recarray.fill(value) Fill the array with a scalar value. Parameters: value : scalar All elements of a will be assigned this value. Examples >>> a = np.array([1, 2]) >>> a.fill(0) >>> a array([0, 0]) >>> a = np.empty(2) >>> a.fill(1) >>> a array([ 1., 1.])

recarray.field(attr, val=None) [source]

recarray.dumps() Returns the pickle of the array as a string. pickle.loads or numpy.loads will convert the string back to an array. Parameters: None

recarray.dump(file) Dump a pickle of the array to the specified file. The array can be read back with pickle.load or numpy.load. Parameters: file : str A string naming the dump file.

recarray.dtype Data-type of the array?s elements. Parameters: None Returns: d : numpy dtype object See also numpy.dtype Examples >>> x array([[0, 1], [2, 3]]) >>> x.dtype dtype('int32') >>> type(x.dtype) <type 'numpy.dtype'>

recarray.dot(b, out=None) Dot product of two arrays. Refer to numpy.dot for full documentation. See also numpy.dot equivalent function Examples >>> a = np.eye(2) >>> b = np.ones((2, 2)) * 2 >>> a.dot(b) array([[ 2., 2.], [ 2., 2.]]) This array method can be conveniently chained: >>> a.dot(b).dot(b) array([[ 8., 8.], [ 8., 8.]])

recarray.diagonal(offset=0, axis1=0, axis2=1) Return specified diagonals. In NumPy 1.9 the returned array is a read-only view instead of a copy as in previous NumPy versions. In a future version the read-only restriction will be removed. Refer to numpy.diagonal for full documentation. See also numpy.diagonal equivalent function

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

recarray.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

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