numpy.polynomial.laguerre.lagvander3d()

numpy.polynomial.laguerre.lagvander3d(x, y, z, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z). If l, m, n are the given degrees in x, y, z, then The pseudo-Vandermonde matrix is defined by where 0 <= i <= l, 0 <= j <= m, and 0 <= j <= n. The leading indices of V index the points (x, y, z) and the last index encodes the degrees of the Laguerre polynomials. If V = lagvander3d(x, y,

matrix.item()

matrix.item(*args) Copy an element of an array to a standard Python scalar and return it. Parameters: *args : Arguments (variable number and type) none: in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned. int_type: this argument is interpreted as a flat index into the array, specifying which element to copy and return. tuple of int_types: functions as does a single int_type argument, exce

matrix.mean()

matrix.mean(axis=None, dtype=None, out=None) [source] Returns the average of the matrix elements along the given axis. Refer to numpy.mean for full documentation. See also numpy.mean Notes Same as ndarray.mean except that, where that returns an ndarray, this returns a matrix object. 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.mean() 5.5 >>> x.mean(0)

matrix.setfield()

matrix.setfield(val, dtype, offset=0) Put a value into a specified place in a field defined by a data-type. Place val into a?s field defined by dtype and beginning offset bytes into the field. Parameters: val : object Value to be placed in field. dtype : dtype object Data-type of the field in which to place val. offset : int, optional The number of bytes into the field at which to place val. Returns: None See also getfield Examples >>> x = np.eye(3) >>> x.getfi

matrix.cumprod()

matrix.cumprod(axis=None, dtype=None, out=None) Return the cumulative product of the elements along the given axis. Refer to numpy.cumprod for full documentation. See also numpy.cumprod equivalent function

chararray.isalnum()

chararray.isalnum() [source] Returns true for each element if all characters in the string are alphanumeric and there is at least one character, false otherwise. See also char.isalnum

MaskedArray.__add__()

MaskedArray.__add__(other) [source] Add self to other, and return a new masked array.

numpy.record

class numpy.record [source] A data-type scalar that allows field access as attribute lookup. Attributes T transpose base base object data pointer to start of data dtype dtype object flags integer value of flags flat a 1-d view of scalar imag imaginary part of scalar itemsize length of one element in bytes nbytes length of item in bytes ndim number of array dimensions real real part of scalar shape tuple of array dimensions size number of elements in the gentype strides tuple of bytes steps

Chebyshev.degree()

Chebyshev.degree() [source] The degree of the series. New in version 1.5.0. Returns: degree : int Degree of the series, one less than the number of coefficients.

generic.sum()

generic.sum() 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