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Get statistics from ensemble run data

`[`

* t,m*] = sbioensemblestats(

`simDataObj`

[

`t,m,v`

`simDataObj`

[

`t,m,v,n`

`simDataObj`

[

`t,m,v,n`

`simDataObj`

`names`

[

`t,m,v,n`

`simDataObj`

`names`

`interpolation`

| Column vector of time points |

| Matrix of mean values from the ensemble data. The number of
rows in is the length
of the time vector and
the number of columns is equal to the number of species. |

| A cell array of SimData objects, where each SimData object
holds data for a separate simulation run. All elements of must
contain data for the same states in the same model. When the time
vectors of the elements of are
not identical, is
first resampled onto a common time vector (see below). |

| Matrix of variance obtained from the ensemble data. has
the same dimensions as . |

| Cell array of character vectors for the quantity names whose
mean and variance are returned in and ,
respectively. The number of elements in is
the same as the number of columns of and .
The order of names in corresponds
to the order of columns of and . |

| Character vector or cell array of character vectors. may
include qualified names such as `'` or `'` to
resolve ambiguities. If you specify empty `{}` for , `sbioensemblestats` returns
statistics on all time courses contained in . |

| Character vector denoting the interpolation method to use for
resampling of the data onto a common time vector with the smallest
simulation stop time. See `resample` for
a list of interpolation methods. Default is `'linear'` . |

`[`

computes
the time-dependent ensemble mean * t,m*] = sbioensemblestats(

`simDataObj`

`m`

of
the ensemble data `simDataObj`

.
If the time vectors of the ensemble data are not identical, by default,
the function uses the `'linear'`

interpolation method
to resample the data onto the common time vector. See `resample`

for a list of interpolation
methods. `[`

also
returns the variance * t,m,v*] = sbioensemblestats(

`simDataObj`

`v`

for
the ensemble run data `simDataObj`

.`[`

also
returns the names of quantities * t,m,v,n*] = sbioensemblestats(

`simDataObj`

`n`

`m`

`v`

`m`

`v`

`[`

computes
statistics only for the quantities specified by * t,m,v,n*] = sbioensemblestats(

`simDataObj`

`names`

`names`

`[`

uses
the interpolation method * t,m,v,n*] = sbioensemblestats(

`simDataObj`

`names`

`interpolation`

`interpolation`

to
resample the simulation data to have a consistent time vector. If
the time vectors of the ensemble data are not identical and if you
do not specify any interpolation method, the function uses the `'linear'`

interpolation
method by default.The project file, `radiodecay.sbproj`

, contains
a model stored in a variable called `m1`

. Load `m1`

into
the MATLAB^{®} workspace.

Load a SimBiology

^{®}model`m1`

from a SimBiology project file.sbioloadproject('radiodecay.sbproj','m1');

Change the solver of the active configuration set to be

`ssa`

. Also, adjust the`LogDecimation`

property on the`SolverOptions`

property of the configuration set.cs = getconfigset(m1, 'active'); set(cs, 'SolverType', 'ssa'); so = get(cs, 'SolverOptions'); set(so, 'LogDecimation', 10);

Perform an ensemble of 20 runs with no interpolation.

simDataObj = sbioensemblerun(m1, 20);

Get ensemble statistics for all species using the default interpolation method.

[T,M,V] = sbioensemblestats(simDataObj);

Get ensemble statistics for a specific species using the default interpolation scheme.

`[T2,M2,V2] = sbioensemblestats(simDataObj, {'z'});`

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