def get_delta_root( arg, dir, par_at_min ):
my_neg_pos = ConfBracket.neg_pos[ dir ]
if is_iterable( arg ):
return arg
#return map( lambda x: my_neg_pos * abs( x - par_at_min ), arg )
elif None != arg:
arg -= par_at_min
return my_neg_pos * abs( arg )
else:
return arg
def get_delta_root(arg, dir, par_at_min):
my_neg_pos = ConfBracket.neg_pos[dir]
if is_iterable(arg):
return arg
# return map( lambda x: my_neg_pos * abs( x - par_at_min ), arg )
elif None != arg:
arg -= par_at_min
return my_neg_pos * abs(arg)
else:
return arg
def myformat( hfmt, str, lowstr, lownum, highstr, highnum ):
str += hfmt % ('Param', 'Best-Fit', 'Lower Bound', 'Upper Bound')
str += hfmt % ('-'*5, '-'*8, '-'*11, '-'*11)
for name, val, lower, upper in izip(self.parnames, self.parvals,
self.parmins, self.parmaxes):
str += '\n %-12s %12g ' % (name, val)
if is_iterable( lower ):
str += ' '
str += list_to_open_interval( lower )
elif (lower is None):
str += lowstr % '-----'
else:
str += lownum % lower
if is_iterable( upper ):
str += ' '
str += list_to_open_interval( upper )
elif (upper is None):
str += highstr % '-----'
else:
str += highnum % upper
return str
def print_status( myblog, verbose, prefix, answer, lock ):
if lock is not None:
lock.acquire()
if 0 == verbose:
msg = '%s\t' % prefix.lstrip()
else:
msg = '%s\t' % prefix
if is_iterable( answer ):
msg += list_to_open_interval( answer )
elif answer is None:
msg += '-----'
else:
msg += '%g' % answer
myblog( msg )
if lock is not None:
lock.release()
def print_status(myblog, verbose, prefix, answer, lock):
if lock is not None:
lock.acquire()
if 0 == verbose:
msg = '%s\t' % prefix.lstrip()
else:
msg = '%s\t' % prefix
if is_iterable(answer):
msg += list_to_open_interval(answer)
elif answer is None:
msg += '-----'
else:
msg += '%g' % answer
myblog(msg)
if lock is not None:
lock.release()
def optneldermead(
afcn,
x0,
xmin,
xmax,
ftol=EPSILON,
maxfev=None,
initsimplex=0,
finalsimplex=None,
step=None,
multicore=False,
verbose=None,
):
x, xmin, xmax = _check_args(x0, xmin, xmax)
nfev, fcn = func_counter(afcn)
if step is None or (numpy.iterable(step) and len(step) != len(x)):
step = 1.2 * numpy.ones(x.shape, numpy.float_, numpy.isfortran(x))
elif numpy.isscalar(step):
step = step * numpy.ones(x.shape, numpy.float_, numpy.isfortran(x))
if maxfev is None:
maxfev = 1024 * len(x)
if finalsimplex is None:
finalsimplex = [0, 2]
if False == is_iterable(finalsimplex):
finalsimplex = [finalsimplex]
# For internal use only:
debug = True
def myloop(xxx, mymaxfev, mystep):
nms = classicNelderMead(fcn)
mynfev = 0
for myfinalsimplex in finalsimplex:
starttime = time.time()
result = nms(
xxx, xmin, xmax, mymaxfev - mynfev, ftol, mystep, initsimplex, myfinalsimplex, multicore, verbose
)
mynfev += result[3]
if 0 != result[0]:
return result[0], result[1], result[2], mynfev
if debug:
print "neldermead::myloop: result = ", result, " took ", time.time() - starttime, " secs"
if multicore:
return result[0], result[1], result[2], mynfev + nfev[0]
else:
return result[0], result[1], result[2], mynfev
def myneldermead(xxx, mymaxfev, mystep, fold=numpy.float_(numpy.finfo(numpy.float_).max)):
result = myloop(xxx, mymaxfev, mystep)
mynfev = result[3]
fnew = result[2]
if (
fnew < fold * 0.995
and 0 == Knuth_close(fnew, fold, ftol)
and 0 == Knuth_close(fnew, fold, ftol)
and 0 == result[0]
and mynfev < mymaxfev
):
if debug:
print "neldermead: fnew = ", fnew, "\tfold = ", fold, "\tx = ", result[1]
result = myneldermead(result[1], mymaxfev - mynfev, step, fold=fnew)
mynfev += result[3]
return result[0], result[1], result[2], mynfev
# result = myneldermead( x, maxfev, step )
result = myloop(x, maxfev, step)
return get_result(result, maxfev)
def optneldermead(afcn,
x0,
xmin,
xmax,
ftol=EPSILON,
maxfev=None,
initsimplex=0,
finalsimplex=None,
step=None,
multicore=False,
verbose=None):
x, xmin, xmax = _check_args(x0, xmin, xmax)
nfev, fcn = func_counter(afcn)
if step is None or (numpy.iterable(step) and len(step) != len(x)):
step = 1.2 * numpy.ones(x.shape, numpy.float_, numpy.isfortran(x))
elif numpy.isscalar(step):
step = step * numpy.ones(x.shape, numpy.float_, numpy.isfortran(x))
if maxfev is None:
maxfev = 1024 * len(x)
if finalsimplex is None:
finalsimplex = [0, 2]
if False == is_iterable(finalsimplex):
finalsimplex = [finalsimplex]
# For internal use only:
debug = True
def myloop(xxx, mymaxfev, mystep):
nms = classicNelderMead(fcn)
mynfev = 0
for myfinalsimplex in finalsimplex:
starttime = time.time()
result = nms(xxx, xmin, xmax, mymaxfev - mynfev, ftol, mystep,
initsimplex, myfinalsimplex, multicore, verbose)
mynfev += result[3]
if 0 != result[0]:
return result[0], result[1], result[2], mynfev
if debug:
print 'neldermead::myloop: result = ', result, ' took ', time.time(
) - starttime, ' secs'
if multicore:
return result[0], result[1], result[2], mynfev + nfev[0]
else:
return result[0], result[1], result[2], mynfev
def myneldermead(xxx,
mymaxfev,
mystep,
fold=numpy.float_(numpy.finfo(numpy.float_).max)):
result = myloop(xxx, mymaxfev, mystep)
mynfev = result[3]
fnew = result[2]
if fnew < fold * 0.995 and 0 == Knuth_close( fnew, fold, ftol ) and \
0 == Knuth_close( fnew, fold, ftol ) and \
0 == result[0] and mynfev < mymaxfev:
if debug:
print 'neldermead: fnew = ', fnew, '\tfold = ', fold, \
'\tx = ', result[ 1 ]
result = myneldermead(result[1],
mymaxfev - mynfev,
step,
fold=fnew)
mynfev += result[3]
return result[0], result[1], result[2], mynfev
#result = myneldermead( x, maxfev, step )
result = myloop(x, maxfev, step)
return get_result(result, maxfev)
