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Derive cadence metrics from step timestamps so peak and percentile summaries reflect instantaneous walking cadence. Expose validated cadence bounds through the CLI and apply them consistently to adjusted and unadjusted outputs. src/stepcount/stepcount.py - Calculate rolling minutely cadence from inter-step intervals. - Filter cadence observations with configurable bounds and handle empty inputs. - Pass validated CLI cadence settings into summary generation. tests/conftest.py - Add reusable step-timestamp test data. tests/test_numerical_regression.py - Update cadence regressions for timestamp-based calculations. tests/test_stepcount.py - Cover cadence thresholds, cohort summaries, CLI validation, and end-to-end option propagation.
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Use a new "true cadence" calculation method for the cadence metrics (Peak1, Peak30, 95th)
Summary of Changes
tiny-sample.cwa.gz:
CadencePeak1(steps/min)Cadence95th(steps/min)CadencePeak1(steps/min)_WeekdayCadence95th(steps/min)_WeekdayCadencePeak1Adjusted(steps/min)Cadence95thAdjusted(steps/min)CadencePeak1Adjusted(steps/min)_WeekdayCadence95thAdjusted(steps/min)_Weekday