record.reshape() 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

numpy.shares_memory(a, b, max_work=None) Determine if two arrays share memory Parameters: a, b : ndarray Input arrays max_work : int, optional Effort to spend on solving the overlap problem (maximum number of candidate solutions to consider). The following special values are recognized: max_work=MAY_SHARE_EXACT (default) The problem is solved exactly. In this case, the function returns True only if there is an element shared between the arrays. max_work=MAY_SHARE_BOUNDS Only the memo

numpy.core.defchararray.swapcase(a) [source] Return element-wise a copy of the string with uppercase characters converted to lowercase and vice versa. Calls str.swapcase element-wise. For 8-bit strings, this method is locale-dependent. Parameters: a : array_like, {str, unicode} Input array. Returns: out : ndarray, {str, unicode} Output array of str or unicode, depending on input type See also str.swapcase Examples >>> c=np.array(['a1B c','1b Ca','b Ca1','cA1b'],'S5'); c a

numpy.atleast_2d(*arys) [source] View inputs as arrays with at least two dimensions. Parameters: arys1, arys2, ... : array_like One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have two or more dimensions are preserved. Returns: res, res2, ... : ndarray An array, or tuple of arrays, each with a.ndim >= 2. Copies are avoided where possible, and views with two or more dimensions are returned. See also atleast_1d, atleast_3d Examples

numpy.polynomial.laguerre.lagmulx(c) [source] Multiply a Laguerre series by x. Multiply the Laguerre series c by x, where x is the independent variable. Parameters: c : array_like 1-D array of Laguerre series coefficients ordered from low to high. Returns: out : ndarray Array representing the result of the multiplication. Notes The multiplication uses the recursion relationship for Laguerre polynomials in the form xP_i(x) = (-(i + 1)*P_{i + 1}(x) + (2i + 1)P_{i}(x) - iP_{i - 1}(x

numpy.true_divide(x1, x2[, out]) = Returns a true division of the inputs, element-wise. Instead of the Python traditional ?floor division?, this returns a true division. True division adjusts the output type to present the best answer, regardless of input types. Parameters: x1 : array_like Dividend array. x2 : array_like Divisor array. Returns: out : ndarray Result is scalar if both inputs are scalar, ndarray otherwise. Notes The floor division operator // was added in Python 2.2

MaskedArray.shrink_mask() [source] Reduce a mask to nomask when possible. Parameters: None Returns: None Examples >>> x = np.ma.array([[1,2 ], [3, 4]], mask=[0]*4) >>> x.mask array([[False, False], [False, False]], dtype=bool) >>> x.shrink_mask() >>> x.mask False

numpy.polynomial.laguerre.lagsub(c1, c2) [source] Subtract one Laguerre series from another. Returns the difference of two Laguerre series c1 - c2. The sequences of coefficients are from lowest order term to highest, i.e., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_2. Parameters: c1, c2 : array_like 1-D arrays of Laguerre series coefficients ordered from low to high. Returns: out : ndarray Of Laguerre series coefficients representing their difference. See also lagadd, lagmul,

RandomState.multinomial(n, pvals, size=None) Draw samples from a multinomial distribution. The multinomial distribution is a multivariate generalisation of the binomial distribution. Take an experiment with one of p possible outcomes. An example of such an experiment is throwing a dice, where the outcome can be 1 through 6. Each sample drawn from the distribution represents n such experiments. Its values, X_i = [X_0, X_1, ..., X_p], represent the number of times the outcome was i. Parameter

chararray.nonzero() Return the indices of the elements that are non-zero. Refer to numpy.nonzero for full documentation. See also numpy.nonzero equivalent function