pyDive.cloned_ndarray package¶
Submodules¶
pyDive.cloned_ndarray.cloned_ndarray module¶
-
class
pyDive.cloned_ndarray.cloned_ndarray.
cloned_ndarray
(shape, dtype=<type 'float'>, target_ranks='all', no_allocation=False)[source]¶ Represents a multidimensional, homogenous array of fixed-size elements which is cloned on the cluster nodes. Cloned means that every participating engine holds an independent, local numpy-array of the user-defined shape. The user can then do e.g. some manual stuff on the local arrays or some computation with
pyDive.algorithm
on them.Note that there exists no ‘original’ array as the name might suggest but something like that can be generated by
merge()
.-
__init__
(shape, dtype=<type 'float'>, target_ranks='all', no_allocation=False)[source]¶ Creates an
pyDive.cloned_ndarray.cloned_ndarray.cloned_ndarray
instance. This is a low-level method for instanciating a cloned_array. Cloned arrays should be constructed using ‘empty’, ‘zeros’ or ‘empty_targets_like’ (seepyDive.cloned_ndarray.factories
).Parameters: - shape (ints) – size of the array on each axis
- dtype (numpy-dtype) – datatype of a single data value
- target_ranks (ints) – list of engine-ids that share this array. Or ‘all’ for all engines.
- no_allocation (bool) – if
True
no actual memory, i.e. numpy-array, will be allocated on engine. Useful when you want to assign an existing numpy array manually.
-
pyDive.cloned_ndarray.factories module¶
This module holds high-level functions for instanciating pyDive.cloned_ndarrays.
-
pyDive.cloned_ndarray.factories.
empty
(shape, dtype=<type 'float'>)[source]¶ Return a new pyDive.cloned_ndarray package utilizing all engines without initializing elements.
Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
-
pyDive.cloned_ndarray.factories.
empty_engines_like
(shape, dtype, a)[source]¶ Return a new
pyDive.cloned_ndarray
utilizing the same engines a does without initializing elements.Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
- a – pyDive.arrays.ndarray module
-
pyDive.cloned_ndarray.factories.
hollow
(shape, dtype=<type 'float'>)[source]¶ - Return a new pyDive.cloned_ndarray package utilizing all engines without allocating a local
- numpy-array.
Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
-
pyDive.cloned_ndarray.factories.
hollow_engines_like
(shape, dtype, a)[source]¶ Return a new
pyDive.cloned_ndarray
utilizing the same engines a does without allocating a local numpy-array.Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
- a – pyDive.arrays.ndarray module
-
pyDive.cloned_ndarray.factories.
ones
(shape, dtype=<type 'float'>)[source]¶ Return a new pyDive.cloned_ndarray package utilizing all engines filled with ones.
Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
-
pyDive.cloned_ndarray.factories.
zeros
(shape, dtype=<type 'float'>)[source]¶ Return a new pyDive.cloned_ndarray package utilizing all engines filled with zeros.
Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
-
pyDive.cloned_ndarray.factories.
zeros_engines_like
(shape, dtype, a)[source]¶ Return a new pyDive.cloned_ndarray package utilizing the same engines a does filled with zeros.
Parameters: - shape (ints) – shape of the array
- dtype (numpy-dtype) – datatype of a single data value
- a – pyDive.arrays.ndarray module