classmethod Laguerre.fit(x, y, deg, domain=None, rcond=None, full=False, w=None, window=None) [source] Least squares fit to data. Return a series instance that is the least squares fit to the data y sampled at x. The domain of the returned instance can be specified and this will often result in a superior fit with less chance of ill conditioning. Parameters: x : array_like, shape (M,) x-coordinates of the M sample points (x[i], y[i]). y : array_like, shape (M,) or (M, K) y-coordinates o

class numpy.memmap [source] Create a memory-map to an array stored in a binary file on disk. Memory-mapped files are used for accessing small segments of large files on disk, without reading the entire file into memory. Numpy?s memmap?s are array-like objects. This differs from Python?s mmap module, which uses file-like objects. This subclass of ndarray has some unpleasant interactions with some operations, because it doesn?t quite fit properly as a subclass. An alternative to using this su

numpy.fromfile(file, dtype=float, count=-1, sep='') Construct an array from data in a text or binary file. A highly efficient way of reading binary data with a known data-type, as well as parsing simply formatted text files. Data written using the tofile method can be read using this function. Parameters: file : file or str Open file object or filename. dtype : data-type Data type of the returned array. For binary files, it is used to determine the size and byte-order of the items in th

generic.flags integer value of flags

numpy.linalg.slogdet(a) [source] Compute the sign and (natural) logarithm of the determinant of an array. If an array has a very small or very large determinant, then a call to det may overflow or underflow. This routine is more robust against such issues, because it computes the logarithm of the determinant rather than the determinant itself. Parameters: a : (..., M, M) array_like Input array, has to be a square 2-D array. Returns: sign : (...) array_like A number representing the si

matrix.put(indices, values, mode='raise') Set a.flat[n] = values[n] for all n in indices. Refer to numpy.put for full documentation. See also numpy.put equivalent function

generic.ravel() 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

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

numpy.triu_indices(n, k=0, m=None) [source] Return the indices for the upper-triangle of an (n, m) array. Parameters: n : int The size of the arrays for which the returned indices will be valid. k : int, optional Diagonal offset (see triu for details). m : int, optional New in version 1.9.0. The column dimension of the arrays for which the returned arrays will be valid. By default m is taken equal to n. Returns: inds : tuple, shape(2) of ndarrays, shape(n) The indices for the tr

RandomState.logseries(p, size=None) Draw samples from a logarithmic series distribution. Samples are drawn from a log series distribution with specified shape parameter, 0 < p < 1. Parameters: loc : float scale : float > 0. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. Returns: samples : ndarray or scalar where the values are all integers