matrix.tobytes(order='C') Construct Python bytes containing the raw data bytes in the array. Constructs Python bytes showing a copy of the raw contents of data memory. The bytes object can be produced in either ?C? or ?Fortran?, or ?Any? order (the default is ?C?-order). ?Any? order means C-order unless the F_CONTIGUOUS flag in the array is set, in which case it means ?Fortran? order. New in version 1.9.0. Parameters: order : {?C?, ?F?, None}, optional Order of the data for multidimensi

numpy.array_str(a, max_line_width=None, precision=None, suppress_small=None) [source] Return a string representation of the data in an array. The data in the array is returned as a single string. This function is similar to array_repr, the difference being that array_repr also returns information on the kind of array and its data type. Parameters: a : ndarray Input array. max_line_width : int, optional Inserts newlines if text is longer than max_line_width. The default is, indirectly, 7

matrix.I Returns the (multiplicative) inverse of invertible self. Parameters: None Returns: ret : matrix object If self is non-singular, ret is such that ret * self == self * ret == np.matrix(np.eye(self[0,:].size) all return True. Raises: numpy.linalg.LinAlgError: Singular matrix If self is singular. See also linalg.inv Examples >>> m = np.matrix('[1, 2; 3, 4]'); m matrix([[1, 2], [3, 4]]) >>> m.getI() matrix([[-2. , 1. ], [ 1.5, -0.5]]) >&

numpy.ma.masked_greater_equal(x, value, copy=True) [source] Mask an array where greater than or equal to a given value. This function is a shortcut to masked_where, with condition = (x >= value). See also masked_where Mask where a condition is met. Examples >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_greater_equal(a, 2) masked_array(data = [0 1 -- --], mask = [False False True True], fill_va

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.core.records.fromarrays(arrayList, dtype=None, shape=None, formats=None, names=None, titles=None, aligned=False, byteorder=None) [source] create a record array from a (flat) list of arrays >>> x1=np.array([1,2,3,4]) >>> x2=np.array(['a','dd','xyz','12']) >>> x3=np.array([1.1,2,3,4]) >>> r = np.core.records.fromarrays([x1,x2,x3],names='a,b,c') >>> print(r[1]) (2, 'dd', 2.0) >>> x1[1]=34 >>> r.a array([1, 2, 3, 4])

numpy.core.records.fromstring(datastring, dtype=None, shape=None, offset=0, formats=None, names=None, titles=None, aligned=False, byteorder=None) [source] create a (read-only) record array from binary data contained in a string

chararray.tostring(order='C') Construct Python bytes containing the raw data bytes in the array. Constructs Python bytes showing a copy of the raw contents of data memory. The bytes object can be produced in either ?C? or ?Fortran?, or ?Any? order (the default is ?C?-order). ?Any? order means C-order unless the F_CONTIGUOUS flag in the array is set, in which case it means ?Fortran? order. This function is a compatibility alias for tobytes. Despite its name it returns bytes not strings. Para

Various windows bartlett(M) Return the Bartlett window. blackman(M) Return the Blackman window. hamming(M) Return the Hamming window. hanning(M) Return the Hanning window. kaiser(M, beta) Return the Kaiser window.

numpy.polynomial.hermite_e.hermeval2d(x, y, c) [source] Evaluate a 2-D HermiteE series at points (x, y). This function returns the values: The parameters x and y are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. In either case, either x and y or their elements must support multiplication and addition both with themselves and with the elements of c. If c is a 1-D array a one is implicitly