Author: tlinnet Date: Tue Aug 12 15:23:55 2014 New Revision: 24999 URL: http://svn.gna.org/viewcvs/relax?rev=24999&view=rev Log: Implemented partial reading of results file. Before reading a results file, it is determined if the file exists. This makes is possible to read a directory with partial results from a previous analysis. This can be handsome, if reading R2eff values in R1rho experiments, and the error estimation has been prepared with a high number of Monte-Carlo simulations. sr #3135(https://gna.org/support/?3135): Optimisation of the R1 relaxation rate for the off-resonance R1rho relaxation dispersion models. Modified: branches/R1_fitting/auto_analyses/relax_disp.py Modified: branches/R1_fitting/auto_analyses/relax_disp.py URL: http://svn.gna.org/viewcvs/relax/branches/R1_fitting/auto_analyses/relax_disp.py?rev=24999&r1=24998&r2=24999&view=diff ============================================================================== --- branches/R1_fitting/auto_analyses/relax_disp.py (original) +++ branches/R1_fitting/auto_analyses/relax_disp.py Tue Aug 12 15:23:55 2014 @@ -30,7 +30,8 @@ from warnings import warn # relax module imports. -from lib.errors import RelaxError, RelaxNoPipeError +from lib.errors import RelaxError, RelaxFileError, RelaxNoPipeError +from lib.io import determine_compression, get_file_path from lib.text.sectioning import section, subsection, subtitle, title from lib.warnings import RelaxWarning from pipe_control.mol_res_spin import return_spin, spin_loop @@ -446,7 +447,21 @@ self.interpreter.relax_disp.r20_from_min_r2eff(force=True) # Use pre-run results as the optimisation starting point. + # Test if file exists. if self.pre_run_dir: + path = self.pre_run_dir + sep + model + # File path. + file_path = get_file_path('results', path) + + # Test if the file exists and determine the compression type. + try: + compress_type, file_path = determine_compression(file_path) + res_file_exists = True + + except RelaxFileError: + res_file_exists = False + + if self.pre_run_dir and res_file_exists: self.pre_run_parameters(model=model) # Otherwise use the normal nesting check and grid search if not nested.