Author: bugman
Date: Mon Jan 11 11:10:14 2010
New Revision: 10166
URL: http://svn.gna.org/viewcvs/relax?rev=10166&view=rev
Log:
Copied the grid.py minimisation module from the original multi_processor
branch.
The command used was:
svn cp
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/multi_processor/minimise/grid.py
subdivide_grid.py
This module is now part of minfx, but the Grid_info class will be used by the
multi-processor code to
subdivide the diffusion tensor grid search. The code needs much work!
Added:
branches/multi_processor_merge/generic_fns/subdivide_grid.py
- copied, changed from r10165, branches/multi_processor/minimise/grid.py
Copied: branches/multi_processor_merge/generic_fns/subdivide_grid.py (from
r10165, branches/multi_processor/minimise/grid.py)
URL:
http://svn.gna.org/viewcvs/relax/branches/multi_processor_merge/generic_fns/subdivide_grid.py?p2=branches/multi_processor_merge/generic_fns/subdivide_grid.py&p1=branches/multi_processor/minimise/grid.py&r1=10165&r2=10166&rev=10166&view=diff
==============================================================================
--- branches/multi_processor/minimise/grid.py (original)
+++ branches/multi_processor_merge/generic_fns/subdivide_grid.py Mon Jan 11
11:10:14 2010
@@ -1,6 +1,7 @@
###############################################################################
#
#
-# Copyright (C) 2003, 2004 Edward d'Auvergne
#
+# Copyright (C) 2003, 2004, 2010 Edward d'Auvergne
#
+# Copyright (C) 2007 Gary S Thompson (https://gna.org/users/varioustoxins)
#
#
#
# This file is part of the program relax.
#
#
#
@@ -21,14 +22,11 @@
###############################################################################
#FIXME exceptiosn not progated properly in main loop
-import sys,math
+import math
from Numeric import Float
from textwrap import dedent
-from copy import copy
-
-from Numeric import Float64, ones, zeros
-
-from constraint_linear import Constraint_linear
+
+from Numeric import Float64, ones
#constants
@@ -261,181 +259,3 @@
def __iter__(self):
return Grid_info.Iterator(self,self.start,self.start+self.range)
-
-
-
-
-
-def grid(func=None, grid_ops=None, args=(), A=None, b=None, l=None, u=None,
c=None, print_flag=0, print_prefix=""):
- """Grid search function.
-
-
- Keyword Arguments
- ~~~~~~~~~~~~~~~~~
-
- func: The function to minimise.
-
- grid_ops: Matrix of options for the grid search.
-
- args: The tuple of arguments to supply to the function func.
-
-
- Grid options
- ~~~~~~~~~~~~
-
- The first dimension of grid_ops corresponds to the parameters of the
function func, and the
- second dimension corresponds to:
- 0 - The number of increments.
- 1 - Lower limit.
- 2 - Upper limit.
- """
-
- if not isinstance(grid_ops, Grid_info):
- info = Grid_info(grid_ops)
- # FIXME: issue warning?
- else:
- info=grid_ops
-
- #print 'info',info
- #info.print_steps()
-
- # Print out.
- if print_flag and pre_and_post_amble:
- if print_flag >= 2:
- print print_prefix
- print print_prefix
- print print_prefix + "Grid search"
- print print_prefix + "~~~~~~~~~~~"
-
- #FIXME: edge conditions l == None u == soemthing
- # Linear constraints.
- if A != None and b != None:
- constraint_flag = 1
- constraint_linear = Constraint_linear(A, b)
- c = constraint_linear.func
- if print_flag >= 3 and pre_and_post_amble:
- print print_prefix + "Linear constraint matrices."
- print print_prefix + "A: " + `A`
- print print_prefix + "b: " + `b`
-
- # Bound constraints.
- elif l != None and u != None:
- constraint_flag = 1
- # FIXME: doesn't raise exceptipn
- print "Bound constraints are not implemented yet."
- return
-
- # General constraints.
- elif c != None:
- constraint_flag = 1
-
- # No constraints.
- else:
- constraint_flag = 0
-
- # Set a ridiculously large initial grid value.
- f_min = 1e300
- # FIXME:should be float.PosMax but internal float classhes with relax
float, rename relax float to ieee_float
-
- # Initial print out.
- if print_flag and pre_and_post_amble:
- print "\n" + print_prefix + "Searching the grid."
-
- # Test if the grid is too large (ie total_steps is a long integer)
- if type(info.steps) == long:
- # FIXME: should be range error
- raise NameError, "A grid search of size " + `total_steps` + " is too
large."
-
- # Search the grid.
-
- iter = info.__iter__()
- k = iter.step
- k_start = k
- first_time = True
- for params in iter:
-
- # Check that the grid point does not violate a constraint, and if it
does, skip the function call.
- skip = False
- if constraint_flag:
- ci = c(params)
- if min(ci) < 0.0:
- if print_flag >= 3:
- print print_prefix + "%-3s%-8i%-4s%-65s" % ("k:", k,
"xk:", `params`)
- print print_prefix + "Constraint violated, skipping grid
point."
- print print_prefix + "ci: " + `ci`
- print ""
- skip = True
- #print 'skip',k,skip
- # Function call, test, and increment grid_size.
- if not skip:
- # Back calculate the current function value.
- f = func(*(params,)+args)
- # nasty hacks (1) to make al results different
- #f=f-k
- #print '*****params',k,f
- # Test if the current function value is less than the least
function value.
- if f < f_min:
- f_min = f
- #FIXME: replacw with a copy
- min_params = params * 1.0
- # nasty hacks (2) to make al results different
- #for i,elem in enumerate(min_params):
- # min_params[i]=elem+((k*(i+1))/1000.0)
-
- # Print out code.
- if print_flag:
- print print_prefix + "%-3s%-8i%-4s%-65s %-4s%-20s" %
("k:", k, "xk:", `min_params`, "fk:", `f_min`)
-
- # FIXME: not needed
- # Grid count.
- #grid_size = grid_size + 1
-
- # Print out code.
- if print_flag >= 2 and pre_and_post_amble:
- if f != f_min:
- print print_prefix + "%-3s%-8i%-4s%-65s %-4s%-20s" %
("k:", k, "xk:", `params`, "fk:", `f`)
- if print_flag >= 3:
- print print_prefix + "%-20s%-20s" % ("Increment:",
`step_num`)
- print print_prefix + "%-20s%-20s" % ("Params:", `params`)
- print print_prefix + "%-20s%-20s" % ("Min params:",
`min_params`)
- print print_prefix + "%-20s%-20g\n" % ("f:", f)
- print print_prefix + "%-20s%-20g\n" % ("Min f:", f_min)
-
- # Increment k.
- k = k + 1
-
-
- # Return the results.
- return min_params, f_min, k-k_start
-
-def test(grid_ops):
-
- n = len(grid_ops)
- grid_size = 0
- total_steps = 1
- step_num = ones((n))
- params = zeros((n), Float64)
- min_params = zeros((n), Float64)
- param_values = [] # This data structure eliminates the round-off error
of summing a step size value to the parameter value.
- for k in xrange(n):
- params[k] = grid_ops[k][GRID_LOWER]
- min_params[k] = grid_ops[k][GRID_LOWER]
- total_steps = total_steps * grid_ops[k][GRID_STEPS]
- param_values.append([])
- for i in xrange(grid_ops[k][GRID_STEPS]):
- param_values[k].append(grid_ops[k][GRID_LOWER] + i *
(grid_ops[k][GRID_UPPER] - grid_ops[k][GRID_LOWER]) /
(grid_ops[k][GRID_STEPS] - 1))
-
- print params
- print param_values
- print step_num
- for i in xrange(total_steps):
- print i,step_num
-
- for j in xrange(n):
- if step_num[j] < grid_ops[j][GRID_STEPS]:
- step_num[j] = step_num[j] + 1
- params[j] = param_values[j][step_num[j]-1]
- break # Exit so that the other step numbers are not
incremented.
- else:
- step_num[j] = 1
- params[j] = grid_ops[j][GRID_LOWER]
r10166 - /branches/multi_processor_merge/generic_fns/subdivide_grid.py