classmethod Laguerre.identity(domain=None, window=None) [source] Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters: domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form [beg, end], where beg and end ar

RandomState.standard_normal(size=None) Draw samples from a standard Normal distribution (mean=0, stdev=1). Parameters: 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: out : float or ndarray Drawn samples. Examples >>> s = np.random.standard_normal(8000) >>> s array([ 0.6888893 , 0.78096262, -0.89086505, ..., 0.49876311,

numpy.extract(condition, arr) [source] Return the elements of an array that satisfy some condition. This is equivalent to np.compress(ravel(condition), ravel(arr)). If condition is boolean np.extract is equivalent to arr[condition]. Note that place does the exact opposite of extract. Parameters: condition : array_like An array whose nonzero or True entries indicate the elements of arr to extract. arr : array_like Input array of the same size as condition. Returns: extract : ndarray

MaskedArray.unshare_mask() [source] Copy the mask and set the sharedmask flag to False. Whether the mask is shared between masked arrays can be seen from the sharedmask property. unshare_mask ensures the mask is not shared. A copy of the mask is only made if it was shared. See also sharedmask

ndarray.sort(axis=-1, kind='quicksort', order=None) Sort an array, in-place. Parameters: axis : int, optional Axis along which to sort. Default is -1, which means sort along the last axis. kind : {?quicksort?, ?mergesort?, ?heapsort?}, optional Sorting algorithm. Default is ?quicksort?. order : str or list of str, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all

numpy.where(condition[, x, y]) Return elements, either from x or y, depending on condition. If only condition is given, return condition.nonzero(). Parameters: condition : array_like, bool When True, yield x, otherwise yield y. x, y : array_like, optional Values from which to choose. x and y need to have the same shape as condition. Returns: out : ndarray or tuple of ndarrays If both x and y are specified, the output array contains elements of x where condition is True, and elements

numpy.sort_complex(a) [source] Sort a complex array using the real part first, then the imaginary part. Parameters: a : array_like Input array Returns: out : complex ndarray Always returns a sorted complex array. Examples >>> np.sort_complex([5, 3, 6, 2, 1]) array([ 1.+0.j, 2.+0.j, 3.+0.j, 5.+0.j, 6.+0.j]) >>> np.sort_complex([1 + 2j, 2 - 1j, 3 - 2j, 3 - 3j, 3 + 5j]) array([ 1.+2.j, 2.-1.j, 3.-3.j, 3.-2.j, 3.+5.j])

numpy.argmin(a, axis=None, out=None) [source] Returns the indices of the minimum values along an axis. Parameters: a : array_like Input array. axis : int, optional By default, the index is into the flattened array, otherwise along the specified axis. out : array, optional If provided, the result will be inserted into this array. It should be of the appropriate shape and dtype. Returns: index_array : ndarray of ints Array of indices into the array. It has the same shape as a.shape

numpy.flatnonzero(a) [source] Return indices that are non-zero in the flattened version of a. This is equivalent to a.ravel().nonzero()[0]. Parameters: a : ndarray Input array. Returns: res : ndarray Output array, containing the indices of the elements of a.ravel() that are non-zero. See also nonzero Return the indices of the non-zero elements of the input array. ravel Return a 1-D array containing the elements of the input array. Examples >>> x = np.arange(-2, 3) &

This module contains all functions in the numpy namespace, with the following replacement functions that return matrices instead of ndarrays. Functions that are also in the numpy namespace and return matrices mat(data[, dtype]) Interpret the input as a matrix. matrix Returns a matrix from an array-like object, or from a string of data. asmatrix(data[, dtype]) Interpret the input as a matrix. bmat(obj[, ldict, gdict]) Build a matrix object from a string, nested sequence, or array. Replacem