def test_nspinspec_sparse():
# GIVEN v and J inputs for the Rioux 3-spin system
v, J = rioux()
# WHEN nspinspec_sparse is called with those inputs
spectrum = nspinspec_sparse(v, J)
# THEN the resulting spectrum matches that using the old algorithm
assert np.allclose(spectrum, SPECTRUM_RIOUX)
def test_hamiltonian_sparse():
# GIVEN v and J inputs for the Rioux 3-spin system
v, J = rioux()
# WHEN hamiltonian_dense is used to calculate the Hamiltonian
H_sparse = hamiltonian_sparse(v, J)
# THEN it matches the Hamiltonian result using the old accepted algorithm
assert np.array_equal(H_sparse.todense(), H_RIOUX)
"""Collection of the current best candidates for nmrtools functions,
for testing speed etc.
"""
from nmrtools.nmrmath import hamiltonian as current_hamiltonian
from nmrtools.nmrmath import simsignals as current_simsignals
from speedtest.compare_hamiltonians import hamiltonian_sparse as \
candidate_hamiltonian
from tests.test_simsignals import vectorized_simsignals as candidate_simsignals
if __name__ == '__main__':
import numpy as np
from simulation_data import rioux
current_h = current_hamiltonian(*rioux())
current_spectrum = current_simsignals(current_h, 3)
candidate_h = candidate_hamiltonian(*rioux())
candidate_spectrum = candidate_simsignals(candidate_h, 3)
print(current_spectrum[:10])
print(candidate_spectrum[:10])
assert np.allclose(current_spectrum, candidate_spectrum)
def test_h_mem():
return candidate_hamiltonian(*rioux())
from nmrtools.nmrmath import is_allowed, normalize_spectrum, transition_matrix
from nmrtools.nmrplot import nmrplot
from speedtest.compare_hamiltonians import hamiltonian, hamiltonian_sparse
from speedtest.speedutils import timefn
from tests.test_spectraspeed import simsignals
from simulation_data import spin8, spin3, spin11, rioux
H3_MATRIX = hamiltonian(*spin3())
H3_NDARRAY = hamiltonian_sparse(*spin3())
H8_MATRIX = hamiltonian(*spin8())
H8_NDARRAY = hamiltonian_sparse(*spin8())
H11_MATRIX = hamiltonian(*spin11())
H11_NDARRAY = hamiltonian_sparse(*spin11())
H_RIOUX = hamiltonian(*rioux())
H_RIOUX_SPARSE = hamiltonian_sparse(*rioux())
@timefn
def numpy_eigh(h):
return np.linalg.eigh(h)
@timefn
def scipy_eigh(h):
return scipy.linalg.eigh(h)
@timefn
def multitest(test, h, n):
import numpy as np
from nmrtools.nmrmath import hamiltonian, nspinspec
from nmrtools.qm import (
hamiltonian_dense,
hamiltonian_sparse,
nspinspec_dense,
nspinspec_sparse,
# hs2, nss2
)
from simulation_data import rioux
H_RIOUX = hamiltonian(*rioux())
SPECTRUM_RIOUX = nspinspec(*rioux())
def test_hamiltonian_dense():
# GIVEN v and J inputs for the Rioux 3-spin system
v, J = rioux()
# WHEN hamiltonian_dense is used to calculate the Hamiltonian
H_dense = hamiltonian_dense(v, J)
# THEN it matches the Hamiltonian result using the old accepted algorithm
assert np.array_equal(H_dense, H_RIOUX)
def test_hamiltonian_sparse():
# GIVEN v and J inputs for the Rioux 3-spin system
v, J = rioux()
# WHEN hamiltonian_dense is used to calculate the Hamiltonian
H_sparse = hamiltonian_sparse(v, J)
# THEN it matches the Hamiltonian result using the old accepted algorithm