Source code for phenotypic.schema._log_growth_model
"""Fitted parameters and bounds for the logistic growth model."""
from ._measurement_info import Entry
from ._tiers import DerivedMeasure
[docs]
class LOG_GROWTH_MODEL(DerivedMeasure):
"""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.
"""
[docs]
@classmethod
def category(cls) -> str:
return "LogGrowthModel"
R_FIT = Entry("r", "The intrinsic growth rate",
tier=1, derivation_type="parameterization", derives_from="SIZE")
K_FIT = Entry("K", "The carrying capacity",
tier=1, derivation_type="parameterization", derives_from="SIZE")
N0_FIT = Entry("N0", "The initial number of the colony size metric being fitted",
tier=1, derivation_type="parameterization", derives_from="SIZE")
LAM = Entry(
"lambda",
"The regularization factor applied to the max specific growth rate "
"and initial population size",
derivation_type="diagnostic",
)
BETA = Entry(
"beta",
(
"The penalty factor applied to relative difference of "
"the carrying capacity from the largest measurement"
),
derivation_type="diagnostic",
)
GROWTH_RATE = Entry("µmax", "The growth rate of the colony calculated as (K*r)/4",
tier=1, derivation_type="parameterization", derives_from="SIZE")
K_MAX = Entry("Kmax", "The upper bound of the carrying capacity for model fitting",
derivation_type="diagnostic")