本文整理汇总了Python中data_store.Relax_data_store.results_dir方法的典型用法代码示例。如果您正苦于以下问题：Python Relax_data_store.results_dir方法的具体用法？Python Relax_data_store.results_dir怎么用？Python Relax_data_store.results_dir使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类data_store.Relax_data_store的用法示例。
在下文中一共展示了Relax_data_store.results_dir方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: hasattr
# 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 results_dir [as 别名]
# The number of Monte-Carlo simulations for estimating the error of the parameters of the fitted models.
if not hasattr(ds, 'mc_sim_num'):
ds.mc_sim_num = 10
# The model selection technique. Either: 'AIC', 'AICc', 'BIC'
if not hasattr(ds, 'modsel'):
ds.modsel = 'AIC'
# The previous result directory with R2eff values.
if not hasattr(ds, 'pre_run_dir'):
ds.pre_run_dir = getcwd() + sep + 'results_R2eff' + sep + 'R2eff'
# The result directory.
if not hasattr(ds, 'results_dir'):
ds.results_dir = getcwd() + sep + 'results_models'
## The optimisation function tolerance.
## This is set to the standard value, and should not be changed.
#if not hasattr(ds, 'opt_func_tol'):
# ds.opt_func_tol = 1e-25
#Relax_disp.opt_func_tol = ds.opt_func_tol
#if not hasattr(ds, 'opt_max_iterations'):
# ds.opt_max_iterations = int(1e7)
#Relax_disp.opt_max_iterations = ds.opt_max_iteration
#########################################
# Create the data pipe.
pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type)
示例2: hasattr
# 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 results_dir [as 别名]
# The number of Monte-Carlo simulations for estimating the error of the parameters of the fitted models.
if not hasattr(ds, 'mc_sim_num'):
ds.mc_sim_num = 10
# The model selection technique. Either: 'AIC', 'AICc', 'BIC'
if not hasattr(ds, 'modsel'):
ds.modsel = 'AIC'
# The previous result directory with R2eff values.
if not hasattr(ds, 'pre_run_dir'):
ds.pre_run_dir = getcwd() + sep + 'results_models' + sep + ds.models[0]
# The result directory.
if not hasattr(ds, 'results_dir'):
ds.results_dir = getcwd() + sep + 'results_clustering'
## The optimisation function tolerance.
## This is set to the standard value, and should not be changed.
#if not hasattr(ds, 'opt_func_tol'):
# ds.opt_func_tol = 1e-25
#Relax_disp.opt_func_tol = ds.opt_func_tol
#if not hasattr(ds, 'opt_max_iterations'):
# ds.opt_max_iterations = int(1e7)
#Relax_disp.opt_max_iterations = ds.opt_max_iteration
#########################################
# Create the data pipe.
ini_pipe_name = '%s - %s' % (ds.models[0], ds.pipe_bundle)
pipe.create(pipe_name=ini_pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type)示例3: hasattr
# 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 results_dir [as 别名]
if not hasattr(ds, 'models'):
ds.models = [MODEL_R2EFF]
# The number of increments per parameter, to split up the search interval in grid search.
if not hasattr(ds, 'grid_inc'):
ds.grid_inc = 21
# The number of Monte-Carlo simulations, for the error analysis in the 'R2eff' model when exponential curves are fitted.
# For estimating the error of the fitted R2eff values,
# a high number should be provided. Later the high quality R2eff values will be read for subsequent model analyses.
if not hasattr(ds, 'exp_mc_sim_num'):
ds.exp_mc_sim_num = 2000
# The result directory.
if not hasattr(ds, 'results_dir'):
ds.results_dir = getcwd() + sep + 'results_R2eff'
## The optimisation function tolerance.
## This is set to the standard value, and should not be changed.
#if not hasattr(ds, 'opt_func_tol'):
# ds.opt_func_tol = 1e-25
#Relax_disp.opt_func_tol = ds.opt_func_tol
#if not hasattr(ds, 'opt_max_iterations'):
# ds.opt_max_iterations = int(1e7)
#Relax_disp.opt_max_iterations = ds.opt_max_iteration
#########################################
### Run script with setup.
script(file='1_setup_r1rho.py', dir=ds.data_path)