Optionally Scipy-accelerated routines (numpy.dual)

Aliases for functions which may be accelerated by Scipy.

Scipy can be built to use accelerated or otherwise improved libraries for FFTs, linear algebra, and special functions. This module allows developers to transparently support these accelerated functions when scipy is available but still support users who have only installed Numpy.

Linear algebra

cholesky (a) Cholesky decomposition.
det (a) Compute the determinant of an array.
eig (a) Compute eigenvalues and right eigenvectors of an array.
eigh (a[, UPLO]) Eigenvalues and eigenvectors of a Hermitian or real symmetric matrix.
eigvals (a) Compute the eigenvalues of a general matrix.
eigvalsh (a[, UPLO]) Compute the eigenvalues of a Hermitean or real symmetric matrix.
inv (a) Compute the inverse of a matrix.
lstsq (a, b[, rcond]) Return the least-squares solution to an equation.
norm (x[, ord]) Matrix or vector norm.
pinv (a[, rcond]) Compute the (Moore-Penrose) pseudo-inverse of a matrix.
solve (a, b) Solve the equation a x = b for x.
svd (a[, full_matrices, compute_uv]) Singular Value Decomposition.


fft (a[, n, axis]) Compute the one dimensional fft on a given axis.
fft2 (a[, s, axes, -1)) Compute the 2-D FFT of an array.
fftn (a[, s, axes]) Compute the N-dimensional Fast Fourier Transform.
ifft (a[, n, axis]) Compute the one-dimensonal inverse fft along an axis.
ifft2 (a[, s, axes, -1)) Compute the inverse 2d fft of an array.
ifftn (a[, s, axes]) Compute the inverse of fftn.


i0 (x) Modified Bessel function of the first kind, order 0.