PyFoam.Basics.Data2DStatistics module¶
Data structure to do some calculations on the results from SpreadSheetData-methods metrics and compare that are organized in 2 dimensions
-
class
PyFoam.Basics.Data2DStatistics.Data2DStatistics(metrics, compare=None, small=1e-10, noStrings=False, failureValue=None)[source]¶ Bases:
objectOranize statistics about data in 2D-Tables and do basic calculations on it
-
_Data2DStatistics__relativeErrorInternal(name)¶ Return a table with the relative error :param name: spcifies the name under which the error is found in the data
-
__dict__= mappingproxy({'__dict__': <attribute '__dict__' of 'Data2DStatistics' objects>, 'compare': <function Data2DStatistics.compare>, '_makeEmptyTable': <function Data2DStatistics._makeEmptyTable>, '_getLabels': <function Data2DStatistics._getLabels>, '__getitem__': <function Data2DStatistics.__getitem__>, 'range': <function Data2DStatistics.range>, '__init__': <function Data2DStatistics.__init__>, '__doc__': 'Oranize statistics about data in 2D-Tables and do basic\n calculations on it', 'names': <function Data2DStatistics.names>, 'func': <function Data2DStatistics.func>, '_extractTable': <function Data2DStatistics._extractTable>, '__module__': 'PyFoam.Basics.Data2DStatistics', '_Data2DStatistics__relativeErrorInternal': <function Data2DStatistics.__relativeErrorInternal>, '__weakref__': <attribute '__weakref__' of 'Data2DStatistics' objects>, 'relativeAverageError': <function Data2DStatistics.relativeAverageError>, 'relativeError': <function Data2DStatistics.relativeError>})¶
-
__init__(metrics, compare=None, small=1e-10, noStrings=False, failureValue=None)[source]¶ Parameters: - metrics – metrics of the data
- compare – metrics of the comparsion with another data-set
- small – the value that is considered to be close to 0
- noStrings – only put numbers into the tables
- failureValue – the value to use if an evaluation fails
-
__module__= 'PyFoam.Basics.Data2DStatistics'¶
-
__weakref__¶ list of weak references to the object (if defined)
-
_extractTable(name, data=None)[source]¶ Extract data and fill it into a data-table :param name: name of the entry that should be got :param data: the dataset. If unset then self.__metrics is used
-
_getLabels()[source]¶ Return a tuple with the names of the rows and the columns. Assumes that the names for the first data-set are valid for all
-