I hold comprehensive results of a multi-setup evaluation in my runs dict, with each element being an instance of Run.

Significantly, I store a copy of the VectorBase subclass instance from each setup's simulation because the original will likely get overwritten soon.

Use Result_SSE instead if all you will ever need is the total SSE.

Method	__init__	Undocumented
Method	SSE	Property: My SSE is the sum of SSEs for all runs, unless one of them is negative or `None`.
Method	__contains__	Undocumented
Method	__len__	Undocumented
Method	__iter__	Undocumented
Method	__getitem__	Undocumented
Method	nameList	Undocumented
Method	makeBogus	Undocumented
Method	__call__	No summary

def __init__(self, nameLists):

Undocumented

@property
def SSE(self):

Property: My SSE is the sum of SSEs for all runs, unless one of them is negative or None.

A run with a negative SSE gives me an SSE of -1. A run with an SSE of None gives me an infinite SSE.

def __contains__(self, ID):

Undocumented

def __len__(self):

Undocumented

def __iter__(self):

Undocumented

def __getitem__(self, ID):

Undocumented

def nameList(self, ID):

Undocumented

def makeBogus(self):

Undocumented

def __call__(self, ID, SSE, *args):

Call my instance with a setup ID and SSE. If not an SSE-only analysis, also include the setup's goal array X and EvalSpec object, and the simulation result's Vectors instance V. Creates a Run with results for that setup.

Critically, the new run object's V attribute is a copy of V, not the supplied object itself. That way, other things can modify V without messing up the results of this run.

This is the only valid way to modify my runs dict.

API Documentation for pingspice, generated by pydoctor at 2021-09-18 08:41:11.

pingspice.analysis.sse.Result(object) class documentation

`pingspice.analysis.sse.Result(object)` class documentation