# MulRunFitter¶↑

A tool for fitting to data the output of a complex simulation involving possibly many runs with different stimulus protocols each with several recordings.

When saved in a session, e.g. fit.ses, two companion files are created called fit.ses.ft1 and fit.ses.fd1. The *.ft1 file contains a readable (and modifiable) definition of the protocols and parameters. The *.fd1 file contains a copy of the data and internal parameters of the panels. When the fit.ses is retrieved, these two files are also read to rebuild the state of the MulRunFitter.

Because it generally takes a long time and a lot of effort to enter the information necessary to specify a complete multiple run fit strategy, it is a good idea to often save the partially built fitter in a session so that if something goes wrong you can always exit and start up again at a safe point.

The usage of the MulRunFitter is expected to undergo considerable refinement in the future.

Pressing the ErrorValue button will execute the “Generator” protocols and show the total error between simulation and data at this particular point in parameter space.

The Parameters menu is used primarily to add, remove, and change parameter names or expressions. Parameter names can be any variable name or any statement involving $1. Statements involving$1 are extremely useful in causing a single parameter to modify many variables. e.g. forall Ra = $1 or some_procedure($1) Even if the parameter is a single variable name, it is most often more useful to express it as a “normalized expression” so that all “optimized” values are close to unity. e.g. cai0_ca_ion = 1e-4*\$1 The Praxis fitter does not work efficiently (or at all) when parameters have very different scales. (but see the log scale factor discussion below)

It also creates panels for:

ParameterPanel
Specifies the current value of the parameter. If the checkbox to the left of the parameter name is active, the parameter will be varied by the fitting algorithm. Otherwise it will be held constant. This panel should be Closed if a parameter name is added, changed, or deleted in order that the list can be updated.
DomainPanel
Specifies the minimum and maximum values of a parameter. Group attributes can be used to set some common domains en masse. If the parameter is set to a value outside this range, the error function will return a very large value (1e9) and not execute the multiple run protocols. If there is an X in the Log column then log scaling is used during optimization. For positive (or negative) definite parameters this can result in very great efficiency improvements during parameter search and certainly obviates scaling difficulties. To change an individual domain property, double click on a name in the domain list. A string editor will pop up and you can enter three space separate numbers. The first is a flag (1 or 0) which specifies whether log scaling is to be used for this parameter. If selected and the range does not include 0, an “X” will appear in the “Log” column. The remaining two numbers are the low and high values of the range. This panel should be Closed if a parameter name is added, changed, or deleted in order to update its list.
OptimizerPanel
This controls the fitting algorithm. This menu item does not really belong here since it has nothing to do with parameters but it had to go somewhere. Currently, the only fitting algorithm that can be used by the MulRunFitter tool is fit_praxis() . “Real time”, “#multiple runs”, and “Minimum so far” show some statistics for the current fitting process. “# quad forms before return” is the argument to a stop_praxis() function call. A value of 0 means that praxis returns when the local space around the minimum it has found meets the criterion chosen by attr_praxis() . In this tool, the default values are tolerance=1e-4 maxstepsize=.5 printmode=0. A non-zero value indicates the number of complete principal axis search steps to be performed before returning. If the error function is a quadratic form, praxis will theoretically find the minimum in one of these steps. After a quad form step, praxis contains a quadratic form approximation to the local search space. The eigenvalues and eigenvectors of this quadratic form are obtainable from pval_praxis()

When the Append the path to savepath.fit checkbox is checked, the elapsed time, fitting error value, and parameters are appended to a file called savepath.fit every time the error value is reduced by a call to the error function..

The Running checkbox is on when the optimizer is running. You should not do much gui interaction at this time such as opening new windows or pressing buttons that could potentially interfere with the protocol runs. First press the Stop button (may need to press it several times) to stop the optimizer. The Optimize button starts the fitting process.

The Generators menu is used to add and view stimulus protocols (which include error functions for calculating the difference between simulation results and data). Each generator is a generalization of a Run Fitter.

creates an empty “Unnamed single run protocol” which is turned off (the “-” in front of its name). A generator which is turned off is not used (does not result in a run and does not contribute to the total error value) during optimization or when the ErrorValue button is pressed.
Remove Generator
destroys a generator when a user double clicks on its name.
Change Name
When you double click on a generator name a string editor pops up in which you can enter a (hopefully meaningful) name for the protocol.
Use Generator
Double click on a generator name to toggle whether it is used by the total error function. When a generator is used, a “+” appears in front of its name.
Multiple Protocol Name
pops up a string editor which allows you to enter a name for this instance of the entire multiple run fit.
Display Generator
Single clicking, or even dragging the mouse over the generator list items, displays the current selection in a separate generator panel. When all the generators are empty this panel is very small. So first select a Fitness/VariableToFit to specify a dependent variable, e.g soma.v(.5) or SEClamp[0].i to fit to data. Then close the panel and reopen it (requires double clicking if the item is already selected in the generator list) in order to see the Graph portion of the display. The generator panel is a Deck and the top card is the one selected in the generator list.

### Fitness menu of a Generator instance in the generator Panel¶↑

Variable to fit
pops up a symbol chooser for selecting a dependent variable which you wish to fit to data for this protocol. For example, possible dependent variable for which you might have data are soma.v(.5) or SEClamp[0].i. Any number of dependent variables can be fit for one protocol (run with particular stimulus values set, see below). For a voltage clamp family, there would only be one current (dependent variable) per generator and different generators for each voltage level. The only case in which there would be more than one dependent variable for a single generator is when there are multiple electrode recordings. The list of dependent variables for this generator is indicated in a sequence of radio button. The large panel below this list contains information about the error function for this variable as well as graph for the data and simulation result for the selected dependent variable.
Remove a Fit Variable and Change a Fit Variable
pop up lists in which you double click an item to perform the removal action or pop up a string editor to change a dependent variable name.
Change Method to
a menu which specifies the fitness (error) functions available for comparing the currently selected (radio list) dependent variable. “RegionFitness” is the default error function and is very similar to the error function for the Run Fitter . In every case, the Graph menu is used to get the data from the clipboard.
RegionFitness
error value is the square norm between data and dependent variable treated as continuous curves.
YFitness
error value is the sum of the square difference of the selected data points (indicated by short vertical blue lines) and the dependent variable at those times. Several Graph menu items are available to add, remove, and move these points.
Protocol Constant
Pops up a symbol chooser in which you can select a stimulus variable. This will be added as a default field editor to the protocol portion of the generator panel. There can be any number of protocol constants. During a run of this generator, the values of the protocol constants are set to the indicated values. After the run, the constants are returned to their original values.
Remove Protocol Constant
Pops ups a list of the existing protocol constants. Double click on an item to throw one away.