I evaluate thermistor curve fitness.

Construct an instance of me, run the setup method, and wait (in non-blocking Twisted-friendly fashion) for the Deferred it returns to fire. Then call the instance a bunch of times with parameter values for a curve to get a (deferred) sum-of-squared-error fitness of the curve to the thermistor data.

Method	setup	Returns a `Deferred` that fires with two equal-length sequences, the names and bounds of all parameters to be determined.
Method	prefix2name	Returns the name of a parameter for the k'th thermistor, having a common prefix with the other thermistors.
Method	values2args	Returns a subset list of parameter values to use as args in a call to `curve` for the specified Yocto-MaxThermistor input k (1-6).
Method	curve	Given a 1-D vector of resistances measured for one thermistor, followed by arguments defining curve parameters, returns a 1-D vector of temperatures (degrees C) for those resistances.
Method	__call__	Evaluation function for the parameter values.

Inherited from Picklable:

Method	__getstate__	Undocumented
Method	__setstate__	Undocumented

def setup(self):

Returns a Deferred that fires with two equal-length sequences, the names and bounds of all parameters to be determined.

Also creates a dict of indices in those sequences, keyed by parameter name.

def prefix2name(self, prefix, k):

Returns the name of a parameter for the k'th thermistor, having a common prefix with the other thermistors.

def values2args(self, values, k):

Returns a subset list of parameter values to use as args in a call to curve for the specified Yocto-MaxThermistor input k (1-6).

def curve(self, R, *args):

Given a 1-D vector of resistances measured for one thermistor, followed by arguments defining curve parameters, returns a 1-D vector of temperatures (degrees C) for those resistances.

The model implements this equation:

T = 1 / (A*b + B*b*ln(R) + C*c*ln(R)^2 + D*d*ln(R)^3 - 273.15

where R is in Ohms and T is in degrees C. Uppercase coefficients are for all thermistors and lowercase are for just the thermistor in question.

def __call__(self, values, xSSE=None):

Evaluation function for the parameter values.

Applies a penalty if the geometric mean of the scaling factors (values after the first six, lowercase param names) deviates from 1.0, to counteract genetic drift.

API Documentation for ade, generated by pydoctor at 2022-11-17 13:13:22.

ade.examples.thermistor.Evaluator(Picklable) class documentation

`ade.examples.thermistor.Evaluator(Picklable)` class documentation