Developer Guide and Reference

  • 2021.3
  • 06/28/2021
  • Public Content
Contents

Online Processing

Online processing computation mode assumes that data arrives in blocks LaTex Math image..
Computation of low order moments in the online processing mode follows the general computation schema for online processing described in Algorithms.

Algorithm Input

The low order moments algorithm accepts the input described below. Pass the
Input ID
as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID
Input
data
Pointer to the numeric table of size LaTex Math image. that represents the current data block.
While the input for
defaultDense
,
singlePassDense
, or
sumDense
method can be an object of any class derived from
NumericTable
, the input for
fastCSR
,
singlePassCSR
, or
sumCSR
method can only be an object of the
CSRNumericTable
class.

Algorithm Parameters

The low order moments algorithm has the following parameters:
Parameter
Default Valude
Description
algorithmFPType
float
The floating-point type that the algorithm uses for intermediate computations. Can be
float
or
double
.
method
defaultDense
Available methods for computation of low order moments:
defaultDense
default performance-oriented method
singlePassDense
implementation of the single-pass algorithm proposed by D.H.D. West
sumDense
implementation of the algorithm in the cases where the basic statistics associated with the numeric table are pre-computed sums; returns an error if pre-computed sums are not defined
fastCSR
performance-oriented method for CSR numeric tables
singlePassCSR
implementation of the single-pass algorithm proposed by D.H.D. West; optimized for CSR numeric tables
sumCSR
implementation of the algorithm in the cases where the basic statistics associated with the numeric table are pre-computed sums; optimized for CSR numeric tables; returns an error if pre-computed sums are not defined
initializationProcedure
Not applicable
The procedure for setting initial parameters of the algorithm in the online processing mode.
By default, the algorithm does the following initialization:
  • Sets
    nObservations
    ,
    partialSum
    , and
    partialSumSquares
    to zero.
  • Sets
    partialMinimum
    and
    partialMaximum
    to the first row of the input table.
estimatesToCompute
estimatesAll
Estimates to be computed by the algorithm:
  • estimatesAll
    - all supported moments
  • estimatesMinMax
    - minimum and maximum
  • estimatesMeanVariance
    - mean and variance

Partial Results

The low order moments algorithm in the online processing mode calculates partial results described below. Pass the
Result ID
as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Result ID
Result
nObservations
Pointer to the LaTex Math image. numeric table that contains the number of rows processed so far.
By default, this result is an object of the
HomogenNumericTable
class, but you can define the result as an object of any class derived from
NumericTable
except
CSRNumericTable
.
Partial characteristics computed so far, each in a LaTex Math image. numeric table. By default, each table is an object of the
HomogenNumericTable
class, but you can define the tables as objects of any class derived from
NumericTable
except
PackedSymmetricMatrix
,
PackedTriangularMatrix
, and
CSRNumericTable
.
Result ID
Result
partialMinimum
Partial minimums
partialMaximum
Partial maximums
partialSum
Partial sums
partialSumSquares
Partial sums of squares
partialSumSquaresCentered
Partial sums of squared differences from the means

Algorithm Output

The low order moments algorithm calculates the results described in the following table. Pass the
Result ID
as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Each result is a pointer to the LaTex Math image. numeric table that contains characteristics for each feature in the data set. By default, the tables are objects of the
HomogenNumericTable
class, but you can define each table as an object of any class derived from
NumericTable
except
PackedSymmetricMatrix
,
PackedTriangularMatrix
, and
CSRNumericTable
.
Result ID
Characteristic
minimum
Minimums
maximum
Maximums
sum
Sums
sumSquares
Sums of squares
sumSquaresCentered
Sums of squared differences from the means
mean
Estimates for the means
secondOrderRawMoment
Estimates for the second order raw moments
variance
Estimates for the variances
standardDeviation
Estimates for the standard deviations
variation
Estimates for the variations
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex​.
Notice revision #20201201

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.