remove obsolete code

nifty/data_objects/my_own_do.py

-import numpy as np
-from .random import Random
-
-
-class data_object(object):
-    def __init__(self, npdata):
-        self._data = np.asarray(npdata)
-
-    @property
-    def dtype(self):
-        return self._data.dtype
-
-    @property
-    def shape(self):
-        return self._data.shape
-
-    @property
-    def size(self):
-        return self._data.size
-
-    @property
-    def real(self):
-        return data_object(self._data.real)
-
-    @property
-    def imag(self):
-        return data_object(self._data.imag)
-
-    def _contraction_helper(self, op, axis):
-        if axis is not None:
-            if len(axis) == len(self._data.shape):
-                axis = None
-        if axis is None:
-            return getattr(self._data, op)()
-
-        # perform the contraction on the data
-        data = getattr(self._data, op)(axis=axis)
-
-        # check if the result is scalar or if a result_field must be constr.
-        if np.isscalar(data):
-            return data
-        else:
-            return data_object(data)
-
-    def fill(self, fill_value):
-        self._data.fill(fill_value)
-
-    def sum(self, axis=None):
-        return self._contraction_helper("sum", axis)
-
-    def _binary_helper(self, other, op):
-        a = self._data
-        if isinstance(other, data_object):
-            b = other._data
-            if a.shape != b.shape:
-                raise ValueError("shapes are incompatible.")
-        else:
-            b = other
-
-        tval = getattr(a, op)(b)
-        return self if tval is a else data_object(tval)
-
-    def __add__(self, other):
-        return self._binary_helper(other, op='__add__')
-
-    def __radd__(self, other):
-        return self._binary_helper(other, op='__radd__')
-
-    def __iadd__(self, other):
-        return self._binary_helper(other, op='__iadd__')
-
-    def __sub__(self, other):
-        return self._binary_helper(other, op='__sub__')
-
-    def __rsub__(self, other):
-        return self._binary_helper(other, op='__rsub__')
-
-    def __isub__(self, other):
-        return self._binary_helper(other, op='__isub__')
-
-    def __mul__(self, other):
-        return self._binary_helper(other, op='__mul__')
-
-    def __rmul__(self, other):
-        return self._binary_helper(other, op='__rmul__')
-
-    def __imul__(self, other):
-        return self._binary_helper(other, op='__imul__')
-
-    def __div__(self, other):
-        return self._binary_helper(other, op='__div__')
-
-    def __rdiv__(self, other):
-        return self._binary_helper(other, op='__rdiv__')
-
-    def __idiv__(self, other):
-        return self._binary_helper(other, op='__idiv__')
-
-    def __truediv__(self, other):
-        return self._binary_helper(other, op='__truediv__')
-
-    def __rtruediv__(self, other):
-        return self._binary_helper(other, op='__rtruediv__')
-
-    def __pow__(self, other):
-        return self._binary_helper(other, op='__pow__')
-
-    def __rpow__(self, other):
-        return self._binary_helper(other, op='__rpow__')
-
-    def __ipow__(self, other):
-        return self._binary_helper(other, op='__ipow__')
-
-    def __eq__(self, other):
-        return self._binary_helper(other, op='__eq__')
-
-    def __ne__(self, other):
-        return self._binary_helper(other, op='__ne__')
-
-    def __neg__(self):
-        return data_object(-self._data)
-
-    def __abs__(self):
-        return data_object(np.abs(self._data))
-
-    def all(self):
-        return self._data.all()
-
-    def any(self):
-        return self._data.any()
-
-
-def full(shape, fill_value, dtype=None):
-    return data_object(np.full(shape, fill_value, dtype))
-
-
-def empty(shape, dtype=np.float):
-    return data_object(np.empty(shape, dtype))
-
-
-def zeros(shape, dtype=np.float):
-    return data_object(np.zeros(shape, dtype))
-
-
-def ones(shape, dtype=np.float):
-    return data_object(np.ones(shape, dtype))
-
-
-def empty_like(a, dtype=None):
-    return data_object(np.empty_like(a._data, dtype))
-
-
-def vdot(a, b):
-    return np.vdot(a._data, b._data)
-
-
-def _math_helper(x, function, out):
-    if out is not None:
-        function(x._data, out=out._data)
-        return out
-    else:
-        return data_object(function(x._data))
-
-
-def abs(a, out=None):
-    return _math_helper(a, np.abs, out)
-
-
-def exp(a, out=None):
-    return _math_helper(a, np.exp, out)
-
-
-def log(a, out=None):
-    return _math_helper(a, np.log, out)
-
-
-def sqrt(a, out=None):
-    return _math_helper(a, np.sqrt, out)
-
-
-def bincount(x, weights=None, minlength=None):
-    if weights is not None:
-        weights = weights._data
-    res = np.bincount(x._data, weights, minlength)
-    return data_object(res)
-
-
-def from_object(object, dtype=None, copy=True):
-    return data_object(np.array(object._data, dtype=dtype, copy=copy))
-
-
-def from_random(random_type, shape, dtype=np.float64, **kwargs):
-    generator_function = getattr(Random, random_type)
-    return data_object(generator_function(dtype=dtype, shape=shape, **kwargs))
-
-
-def local_data(arr):
-    return arr._data
-
-
-def ibegin(arr):
-    return (0,)*arr._data.ndim
-
-
-def np_allreduce_sum(arr):
-    return arr
-
-
-def distaxis(arr):
-    return -1
-
-
-def from_local_data(shape, arr, distaxis):
-    if shape != arr.shape:
-        raise ValueError
-    return data_object(arr)
-
-
-def from_global_data(arr, distaxis=-1):
-    return data_object(arr)
-
-
-def to_global_data(arr):
-    return arr._data
-
-
-def redistribute(arr, dist=None, nodist=None):
-    return arr
-
-
-def default_distaxis():
-    return -1
-
-
-def local_shape(glob_shape, distaxis):
-    return glob_shape