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scipy.misc.common

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

Functions

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.

Classes

poly1d(c_or_r[, r, variable])

A one-dimensional polynomial class.