"""
Distributed components.
Components that are used in multiple places for testing distributed components.
"""
import numpy as np
import openmdao.api as om
from openmdao.utils.array_utils import evenly_distrib_idxs
[docs]class DistribComp(om.ExplicitComponent):
"""Simple Distributed Component."""
[docs] def initialize(self):
self.options.declare('size', types=int, default=1,
desc="Size of input and output vectors.")
[docs] def setup(self):
comm = self.comm
rank = comm.rank
size = self.options['size']
# if comm.size is 2 and size is 15, this results in
# 8 entries for proc 0 and 7 entries for proc 1
sizes, _ = evenly_distrib_idxs(comm.size, size)
mysize = sizes[rank]
self.add_input('invec', np.ones(mysize, float), distributed=True)
self.add_output('outvec', np.ones(mysize, float), distributed=True,)
[docs] def compute(self, inputs, outputs):
if self.comm.rank == 0:
outputs['outvec'] = inputs['invec'] * 2.0
else:
outputs['outvec'] = inputs['invec'] * -3.0
[docs]class Summer(om.ExplicitComponent):
"""Sums an input array."""
[docs] def initialize(self):
self.options.declare('size', types=int, default=1,
desc="Size of input and output vectors.")
[docs] def setup(self):
self.add_input('invec', np.ones(self.options['size'], float))
self.add_output('sum', 0.0, shape=1)
[docs] def compute(self, inputs, outputs):
outputs['sum'] = np.sum(inputs['invec'])
[docs]class DistribCompDerivs(om.ExplicitComponent):
"""Simple Distributed Component with Derivatives."""
[docs] def initialize(self):
self.options.declare('size', types=int, default=1,
desc="Size of input and output vectors.")
[docs] def setup(self):
comm = self.comm
rank = comm.rank
size = self.options['size']
# if comm.size is 2 and size is 15, this results in
# 8 entries for proc 0 and 7 entries for proc 1
sizes, _ = evenly_distrib_idxs(comm.size, size)
self.mysize = mysize = sizes[rank]
# don't set src_indices on the input, just use default behavior
self.add_input('invec', np.ones(mysize, float), distributed=True)
self.add_output('outvec', np.ones(mysize, float), distributed=True)
[docs] def setup_partials(self):
# declare partial derivatives (diagonal of mysize)
self.declare_partials('outvec', 'invec',
rows=np.arange(0, self.mysize),
cols=np.arange(0, self.mysize))
[docs] def compute(self, inputs, outputs):
if self.comm.rank == 0:
outputs['outvec'] = inputs['invec'] * 2.0
else:
outputs['outvec'] = inputs['invec'] * -3.0
[docs] def compute_partials(self, inputs, J):
# get mysize from the input vector for this process
mysize = inputs['invec'].size
if self.comm.rank == 0:
J['outvec', 'invec'] = np.ones((mysize,)) * 2.0
else:
J['outvec', 'invec'] = np.ones((mysize,)) * -3.0
[docs]class SummerDerivs(om.ExplicitComponent):
"""Sums an input array."""
[docs] def initialize(self):
self.options.declare('size', types=int, default=1,
desc="Size of input and output vectors.")
[docs] def setup(self):
self.add_input('invec', np.ones(self.options['size'], float))
self.add_output('sum', 0.0, shape=1)
[docs] def setup_partials(self):
# the derivative is constant
self.declare_partials('sum', 'invec', val=1.)
[docs] def compute(self, inputs, outputs):
outputs['sum'] = np.sum(inputs['invec'])
