Stream evaluators are different then stream sources or stream decorators. Both stream sources and stream decorators return streams of tuples. Stream evaluators are more like a traditional function that evaluates its parameters and returns an result. That result can be a single value, array, map or other structure.
Stream evaluators can be nested so that the output of an evaluator becomes the input for another evaluator.
Stream evaluators can be called in different contexts. For example a stream evaluator can be called on its own or it can be called within the context of a streaming expression.
abs
The abs function will return the absolute value of the provided single parameter. The abs function will fail to execute if the value is non-numeric. If a null value is found then null will be returned as the result.
abs Parameters
-
Field Name | Raw Number | Number Evaluator
abs Syntax
The expressions below show the various ways in which you can use the abs evaluator. Only one parameter is accepted. Returns a numeric value.
abs(1) // 1, not really a good use case for it
abs(-1) // 1, not really a good use case for it
abs(add(fieldA,fieldB)) // absolute value of fieldA + fieldB
abs(fieldA) // absolute value of fieldAacos
The acos function returns the trigonometric arccosine of a number.
acos Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the arccosine of.
acos Syntax
acos(100.4) // returns the arccosine of 100.4
acos(fieldA) // returns the arccosine for fieldA.
if(gt(fieldA,fieldB),sin(fieldA),sin(fieldB)) // if fieldA > fieldB then return the arccosine of fieldA, else return the arccosine of fieldBadd
The add function will take 2 or more numeric values and add them together. The add function will fail to execute if any of the values are non-numeric. If a null value is found then null will be returned as the result.
add Parameters
-
Field Name | Raw Number | Number Evaluator -
Field Name | Raw Number | Number Evaluator -
…… -
Field Name | Raw Number | Number Evaluator
add Syntax
The expressions below show the various ways in which you can use the add evaluator. The number and order of these parameters do not matter and is not limited except that at least two parameters are required. Returns a numeric value.
add(1,2,3,4) // 1 + 2 + 3 + 4 == 10
add(1,fieldA) // 1 + value of fieldA
add(fieldA,1.4) // value of fieldA + 1.4
add(fieldA,fieldB,fieldC) // value of fieldA + value of fieldB + value of fieldC
add(fieldA,div(fieldA,fieldB)) // value of fieldA + (value of fieldA / value of fieldB)
add(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA + fieldA, else fieldA + fieldBanalyze
The analyze function analyzes text using a Lucene/Solr analyzer and returns a list of tokens
emitted by the analyzer. The analyze function can be called on its own or within the
select and cartesianProduct streaming expressions.
analyze Parameters
-
Field Name|Raw Text: Either the field in a tuple or the raw text to be analyzed. -
Analyzer Field Name: The field name of the analyzer to use to analyze the text.
analyze Syntax
The expressions below show the various ways in which you can use the analyze evaluator.
-
Analyze the raw text:
analyze("hello world", analyzerField) -
Analyze a text field within a
selectexpression. This will annotate the tuples with output of the analyzer:select(expr, analyze(textField, analyzerField) as outField) -
Analyze a text field with a
cartesianProductexpression. This will stream each token emitted by the analyzer in its own tuple:cartesianProduct(expr, analyze(textField, analyzer) as outField)
and
The and function will return the logical AND of at least 2 boolean parameters. The function will fail to execute if any parameters are non-boolean or null. Returns a boolean value.
and Parameters
-
Field Name | Raw Boolean | Boolean Evaluator -
Field Name | Raw Boolean | Boolean Evaluator -
…… -
Field Name | Raw Boolean | Boolean Evaluator
and Syntax
The expressions below show the various ways in which you can use the and evaluator. At least two parameters are required, but there is no limit to how many you can use.
and(true,fieldA) // true && fieldA
and(fieldA,fieldB) // fieldA && fieldB
and(or(fieldA,fieldB),fieldC) // (fieldA || fieldB) && fieldC
and(fieldA,fieldB,fieldC,or(fieldD,fieldE),fieldF)anova
The anova function calculates the analysis of variance for two or more numeric arrays.
anova Parameters
-
numeric array… (two or more)
anova Syntax
anova(numericArray1, numericArray2) // calculates ANOVA for two numeric arrays
anova(numericArray1, numericArray2, numericArray2) // calculates ANOVA for three numeric arraysarray
The array function returns an array of numerics or other objects including other arrays.
array Parameters
-
numeric|array…
array Syntax
array(1, 2, 3) // Array of numerics
array(array(1,2,3), array(4,5,6)) // Array of arraysasin
The asin function returns the trigonometric arcsine of a number.
asin Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the arcsine of.
asin Syntax
asin(100.4) // returns the sine of 100.4
asine(fieldA) // returns the sine for fieldA.
if(gt(fieldA,fieldB),asin(fieldA),asin(fieldB)) // if fieldA > fieldB then return the asine of fieldA, else return the asine of fieldBatan
The atan function returns the trigonometric arctangent of a number.
atan Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the arctangent of.
atan Syntax
atan(100.4) // returns the arctangent of 100.4
atan(fieldA) // returns the arctangent for fieldA.
if(gt(fieldA,fieldB),atan(fieldA),atan(fieldB)) // if fieldA > fieldB then return the arctanget of fieldA, else return the arctangent of fieldBbetaDistribution
The betaDistribution function returns a beta probability distribution
based on its parameters. This function is part of the
probability distribution framework and is designed to work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
betaDistribution Parameters
-
double: shape1 -
double: shape2
betaDistribution Returns
A probability distribution function.
betaDistribution Syntax
betaDistribution(1, 5)binomialCoefficient
The binomialCoefficient function returns a Binomial Coefficient, the number of k-element subsets that can
be selected from an n-element set.
binomialCoefficient Parameters
-
integer: [n] set -
integer: [k] subset
binomialCoefficient Returns
A long value: The number of k-element subsets that can be selected from an n-element set.
binomialCoefficient Syntax
binomialCoefficient(8, 3) // Returns the number of 3 element subsets from an 8 element set.binomialDistribution
The binomialDistribution function returns a binomial probability distribution
based on its parameters. This function is part of the probability distribution framework and is designed to
work with the sample, probability and cumulativeProbability functions.
binomialDistribution Parameters
-
integer: number of trials -
double: probability of success
binomialDistribution Returns
A probability distribution function.
binomialDistribution Syntax
binomialDistribution(1000, .5)canberraDistance
The canberraDistance function calculates the Canberra distance of two numeric arrays.
canberraDistance Parameters
-
numeric array -
numeric array
canberraDistance Returns
A numeric.
canberraDistance Syntax
canberraDistance(numericArray1, numuericArray2))cbrt
The cbrt function returns the trigonometric cube root of a number.
cbrt Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the cube root of.
cbrt Syntax
cbrt(100.4) // returns the square root of 100.4
cbrt(fieldA) // returns the square root for fieldA.
if(gt(fieldA,fieldB),cbrt(fieldA),cbrt(fieldB)) // if fieldA > fieldB then return the cbrt of fieldA, else return the cbrt of fieldBceil
The ceil function rounds a decimal value to the next highest whole number.
ceil Parameters
-
Field Name | Raw Number | Number Evaluator: The decimal to round up.
ceil Syntax
The expressions below show the various ways in which you can use the ceil evaluator.
ceil(100.4) // returns 101.
ceil(fieldA) // returns the next highest whole number for fieldA.
if(gt(fieldA,fieldB),ceil(fieldA),ceil(fieldB)) // if fieldA > fieldB then return the ceil of fieldA, else return the ceil of fieldB.chebyshevDistance
The chebyshevDistance function calculates the Chebyshev distance of two numeric arrays.
chebyshevDistance Parameters
-
numeric array -
numeric array
chebyshevDistance Returns
A numeric.
chebyshevDistance Syntax
chebyshevDistance(numericArray1, numuericArray2))col
The col function returns a numeric array from a list of Tuples. The col
function is used to create numeric arrays from stream sources.
col Parameters
-
list of Tuples -
field name: The field to create the array from.
col Syntax
col(tupleList, fieldName)constantDistribution
The constantDistribution function returns a constant probability distribution based on its parameter.
This function is part of the probability distribution framework and is designed to
work with the sample and cumulativeProbability functions.
When sampled the constant distribution always returns its constant value.
constantDistribution Parameters
-
double: constant value
constantDistribution Returns
A probability distribution function.
constantDistribution Syntax
constantDistribution(constantValue)conv
The conv function returns the convolution of two numeric arrays.
conv Parameters
-
numeric array -
numeric array
conv Syntax
conv(numericArray1, numericArray2)copyOf
The copyOf function creates a copy of a numeric array.
copyOf Parameters
-
numeric array -
length: The length of the copied array. The returned array will be right padded with zeros if the length parameter exceeds the size of the original array.
copyOf Syntax
copyOf(numericArray, length)copyOfRange
The copyOfRange function creates a copy of a range of a numeric array.
copyOfRange Parameters
-
numeric array -
start index -
end index
copyOfRange Syntax
copyOfRange(numericArray, startIndex, endIndex)corr
The corr function returns the Pearson Product Moment Correlation of two numeric arrays.
corr Parameters
-
numeric array -
numeric array
corr Returns
A double between -1 and 1.
corr Syntax
corr(numericArray1, numericArray2)cos
The cos function returns the trigonometric cosine of a number.
cos Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the hyperbolic cosine of.
cos Syntax
cos(100.4) // returns the arccosine of 100.4
cos(fieldA) // returns the arccosine for fieldA.
if(gt(fieldA,fieldB),cos(fieldA),cos(fieldB)) // if fieldA > fieldB then return the arccosine of fieldA, else return the cosine of fieldBcosineSimilarity
The cosineSimilarity function returns the cosine similarity of two numeric arrays.
cosineSimilarity Parameters
-
numeric array -
numeric array
cosineSimilarity Returns
A numeric.
cosineSimilarity Syntax
cosineSimilarity(numericArray, numericArray)cov
The cov function returns the covariance of two numeric arrays.
cov Parameters
-
numeric array -
numeric array
cov Syntax
cov(numericArray, numericArray)cumulativeProbability
The cumulativeProbability function returns the cumulative probability of a random variable within a
probability distribution. The cumulative probability is the total probability of
all random variables less then or equal to a random variable.
cumulativeProbability Parameters
-
probability distribution -
number: Value to compute the probability for.
cumulativeProbability Returns
A double: the cumulative probability.
cumulativeProbability Syntax
cumulativeProbability(normalDistribution(500, 25), 502) // Returns the cumulative probability of the random sample 502 in a normal distribution with a mean of 500 and standard deviation of 25.describe
The describe function returns a tuple containing the descriptive statistics for an array.
describe Parameters
-
numeric array
describe Syntax
describe(numericArray)distance
The distance function calculates the Euclidian distance of two numeric arrays.
distance Parameters
-
numeric array -
numeric array
distance Syntax
distance(numericArray1, numuericArray2))div
The div function will take two numeric values and divide them. The function will fail to execute if any of the values are non-numeric or null, or the 2nd value is 0. Returns a numeric value.
div Parameters
-
Field Name | Raw Number | Number Evaluator -
Field Name | Raw Number | Number Evaluator
div Syntax
The expressions below show the various ways in which you can use the div evaluator. The first value will be divided by the second and as such the second cannot be 0.
div(1,2) // 1 / 2
div(1,fieldA) // 1 / fieldA
div(fieldA,1.4) // fieldA / 1.4
div(fieldA,add(fieldA,fieldB)) // fieldA / (fieldA + fieldB)dotProduct
The dotProduct function returns the dotproduct of a numeric array.
dotProduct Parameters
-
numeric array
dotProduct Returns
A number.
dotProduct Syntax
dotProduct(numericArray)earthMoversDistance
The earthMoversDistance function calculates the Earth Movers distance of two numeric arrays.
earthMoversDistance Parameters
-
numeric array -
numeric array
earthMoversDistance Returns
A numeric.
earthMoversDistance Syntax
earthMoversDistance(numericArray1, numericArray2))ebeAdd
The ebeAdd function performs an element-by-element addition of two numeric arrays.
ebeAdd Parameters
-
numeric array -
numeric array
ebeAdd Returns
A numeric array.
ebeAdd Syntax
ebeAdd(numericArray, numericArray)ebeDivide
The ebeDivide function performs an element-by-element division of two numeric arrays.
ebeDivide Parameters
-
numeric array -
numeric array
ebeDivide Returns
A numeric array.
ebeDivide Syntax
ebeDivide(numericArray, numericArray)ebeMultiple
The ebeMultiply function performs an element-by-element multiplication of two numeric arrays.
ebeMultiply Parameters
-
numeric array -
numeric array
ebeMultiply Returns
A numeric array.
ebeMultiply Syntax
ebeMultiply(numericArray, numericArray)ebeSubtract
The ebeSubtract function performs an element-by-element subtraction of two numeric arrays.
ebeSubtract Parameters
-
numeric array -
numeric array
ebeSubtract Returns
A numeric array.
ebeSubtract Syntax
ebeSubtract(numericArray, numericArray)empiricalDistribution
The empiricalDistribution function returns empirical distribution function, a continuous probability distribution function based
on an actual data set. This function is part of the probability distribution framework and is designed to work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
This function is designed to work with continuous data. To build a distribution from
a discrete data set use the enumeratedDistribution.
empiricalDistribution Parameters
-
numeric array: empirical observations
empiricalDistribution Returns
A probability distribution function.
empiricalDistribution Syntax
empiricalDistribution(numericArray)
enumeratedDistribution
The enumeratedDistribution function returns a discrete probability distribution function based
on an actual data set or a pre-defined set of data and probabilities.
This function is part of the probability distribution framework and is designed to
work with the sample, probability and cumulativeProbability functions.
The enumeratedDistribution can be called in two different scenarios:
1) Single array of discrete values. This works like an empirical distribution for discrete data.
2) An array of singleton discrete values and an array of double values representing the probabilities of the discrete values.
This function is designed to work with discrete data. To build a distribution from
a continuous data set use the empiricalDistribution.
enumeratedDistribution Parameters
-
integer array: discrete observations or singleton discrete values. -
double array: (Optional) values representing the probabilities of the singleton discrete values.
enumeratedDistribution Returns
A probability distribution function.
enumeratedDistribution Syntax
enumeratedDistribution(integerArray) // This creates an enumerated distribution from the observations in the numeric array.
enumeratedDistribution(array(1,2,3,4), array(.25,.25,.25,.25)) // This creates an enumerated distribution with four discrete values (1,2,3,4) each with a probability of .25.eor
The eor function will return the logical exclusive or of at least two boolean parameters. The function will fail to execute if any parameters are non-boolean or null. Returns a boolean value.
eor Parameters
-
Field Name | Raw Boolean | Boolean Evaluator -
Field Name | Raw Boolean | Boolean Evaluator -
…… -
Field Name | Raw Boolean | Boolean Evaluator
eor Syntax
The expressions below show the various ways in which you can use the eor evaluator. At least two parameters are required, but there is no limit to how many you can use.
eor(true,fieldA) // true iff fieldA is false
eor(fieldA,fieldB) // true iff either fieldA or fieldB is true but not both
eor(eq(fieldA,fieldB),eq(fieldC,fieldD)) // true iff either fieldA == fieldB or fieldC == fieldD but not botheq
The eq function will return whether all the parameters are equal, as per Java’s standard equals(…) function. The function accepts parameters of any type, but will fail to execute if all the parameters are not of the same type. That is, all are Boolean, all are String, or all are Numeric. If any any parameters are null and there is at least one parameter that is not null then false will be returned. Returns a boolean value.
eq Parameters
-
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator -
…… -
Field Name | Raw Value | Evaluator
eq Syntax
The expressions below show the various ways in which you can use the eq evaluator.
eq(1,2) // 1 == 2
eq(1,fieldA) // 1 == fieldA
eq(fieldA,val(foo)) fieldA == "foo"
eq(add(fieldA,fieldB),6) // fieldA + fieldB == 6expMovingAge
The expMovingAverage function computes an exponential moving average for a numeric array.
expMovingAge Parameters
-
numeric array: The array to compute the exponential moving average from. -
integer: window size
expMovingAvg Returns
A numeric array. The first element of the returned array will start from the windowSize-1 index of the original array.
expMovingAvg Syntax
expMovingAvg(numericArray, 5) //Computes an exponential moving average with a window size of 5.factorial
The factorial function returns the factorial of its parameter.
factorial Parameters
-
integer: The value to compute the factorial for. The largest supported value of this parameter is 170.
factorial Returns
A double.
factorial Syntax
factorial(100) //Computes the factorial of 100finddelay
The finddelay function performs a cross-correlation between two numeric arrays and returns the delay.
finddelay Parameters
-
numeric array -
numeric array
finddelay Syntax
finddelay(numericArray1, numericArray2)floor
The floor function rounds a decimal value to the next lowest whole number.
floor Parameters
-
Field Name | Raw Number | Number Evaluator: The decimal to round down.
floor Syntax
The expressions below show the various ways in which you can use the floor evaluator.
floor(100.4) // returns 100.
ceil(fieldA) // returns the next lowestt whole number for fieldA.
if(gt(fieldA,fieldB),floor(fieldA),floor(fieldB)) // if fieldA > fieldB then return the floor of fieldA, else return the floor of fieldB.freqTable
The freqTable function returns a frequency distribution from
an array of discrete values.
This function is designed to work with discrete values. To work with continuous data
use the hist function.
freqTable Parameters
-
integer array: The values to build the frequency distribution from.
freqTable Returns
A list of tuples containing the frequency information for each discrete value.
freqTable Syntax
freqTable(integerArray)gammaDistribution
The gammaDistribution function returns a gamma probability distribution based on its parameters. This function is part of the
probability distribution framework and is designed to work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
gammaDistribution Parameters
-
double: shape -
double: scale
gammaDistribution Returns
A probability distribution function,
gammaDistribution Syntax
gammaDistribution(1, 10)gt
The gt function will return whether the first parameter is greater than the second parameter. The function accepts numeric or string parameters, but will fail to execute if all the parameters are not of the same type. That is, all are String or all are Numeric. If any any parameters are null then an error will be raised. Returns a boolean value.
gt Parameters
-
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator
gt Syntax
The expressions below show the various ways in which you can use the gt evaluator.
gt(1,2) // 1 > 2
gt(1,fieldA) // 1 > fieldA
gt(fieldA,val(foo)) // fieldA > "foo"
gt(add(fieldA,fieldB),6) // fieldA + fieldB > 6gteq
The gteq function will return whether the first parameter is greater than or equal to the second parameter. The function accepts numeric and string parameters, but will fail to execute if all the parameters are not of the same type. That is, all are String or all are Numeric. If any any parameters are null then an error will be raised. Returns a boolean value.
gteq Parameters
-
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator
gteq Syntax
The expressions below show the various ways in which you can use the gteq evaluator.
gteq(1,2) // 1 >= 2
gteq(1,fieldA) // 1 >= fieldA
gteq(fieldA,val(foo)) fieldA >= "foo"
gteq(add(fieldA,fieldB),6) // fieldA + fieldB >= 6hist
The hist function creates a histogram from a numeric array. The hist function is designed
to work with continuous variables.
hist Parameters
-
numeric array -
bins: The number of bins in the histogram. Each returned tuple contains summary statistics for the observations that were within the bin.
hist Syntax
hist(numericArray, bins)hsin
The hsin function returns the trigonometric hyperbolic sine of a number.
hsin Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the hyperbolic sine of.
hsin Syntax
hsin(100.4) // returns the hsine of 100.4
hsin(fieldA) // returns the hsine for fieldA.
if(gt(fieldA,fieldB),sin(fieldA),sin(fieldB)) // if fieldA > fieldB then return the hsine of fieldA, else return the hsine of fieldBif
The if function works like a standard conditional if/then statement. If the first parameter is true, then the second parameter will be returned, else the third parameter will be returned. The function accepts a boolean as the first parameter and anything as the second and third parameters. An error will occur if the first parameter is not a boolean or is null.
if Parameters
-
Field Name | Raw Value | Boolean Evaluator -
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator
if Syntax
The expressions below show the various ways in which you can use the if evaluator.
if(fieldA,fieldB,fieldC) // if fieldA is true then fieldB else fieldC
if(gt(fieldA,5), fieldA, 5) // if fieldA > 5 then fieldA else 5
if(eq(fieldB,null), null, div(fieldA,fieldB)) // if fieldB is null then null else fieldA / fieldBkendallsCorr
The kendallsCorr function returns the Kendall’s Tau-b Rank Correlation of two numeric arrays.
kendallsCorr Parameters
-
numeric array -
numeric array
kendalsCorr Returns
A double between -1 and 1.
kendalsCorr Syntax
kendallsCorr(numericArray1, numericArray2)length
The length function returns the length of a numeric array.
length Parameters
-
numeric array
length Syntax
length(numericArray)log
The log function will return the natural log of the provided single parameter. The log function will fail to execute if the value is non-numeric. If a null value is found, then null will be returned as the result.
log Parameters
-
Field Name | Raw Number | Number Evaluator
log Syntax
The expressions below show the various ways in which you can use the log evaluator. Only one parameter is accepted. Returns a numeric value.
log(100)
log(add(fieldA,fieldB))
log(fieldA)logNormalDistribution
The logNormalDistribution function returns a log normal probability distribution based on its parameters. This function is part of the probability distribution framework and is designed to
work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
logNormalDistribution Parameters
-
double: shape -
double: scale
logNormalDistribution Returns
A probability distribution function.
logNormalDistribution Syntax
logNormalDistribution(.3, .0)kolmogorovSmirnov
The kolmogorovSmirnov function performs a Kolmogorov Smirnov test,
between a reference continuous probability distribution and a sample set.
The supported distribution functions are: empiricalDistribution, normalDistribution, logNormalDistribution, weibullDistribution, gammaDistribution, and betaDistribution.
kolmogorovSmirnov Parameters
-
continuous probability distribution: Reference distribution -
numeric array: sample set
kolmogorovSmirnov Returns
result tuple : A tuple containing the p-value and d-statistic for the test result.
kolmogorovSmirnov Syntax
kolmogorovSmirnov(normalDistribution(10, 2), sampleSet)lt
The lt function will return whether the first parameter is less than the second parameter. The function accepts numeric or string parameters, but will fail to execute if all the parameters are not of the same type. That is, all are String or all are Numeric. If any any parameters are null then an error will be raised. Returns a boolean value.
lt Parameters
-
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator
lt Syntax
The expressions below show the various ways in which you can use the lt evaluator.
lt(1,2) // 1 < 2
lt(1,fieldA) // 1 < fieldA
lt(fieldA,val(foo)) fieldA < "foo"
lt(add(fieldA,fieldB),6) // fieldA + fieldB < 6lteq
The lteq function will return whether the first parameter is less than or equal to the second parameter. The function accepts numeric and string parameters, but will fail to execute if all the parameters are not of the same type. That is, all are String or all are Numeric. If any any parameters are null then an error will be raised. Returns a boolean value.
lteq Parameters
-
Field Name | Raw Value | Evaluator -
Field Name | Raw Value | Evaluator
lteq Syntax
The expressions below show the various ways in which you can use the lteq evaluator.
lteq(1,2) // 1 <= 2
lteq(1,fieldA) // 1 <= fieldA
lteq(fieldA,val(foo)) fieldA <= "foo"
lteq(add(fieldA,fieldB),6) // fieldA + fieldB <= 6manhattanDistance
The manhattanDistance function calculates the Manhattan distance of two numeric arrays.
manhattanDistance Parameters
-
numeric array -
numeric array
manhattanDistance Returns
A numeric.
manhattanDistance Syntax
manhattanDistance(numericArray1, numuericArray2))meanDifference
The meanDifference function calculates the mean of the differences following the element-by-element subtraction between two numeric arrays.
meanDifference Parameters
-
numeric array -
numeric array
meanDifference Returns
A numeric.
meanDifference Syntax
meanDifference(numericArray, numericArray)mod
The mod function returns the remainder (modulo) of the first parameter divided by the second parameter.
mod Parameters
-
Field Name | Raw Number | Number Evaluator: Parameter 1 -
Field Name | Raw Number | Number Evaluator: Parameter 2
mod Syntax
The expressions below show the various ways in which you can use the mod evaluator.
mod(100,3) // returns the remainder of 100 / 3 .
mod(100,fieldA) // returns the remainder of 100 divided by the value of fieldA.
mod(fieldA,1.4) // returns the remainder of fieldA divided by 1.4.
if(gt(fieldA,fieldB),mod(fieldA,fieldB),mod(fieldB,fieldA)) // if fieldA > fieldB then return the remainder of fieldA/fieldB, else return the remainder of fieldB/fieldA.monteCarlo
The monteCarlo function performs a Monte Carlo simulation (https://en.wikipedia.org/wiki/Monte_Carlo_method)
based on its parameters. The monteCarlo function runs another function a specified number of times and returns the results.
The function being run typically has one or more variables that are drawn from probability
distributions on each run. The sample function is used in the function to draw the samples.
The simulation’s result array can then be treated as an empirical distribution to understand the probabilities of the simulation results.
monteCarlo Parameters
-
numeric function: The function being run by the simulation, which must return a numeric value. -
integer: The number of times to run the function.
monteCarlo Returns
A numeric array: The results of simulation runs.
monteCarlo Syntax
let(a=uniformIntegerDistribution(1, 6),
b=uniformIntegerDistribution(1, 6),
c=monteCarlo(add(sample(a), sample(b)), 1000))In the expression above the monteCarlo function is running the function add(sample(a), sample(b))
1000 times and returning the result. Each time the function is run samples are drawn from the
probability distributions stored in variables a and b.
movingAvg
The movingAvg function calculates a moving average over an array of numbers.
movingAvg Parameters
-
numeric array -
window size
movingAvg Returns
A numeric array. The first element of the returned array will start from the windowSize-1 index of the original array.
movingAvg Syntax
movingAverage(numericArray, 30)movingMedian
The movingMedian function calculates a moving median over an array of numbers.
movingMedian Parameters
-
numeric array -
window size
movingMedian Returns
A numeric array. The first element of the returned array will start from the windowSize-1 index of the original array.
movingMedian Syntax
movingMedian(numericArray, 30)mult
The mult function will take two or more numeric values and multiply them together. The mult function will fail to execute if any of the values are non-numeric. If a null value is found then null will be returned as the result.
mult Parameters
-
Field Name | Raw Number | Number Evaluator -
Field Name | Raw Number | Number Evaluator -
…… -
Field Name | Raw Number | Number Evaluator
mult Syntax
The expressions below show the various ways in which you can use the mult evaluator. The number and order of these parameters do not matter and is not limited except that at least two parameters are required. Returns a numeric value.
mult(1,2,3,4) // 1 * 2 * 3 * 4
mult(1,fieldA) // 1 * value of fieldA
mult(fieldA,1.4) // value of fieldA * 1.4
mult(fieldA,fieldB,fieldC) // value of fieldA * value of fieldB * value of fieldC
mult(fieldA,div(fieldA,fieldB)) // value of fieldA * (value of fieldA / value of fieldB)
mult(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA * fieldA, else fieldA * fieldBnormalDistribution
The normalDistribution function returns a normal probability distribution
based on its parameters. This function is part of the probability distribution framework and is designed to
work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
normalDistribution Parameters
-
double: mean -
double: standard deviation
normalDistribution Returns
A probability distribution function.
normalDistribution Syntax
normalDistribution(mean, stddev)normalize
The normalize function normalizes a numeric array so that values within the array
have a mean of 0 and standard deviation of 1.
normalize Parameters
-
numeric array
normalize Syntax
normalize(numericArray)not
The not function will return the logical NOT of a single boolean parameter. The function will fail to execute if the parameter is non-boolean or null. Returns a boolean value.
not Parameters
-
Field Name | Raw Boolean | Boolean Evaluator
not Syntax
The expressions below show the various ways in which you can use the not evaluator. Only one parameter is allowed.
not(true) // false
not(fieldA) // true if fieldA is false else false
not(eq(fieldA,fieldB)) // true if fieldA != fieldBor
The or function will return the logical OR of at least 2 boolean parameters. The function will fail to execute if any parameters are non-boolean or null. Returns a boolean value.
or Parameters
-
Field Name | Raw Boolean | Boolean Evaluator -
Field Name | Raw Boolean | Boolean Evaluator -
…… -
Field Name | Raw Boolean | Boolean Evaluator
or Syntax
The expressions below show the various ways in which you can use the or evaluator. At least two parameters are required, but there is no limit to how many you can use.
or(true,fieldA) // true || fieldA
or(fieldA,fieldB) // fieldA || fieldB
or(and(fieldA,fieldB),fieldC) // (fieldA && fieldB) || fieldC
or(fieldA,fieldB,fieldC,and(fieldD,fieldE),fieldF)poissonDistribution
The poissonDistribution function returns a poisson probability distribution
based on its parameter. This function is part of the probability distribution framework and is designed to
work with the sample, probability and cumulativeProbability functions.
poissonDistribution Parameters
-
double: mean
poissonDistribution Returns
A probability distribution function.
poissonDistribution Syntax
poissonDistribution(mean)polyFit
The polyFit function performs polynomial curve fitting.
polyFit Parameters
-
numeric array: (Optional) x values. If omitted a sequence will be created for the x values. -
numeric array: y values -
integer: (Optional) polynomial degree. Defaults to 3.
polyFit Returns
A numeric array: curve that was fit to the data points.
polyFit Syntax
polyFit(yValues) // This creates the xValues automatically and fits a curve through the data points using the default 3 degree polynomial.
polyFit(yValues, 5) // This creates the xValues automatically and fits a curve through the data points using a 5 degree polynomial.
polyFit(xValues, yValues, 5) // This will fit a curve through the data points using a 5 degree polynomial.polyfitDerivative
The polyfitDerivative function returns the derivative of the curve created by the polynomial curve fitter.
polyfitDerivative Parameters
-
numeric array: (Optional) x values. If omitted a sequence will be created for the x values. -
numeric array: y values -
integer: (Optional) polynomial degree. Defaults to 3.
polyfitDerivative Returns
A numeric array: The curve for the derivative created by the polynomial curve fitter.
polyfitDerivative Syntax
polyfitDerivative(yValues) // This creates the xValues automatically and returns the polyfit derivative
polyfitDerivative(yValues, 5) // This creates the xValues automatically and fits a curve through the data points using a 5 degree polynomial and returns the polyfit derivative.
polyfitDerivative(xValues, yValues, 5) // This will fit a curve through the data points using a 5 degree polynomial and returns the polyfit derivative.pow
The pow function returns the value of its first parameter raised to the power of its second parameter.
pow Parameters
-
Field Name | Raw Number | Number Evaluator: Parameter 1 -
Field Name | Raw Number | Number Evaluator: Parameter 2
pow Syntax
The expressions below show the various ways in which you can use the pow evaluator.
pow(2,3) // returns 2 raised to the 3rd power.
pow(4,fieldA) // returns 4 raised by the value of fieldA.
pow(fieldA,1.4) // returns the value of fieldA raised by 1.4.
if(gt(fieldA,fieldB),pow(fieldA,fieldB),pow(fieldB,fieldA)) // if fieldA > fieldB then raise fieldA by fieldB, else raise fieldB by fieldA.predict
The predict function predicts the value of an dependent variable based on
the output of the regress function.
predict Parameters
-
regress output -
numeric predictor
predict Syntax
predict(regressOutput, predictor)primes
The primes function returns an array of prime numbers starting from a specified number.
primes Parameters
-
integer: The number of primes to return in the list -
integer: The starting point for returning the primes
primes Returns
A numeric array.
primes Syntax
primes(100, 2000) // returns 100 primes starting from 2000probability
The probability function returns the probability of a random variable within a discrete probability distribution.
probability Parameters
-
discrete probability distribution: poissonDistribution | binomialDistribution | uniformDistribution | enumeratedDistribution -
integer: Value of the random variable to compute the probability for.
probability Returns
A double: the probability.
probability Syntax
probability(poissonDistribution(10), 7) // Returns the probability of a random sample of 7 in a poisson distribution with a mean of 10.rank
The rank performs a rank transformation on a numeric array.
rank Parameters
-
numeric array
rank Syntax
rank(numericArray)raw
The raw function will return whatever raw value is the parameter. This is useful for cases where you want to use a string as part of another evaluator.
raw Parameters
-
Raw Value
raw Syntax
The expressions below show the various ways in which you can use the raw evaluator. Whatever is inside will be returned as-is. Internal evaluators are considered strings and are not evaluated.
raw(foo) // "foo"
raw(count(*)) // "count(*)"
raw(45) // 45
raw(true) // "true" (note: this returns the string "true" and not the boolean true)
eq(raw(fieldA), fieldA) // true if the value of fieldA equals the string "fieldA"regress
residuals
The residuals function takes three parameters: a simple regression model, an array of predictor values
and an array of actual values. The residuals function applies the simple regression model to the
array of predictor values and computes a predictions array. The predicted values array is then
subtracted from the actual value array to compute the residuals array.
residuals Parameters
-
regress output -
numeric array: The array of predictor values -
numeric array: The array of actual values
residuals Returns
A numeric array of residuals.
residuals Syntax
residuals(regressOutput, numericArray, numericArray)rev
The rev function reverses the order of a numeric array.
rev Parameters
-
numeric array
rev Syntax
rev(numericArray)round
The round function returns the closest whole number to the argument.
round Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the square root of.
round Syntax
round(100.4)
round(fieldA)
if(gt(fieldA,fieldB),sqrt(fieldA),sqrt(fieldB)) // if fieldA > fieldB then return the round of fieldA, else return the round of fieldBsample
The sample function can be used to draw random samples from a probability distribution.
sample Parameters
-
probability distribution: The distribution to sample. -
integer: (Optional) Sample size. Defaults to 1.
sample Returns
Either a single numeric random sample, or a numeric array depending on the sample size parameter.
sample Syntax
sample(poissonDistribution(5)) // Returns a single random sample from a poissonDistribution with mean of 5.
sample(poissonDistribution(5), 1000) // Returns 1000 random samples from poissonDistribution with a mean of 5.scale
The scale function multiplies all the elements of an array by a number.
scale Parameters
-
number -
numeric array
scale Syntax
scale(number, numericArray)sequence
The sequence function returns an array of numbers based on its parameters.
sequence Parameters
-
length -
start -
stride
sequence Syntax
sequence(100, 0, 1) // Returns a sequence of length 100, starting from 0 with a stride of 1.sin
The sin function returns the trigonometric sine of a number.
sin Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the sine of.
sin Syntax
sin(100.4) // returns the sine of 100.4
sine(fieldA) // returns the sine for fieldA.
if(gt(fieldA,fieldB),sin(fieldA),sin(fieldB)) // if fieldA > fieldB then return the sine of fieldA, else return the sine of fieldBspearmansCorr
The spearmansCorr function returns the Spearmans Rank Correlation of two numeric arrays.
spearmansCorr Parameters
-
numeric array -
numeric array
spearmansCorr Returns
A double between -1 and 1.
spearmansCorr Syntax
spearmansCorr(numericArray1, numericArray2)sqrt
The sqrt function returns the trigonometric square root of a number.
sqrt Parameters
-
Field Name | Raw Number | Number Evaluator: The value to return the square root of.
sqrt Syntax
sqrt(100.4) // returns the square root of 100.4
sqrt(fieldA) // returns the square root for fieldA.
if(gt(fieldA,fieldB),sqrt(fieldA),sqrt(fieldB)) // if fieldA > fieldB then return the sqrt of fieldA, else return the sqrt of fieldBsub
The sub function will take 2 or more numeric values and subtract them, from left to right. The sub function will fail to execute if any of the values are non-numeric. If a null value is found then null will be returned as the result.
sub Parameters
-
Field Name | Raw Number | Number Evaluator -
Field Name | Raw Number | Number Evaluator -
…… -
Field Name | Raw Number | Number Evaluator
sub Syntax
The expressions below show the various ways in which you can use the sub evaluator. The number of these parameters does not matter and is not limited except that at least two parameters are required. Returns a numeric value.
sub(1,2,3,4) // 1 - 2 - 3 - 4
sub(1,fieldA) // 1 - value of fieldA
sub(fieldA,1.4) // value of fieldA - 1.4
sub(fieldA,fieldB,fieldC) // value of fieldA - value of fieldB - value of fieldC
sub(fieldA,div(fieldA,fieldB)) // value of fieldA - (value of fieldA / value of fieldB)
if(gt(fieldA,fieldB),sub(fieldA,fieldB),sub(fieldB,fieldA)) // if fieldA > fieldB then fieldA - fieldB, else fieldB - fieldsumDifference
The sumDifference function calculates the sum of the differences following an element-by-element subtraction between two numeric arrays.
sumDifference Parameters
-
numeric array -
numeric array
sumDifference Returns
A numeric.
sumDifference Syntax
sumDifference(numericArray, numericArray)uniformDistribution
The uniformDistribution function returns a continuous uniform probability distribution
based on its parameters. See the uniformIntegerDistribution to work with discrete uniform distributions. This function is part of the
probability distribution framework and is designed to work with the sample and cumulativeProbability functions.
uniforDistribution Parameters
-
double: start -
double: end
uniformDistribution Returns
A probability distribution function.
uniformDistribution Syntax
uniformDistribution(0.0, 100.0)uniformIntegerDistribution
The uniformIntegerDistribution function returns a discrete uniform probability distribution
based on its parameters. See the uniformDistribution to work with continuous uniform distributions. This function is part of the
probability distribution framework and is designed to work with the sample, probability and cumulativeProbability functions.
uniformIntegerDistribution Parameters
-
integer: start -
integer: end
uniformIntegerDistribution Returns
A probability distribution function.
uniformIntegerDistribution Syntax
uniformDistribution(1, 6)weibullDistribution
The weibullDistribution function returns a Weibull probability distribution
based on its parameters. This function is part of the
probability distribution framework and is designed to work with the sample, kolmogorovSmirnov and cumulativeProbability functions.
weibullDistribution Parameters
-
double: shape -
double: scale
weibullDistribution Returns
A probability distribution function.
weibullDistribution Syntax
weibullDistribution(.5, 10)zipFDistribution
The zipFDistribution function returns a ZipF distribution
based on its parameters. This function is part of the
probability distribution framework and is designed to work with the sample,
probability and cumulativeProbability functions.
zipFDistribution Parameters
-
integer: size -
double: exponent
zipFDistribution Returns
A probability distribution function.
zipFDistribution Syntax
zipFDistribution(5000, 1.0)
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