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There is a range of functions that allow the calculation of statistical properties of Monte-Carlo data.
In general, when running a simulation, the results are recorded with an Observable-class and stored in a HDF5 file. These files can then later be read and statistical properties can be calculated. These results can also be written back into the file. There are several examples on how to do this in the examples/alea folder.
Here is an overview of the functions available
Function Name |
Argument(s) |
Options |
Return Type |
---|---|---|---|
|
Timeseries |
None |
|
|
Timeseries |
None |
|
|
Timeseries |
uncorrelated, binning |
|
|
Timeseries |
_distance, _limit |
|
|
Scalar MCTimeseries |
_from & _to, _max & _min |
|
|
Scalar MCTimeseries, |
None |
|
|
Timeseries |
None |
|
|
Timeseries |
None |
|
where AverageType
is typename average_type<ValueType>::type,\\
Timeseries is
one of
mcdata<ValueType>,
mctimeseries<ValueType> or mctimeseries_view<ValueType>[newline] and
Scalar
MCTimeseries` is one of mctimeseries<double> or mctimeseries_view<double>\
The objects mctimeseries<ValueType>
and mctimeseries_view<ValueType>
are essentially wrapped boost::shared_ptr's to the timeseries. while the constructor
of the mctimeseries class copies the whole data, the constructor of the mctimeseries_view
class only creates a reference. One can easily create views of timeseries by
using the functions cut_head and cut_tail:
Function Name |
Argument(s) |
Options |
Return Type |
---|---|---|---|
|
Timeseries |
_distance, _limit |
|
|
Timeseries |
_distance, _limit |
|
Copyright © 1994, 2002-2004, 2012 Matthias Troyer, Synge Todo, Maximilian Poprawe |