numpy.real(val) [source] Return the real part of the elements of the array. Parameters: val : array_like Input array. Returns: out : ndarray Output array. If val is real, the type of val is used for the output. If val has complex elements, the returned type is float. See also real_if_close, imag, angle Examples >>> a = np.array([1+2j, 3+4j, 5+6j]) >>> a.real array([ 1., 3., 5.]) >>> a.real = 9 >>> a array([ 9.+2.j, 9.+4.j, 9.+6.j]) >>&

MaskedArray.flatten(order='C') [source] Return a copy of the array collapsed into one dimension. Parameters: order : {?C?, ?F?, ?A?, ?K?}, optional ?C? means to flatten in row-major (C-style) order. ?F? means to flatten in column-major (Fortran- style) order. ?A? means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ?K? means to flatten a in the order the elements occur in memory. The default is ?C?. Returns: y : ndarray A copy of the

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.apply_over_axes(func, a, axes) [source] Apply a function repeatedly over multiple axes. func is called as res = func(a, axis), where axis is the first element of axes. The result res of the function call must have either the same dimensions as a or one less dimension. If res has one less dimension than a, a dimension is inserted before axis. The call to func is then repeated for each axis in axes, with res as the first argument. Parameters: func : function This function must take tw

generic.choose() 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

numpy.savez_compressed(file, *args, **kwds) [source] Save several arrays into a single file in compressed .npz format. If keyword arguments are given, then filenames are taken from the keywords. If arguments are passed in with no keywords, then stored file names are arr_0, arr_1, etc. Parameters: file : str File name of .npz file. args : Arguments Function arguments. kwds : Keyword arguments Keywords. See also numpy.savez Save several arrays into an uncompressed .npz file format

generic.base base object

record.byteswap() 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

ndarray.__or__ x.__or__(y) <==> x|y

ndarray.__setitem__ x.__setitem__(i, y) <==> x[i]=y