Python Relax_data_store.tmpdir方法代码示例

# 需要导入模块: from data_store import Relax_data_store [as 别名]
# 或者: from data_store.Relax_data_store import tmpdir [as 别名]
if not hasattr(ds, 'models'):
    ds.models = ['R2eff', 'TP02']

# The grid search size (the number of increments per dimension).
GRID_INC = 4

# The number of Monte Carlo simulations to be used for error analysis at the end of the analysis.
MC_NUM = 1


# Set up the data pipe.
#######################

# The results directory.
if not hasattr(ds, 'tmpdir'):
    ds.tmpdir = None

# Create the data pipe.
pipe_name = 'base pipe'
pipe_bundle = 'relax_disp'
pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type='relax_disp')

# The path to the data files (use the M61 model data for now).
data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02'

# Create the sequence data.
spin.create(res_name='Trp', res_num=1, spin_name='N')
spin.create(res_name='Trp', res_num=2, spin_name='N')

# Set the isotope information.
spin.isotope(isotope='15N')

# 需要导入模块: from data_store import Relax_data_store [as 别名]
# 或者: from data_store.Relax_data_store import tmpdir [as 别名]
# Script for model-free analysis using the program 'Modelfree4'.

# Python module imports.
from os import sep

# relax module imports.
from data_store import Relax_data_store; ds = Relax_data_store()
from status import Status; status = Status()


# Missing temp directory (allow this script to run outside of the system test framework).
if not hasattr(ds, 'tmpdir'):
    ds.tmpdir = 'temp_script'

# Path of the relaxation data.
DATA_PATH = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'model_free'+sep+'OMP'


def exec_stage_1(pipes):
    """Stage 1 function.

    Initial model-free minimisation.
    """

    # Loop over the data pipes.
    for name in pipes:
        # Create the data pipe.
        print("\n\n# " + name + " #")
        pipe.create(name, 'mf')

        # Copy the sequence.

# 需要导入模块: from data_store import Relax_data_store [as 别名]
# 或者: from data_store.Relax_data_store import tmpdir [as 别名]
# Analysis variables.
#####################

# The dispersion models.
if not hasattr(ds, 'models'):
    ds.models = ['R2eff', 'No Rex', 'NS MMQ 2-site']

# The grid search size (the number of increments per dimension).
GRID_INC = 4

# The number of Monte Carlo simulations to be used for error analysis at the end of the analysis.
MC_NUM = 3

# The temporary directory, if needed.
if not hasattr(ds, 'tmpdir'):
    ds.tmpdir = 'temp'


# Set up the data pipe.
#######################

# Create the data pipe.
pipe_name = 'base pipe'
pipe_bundle = 'relax_disp'
pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type='relax_disp')

# The path to the data files.
data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP'

# Create the sequence.
spin.create(res_num=135, spin_name='S')

# 需要导入模块: from data_store import Relax_data_store [as 别名]
# 或者: from data_store.Relax_data_store import tmpdir [as 别名]
MIN_ALGOR = 'newton'

# The number of Monte Carlo simulations to be used for error analysis at the end of the analysis.
MC_NUM = 3

# Automatic looping over all rounds until convergence (must be a boolean value of True or False).
CONV_LOOP = True



# Load the state.
data_path = status.install_path + sep + 'test_suite' + sep + 'shared_data' + sep + 'model_free' + sep + 'bug_20613_auto_mf_diff_tensor_pdb'
state.load('state', dir=data_path)

# The results dir.
ds.tmpdir = mkdtemp()

# The pipe and bundle names from the state file.
pipe_bundle = 'mf (Fri Mar  8 07:43:00 2013)'
name = 'origin - mf (Fri Mar  8 07:43:00 2013)'


# Execution.
############

dAuvergne_protocol.opt_func_tol = 1e-5
dAuvergne_protocol.opt_max_iterations = 2000

# Do not change!
dAuvergne_protocol(pipe_name=name, pipe_bundle=pipe_bundle, results_dir=data_path, write_results_dir=ds.tmpdir, diff_model=DIFF_MODEL, mf_models=MF_MODELS, local_tm_models=LOCAL_TM_MODELS, grid_inc=GRID_INC, min_algor=MIN_ALGOR, mc_sim_num=MC_NUM, max_iter=2, conv_loop=CONV_LOOP)