nditer.remove_axis(i) Removes axis i from the iterator. Requires that the flag ?multi_index? be enabled.

ndarray.conj() Complex-conjugate all elements. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

record.shape tuple of array dimensions

numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None) [source] Return numbers spaced evenly on a log scale. In linear space, the sequence starts at base ** start (base to the power of start) and ends with base ** stop (see endpoint below). Parameters: start : float base ** start is the starting value of the sequence. stop : float base ** stop is the final value of the sequence, unless endpoint is False. In that case, num + 1 values are spaced over the interval in log

record.dump() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The

RandomState.logistic(loc=0.0, scale=1.0, size=None) Draw samples from a logistic distribution. Samples are drawn from a logistic distribution with specified parameters, loc (location or mean, also median), and scale (>0). Parameters: loc : float scale : float > 0. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. Returns: samples : ndarray or scal

numpy.reshape(a, newshape, order='C') [source] Gives a new shape to an array without changing its data. Parameters: a : array_like Array to be reshaped. newshape : int or tuple of ints The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions. order : {?C?, ?F?, ?A?}, optional Read the elements of

recarray.take(indices, axis=None, out=None, mode='raise') Return an array formed from the elements of a at the given indices. Refer to numpy.take for full documentation. See also numpy.take equivalent function

recarray.conjugate() Return the complex conjugate, element-wise. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

ndarray.clip(min=None, max=None, out=None) Return an array whose values are limited to [min, max]. One of max or min must be given. Refer to numpy.clip for full documentation. See also numpy.clip equivalent function