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Meta.Numerics.Statistics.UncertainMeasurementSample< T > Class Template Reference

Represents a set of measurements. More...

+ Inheritance diagram for Meta.Numerics.Statistics.UncertainMeasurementSample< T >:
+ Collaboration diagram for Meta.Numerics.Statistics.UncertainMeasurementSample< T >:

Public Member Functions

 UncertainMeasurementSample ()
 Initializes a new, empty data set. More...
 
void Add (UncertainMeasurement< T > datum)
 Adds a new data point to the set. More...
 
void Add (T x, double y, double dy)
 Adds a new data point to the set. More...
 
void Add (IEnumerable< UncertainMeasurement< T >> data)
 Adds a series of data points to the set. More...
 
bool Remove (UncertainMeasurement< T > datum)
 Removes a data point from the set. More...
 
bool Contains (UncertainMeasurement< T > datum)
 Determines whether the set contains the given data point. More...
 
void Clear ()
 Removes all data points from the set. More...
 
FitResult FitToLinearFunction (Func< T, double >[] functions)
 Fits the data to a linear combination of fit functions. More...
 
FitResult FitToFunction (Func< double[], T, double > function, double[] start)
 Fits the data to an arbitrary parameterized function. More...
 
IEnumerator
< UncertainMeasurement< T > > 
GetEnumerator ()
 Gets an enumerator over the measurements. More...
 

Properties

int Count [get]
 Gets the size of the data set. More...
 
bool ICollection
< UncertainMeasurement< T > >. 
IsReadOnly [get]
 

Private Member Functions

void ICollection
< UncertainMeasurement< T > >. 
CopyTo (UncertainMeasurement< T >[] array, int offset)
 
System.Collections.IEnumerator
System.Collections.IEnumerable. 
GetEnumerator ()
 

Private Attributes

List< UncertainMeasurement< T > > data = new List<UncertainMeasurement<T>>()
 

Detailed Description

Represents a set of measurements.

Template Parameters
TThe type of independent variable associated with each measurement.

Constructor & Destructor Documentation

Initializes a new, empty data set.

Member Function Documentation

void Meta.Numerics.Statistics.UncertainMeasurementSample< T >.Add ( UncertainMeasurement< T >  datum)
inline

Adds a new data point to the set.

Parameters
datumThe data point.
void Meta.Numerics.Statistics.UncertainMeasurementSample< T >.Add ( x,
double  y,
double  dy 
)
inline

Adds a new data point to the set.

Parameters
xThe value of the ordinate (independent variable).
yThe value of the abcissa (dependent variable).
dyThe uncertainty of the abcissa (dependent variable).
void Meta.Numerics.Statistics.UncertainMeasurementSample< T >.Add ( IEnumerable< UncertainMeasurement< T >>  data)
inline

Adds a series of data points to the set.

Parameters
dataThe data points.
bool Meta.Numerics.Statistics.UncertainMeasurementSample< T >.Remove ( UncertainMeasurement< T >  datum)
inline

Removes a data point from the set.

Parameters
datumThe data point to remove.
Returns
True if the data point was found and removed; otherwise false.
bool Meta.Numerics.Statistics.UncertainMeasurementSample< T >.Contains ( UncertainMeasurement< T >  datum)
inline

Determines whether the set contains the given data point.

Parameters
datumThe data point.
Returns
True if the set contains the given data point, otherwise false.

Removes all data points from the set.

FitResult Meta.Numerics.Statistics.UncertainMeasurementSample< T >.FitToLinearFunction ( Func< T, double >[]  functions)
inline

Fits the data to a linear combination of fit functions.

Parameters
functionsThe component functions.
Returns
A fit result containing the best-fit coefficients of the component functions and a &#x3C7;2 test of the quality of the fit.
Exceptions
ArgumentNullExceptionfunctions is null.
InsufficientDataExceptionThere are fewer data points than fit parameters.
FitResult Meta.Numerics.Statistics.UncertainMeasurementSample< T >.FitToFunction ( Func< double[], T, double >  function,
double[]  start 
)
inline

Fits the data to an arbitrary parameterized function.

Parameters
functionThe fit function.
startAn initial guess at the parameters.
Returns
A fit result containing the best-fitting function parameters and a &#x3C7;2 test of the quality of the fit.
Exceptions
ArgumentNullExceptionfunction or start are null.
InsufficientDataExceptionThere are fewer data points than fit parameters.

References Meta.Numerics.Matrices.SymmetricMatrix.CholeskyDecomposition(), Meta.Numerics.Analysis.FunctionMath.FindMinimum(), and Meta.Numerics.Matrices.CholeskyDecomposition.Inverse().

IEnumerator<UncertainMeasurement<T> > Meta.Numerics.Statistics.UncertainMeasurementSample< T >.GetEnumerator ( )
inline

Gets an enumerator over the measurements.

Returns
An enumerator over the measurements.
void ICollection<UncertainMeasurement<T> >. Meta.Numerics.Statistics.UncertainMeasurementSample< T >.CopyTo ( UncertainMeasurement< T >[]  array,
int  offset 
)
inlineprivate
System.Collections.IEnumerator System.Collections.IEnumerable. Meta.Numerics.Statistics.UncertainMeasurementSample< T >.GetEnumerator ( )
inlineprivate

Member Data Documentation

List<UncertainMeasurement<T> > Meta.Numerics.Statistics.UncertainMeasurementSample< T >.data = new List<UncertainMeasurement<T>>()
private

Property Documentation

Gets the size of the data set.

bool ICollection<UncertainMeasurement<T> >. Meta.Numerics.Statistics.UncertainMeasurementSample< T >.IsReadOnly
getprivate

The documentation for this class was generated from the following file: