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run_test.py
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import asparagus
import os
import torch
import numpy as np
#==============================================================================
# Test Parameter
#==============================================================================
flag_dictionary_initialization = True
flag_database_sql = True
flag_database_npz = True
flag_database_hdf5 = False
flag_datareader = True
flag_sampler_all = True
flag_sampler_shell = True
flag_sampler_slurm = False
flag_sampler_shell_case = True
flag_model_physnet = True
flag_train_physnet_sql = True
flag_train_physnet_npz = True
flag_ase_physnet = True
flag_model_painn = True
flag_train_painn = True
flag_transfer_learning = True
flag_train_cuda = False
# ==============================================================================
# Test Asparagus Main Class Initialization
# ==============================================================================
config_file = 'test/init.json'
config = {
'config_file': config_file}
device = 'cpu'
dtype = torch.float32
# Config dictionary initialization
if flag_dictionary_initialization:
model = asparagus.Asparagus(config)
model = asparagus.Asparagus(config=config_file)
model = asparagus.Asparagus(config_file=config_file)
model = asparagus.Asparagus(
config,
model_device=device,
model_dtype=dtype)
model = asparagus.Asparagus(
config,
model_device=device,
model_dtype=dtype)
# ==============================================================================
# Test Asparagus DataContainer Class Initialization
# ==============================================================================
config_file = 'test/data.json'
config = {
'config_file': config_file}
# SQL
if flag_database_sql:
if os.path.exists(config_file):
os.remove(config_file)
# Open DataBase file
model = asparagus.Asparagus(
config=config_file,
data_file='test/test.db',
data_source=[
'data/nms_nh3.db',
'data/h2co_B3LYP_cc-pVDZ_4001.npz',
('data/h2co_B3LYP_cc-pVDZ_4001.npz', 'npz'),
'data/meta_nh3.traj',
('data/meta_nh3.traj', 'traj'),
],
data_seed=1001,
)
model.set_data_container()
# Create new DataBase file
model.set_data_container(
config=config_file,
data_file='test/test.db',
data_source='data/nms_nh3.db',
data_overwrite=True,
)
# Add same source to DataBase file, should be skipped
model.set_data_container(
config=config_file,
data_file='test/test.db',
data_source='data/nms_nh3.db',
data_overwrite=False,
)
# Load new DataBase with different source property units
model.set_data_container(
config=config_file,
data_file='test/test.db',
data_source='data/h2co_B3LYP_cc-pVDZ_4001.npz',
data_source_unit_properties={
'positions': 'Bohr',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Bohr',
'dipole': 'e*Bohr',
},
data_overwrite=True,
)
os.remove(config_file)
# Load new DataBase with different source property units
model.set_data_container(
config=config_file,
data_file='test/test.db',
data_source='data/h2co_B3LYP_cc-pVDZ_4001.npz',
data_unit_properties={
'positions': 'Ang',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Ang',
'dipole': 'e*Ang',
},
data_source_unit_properties={
'positions': 'Bohr',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Bohr',
'dipole': 'e*Bohr',
},
data_overwrite=True,
)
os.remove(config_file)
# Create new DataBase file with itself as source, should return error
try:
model.set_data_container(
config=config_file,
data_file='test/nms_nh3_test.db',
data_source='test/nms_nh3_test.db',
data_overwrite=True,
)
except SyntaxError:
print("\nSyntaxError as expected\n")
# Get DataContainer (Reset data source)
model = asparagus.Asparagus(
config=config_file,
data_file='test/nms_nh3_test.db',
data_source='data/nms_nh3.db',
)
data = model.get_data_container()
# Test property scaling calculation
data.get_property_scaling(
property_atom_scaled={'energy': 'atomic_energies'})
data.get_property_scaling()
print("\nDatabase path: ", model.get_data_container(), "\n")
print("\nDatabase entry '0': ", data[0]['energy'])
print("\nDatabase Train entry '1': ", data.get_train(1)['atoms_number'])
print("\nDatabase Valid entry '2': ", data.get_valid(2)['cell'])
print("\nDatabase Valid entry '2': ", data.get_valid(2)['pbc'])
print("\nDatabase Test entry '3': ", data.get_test(3)['positions'])
print("\nDatabase Test entry '3': ", data.get_test(4)['forces'])
# Load Numpy .npz files
model.set_data_container(
config=config_file,
data_file='test/h2co_test.db',
data_source='data/h2co_B3LYP_cc-pVDZ_4001.npz',
data_overwrite=True,
)
data = model.get_data_container(data_file='test/h2co_test.db')
print("\nDatabase path: ", data, "\n")
print("\nDatabase entry '0': ", data[0]['energy'])
print("\nDatabase Train entry '1': ", data.get_train(1)['atomic_numbers'])
print("\nDatabase Valid entry '2': ", data.get_valid(2)['charge'])
print("\nDatabase Test entry '3': ", data.get_test(3)['pbc'])
# Test property scaling calculation
data.get_property_scaling(
property_atom_scaled={'energy': 'atomic_energies'})
data.get_property_scaling()
# Load multiple source files files
model.set_data_container(
config=config_file,
data_file='test/nh3_h2co_test.db',
data_source=['data/h2co_B3LYP_cc-pVDZ_4001.npz', 'data/nms_nh3.db'],
data_overwrite=True,
)
# Check if repeated data source is skipped
model.set_data_container(
config=config_file,
data_file='test/nh3_h2co_test.db',
data_source=['data/nms_nh3.db'],
data_overwrite=False,
)
# Load ASE trajectory file
model.set_data_container(
config=config_file,
data_file='test/meta_nh3_test.db',
data_source='data/meta_nh3.traj',
data_overwrite=True,
)
# Load ASE trajectory file with different property units
model.set_data_container(
config=config_file,
data_file='test/meta_nh3_test_unit.db',
data_source='data/meta_nh3.traj',
data_properties=['energy', 'forces'],
data_unit_properties={
'positions': 'Bohr',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Bohr'},
data_overwrite=True,
)
# Test training initialization
model.train(
trainer_max_epochs=0,
model_directory='test/test_model')
# Check automatic model property assignment from data properties
if os.path.exists(config_file):
os.remove(config_file)
model = asparagus.Asparagus(
config=config_file,
data_file='test/meta_nh3_test_unit.db',
data_source='data/meta_nh3.traj',
data_properties=['energy', 'forces'],
data_unit_properties={
'positions': 'Bohr',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Bohr'},
data_overwrite=True,
)
# Test training initialization
model.train(
trainer_max_epochs=0,
model_directory='test/test_model')
# Numpy npz
if flag_database_npz:
model = asparagus.Asparagus(
config=config_file,
data_file='test/nms_nh3_test.db.npz',
data_source='data/nms_nh3.db',
data_overwrite=True,
)
# Create new DataBase file
data = model.get_data_container(
config=config_file,
data_file='test/nms_nh3_test.db.npz',
data_source='data/nms_nh3.db',
data_overwrite=False,
)
print("\nDatabase path: ", data, "\n")
print("\nDatabase entry '0': ", data[0]['energy'])
print("\nDatabase Train entry '1': ", data.get_train(1)['atoms_number'])
print("\nDatabase Valid entry '2': ", data.get_valid(2)['cell'])
print("\nDatabase Valid entry '2': ", data.get_valid(2)['pbc'])
print("\nDatabase Test entry '3': ", data.get_test(3)['positions'])
print("\nDatabase Test entry '3': ", data.get_test(4)['forces'])
# Test training initialization
model.train(
trainer_max_epochs=0,
model_directory='test/test_model')
# Open DataBase file
model = asparagus.Asparagus(
config=config_file,
data_file='test/test.db.npz',
data_source=[
'data/nms_nh3.db',
'data/h2co_B3LYP_cc-pVDZ_4001.npz',
('data/h2co_B3LYP_cc-pVDZ_4001.npz', 'npz'),
'data/meta_nh3.traj',
('data/meta_nh3.traj', 'traj'),
],
data_overwrite=True,
)
model.set_data_container()
data = model.get_data_container()
metadata = data.get_metadata()
# Test property scaling calculation
data.get_property_scaling(data_label='test')
# Load with different property units
model.set_data_container(
config=config_file,
data_file='test/test.db.npz',
data_source='data/h2co_B3LYP_cc-pVDZ_4001.npz',
data_properties=['energy', 'forces'],
data_unit_properties={
'positions': 'Bohr',
'energy': 'kcal/mol',
'forces': 'kcal/mol/Bohr'},
data_source_unit_properties={
'positions': 'Ang',
'energy': 'eV',
'forces': 'kcal/mol/Ang'},
data_overwrite=True,
)
os.remove(config_file)
# HDF5
if flag_database_hdf5:
# Create new DataBase file
model = asparagus.Asparagus(
config=config_file,
data_file='test/nms_nh3_test.db.h5',
data_file_format='hdf5',
data_source='data/nms_nh3.db',
data_source_format='sql',
data_overwrite=True,
)
data = model.get_data_container()
# Test training initialization
model.train(
trainer_max_epochs=0,
model_directory='test/test_model')
#==============================================================================
# Test Asparagus DataReader
#==============================================================================
# Check DataReader functions for consistency
if flag_datareader:
config_file = 'test/read.json'
# Read from Asparagus data file
model = asparagus.Asparagus(
config=config_file,
data_file='test/test.db',
data_source='data/nms_nh3.db',
data_overwrite=True,
)
data = model.get_data_container()
print("\nDatabase entry '0': ", data.get(2)['cell'])
# Read from npz data file
model = asparagus.Asparagus(
config=config_file,
data_file='test/test.db',
data_source='data/h2co_B3LYP_cc-pVDZ_4001.npz',
data_overwrite=True,
)
data = model.get_data_container()
print("\nDatabase entry '0': ", data.get(2)['cell'])
#==============================================================================
# Test Asparagus Sampler Methods
#==============================================================================
# Sampler - with XTB and ORCA
# Mind: XTB is not thread safe when using with ASE modules such as Optimizer
# or Vibrations, but simple Calculator call works
if flag_sampler_all:
from asparagus.sampling import Sampler
# Load single system from xyz file and compute properties using XTB default
# calculator
sampler = Sampler(
config='test/smpl_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB',
sample_calculator_args = {
'charge': 0,
'directory': 'test/xtb'},
sample_num_threads=1,
)
sampler.run()
# Load two system from xyz file and compute properties using XTB default
# calculator in parallel (still works without using other ASE functions)
sampler = Sampler(
config='test/smpl_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/nh3_d3h.xyz'],
sample_systems_format='xyz',
sample_calculator='XTB',
sample_calculator_args = {
'charge': 0,
'directory': 'test/xtb'},
sample_num_threads=2,
)
sampler.run()
# Load two systems from xyz file and a ASE trajectory file and compute
# properties using XTB default calculator
sampler = Sampler(
config='test/smpl_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/meta_nh3.traj'],
sample_calculator='XTB',
sample_calculator_args = {
'charge': 0,
'directory': 'test/xtb'},
sample_num_threads=1,
)
sampler.run()
# Load a selection of sample system from an Asparagus data file and compute
# properties using XTB default calculator
sampler = Sampler(
config='test/smpl_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nms_nh3.db',
sample_systems_format='db',
sample_systems_indices=[0, 1, 2, 3, -4, -3, -2, -1],
sample_calculator='XTB',
sample_calculator_args = {
'charge': 0,
'directory': 'test/xtb'},
sample_num_threads=1,
)
sampler.run()
from asparagus.sampling import MCSampler
# Sample a single system loaded from a xyz file using the Monte-Carlo
# sampling method with the XTB calculator
sampler = MCSampler(
config='test/mc_nh3.json',
sample_directory='test',
sample_data_file='test/mc_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
mc_temperature=300.0,
mc_steps=100,
mc_max_displacement=0.1,
mc_save_interval=1,
)
sampler.run()
# Sample two systems loaded from a xyz files in parallel using the
# Monte-Carlo sampling method and the ORCA calculator (thread safe)
sampler = MCSampler(
config='test/mc_nh3.json',
sample_directory='test',
sample_data_file='test/mc_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/nh3_d3h.xyz'],
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_save_trajectory=True,
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
mc_temperature=300.0,
mc_steps=10,
mc_max_displacement=0.1,
mc_save_interval=1,
)
sampler.run()
from asparagus.sampling import MDSampler
# Sample a single system loaded from a xyz file using the Molecular
# Dynamics sampling method with the XTB calculator
sampler = MDSampler(
config='test/md_nh3.json',
sample_directory='test',
sample_data_file='test/md_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
md_temperature=500,
md_time_step=1.0,
md_simulation_time=100.0,
md_save_interval=10,
md_langevin_friction=0.01,
md_equilibration_time=0,
md_initial_velocities=False,
)
sampler.run()
# Sample a single system loaded from a xyz file using the Molecular
# Dynamics sampling method with the XTB calculator
sampler = MDSampler(
config='test/md_nh3.json',
sample_directory='test',
sample_data_file='test/md_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
md_temperature={
'tstart': 10.0,
'tend': 100.0,
'tincrement': 10.0},
md_time_step=1.0,
md_simulation_time=10.0,
md_save_interval=10,
md_langevin_friction=0.01,
md_equilibration_time=0,
md_initial_velocities=False,
)
sampler.run()
# Sample a single system loaded from a xyz file using the Molecular
# Dynamics sampling method with the XTB calculator
sampler = MDSampler(
config='test/md_nh3.json',
sample_directory='test',
sample_data_file='test/md_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
md_temperature={
'tstart': 10.0,
'tinterval': 10.0},
md_time_step=1.0,
md_simulation_time=10.0,
md_save_interval=10,
md_langevin_friction=0.01,
md_equilibration_time=0,
md_initial_velocities=False,
)
sampler.run()
# Sample a single system loaded from a xyz file using the Molecular
# Dynamics sampling method with the XTB calculator
sampler = MDSampler(
config='test/md_nh3.json',
sample_directory='test',
sample_data_file='test/md_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
md_temperature={
'tstart': 10.0,
'tend': 100.0},
md_time_step=1.0,
md_simulation_time=10.0,
md_save_interval=10,
md_langevin_friction=0.01,
md_equilibration_time=0,
md_initial_velocities=False,
)
sampler.run()
# Sample two systems loaded from a xyz files in parallel using the
# Molecular Dynamics sampling method and the ORCA calculator (thread safe)
sampler = MDSampler(
config='test/md_nh3.json',
sample_directory='test',
sample_data_file='test/md_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/nh3_d3h.xyz'],
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_save_trajectory=True,
sample_num_threads=2,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
md_temperature=500,
md_time_step=1.0,
md_simulation_time=20.0,
md_save_interval=10,
md_langevin_friction=0.01,
md_equilibration_time=0,
md_initial_velocities=True,
md_initial_temperature=300,
)
sampler.run()
from asparagus.sampling import MetaSampler
# Sample a single system loaded from a xyz file using the Meta Dynamics
# sampling method with the XTB calculator
sampler = MetaSampler(
config='test/meta_nh3.json',
sample_directory='test',
sample_data_file='test/meta_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_save_trajectory=True,
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
meta_cv=[[0, 1], [0, 2], [0, 3]],
meta_gaussian_height=0.10,
meta_gaussian_widths=0.1,
meta_gaussian_interval=10,
meta_hookean=[[0, 1, 4.0], [0, 2, 4.0], [0, 3, 4.0]],
meta_temperature=500,
meta_time_step=1.0,
meta_simulation_time=10_0.0,
meta_save_interval=10,
)
sampler.run()
# Sample a system loaded from a xyz files in parallel using the Meta
# Dynamics sampling method and the ORCA calculator (thread safe)
# Here each of the multiple runs store the Gaussian add-potentials into
# in the same list, affecting the other runs as well and decrease the
# sample steps to reach higher potential areas.
# Not yet working as planned
sampler = MetaSampler(
config='test/meta_nh3.json',
sample_directory='test',
sample_data_file='test/meta_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_save_trajectory=True,
sample_num_threads=4,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
meta_cv=[[0, 1], [0, 2], [0, 3]],
meta_gaussian_height=0.10,
meta_gaussian_widths=0.1,
meta_gaussian_interval=10,
meta_hookean=[[0, 1, 4.0], [0, 2, 4.0], [0, 3, 4.0]],
meta_temperature=500,
meta_time_step=1.0,
meta_simulation_time=20.0,
meta_save_interval=10,
meta_parallel=True,
)
sampler.run()
# Sample two system loaded from a xyz files in parallel using the Meta
# Dynamics sampling method and the ORCA calculator (thread safe)
sampler = MetaSampler(
config='test/meta_nh3.json',
sample_directory='test',
sample_data_file='test/meta_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/nh3_d3h.xyz'],
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_save_trajectory=True,
sample_num_threads=2,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
meta_cv=[[0, 1], [0, 2], [0, 3]],
meta_gaussian_height=0.10,
meta_gaussian_widths=0.1,
meta_gaussian_interval=10,
meta_hookean=[[0, 1, 4.0], [0, 2, 4.0], [0, 3, 4.0]],
meta_temperature=500,
meta_time_step=1.0,
meta_simulation_time=20.0,
meta_save_interval=10,
)
sampler.run()
from asparagus.sampling import NormalModeScanner
# Sample a single system loaded from a xyz file using the Normal Mode
# Scanner sampling method with the XTB calculator
sampler = NormalModeScanner(
config='test/nms_nh3.json',
sample_directory='test',
sample_data_file='test/nms_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
nms_harmonic_energy_step=0.10,
nms_energy_limits=0.50,
nms_number_of_coupling=1,
nms_limit_of_steps=10,
nms_limit_com_shift=0.01,
nms_save_displacements=True,
)
sampler.run()
# Sample two systems loaded from a xyz file using the Normal Mode
# Scanner sampling method with the ORCA calculator (thread safe).
# Here it parallelize over the (1) system optimizations, (2) atom
# displacement calculations for numeric normal mode analysis and (3) the
# scans along single or combinations of normal modes. Step (2) and (3) will
# run in serial for each sample system.
sampler = NormalModeScanner(
config='test/nms_nh3.json',
sample_directory='test',
sample_data_file='test/nms_nh3.db',
sample_systems=['data/nh3_c3v.xyz', 'data/nh3_d3h.xyz'],
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_num_threads=4,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
nms_harmonic_energy_step=0.10,
nms_energy_limits=0.50,
nms_number_of_coupling=1,
nms_limit_of_steps=10,
nms_limit_com_shift=0.01,
nms_save_displacements=False,
)
sampler.run()
from asparagus.sampling import NormalModeSampler
# Sample a single system loaded from a xyz file using the Normal Mode
# Sampler sampling method with the XTB calculator
sampler = NormalModeSampler(
config='test/nms_nh3.json',
sample_directory='test',
sample_data_file='test/nms_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='XTB', # Not thread save when using ASE modules
sample_num_threads=1,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
nms_temperature=500.0,
nms_nsamples=100,
)
sampler.run()
# Sample a system loaded from a xyz file using the Normal Mode
# Sampler sampling method with the ORCA calculator (thread safe).
# Here it parallelize over the (1) system optimizations, (2) atom
# displacement calculations for numeric normal mode analysis and (3) the
# number of randomly sampled system conformations. Step (2) and (3) will
# run in serial for each potential sample system.
sampler = NormalModeSampler(
config='test/nms_nh3.json',
sample_directory='test',
sample_data_file='test/nms_nh3.db',
sample_systems='data/nh3_d3h.xyz',
sample_systems_format='xyz',
sample_calculator='ORCA',
sample_calculator_args = {
'charge': 0,
'mult': 1,
'orcasimpleinput': 'RI PBE D3BJ def2-SVP def2/J TightSCF',
'orcablocks': '%pal nprocs 1 end',
'directory': 'test/orca'},
sample_num_threads=4,
sample_systems_optimize=True,
sample_systems_optimize_fmax=0.001,
nms_temperature=500.0,
nms_nsamples=10,
)
sampler.run()
#==============================================================================
# Test Asparagus Calculators - Shell & Slurm
#==============================================================================
# Shell Calculator
if flag_sampler_shell:
from asparagus.sampling import Sampler
# Calculate properties of a sample system with multiple conformations
# using the Shell calculator with template files for an ORCA calculation.
sampler = Sampler(
config='test/calc_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='shell',
sample_calculator_args = {
'files': [
'asparagus/templates/shell/run_orca.sh',
'asparagus/templates/shell/run_orca.inp',
'asparagus/templates/shell/run_orca.py',
],
'files_replace': {
'%xyz%': '$xyz',
'%charge%': '$charge',
'%multiplicity%': '$multiplicity',
},
'execute_file': 'run_orca.sh',
'charge': 0,
'multiplicity': 1,
'directory': 'test/shell',
'result_properties': ['energy', 'forces', 'dipole']
},
sample_num_threads=1,
)
sampler.run()
# Calculate properties of a sample system with multiple conformations
# using the Shell calculator with template files for an ORCA calculation
# and in parallel.
sampler = Sampler(
config='test/calc_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/meta_nh3.traj',
sample_calculator='shell',
sample_calculator_args = {
'files': [
'asparagus/templates/shell/run_orca.sh',
'asparagus/templates/shell/run_orca.inp',
'asparagus/templates/shell/run_orca.py',
],
'files_replace': {
'%xyz%': '$xyz',
'%charge%': '$charge',
'%multiplicity%': '$multiplicity',
},
'execute_file': 'asparagus/templates/shell/run_orca.sh',
'charge': 0,
'multiplicity': 1,
'directory': 'test/shell',
'result_properties': ['energy', 'forces', 'dipole']
},
sample_num_threads=4,
sample_save_trajectory=True,
)
sampler.run()
# Slurm Calculator
if flag_sampler_slurm:
from asparagus.sampling import Sampler
# Calculate properties of a sample system with multiple conformations
# using the slurm calculator with template files for a MOLPRO calculation.
sampler = Sampler(
config='test/calc_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='slurm',
sample_calculator_args = {
'remote_client': 'pc-beethoven',
'files': [
'asparagus/templates/slurm/run_molpro.sh',
'asparagus/templates/slurm/run_molpro.inp',
'asparagus/templates/slurm/run_molpro.py',
],
'files_replace': {
'%xyz%': '$xyz',
'%charge%': '$charge',
'%spin2%': '$spin2',
},
'execute_file': 'run_molpro.sh',
'charge': 0,
'multiplicity': 1,
'directory': 'test/slurm',
'result_properties': ['energy', 'forces', 'dipole'],
},
sample_num_threads=1,
)
sampler.run()
# Calculate properties of a sample system with multiple conformations
# using the Slurm calculator with template files for a MOLPRO calculation.
# Here, define own slurm task id catch and check function
import subprocess
def catch_id(
stdout: str,
) -> int:
"""
Catch slurm task id from the output when running:
subrocess.run([command, execute_file], capture_output=True)
(here [command, execute_file] -> 'sbatch run_molpro.sh')
Parameters
----------
stdout: str
Decoded output line (e.g. 'Submitted batch job 10937679')
Return
------
int
Task id
"""
return int(proc.stdout.decode().split()[-1])
sampler = Sampler(
config='test/calc_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nh3_c3v.xyz',
sample_systems_format='xyz',
sample_calculator='slurm',
sample_calculator_args = {
'remote_client': 'pc-beethoven',
'files': [
'asparagus/templates/slurm/run_molpro.sh',
'asparagus/templates/slurm/run_molpro.inp',
'asparagus/templates/slurm/run_molpro.py',
],
'files_replace': {
'%xyz%': '$xyz',
'%charge%': '$charge',
'%spin2%': '$spin2',
},
'execute_file': 'run_molpro.sh',
'charge': 0,
'multiplicity': 1,
'directory': 'test/slurm',
'result_properties': ['energy', 'forces', 'dipole']
},
sample_num_threads=1,
scan_interval=1,
scan_catch_id=catch_id,
)
sampler.run()
# Calculate properties of a sample system with multiple conformations
# using the Slurm calculator with template files for a MOLPRO calculation.
sampler = Sampler(
config='test/calc_nh3.json',
sample_directory='test',
sample_data_file='test/smpl_nh3.db',
sample_systems='data/nms_nh3.db',
sample_systems_format='db',
sample_systems_indices=[0, 1, 2, 3, -4, -3, -2, -1],
sample_calculator='slurm',
sample_calculator_args = {
'remote_client': 'pc-beethoven',
'files': [
'asparagus/templates/slurm/run_molpro.sh',
'asparagus/templates/slurm/run_molpro.inp',
'asparagus/templates/slurm/run_molpro.py',
],
'files_replace': {
'%xyz%': '$xyz',
'%charge%': '$charge',
'%spin2%': '$spin2',