TAPE v0.2.2

What's Changed

• Add pip install instructions by @dougbrn in #136
• Read datasets by @dougbrn in #138
• Fix codecov integration by @dougbrn in #147
• Create stub notebook for Structure Function science showcase. by @drewoldag in #134
• Update README.md by @drewoldag in #153
• Issue74 improve dropna by @wenneman in #155
• Quickstart by @dougbrn in #160
• add installation guide by @dougbrn in #162
• downgrade numpy for numba support by @dougbrn in #167
• SF^1 to SF^2 bug fix by @nevencaplar in #168
• Add Repo Badges by @dougbrn in #170
• overhaul loading docs by @dougbrn in #171
• update default meta by @dougbrn in #179
• add coalesce by @dougbrn in #178
• changed replace False to True in random_generator by @nevencaplar in #182
• Add support for Python 3.11 on Github Actions by @aitorres in #188
• Dedicated error estimate in structure function by @nevencaplar in #189
• Flux to Mag Converter Function by @dougbrn in #190

New Contributors

• @wenneman made their first contribution in #155
• @aitorres made their first contribution in #188

Full Changelog: v0.2.1...v0.2.2

TAPE v0.2.1

Updates naming for PyPI and ReadTheDocs

TAPE v0.2.0

TAPE v0.2.0 includes the following:

• Object/Source Paradigm: The Ensemble dataframe has been broken into two dataframes, the "source" and "object" frames. Where the object dataframe stores object level information, and the source frame stores their corresponding time-domain data. These dataframes are kept in-sync with one another as the dataframes are worked with.
• Expanded Dataframe API: Ensemble.insert, Ensemble.persist, Ensemble.select, Ensemble.query, Ensemble.assign, Ensemble.from_source_dict
• ColumnMapper Utility Class: Facilitates mapping of dataset columns to the internal Ensemble known columns.
• Temporal Binning Functionality: Added via Ensemble.bin_sources, with a full tutorial notebook on it's usage
• Greatly Expanded Structure Function: including a number of implementations to choose from, many new keyword arguments, the ability to implement your own function within the Structure Function framework, and a partial tutorial notebook.

Initial Release

lsstseries v0.1.0 establishes several core components of lsstseries, namely:

• The Ensemble
• The TimeSeries
• The analysis module and the StetsonJ and StructureFunction functions
• Initial Documentation