class numpy.lib.user_array.container(data, dtype=None, copy=True) [source] Standard container-class for easy multiple-inheritance. Methods copy tostring byteswap astype

numpy.random.negative_binomial(n, p, size=None) Draw samples from a negative binomial distribution. Samples are drawn from a negative binomial distribution with specified parameters, n trials and p probability of success where n is an integer > 0 and p is in the interval [0, 1]. Parameters: n : int Parameter, > 0. p : float Parameter, >= 0 and <=1. 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.

numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII') [source] Load arrays or pickled objects from .npy, .npz or pickled files. Parameters: file : file-like object or string The file to read. File-like objects must support the seek() and read() methods. Pickled files require that the file-like object support the readline() method as well. mmap_mode : {None, ?r+?, ?r?, ?w+?, ?c?}, optional If not None, then memory-map the file, using the given mode (see

record.max() 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

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

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

generic.size number of elements in the gentype

chararray.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.ge

numpy.polynomial.legendre.legint(c, m=1, k=[], lbnd=0, scl=1, axis=0) [source] Integrate a Legendre series. Returns the Legendre series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, is added. The scaling factor is for use in a linear change of variable. (?Buyer beware?: note that, depending on what one is doing, one may want scl to be the reciprocal of what one might expect; for more inform

recarray.repeat(repeats, axis=None) Repeat elements of an array. Refer to numpy.repeat for full documentation. See also numpy.repeat equivalent function