def test_add_nets_build_analysis(self):
mat_in, mat_out = test_data()
builder = NetworkBuilder(mat_in, mat_out)
net = builder.build(input_params=[{"multiplicity": 1},
{"multiplicity": 2}])
pool = NetworkPool()
pool.add_networks([net, net, net])
analysis_instances = pool.build_analysis(time_mux_output_data * 3)
self.assertEqual(6, len(analysis_instances))
test_time_mux_res(self, analysis_instances[0:2])
test_time_mux_res(self, analysis_instances[2:4])
test_time_mux_res(self, analysis_instances[4:6])
def test_add_nets_build_analysis(self):
mat_in, mat_out = test_data()
builder = NetworkBuilder(mat_in, mat_out)
net = builder.build(input_params=[{
"multiplicity": 1
}, {
"multiplicity": 2
}])
pool = NetworkPool()
pool.add_networks([net, net, net])
analysis_instances = pool.build_analysis(time_mux_output_data * 3)
self.assertEqual(6, len(analysis_instances))
test_time_mux_res(self, analysis_instances[0:2])
test_time_mux_res(self, analysis_instances[2:4])
test_time_mux_res(self, analysis_instances[4:6])
def test_calculate_output_matrix_stub_sim(self):
dp1 = {
"n_bits_in": 14,
"n_bits_out": 10,
"n_ones_in": 3,
"n_ones_out": 3,
"n_samples": 40
}
dp2 = {
"n_bits_in": 8,
"n_bits_out": 16,
"n_ones_in": 2,
"n_ones_out": 4,
"n_samples": 50
}
dp3 = {
"n_bits_in": 5,
"n_bits_out": 8,
"n_ones_in": 1,
"n_ones_out": 3,
"n_samples": 20
}
tp1 = {"multiplicity": 1}
tp2 = {"multiplicity": 3}
tp3 = {"multiplicity": 2}
# Build three networks
net1 = NetworkBuilder(data_params=dp1)
net2 = NetworkBuilder(data_params=dp2)
net3 = NetworkBuilder(data_params=dp3)
# Add them to a network pool
pool = NetworkPool()
pool.add_networks([
net1.build(topology_params=tp1),
net2.build(topology_params=tp2),
net3.build(topology_params=tp3)
])
# Simulate some expected output
output = (stub_simulation(
net1.mat_out, data_params=dp1, topology_params=tp1, latency=20.0) +
stub_simulation(net2.mat_out,
data_params=dp2,
topology_params=tp2,
latency=30.0) +
stub_simulation(net3.mat_out,
data_params=dp3,
topology_params=tp3,
latency=10.0))
# Fetch the analysis instance for the output
analysis_instances = pool.build_analysis(output)
# Compare the output matrices
m1 = analysis_instances[0].calculate_output_matrix()
m2 = analysis_instances[1].calculate_output_matrix()
m3 = analysis_instances[2].calculate_output_matrix()
np.testing.assert_almost_equal(net1.mat_out, m1)
np.testing.assert_almost_equal(net2.mat_out, m2)
np.testing.assert_almost_equal(net3.mat_out, m3)
def test_calculate_output_matrix_stub_sim(self):
dp1 = {
"n_bits_in": 14,
"n_bits_out": 10,
"n_ones_in": 3,
"n_ones_out": 3,
"n_samples": 40
}
dp2 = {
"n_bits_in": 8,
"n_bits_out": 16,
"n_ones_in": 2,
"n_ones_out": 4,
"n_samples": 50
}
dp3 = {
"n_bits_in": 5,
"n_bits_out": 8,
"n_ones_in": 1,
"n_ones_out": 3,
"n_samples": 20
}
tp1 = {
"multiplicity": 1
}
tp2 = {
"multiplicity": 3
}
tp3 = {
"multiplicity": 2
}
# Build three networks
net1 = NetworkBuilder(data_params=dp1)
net2 = NetworkBuilder(data_params=dp2)
net3 = NetworkBuilder(data_params=dp3)
# Add them to a network pool
pool = NetworkPool()
pool.add_networks([
net1.build(topology_params=tp1),
net2.build(topology_params=tp2),
net3.build(topology_params=tp3)])
# Simulate some expected output
output = (
stub_simulation(net1.mat_out, data_params=dp1,
topology_params=tp1, latency=20.0) +
stub_simulation(net2.mat_out, data_params=dp2,
topology_params=tp2, latency=30.0) +
stub_simulation(net3.mat_out, data_params=dp3,
topology_params=tp3, latency=10.0))
# Fetch the analysis instance for the output
analysis_instances = pool.build_analysis(output)
# Compare the output matrices
m1 = analysis_instances[0].calculate_output_matrix()
m2 = analysis_instances[1].calculate_output_matrix()
m3 = analysis_instances[2].calculate_output_matrix()
np.testing.assert_almost_equal(net1.mat_out, m1)
np.testing.assert_almost_equal(net2.mat_out, m2)
np.testing.assert_almost_equal(net3.mat_out, m3)
