numpy.ma.compress_rowcols(x, axis=None) [source] Suppress the rows and/or columns of a 2-D array that contain masked values. The suppression behavior is selected with the axis parameter. If axis is None, both rows and columns are suppressed. If axis is 0, only rows are suppressed. If axis is 1 or -1, only columns are suppressed. Parameters: x : array_like, MaskedArray The array to operate on. If not a MaskedArray instance (or if no array elements are masked), x is interpreted as a MaskedA

generic.__array_interface__ Array protocol: Python side

ndindex.ndincr() [source] Increment the multi-dimensional index by one. This method is for backward compatibility only: do not use.

numpy.polynomial.chebyshev.chebval(x, c, tensor=True) [source] Evaluate a Chebyshev series at points x. If c is of length n + 1, this function returns the value: The parameter x is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either x or its elements must support multiplication and addition both with themselves and with the elements of c. If c is a 1-D array, then p(x) will have the same shape as x. If c is multidimensional,

ndarray.__array_wrap__(obj) ? Object of same type as ndarray object a.

ndarray.conj() Complex-conjugate all elements. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function

numpy.source(object, output=', mode 'w' at 0x402ae078>) [source] Print or write to a file the source code for a Numpy object. The source code is only returned for objects written in Python. Many functions and classes are defined in C and will therefore not return useful information. Parameters: object : numpy object Input object. This can be any object (function, class, module, ...). output : file object, optional If output not supplied then source code is printed to screen (sys.stdo

numpy.polynomial.hermite_e.poly2herme(pol) [source] Convert a polynomial to a Hermite 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 Hermite 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 equivalen

numpy.polynomial.hermite_e.hermeder(c, m=1, scl=1, axis=0) [source] Differentiate a Hermite_e series. Returns the series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl (the scaling factor is for use in a linear change of variable). The argument c is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the series 1*He_0 + 2*He_1 + 3*He_2 while [[1,2],[1,2]] represents 1*He_0(x)*He_0(y) + 1*He_1(x)*He_0

numpy.in1d(ar1, ar2, assume_unique=False, invert=False) [source] Test whether each element of a 1-D array is also present in a second array. Returns a boolean array the same length as ar1 that is True where an element of ar1 is in ar2 and False otherwise. Parameters: ar1 : (M,) array_like Input array. ar2 : array_like The values against which to test each value of ar1. assume_unique : bool, optional If True, the input arrays are both assumed to be unique, which can speed up the calcul