mirror of https://github.com/apache/lucene.git
SOLR-11947: Work in progress
This commit is contained in:
Joel Bernstein
parent
35cf4f6b31
commit
cb88bdbee2
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@ -92,6 +92,8 @@ add(fieldA,div(fieldA,fieldB)) // value of fieldA + (value of fieldA / value of
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add(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA + fieldA, else fieldA + fieldB
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----
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== akima (TODO)
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== analyze
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The `analyze` function analyzes text using a Lucene/Solr analyzer and returns a list of tokens
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@ -273,6 +275,7 @@ cbrt(fieldA) // returns the square root for fieldA.
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if(gt(fieldA,fieldB),cbrt(fieldA),cbrt(fieldB)) // if fieldA > fieldB then return the cbrt of fieldA, else return the cbrt of fieldB
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----
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== ceil
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The `ceil` function rounds a decimal value to the next highest whole number.
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@ -291,6 +294,9 @@ ceil(fieldA) // returns the next highest whole number for fieldA.
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if(gt(fieldA,fieldB),ceil(fieldA),ceil(fieldB)) // if fieldA > fieldB then return the ceil of fieldA, else return the ceil of fieldB.
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----
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== chiSquareDataSet (TODO)
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== col
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The `col` function returns a numeric array from a list of Tuples. The `col`
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@ -308,6 +314,41 @@ function is used to create numeric arrays from stream sources.
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[source,text]
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col(tupleList, fieldName)
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== colAt
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The `colAt` function returns the column of a matrix at a specific index as a numeric array.
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=== colAt Parameters
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* `matrix`: the matrix to operate on
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* `integer`: the index of the column to return
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=== colAt Syntax
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[source,text]
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colAt(matrix, 10)
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=== colAt Returns
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numeric array : the column of the matrix
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== columnCount
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The `columnCount` function returns the number of columns in a `matrix`.
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=== columnCount Parameters
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* `matrix`: the matrix to operate on
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=== columnCount Syntax
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[source,text]
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columnCount(matrix)
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=== columnCount Returns
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integer : number columns in the matrix.
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== constantDistribution
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The `constantDistribution` function returns a constant probability distribution based on its parameter.
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@ -483,6 +524,10 @@ A double: the cumulative probability.
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[source,text]
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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.
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== density (TODO)
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== derivative
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The `derivative` function returns the https://en.wikipedia.org/wiki/Derivative[derivative] of a function. The derivative function
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@ -491,7 +536,7 @@ take the derivative of a derivative.
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=== derivative Parameters
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* `spline` | `loess` | `derivative`: The functions to compute the derivative for.
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* `spline` | `loess` | `akima` | `lerp` | `derivative`: The functions to compute the derivative for.
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=== derivative Syntax
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@ -815,6 +860,9 @@ A double.
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factorial(100) //Computes the factorial of 100
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----
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== featureSelect (TODO)
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== finddelay
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The `finddelay` function performs a cross-correlation between two numeric arrays and returns the delay.
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@ -870,23 +918,7 @@ A list of tuples containing the frequency information for each discrete value.
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freqTable(integerArray)
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----
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== geometricDistribution
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The `geometricDistribution` function returns a https://en.wikipedia.org/wiki/Geometric_distribution[geometric probability distribution] based on its parameters. This function is part of the
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probability distribution framework and is designed to work with the <<sample>>, <<probability>> and <<cumulativeProbability>> functions.
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=== geometricDistribution Parameters
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* `double`: probability
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=== geometricDistribution Syntax
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[source,text]
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geometricDistribution(.5) // Creates a geometric distribution with probability of .5
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=== geometricDistribution Returns
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A probability distribution function
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== fuzzyKmeans (TODO)
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== gammaDistribution
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@ -907,6 +939,105 @@ A probability distribution function,
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[source,text]
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gammaDistribution(1, 10)
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== geometricDistribution
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The `geometricDistribution` function returns a https://en.wikipedia.org/wiki/Geometric_distribution[geometric probability distribution] based on its parameters. This function is part of the
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probability distribution framework and is designed to work with the <<sample>>, <<probability>> and <<cumulativeProbability>> functions.
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=== geometricDistribution Parameters
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* `double`: probability
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=== geometricDistribution Syntax
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[source,text]
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geometricDistribution(.5) // Creates a geometric distribution with probability of .5
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=== geometricDistribution Returns
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A probability distribution function
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== getAttribute
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The `getAttribute` function returns an attribute from a `matrix` by its key. Any function that returns a `matrix` can
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also set attributes on the `matrix` with additional information. The `<<setAttribute>>` function can also be used
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to set attributes on a `matrix`. The key to an attribute is always a string. The value of attribute can be any object
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including numerics, arrays, maps, matrixes etc...
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=== getAttribute Parameters
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* `matrix` : The matrix to set the attribute on
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* `string` : The key for the attribute
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=== getAttribute Syntax
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[source,text]
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getAttribute(matrix, key)
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=== getAttribute Returns
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object : any object
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== getAttributes
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The `getAttributes` function returns the attribute map from matrix. See the `getAttribute` function for more details
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on attributes.
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=== getAttributes Parameters
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* `matrix` : The matrix to retrieve the attribute map from.
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=== getAttributes Syntax:
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[source,text]
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getAttributes(matrix)
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=== getAttributes Returns
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map : The map of attributes.
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== getCentroids (TODO)
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== getClusters (TODO)
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== getColumnLabels
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The `getColumnLabels` function returns the columns labels of a matrix. The column labels can be optionally
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set by any function that returns a matrix. The column labels can also be set via the `setColumnLabels` function.
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=== getColumnLabels Parameters
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* `matrix`: The matrix to return the column labels of.
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=== getColumnLabels Syntax
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getColumnLabels(matrix)
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=== getColumnLabels Returns
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string array : The labels for each column in the matrix
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== getMembershipMatrix (TODO)
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== getRowLabels
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The `getRowLabels` function returns the row labels of a matrix. The row labels can be optionally
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set by any function that returns a matrix. The row labels can also be set via the `setRowLabels` function.
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=== getRowLabels Parameters
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* `matrix`: The matrix to return the row labels from.
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=== getRowLabels Syntax
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getRowLabels(matrix)
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=== getRowLabels Returns
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string array : The labels for each row in the matrix
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== grandSum
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The `grandSum` function sums all the values in a matrix.
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@ -1020,6 +1151,43 @@ if(gt(fieldA,5), fieldA, 5) // if fieldA > 5 then fieldA else 5
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if(eq(fieldB,null), null, div(fieldA,fieldB)) // if fieldB is null then null else fieldA / fieldB
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----
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== indexOf
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The `indexOf` function returns the index of a string in an array of strings.
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=== indexOf Parameters
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* `string array` : The array to operate on.
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* `string` : The string to search for in the array.
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=== indexOf Syntax
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[source,text]
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indexOf(stringArray, string)
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=== indexOf Returns
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integer : The index of the string in the array or -1 if the string is not found.
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== integrate
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The `integrate` function computes the integral of an interpolation function for a specific range of the curve.
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=== integrate Parameters
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* `spline` | `akima` | `lerp` | `loess` : The interpolation function to compute the integral for.
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* `numeric` : start of integral range
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* `numeric` : end of integral range
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=== integrate Syntax
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[source,text]
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integrate(function, start, end)
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=== integrate Returns
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numeric : The integral
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== length
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The `length` function returns the length of a numeric array.
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@ -1034,6 +1202,8 @@ The `length` function returns the length of a numeric array.
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[source,text]
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length(numericArray)
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== lerp (TOD0)
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== loess
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The `leoss` function is a smoothing curve fitter which uses a https://en.wikipedia.org/wiki/Local_regression[local regression] algorithm.
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@ -1100,6 +1270,10 @@ A probability distribution function.
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[source,text]
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logNormalDistribution(.3, .0)
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== kmeans (TODO)
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== knn (TODO)
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== kolmogorovSmirnov
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The `kolmogorovSmirnov` function performs a https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test[Kolmogorov Smirnov test],
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@ -1163,6 +1337,9 @@ lteq(fieldA,val(foo)) fieldA <= "foo"
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lteq(add(fieldA,fieldB),6) // fieldA + fieldB <= 6
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----
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== mannWhitney (TODO)
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== markovChain
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The `markovChain` function can be used to perform https://en.wikipedia.org/wiki/Markov_chain[Markov Chain] simulations.
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@ -1357,6 +1534,11 @@ mult(fieldA,div(fieldA,fieldB)) // value of fieldA * (value of fieldA / value of
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mult(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA * fieldA, else fieldA * fieldB
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----
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== multiKmeans (TODO)
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== multiVariateNormalDistribution (TODO)
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== normalDistribution
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The `normalDistribution` function returns a https://en.wikipedia.org/wiki/Normal_distribution[normal probability distribution]
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@ -1463,6 +1645,8 @@ or(and(fieldA,fieldB),fieldC) // (fieldA && fieldB) || fieldC
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or(fieldA,fieldB,fieldC,and(fieldD,fieldE),fieldF)
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----
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== pairedTtest (TODO)
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== poissonDistribution
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The `poissonDistribution` function returns a https://en.wikipedia.org/wiki/Poisson_distribution[poisson probability distribution]
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@ -1691,6 +1875,41 @@ round(fieldA)
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if(gt(fieldA,fieldB),sqrt(fieldA),sqrt(fieldB)) // if fieldA > fieldB then return the round of fieldA, else return the round of fieldB
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----
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== rowAt
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The `rowAt` function returns the row of a matrix at a specific index as a numeric array.
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=== rowAt Parameters
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* `matrix`: the matrix to operate on
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* `integer`: the index of the row to return
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=== rowAt Syntax
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[source,text]
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rowAt(matrix, 10)
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=== rowAt Returns
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numeric array : the row of the matrix
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== rowCount
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The `rowCount` function returns the number of rows in a `matrix`.
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=== rowCount Parameters
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* `matrix`: the matrix to operate on
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=== rowCount Syntax
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[source,text]
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rowCount(matrix)
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=== rowCount Returns
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integer : number rows in the matrix.
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== sample
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The `sample` function can be used to draw random samples from a probability distribution or Markov Chain.
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@ -1826,7 +2045,60 @@ The `sequence` function returns an array of numbers based on its parameters.
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[source,text]
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sequence(100, 0, 1) // Returns a sequence of length 100, starting from 0 with a stride of 1.
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== setAttributes
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The `setAttributes` function sets an attributes map of a `matrix`.
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=== setAttributes Parameters
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* `matrix` : The matrix to set the attributes map to.
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* `map` : The map of attributes to set on the matrix.
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=== setAttributes Syntax
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[source,text]
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setAttributes(matrix, map)
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=== setAttributes Returns
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matrix : The matrix with the attributes set.
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== setColumnLabels
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The `setColumnLabels` function sets the columns labels of a matrix.
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=== setColumnLabels Parameters
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* `matrix`: The matrix to set the column labels to.
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* `string array` : The column labels to set the matrix
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=== setColumnLabels Syntax
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setColumnLabels(matrix, labels)
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=== setColumnLabels Returns
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matrix : The matrix with the labels set.
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== setRowLabels
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The `setRowLabels` function sets the row labels of a matrix.
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=== setRowLabels Parameters
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* `matrix`: The matrix to set the row labels to.
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* `string array` : The row labels to set to the matrix
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=== setRowLabels Syntax
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setRowLabels(matrix, labels)
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=== setRowLabels Returns
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matrix : The matrix with the labels set.
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== sin
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The `sin` function returns the trigonometric sine of a number.
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=== sin Parameters
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@ -1979,6 +2251,27 @@ sumRows(matrix)
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numeric array: sum of the rows.
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== sumSq
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The `sumSq` function returns the sum-of-squares of the values in a numeric array.
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=== sumSq Parameters
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* `numeric array` : The numeric array to compute the sumSq of.
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=== sumSq Syntac
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[source,text]
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sumSq(numericArray)
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=== sumSq Returns
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numeric : result of the sumSq calculation
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== termVectors (TODO)
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== topFeatures (TODO)
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== transpose
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The `transpose` function https://en.wikipedia.org/wiki/Transpose[transposes] a matrix .
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@ -2017,6 +2310,8 @@ triangularDistribution(10, 15, 20) // A triangular distribution with a low value
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Probability distribution function
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== ttest (TODO)
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== uniformDistribution
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The `uniformDistribution` function returns a https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)[continuous uniform probability distribution]
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