Author: bugman
Date: Mon Jul 21 09:17:44 2014
New Revision: 24579
URL: http://svn.gna.org/viewcvs/relax?rev=24579&view=rev
Log:
Updated all of the specific API minimise() methods to accept the
scaling_matrix argument.
The list of per-model scaling matrices is now created independently of the
analysis type by the
pipe_control.minimise methods for the minimise.calculate,
minimise.grid_search and minimise.execute
user functions and sent into the specific analysis backend.
Modified:
branches/zooming_grid_search/specific_analyses/frame_order/api.py
branches/zooming_grid_search/specific_analyses/model_free/api.py
branches/zooming_grid_search/specific_analyses/n_state_model/api.py
branches/zooming_grid_search/specific_analyses/relax_disp/api.py
Modified: branches/zooming_grid_search/specific_analyses/frame_order/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/zooming_grid_search/specific_analyses/frame_order/api.py?rev=24579&r1=24578&r2=24579&view=diff
==============================================================================
--- branches/zooming_grid_search/specific_analyses/frame_order/api.py
(original)
+++ branches/zooming_grid_search/specific_analyses/frame_order/api.py Mon
Jul 21 09:17:44 2014
@@ -519,33 +519,33 @@
return [0.0, pi]
- def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling=True,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
+ def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
"""Minimisation function.
- @param min_algor: The minimisation algorithm to use.
- @type min_algor: str
- @param min_options: An array of options to be used by the
minimisation algorithm.
- @type min_options: array of str
- @param func_tol: The function tolerance which, when reached,
terminates optimisation. Setting this to None turns of the check.
- @type func_tol: None or float
- @param grad_tol: The gradient tolerance which, when reached,
terminates optimisation. Setting this to None turns of the check.
- @type grad_tol: None or float
- @param max_iterations: The maximum number of iterations for the
algorithm.
- @type max_iterations: int
- @param constraints: If True, constraints are used during
optimisation.
- @type constraints: bool
- @param scaling: If True, diagonal scaling is enabled during
optimisation to allow the problem to be better conditioned.
- @type scaling: bool
- @param verbosity: A flag specifying 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
- @keyword lower: The lower bounds of the grid search which
must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
- @type lower: array of numbers
- @keyword upper: The upper bounds of the grid search which
must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
- @type upper: array of numbers
- @keyword inc: The increments for each dimension of the
space for the grid search. The number of elements in the array must equal to
the number of parameters in the model. This argument is only used when doing
a grid search.
- @type inc: array of int
+ @param min_algor: The minimisation algorithm to use.
+ @type min_algor: str
+ @param min_options: An array of options to be used by the
minimisation algorithm.
+ @type min_options: array of str
+ @param func_tol: The function tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
+ @type func_tol: None or float
+ @param grad_tol: The gradient tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
+ @type grad_tol: None or float
+ @param max_iterations: The maximum number of iterations for the
algorithm.
+ @type max_iterations: int
+ @param constraints: If True, constraints are used during
optimisation.
+ @type constraints: bool
+ @keyword scaling_matrix: The per-model list of diagonal and
square scaling matrices.
+ @type scaling_matrix: list of numpy rank-2, float64 array or
list of None
+ @param verbosity: A flag specifying 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
+ @keyword lower: The lower bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
+ @type lower: array of numbers
+ @keyword upper: The upper bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
+ @type upper: array of numbers
+ @keyword inc: The increments for each dimension of the
space for the grid search. The number of elements in the array must equal to
the number of parameters in the model. This argument is only used when doing
a grid search.
+ @type inc: array of int
"""
# Set up the target function for direct calculation.
Modified: branches/zooming_grid_search/specific_analyses/model_free/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/zooming_grid_search/specific_analyses/model_free/api.py?rev=24579&r1=24578&r2=24579&view=diff
==============================================================================
--- branches/zooming_grid_search/specific_analyses/model_free/api.py
(original)
+++ branches/zooming_grid_search/specific_analyses/model_free/api.py Mon
Jul 21 09:17:44 2014
@@ -1060,7 +1060,7 @@
return [-100 * 1e-6, -300 * 1e-6]
- def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling=True,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
+ def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
"""Model-free minimisation function.
Three categories of models exist for which the approach to
minimisation is different. These
@@ -1081,37 +1081,25 @@
@type min_algor: str
@keyword min_options: An array of options to be used by the
minimisation algorithm.
@type min_options: array of str
- @keyword func_tol: The function tolerance which, when
reached, terminates optimisation.
- Setting this to None turns of the check.
+ @keyword func_tol: The function tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
@type func_tol: None or float
- @keyword grad_tol: The gradient tolerance which, when
reached, terminates optimisation.
- Setting this to None turns of the check.
+ @keyword grad_tol: The gradient tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
@type grad_tol: None or float
@keyword max_iterations: The maximum number of iterations for the
algorithm.
@type max_iterations: int
@keyword constraints: If True, constraints are used during
optimisation.
@type constraints: bool
- @keyword scaling: If True, diagonal scaling is enabled
during optimisation to allow
- the problem to be better conditioned.
- @type scaling: bool
- @keyword verbosity: The amount of information to print. The
higher the value, the
- greater the verbosity.
+ @keyword scaling_matrix: The per-model list of diagonal and
square scaling matrices.
+ @type scaling_matrix: list of numpy rank-2, float64 array or
list of None
+ @keyword verbosity: The amount of information to print. The
higher the value, the greater the verbosity.
@type verbosity: int
- @keyword sim_index: The index of the simulation to optimise.
This should be None if
- normal optimisation is desired.
+ @keyword sim_index: The index of the simulation to optimise.
This should be None if normal optimisation is desired.
@type sim_index: None or int
- @keyword lower: The lower bounds of the grid search
which must be equal to the
- number of parameters in the model. This
optional argument is only
- used when doing a grid search.
+ @keyword lower: The lower bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
@type lower: array of numbers
- @keyword upper: The upper bounds of the grid search
which must be equal to the
- number of parameters in the model. This
optional argument is only
- used when doing a grid search.
+ @keyword upper: The upper bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
@type upper: array of numbers
- @keyword inc: The increments for each dimension of the
space for the grid search.
- The number of elements in the array must
equal to the number of
- parameters in the model. This argument
is only used when doing a
- grid search.
+ @keyword inc: The increments for each dimension of the
space for the grid search. The number of elements in the array must equal to
the number of parameters in the model. This argument is only used when doing
a grid search.
@type inc: array of int
"""
Modified: branches/zooming_grid_search/specific_analyses/n_state_model/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/zooming_grid_search/specific_analyses/n_state_model/api.py?rev=24579&r1=24578&r2=24579&view=diff
==============================================================================
--- branches/zooming_grid_search/specific_analyses/n_state_model/api.py
(original)
+++ branches/zooming_grid_search/specific_analyses/n_state_model/api.py Mon
Jul 21 09:17:44 2014
@@ -419,33 +419,33 @@
return [-100.0, 100.0]
- def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling=True,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
+ def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
"""Minimisation function.
- @param min_algor: The minimisation algorithm to use.
- @type min_algor: str
- @param min_options: An array of options to be used by the
minimisation algorithm.
- @type min_options: array of str
- @param func_tol: The function tolerance which, when reached,
terminates optimisation. Setting this to None turns of the check.
- @type func_tol: None or float
- @param grad_tol: The gradient tolerance which, when reached,
terminates optimisation. Setting this to None turns of the check.
- @type grad_tol: None or float
- @param max_iterations: The maximum number of iterations for the
algorithm.
- @type max_iterations: int
- @param constraints: If True, constraints are used during
optimisation.
- @type constraints: bool
- @param scaling: If True, diagonal scaling is enabled during
optimisation to allow the problem to be better conditioned.
- @type scaling: bool
- @param verbosity: A flag specifying 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
- @keyword lower: The lower bounds of the grid search which
must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
- @type lower: array of numbers
- @keyword upper: The upper bounds of the grid search which
must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
- @type upper: array of numbers
- @keyword inc: The increments for each dimension of the
space for the grid search. The number of elements in the array must equal to
the number of parameters in the model. This argument is only used when doing
a grid search.
- @type inc: array of int
+ @param min_algor: The minimisation algorithm to use.
+ @type min_algor: str
+ @param min_options: An array of options to be used by the
minimisation algorithm.
+ @type min_options: array of str
+ @param func_tol: The function tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
+ @type func_tol: None or float
+ @param grad_tol: The gradient tolerance which, when
reached, terminates optimisation. Setting this to None turns of the check.
+ @type grad_tol: None or float
+ @param max_iterations: The maximum number of iterations for the
algorithm.
+ @type max_iterations: int
+ @param constraints: If True, constraints are used during
optimisation.
+ @type constraints: bool
+ @keyword scaling_matrix: The per-model list of diagonal and
square scaling matrices.
+ @type scaling_matrix: list of numpy rank-2, float64 array or
list of None
+ @param verbosity: A flag specifying 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
+ @keyword lower: The lower bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
+ @type lower: array of numbers
+ @keyword upper: The upper bounds of the grid search
which must be equal to the number of parameters in the model. This optional
argument is only used when doing a grid search.
+ @type upper: array of numbers
+ @keyword inc: The increments for each dimension of the
space for the grid search. The number of elements in the array must equal to
the number of parameters in the model. This argument is only used when doing
a grid search.
+ @type inc: array of int
"""
# Set up the target function for direct calculation.
Modified: branches/zooming_grid_search/specific_analyses/relax_disp/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/zooming_grid_search/specific_analyses/relax_disp/api.py?rev=24579&r1=24578&r2=24579&view=diff
==============================================================================
--- branches/zooming_grid_search/specific_analyses/relax_disp/api.py
(original)
+++ branches/zooming_grid_search/specific_analyses/relax_disp/api.py Mon
Jul 21 09:17:44 2014
@@ -548,7 +548,7 @@
return [lower_new[i], upper_new[i]]
- def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling=True,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
+ def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
"""Relaxation dispersion curve fitting function.
@keyword min_algor: The minimisation algorithm to use.
@@ -563,8 +563,8 @@
@type max_iterations: int
@keyword constraints: If True, constraints are used during
optimisation.
@type constraints: bool
- @keyword scaling: If True, diagonal scaling is enabled
during optimisation to allow the problem to be better conditioned.
- @type scaling: bool
+ @keyword scaling_matrix: The per-model list of diagonal and
square scaling matrices.
+ @type scaling_matrix: list of numpy rank-2, float64 array or
list of None
@keyword verbosity: The amount of information to print. The
higher the value, the greater the verbosity.
@type verbosity: int
@keyword sim_index: The index of the simulation to optimise.
This should be None if normal optimisation is desired.
r24579 - in /branches/zooming_grid_search/specific_analyses: frame_order/ model_free/ n_state_model/ relax_disp/