numpy.fft.irfft2(a, s=None, axes=(-2, -1), norm=None) [source] Compute the 2-dimensional inverse FFT of a real array. Parameters: a : array_like The input array s : sequence of ints, optional Shape of the inverse FFT. axes : sequence of ints, optional The axes over which to compute the inverse fft. Default is the last two axes. norm : {None, ?ortho?}, optional New in version 1.10.0. Normalization mode (see numpy.fft). Default is None. Returns: out : ndarray The result of the i

numpy.logical_not(x[, out]) = Compute the truth value of NOT x element-wise. Parameters: x : array_like Logical NOT is applied to the elements of x. Returns: y : bool or ndarray of bool Boolean result with the same shape as x of the NOT operation on elements of x. See also logical_and, logical_or, logical_xor Examples >>> np.logical_not(3) False >>> np.logical_not([True, False, 0, 1]) array([False, True, True, False], dtype=bool) >>> x = np.arange(5)

numpy.swapaxes(a, axis1, axis2) [source] Interchange two axes of an array. Parameters: a : array_like Input array. axis1 : int First axis. axis2 : int Second axis. Returns: a_swapped : ndarray For Numpy >= 1.10, if a is an ndarray, then a view of a is returned; otherwise a new array is created. For earlier Numpy versions a view of a is returned only if the order of the axes is changed, otherwise the input array is returned. Examples >>> x = np.array([[1,2,3]]) >&g

numpy.rint(x[, out]) = Round elements of the array to the nearest integer. Parameters: x : array_like Input array. Returns: out : ndarray or scalar Output array is same shape and type as x. See also ceil, floor, trunc Examples >>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) >>> np.rint(a) array([-2., -2., -0., 0., 2., 2., 2.])

numpy.mgrid = nd_grid instance which returns a dense multi-dimensional ?meshgrid?. An instance of numpy.lib.index_tricks.nd_grid which returns an dense (or fleshed out) mesh-grid when indexed, so that each returned argument has the same shape. The dimensions and number of the output arrays are equal to the number of indexing dimensions. If the step length is not a complex number, then the stop is not inclusive. However, if the step length is a complex number (e.g. 5j), then the integer par

Chebyshev.has_samedomain(other) [source] Check if domains match. New in version 1.6.0. Parameters: other : class instance The other class must have the domain attribute. Returns: bool : boolean True if the domains are the same, False otherwise.

numpy.fft.rfftfreq(n, d=1.0) [source] Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft). The returned float array f contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instance, if the sample spacing is in seconds, then the frequency unit is cycles/second. Given a window length n and a sample spacing d: f = [0, 1, ..., n/2-1, n/2] / (d*n) if n is even f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*

numpy.sqrt(x[, out]) = Return the positive square-root of an array, element-wise. Parameters: x : array_like The values whose square-roots are required. out : ndarray, optional Alternate array object in which to put the result; if provided, it must have the same shape as x Returns: y : ndarray An array of the same shape as x, containing the positive square-root of each element in x. If any element in x is complex, a complex array is returned (and the square-roots of negative reals

classmethod Legendre.fromroots(roots, domain=[], window=None) [source] Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parameters: roots : array_like List of roots. domain : {[], None, array_like}, optional Domain for the resulting series. If None the domain is the interval from the smallest root to the largest. If [] the domain is the class domain. The default is []. wind

numpy.apply_over_axes(func, a, axes) [source] Apply a function repeatedly over multiple axes. func is called as res = func(a, axis), where axis is the first element of axes. The result res of the function call must have either the same dimensions as a or one less dimension. If res has one less dimension than a, a dimension is inserted before axis. The call to func is then repeated for each axis in axes, with res as the first argument. Parameters: func : function This function must take tw