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maped = MAP({expressions = ['x + 2.0', 'x * 2.0', 'x * toProbabilisticDouble([1.0,0.5;2,0.5])', 'x * toProbabilisticDouble([1.0,0.5])']}, input)

Mathematic Functions

SQRT(Probabilistic Value)

Computes the probabilistic square root of the given probabilistic value.

Datatype Functions

ToProbabilisticDouble(Matrix)

Constructs a discrete probabilistic value using the first column of the given matrix for the values and the second column of the matrix for the probabilities for each value.

DoubleToShort(Probabilistic Value)

Converts the given probabilistic double value to a probabilistic short value

DoubleToByte(Probabilistic Value)

Converts the given probabilistic double value to a probabilistic byte value

DoubleToInteger(Probabilistic Value)

Converts the given probabilistic double value to a probabilistic integer value

DoubleToFloat(Probabilistic Value)

Converts the given probabilistic double value to a probabilistic float value

DoubleToLong(Probabilistic Value)

Converts the given probabilistic double value to a probabilistic long value

as2DVector(Object, Object)

Converts the two object into a 2D vector.

as3DVector(Object, Object, Object)

Similar to the as2DVector function, this function creates a 3D vector with the given objects.

Int(Distribution, Lower Limit, Upper Limit)

Estimates the multivariate normal distribution probability with lower and upper integration limit.

Similarity(Distribution, Distribution)

Calculates the Bhattacharyya distance between two distributions.

SELECT similarity(as2DVector(x1,y1), as2DVector(x2,y2)) FROM stream

Distance(Distribution, Value)

Calculates the Mahalanobis distance between the distribution and the value. The value can be a scalar value or a vector.

SELECT distance(as3DVector(x, y, z), [1.0;2.0;3.0]) FROM stream

Access to tuple existence

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