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.
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