Functions which are common and require SciPy Base and Level 1 SciPy (special, linalg)


arange([dtype]) Return evenly spaced values within a given interval.
array(object[, dtype, copy, order, subok, ndmin]) Create an array.
asarray(a[, dtype, order]) Convert the input to an array.
central_diff_weights(Np[, ndiv]) Return weights for an Np-point central derivative of order ndiv
comb(N, k[, exact]) The number of combinations of N things taken k at a time.
derivative(func, x0[, dx, n, args, order]) Find the n-th derivative of a function at point x0.
dot(a, b[, out]) Dot product of two arrays.
extract(condition, arr) Return the elements of an array that satisfy some condition.
eye(N[, M, k, dtype]) Return a 2-D array with ones on the diagonal and zeros elsewhere.
factorial(n[, exact]) The factorial function, n! = special.gamma(n+1).
factorial2(n[, exact]) Double factorial.
factorialk(n, k[, exact]) n(!!...!) = multifactorial of order k
hstack(tup) Stack arrays in sequence horizontally (column wise).
lena() Get classic image processing example image, Lena, at 8-bit grayscale
pade(an, m) Given Taylor series coefficients in an, return a Pade approximation to
place(arr, mask, vals) Change elements of an array based on conditional and input values.
product(a[, axis, dtype, out]) Return the product of array elements over a given axis.
where(condition, x) Return elements, either from x or y, depending on condition.
zeros(shape[, dtype, order]) Return a new array of given shape and type, filled with zeros.


poly1d(c_or_r[, r, variable]) A one-dimensional polynomial class.

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