numpy.histogram(a, bins=10, range=None, normed=False, weights=None, density=None) [source] Compute the histogram of a set of data. Parameters: a : array_like Input data. The histogram is computed over the flattened array. bins : int or sequence of scalars or str, optional If bins is an int, it defines the number of equal-width bins in the given range (10, by default). If bins is a sequence, it defines the bin edges, including the rightmost edge, allowing for non-uniform bin widths. New

numpy.exp(x[, out]) = Calculate the exponential of all elements in the input array. Parameters: x : array_like Input values. Returns: out : ndarray Output array, element-wise exponential of x. See also expm1 Calculate exp(x) - 1 for all elements in the array. exp2 Calculate 2**x for all elements in the array. Notes The irrational number e is also known as Euler?s number. It is approximately 2.718281, and is the base of the natural logarithm, ln (this means that, if , then .

numpy.all(a, axis=None, out=None, keepdims=False) [source] Test whether all array elements along a given axis evaluate to True. Parameters: a : array_like Input array or object that can be converted to an array. axis : None or int or tuple of ints, optional Axis or axes along which a logical AND reduction is performed. The default (axis = None) is to perform a logical AND over all the dimensions of the input array. axis may be negative, in which case it counts from the last to the first

numpy.polynomial.hermite_e.hermeval3d(x, y, z, c) [source] Evaluate a 3-D Hermite_e series at points (x, y, z). This function returns the values: The parameters x, y, and z 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, y, and z or their elements must support multiplication and addition both with themselves and with the elements of c. If c has fewer than 3 di

record.pprint() [source] Pretty-print all fields.

numpy.polynomial.chebyshev.chebx = array([0, 1])

vectorize.__call__(*args, **kwargs) [source] Return arrays with the results of pyfunc broadcast (vectorized) over args and kwargs not in excluded.

class numpy.recarray [source] Construct an ndarray that allows field access using attributes. Arrays may have a data-types containing fields, analogous to columns in a spread sheet. An example is [(x, int), (y, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['x'] and arr['y']. Record arrays allow the fields to be accessed as members of the array, using arr.x and arr.y. Parameters: shape : tuple

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

numpy.polynomial.legendre.legfit(x, y, deg, rcond=None, full=False, w=None) [source] Least squares fit of Legendre series to data. Return the coefficients of a Legendre series of degree deg that is the least squares fit to the data values y given at points x. If y is 1-D the returned coefficients will also be 1-D. If y is 2-D multiple fits are done, one for each column of y, and the resulting coefficients are stored in the corresponding columns of a 2-D return. The fitted polynomial(s) are