def empty(shape, dtype=np.float):
"""Return a new :ref:`pyDive.cloned_ndarray` utilizing all engines without initializing elements.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
"""
result = cloned_ndarray.cloned_ndarray(shape, dtype, target_ranks='all')
return result
def hollow(shape, dtype=np.float):
"""Return a new :ref:`pyDive.cloned_ndarray` utilizing all engines without allocating a local
*numpy-array*.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
"""
result = cloned_ndarray.cloned_ndarray(shape, dtype, target_ranks='all', no_allocation=True)
return result
def empty_engines_like(shape, dtype, a):
"""Return a new :obj:`pyDive.cloned_ndarray` utilizing the same engines *a* does
without initializing elements.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
:param a: :ref:`pyDive.ndarray`
"""
return cloned_ndarray.cloned_ndarray(shape, dtype, a.target_ranks)
def hollow_engines_like(shape, dtype, a):
"""Return a new :obj:`pyDive.cloned_ndarray` utilizing the same engines *a* does
without allocating a local *numpy-array*.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
:param a: :ref:`pyDive.ndarray`
"""
return cloned_ndarray.cloned_ndarray(shape, dtype, a.target_ranks, True)
def ones(shape, dtype=np.float):
"""Return a new :ref:`pyDive.cloned_ndarray` utilizing all engines filled with ones.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
"""
result = cloned_ndarray.cloned_ndarray(shape, dtype, target_ranks='all', no_allocation=True)
view = com.getView()
view.push({'myshape' : shape, 'dtype' : dtype}, targets=result.target_ranks)
view.execute('%s = np.ones(myshape, dtype)' % repr(result), targets=result.target_ranks)
return result
def zeros_engines_like(shape, dtype, a):
"""Return a new :ref:`pyDive.cloned_ndarray` utilizing the same engines *a* does
filled with zeros.
:param ints shape: shape of the array
:param numpy-dtype dtype: datatype of a single data value
:param a: :ref:`pyDive.ndarray`
"""
result = cloned_ndarray.cloned_ndarray(shape, dtype, a.target_ranks, True)
view = com.getView()
view.push({'myshape' : shape, 'dtype' : dtype}, targets=result.target_ranks)
view.execute('%s = np.zeros(myshape, dtype)' % repr(result), targets=result.target_ranks)
return result