Note
We are actively expanding the set of operators and are keen to receive feature requests for new operators. Are you missing an operator? Let us know by providing

  • a (short) example exercise
  • description of the input and output of the operator
  • Operator name suggestion

We will quickly get back to you whether we can implement such an operator.

List of operators

We currently support the following operators in parameter definitions:

Basic operators

  • Random: Generate a random number between two bounds
  • Range:  Generate a random number between two bounds, with a specified step
  • Formula: Perform an arbitrary expression calculation
  • Select: Extract a value from a list / matrix
  • Unique: Return all unique values of the input list
  • Length: Return the length of the input list

Calculus

  • Imaginair part: Extract the Imaginair part of an expression
  • Real part: Extract the real part of an expression
  • Integral: Evaluate the integral of an expression
  • Derivative: Evaluate the derivative of an expression
  • Limit: Calculate the limit of an expression
  • Substitute: Substitute variables in an expression

Linear Algebra

  • Determinant: Calculate the determinant of a matrix
  • Column space: Calculate the column-space of a matrix
  • Null space: Calculate the null-space of a matrix
  • Rank: Calculate the rank of a matrix
  • Transpose: Transpose a matrix
  • RREF: Calculate the Row Reduced Echelon Form of a matrix
  • EigenValues: Calculate the Eigenvalues of a matrix
  • EigenVectors: Calculate the Eigenvectors of a matrix
  • Shape: Calculates the shape of a matrix
  • Diagonalize: Calculates the P and D matrices of an input matrix

Statistics

  • Dataset: Upload a dataset to the platform
  • Sample: Sample rows from a given dataset
  • Correlation: Calculates the correlation between two lists of numeric values
  • Linear Regression: Perform Ordinary least squares linear regression

Detailed descriptions

Random

Input: 

  • min: minimal value for the range
  • max: maximum value for the range
  • decimals: number of decimals to round the answer to

Output: A value between min and max rounded to decimals numbers

Range

Input: 

  • min: minimal value for the range
  • step: the step-size between min and max
  • max: maximum value for the range

Output: A value out of the set [min, min+1*step_size, min+2*stepsize, ..., min+n*stepsize, max] 

Formula

Input: 

  • formula: any formula expression
  • decimals: number of decimals to round the answer to

Output: The results of evaluating and simplifying the formula, optionally rounded to decimals places

Select

Input: 

  • value: any formula expression resulting in a Matrix, Vector, list or Dataset
  • first index selector: a selector for the first dimension to select (see comments below)
  • second index selector: a selector for the second dimension to select (see comments below). This selector is only used of the value has more than 1 dimension.

Output: The value of the selected dimensions. Depending on the input this can be a list, a matrix, a vector, or a single value.

Index selectors are either

  • a single index value (starting the count at 1)
  • a list of index values separated by a comma (e.g. "[1,3]")
  • a ':' to represent the whole range
  • a range in the form of "range_start:range_end" where the "range_end" can be negative which is a short-hand notation for counting back from length (e.g. "1:4" or "2:-1")

Unique

Input: Any formula expression resulting in a list

Output: A list containing all unique values of the input list

Length

Input: Any formula expression resulting in a list

Output: The number of items in the input list

Imaginair part

Input: Any formula expression

Output: The imaginary part of the expression

For more details on the implementation see the underlying function documentation.

Real part

Input: Any formula expression

Output: The real part of the expression

For more details on the implementation see the underlying function documentation.

Integral

Input: 

  • Formula: the formula to integrate
  • Argument: the variable which to integrate to
  • sub (optional): the lower bounds of the interval to integrate on
  • sup (optional): the upper bounds of the interval to integrate on

Output: The integrated formula
For more details on the implementation see the underlying function documentation.

Derivative

Input: 

  • Formula: the formula to differentiate
  • Argument: the variable which to differentiate to

Output: The differentiated formula
For more details on the implementation see the underlying function documentation.

Limit

Input: 

  • Formula: the formula to calculate the limit of
  • Argument: the variable to calculate the limit of
  • C: the value which argument approaches
  • direction (optional, either + or -): the direction in which the limit should be calculated

Output: The limit of formula of argument as argument approaches C
For more details on the implementation see the underlying function documentation.

Substitute

Input: 

  • Formula: the formula to substitute values in
  • substitutions: a list of tuples (pattern, replacement)

Output: The formula in which all patterns are substituted by replacements (in the specified order)
For more details on the implementation see the underlying function documentation.

Determinant

Input: A matrix

Output: The determinant of matrix

For more details on the implementation see the underlying function documentation.

Column space

Input: A matrix

Output: List of column vectors that span the column space of the matrix

For more details on the implementation see the underlying function documentation.

Null space

Input: A matrix

Output: List of column vectors that span the null space of the matrix

For more details on the implementation see the underlying function documentation.

Rank

Input: A matrix

Output: The rank of the input matrix

For more details on the implementation see the underlying function documentation.

Transpose

Input: A matrix

Output: The transpose of the input matrix

For more details on the implementation see the underlying function documentation.

RREF

Input: A matrix

Output: The Row Reduced Echelon Form of the input matrix

For more details on the implementation see the underlying function documentation. Note that we only return a matrix, not the tuple of index columns.

EigenValues

Input: A matrix

Output: A list with the EigenValues of the input matrix

For more details on the implementation see the underlying function documentation. Note that we return the EigenValues in the same order as the EigenVectors

EigenVectors

Input: A matrix

Output: A list with the EigenVectors of the input matrix

For more details on the implementation see the underlying function documentation. Note that we return the EigenVectors in the same order as the EigenValues

Shape

Input: A matrix

Output: Two values, one for the number of rows of the matrix and one for the number of columns of the matrix. These values can be selected as separate placeholder names.

Diagonalize

Input: A matrix

Output: Two values, one matrix D which is diagonal, and a matrix P such that 𝑃𝐷𝑃^-1 gives the input matrix. 

For more details on the implementation see the underlying function documentation. 

Dataset

Input: A file with comma separated values. This file should have column names in the first row, no missing values, and should be less than 2MB in size.

Output: A dataset variable which can be used in other dataset-based operators

Sample

Input:

  • A dataset based variable
  • The size of the samples

Output: A dataset variable which can be used in other dataset-based operators

Correlation

Input:

  • Two lists of numeric values. These values can be the result of mathematical expressions, or result of selecting a single column of a dataset using the Select operator.
    Note: all values of the lists should be numeric and available. The current operator cannot deal with missing data.
  • The method of correlation to use

Output: Two values:

  • the estimate of the correlation
  • the p-value of the correlation

These values can be selected as separate placeholder names.

Linear Regression

Input:

  • A list of numeric values for the dependent variable,
  • A list of lists of numeric values, one for each coefficient B1 ... Bn

These values can be the result of mathematical expressions, or result of selecting a single column of a dataset using the Select operator.

Note: all values of the lists should be numeric and available. The current operator cannot deal with missing data.

Output: Multiple values:

  • The coefficient of the constant
  • The standard deviation of the coefficient of the constant
  • The coefficient of each of B1 ... Bn
  • The standard deviation of each coefficient B1 ... Bn
  • The R-Squared value of the model
  • The adjusted R-Squared value of the model
  • The residual standard error of the model

These values can be selected as separate placeholder names.

New operators

The following operators are planned to be added in the next release.

  • Combine matrices and vectors
  • Remove row/column of a matrix

We are actively expanding the set of operators and are keen to receive feature requests for new operators. Are you missing an operator? Let us know by providing

  • a (short) example exercise
  • description of the input and output of the operator
  • Operator name suggestion

We will quickly get back to you whether we can implement such an operator.

If you have any questions regarding operators or other functionality, please reach out to us via the chat icon in the bottom right.

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