Hermite.has_samedomain()

Hermite.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.

Hermite.has_samecoef()

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

MaskedArray.harden_mask()

MaskedArray.harden_mask() [source] Force the mask to hard. Whether the mask of a masked array is hard or soft is determined by its hardmask property. harden_mask sets hardmask to True. See also hardmask

numpy.core.defchararray.rjust()

numpy.core.defchararray.rjust(a, width, fillchar=' ') [source] Return an array with the elements of a right-justified in a string of length width. Calls str.rjust element-wise. Parameters: a : array_like of str or unicode width : int The length of the resulting strings fillchar : str or unicode, optional The character to use for padding Returns: out : ndarray Output array of str or unicode, depending on input type See also str.rjust

numpy.lexsort()

numpy.lexsort(keys, axis=-1) Perform an indirect sort using a sequence of keys. Given multiple sorting keys, which can be interpreted as columns in a spreadsheet, lexsort returns an array of integer indices that describes the sort order by multiple columns. The last key in the sequence is used for the primary sort order, the second-to-last key for the secondary sort order, and so on. The keys argument must be a sequence of objects that can be converted to arrays of the same shape. If a 2D a

matrix.resize()

matrix.resize(new_shape, refcheck=True) Change shape and size of array in-place. Parameters: new_shape : tuple of ints, or n ints Shape of resized array. refcheck : bool, optional If False, reference count will not be checked. Default is True. Returns: None Raises: ValueError If a does not own its own data or references or views to it exist, and the data memory must be changed. SystemError If the order keyword argument is specified. This behaviour is a bug in NumPy. See also

MaskedArray.count()

MaskedArray.count(axis=None) [source] Count the non-masked elements of the array along the given axis. Parameters: axis : int, optional Axis along which to count the non-masked elements. If axis is None, all non-masked elements are counted. Returns: result : int or ndarray If axis is None, an integer count is returned. When axis is not None, an array with shape determined by the lengths of the remaining axes, is returned. See also count_masked Count masked elements in array or a

matrix.getA1()

matrix.getA1() [source] Return self as a flattened ndarray. Equivalent to np.asarray(x).ravel() Parameters: None Returns: ret : ndarray self, 1-D, as an ndarray Examples >>> x = np.matrix(np.arange(12).reshape((3,4))); x matrix([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> x.getA1() array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])

matrix.sort()

matrix.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.polynomial.laguerre.lagvander2d()

numpy.polynomial.laguerre.lagvander2d(x, y, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y). The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg[0] and 0 <= j <= deg[1]. The leading indices of V index the points (x, y) and the last index encodes the degrees of the Laguerre polynomials. If V = lagvander2d(x, y, [xdeg, ydeg]), then the columns of V correspond to the elements of a