stdlib ORG

✨ The fundamental numerical library for JavaScript and TypeScript. ✨

Standard library basic linear algebra subprograms (BLAS).

Uptime and status monitor for the stdlib website.

REPL environment.

Standard library math.

LAPACK routines.

Project code coverage.

Multidimensional array constructor.

Base multidimensional array.

Standard library basic linear algebra subprograms (BLAS).

Beta distributed pseudorandom numbers.

Create an iterator for generating pseudorandom numbers drawn from a chi-square distribution.

Standard library for interfacing with a fileystem.

Return abbreviated help text associated with a provided alias.

Return help text associated with a provided alias.

Return an example associated with a provided alias.

Return package names related to a specified package name.

Return the alias associated with a specified package name.

Return aliases related to a specified alias.

The standard library namespace.

Return the package name associated with a specified alias.

Broadcast an ndarray to a specified shape if and only if the specified shape differs from the provided ndarray's shape.

Broadcast an ndarray to a specified shape.

Return a new array containing every element from an input array, except for the element at a specified index.

Perform a reduction over elements in a input ndarray.

Copy all or part of a matrix A to another matrix B.

Apply a unary callback to elements in a input ndarray and assign results to elements in an output ndarray.

Generate a linearly spaced numeric array.

Compute the sum of absolute values (L1 norm).

Standard library extended basic linear algebra subroutines (BLAS).

Multiply x by a constant and add the result to y.

Convert an array to the same data type as a second input array.

Convert an array to an array of a different data type.

Pseudorandom number generator array creation functions.

Standard library base pseudorandom number generators.

Revive a JSON-serialized pseudorandom number generator (PRNG).

Standard library pseudorandom number generator iterators.

Create an iterator for generating pseudorandom numbers drawn from a beta distribution.

Standard library pseudorandom number generator streams.

Create a readable stream for generating pseudorandom numbers drawn from a beta distribution.

Create an iterator for generating pseudorandom numbers drawn from a beta prime distribution.

Create a readable stream for generating pseudorandom numbers drawn from a beta prime distribution.

Fill a strided array with pseudorandom numbers drawn from a beta prime distribution.

Beta prime distributed pseudorandom numbers.

Create an iterator for generating pseudorandom numbers drawn from a chi distribution.

Create a readable stream for generating pseudorandom numbers drawn from an F distribution.

F distributed pseudorandom numbers.

Create a readable stream for generating pseudorandom numbers drawn from a Student's t distribution.

Student's t-distributed pseudorandom numbers.

Chi-square distributed pseudorandom numbers.

Create an iterator for generating pseudorandom numbers drawn from an inverse gamma distribution.

Create a readable stream for generating pseudorandom numbers drawn from an inverse gamma distribution.

Fill a strided array with pseudorandom numbers drawn from an inverse gamma distribution.

Inverse gamma distributed pseudorandom numbers.

Create a readable stream for generating pseudorandom numbers drawn from a negative binomial distribution.

Negative binomial distributed pseudorandom numbers.

Create an iterator for generating pseudorandom numbers drawn from a gamma distribution.

Gamma distributed pseudorandom numbers.

Create an iterator for generating pseudorandom numbers having integer values.

Remove a directory entry.

Return the typed signature(s) associated with a provided alias.

Return the signature(s) associated with a provided alias.

Return the internal package name associated with a provided standalone package name.

Return the standalone package name associated with a provided internal package name.

Standard library aliases.

Weibull distribution mode.

Weibull distribution expected value.

Uniform distribution median.

Uniform distribution expected value.

Triangular distribution mode.

Rayleigh distribution mode.

Rayleigh distribution median.

Rayleigh distribution expected value.

Planck distribution expected value.

Normal distribution mode.

Broadcast ndarrays to a common shape.

Broadcast ndarrays to a common shape.

Create an uninitialized ndarray having a specified shape and data type.

Convert an ndarray-like object to an ndarray.

Create an uninitialized ndarray having a specified shape and data type.

Convert an ndarray-like object to an ndarray.

Return a shallow copy of a portion of an array.

Take elements from an array and return a new array after applying a mapping function.

Take elements from an array.

Take elements from an array.

Return a new array with elements in reverse order.

Take elements from either one of two arrays depending on a condition.

Generate a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length and data type as a provided input array.

Generate a linearly spaced numeric array whose elements increment by 1 starting from zero.

Reorder ndarray dimensions and associated strides for loop interchange.

Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.

Set the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values.

Apply a nullary function and assign results to elements in an output ndarray.

Reorder ndarray dimensions and associated strides for loop interchange.

Copy all or part of a matrix A to another matrix B.

Copy all or part of a matrix A to another matrix B.

Copy all or part of a matrix A to another matrix B.

Assign elements in a input ndarray to elements in an output ndarray.

Apply a unary function to each element retrieved from a input ndarray according to a callback function and assign results to elements in an output ndarray.

Reorder ndarray dimensions and associated strides for loop interchange.

Generate a linearly spaced numeric array whose elements increment by 1 starting from zero.

Assign element values from a broadcasted input array to corresponding elements in an output array.

Return a shallow copy of a portion of an array.

Create an array containing pseudorandom numbers drawn from a beta distribution.

Pseudorandom number generator strided array functions.

Fill a strided array with pseudorandom numbers drawn from a beta distribution.

Create an array containing pseudorandom numbers drawn from a gamma distribution.

Create an array containing pseudorandom numbers drawn from a beta prime distribution.

Create an array containing pseudorandom numbers drawn from a chi-square distribution.

Create an array containing pseudorandom numbers drawn from a chi distribution.

Create a readable stream for generating pseudorandom numbers drawn from a chi distribution.

Fill a strided array with pseudorandom numbers drawn from a chi distribution.

Chi distributed pseudorandom numbers.

Create an array containing pseudorandom numbers drawn from an F distribution.

Create an iterator for generating pseudorandom numbers drawn from an F distribution.

Create an array containing pseudorandom numbers drawn from a Student's t-distribution.

Create an iterator for generating pseudorandom numbers drawn from a Student's t distribution.

Fill a strided array with pseudorandom numbers drawn from a Student's t distribution.

Create a readable stream for generating pseudorandom numbers drawn from a chi-square distribution.

Fill a strided array with pseudorandom numbers drawn from a chi-square distribution.

Create an array containing pseudorandom numbers drawn from an inverse gamma distribution.

Create an array containing pseudorandom numbers drawn from a negative binomial distribution.

Create an iterator for generating pseudorandom numbers drawn from a negative binomial distribution.

Create a readable stream for generating pseudorandom numbers drawn from a gamma distribution.

Fill a strided array with pseudorandom numbers drawn from a gamma distribution.

Create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG) whose output is shuffled.

Number.

Return the standalone package name associated with a specified alias.

Weibull distribution median.

Compute the Fresnel integral C(x).

Triangular distribution median.

Triangular distribution expected value.

Poisson distribution mode.

Poisson distribution median.

Poisson distribution expected value.

Planck (discrete exponential) distribution mode.

Pareto (Type I) distribution median.

Normal distribution median.

Broadcast an ndarray to a specified shape while keeping a list of specified dimensions unchanged if and only if the specified shape differs from the provided ndarray's shape.

Broadcast an input ndarray to a target shape while keeping a list of specified dimensions unchanged.

Assign elements from a broadcasted input ndarray to a specified diagonal of an output ndarray.

Convert an array to a one-dimensional ndarray.

Apply a one-dimensional strided array function to a list of specified dimensions in an ndarray.

Perform a reduction over a list of specified dimensions in an input ndarray via a one-dimensional strided array reduction function and assign results to a provided output ndarray.

Perform a reduction over a list of specified dimensions in an input ndarray via a one-dimensional strided array reduction function and assign results to a provided output ndarray.

Apply a one-dimensional strided array function to a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

Zip one or more one-dimensional ndarrays to an array of composite views.

Reinterpret a boolean ndarray as an unsigned 8-bit integer ndarray.

Reinterpret a complex-valued floating-point ndarray as a real-valued floating-point ndarray having the same precision.

Reinterpret a double-precision complex floating-point ndarray as a real-valued double-precision floating-point ndarray containing interleaved real and imaginary components.

Reinterpret a single-precision complex floating-point ndarray as a real-valued single-precision floating-point ndarray containing interleaved real and imaginary components.

Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

Return a new array containing every element from an input array and with a provided value inserted at a specified index.

Apply a binary callback to elements in input ndarrays and assign results to elements in an output ndarray.

Reorder ndarray dimensions and associated strides for loop interchange.

Reorder ndarray dimensions and associated strides for loop interchange.

Apply a ternary callback to elements in input ndarrays and assign results to elements in an output ndarray.

Reorder ndarray dimensions and associated strides for loop interchange.

Reorder ndarray dimensions and associated strides for loop interchange.

Base (i.e., lower-level) LAPACK routines.

Set the off-diagonal elements and the diagonal elements of a double-precision floating-point matrix to specified values.

Test whether at least one element in an ndarray is truthy.

Assign a scalar value to every element of an output ndarray.

Count the number of falsy elements in an ndarray.

Count the number of truthy elements in an ndarray.

Test whether every element in an ndarray is truthy.

Test whether an ndarray contains a specified value.

Test whether at least `n` elements in an ndarray are truthy.

Statistical operations for strided arrays.

Compute the covariance matrix for an `M` by `N` double-precision floating-point matrix `A` and assigns the results to a matrix `B` when provided known means and using a one-pass textbook algorithm.

Copy an input ndarray to a new ndarray having the same shape and data type.

Return a new ndarray where an ndarray is rotated 180 degrees in a specified plane.

Return a new ndarray where an ndarray is rotated 90 degrees in a specified plane.

Return a new ndarray where a matrix (or a stack of matrices) is rotated 90 degrees counterclockwise.

Return a new ndarray where a matrix (or a stack of matrices) is rotated 90 degrees clockwise.

Return a new ndarray containing the elements of an input ndarray but whose last two dimensions are transposed.

Return a new ndarray in which a specified dimension of an input ndarray is expanded over multiple dimensions.

Create an object from a provided list of properties and a provided list of corresponding values.

Base ndarray BLAS functions.

Compute the sum of absolute values for all elements in a one-dimensional ndarray.

Multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`.

Base ndarray extended BLAS functions.

Multiply a one-dimensional ndarray by a scalar constant and add the result to a second one-dimensional ndarray multiplied by a scalar constant.

Multiply a strided array `x` by a constant and add the result to a strided array `y` multiplied by a constant.

Copy values from a one-dimensional ndarray `x` into a one-dimensional ndarray `y`.

Compute the Cartesian product for two strided arrays.

Compute the Cartesian square for a strided array.

Calculate the k-th discrete forward difference of a strided array.

Calculate the differences between consecutive elements of a strided array.

Multiply each element in a strided array `x` by a scalar constant and add a scalar constant before assigning the results to a strided array `w`.

Add a scalar constant to each element in a strided array `x` and assign the results to elements in a strided array `w`

Multiply each element in a strided array `x` by a scalar constant and assign the results to elements in a strided array `w`.

Subtract a scalar constant from each element in a strided array `x` and assign the results to elements in a strided array `y`

Evaluate the identity function for an unsigned 32-bit integer.

Wald distribution variance.

Wald distribution skewness.

Wald distribution mode.

Wald distribution expected value.

Wald distribution excess kurtosis.

Planck (discrete exponential) distribution median.