Python scipy.optimize.fmin_tnc() Examples
The following are 19
code examples of scipy.optimize.fmin_tnc().
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Example #1
| Source File: optimization.py From paramz with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def get_optimizer(f_min):
optimizers = {'fmin_tnc': opt_tnc,
'simplex': opt_simplex,
'lbfgsb': opt_lbfgsb,
'org-bfgs': opt_bfgs,
'scg': opt_SCG,
'adadelta':Opt_Adadelta,
'rprop':RProp,
'adam':Adam}
#if rasm_available:
# optimizers['rasmussen'] = opt_rasm
for opt_name in sorted(optimizers.keys()):
if opt_name.lower().find(f_min.lower()) != -1:
return optimizers[opt_name]
raise KeyError('No optimizer was found matching the name: %s' % f_min)
Example #2
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc45(self):
fg, x, bounds = self.fg45, [2] * 5, [(0, 1), (0, 2), (0, 3),
(0, 4), (0, 5)]
xopt = [1, 2, 3, 4, 5]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f45(x), self.f45(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #3
| Source File: optimization.py From paramz with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def opt(self, x_init, f_fp=None, f=None, fp=None):
"""
Run the TNC optimizer
"""
tnc_rcstrings = ['Local minimum', 'Converged', 'XConverged', 'Maximum number of f evaluations reached',
'Line search failed', 'Function is constant']
assert f_fp != None, "TNC requires f_fp"
opt_dict = {}
if self.xtol is not None:
opt_dict['xtol'] = self.xtol
if self.ftol is not None:
opt_dict['ftol'] = self.ftol
if self.gtol is not None:
opt_dict['pgtol'] = self.gtol
opt_result = optimize.fmin_tnc(f_fp, x_init, messages=self.messages,
maxfun=self.max_f_eval, **opt_dict)
self.x_opt = opt_result[0]
self.f_opt = f_fp(self.x_opt)[0]
self.funct_eval = opt_result[1]
self.status = tnc_rcstrings[opt_result[2]]
Example #4
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc38(self):
fg, x, bounds = self.fg38, np.array([-3, -1, -3, -1]), [(-10, 10)]*4
xopt = [1]*4
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f38(x), self.f38(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #5
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc5(self):
fg, x, bounds = self.fg5, [0, 0], [(-1.5, 4),(-3, 3)]
xopt = [-0.54719755119659763, -1.5471975511965976]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f5(x), self.f5(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #6
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc3(self):
fg, x, bounds = self.fg3, [10, 1], ([-np.inf, None], [0.0, None])
xopt = [0, 0]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f3(x), self.f3(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #7
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc2(self):
fg, x, bounds = self.fg1, [-2, 1], ([-np.inf, None], [1.5, None])
xopt = [-1.2210262419616387, 1.5]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #8
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc1c(self):
x, bounds = [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(self.f1, x, fprime=self.g1,
bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #9
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc1b(self):
x, bounds = [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(self.f1, x, approx_grad=True,
bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-4,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #10
| Source File: test_tnc.py From GraphicDesignPatternByPython with MIT License | 5 votes |
|
def test_tnc1(self):
fg, x, bounds = self.fg1, [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds, args=(100.0, ),
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #11
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc45(self):
fg, x, bounds = self.fg45, [2] * 5, [(0, 1), (0, 2), (0, 3),
(0, 4), (0, 5)]
xopt = [1, 2, 3, 4, 5]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f45(x), self.f45(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #12
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc38(self):
fg, x, bounds = self.fg38, np.array([-3, -1, -3, -1]), [(-10, 10)]*4
xopt = [1]*4
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f38(x), self.f38(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #13
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc5(self):
fg, x, bounds = self.fg5, [0, 0], [(-1.5, 4),(-3, 3)]
xopt = [-0.54719755119659763, -1.5471975511965976]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f5(x), self.f5(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #14
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc3(self):
fg, x, bounds = self.fg3, [10, 1], ([-np.inf, None], [0.0, None])
xopt = [0, 0]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f3(x), self.f3(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #15
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc2(self):
fg, x, bounds = self.fg1, [-2, 1], ([-np.inf, None], [1.5, None])
xopt = [-1.2210262419616387, 1.5]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #16
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc1c(self):
x, bounds = [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(self.f1, x, fprime=self.g1,
bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #17
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc1b(self):
x, bounds = [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(self.f1, x, approx_grad=True,
bounds=bounds,
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-4,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #18
| Source File: test_tnc.py From Computable with MIT License | 5 votes |
|
def test_tnc1(self):
fg, x, bounds = self.fg1, [-2, 1], ([-np.inf, None], [-1.5, None])
xopt = [1, 1]
x, nf, rc = optimize.fmin_tnc(fg, x, bounds=bounds, args=(100.0, ),
messages=optimize.tnc.MSG_NONE,
maxfun=200)
assert_allclose(self.f1(x), self.f1(xopt), atol=1e-8,
err_msg="TNC failed with status: " +
optimize.tnc.RCSTRINGS[rc])
Example #19
| Source File: param_search.py From catch with MIT License | 4 votes |
|
def _optimize_loss(probe_counts, loss_fn, bounds, x0,
initial_eps=10.0, step_size=0.001,
interp_fn_type='standard'):
"""Optimize loss function with barrier.
This uses scipy's optimize.fmin_tnc to minimize the loss function
in which the barrier is weighted by eps. It repeatedly minimizes
the loss while decreasing eps so that, by the last iteration, the
weight on the barrier is very small. On each iteration, it starts
the initial guess/position at the solution to the previous iteration.
Args:
probe_counts: dict giving number of probes required for each
dataset and choice of parameters
loss_fn: the loss function provided by _make_loss_fn
bounds: bounds on the parameter values provided by _make_param_bounds_*
x0: the initial guess of parameter values (i.e., starting position)
initial_eps: weight of the barrier on the first iteration
step_size: epsilon value provided to optimize.fmin_tnc
interp_fn_type: 'standard' (only perform interpolation on mismatches
and cover_extension parameters) or 'nd' (use scipy's interpolate
package to interpolate over n-dimensions)
Returns:
list of length (number of datasets)*(number of parameters) where
x_i is the (i % N)'th parameter of the (i/N)'th dataset,
for i=0,1,2,... where N=(number of datasets)
"""
eps = initial_eps
while eps >= 0.01:
x0_probe_count = ic._make_total_probe_count_across_datasets_fn(
probe_counts, interp_fn_type=interp_fn_type)(x0)
logger.info(("Starting an iteration with eps=%f, with x0 yielding %f "
"probes"), eps, x0_probe_count)
sol, nfeval, rc = optimize.fmin_tnc(loss_fn, x0, bounds=bounds,
args=(eps,),
approx_grad=True,
epsilon=step_size, disp=1, maxfun=2500)
if rc in [0, 1, 2]:
# rc == 0 indicates reaching the local minimum, and rc == 1 or
# rc == 2 indicates the function value converged
logger.info(" Iteration was successful")
else:
logger.info(" Iteration failed to converge!")
x0 = sol
eps = 0.1 * eps
return sol
