keras 3 [#73]
• Dockerfile images now use debian bookworm [#73]

1.1.1rc1

installation

• Set minimum python version to 3.10, include py312 in test suite, replace deprecated pkg_resources with importlib.metadata [#73]
• Set minimum tensorflow version to 2.16.1 [#73]
• Pre-trained neural networks updated for compatibility with Keras 3 [#73]
• Dockerfile images now use debian bookworm [#73]

1.1.0

new features

• builder.trained_networks jwst_cal.zip includes updated (v2) img3_reg and new spec3_reg predictive models for image and spectroscopic data [#58]
• preprocessor.ingest.JwstCalIngest class and cmdline script for automated training data ingest [#57]
• extractor.radio.JwstCalRadio subclass for scraping datasets from MAST using ASN metadata [#51]
• extractor.scrape.FitsScraper.scrape_dataframe method added for scraping Fits data from dataframe [#52]

enhancements

• skopes.jwst.cal.predict generates predictions for spectrosopic datasets in addition to image data. This update also allows further customization of user arguments: [#58]
  • obs to specify selection of a program ID + observation number
  • input_path accepts either a directory (default) or a filename. If filename, the script will try to find any input exposures that belong to the same program and observation number as that file.
  • sfx attribute is now customizable on instantiation of the class object (default is '_uncal.fits')
• architect.builder.Builder.save_model uses preferred keras archive format by default [#50]
• preprocessor.transform.SkyTransformer set offsets to 0 for gs/targ fiducial NaN values; custom filename for tx_file [#54]
• preprocessor.prep.JwstCalPrep updates in preparation for preprocessing spectroscopic data [#55]
  • revise spectroscopic data columns
  • save tx_file name with "-{expmode}" to differentiate between image and spec normalization params
  • rename target attributes: y_img_train, y_img_test to y_reg_train, y_reg_test
• preprocessor.scrub.JwstCalScrubber more sophisticated exposure grouping and L3 product naming [#56]

bug fixes

• preprocessor.encode.PairEncoder.handle_unknowns create single new encoding value per unidentified variable [#53]

installation / deps

• Install astropy dev from wheel by @pllim in #48
• Bump sphinx-automodapi from 0.15.0 to 0.17.0 by @dependabot in #60
• Bump plotly from 5.15.0 to 5.20.0 by @dependabot in #59
• Bump pydot from 1.4.2 to 2.0.0 by @dependabot in #62
• Bump pydot from 1.4.2 to 2.0.0 by @alphasentaurii in #64

New Contributors

• @pllim made their first contribution in #48

Full Changelog: 1.0.1...1.1.0

Spacekit v1.1.0 Release Candidate 1

• builder.trained_networks jwst_cal.zip includes updated (v2) img3_reg and new spec3_reg predictive models for image and spectroscopic data [#58]

• preprocessor.ingest.JwstCalIngest class and cmdline script for automated training data ingest [#57]

• extractor.radio.JwstCalRadio subclass for scraping datasets from MAST using ASN metadata [#51]

• extractor.scrape.FitsScraper.scrape_dataframe method added for scraping Fits data from dataframe [#52]

• skopes.jwst.cal.predict generates predictions for spectrosopic datasets in addition to image data. This update also allows further customization of user arguments: [#58]

  • obs to specify selection of a program ID + observation number
  • input_path accepts either a directory (default) or a filename. If filename, the script will try to find any input exposures that belong to the same program and observation number as that file.
  • sfx attribute is now customizable on instantiation of the class object (default is '_uncal.fits')

• architect.builder.Builder.save_model uses preferred keras archive format by default [#50]

• preprocessor.transform.SkyTransformer set offsets to 0 for gs/targ fiducial NaN values; custom filename for tx_file [#54]

• preprocessor.prep.JwstCalPrep updates in preparation for preprocessing spectroscopic data [#55]

  • revise spectroscopic data columns
  • save tx_file name with "-{expmode}" to differentiate between image and spec normalization params
  • rename target attributes: y_img_train, y_img_test to y_reg_train, y_reg_test

• preprocessor.scrub.JwstCalScrubber more sophisticated exposure grouping and L3 product naming [#56]

• preprocessor.encode.PairEncoder.handle_unknowns create single new encoding value per unidentified variable [#53]

1.0.1

What's Changed

bugfixes by @alphasentaurii

• move HstSvmRadio import inside HstSvmScrubber class method to avoid importing astroquery unnecessarily #49
• matplotlib style setting looks for "seaborn-v0_8-bright" if "seaborn-bright" unavailable, fallback uses default style #49

installation / automation by @alphasentaurii

• temporarily pin tf max version to 2.15 to ensure compatibility with models saved in 2.13 or older #49
• GA workflow minor revision: pypi publish #46
• Replace flake8 with ruff, replace deprecated tf.keras.wrappers.scikit_learn with scikeras, add GA workflows #45

documentation by @alphasentaurii

• Update readthedocs.yaml for compatibility with latest formatting requirements [#44]
• RTD: Install graphviz before building docs [#47]

Full Changelog: 1.0.0...1.0.1

v1.0.1 - Release Candidate 1

What's Changed

• config/update-rtd-config by @alphasentaurii in #44
• Project cfg updates by @alphasentaurii in #45
• automation/pypi-workflow by @alphasentaurii in #46
• cfg/docs-and-actions-updates by @alphasentaurii in #47
• bugfix/astroquery-import by @alphasentaurii in #49

Full Changelog: 1.0.0...1.0.1rc1

Spacekit v1.0.0

What's Changed

skopes/jwst/cal/predict by @alphasentaurii in #37

• added new skope for jwst calibration pipeline resource prediction modeling

jwst/minimal-install by @alphasentaurii in #38

• Default installation is a minimal set of dependencies. To install all dependencies, users must now use pip install spacekit[x]

compute/use-npz-instead-of-pickle by @alphasentaurii in #39

• Model training results files use compressed numpy files (.npz) and .csv instead of pickle.

preprocessor/skytransformer by @alphasentaurii in #40

• New class for estimating pixel offset calculations for a Level 3 image product using fiducial values of Level 1 exposures

pytest/compatibility-checks by @alphasentaurii in #41

• Compatibility updates for python 3.10 and 3.11 (backwards compatible with 3.9)

skopes/jwst-predict-tests by @alphasentaurii in #42

• New tests added for JWST skope and dependent scripts.
• Tests modified to reflect updates made to HST skopes and models being renamed

Full Changelog: 0.4.1...1.0.0

1.0.0rc1

What's Changed

• skopes/jwst/cal/predict by @alphasentaurii in #37
• jwst/minimal-install by @alphasentaurii in #38
• compute/use-npz-instead-of-pickle by @alphasentaurii in #39
• preprocessor/skytransformer by @alphasentaurii in #40
• pytest/compatibility-checks by @alphasentaurii in #41
• skopes/jwst-predict-tests by @alphasentaurii in #42

Full Changelog: 0.4.1...1.0.0rc1

Spacekit v0.4.1

What's Changed

skopes/hst-cal-predict by @alphasentaurii in #34

• added predict script for hst cal skope
• enhancements for loading pretrained models
• updated docker dashboard templates
• improved log handling with spacekit/logger module

datasets/external-data by @alphasentaurii in #35

• plugin for external test data
• updated repo url badges
• updated documentation

pytest/cfg-updates-and-cal-s3-predict-tests by @alphasentaurii in #36

• bugfix set dataframe columns with bracket instead of curly bracket (resolves pandas>1.4 incompatibility)
• remove pandas pinned version
• pytest configuration updates and new tests added

Full Changelog: 0.4.0...0.4.1

Spacekit v0.4.0

What's Changed in 0.4.0 (2022-12-08)

• bugfix scikit-learn replaces deprecated sklearn dependency

• temporarily pinned pandas dependency to 1.4.x and below due to column setting bug in v1.5

• bugfix keras load_img method imported from tf.keras.preprocessing.image instead of tf.keras.utils

• new feature skopes.hst.cal model training, inference, cross-validation scripts added

• new feature svm dashboard predict view

• svm ensemble model archive file ensembleSVM.zip renamed as ensemble.zip. This extracts to models/ensemble/ with tx_data.json (transform data) and ensembleSVM (keras model binaries) inside of the ensemble/ parent directory. Previously, the json file was inside ensembleSVM alongside the binaries.

Full Changelog: alphasentaurii/spacekit@0.3.2...0.4.0