def test_set_parameters_is_noop_in_wavefunction_product():
orig1 = SimpleGaussian(0.4)
fixed = FixedWavefunction(orig1)
orig2 = SimpleGaussian(0.6)
prod = WavefunctionProduct(fixed, orig2)
# Only the params related to orig2 should change after this.
# Also, orig2's beta should not change because it is const by def.
prod.parameters = [0.5, 1.1, 123, 321]
np.testing.assert_array_equal(prod.parameters, [0.4, 1, 123, 1])
# Sorted
simple_gaussian2 = SimpleGaussian(alpha=0.5)
jastrow2 = JastrowPade(alpha=1, beta=1)
simple_and_jastrow2 = WavefunctionProduct(simple_gaussian2, jastrow2)
layers2 = [
DenseLayer(P * D, 32, activation=tanh, scale_factor=0.001),
DenseLayer(32, 16, activation=tanh),
DenseLayer(16, 1, activation=exponential),
]
dnn2 = Dnn()
for l in layers2:
dnn2.add_layer(l)
psi_sorted_base = WavefunctionProduct(simple_and_jastrow2, dnn2)
psi_sorted = InputSorter(psi_sorted_base)
psi.parameters = psi_sorted.parameters
psi_sorted_sampler = ImportanceSampler(system, psi_sorted, step_size=0.1)
# Benchmark:
simple_gaussian_bench = SimpleGaussian(alpha=0.5)
jastrow_bench = JastrowPade(alpha=1, beta=1)
psi_bench = WavefunctionProduct(simple_gaussian_bench, jastrow_bench)
psi_bench_sampler = ImportanceSampler(system, psi_bench, step_size=0.1)
plot_samples = 1_000_000
iters = 30000
samples = 1000
gamma = 0.0
evaluation_points = 2**23
psi_energies = EnergyCallback(samples=plot_samples, verbose=True)
# Wave functions:
simple_gaussian = SimpleGaussian(alpha=0.5)
jastrow = JastrowPade(alpha=1, beta=1)
simple_and_jastrow = WavefunctionProduct(simple_gaussian, jastrow)
layers = [
DenseLayer(P * D, 32, activation=tanh, scale_factor=0.001),
DenseLayer(32, 16, activation=tanh),
DenseLayer(16, 1, activation=exponential),
]
dnn = Dnn()
for l in layers:
dnn.add_layer(l)
psi = WavefunctionProduct(simple_and_jastrow, dnn)
psi_sampler = ImportanceSampler(system, psi, step_size=0.1)
psi.parameters = np.loadtxt("QD-parameters-dnn-regular.txt")
# Sorted
simple_gaussian2 = SimpleGaussian(alpha=0.5)
jastrow2 = JastrowPade(alpha=1, beta=1)
simple_and_jastrow2 = WavefunctionProduct(simple_gaussian2, jastrow2)
layers2 = [
DenseLayer(P * D, 32, activation=tanh, scale_factor=0.001),
DenseLayer(32, 16, activation=tanh),
DenseLayer(16, 1, activation=exponential),
]
dnn2 = Dnn()
for l in layers2:
dnn2.add_layer(l)
psi_sorted_base = WavefunctionProduct(simple_and_jastrow2, dnn2)