pyop2.types package

Submodules

pyop2.types.access module

class pyop2.types.access.Access(value)

Bases: IntEnum

An enumeration.

READ = 1
WRITE = 2
RW = 3
INC = 4
MIN = 5
MAX = 6
pyop2.types.access.READ = Access.READ

The Global, Dat, or Mat is accessed read-only.

pyop2.types.access.WRITE = Access.WRITE

The Global, Dat, or Mat is accessed write-only, and OP2 is not required to handle write conflicts.

pyop2.types.access.RW = Access.RW

The Global, Dat, or Mat is accessed for reading and writing, and OP2 is not required to handle write conflicts.

pyop2.types.access.INC = Access.INC

The kernel computes increments to be summed onto a Global, Dat, or Mat. OP2 is responsible for managing the write conflicts caused.

pyop2.types.access.MIN = Access.MIN

The kernel contributes to a reduction into a Global using a min operation. OP2 is responsible for reducing over the different kernel invocations.

pyop2.types.access.MAX = Access.MAX

The kernel contributes to a reduction into a Global using a max operation. OP2 is responsible for reducing over the different kernel invocations.

pyop2.types.dat module

class pyop2.types.dat.AbstractDat(dataset, data=None, dtype=None, name=None)

Bases: DataCarrier, EmptyDataMixin, ABC

OP2 vector data. A Dat holds values on every element of a DataSet.o

If a Set is passed as the dataset argument, rather than a DataSet, the Dat is created with a default DataSet dimension of 1.

If a Dat is passed as the dataset argument, a copy is returned.

It is permissible to pass None as the data argument. In this case, allocation of the data buffer is postponed until it is accessed.

Note

If the data buffer is not passed in, it is implicitly initialised to be zero.

When a Dat is passed to pyop2.op2.par_loop(), the map via which indirection occurs and the access descriptor are passed by calling the Dat. For instance, if a Dat named D is to be accessed for reading via a Map named M, this is accomplished by

D(pyop2.READ, M)

The Map through which indirection occurs can be indexed using the index notation described in the documentation for the Map. Direct access to a Dat is accomplished by omitting the path argument.

Dat objects support the pointwise linear algebra operations +=, *=, -=, /=, where *= and /= also support multiplication / division by a scalar.

split

Tuple containing only this Dat.

dataset

DataSet on which the Dat is defined.

dim

The shape of the values for each element of the object.

cdim

The scalar number of values for each member of the object. This is the product of the dim tuple.

property data

Numpy array containing the data values.

With this accessor you are claiming that you will modify the values you get back. If you only need to look at the values, use data_ro() instead.

This only shows local values, to see the halo values too use data_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_with_halos

A view of this Dats data.

This accessor marks the Dat as dirty, see data() for more details on the semantics.

With this accessor, you get to see up to date halo values, but you should not try and modify them, because they will be overwritten by the next halo exchange.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro

Numpy array containing the data values. Read-only.

With this accessor you are not allowed to modify the values you get back. If you need to do so, use data() instead.

This only shows local values, to see the halo values too use data_ro_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro_with_halos

A view of this Dats data.

This accessor does not mark the Dat as dirty, and is a read only view, see data_ro() for more details on the semantics.

With this accessor, you get to see up to date halo values, but you should not try and modify them, because they will be overwritten by the next halo exchange.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo

Numpy array containing the data values that is only valid for writing to.

This only shows local values, to see the halo values too use data_wo_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo_with_halos

Return a write-only view of all the data values.

This method, unlike data_with_halos(), avoids a halo exchange if the halo is dirty.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

save(filename)

Write the data array to file filename in NumPy format.

load(filename)

Read the data stored in file filename into a NumPy array and store the values in _data().

shape
dtype
nbytes

Return an estimate of the size of the data associated with this Dat in bytes. This will be the correct size of the data payload, but does not take into account the (presumably small) overhead of the object and its metadata.

Note that this is the process local memory usage, not the sum over all MPI processes.

zero(subset=None)

Zero the data associated with this Dat

Parameters:

subset – A Subset of entries to zero (optional).

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

copy(other, subset=None)

Copy the data in this Dat into another.

Parameters:
  • other – The destination Dat

  • subset – A Subset of elements to copy (optional)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

inner(other)

Compute the l2 inner product of the flattened Dat

Parameters:

other – the other Dat to compute the inner product against. The complex conjugate of this is taken.

property norm

Compute the l2 norm of this Dat

Note

This acts on the flattened data (see also inner()).

global_to_local_begin(access_mode)

Begin a halo exchange from global to ghosted representation.

Parameters:

access_mode – Mode with which the data will subsequently be accessed.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

global_to_local_end(access_mode)

End a halo exchange from global to ghosted representation.

Parameters:

access_mode – Mode with which the data will subsequently be accessed.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_begin(insert_mode)

Begin a halo exchange from ghosted to global representation.

Parameters:

insert_mode – insertion mode (an access descriptor)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_end(insert_mode)

End a halo exchange from ghosted to global representation.

Parameters:

insert_mode – insertion mode (an access descriptor)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

frozen_halo(access_mode)

Temporarily disable halo exchanges inside a context manager.

Parameters:

access_mode – Mode with which the data will subsequently be accessed.

This is useful in cases where one is repeatedly writing to a Dat with the same access descriptor since the intermediate updates can be skipped.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

freeze_halo(access_mode)

Disable halo exchanges.

Parameters:

access_mode – Mode with which the data will subsequently be accessed.

Note that some bookkeeping is needed when freezing halos. Prefer to use the Dat.frozen_halo() context manager.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

unfreeze_halo()

Re-enable halo exchanges.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

class pyop2.types.dat.DatView(dat, index)

Bases: AbstractDat

An indexed view into a Dat.

This object can be used like a Dat but the kernel will only see the requested index, rather than the full data.

Parameters:
  • dat – The Dat to create a view into.

  • index – The component to select a view of.

cdim
dim
shape
property halo_valid
property data

Numpy array containing the data values.

With this accessor you are claiming that you will modify the values you get back. If you only need to look at the values, use data_ro() instead.

This only shows local values, to see the halo values too use data_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro

Numpy array containing the data values. Read-only.

With this accessor you are not allowed to modify the values you get back. If you need to do so, use data() instead.

This only shows local values, to see the halo values too use data_ro_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo

Numpy array containing the data values that is only valid for writing to.

This only shows local values, to see the halo values too use data_wo_with_halos().

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_with_halos

A view of this Dats data.

This accessor marks the Dat as dirty, see data() for more details on the semantics.

With this accessor, you get to see up to date halo values, but you should not try and modify them, because they will be overwritten by the next halo exchange.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro_with_halos

A view of this Dats data.

This accessor does not mark the Dat as dirty, and is a read only view, see data_ro() for more details on the semantics.

With this accessor, you get to see up to date halo values, but you should not try and modify them, because they will be overwritten by the next halo exchange.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo_with_halos

Return a write-only view of all the data values.

This method, unlike data_with_halos(), avoids a halo exchange if the halo is dirty.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

class pyop2.types.dat.Dat(*args, **kwargs)

Bases: AbstractDat, VecAccessMixin

vec_context(access)

A context manager for a PETSc.Vec from a Dat.

Parameters:

access – Access descriptor: READ, WRITE, or RW.

class pyop2.types.dat.MixedDat(mdset_or_dats)

Bases: AbstractDat, VecAccessMixin

A container for a bag of Dats.

Initialized either from a MixedDataSet, a MixedSet, or an iterable of DataSets and/or Sets, where all the Sets are implcitly upcast to DataSets

mdat = op2.MixedDat(mdset)
mdat = op2.MixedDat([dset1, ..., dsetN])

or from an iterable of Dats

mdat = op2.MixedDat([dat1, ..., datN])
property dat_version
increment_dat_version()
dtype

The NumPy dtype of the data.

split

The underlying tuple of Dats.

dataset

MixedDataSets this MixedDat is defined on.

property data

Numpy arrays containing the data excluding halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_with_halos

Numpy arrays containing the data including halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro

Numpy arrays with read-only data excluding halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_ro_with_halos

Numpy arrays with read-only data including halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo

Numpy arrays with read-only data excluding halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property data_wo_with_halos

Numpy arrays with read-only data including halos.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property halo_valid

Does this Dat have up to date halos?

global_to_local_begin(access_mode)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

global_to_local_end(access_mode)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_begin(insert_mode)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_end(insert_mode)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

freeze_halo(access_mode)

Disable halo exchanges.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

unfreeze_halo()

Re-enable halo exchanges.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

zero(subset=None)

Zero the data associated with this MixedDat.

Parameters:

subset – optional subset of entries to zero (not implemented).

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

nbytes

Return an estimate of the size of the data associated with this MixedDat in bytes. This will be the correct size of the data payload, but does not take into account the (presumably small) overhead of the object and its metadata.

Note that this is the process local memory usage, not the sum over all MPI processes.

copy(other, subset=None)

Copy the data in this MixedDat into another.

Parameters:
  • other – The destination MixedDat

  • subset – Subsets are not supported, this must be None

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

inner(other)

Compute the l2 inner product.

Parameters:

other – the other MixedDat to compute the inner product against

vec_context(access)

A context manager scattering the arrays of all components of this MixedDat into a contiguous PETSc.Vec and reverse scattering to the original arrays when exiting the context.

Parameters:

access – Access descriptor: READ, WRITE, or RW.

Note

The Vec obtained from this context is in the correct order to be left multiplied by a compatible MixedMat. In parallel it is not just a concatenation of the underlying Dats.

class pyop2.types.dat.frozen_halo(dat, access_mode)

Bases: object

Context manager handling the freezing and unfreezing of halos.

Parameters:
  • dat – The Dat whose halo is to be frozen.

  • access_mode – Mode with which the Dat will be accessed whilst its halo is frozen.

pyop2.types.data_carrier module

class pyop2.types.data_carrier.DataCarrier

Bases: ABC

Abstract base class for OP2 data.

Actual objects will be DataCarrier objects of rank 0 (Global), rank 1 (Dat), or rank 2 (Mat)

dtype

The Python type of the data.

ctype

The c type of the data.

name

User-defined label.

dim

The shape tuple of the values for each element of the object.

cdim

The scalar number of values for each member of the object. This is the product of the dim tuple.

increment_dat_version()
class pyop2.types.data_carrier.EmptyDataMixin(data, dtype, shape)

Bases: ABC

A mixin for Dat and Global objects that takes care of allocating data on demand if the user has passed nothing in.

Accessing the _data property allocates a zeroed data array if it does not already exist.

class pyop2.types.data_carrier.VecAccessMixin(petsc_counter=None)

Bases: ABC

property dat_version
abstract vec_context(access)
property vec

Context manager for a PETSc Vec appropriate for this Dat.

You’re allowed to modify the data you get back from this view.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property vec_wo

Context manager for a PETSc Vec appropriate for this Dat.

You’re allowed to modify the data you get back from this view, but you cannot read from it.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property vec_ro

Context manager for a PETSc Vec appropriate for this Dat.

You’re not allowed to modify the data you get back from this view.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

pyop2.types.dataset module

class pyop2.types.dataset.DataSet(*args, **kwargs)

Bases: ObjectCached

PyOP2 Data Set

Set used in the op2.Dat structures to specify the dimension of the data.

dim

The shape tuple of the values for each element of the set.

cdim

The scalar number of values for each member of the set. This is the product of the dim tuple.

name

Returns the name of the data set.

set

Returns the parent set of the data set.

lgmap

A PETSc LGMap mapping process-local indices to global indices for this DataSet.

scalar_lgmap
unblocked_lgmap

A PETSc LGMap mapping process-local indices to global indices for this DataSet with a block size of 1.

field_ises

A list of PETSc ISes defining the global indices for each set in the DataSet.

Used when extracting blocks from matrices for solvers.

local_ises

A list of PETSc ISes defining the local indices for each set in the DataSet.

Used when extracting blocks from matrices for assembly.

layout_vec

A PETSc Vec compatible with the dof layout of this DataSet.

dm
class pyop2.types.dataset.GlobalDataSet(*args, **kwargs)

Bases: DataSet

A proxy DataSet for use in a Sparsity where the matrix has Global rows or columns.

Parameters:

global – The Global on which this object is based.

dim

The shape tuple of the values for each element of the set.

cdim

The scalar number of values for each member of the set. This is the product of the dim tuple.

name

Returns the name of the data set.

set

Returns the parent set of the data set.

size

The number of local entries in the Dataset (1 on rank 0)

lgmap

A PETSc LGMap mapping process-local indices to global indices for this DataSet.

unblocked_lgmap

A PETSc LGMap mapping process-local indices to global indices for this DataSet with a block size of 1.

local_ises

A list of PETSc ISes defining the local indices for each set in the DataSet.

Used when extracting blocks from matrices for assembly.

layout_vec

A PETSc Vec compatible with the dof layout of this DataSet.

dm
class pyop2.types.dataset.MixedDataSet(*args, **kwargs)

Bases: DataSet

A container for a bag of DataSets.

Initialized either from a MixedSet and an iterable or iterator of dims of corresponding length

mdset = op2.MixedDataSet(mset, [dim1, ..., dimN])

or from a tuple of Sets and an iterable of dims of corresponding length

mdset = op2.MixedDataSet([set1, ..., setN], [dim1, ..., dimN])

If all dims are to be the same, they can also be given as an int for either of above invocations

mdset = op2.MixedDataSet(mset, dim)
mdset = op2.MixedDataSet([set1, ..., setN], dim)

Initialized from a MixedSet without explicitly specifying dims they default to 1

mdset = op2.MixedDataSet(mset)

Initialized from an iterable or iterator of DataSets and/or Sets, where Sets are implicitly upcast to DataSets of dim 1

mdset = op2.MixedDataSet([dset1, ..., dsetN])
Parameters:
  • arg – a MixedSet or an iterable or a generator expression of Sets or DataSets or a mixture of both

  • dimsNone (the default) or an int or an iterable or generator expression of ints, which must be of same length as arg

Warning

When using generator expressions for arg or dims, these must terminate or else will cause an infinite loop.

split

The underlying tuple of DataSets.

dim

The shape tuple of the values for each element of the sets.

cdim

The sum of the scalar number of values for each member of the sets. This is the sum of products of the dim tuples.

name

Returns the name of the data sets.

set

Returns the MixedSet this MixedDataSet is defined on.

layout_vec

A PETSc Vec compatible with the dof layout of this MixedDataSet.

lgmap

A PETSc LGMap mapping process-local indices to global indices for this MixedDataSet.

unblocked_lgmap

A PETSc LGMap mapping process-local indices to global indices for this DataSet with a block size of 1.

pyop2.types.glob module

class pyop2.types.glob.SetFreeDataCarrier(dim, data=None, dtype=None, name=None)

Bases: DataCarrier, EmptyDataMixin

property shape
property dtype

The Python type of the data.

property data_ro

Data array.

property data_wo
property data

Data array.

property data_with_halos
property data_ro_with_halos
property data_wo_with_halos
property halo_valid
copy(other, subset=None)

Copy the data in this SetFreeDataCarrier into another.

Parameters:
  • other – The destination Global

  • subset – A Subset of elements to copy (optional)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

property split
property nbytes

Return an estimate of the size of the data associated with this Global in bytes. This will be the correct size of the data payload, but does not take into account the overhead of the object and its metadata. This renders this method of little statistical significance, however it is included to make the interface consistent.

inner(other)
class pyop2.types.glob.Global(dim, data=None, dtype=None, name=None, comm=None)

Bases: SetFreeDataCarrier, VecAccessMixin

OP2 global value.

When a Global is passed to a pyop2.op2.par_loop(), the access descriptor is passed by calling the Global. For example, if a Global named G is to be accessed for reading, this is accomplished by:

G(pyop2.READ)

It is permissible to pass None as the data argument. In this case, allocation of the data buffer is postponed until it is accessed.

Note

If the data buffer is not passed in, it is implicitly initialised to be zero.

dataset
duplicate()

Return a deep copy of self.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

zero(subset=None)

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

global_to_local_begin(access_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

global_to_local_end(access_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_begin(insert_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

local_to_global_end(insert_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

frozen_halo(access_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

freeze_halo(access_mode)

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

unfreeze_halo()

Dummy halo operation for the case in which a Global forms part of a MixedDat.

This function is logically collective over MPI ranks, it is an error to call it on fewer than all the ranks in MPI communicator.

vec_context(access)

A context manager for a PETSc.Vec from a Global.

Parameters:

access – Access descriptor: READ, WRITE, or RW.

class pyop2.types.glob.Constant(dim, data=None, dtype=None, name=None, comm=None)

Bases: SetFreeDataCarrier

OP2 constant value.

When a Constant is passed to a pyop2.op2.par_loop(), the access descriptor is always Access.READ. Used in cases where collective functionality is not required, or is not desirable. For example: objects with no associated mesh and do not have a communicator.

duplicate()

Return a deep copy of self.

pyop2.types.halo module

class pyop2.types.halo.Halo

Bases: ABC

A description of a halo associated with a pyop2.types.set.Set.

The halo object describes which pyop2.types.set.Set elements are sent where, and which pyop2.types.set.Set elements are received from where.

abstract property comm

The MPI communicator for this halo.

abstract property local_to_global_numbering

The mapping from process-local to process-global numbers for this halo.

abstract global_to_local_begin(dat, insert_mode)

Begin an exchange from global (assembled) to local (ghosted) representation.

Parameters:
abstract global_to_local_end(dat, insert_mode)

Finish an exchange from global (assembled) to local (ghosted) representation.

Parameters:
abstract local_to_global_begin(dat, insert_mode)

Begin an exchange from local (ghosted) to global (assembled) representation.

Parameters:
abstract local_to_global_end(dat, insert_mode)

Finish an exchange from local (ghosted) to global (assembled) representation.

Parameters:

pyop2.types.map module

class pyop2.types.map.Map(iterset, toset, arity, values=None, name=None, offset=None, offset_quotient=None)

Bases: object

OP2 map, a relation between two Set objects.

Each entry in the iterset maps to arity entries in the toset. When a map is used in a pyop2.op2.par_loop(), it is possible to use Python index notation to select an individual entry on the right hand side of this map. There are three possibilities:

  • No index. All arity Dat entries will be passed to the kernel.

  • An integer: some_map[n]. The n th entry of the map result will be passed to the kernel.

dtype = dtype('int32')
split
iterset

Set mapped from.

toset

Set mapped to.

arity

Arity of the mapping: number of toset elements mapped to per iterset element.

arities

Arity of the mapping: number of toset elements mapped to per iterset element.

Return type:

tuple

arange

Tuple of arity offsets for each constituent Map.

values

Mapping array.

This only returns the map values for local points, to see the halo points too, use values_with_halo().

values_with_halo

Mapping array.

This returns all map values (including halo points), see values() if you only need to look at the local points.

name

User-defined label

offset

The vertical offset.

offset_quotient

The offset quotient.

flattened_maps

Return all component maps.

This is useful to flatten nested :class:`ComposedMap`s.

class pyop2.types.map.PermutedMap(map_, permutation)

Bases: Map

Composition of a standard Map with a constant permutation.

Parameters:
  • map – The map to permute.

  • permutation – The permutation of the map indices.

Where normally staging to element data is performed as

local[i] = global[map[i]]

With a PermutedMap we instead get

local[i] = global[map[permutation[i]]]

This might be useful if your local kernel wants data in a different order to the one that the map provides, and you don’t want two global-sized data structures.

class pyop2.types.map.ComposedMap(*maps_, name=None)

Bases: Map

Composition of :class:`Map`s, :class:`PermutedMap`s, and/or :class:`ComposedMap`s.

Parameters:

maps – The maps to compose.

Where normally staging to element data is performed as

local[i] = global[map[i]]

With a ComposedMap we instead get

local[i] = global[maps_[0][maps_[1][maps_[2][...[i]]]]]

This might be useful if the map you want can be represented by a composition of existing maps.

values
values_with_halo
flattened_maps
class pyop2.types.map.MixedMap(*args, **kwargs)

Bases: Map, ObjectCached

A container for a bag of Maps.

Parameters:

maps (iterable) – Iterable of Maps

split

The underlying tuple of Maps.

iterset

MixedSet mapped from.

toset

MixedSet mapped to.

arity

Arity of the mapping: total number of toset elements mapped to per iterset element.

arities

Arity of the mapping: number of toset elements mapped to per iterset element.

Return type:

tuple

arange

Tuple of arity offsets for each constituent Map.

values

Mapping arrays excluding data for halos.

This only returns the map values for local points, to see the halo points too, use values_with_halo().

values_with_halo

Mapping arrays including data for halos.

This returns all map values (including halo points), see values() if you only need to look at the local points.

name

User-defined labels

offset

Vertical offsets.

offset_quotient

Offsets quotient.

flattened_maps

pyop2.types.mat module

pyop2.types.set module

class pyop2.types.set.Set(size, name=None, halo=None, comm=None)

Bases: object

OP2 set.

Parameters:
  • size (integer or list of four integers.) – The size of the set.

  • name (string) – The name of the set (optional).

  • halo – An exisiting halo to use (optional).

When the set is employed as an iteration space in a pyop2.op2.par_loop(), the extent of any local iteration space within each set entry is indicated in brackets. See the example in pyop2.op2.par_loop() for more details.

The size of the set can either be an integer, or a list of four integers. The latter case is used for running in parallel where we distinguish between:

  • CORE (owned and not touching halo)

  • OWNED (owned, touching halo)

  • EXECUTE HALO (not owned, but executed over redundantly)

  • NON EXECUTE HALO (not owned, read when executing in the execute halo)

If a single integer is passed, we assume that we’re running in serial and there is no distinction.

The division of set elements is:

[0, CORE)
[CORE, OWNED)
[OWNED, GHOST)

Halo send/receive data is stored on sets in a Halo.

core_size

Core set size. Owned elements not touching halo elements.

size

Set size, owned elements.

total_size

Set size including ghost elements.

sizes

Set sizes: core, owned, execute halo, total.

core_part
owned_part
name

User-defined label

halo

Halo associated with this Set

property partition_size

Default partition size

layers

Return None (not an ExtrudedSet).

intersection(other)
union(other)
difference(other)
symmetric_difference(other)
class pyop2.types.set.GlobalSet(comm=None)

Bases: Set

core_size
size
total_size

Total set size, including halo elements.

sizes

Set sizes: core, owned, execute halo, total.

name

User-defined label

halo

Halo associated with this Set

property partition_size

Default partition size

class pyop2.types.set.ExtrudedSet(parent, layers, extruded_periodic=False)

Bases: Set

OP2 ExtrudedSet.

Parameters:
  • parent (a Set.) – The parent Set to build this ExtrudedSet on top of

  • layers (an integer, indicating the number of layers for every entity, or an array of shape (parent.total_size, 2) giving the start and one past the stop layer for every entity. An entry a, b = layers[e, ...] means that the layers for entity e run over [a, b).) – The number of layers in this ExtrudedSet.

The number of layers indicates the number of time the base set is extruded in the direction of the ExtrudedSet. As a result, there are layers-1 extruded “cells” in an extruded set.

parent
layers

The layers of this extruded set.

layers_array
class pyop2.types.set.Subset(superset, indices)

Bases: ExtrudedSet

OP2 subset.

Parameters:
  • superset (a Set or a Subset.) – The superset of the subset.

  • indices (a list of integers, or a numpy array.) – Elements of the superset that form the subset. Duplicate values are removed when constructing the subset.

superset

Returns the superset Set

indices

Returns the indices pointing in the superset.

owned_indices

Return the indices that correspond to the owned entities of the superset.

layers_array
intersection(other)
union(other)
difference(other)
symmetric_difference(other)
class pyop2.types.set.SetPartition(set, offset, size)

Bases: object

class pyop2.types.set.MixedSet(*args, **kwargs)

Bases: Set, ObjectCached

A container for a bag of Sets.

Parameters:

sets (iterable) – Iterable of Sets or ExtrudedSets

split

The underlying tuple of Sets.

core_size

Core set size. Owned elements not touching halo elements.

size

Set size, owned elements.

total_size

Total set size, including halo elements.

sizes

Set sizes: core, owned, execute halo, total.

name

User-defined labels.

halo

Halos associated with these Sets.

layers

Numbers of layers in the extruded mesh (or None if this MixedSet is not extruded).

Module contents