def run_short_ci(model_input, cuda_device_index, long_check=True):
start_dir = os.getcwd()
model, xml_path = prepare.prepare(model_input, force_overwrite=False)
model_dir = os.path.dirname(xml_path)
model.anchor_rootdir = os.path.abspath(model_dir)
check.check_pre_simulation_all(model)
run.run(model,
"any",
min_b_surface_simulation_length=1000,
num_rev_launches=10,
cuda_device_index=cuda_device_index,
save_state_file=True)
data_sample_list = converge.converge(model, k_on_state=0)
rmsd_convergence_results = common_converge.calc_RMSD_conv_amount(
model, data_sample_list)
transition_minima, transition_details, transition_times \
= common_converge.calc_transition_steps(
model, data_sample_list[-1])
converge.print_convergence_results(
model,
rmsd_convergence_results,
cutoff=0.1,
transition_results=transition_details,
transition_time_results=transition_times,
minimum_anchor_transitions=10,
bd_transition_counts=data_sample_list[-1].bd_transition_counts)
check.check_post_simulation_all(model, long_check=long_check)
analysis = analyze.analyze(model)
analysis.print_results()
os.chdir(start_dir)
return
def test_run_planar(planar_mmvt_model):
check.check_pre_simulation_all(planar_mmvt_model)
run.run(planar_mmvt_model,
"1",
min_total_simulation_length=10,
force_overwrite=True)
check.check_post_simulation_all(planar_mmvt_model)
def test_run_tiwary(tiwary_mmvt_model):
check.check_pre_simulation_all(tiwary_mmvt_model)
run.run(tiwary_mmvt_model,
"0",
min_total_simulation_length=10,
force_overwrite=True)
check.check_post_simulation_all(tiwary_mmvt_model)
def test_normal_run_openmm(toy_mmvt_model):
"""
Test a normal toy run - no restarts or anything.
"""
num_steps = 10000
dcd_interval = toy_mmvt_model.calculation_settings\
.trajectory_reporter_interval
num_dcd_frames = num_steps // dcd_interval
toy_mmvt_model.calculation_settings.num_production_steps = num_steps
toy_mmvt_model.openmm_settings.cuda_platform_settings = None
toy_mmvt_model.openmm_settings.reference_platform = True
check.check_pre_simulation_all(toy_mmvt_model)
run.run(toy_mmvt_model, "any", force_overwrite=True)
check.check_post_simulation_all(toy_mmvt_model)
for anchor in toy_mmvt_model.anchors:
if anchor.bulkstate:
continue
checkpoint_step = get_checkpoint_step(toy_mmvt_model, anchor)
assert checkpoint_step == num_steps
dcd_length, dcd_file_number = get_trajectory_length(
toy_mmvt_model, anchor)
dummy_file = tempfile.NamedTemporaryFile()
num_swarm = mmvt_sim_openmm.\
get_starting_structure_num_frames(toy_mmvt_model, anchor,
dummy_file.name)
assert dcd_length == num_dcd_frames * num_swarm
return
argparser.add_argument(
"-T", "--maximum_time", dest="maximum_time", default=None, type=float,
help="A user may wish to stop the analysis of simulation time for "\
"each anchor at a particular time. Enter the time (in ps) at which to "\
"end the analysis at a given anchor if the simulation time exceeds it.")
args = argparser.parse_args() # parse the args into a dictionary
args = vars(args)
model_file = args["model_file"]
force_warning = args["force_warning"]
num_error_samples = args["num_error_samples"]
stride_error_samples = args["stride_error_samples"]
skip_error_samples = args["skip_error_samples"]
image_directory = args["image_directory"]
skip_checks = args["skip_checks"]
min_time = args["minimum_time"]
max_time = args["maximum_time"]
model = base.load_model(model_file)
image_directory = common_analyze.make_image_directory(
model, image_directory)
if not skip_checks:
check.check_post_simulation_all(model, long_check=True)
analysis = analyze(model, force_warning=force_warning,
num_error_samples=num_error_samples,
stride_error_samples=stride_error_samples,
skip_error_samples=skip_error_samples,
skip_checks=skip_checks, min_time=min_time, max_time=max_time)
analysis.print_results()
print("All plots being saved to:", image_directory)
analysis.save_plots(image_directory)
def test_run_elber(toy_elber_model):
check.check_pre_simulation_all(toy_elber_model)
run.run(toy_elber_model, "0", min_total_simulation_length=1000)
check.check_post_simulation_all(toy_elber_model)