Handle TVP media in channel_contributions_forward_pass
#998
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* add scaling into lift test method * test scaling methods * test change of MMM likelihood * link up beta_channel parameters * change name to sigma * reorganize and edit * closes pymc-labs#406 * address the feedback in docstrings * add more to docstring * format the docstring * be verbose for future devs * be explicit for the column max values * incorporate the feedback * hide cells and add to intro * add conclusion * switch to header 2 * run notebook through * move the types together * separate model estimated from empirical * fix typos
* drop python 3.9 * try python 3.12 * undo try python 3.12
* improve nb * rm warnings and add link to lifetimes quickstart * address comments * feedback part 3 * remove warnings manually
* add more info to the notebook * hide plots code * fix plot y labels * fix plot outputs and remove model build * improve final note probability plots * address comments * use quickstart dataset * feedback part 3 * remowe warnings manually * feedback part 4
* improve mmm docs init * add more code examples to docstrings * minor improvemeents * typo * better phrasing * add thomas suggestion
* move fixtures to conftest * docstrings and moved set_model_fit to conftest * fixed pandas quickstart warnings * revert to MockModel and add ParetoNBD support * quickstart edit for issue 609 * notebook edit
remove ruff E501 ignore
updates: - [github.com/astral-sh/ruff-pre-commit: v0.3.5 → v0.3.7](astral-sh/ruff-pre-commit@v0.3.5...v0.3.7) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Juan Orduz <[email protected]>
* fix potential bugs * minor improvements * remove rule for nb * fix test * improve tests syntax * use stacklevel 2 for warnings * use stacklevel 1 for warnings as they are used in public methods * ignore B904 * undo change * ricardos feedback * use fit_posterior * Update pymc_marketing/clv/models/gamma_gamma.py Co-authored-by: Ricardo Vieira <[email protected]> * last fix XD --------- Co-authored-by: Ricardo Vieira <[email protected]>
* notebook opening and imports * model definition markdown * Data Load Notebook section * WIP model fitting section * added notebook to docs directory * notebook edits and graph code * ppc section and nb cleanup * demz sampling and WIP plotting * WIP predictive plots * WIP heatmap plots * predictive plots * WIP covariates and nbqa-ruff edits * covariate section * plot additions * fig sizes * remove model file
…book (pymc-labs#651) * add spaces, increase indentation, and fix number order * explicit with 6
* Creating plot waterfall Co-Authored-By: Carlos Trujillo <[email protected]> * requested changes * pre-commit --------- Co-authored-by: Carlos Trujillo <[email protected]>
Databricks should have a lower-case b.
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* support for negative values and dates (if used) * fix terrible spelling * test dates in coords * cover numpy objects * consolidate the tests
…abs#960) * Enforce check_parameters in geometric_adstock * Remove check_parameters on l_max. Revert to original test * Add test_geometric_adstock_bad_alpha * use ge, le instead of gt,lt * Update tests/mmm/test_transformers.py Co-authored-by: Will Dean <[email protected]> * Simplify test parameters * Update tests/mmm/test_transformers.py Co-authored-by: Will Dean <[email protected]> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: Will Dean <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
…#967) * change repo and python file change to kick off * comment to check for failure * using the repo * delete to trigger * the previous trigger * push up again * check for the owner being pymc-labs * remove unused * only run after merge to main
* deprecations and moving files * Update UML Diagrams * change the imports in notebooks * push up the code / test changes. need to run * remove _get_\w*_function tests * rerun the tvp notebook * remove stale test * move away from string initialization * change the tvp media example
* allow register and use custom transform * add to the example block
updates: - [github.com/astral-sh/ruff-pre-commit: v0.6.1 → v0.6.2](astral-sh/ruff-pre-commit@v0.6.1...v0.6.2) - [github.com/pre-commit/mirrors-mypy: v1.11.1 → v1.11.2](pre-commit/mirrors-mypy@v1.11.1...v1.11.2) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Will Dean <[email protected]> Co-authored-by: Juan Orduz <[email protected]>
* add table * sync index * empty * improvements
* nb init * add param stability * crps init * add crps to package * make mypy happy * clean * relax req * update path * add crps test * first iteration * improvements * improve tests * improve tests * improve references * feedback 1 * add examples
…ocs (pymc-labs#992) * Changed pt=pt to pt_lib = None to avoid showing full module path in docs * Changed pt to pt_lib inside calculate_lift_measurements_from_curve
* push up some linear-trend work I had * image for the documentation * start the slopes at t=0 * additional checks at init * import at mmm module * update the image * Move to reference section * Move coords to single line * Add hierarchical trend example * add image for the example * migrate to pydantic * update images after seed * Correct the latex * fix check from tests
updates: - [github.com/astral-sh/ruff-pre-commit: v0.6.2 → v0.6.3](astral-sh/ruff-pre-commit@v0.6.2...v0.6.3) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Juan Orduz <[email protected]>
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I am not sure if it's right logic to do time_varying_channel_contributions_forward_pass and need some help with relevant test |
wd60622
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Sep 4, 2024
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| time_index = ( | ||
| np.arange(0, self.preprocessed_data["X"].shape[0]) | ||
| if self.time_varying_media | ||
| else None | ||
| ) |
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Will we know if the dates are correct? Is this only used for the insampel data? What if the channel_contributions input are from a subset of the input. We will likely need to use the infer_time_index if this is used for new data. This a complaint of mine from the original implementation. If it is always used in the context of the insample, can we not just use the self._time_index variables create in fit call.
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Hi @radiokosmos |
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Description
Related Issue
channel_contributions_forward_pass#819Checklist
Modules affected
Type of change
📚 Documentation preview 📚: https://pymc-marketing--998.org.readthedocs.build/en/998/