MaskedArray.transpose(*axes) [source] Returns a view of the array with axes transposed. For a 1-D array, this has no effect. (To change between column and row vectors, first cast the 1-D array into a matrix object.) For a 2-D array, this is the usual matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and a.shape = (i[0], i[1], ... i[n-2], i[n-1]), then a.transpose().shape = (i[n-1], i[n-2], ... i[1]

MaskedArray.compressed() [source] Return all the non-masked data as a 1-D array. Returns: data : ndarray A new ndarray holding the non-masked data is returned. Notes The result is not a MaskedArray! Examples >>> x = np.ma.array(np.arange(5), mask=[0]*2 + [1]*3) >>> x.compressed() array([0, 1]) >>> type(x.compressed()) <type 'numpy.ndarray'>

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

HermiteE.deriv(m=1) [source] Differentiate. Return a series instance of that is the derivative of the current series. Parameters: m : non-negative int Find the derivative of order m. Returns: new_series : series A new series representing the derivative. The domain is the same as the domain of the differentiated series.

numpy.core.defchararray.mod(a, values) [source] Return (a % i), that is pre-Python 2.6 string formatting (iterpolation), element-wise for a pair of array_likes of str or unicode. Parameters: a : array_like of str or unicode values : array_like of values These values will be element-wise interpolated into the string. Returns: out : ndarray Output array of str or unicode, depending on input types See also str.__mod__

classmethod HermiteE.identity(domain=None, window=None) [source] Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters: domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form [beg, end], where beg and end ar

numpy.testing.assert_warns(warning_class, *args, **kwargs) [source] Fail unless the given callable throws the specified warning. A warning of class warning_class should be thrown by the callable when invoked with arguments args and keyword arguments kwargs. If a different type of warning is thrown, it will not be caught, and the test case will be deemed to have suffered an error. If called with all arguments other than the warning class omitted, may be used as a context manager: with asser

numpy.polynomial.chebyshev.chebvander(x, deg) [source] Pseudo-Vandermonde matrix of given degree. Returns the pseudo-Vandermonde matrix of degree deg and sample points x. The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg. The leading indices of V index the elements of x and the last index is the degree of the Chebyshev polynomial. If c is a 1-D array of coefficients of length n + 1 and V is the matrix V = chebvander(x, n), then np.dot(V, c) and chebval(x, c) are the s

numpy.polynomial.chebyshev.poly2cheb(pol) [source] Convert a polynomial to a Chebyshev series. Convert an array representing the coefficients of a polynomial (relative to the ?standard? basis) ordered from lowest degree to highest, to an array of the coefficients of the equivalent Chebyshev series, ordered from lowest to highest degree. Parameters: pol : array_like 1-D array containing the polynomial coefficients Returns: c : ndarray 1-D array containing the coefficients of the equiva

See also Array creation Ones and zeros empty(shape[, dtype, order]) Return a new array of given shape and type, without initializing entries. empty_like(a[, dtype, order, subok]) Return a new array with the same shape and type as a given array. eye(N[, M, k, dtype]) Return a 2-D array with ones on the diagonal and zeros elsewhere. identity(n[, dtype]) Return the identity array. ones(shape[, dtype, order]) Return a new array of given shape and type, filled with ones. ones_like(a[, dtyp