steppar

Perform a fit while stepping the value of a parameter through a given range. Useful for determining confidence ranges in situations where greater control is needed than given with the error command.

Syntax: |
steppar |
[current|best] <step spec>[<step spec>...] |
---|

where `<step spec>` ::= `[log|nolog] [<modelName>:]<param index>
<low value> <high value> <# steps>`

or `<step spec>` ::= `[log|nolog] [<modelName>:]<param index>
delta <step size> <# steps>`

In the first case the parameter is stepped from `<low value>` to `<high value>`
in `<# steps>` plus one trials. In the second case the parameter is stepped
from `<best fit value>`-`<step size>`*`<# steps>` to `<best fit value»`
+`<step size>`*`<# steps>`, ie a total of 2`<# steps>`+1 trials.
The stepping is either linear or
log. Initially, the stepping is linear but it can be changed by the optional
string `log` before the parameter index. `nolog` will force the stepping to be
returned to the linear form. If more than one parameter is entered, then
`<# steps>` must be entered for each one except the last. Note that every
variable parameter whose `<param index>` is NOT entered in the command will
still be allowed to vary freely during each steppar iteration.

To perform a steppar run on gain (or response) parameters,
the optional `[<modelName>:]` specifier is replaced by an optional
`[<sourceNumber>:]` specifier, and the letter 'r' needs to be
attached as a prefix to the `<parameter index>`. For example:

steppar 2:r3 1.5 2. 10

will step the third response parameter belonging to source number 2.

The number of steps is set initially to 10. At each value, the parameter is
frozen, a fit performed, and the resulting value of chi-squared given.
If `best` is given as an argument then the non-stepped parameters are
reset to the best-fit values at each grid point. Alternatively, if
`current` is given as an argument then the non-stepped parameters
are started at their values after the last grid point (the default).

If multiple `<step spec>` are given for different parameters, then a
raster scan of the parameter ranges is performed. At the end of the set,
the parameters and chi-squared are restored to the values they had initially.

If the model is in a best-fit state when a steppar run is started and a new best fit is found during the run, the user will be prompted at the end of the run to determine if they wish to accept the new best-fit values for their parameters. This prompting can be disabled by the setting of the query flag.

Depending on the machine, a steppar run may be sped up significantly by assigning it to multiple processes. See the parallel command with the steppar option for more details.

**Examples:**

Assume that the current model has four parameters:

XSPEC12> steppar 3 1.5 2.5 //Step parameter 3 from 1.5 to 2.5 in steps of .1. XSPEC12> steppar log //Repeat the above, only use multiplicative steps of 1.0524. XSPEC12> step nolog 2 -.2 .2 20 //Step parameter 2 linearly from -.2 to .2 in steps of 0.02. XSPEC12> step 2 delta 0.02 5 //Step parameter 2 linearly from the best-fit value-0.1 to //the best-fit value+0.1 in a total of 11 steps.