MaskedArray.__lt__ x.__lt__(y) <==> x<y

MaskedArray.sort(axis=-1, kind='quicksort', order=None, endwith=True, fill_value=None) [source] Sort the array, in-place Parameters: a : array_like Array to be sorted. axis : int, optional Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis. kind : {?quicksort?, ?mergesort?, ?heapsort?}, optional Sorting algorithm. Default is ?quicksort?. order : list, optional When a is a structured array, this argument specif

HermiteE.__call__(arg) [source]

ndenumerate.next() [source] Standard iterator method, returns the index tuple and array value. Returns: coords : tuple of ints The indices of the current iteration. val : scalar The array element of the current iteration.

Finding help lookfor(what[, module, import_modules, ...]) Do a keyword search on docstrings. Reading help info([object, maxwidth, output, toplevel]) Get help information for a function, class, or module. source(object[, output]) Print or write to a file the source code for a Numpy object.

numpy.ma.fromfunction(function, shape, **kwargs) = Construct an array by executing a function over each coordinate. The resulting array therefore has a value fn(x, y, z) at coordinate (x, y, z). Parameters: function : callable The function is called with N parameters, where N is the rank of shape. Each parameter represents the coordinates of the array varying along a specific axis. For example, if shape were (2, 2), then the parameters in turn be (0, 0), (0, 1), (1, 0), (1, 1). shape :

numpy.ma.apply_along_axis(func1d, axis, arr, *args, **kwargs) [source] Apply a function to 1-D slices along the given axis. Execute func1d(a, *args) where func1d operates on 1-D arrays and a is a 1-D slice of arr along axis. Parameters: func1d : function This function should accept 1-D arrays. It is applied to 1-D slices of arr along the specified axis. axis : integer Axis along which arr is sliced. arr : ndarray Input array. args : any Additional arguments to func1d. kwargs: any

numpy.tril(m, k=0) [source] Lower triangle of an array. Return a copy of an array with elements above the k-th diagonal zeroed. Parameters: m : array_like, shape (M, N) Input array. k : int, optional Diagonal above which to zero elements. k = 0 (the default) is the main diagonal, k < 0 is below it and k > 0 is above. Returns: tril : ndarray, shape (M, N) Lower triangle of m, of same shape and data-type as m. See also triu same thing, only for the upper triangle Examples

matrix.H Returns the (complex) conjugate transpose of self. Equivalent to np.transpose(self) if self is real-valued. Parameters: None Returns: ret : matrix object complex conjugate transpose of self Examples >>> x = np.matrix(np.arange(12).reshape((3,4))) >>> z = x - 1j*x; z matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j], [ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j], [ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]]) >>> z.getH() matrix([[

numpy.polynomial.polynomial.polydomain = array([-1, 1])