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Python Relax_data_store.pre_run_dir方法代碼示例

本文整理匯總了Python中data_store.Relax_data_store.pre_run_dir方法的典型用法代碼示例。如果您正苦於以下問題:Python Relax_data_store.pre_run_dir方法的具體用法?Python Relax_data_store.pre_run_dir怎麽用?Python Relax_data_store.pre_run_dir使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在data_store.Relax_data_store的用法示例。


在下文中一共展示了Relax_data_store.pre_run_dir方法的2個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: hasattr

# 需要導入模塊: from data_store import Relax_data_store [as 別名]
# 或者: from data_store.Relax_data_store import pre_run_dir [as 別名]
# This is not used, when pointing to a previous result directory.
# Then an average of the previous values will be used.
if not hasattr(ds, 'grid_inc'):
    ds.grid_inc = 10

# 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
開發者ID:pombredanne,項目名稱:relax,代碼行數:32,代碼來源:5_clustered_analyses.py

示例2: hasattr

# 需要導入模塊: from data_store import Relax_data_store [as 別名]
# 或者: from data_store.Relax_data_store import pre_run_dir [as 別名]
# The number of increments per parameter, to split up the search interval in grid search.
if not hasattr(ds, 'grid_inc'):
    ds.grid_inc = 10

# 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
開發者ID:pombredanne,項目名稱:relax,代碼行數:31,代碼來源:3_analyse_models.py


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