def myfdjac( myx, myfvec, myfjac, myxmax, myiflag, myepsfcn ):
eps = numpy.sqrt( max( [ EPSILON, myepsfcn ] ) )
n = len( myx )
def fdjac( xxx, origxxx, fvec, upbound, iflag, epsilon ):
myn = len( xxx )
diffs = []
for jj in xrange( myn ):
temp = xxx[ jj ]
h = epsilon * abs( xxx[ jj ] )
if 0.0 == h:
h = eps
if xxx[ jj ] + h > upbound[ jj ]:
h = - h
xxx[ jj ] = temp + h
wa, iflag = fcn( origxxx, iflag )
xxx[ jj ] = temp
diff = ( wa - fvec ) / h
diff = numpy.append( diff, iflag )
diffs.append( diff )
return diffs
diffs = divide_run_parallel( fdjac, myx, myx, myfvec, myxmax, myiflag, eps )
for jj in range( n ):
myfjac[ 0:, jj ] = diffs[ jj ][:-1].copy()
if diffs[ jj ][ -1 ] < 0:
myiflag = diffs[ jj ][ -1 ]
return myiflag, myfjac
def __call__(self, x, xmin, xmax, maxfev, tol, step, initsimplex, finalsimplex, multicore, verbose):
try:
def optimize(bad_index, fcn, npar, aflatarray):
rho_chi = self.reflection_coef * self.expansion_coef
rho_gamma = self.reflection_coef * self.contraction_coef
result = []
for badindex in bad_index:
begin_nfev = self.nfev[0]
simplex = classicSimplex(fcn, npar, aflatarray, xmin, xmax)
shrinkme = False
centroid = simplex.calc_centroid(badindex)
reflection_pt = simplex.move_vertex(centroid, self.reflection_coef, badindex)
if simplex[0, -1] <= reflection_pt[-1] and reflection_pt[-1] < simplex[badindex - 1, -1]:
# simplex[ badindex ] = reflection_pt[ : ]
simplex.replace_vertex(badindex, reflection_pt)
if verbose:
print "\taccept reflection point"
elif reflection_pt[-1] < simplex[0, -1]:
# calculate the expansion point
expansion_pt = simplex.move_vertex(centroid, rho_chi, badindex)
if expansion_pt[-1] < reflection_pt[-1]:
# simplex[ badindex ] = expansion_pt[ : ]
simplex.replace_vertex(badindex, expansion_pt)
if verbose:
print "\taccept expansion point"
else:
# simplex[ badindex ] = reflection_pt[ : ]
simplex.replace_vertex(badindex, reflection_pt)
if verbose:
print "\taccept reflection point"
else:
shrinkme = simplex.contract_in_out(
centroid, reflection_pt, rho_gamma, self.contraction_coef, badindex, verbose
)
if shrinkme is False:
shrinkme = 0
else:
skrinkme = 1
result.append(
numpy.append(simplex.polytope.ravel(), [self.nfev[0] - begin_nfev, shrinkme, badindex])
)
return numpy.asarray(result)
x, xmin, xmax = self.check_args(x, xmin, xmax)
polytope = Polytope(self.fcn, x, xmin, xmax, step, initsimplex)
npar = len(x)
bad_vertices = [npar]
mynfev = 0
while self.nfev[0] < maxfev:
polytope.order_simplex()
if verbose:
print "f%s=%f" % (polytope[0, :-1], polytope[0, -1])
if polytope.check_convergence(tol, finalsimplex):
break
if multicore:
badindex = multiprocessing.cpu_count()
if badindex == npar:
badindex = 1
bad_vertices = range(npar, npar - badindex, -1)
results = divide_run_parallel(optimize, bad_vertices, polytope.fcn, npar, polytope.polytope.ravel())
else:
results = optimize(bad_vertices, polytope.fcn, npar, polytope.polytope.ravel())
datasize = npar * (npar + 2) + 4
nrow = results.size / datasize
ncol = results.size / nrow
results = results.reshape(nrow, ncol)
num_not_modified = 0
for result in results:
mynfev += int(result[-3])
shrinkme = int(result[-2])
index = int(result[-1])
aflatarray = result[:-3]
if shrinkme:
num_not_modified += 1
else:
aflatarray.shape = (npar + 1, npar + 1)
# print index, polytope[ index, -1 ], aflatarray[ index, -1 ]
polytope[index] = numpy.array(aflatarray[index], copy=True)
if num_not_modified == len(bad_vertices):
polytope.shrink(self.shrink_coef, npar)
if verbose:
print "\tshrink"
ierr = 0
if mynfev >= maxfev:
ierr = 3
vertex = polytope[0]
bestpar = vertex[:-1]
bestval = vertex[-1]
return ierr, bestpar, bestval, mynfev
except InputErr:
vertex = polytope.get_vertex(0)
bestpar = vertex[:-1]
bestval = vertex[-1]
return 1, bestpar, bestval, mynfev
except OutOfBoundErr:
return 2, x, numpy.nan, mynfev
def __call__(self, x, xmin, xmax, maxfev, tol, step, initsimplex,
finalsimplex, multicore, verbose):
try:
def optimize(bad_index, fcn, npar, aflatarray):
rho_chi = self.reflection_coef * self.expansion_coef
rho_gamma = self.reflection_coef * self.contraction_coef
result = []
for badindex in bad_index:
begin_nfev = self.nfev[0]
simplex = classicSimplex(fcn, npar, aflatarray, xmin, xmax)
shrinkme = False
centroid = simplex.calc_centroid(badindex)
reflection_pt = simplex.move_vertex(
centroid, self.reflection_coef, badindex)
if simplex[ 0, -1 ] <= reflection_pt[ -1 ] and \
reflection_pt[ -1 ] < simplex[ badindex - 1, -1 ]:
#simplex[ badindex ] = reflection_pt[ : ]
simplex.replace_vertex(badindex, reflection_pt)
if verbose:
print '\taccept reflection point'
elif reflection_pt[-1] < simplex[0, -1]:
# calculate the expansion point
expansion_pt = simplex.move_vertex(
centroid, rho_chi, badindex)
if expansion_pt[-1] < reflection_pt[-1]:
#simplex[ badindex ] = expansion_pt[ : ]
simplex.replace_vertex(badindex, expansion_pt)
if verbose:
print '\taccept expansion point'
else:
#simplex[ badindex ] = reflection_pt[ : ]
simplex.replace_vertex(badindex, reflection_pt)
if verbose:
print '\taccept reflection point'
else:
shrinkme = simplex.contract_in_out(
centroid, reflection_pt, rho_gamma,
self.contraction_coef, badindex, verbose)
if shrinkme is False:
shrinkme = 0
else:
skrinkme = 1
result.append(
numpy.append(
simplex.polytope.ravel(),
[self.nfev[0] - begin_nfev, shrinkme, badindex]))
return numpy.asarray(result)
x, xmin, xmax = self.check_args(x, xmin, xmax)
polytope = Polytope(self.fcn, x, xmin, xmax, step, initsimplex)
npar = len(x)
bad_vertices = [npar]
mynfev = 0
while (self.nfev[0] < maxfev):
polytope.order_simplex()
if verbose:
print 'f%s=%f' % (polytope[0, :-1], polytope[0, -1])
if polytope.check_convergence(tol, finalsimplex):
break
if multicore:
badindex = multiprocessing.cpu_count()
if badindex == npar:
badindex = 1
bad_vertices = range(npar, npar - badindex, -1)
results = divide_run_parallel(optimize, bad_vertices,
polytope.fcn, npar,
polytope.polytope.ravel())
else:
results = optimize(bad_vertices, polytope.fcn, npar,
polytope.polytope.ravel())
datasize = npar * (npar + 2) + 4
nrow = results.size / datasize
ncol = results.size / nrow
results = results.reshape(nrow, ncol)
num_not_modified = 0
for result in results:
mynfev += int(result[-3])
shrinkme = int(result[-2])
index = int(result[-1])
aflatarray = result[:-3]
if shrinkme:
num_not_modified += 1
else:
aflatarray.shape = (npar + 1, npar + 1)
#print index, polytope[ index, -1 ], aflatarray[ index, -1 ]
polytope[index] = numpy.array(aflatarray[index],
copy=True)
if num_not_modified == len(bad_vertices):
polytope.shrink(self.shrink_coef, npar)
if verbose:
print '\tshrink'
ierr = 0
if mynfev >= maxfev:
ierr = 3
vertex = polytope[0]
bestpar = vertex[:-1]
bestval = vertex[-1]
return ierr, bestpar, bestval, mynfev
except InputErr:
vertex = polytope.get_vertex(0)
bestpar = vertex[:-1]
bestval = vertex[-1]
return 1, bestpar, bestval, mynfev
except OutOfBoundErr:
return 2, x, numpy.nan, mynfev
