def make_mmvt_milestone_between_two_anchors(self, anchor1, anchor2,
input_anchor1, input_anchor2,
milestone_index):
neighbor_index1 = anchor2.index
neighbor_index2 = anchor1.index
milestone1 = base.Milestone()
milestone1.index = milestone_index
milestone1.neighbor_anchor_index = neighbor_index1
milestone1.alias_index = len(anchor1.milestones) + 1
milestone1.cv_index = self.index
if input_anchor1.upper_milestone_radius is None:
value = 0.5 * (input_anchor1.radius + input_anchor2.radius)
else:
value = input_anchor2.upper_milestone_radius
milestone2 = base.Milestone()
milestone2.index = milestone_index
milestone2.neighbor_anchor_index = neighbor_index2
milestone2.alias_index = len(anchor2.milestones) + 1
milestone2.cv_index = self.index
if input_anchor2.lower_milestone_radius is None:
value = 0.5 * (input_anchor1.radius + input_anchor2.radius)
else:
value = input_anchor2.lower_milestone_radius
# assign k
milestone1.variables = {"k": 1.0, "radius": value}
milestone2.variables = {"k": -1.0, "radius": value}
for milestone in anchor1.milestones:
if milestone.neighbor_anchor_index == neighbor_index1:
# Then anchor1 already has this milestone added to it
return milestone_index
anchor1.milestones.append(milestone1)
anchor2.milestones.append(milestone2)
milestone_index += 1
return milestone_index
def make_elber_milestoning_objects_external(
external_cv_input, milestone_alias, milestone_index,
input_anchor_index, anchor_index, input_anchors,
umbrella_force_constant):
"""
Make a set of 1-dimensional external Milestone objects to be put into
an Anchor, and eventually, the Model.
"""
milestones = []
num_input_anchors = len(input_anchors)
if input_anchor_index > 0:
neighbor_index = anchor_index - 1
neighbor_index_input = input_anchor_index - 1
milestone1 = base.Milestone()
milestone1.index = milestone_index - 1
milestone1.neighbor_anchor_index = neighbor_index
milestone1.alias_index = 1
milestone1.is_source_milestone = False
milestone1.cv_index = external_cv_input.index
if input_anchors[input_anchor_index].lower_milestone_value is None:
value = 0.5 * (input_anchors[input_anchor_index].value \
+ input_anchors[neighbor_index_input].value)
else:
value = input_anchors[input_anchor_index].lower_milestone_value
milestone1.variables = {"k": umbrella_force_constant, "value": value}
milestones.append(milestone1)
milestone2 = base.Milestone()
milestone2.index = milestone_index
milestone2.neighbor_anchor_index = milestone_index
#milestone2.alias_index = milestone_alias
milestone2.alias_index = 2
milestone2.is_source_milestone = True
milestone2.cv_index = external_cv_input.index
value = input_anchors[input_anchor_index].value
milestone2.variables = {"k": umbrella_force_constant, "value": value}
milestones.append(milestone2)
if input_anchor_index < num_input_anchors-1:
neighbor_index = anchor_index + 1
neighbor_index_input = input_anchor_index + 1
milestone3 = base.Milestone()
milestone3.index = milestone_index + 1
milestone3.neighbor_anchor_index = neighbor_index
milestone3.alias_index = 3
milestone3.is_source_milestone = False
milestone3.cv_index = external_cv_input.index
if input_anchors[input_anchor_index].upper_milestone_value is None:
value = 0.5 * (input_anchors[input_anchor_index].value \
+ input_anchors[neighbor_index_input].value)
else:
value = input_anchors[input_anchor_index].upper_milestone_value
milestone3.variables = {"k": umbrella_force_constant, "value": value}
milestones.append(milestone3)
return milestones, milestone_alias, milestone_index+1
def make_elber_milestoning_objects_spherical(
spherical_cv_input, milestone_alias, milestone_index,
input_anchor_index, anchor_index, input_anchors, umbrella_force_constant):
"""
Make a set of 1-dimensional spherical Milestone objects to be put into
an Anchor, and eventually, the Model. Each anchor needs 3 milestones.
"""
milestones = []
num_anchors = len(input_anchors)
if input_anchor_index > 0:
neighbor_index = anchor_index - 1
neighbor_index_input = input_anchor_index - 1
milestone1 = base.Milestone()
milestone1.index = milestone_index-1
milestone1.neighbor_anchor_index = neighbor_index
#milestone1.alias_index = milestone_alias
milestone1.alias_index = 1
milestone1.is_source_milestone = False
milestone1.cv_index = spherical_cv_input.index
radius = input_anchors[neighbor_index_input].radius
milestone1.variables = {"k": umbrella_force_constant, "radius": radius}
#milestone_alias += 1
#milestone_index += 1
milestones.append(milestone1)
milestone2 = base.Milestone()
milestone2.index = milestone_index
milestone2.neighbor_anchor_index = milestone_index
#milestone2.alias_index = milestone_alias
milestone2.alias_index = 2
milestone2.is_source_milestone = True
milestone2.cv_index = spherical_cv_input.index
radius = input_anchors[input_anchor_index].radius
milestone2.variables = {"k": umbrella_force_constant, "radius": radius}
milestones.append(milestone2)
if input_anchor_index < num_anchors-1:
neighbor_index = anchor_index + 1
neighbor_index_input = input_anchor_index + 1
milestone3 = base.Milestone()
milestone3.index = milestone_index+1
milestone3.neighbor_anchor_index = neighbor_index
#milestone3.alias_index = milestone_alias+1
milestone3.alias_index = 3
milestone3.is_source_milestone = False
milestone3.cv_index = spherical_cv_input.index
radius = input_anchors[neighbor_index_input].radius
milestone3.variables = {"k": umbrella_force_constant, "radius": radius}
milestones.append(milestone3)
return milestones, milestone_alias, milestone_index+1
def make_mmvt_milestoning_objects_spherical(
spherical_cv_input, milestone_alias, milestone_index,
index, input_anchors):
"""
Make a set of 1-dimensional spherical Milestone objects to be put into
an Anchor, and eventually, the Model.
"""
milestones = []
num_anchors = len(input_anchors)
if index > 0:
neighbor_index = index - 1
milestone1 = base.Milestone()
milestone1.index = milestone_index
milestone1.neighbor_anchor_index = neighbor_index
milestone1.alias_index = milestone_alias
milestone1.cv_index = spherical_cv_input.index
if input_anchors[index].lower_milestone_radius is None:
radius = 0.5 * (input_anchors[index].radius \
+ input_anchors[neighbor_index].radius)
else:
radius = input_anchors[index].lower_milestone_radius
milestone1.variables = {"k": -1.0, "radius": radius}
milestone_alias += 1
milestone_index += 1
milestones.append(milestone1)
if index < num_anchors-1:
neighbor_index = index + 1
milestone2 = base.Milestone()
milestone2.index = milestone_index
milestone2.neighbor_anchor_index = neighbor_index
milestone2.alias_index = milestone_alias
milestone2.cv_index = spherical_cv_input.index
if input_anchors[index].upper_milestone_radius is None:
radius = 0.5 * (input_anchors[index].radius \
+ input_anchors[neighbor_index].radius)
else:
radius = input_anchors[index].upper_milestone_radius
milestone2.variables = {"k": 1.0, "radius": radius}
milestones.append(milestone2)
return milestones, milestone_alias, milestone_index
def make_simple_model():
n_anchors = 3
n_milestones = 3
# generate data to feed directly into MMVT_data_sample()
model = base.Model()
model.calculation_type = "elber"
model.num_milestones = n_milestones
model.num_anchors = n_anchors
anchor0 = elber_base.Elber_toy_anchor()
anchor0.index = 0
anchor0.endstate = True
milestone_0_0 = base.Milestone()
milestone_0_0.index = 0
milestone_0_0.neighbor_anchor_index = 0
milestone_0_0.alias_index = 2
milestone_0_1 = base.Milestone()
milestone_0_1.index = 1
milestone_0_1.neighbor_anchor_index = 1
milestone_0_1.alias_index = 3
anchor0.milestones = [milestone_0_0, milestone_0_1]
anchor1 = elber_base.Elber_toy_anchor()
anchor1.index = 1
milestone_1_0 = base.Milestone()
milestone_1_0.index = 0
milestone_1_0.neighbor_anchor_index = 0
milestone_1_0.alias_index = 1
milestone_1_1 = base.Milestone()
milestone_1_1.index = 1
milestone_1_1.neighbor_anchor_index = 1
milestone_1_1.alias_index = 2
milestone_1_2 = base.Milestone()
milestone_1_2.index = 2
milestone_1_2.neighbor_anchor_index = 2
milestone_1_2.alias_index = 3
anchor1.milestones = [milestone_1_0, milestone_1_1, milestone_1_2]
anchor2 = elber_base.Elber_toy_anchor()
anchor2.index = 2
milestone_2_0 = base.Milestone()
milestone_2_0.index = 1
milestone_2_0.neighbor_anchor_index = 1
milestone_2_0.alias_index = 1
milestone_2_1 = base.Milestone()
milestone_2_1.index = 2
milestone_2_1.neighbor_anchor_index = 2
milestone_2_1.alias_index = 2
anchor2.milestones = [milestone_2_0, milestone_2_1]
anchor2.bulkstate = True
model.anchors = [anchor0, anchor1, anchor2]
return model
def make_simple_model():
n_anchors = 4
n_milestones = 3
# generate data to feed directly into MMVT_data_sample()
model = base.Model()
model.num_milestones = n_milestones
model.num_anchors = n_anchors
anchor0 = mmvt_base.MMVT_toy_anchor()
anchor0.index = 0
milestone_0_0 = base.Milestone()
milestone_0_0.index = 0
milestone_0_0.neighbor_anchor_index = 1
milestone_0_0.alias_index = 1
anchor0.milestones = [milestone_0_0]
anchor1 = mmvt_base.MMVT_toy_anchor()
anchor1.index = 1
milestone_1_0 = base.Milestone()
milestone_1_0.index = 0
milestone_1_0.neighbor_anchor_index = 0
milestone_1_0.alias_index = 1
milestone_1_1 = base.Milestone()
milestone_1_1.index = 1
milestone_1_1.neighbor_anchor_index = 2
milestone_1_1.alias_index = 2
anchor1.milestones = [milestone_1_0, milestone_1_1]
anchor2 = mmvt_base.MMVT_toy_anchor()
anchor2.index = 2
milestone_2_0 = base.Milestone()
milestone_2_0.index = 1
milestone_2_0.neighbor_anchor_index = 1
milestone_2_0.alias_index = 1
milestone_2_1 = base.Milestone()
milestone_2_1.index = 2
milestone_2_1.neighbor_anchor_index = 3
milestone_2_1.alias_index = 2
anchor2.milestones = [milestone_2_0, milestone_2_1]
anchor3 = mmvt_base.MMVT_toy_anchor()
anchor3.index = 3
milestone_3_0 = base.Milestone()
milestone_3_0.index = 2
milestone_3_0.neighbor_anchor_index = 2
milestone_3_0.alias_index = 1
anchor3.milestones = [milestone_3_0]
model.anchors = [anchor0, anchor1, anchor2, anchor3]
return model
def make_test_model(tmp_dir,
num_anchors=3,
milestone_type="spherical",
make_dir=True,
mode="amber",
engine="openmm",
no_BD=False):
if milestone_type == "spherical":
#group1 = [2478, 2489, 2499, 2535, 2718, 2745, 2769, 2787, 2794, 2867,
# 2926]
group1 = list(range(147))
#group2 = [3221, 3222, 3223, 3224, 3225, 3226, 3227, 3228, 3229]
group2 = list(range(147, 162))
groups = [group1, group2]
cv1 = mmvt_base.MMVT_spherical_CV(index=0, groups=groups)
cvs = [cv1]
else:
raise Exception("milestone type not implemented")
mymodel = base.Model()
mymodel.temperature = 277.8
mymodel.calculation_type = "MMVT"
mymodel.calculation_settings = mmvt_base.MMVT_settings()
mymodel.calculation_settings.num_production_steps = 100
mymodel.anchor_rootdir = tmp_dir
mymodel.num_anchors = num_anchors
mymodel.num_milestones = num_anchors - 1
if engine == "openmm":
mymodel.openmm_settings = base.Openmm_settings()
mymodel.openmm_settings.energy_reporter_frequency = 50
mymodel.openmm_settings.trajectory_reporter_frequency = 50
mymodel.openmm_settings.restart_checkpoint_frequency = 50
mymodel.openmm_settings.total_simulation_length = 50
mymodel.openmm_settings.cuda_platform_settings = None
mymodel.openmm_settings.reference_platform = True
if engine == "namd":
mymodel.namd_settings = base.Namd_settings()
mymodel.namd_settings.energy_reporter_frequency = 50
mymodel.namd_settings.trajectory_reporter_frequency = 50
mymodel.namd_settings.restart_checkpoint_frequency = 50
mymodel.namd_settings.total_simulation_length = 50
if not no_BD:
my_k_on_info = base.K_on_info()
my_k_on_info.source_milestones = [2]
mymodel.k_on_info = my_k_on_info
mymodel.collective_variables = cvs
'''
for index in range(num_anchors):
milestone_list = []
if index < num_anchors-1:
milestone1 = base.Milestone()
milestone1.index = index
milestone1.neighbor_index = index+1
milestone1.alias_id = 2
milestone1.cv_index = 0
milestone1.variables = {"radius": 1.3}
milestone_list.append(milestone1)
bulkstate = False
else:
bulkstate = True
if index > 0:
milestone2 = base.Milestone()
milestone2.index = index-1
milestone2.neighbor_index = index-1
milestone2.alias_id = 1
milestone2.cv_index = 0
milestone2.variables = {"radius": 1.1}
milestone_list.append(milestone2)
endstate = False
else:
endstate = True
if bulkstate:
endstate = True
'''
for i in range(num_anchors):
index = i
milestone_list = []
num_milestones = 0
if i > 0:
milestone1 = base.Milestone()
milestone1.index = i - 1
milestone1.neighbor_anchor_index = i - 1
milestone1.alias_index = num_milestones + 1
milestone1.cv_index = 0
milestone1.variables = {"k": -1.0, "radius": 0.1 * i}
milestone_list.append(milestone1)
num_milestones += 1
endstate = False
else:
endstate = True
if i < num_anchors - 1:
milestone2 = base.Milestone()
milestone2.index = i
milestone2.neighbor_anchor_index = i + 1
milestone2.alias_index = num_milestones + 1
milestone2.cv_index = 0
milestone2.variables = {"k": 1.0, "radius": 0.1 * (i + 1)}
milestone_list.append(milestone2)
bulkstate = False
else:
bulkstate = True
name = "anchor_%d" % index
directory = name
if make_dir:
full_anchor_dir = os.path.join(tmp_dir, directory)
os.mkdir(full_anchor_dir)
prod_dir = os.path.join(full_anchor_dir, "prod")
os.mkdir(prod_dir)
building_dir = os.path.join(full_anchor_dir, "building")
os.mkdir(building_dir)
md_glob = "mmvt*.out"
md = True
bd = False
#anchor = base.Anchor(name, index, directory, md_glob, md, bd,
# endstate, bulkstate, len(milestone_list), milestone_list)
anchor = mmvt_base.MMVT_anchor()
anchor.name = name
anchor.index = index
anchor.directory = directory
anchor.md_mmvt_output_glob = md_glob
anchor.md = md
anchor.bd = bd
anchor.endstate = endstate
anchor.bulkstate = bulkstate
#anchor.num_milestones = len(milestone_list)
anchor.milestones = milestone_list
if mode == 'amber':
make_amber_params(anchor, building_dir, engine=engine)
elif mode == 'forcefield':
make_forcefield_params(anchor, building_dir)
else:
raise Exception("mode not implemented:" + mode)
mymodel.anchors.append(anchor)
if not no_BD:
mymodel.browndye_settings = base.Browndye_settings()
mymodel.browndye_settings.apbs_grid_spacing = 0.5
mymodel.browndye_settings.n_threads = 1
mymodel.browndye_settings.recompute_ligand_electrostatics = 1
mymodel.browndye_settings.debye_length = 7.5612
mymodel.browndye_settings.ghost_indices_rec = [147]
mymodel.browndye_settings.ghost_indices_lig = [15]
mymodel.k_on_info.b_surface_directory = "b_surface"
mymodel.k_on_info.b_surface_num_steps = 100
ion1 = base.Ion()
ion1.radius = 1.2
ion1.charge = -1.0
ion1.conc = 0.15
ion2 = base.Ion()
ion2.radius = 0.9
ion2.charge = 1.0
ion2.conc = 0.15
mymodel.k_on_info.ions = [ion1, ion2]
if make_dir:
b_surface_abs_path = os.path.join(tmp_dir, "b_surface")
os.mkdir(b_surface_abs_path)
make_browndye_params_b_surface(mymodel, b_surface_abs_path)
mymodel.k_on_info.bd_milestones = []
bd_milestone = base.BD_milestone()
bd_milestone.index = 0
bd_milestone.name = "bd_milestone_0"
bd_milestone.directory = bd_milestone.name
bd_milestone.outer_milestone = milestone2
#bd_milestone.outer_milestone = mymodel.anchors[-1].milestones[-1]
assert "radius" in bd_milestone.outer_milestone.variables, \
"A BD outer milestone must be spherical."
bd_milestone.inner_milestone = milestone1
bd_milestone.num_steps = 1
bd_milestone.receptor_indices = list(range(147))
bd_milestone.ligand_indices = list(range(15))
mymodel.k_on_info.bd_milestones.append(bd_milestone)
for bd_milestone in mymodel.k_on_info.bd_milestones:
bd_milestone_dict = {}
bd_milestone_dict[bd_milestone.extracted_directory] = {}
bd_milestone_dict[bd_milestone.fhpd_directory] = {}
bd_milestone_filetree = filetree.Filetree(
{bd_milestone.directory: bd_milestone_dict})
bd_milestone_filetree.make_tree(tmp_dir)
return mymodel
def make_smol_model(tmp_path, num_anchors, intervals):
basename = "testmmvt.dat"
mymodel = base.Model()
mymodel.temperature = 300.0
mymodel.calculation_type = "mmvt"
mymodel.anchor_rootdir = tmp_path
mymodel.num_anchors = num_anchors+1
mymodel.num_milestones = mymodel.num_anchors - 1
# TEMPORARY: toy system will eventually have its own settings
mymodel.openmm_settings = base.Openmm_settings()
intervals.append(1.0)
for index in range(mymodel.num_anchors):
boundary1 = float(index)
boundary2 = float(index)+intervals[index]
x0 = boundary1 + 0.5
milestones = []
anchor = mmvt_base.MMVT_anchor()
if index == 0:
milestone_count = 1
milestone1 = base.Milestone()
milestone1.index = 0
milestone1.neighbor_anchor_index = 1
milestone1.alias_index = 1
milestone1.cv_index = 0
milestones.append(milestone1)
anchor.bulkstate = False
end_state = True
elif index > 0 and index < mymodel.num_anchors-1:
milestone_count = 2
milestone1 = base.Milestone()
milestone1.index = index-1
milestone1.neighbor_anchor_index = index-1
milestone1.alias_index = 1
milestone1.cv_index = 0
milestone2 = base.Milestone()
milestone2.index = index
milestone2.neighbor_anchor_index = index+1
milestone2.alias_index = 2
milestone2.cv_index = 0
milestones.append(milestone1)
milestones.append(milestone2)
anchor.bulkstate = False
end_state = False
elif index == mymodel.num_anchors-1:
milestone_count = 1
milestone1 = base.Milestone()
milestone1.index = index-1
milestone1.neighbor_anchor_index = index-1
milestone1.alias_index = 1
milestone1.cv_index = 0
milestones.append(milestone1)
anchor.bulkstate = True
end_state = False
anchor.name = "anchor_%d" % index
anchor.index = index
anchor.directory = anchor.name
anchor.md_mmvt_output_glob = basename
anchor.md = True
anchor.endstate = end_state
anchor.milestones = milestones
mymodel.anchors.append(anchor)
return mymodel
def test_mcmc_3x3_mmvt(tmpdir_factory):
"""
Use the same statistics to generate both MMVT and Elber rate matrices.
Then use the data to sample matrices and compare the distributions to
ensure that the MMVT and Elber matrix sampling methods are consistent.
"""
num = 10000 #100000
stride = 4
skip = 90
n_anchors = 4
n_milestones = 3
# generate data to feed directly into MMVT_data_sample()
model = base.Model()
model.num_milestones = n_milestones
model.num_anchors = n_anchors
anchor0 = mmvt_base.MMVT_toy_anchor()
anchor0.index = 0
milestone_0_0 = base.Milestone()
milestone_0_0.index = 0
milestone_0_0.neighbor_anchor_index = 1
milestone_0_0.alias_index = 1
anchor0.milestones = [milestone_0_0]
anchor1 = mmvt_base.MMVT_toy_anchor()
anchor1.index = 1
milestone_1_0 = base.Milestone()
milestone_1_0.index = 0
milestone_1_0.neighbor_anchor_index = 0
milestone_1_0.alias_index = 1
milestone_1_1 = base.Milestone()
milestone_1_1.index = 1
milestone_1_1.neighbor_anchor_index = 2
milestone_1_1.alias_index = 2
anchor1.milestones = [milestone_1_0, milestone_1_1]
anchor2 = mmvt_base.MMVT_toy_anchor()
anchor2.index = 2
milestone_2_0 = base.Milestone()
milestone_2_0.index = 1
milestone_2_0.neighbor_anchor_index = 1
milestone_2_0.alias_index = 1
milestone_2_1 = base.Milestone()
milestone_2_1.index = 2
milestone_2_1.neighbor_anchor_index = 3
milestone_2_1.alias_index = 2
anchor2.milestones = [milestone_2_0, milestone_2_1]
anchor3 = mmvt_base.MMVT_toy_anchor()
anchor3.index = 3
milestone_3_0 = base.Milestone()
milestone_3_0.index = 2
milestone_3_0.neighbor_anchor_index = 2
milestone_3_0.alias_index = 1
anchor3.milestones = [milestone_3_0]
model.anchors = [anchor0, anchor1, anchor2, anchor3]
# MMVT stats
N_alpha_beta = {(0,1):12, (1,0):12,
(1,2):12, (2,1):12,
(2,3):6, (3,2):6}
k_alpha_beta = {(0,1):20.0, (1,0):10.0,
(1,2):10.0, (2,1):(40.0/3.0),
(2,3):(20.0/3.0), (3,2):20.0}
N_i_j_alpha = [{},
{(0,1):4, (1,0):4},
{(1,2):2, (2,1):2},
{}]
R_i_alpha_total = [{0: 1.2},
{0: 1.2, 1:1.2},
{1: 1.2, 2:0.6},
{2: 0.6}]
T_alpha_total = [1.2,
2.4,
1.8,
0.6]
main_data_sample = mmvt_analyze.MMVT_data_sample(
model, N_alpha_beta, k_alpha_beta, N_i_j_alpha,
R_i_alpha_total, T_alpha_total)
main_data_sample.calculate_pi_alpha()
main_data_sample.fill_out_data_quantities()
main_data_sample.compute_rate_matrix()
main_data_sample.calculate_thermodynamics()
main_data_sample.calculate_kinetics()
mmvt_Q = main_data_sample.Q
# Elber stats
N_i_j = {(0,1): 4, (1,0): 4, (1,2): 2, (2,1): 2}
R_i = {0: 2.4, 1: 2.4, 2: 1.2}
elber_N = np.array([[0, 4, 0],
[4, 0, 2],
[0, 2, 0]])
elber_R = np.array([[2.4],
[2.4],
[1.2]])
elber_Q = np.zeros((n_milestones, n_milestones))
for i in range(n_milestones):
for j in range(n_milestones):
key = (i,j)
if key in N_i_j:
elber_Q[i,j] = N_i_j[key] / R_i[i]
for i in range(n_milestones):
elber_Q[i,i] = -np.sum(elber_Q[i,:])
# Make sure the two models make identical matrices
assert np.isclose(mmvt_Q, elber_Q).all()
# Now compare the distributions of both of them
# MMVT matrix sampler
data_sample_list, p_i_error, free_energy_profile_err, MFPTs_error, \
k_off_error, k_ons_error = mmvt_analyze.monte_carlo_milestoning_error(
main_data_sample, num=num, stride=stride, skip=skip, verbose=True)
mmvt_q1_distribution = []
mmvt_q2_distribution = []
for data_sample in data_sample_list:
mmvt_q1_distribution.append(data_sample.Q[0,1])
mmvt_q2_distribution.append(data_sample.Q[1,0])
# Elber matrix sampler
elber_q1_distribution = []
elber_q2_distribution = []
for counter in range(num * (stride) + skip):
#if verbose: print("MCMC stepnum: ", counter)
elber_Qnew = markov_chain_monte_carlo\
.irreversible_stochastic_matrix_algorithm_sample(
elber_Q, elber_N, elber_R)
if counter > skip and counter % stride == 0:
elber_q1_distribution.append(elber_Q[0,1])
elber_q2_distribution.append(elber_Q[1,0])
elber_Q = elber_Qnew
assert np.isclose(np.mean(elber_q1_distribution),
np.mean(mmvt_q1_distribution), rtol=0.5, atol=0.01)
assert np.isclose(np.std(elber_q1_distribution),
np.std(mmvt_q1_distribution), rtol=0.5, atol=0.01)
assert np.isclose(np.mean(elber_q2_distribution),
np.mean(mmvt_q2_distribution), rtol=0.5, atol=0.01)
assert np.isclose(np.std(elber_q2_distribution),
np.std(mmvt_q2_distribution), rtol=0.5, atol=0.01)
return