hysop.backend.host.fortran.fortran_operator module

Abstract class providing a common interface to all discrete operators working with fortran.

• FortranOperator is an abstract class

  used to provide a common interface to all discrete operators working with fortran.

class hysop.backend.host.fortran.fortran_operator.FortranOperator(cl_env=None, **kwds)

Bases: HostOperator

Abstract class for discrete operators working with fortran.

Create the common attributes of all host operators.

All input and output variable topologies should be of kind Backend.HOST and share the same HostEnvironment.

check_dfield_memory_order(df)

check_memory_order()

discretize()

By default, an operator discretize all its variables. For each input continuous field that is also an output field, input topology may be different from the output topology.

After this call, one can access self.input_discrete_fields and self.output_discrete_fields, which contains input and output dicretised fields mapped by continuous fields.

self.discrete_fields will be a tuple containing all input and output discrete fields.

Discrete tensor fields are built back from discretized scalar fields and are accessible from self.input_tensor_fields, self.output_tensor_fields and self.discrete_tensor_fields like their scalar counterpart.

get_field_requirements()

Called just after handle_method(), ie self.method has been set. Field requirements are:

1. required local and global transposition state, if any.

2. required memory ordering (either C or Fortran)

Default is Backend.HOST, no min or max ghosts, MemoryOrdering.ANY and no specific default transposition state for each input and output variables.

setup(work)

Setup temporary buffer that have been requested in get_work_properties(). This function may be used to execute post allocation routines. This sets self.ready flag to True. Once this flag is set one may call ComputationalGraphNode.apply() and ComputationalGraphNode.finalize().

Automatically honour temporary field memory requests.