numpy.busday_count(begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None) Counts the number of valid days between begindates and enddates, not including the day of enddates. If enddates specifies a date value that is earlier than the corresponding begindates date value, the count will be negative. New in version 1.7.0. Parameters: begindates : array_like of datetime64[D] The array of the first dates for counting. enddates : array_like of datetime64[D] The arr

MaskedArray.__ne__(other) [source] Check whether other doesn?t equal self elementwise

MaskedArray.__ifloordiv__(other) [source] Floor divide self by other in-place.

numpy.linalg.eigh(a, UPLO='L') [source] Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix. Returns two objects, a 1-D array containing the eigenvalues of a, and a 2-D square array or matrix (depending on the input type) of the corresponding eigenvectors (in columns). Parameters: a : (..., M, M) array Hermitian/Symmetric matrices whose eigenvalues and eigenvectors are to be computed. UPLO : {?L?, ?U?}, optional Specifies whether the calculation is done with the l

numpy.polynomial.legendre.leggrid3d(x, y, z, c) [source] Evaluate a 3-D Legendre series on the Cartesian product of x, y, and z. This function returns the values: where the points (a, b, c) consist of all triples formed by taking a from x, b from y, and c from z. The resulting points form a grid with x in the first dimension, y in the second, and z in the third. The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars.

ndarray.T Same as self.transpose(), except that self is returned if self.ndim < 2. Examples >>> x = np.array([[1.,2.],[3.,4.]]) >>> x array([[ 1., 2.], [ 3., 4.]]) >>> x.T array([[ 1., 3.], [ 2., 4.]]) >>> x = np.array([1.,2.,3.,4.]) >>> x array([ 1., 2., 3., 4.]) >>> x.T array([ 1., 2., 3., 4.])

numpy.core.defchararray.add(x1, x2) [source] Return element-wise string concatenation for two arrays of str or unicode. Arrays x1 and x2 must have the same shape. Parameters: x1 : array_like of str or unicode Input array. x2 : array_like of str or unicode Input array. Returns: add : ndarray Output array of string_ or unicode_, depending on input types of the same shape as x1 and x2.

Standard FFTs fft(a[, n, axis, norm]) Compute the one-dimensional discrete Fourier Transform. ifft(a[, n, axis, norm]) Compute the one-dimensional inverse discrete Fourier Transform. fft2(a[, s, axes, norm]) Compute the 2-dimensional discrete Fourier Transform ifft2(a[, s, axes, norm]) Compute the 2-dimensional inverse discrete Fourier Transform. fftn(a[, s, axes, norm]) Compute the N-dimensional discrete Fourier Transform. ifftn(a[, s, axes, norm]) Compute the N-dimensional inverse dis

numpy.binary_repr(num, width=None) [source] Return the binary representation of the input number as a string. For negative numbers, if width is not given, a minus sign is added to the front. If width is given, the two?s complement of the number is returned, with respect to that width. In a two?s-complement system negative numbers are represented by the two?s complement of the absolute value. This is the most common method of representing signed integers on computers [R16]. A N-bit two?s-com

numpy.result_type(*arrays_and_dtypes) Returns the type that results from applying the NumPy type promotion rules to the arguments. Type promotion in NumPy works similarly to the rules in languages like C++, with some slight differences. When both scalars and arrays are used, the array?s type takes precedence and the actual value of the scalar is taken into account. For example, calculating 3*a, where a is an array of 32-bit floats, intuitively should result in a 32-bit float output. If the