def tst_prob1(multicore):
def prob1(x):
return (
5.0 * x[0] * x[0]
+ 2.0 * x[1] * x[1]
+ 2.0 * x[2] * x[2]
+ 2.0 * x[0] * x[1]
+ 2.0 * x[1] * x[2]
- 2.0 * x[0] * x[2]
- 6.0 * x[2]
)
x0 = (0.0, 0.0, 0.0)
xmin = (-10.0, -10, -10)
xmax = (10.0, 10, 10)
maxfev = 4096
verbose = False
ftol = numpy.float_(numpy.finfo(numpy.float32).eps)
step = None
initsimplex = 0
finalsimplex = 0
starttime = time.time()
print neldermead(
prob1, x0, xmin, xmax, ftol, maxfev, initsimplex, finalsimplex, step=None, verbose=False, multicore=multicore
)
print "%f secs" % (time.time() - starttime)
solution = (1.0, -2.0, 3.0)
print prob1(solution)
def tst_prob2(multicore):
def prob2(x):
return 2.0 * x[0] * x[0] + x[1] * x[1] - x[0] * x[1]
x0 = (2.0, 2.0)
xmin = (-10., -10)
xmax = (10., 10)
maxfev = 4096
verbose = False
ftol = numpy.float_(numpy.finfo(numpy.float32).eps)
step = None
initsimplex = 0
finalsimplex = 0
starttime = time.time()
print neldermead(prob2,
x0,
xmin,
xmax,
ftol,
maxfev,
initsimplex,
finalsimplex,
step=None,
verbose=False,
multicore=multicore)
print '%f secs' % (time.time() - starttime)
solution = (0.0, 0.0)
print prob2(solution)
def tst_rosen(npar, multicore):
x0 = npar * [-1.2, 1.0]
xmin = npar * [-10, -10.0]
xmax = npar * [10, 10]
maxfev = npar * 4096 * 16
verbose = False
ftol = numpy.float_(numpy.finfo(numpy.float32).eps)
step = None
initsimplex = 0
finalsimplex = 0
starttime = time.time()
print neldermead(
rosen, x0, xmin, xmax, ftol, maxfev, initsimplex, finalsimplex, step=step, verbose=verbose, multicore=multicore
)
print "%f secs" % (time.time() - starttime)
def tst_prob2( multicore ):
def prob2( x ):
return 2.0 * x[ 0 ] * x[ 0 ] + x[ 1 ] * x[ 1 ] - x[ 0 ] * x[ 1 ]
x0 = ( 2.0, 2.0 )
xmin = ( -10., -10 )
xmax = ( 10., 10 )
maxfev = 4096
verbose = False
ftol = numpy.float_(numpy.finfo(numpy.float32).eps)
step = None
initsimplex = 0
finalsimplex = 0
starttime = time.time( )
print neldermead( prob2, x0, xmin, xmax, ftol, maxfev, initsimplex,
finalsimplex, step=None, verbose=False,
multicore=multicore )
print '%f secs' % ( time.time() - starttime )
solution = ( 0.0, 0.0 )
print prob2( solution )
def tst_rosen(npar, multicore):
x0 = npar * [-1.2, 1.0]
xmin = npar * [-10, -10.]
xmax = npar * [10, 10]
maxfev = npar * 4096 * 16
verbose = False
ftol = numpy.float_(numpy.finfo(numpy.float32).eps)
step = None
initsimplex = 0
finalsimplex = 0
starttime = time.time()
print neldermead(rosen,
x0,
xmin,
xmax,
ftol,
maxfev,
initsimplex,
finalsimplex,
step=step,
verbose=verbose,
multicore=multicore)
print '%f secs' % (time.time() - starttime)
model = ngauss(x, pars[0], pars[1], pars[2])
delta = model - y
statval = (delta * delta).sum()
# Keep a record of the parameters we've visited
store.add_row([statval] + list(pars))
return statval, delta
start = [y.max(), (x[0] + x[-1]) / 2, (x[-1] - x[0]) / 10]
lows = [0, x[0], 0]
his = [1e4, x[-1], x[-1] - x[0]]
store = Table(names=['stat', 'ampl', 'pos', 'fwhm'])
flag, bestfit, statval, msg, opts = optfcts.neldermead(cb,
start,
lows,
his,
ftol=1e-4)
print(flag)
print(bestfit)
print(statval)
print(opts)
print(len(store))
plt.clf()
plt.plot(x, y, label='Data', alpha=0.5)
plt.plot(x, ngauss(x, *start), label='Start')
plt.plot(x, ngauss(x, *bestfit), label='Best fit', c='k')
plt.legend()
savefig('normgauss1d-example.png')
