mailRe: r24999 - /branches/R1_fitting/auto_analyses/relax_disp.py


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Posted by Edward d'Auvergne on August 18, 2014 - 18:38:
That is a far more robust solution!

Cheers,

Edward


On 12 August 2014 15:23,  <tlinnet@xxxxxxxxxxxxx> wrote:
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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