ndarray.data Python buffer object pointing to the start of the array?s data.

numpy.testing.assert_almost_equal(actual, desired, decimal=7, err_msg='', verbose=True) [source] Raises an AssertionError if two items are not equal up to desired precision. Note It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp instead of this function for more consistent floating point comparisons. The test is equivalent to abs(desired-actual) < 0.5 * 10**(-decimal). Given two objects (numbers or ndarrays), check that all elements

flatiter.coords An N-dimensional tuple of current coordinates. Examples >>> x = np.arange(6).reshape(2, 3) >>> fl = x.flat >>> fl.coords (0, 0) >>> fl.next() 0 >>> fl.coords (0, 1)

MaskedArray.__ipow__(other) [source] Raise self to the power other, in place.

generic.item() 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

recarray.ptp(axis=None, out=None) Peak to peak (maximum - minimum) value along a given axis. Refer to numpy.ptp for full documentation. See also numpy.ptp equivalent function

numpy.argpartition(a, kth, axis=-1, kind='introselect', order=None) [source] Perform an indirect partition along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in partitioned order. New in version 1.8.0. Parameters: a : array_like Array to sort. kth : int or sequence of ints Element index to partition by. The kth element will be in its final sorted position and all smaller ele

matrix.copy(order='C') Return a copy of the array. Parameters: order : {?C?, ?F?, ?A?, ?K?}, optional Controls the memory layout of the copy. ?C? means C-order, ?F? means F-order, ?A? means ?F? if a is Fortran contiguous, ?C? otherwise. ?K? means match the layout of a as closely as possible. (Note that this function and :func:numpy.copy are very similar, but have different default values for their order= arguments.) See also numpy.copy, numpy.copyto Examples >>> x = np.array(

dtype.char A unique character code for each of the 21 different built-in types.

numpy.ma.getdata(a, subok=True) [source] Return the data of a masked array as an ndarray. Return the data of a (if any) as an ndarray if a is a MaskedArray, else return a as a ndarray or subclass (depending on subok) if not. Parameters: a : array_like Input MaskedArray, alternatively a ndarray or a subclass thereof. subok : bool Whether to force the output to be a pure ndarray (False) or to return a subclass of ndarray if appropriate (True, default). See also getmask Return the ma