LOG_GROWTH_MODEL

Python object: phenotypic.schema._log_growth_model.LOG_GROWTH_MODEL

Fitted parameters and bounds of the logistic growth model.

Output columns are metric-qualified: each header is LogGrowthModel_<metric>_<parameter>, where <metric> records the measurement the model was fit on (self.on with its category prefix stripped, e.g. Shape_Area → Area). For example, fitting on Shape_Area emits LogGrowthModel_Area_r (intrinsic growth rate) and LogGrowthModel_Area_µmax (maximum specific growth rate). The labels below are the <parameter> segment; the <metric> infix is filled in at fit time.

Category: LogGrowthModel

Column label	Description	Type
LogGrowthModel_r	The intrinsic growth rate	Tier 1 · Direct phenotype
LogGrowthModel_K	The carrying capacity	Tier 1 · Direct phenotype
LogGrowthModel_N0	The initial number of the colony size metric being fitted	Tier 1 · Direct phenotype
LogGrowthModel_lambda	The regularization factor applied to the max specific growth rate and initial population size	Quality
LogGrowthModel_beta	The penalty factor applied to relative difference of the carrying capacity from the largest measurement	Quality
LogGrowthModel_µmax	The growth rate of the colony calculated as (K*r)/4	Tier 1 · Direct phenotype
LogGrowthModel_Kmax	The upper bound of the carrying capacity for model fitting	Quality