recarray.repeat(repeats, axis=None) Repeat elements of an array. Refer to numpy.repeat for full documentation. See also numpy.repeat equivalent function

numpy.genfromtxt(fname, dtype=, comments='#', delimiter=None, skip_header=0, skip_footer=0, converters=None, missing_values=None, filling_values=None, usecols=None, names=None, excludelist=None, deletechars=None, replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i', unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None) [source] Load data from a text file, with missing values handled as specified. Each line past the first skip_header lines is split a

record.take() 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.T Same as self.transpose(), except that self is returned if self.ndim < 2. Examples >>> x = np.array([[1.,2.],[3.,4.]]) >>> x array([[ 1., 2.], [ 3., 4.]]) >>> x.T array([[ 1., 3.], [ 2., 4.]]) >>> x = np.array([1.,2.,3.,4.]) >>> x array([ 1., 2., 3., 4.]) >>> x.T array([ 1., 2., 3., 4.])

Background The API exposed by NumPy for third-party extensions has grown over years of releases, and has allowed programmers to directly access NumPy functionality from C. This API can be best described as ?organic?. It has emerged from multiple competing desires and from multiple points of view over the years, strongly influenced by the desire to make it easy for users to move to NumPy from Numeric and Numarray. The core API originated with Numeric in 1995 and there are patterns such as the

generic.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

chararray.ljust(width, fillchar=' ') [source] Return an array with the elements of self left-justified in a string of length width. See also char.ljust

matrix.getH() [source] Returns the (complex) conjugate transpose of self. Equivalent to np.transpose(self) if self is real-valued. Parameters: None Returns: ret : matrix object complex conjugate transpose of self Examples >>> x = np.matrix(np.arange(12).reshape((3,4))) >>> z = x - 1j*x; z matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j], [ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j], [ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]]) >>> z.get

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

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