A TimeSeriesProperty is a specialised mantid.kernel.Property class that holds time/value pairs. It offers a selection of statistics through it’s Python interface which you can use in your scripts.

Specific classes that implement this are:


To get hold of a time series property, you need to get the handle to the object from the mantid.api.Run object.

To get the mantid.kernel.TimeSeriesPropertyStatistics object, you then call getStatistics() on the property.

This allows you to access the following attributes:

  • minimum

  • maximum

  • mean

  • median

  • standard_deviation

  • duration



Handling boundary condition

Definition: log_t0, log_tf, filter_t0, filter_tf

  • Beginning of the filter

    • If filter_t0 < log_t0`, then the log is extended to filter_t0

    • If filter_t0 > log_t0, all logs before first occurrence of False in filter are in the prohibited region.

It is to say that the first entry of a log starts from the first occurrence of TRUE value.

  • End of the filter

    • If filter_tf > log_tf, and filter_tf is false, the (virtual) filtered log is extended by all filter entries beyond log_tf;

    • If filter_tf < log_tf`, and last filter entry is false, then all entries of the log after filter_tf are in the disallowed region;


Return the nth interval

  • An interval starts from filter’s time.

  • If the starting filter time is not same as any log entry, then from this filter time to the log entry just behind it will be an interval.

  • An interval ends at filter’s time if there is a filter value change between this log entry and its next log entry;

  • An interval can go beyond real log.

  • If it is the last interval, dt is estimated from either previous log entry or previous (false) filter entry, which is later in time.


Return the value of nth interval.

  • If the interval starts from a filter time, then the value is either

    • the log value just before the filter time if filter time is not ahead all log entries’ time or

    • the value of first log entry