Author: bugman
Date: Wed Jan 9 14:38:00 2008
New Revision: 4549
URL: http://svn.gna.org/viewcvs/relax?rev=4549&view=rev
Log:
Changed all instances of the 'print_flag' arg to 'verbosity' in the
generic_fns.minimise module.
Modified:
1.3/generic_fns/minimise.py
Modified: 1.3/generic_fns/minimise.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/generic_fns/minimise.py?rev=4549&r1=4548&r2=4549&view=diff
==============================================================================
--- 1.3/generic_fns/minimise.py (original)
+++ 1.3/generic_fns/minimise.py Wed Jan 9 14:38:00 2008
@@ -108,12 +108,12 @@
-def calc(print_flag=1):
+def calc(verbosity=1):
"""Function for calculating the function value.
- @param print_flag: A flag specifying the amount of information to
print. The higher the value,
- the greater the verbosity.
- @type print_flag: int
+ @param verbosity: The amount of information to print. The higher the
value, the greater
+ the verbosity.
+ @type verbosity: int
"""
# Alias the current data pipe.
@@ -130,16 +130,16 @@
if hasattr(cdp, 'sim_state') and cdp.sim_state == 1:
# Loop over the simulations.
for i in xrange(cdp.sim_number):
- if print_flag:
+ if verbosity:
print "Simulation " + `i+1`
- calculate(print_flag=print_flag-1, sim_index=i)
+ calculate(verbosity=verbosity-1, sim_index=i)
# Minimisation.
else:
- calculate(print_flag=print_flag)
-
-
-def grid_search(lower=None, upper=None, inc=None, constraints=1,
print_flag=1):
+ calculate(verbosity=verbosity)
+
+
+def grid_search(lower=None, upper=None, inc=None, constraints=1,
verbosity=1):
"""The grid search function.
@param lower: The lower bounds of the grid search which must be
equal to the number of
@@ -155,9 +155,9 @@
@param constraints: If true, constraints are applied during the grid
search (elinating parts of
the grid). If false, no constraints are used.
@type constraints: bool
- @param print_flag: A flag specifying the amount of information to
print. The higher the value,
- the greater the verbosity.
- @type print_flag: int
+ @param verbosity: The amount of information to print. The higher the
value, the greater
+ the verbosity.
+ @type verbosity: int
"""
# Alias the current data pipe.
@@ -174,16 +174,16 @@
if hasattr(cdp, 'sim_state') and cdp.sim_state == 1:
# Loop over the simulations.
for i in xrange(cdp.sim_number):
- if print_flag:
+ if verbosity:
print "Simulation " + `i+1`
- grid_search(lower=lower, upper=upper, inc=inc,
constraints=constraints, print_flag=print_flag-1, sim_index=i)
+ grid_search(lower=lower, upper=upper, inc=inc,
constraints=constraints, verbosity=verbosity-1, sim_index=i)
# Grid search.
else:
- grid_search(lower=lower, upper=upper, inc=inc,
constraints=constraints, print_flag=print_flag)
-
-
-def minimise(min_algor=None, min_options=None, func_tol=None, grad_tol=None,
max_iterations=None, constraints=1, scaling=1, print_flag=1, sim_index=None):
+ grid_search(lower=lower, upper=upper, inc=inc,
constraints=constraints, verbosity=verbosity)
+
+
+def minimise(min_algor=None, min_options=None, func_tol=None, grad_tol=None,
max_iterations=None, constraints=1, scaling=1, verbosity=1, sim_index=None):
"""Minimisation function.
@param min_algor: The minimisation algorithm to use.
@@ -203,9 +203,9 @@
@param scaling: If true, diagonal scaling is enabled during
optimisation to allow the
problem to be better conditioned.
@type scaling: bool
- @param print_flag: A flag specifying the amount of information to
print. The higher the
- value, the greater the verbosity.
- @type print_flag: int
+ @param verbosity: The amount of information to print. The higher
the value, the greater
+ the verbosity.
+ @type verbosity: int
@param sim_index: The index of the simulation to optimise. This
should be None if normal
optimisation is desired.
@type sim_index: None or int
@@ -223,18 +223,18 @@
# Single Monte Carlo simulation.
if sim_index != None:
- minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, print_flag=print_flag,
sim_index=sim_index)
+ minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, verbosity=verbosity,
sim_index=sim_index)
# Monte Carlo simulation minimisation.
elif hasattr(relax_data_store, 'sim_state') and
relax_data_store.sim_state == 1:
for i in xrange(relax_data_store.sim_number):
- if print_flag:
+ if verbosity:
print "Simulation " + `i+1`
- minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, print_flag=print_flag-1,
sim_index=i)
+ minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, verbosity=verbosity-1, sim_index=i)
# Standard minimisation.
else:
- minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, print_flag=print_flag)
+ minimise(min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, max_iterations=max_iterations,
constraints=constraints, scaling=scaling, verbosity=verbosity)
def return_conversion_factor(stat_type):
r4549 - /1.3/generic_fns/minimise.py