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This commit introduces the new `senspy.power` module, providing foundational tools for statistical power and sample size calculations related to binomial tests, which are crucial for sensory discrimination testing. Key functions implemented: - `find_critical_binomial_value`: Determines the critical number of successes for a binomial test, analogous to `sensR::findcr`. - `exact_binomial_power`: Calculates the exact statistical power for a one-sample binomial test using the critical value. - `sample_size_for_binomial_power`: Estimates the sample size required to achieve a target power for a binomial test, using an iterative search. - `power_discrim`: A general function to calculate power for various sensory discrimination methods (e.g., "2afc", "triangle") by converting d-prime values to proportions correct and then utilizing `exact_binomial_power`. Unit tests for these new functions have been written and added to `tests/test_power.py`. However, due to persistent issues with the script execution environment (`pytest` failing to find the test file), these tests could not be run to confirm their pass/fail status during this session. The implemented power functions are based on established statistical principles and `sensR`'s logic. This commit represents the initial phase of building out `sensPy`'s power analysis capabilities.
catch up with master
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Testing
pytest