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/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/
H A Dbase.py74 parametrization: p.Parameter,
80 self.parametrization = parametrization
105 @parametrization.setter
106 def parametrization(self, parametrization: p.Parameter) -> None: member in ExperimentFunction
127 desc.update(parametrization=self.parametrization.name, dimension=self.dimension)
149 and self.parametrization.name == other.parametrization.name
176 if output.parametrization.name != self.parametrization.name:
177 output.parametrization = _reset_copy(self.parametrization)
188 output.parametrization._constraint_checkers = self.parametrization._constraint_checkers
315 assert (parametrization.bounds[0] is None) == (parametrization.bounds[1] is None)
[all …]
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/optimization/
H A Doptimizerlib.py18 from nevergrad.parametrization import transforms
20 from nevergrad.parametrization import _layering
68 parametrization: IntOrParameter,
167 ref = self.parametrization
375 parametrization: IntOrParameter,
577 self.parametrization
654 parametrization: IntOrParameter,
671 self.parametrization
779 parametrization: IntOrParameter,
1002 parametrization: IntOrParameter,
[all …]
H A Dtest_doc.py23 optimizer = ng.optimizers.OnePlusOne(parametrization=2, budget=100)
40 optimizer = ng.optimizers.OnePlusOne(parametrization=2, budget=100)
49 optimizer = ng.optimizers.OnePlusOne(parametrization=instrum, budget=100)
122 optimizer = ng.optimizers.OnePlusOne(parametrization=instru, budget=100)
143 optimizer = ng.optimizers.OnePlusOne(parametrization=2, budget=100)
145 optimizer.parametrization.register_cheap_constraint(lambda x: x[0] >= 1)
164 optimizer = ng.optimizers.OnePlusOne(parametrization=2, budget=4)
172 optim = ng.optimizers.OnePlusOne(parametrization=2, budget=100)
176 candidate = optim.parametrization.spawn_child(new_value=[12, 12])
181 optim = ng.optimizers.OnePlusOne(parametrization=param, budget=100)
[all …]
H A Dtest_optimizerlib.py149 optim = optim_cls(parametrization=2, budget=70)
268 optim.parametrization.random_state.seed(12)
366 optim.parametrization.random_state.seed(12)
409 xpvariants.QRBO(parametrization, budget=10)
424 optimizer = my_opt(parametrization=arg, budget=10)
443 parametrization.random_state.seed(12)
449 recom = optimizer.parametrization.spawn_child()
540 optimizer.parametrization.random_state.seed(12)
698 parametrization = ng.p.Instrumentation(
709 optimizer = ng.optimizers.NGOpt(parametrization=parametrization, budget=budget)
[all …]
H A Dtest_externalbo.py57 def test_hyperopt(parametrization, has_transform) -> None: argument
58 optim1 = registry["HyperOpt"](parametrization=parametrization, budget=5)
59 optim2 = registry["HyperOpt"](parametrization=parametrization.copy(), budget=5)
74 opt = registry["HyperOpt"](parametrization=parametrization, budget=30, num_workers=5)
128 def test_hyperopt_helpers(parametrization, values): argument
130 parametrization.value = val
131 … assert flatten(_hp_parametrization_to_dict(parametrization)) == pytest.approx(flatten(dict_val))
133 flatten(parametrization.value)
H A Dtest_base.py31 super().__init__(parametrization=1, budget=5, num_workers=num_workers)
93 zeroptim = xpvariants.Zero(parametrization=2, budget=4, num_workers=1)
95 zeroptim.parametrization.descriptors.deterministic_function = False
96 assert not zeroptim.parametrization.function.deterministic
101 zeroptim.tell(zeroptim.parametrization.spawn_child().set_standardized_data([0.0, 0]), 0)
102 zeroptim.tell(zeroptim.parametrization.spawn_child().set_standardized_data([1.0, 1]), 1)
116 optimizer = optimizerlib.OnePlusOne(parametrization=1, budget=100, num_workers=5)
134 optimizer = optimizerlib.CMA(parametrization=3, budget=1000, num_workers=5)
149 opt = optf(parametrization=2, budget=4, num_workers=1)
156 opt = base.registry["BlubluOptimizer"](parametrization=2, budget=4, num_workers=1)
[all …]
H A Dbase.py13 from nevergrad.parametrization import parameter as p
100 self.parametrization = (
101 parametrization
103 else p.Array(shape=(parametrization,))
114 x: utils.MultiValue(self.parametrization, np.inf, reference=self.parametrization)
142 return self.parametrization.random_state
147 return self.parametrization.dimension
237 inststr = self.parametrization.name
508 out = self.parametrization.spawn_child()
647 ref = self.parametrization
[all …]
H A Dtest_recaster.py60 return self.__class__(self.parametrization, self.budget, self.num_workers)._optim_function
63 suboptim = optimizerlib.OnePlusOne(parametrization=2, budget=self.budget)
65 return recom.get_standardized_data(reference=self.parametrization)
69 optimizer = FakeOptimizer(parametrization=2, budget=100)
76 optimizer = FakeOptimizer(parametrization=2, budget=100)
81 optimizer = FakeOptimizer(parametrization=2, budget=100)
87 opt = optimizerlib.SQP(parametrization=2, budget=100)
H A Dexternalbo.py10 from nevergrad.parametrization import transforms
11 from nevergrad.parametrization import parameter as p
103 parametrization: IntOrParameter,
113 super().__init__(parametrization, budget=budget, num_workers=num_workers)
116 if not isinstance(self.parametrization, p.Instrumentation):
118 self.space = _get_search_space(self.parametrization.name, self.parametrization)
143 candidate = self.parametrization.spawn_child()
153 … != self._transform.forward(candidate.get_standardized_data(reference=self.parametrization))
156 … self._transform.forward(candidate.get_standardized_data(reference=self.parametrization))
189 data = candidate.get_standardized_data(reference=self.parametrization)
H A Ddifferentialevolution.py9 from nevergrad.parametrization import parameter as p
75 parametrization: base.IntOrParameter,
80 super().__init__(parametrization, budget=budget, num_workers=num_workers)
112 [g.get_standardized_data(reference=self.parametrization) for g in good_guys]
114 out = self.parametrization.spawn_child()
127 self.parametrization,
131 candidate = self.parametrization.sample()
136 candidate = self.parametrization.spawn_child().set_standardized_data(new_guy)
146 data = candidate.get_standardized_data(reference=self.parametrization)
168 candidate.recombine(self.parametrization.spawn_child().set_standardized_data(donor))
[all …]
H A Drecastlib.py9 from nevergrad.parametrization import parameter as p
18 parametrization: IntOrParameter,
25 super().__init__(parametrization, budget=budget, num_workers=num_workers)
43 parametrization=self.parametrization,
/dports/graphics/p5-Cairo/Cairo-1.109/examples/
H A Dtwisted-text.pl22 my @parametrization = ();
26 $parametrization[$_] = 0.0;
33 $parametrization[$_] = two_points_distance ($current_point, $data->{points}[0]);
45 return \@parametrization;
170 my $parametrization = $param->{parametrization};
178 for ($i = 0; $i < $length && $d > $parametrization->[$i]; $i++) {
179 $d -= $parametrization->[$i];
195 my $ratio = $d / $parametrization->[$i];
203 $ratio = $d / $parametrization->[$i];
210 $ratio = $d / $parametrization->[$i];
[all …]
/dports/graphics/blender/blender-2.91.0/source/blender/nodes/shader/nodes/
H A Dnode_shader_bsdf_hair_principled.c65 int parametrization = node->custom1; in node_shader_update_hair_principled() local
69 if (parametrization == SHD_PRINCIPLED_HAIR_REFLECTANCE) { in node_shader_update_hair_principled()
77 if (parametrization == SHD_PRINCIPLED_HAIR_PIGMENT_CONCENTRATION) { in node_shader_update_hair_principled()
85 if (parametrization == SHD_PRINCIPLED_HAIR_PIGMENT_CONCENTRATION) { in node_shader_update_hair_principled()
93 if (parametrization == SHD_PRINCIPLED_HAIR_PIGMENT_CONCENTRATION) { in node_shader_update_hair_principled()
101 if (parametrization == SHD_PRINCIPLED_HAIR_DIRECT_ABSORPTION) { in node_shader_update_hair_principled()
109 if (parametrization == SHD_PRINCIPLED_HAIR_PIGMENT_CONCENTRATION) { in node_shader_update_hair_principled()
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/pyomo/
H A Dtest_core.py19 optimizer = ng.optimizers.NGO(parametrization=func.parametrization, budget=100)
38 optimizer = ng.optimizers.OnePlusOne(parametrization=func.parametrization, budget=100)
59 optimizer = ng.optimizers.OnePlusOne(parametrization=func.parametrization, budget=200)
81 func.parametrization.random_state.seed(12)
82 optimizer = ng.optimizers.OnePlusOne(parametrization=func.parametrization, budget=100)
/dports/graphics/openfx-arena/openfx-arena-Natron-2.3.14/Extra/
H A Dfx.h235 parametrization_t* parametrization = 0; in parametrize_path() local
244 parametrization = (parametrization_t*)malloc(path->num_data * sizeof(parametrization[0])); in parametrize_path()
248 parametrization[i] = 0.0; in parametrize_path()
268 parametrization[i] = curve_length( in parametrize_path()
281 return parametrization; in parametrize_path()
314 parametrization_t* parametrization; member
346 parametrization_t* parametrization = param->parametrization; in point_on_path() local
360 the_x -= parametrization[i]; in point_on_path()
396 ratio = the_x / parametrization[i]; in point_on_path()
406 ratio = the_y / parametrization[i]; in point_on_path()
[all …]
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/photonics/
H A Dtest_core.py26 output = func.parametrization.spawn_child().set_standardized_data(x).value.ravel()
40 all_x = func.parametrization.value
48 output1 = func.parametrization.spawn_child().set_standardized_data(x)
60 func.parametrization.random_state.seed(24)
61 arrays = [func.parametrization.spawn_child() for _ in range(2)]
71 param = func.parametrization.spawn_child()
76 func.evaluation_function(func.parametrization)
183 candidate = photo.parametrization.spawn_child().set_standardized_data(x)
185 candidate = photo.parametrization.spawn_child(new_value=data)
/dports/textproc/texi2html/texi2html-5.0/test/singular_manual/d2t_singular/
H A Dparamet_lib.tex28 a parametrization of a plane curve singularity with the aid of a
65 the parametrization ring, that is to the ring PR=0,(s,t),dp;
71 the number of variables needed for the parametrization resp. 0, and
72 1 resp. 0 depending on whether the parametrization was successful
75 @cindex parametrization
129 the parametrization ring, that is to the ring PR=0,(s,t),dp;
134 a list of lists, where each entry contains the parametrization
136 resp. 0, and 1 resp. 0 depending on whether the parametrization
139 @cindex parametrization
210 the parametrization ring, that is to the ring 0,(x,y),ls;
[all …]
/dports/x11-toolkits/pango/pango-1.48.11/examples/
H A Dcairotwisted.c222 parametrization_t *parametrization; in parametrize_path() local
224 parametrization = g_malloc (path->num_data * sizeof (parametrization[0])); in parametrize_path()
228 parametrization[i] = 0.0; in parametrize_path()
260 return parametrization; in parametrize_path()
330 parametrization_t *parametrization = param->parametrization; in point_on_path() local
333 (the_x > parametrization[i] || in point_on_path()
336 the_x -= parametrization[i]; in point_on_path()
367 ratio = the_x / parametrization[i]; in point_on_path()
377 ratio = the_y / parametrization[i]; in point_on_path()
396 ratio = the_x / parametrization[i]; in point_on_path()
[all …]
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/iohprofiler/
H A Dtest_core.py22 x = func.parametrization.sample()
28 optim = OnePlusOne(func.parametrization, budget=100)
42 x = func.parametrization.sample()
53 x = func.parametrization.sample()
57 x = func.parametrization.sample()
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/benchmark/
H A Dxpbase.py14 from nevergrad.parametrization import parameter as p
85 def instantiate(self, parametrization: p.Parameter) -> obase.Optimizer:
88 parametrization=parametrization, budget=self.budget, num_workers=self.num_workers
169 self.function.parametrization.random_state # pylint: disable=pointless-statement
241 assert len(pfunc.parametrization._constraint_checkers) == len(
242 self.function.parametrization._constraint_checkers
246 self._optimizer = self.optimsettings.instantiate(parametrization=pfunc.parametrization)
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/parametrization/
H A D__init__.py6 from nevergrad.parametrization.instantiate import FolderFunction as FolderFunction
7 from nevergrad.parametrization.utils import TemporaryDirectoryCopy as TemporaryDirectoryCopy
8 from nevergrad.parametrization.utils import CommandFunction as CommandFunction
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/control/
H A Dcore.py12 from nevergrad.parametrization import parameter as p
76 parametrization: p.Tuple = p.Tuple(*list_parametrizations).set_name(self.env_name)
77 super().__init__(self._simulate, parametrization)
96 self.parametrization.function.deterministic = False
109 random_state=self.parametrization.random_state,
114 … self.random_state if self.deterministic_sim else self.parametrization.random_state.randint(10000)
/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/functions/arcoating/
H A Dtest_core.py31 func.parametrization.random_state.seed(24)
34 arrays.append(func.parametrization.spawn_child()) # type: ignore
45 data = func.parametrization.spawn_child().set_standardized_data(x).args[0]
48 param = func.parametrization.spawn_child().set_standardized_data(np.arange(8))
/dports/math/openturns/openturns-1.18/python/src/
H A DArcsine_doc.i.in35 … parametrization :math:`(\mu, \sigma)`: see :class:`~openturns.ArcsineMuSigma`. In that case, all…
37 …parametrization :math:`(\mu, \sigma)` only to create the distribution, see the example below: all …
46 Create a it from the alternative parametrization :math:`(\mu, \sigma)`:
51 Create it from :math:`(\mu, \sigma)` and keep that parametrization for the remaining study:
H A DGumbel_doc.i.in38 …nturns.GumbelLambdaGamma`. In that case, all the results are presented in that new parametrization.
40 …rnative parametrization only to create the distribution, see the example below: all the results w…
49 Create it from the alternative parametrization :math:`(\mu, \sigma)`:
54 Create it from the alternative parametrization :math:`(\lambda, \gamma)`:
59 Create it from :math:`(\mu, \sigma)` and keep that parametrization for the remaining study:
64 Create it from :math:`(\lambda, \gamma)` and keep that parametrization for the remaining study:

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