Author: bugman
Date: Thu Apr 4 16:28:42 2013
New Revision: 19363
URL: http://svn.gna.org/viewcvs/relax?rev=19363&view=rev
Log:
The relax_disp function _grid_search_setup() now operates in the same way as
the relax_fit code.
This function originates from the 'relax_fit' specific analysis code, but
that code has since
evolved. The 'relax_disp' code now mimics the new code, returning lists of
grid search increments
and upper and lower limits.
Modified:
branches/relax_disp/specific_analyses/relax_disp.py
Modified: branches/relax_disp/specific_analyses/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp.py?rev=19363&r1=19362&r2=19363&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp.py Thu Apr 4 16:28:42
2013
@@ -538,103 +538,91 @@
raise RelaxError("Cannot run a grid search on a model with zero
parameters.")
# Lower bounds.
- if lower != None:
- if len(lower) != n:
- raise RelaxLenError('lower bounds', n)
+ if lower != None and len(lower) != n:
+ raise RelaxLenError('lower bounds', n)
# Upper bounds.
- if upper != None:
- if len(upper) != n:
- raise RelaxLenError('upper bounds', n)
+ if upper != None and len(upper) != n:
+ raise RelaxLenError('upper bounds', n)
# Increment.
- if type(inc) == list:
- if len(inc) != n:
- raise RelaxLenError('increment', n)
- inc = inc
- elif type(inc) == int:
- temp = []
- for j in xrange(n):
- temp.append(inc)
- inc = temp
-
- # Minimisation options initialisation.
- min_options = []
- j = 0
-
- # First add the spin specific parameters.
- for spin_index in range(len(spins)):
- # Alias the spin.
- spin = spins[spin_index]
-
- # Loop over each exponential curve.
- for exp_i, key in self._exp_curve_loop():
- # Loop over the parameters.
- for i in range(len(spin.params)):
- # R2eff relaxation rate (from 0 to 40 s^-1).
- if spin.params[i] == 'R2eff':
- min_options.append([inc[j], 0.0, 40.0])
-
- # Intensity.
- elif spin.params[i] == 'I0':
- min_options.append([inc[j], 0.0,
max(spin.intensities.values())])
-
- # Increment j.
- j += 1
-
- # Then the spin block specific parameters.
- spin = spins[0]
- for i in range(len(spin.params)):
- # R2 relaxation rate (from 0 to 40 s^-1).
- if spin.params[i] == 'R2':
- min_options.append([inc[j], 0.0, 40.0])
-
- # Chemical exchange contribution to 'R2'.
- elif spin.params[i] == 'Rex':
- min_options.append([inc[j], 0.0, 20.0])
-
- # Exchange rate.
- elif spin.params[i] == 'kex':
- min_options.append([inc[j], 0.0, 100000.0])
-
- # Transversal relaxation rate for state A.
- elif spin.params[i] == 'R2A':
- min_options.append([inc[j], 0.0, 20.0])
-
- # Exchange rate from state A to state B.
- elif spin.params[i] == 'kA':
- min_options.append([inc[j], 0.0, 100000.0])
-
- # Chemical shift difference between states A and B.
- elif spin.params[i] == 'dw':
- min_options.append([inc[j], 0.0, 10000.0])
-
- # Increment j.
- j += 1
-
- # Set the lower and upper bounds if these are supplied.
- if lower != None:
- for j in xrange(n):
- if lower[j] != None:
- min_options[j][1] = lower[j]
- if upper != None:
- for j in xrange(n):
- if upper[j] != None:
- min_options[j][2] = upper[j]
+ if isinstance(inc, list) and len(inc) != n:
+ raise RelaxLenError('increment', n)
+ elif isinstance(inc, int):
+ inc = [inc]*n
+
+ # Set up the default bounds.
+ if not lower:
+ # Init.
+ lower = []
+ upper = []
+
+ # First add the spin specific parameters.
+ for spin_index in range(len(spins)):
+ # Alias the spin.
+ spin = spins[spin_index]
+
+ # Loop over each exponential curve.
+ for exp_i, key in self._exp_curve_loop():
+ # Loop over the parameters.
+ for i in range(len(spin.params)):
+ # R2eff relaxation rate (from 0 to 40 s^-1).
+ if spin.params[i] == 'R2eff':
+ lower.append(0.0)
+ upper.append(40.0)
+
+ # Intensity.
+ elif spin.params[i] == 'I0':
+ lower.append(0.0)
+ upper.append(max(spin.intensities.values()))
+
+ # Then the spin block specific parameters.
+ spin = spins[0]
+ for i in range(len(spin.params)):
+ # R2 relaxation rate (from 0 to 40 s^-1).
+ if spin.params[i] == 'R2':
+ lower.append(0.0)
+ upper.append(40.0)
+
+ # Chemical exchange contribution to 'R2'.
+ elif spin.params[i] == 'Rex':
+ lower.append(0.0)
+ upper.append(20.0)
+
+ # Exchange rate.
+ elif spin.params[i] == 'kex':
+ lower.append(0.0)
+ upper.append(100000.0)
+
+ # Transversal relaxation rate for state A.
+ elif spin.params[i] == 'R2A':
+ lower.append(0.0)
+ upper.append(20.0)
+
+ # Exchange rate from state A to state B.
+ elif spin.params[i] == 'kA':
+ lower.append(0.0)
+ upper.append(100000.0)
+
+ # Chemical shift difference between states A and B.
+ elif spin.params[i] == 'dw':
+ lower.append(0.0)
+ upper.append(10000.0)
# Test if the grid is too large.
grid_size = 1
- for i in xrange(len(min_options)):
- grid_size = grid_size * min_options[i][0]
- if type(grid_size) == long:
+ for i in range(n):
+ grid_size = grid_size * inc[0]
+ if isinstance(grid_size, long):
raise RelaxError("A grid search of size %s is too large." %
grid_size)
# Diagonal scaling of minimisation options.
- for j in range(len(min_options)):
- min_options[j][1] = min_options[j][1] * scaling_matrix[j, j]
- min_options[j][2] = min_options[j][2] * scaling_matrix[j, j]
-
- return grid_size, min_options
+ for i in range(n):
+ lower[i] = lower[i] / scaling_matrix[i, i]
+ upper[i] = upper[i] / scaling_matrix[i, i]
+
+ # Return the data structures.
+ return grid_size, inc, lower, upper
def _linear_constraints(self, spins=None, scaling_matrix=None):
@@ -1066,7 +1054,7 @@
# Get the grid search minimisation options.
if match('^[Gg]rid', min_algor):
- grid_size, min_options =
self._grid_search_setup(spins=spins, param_vector=param_vector, lower=lower,
upper=upper, inc=inc, scaling_matrix=scaling_matrix)
+ grid_size, inc, lower, upper =
self._grid_search_setup(spins=spins, param_vector=param_vector, lower=lower,
upper=upper, inc=inc, scaling_matrix=scaling_matrix)
# Linear constraints.
A, b = None, None
r19363 - /branches/relax_disp/specific_analyses/relax_disp.py