pandas-association-measures - v0.3.1

compatibility release - drop support for Python3.8 (reached EOL), support Python3.13 instead - switch from pipenv to venv - use pandas >=2.2.2 and numpy >=2.0 (numpy2 and pandas2 are now compatible again) - include separate requirements-dev - remove travis.yml (everything runs in GitHub actions anyway)

also includes some WIP on categorisation of measures and profile comparisons

- Python
Published by ausgerechnet about 1 year ago

pandas-association-measures - v0.3.0

• add feature for creating topographic grids
• default to Poisson boundary in LRC
• now requires Python>=3.8, pandas>=2.0

- Python
Published by ausgerechnet almost 2 years ago

pandas-association-measures - v0.2.7

• discounting according to Walter1975 for log-ratio
• make Poisson boundary the default for LRC
• major performance improvement for LRC with Poisson boundary
• further performance improvement: only calculate scores once for each frequency signature

- Python
Published by ausgerechnet over 2 years ago

pandas-association-measures - v0.2.6

• force np.vectorize to return float, otherwise conservative log ratio might be rounded to integer

- Python
Published by ausgerechnet over 3 years ago

pandas-association-measures - v0.2.5

• repair measuring performance
• do not calculate binomial likelihood by default

- Python
Published by ausgerechnet over 3 years ago

pandas-association-measures - v0.2.4

make calculation of conservative log ratio with Poisson boundary robust against observations with O11=O21=0: return 0.

- Python
Published by ausgerechnet over 3 years ago

pandas-association-measures - v0.2.3

• setup.py: installation under Windows should work properly now
• deprecated calculate_measures()
• correction in liddell()
• allow integers to be passed to observed_frequencies(); extend functionality
• don't use methods to be tested in conftest.py

- Python
Published by AndreasBlombach over 3 years ago

pandas-association-measures - v0.2.2

• new AM: conservative log ratio with correct CI boundary from Poisson distribution (Evert 2022)
• include wheel as build dependency in pyproject.toml
• use score() rather than calculate_measures() in tests; extend propagation of score() parameters
• include pytest.ini
• simplify setup.py

- Python
Published by ausgerechnet over 3 years ago

pandas-association-measures - v0.2.1

update requirements - maximum of version numbers s.t. python3.6 - specify wheel as requirement (for building)

two new measures: - minimum sensitivity - Liddell

- Python
Published by ausgerechnet almost 4 years ago

pandas-association-measures - v0.2.0

• new possible input: "keyword-friendly" corpus frequencies notation (f1, N1, f2, N2)
• new score wrapper also allows constant integer counts (N1, N2 for keyword notation; f1, N for frequency signatures) to be given as parameters
• keyword arguments are now passed from calculate_measures() (and score()) to underlying measures

- Python
Published by ausgerechnet over 4 years ago

pandas-association-measures - v0.1.7

compatibility: - require scipy instead of python3.8

measures: - local MI - simple LL - extend parameters of conservative log ratio (Sidak correction)

sort & categorize measures: - asymptotic hypothesis tests - point estimates of association strength - (likelihood measures) - information theory - conservative estimates

universal discounting for zeros: - O11 and O12 are set to a small value where they're 0 (0.001 by default; except for Hardie's dubious discounting of 0.5) - this makes additional definition of phi-function obsolete - NB discounting does not have any effect for some measures (log-likelihood, local MI)

- Python
Published by ausgerechnet over 4 years ago

pandas-association-measures - v0.1.6

What's Changed

• github workflows by @ausgerechnet in https://github.com/fau-klue/pandas-association-measures/pull/20
• V0.1.6 by @ausgerechnet in https://github.com/fau-klue/pandas-association-measures/pull/19

Full Changelog: https://github.com/fau-klue/pandas-association-measures/compare/v0.1.5...v0.1.6

- Python
Published by ausgerechnet over 4 years ago