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# relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7)
</source>
=== 2_pre_run_r2eff.py ===
# Run the analysis.
Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=ds.results_dir, models=ds.models, grid_inc=ds.grid_inc, exp_mc_sim_num=ds.exp_mc_sim_num)
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=== 3_analyse_models.py ===
This a script file to analyse the models.
file: '''3_analyse_models.py'''.
<source lang="Python">
# Python module imports.
from os import getcwd, sep
import re
# relax module imports.
from auto_analyses.relax_disp import Relax_disp
from data_store import Relax_data_store; ds = Relax_data_store()
from specific_analyses.relax_disp.variables import MODEL_R2EFF, MODEL_NOREX_R1RHO_FIT_R1, MODEL_DPL94_FIT_R1
#########################################
#### Setup
# The pipe names.
if not (hasattr(ds, 'pipe_name') and hasattr(ds, 'pipe_bundle') and hasattr(ds, 'pipe_type')):
# Set pipe name, bundle and type.
ds.pipe_name = 'base pipe'
ds.pipe_bundle = 'relax_disp'
ds.pipe_type = 'relax_disp'
# The data path
if not hasattr(ds, 'data_path'):
ds.data_path = getcwd()
# The models to analyse.
if not hasattr(ds, 'models'):
ds.models = [MODEL_NOREX_R1RHO_FIT_R1, MODEL_DPL94_FIT_R1]
# 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
#########################################
# Create the data pipe.
pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type)
# Load the previous results into the base pipe.
results.read(file='results', dir=ds.pre_run_dir)
# Run the analysis.
Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=ds.results_dir, models=ds.models, grid_inc=ds.grid_inc, mc_sim_num=ds.mc_sim_num, modsel=ds.modsel)
</source>
= See also =
[[Category:Tutorials]]
