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/dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/testing/
H A Dlin_alg_utils.py40 random_state = value.parse_random_state(random_state)
42 state_vector = random_state.randn(dim).astype(complex)
43 state_vector += 1j * random_state.randn(dim)
64 random_state = value.parse_random_state(random_state)
66 mat = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
87 random_state = value.parse_random_state(random_state)
89 z = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
113 random_state = value.parse_random_state(random_state)
115 m = random_state.randn(dim, dim)
135 r = random_unitary(dim, random_state=random_state)
[all …]
/dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/testing/
H A Dlin_alg_utils.py40 random_state = value.parse_random_state(random_state)
42 state_vector = random_state.randn(dim).astype(complex)
43 state_vector += 1j * random_state.randn(dim)
64 random_state = value.parse_random_state(random_state)
66 mat = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
87 random_state = value.parse_random_state(random_state)
89 z = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
113 random_state = value.parse_random_state(random_state)
115 m = random_state.randn(dim, dim)
135 r = random_unitary(dim, random_state=random_state)
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/dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/testing/
H A Dlin_alg_utils.py40 random_state = value.parse_random_state(random_state)
42 state_vector = random_state.randn(dim).astype(complex)
43 state_vector += 1j * random_state.randn(dim)
64 random_state = value.parse_random_state(random_state)
66 mat = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
87 random_state = value.parse_random_state(random_state)
89 z = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
113 random_state = value.parse_random_state(random_state)
115 m = random_state.randn(dim, dim)
135 r = random_unitary(dim, random_state=random_state)
[all …]
/dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/testing/
H A Dlin_alg_utils.py40 random_state = value.parse_random_state(random_state)
42 state_vector = random_state.randn(dim).astype(complex)
43 state_vector += 1j * random_state.randn(dim)
64 random_state = value.parse_random_state(random_state)
66 mat = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
87 random_state = value.parse_random_state(random_state)
89 z = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
113 random_state = value.parse_random_state(random_state)
115 m = random_state.randn(dim, dim)
135 r = random_unitary(dim, random_state=random_state)
[all …]
/dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/testing/
H A Dlin_alg_utils.py40 random_state = value.parse_random_state(random_state)
42 state_vector = random_state.randn(dim).astype(complex)
43 state_vector += 1j * random_state.randn(dim)
64 random_state = value.parse_random_state(random_state)
66 mat = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
87 random_state = value.parse_random_state(random_state)
89 z = random_state.randn(dim, dim) + 1j * random_state.randn(dim, dim)
113 random_state = value.parse_random_state(random_state)
115 m = random_state.randn(dim, dim)
135 r = random_unitary(dim, random_state=random_state)
[all …]
/dports/science/py-nilearn/nilearn-0.8.1/nilearn/mass_univariate/tests/
H A Dtest_permuted_least_squares.py286 n_perm=0, random_state=random_state)
292 n_perm=0, random_state=random_state)
299 n_perm=0, random_state=random_state)
366 n_perm=0, random_state=random_state)
374 n_perm=0, random_state=random_state)
409 n_perm=0, random_state=random_state)
416 n_perm=0, random_state=random_state)
495 random_state=random_state)
531 random_state=random_state)
562 random_state=random_state)
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/ensemble/tests/
H A Dtest_base.py32 random_state = np.random.RandomState(3)
33 ensemble._make_estimator(random_state=random_state)
34 ensemble._make_estimator(random_state=random_state)
41 assert ensemble[0].random_state is None
44 assert ensemble[1].random_state != ensemble[2].random_state
78 clf1 = Perceptron(random_state=None)
79 assert clf1.random_state is None
82 assert isinstance(clf1.random_state, int)
86 assert isinstance(clf1.random_state, int)
87 clf2 = Perceptron(random_state=None)
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H A Dtest_bagging.py129 random_state=1,
137 random_state=1,
255 random_state=rng,
642 n_estimators=10, random_state=random_state, warm_start=False
728 random_state=1,
742 random_state=1,
811 random_state=1,
820 random_state = 5
826 BaggingClassifier(oob_score=True, random_state=random_state)
831 BaggingClassifier(oob_score=True, random_state=random_state)
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H A Dtest_gradient_boosting.py172 random_state=0,
185 random_state=0,
206 random_state=1,
269 X, y = datasets.make_friedman2(n_samples=1200, random_state=random_state)
279 X, y = datasets.make_friedman3(n_samples=1200, random_state=random_state)
365 random_state=1,
389 random_state=0,
1173 random_state=42,
1181 random_state=42,
1220 random_state=42,
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/dports/finance/py-quantecon/quantecon-0.5.2/quantecon/game_theory/
H A Drandom.py13 def random_game(nums_actions, random_state=None): argument
38 random_state = check_random_state(random_state)
40 Player(random_state.random_sample(nums_actions[i:]+nums_actions[:i]))
47 def covariance_game(nums_actions, rho, random_state=None): argument
92 random_state = check_random_state(random_state)
94 random_state.multivariate_normal(mean, cov, nums_actions)
99 def random_pure_actions(nums_actions, random_state=None): argument
120 random_state = check_random_state(random_state)
127 def random_mixed_actions(nums_actions, random_state=None): argument
148 random_state = check_random_state(random_state)
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/dports/finance/py-quantecon/quantecon-0.5.2/quantecon/markov/
H A Drandom.py58 random_state=random_state)
64 random_state=None): argument
102 random_state=random_state)
107 random_state=None): argument
119 probvecs = probvec(m, k, random_state=random_state)
132 n, k, num_trials=m, random_state=random_state
147 random_state=None): argument
197 random_state = check_random_state(random_state)
198 R = scale * random_state.randn(L)
201 random_state=random_state)
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/manifold/tests/
H A Dtest_t_sne.py297 X, _ = make_blobs(n_features=3, random_state=random_state)
305 random_state=0,
326 random_state=0,
410 random_state=42,
424 random_state=42,
798 random_state=0,
824 random_state=0,
1170 random_state=0,
1178 random_state=0,
1276 random_state=0,
[all …]
H A Dtest_spectral_embedding.py90 random_state = np.random.RandomState(seed)
158 random_state=0,
286 n_components=n_clusters, affinity="rbf", random_state=random_state
292 random_state=random_state,
295 km = KMeans(n_clusters=n_clusters, random_state=random_state)
353 random_state = np.random.RandomState(36)
354 data = random_state.randn(10, 30)
364 random_state = np.random.RandomState(36)
365 data = random_state.randn(10, 30)
385 data = random_state.randn(10, 30)
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/linear_model/tests/
H A Dtest_theil_sen.py37 random_state = np.random.RandomState(0)
46 x = random_state.normal(size=n_samples)
65 random_state = np.random.RandomState(0)
68 X = random_state.normal(size=(n_samples, 2))
81 random_state = np.random.RandomState(0)
84 X = random_state.normal(size=(n_samples, 4))
141 random_state = np.random.RandomState(0)
229 random_state = np.random.RandomState(0)
232 y = random_state.normal(size=n_samples)
275 random_state = np.random.RandomState(0)
[all …]
H A Dtest_ransac.py64 random_state=0,
82 random_state=0,
96 random_state=0,
119 random_state=0,
133 random_state=0,
179 random_state=0,
344 random_state=0,
435 random_state=0,
442 random_state=0,
468 random_state=0,
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/examples/cluster/
H A Dplot_kmeans_assumptions.py26 random_state = 170 variable
27 X, y = make_blobs(n_samples=n_samples, random_state=random_state)
30 y_pred = KMeans(n_clusters=2, random_state=random_state).fit_predict(X)
39 y_pred = KMeans(n_clusters=3, random_state=random_state).fit_predict(X_aniso)
47 n_samples=n_samples, cluster_std=[1.0, 2.5, 0.5], random_state=random_state
49 y_pred = KMeans(n_clusters=3, random_state=random_state).fit_predict(X_varied)
57 y_pred = KMeans(n_clusters=3, random_state=random_state).fit_predict(X_filtered)
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/
H A Drandom_projection.py188 rng = check_random_state(random_state)
258 rng = check_random_state(random_state)
274 n_features, n_nonzero_i, random_state=rng
307 self.random_state = random_state
502 random_state=random_state,
523 random_state = check_random_state(self.random_state)
525 n_components, n_features, random_state=random_state
657 random_state=None,
663 random_state=random_state,
686 random_state = check_random_state(self.random_state)
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/cluster/tests/
H A Dtest_spectral.py49 random_state=0,
77 n_samples=100, centers=centers, cluster_std=1.0, random_state=42
96 n_samples=100, centers=centers, cluster_std=1.0, random_state=42
135 random_state=0,
161 sp = SpectralClustering(n_clusters=2, gamma=2, random_state=0)
198 random_state = np.random.RandomState(seed=8)
201 y_true = random_state.randint(0, n_class + 1, n_samples)
211 y_pred = discretize(y_true_noisy, random_state=random_state)
249 graph, n_clusters=2, eigen_solver="arpack", random_state=0
256 graph, n_clusters=2, eigen_solver="amg", random_state=0
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/decomposition/tests/
H A Dtest_sparse_pca.py17 def generate_toy_data(n_components, n_samples, image_size, random_state=None): argument
20 rng = check_random_state(random_state)
46 spca = SparsePCA(n_components=8, random_state=rng)
51 spca = SparsePCA(n_components=13, random_state=rng)
121 pca = MiniBatchSparsePCA(n_components=8, random_state=rng)
126 pca = MiniBatchSparsePCA(n_components=13, random_state=rng)
148 n_components=3, n_jobs=2, alpha=alpha, random_state=0
160 n_components=3, method="cd", alpha=alpha, random_state=0
168 Y, _, _ = generate_toy_data(3, 1000, (8, 8), random_state=rng)
177 Y, _, _ = generate_toy_data(3, 1000, (8, 8), random_state=rng)
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/covariance/
H A D_robust_covariance.py95 random_state = check_random_state(random_state)
103 random_state=random_state,
323 random_state=random_state,
338 random_state=random_state,
499 random_state=random_state,
520 random_state=random_state,
539 random_state=random_state,
557 random_state=random_state,
566 random_state=random_state,
714 self.random_state = random_state
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/dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/optimization/
H A Dsequences.py40 if random_state is None:
42 self.random_state = random_state
95 random_state: tp.Optional[RandomState] = None,
99 super().__init__(dimension, budget, random_state=random_state)
123 random_state: tp.Optional[RandomState] = None,
127 super().__init__(dimension, budget, random_state=random_state)
141 if random_state is None:
167 random_state: tp.Optional[RandomState] = None,
169 super().__init__(dimension, budget, random_state=random_state)
170 self.permgen = HaltonPermutationGenerator(dimension, scrambling, random_state=random_state)
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/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/tests/
H A Dtest_dummy.py250 y = random_state.randn(4)
267 y_test = random_state.randn(20, 5)
290 y = random_state.randn(5)
307 y_test = random_state.randn(20, 5)
324 y = random_state.randn(5)
354 y_test = random_state.randn(20, 5)
418 y = random_state.randn(5)
437 constants = random_state.randn(5)
482 X = random_state.randn(10, 10)
483 y = random_state.randn(10, 5)
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/cluster/
H A D_spectral.py79 random_state = check_random_state(random_state)
112 rotation[:, 0] = vectors[random_state.randint(n_samples), :].T
166 random_state=None, argument
291 random_state = check_random_state(random_state)
304 random_state=random_state,
313 maps, n_clusters, random_state=random_state, n_init=n_init, verbose=verbose
316 labels = discretize(maps, random_state=random_state)
527 random_state=None, argument
543 self.random_state = random_state
621 random_state = check_random_state(self.random_state)
[all …]
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/metrics/tests/
H A Dtest_common.py560 random_state = check_random_state(0)
591 random_state = check_random_state(0)
610 random_state = check_random_state(0)
630 random_state = check_random_state(0)
675 random_state = check_random_state(0)
797 random_state = check_random_state(0)
1019 random_state=0,
1026 random_state=1,
1175 random_state=0,
1182 random_state=1,
[all …]
/dports/textproc/py-wordcloud/word_cloud-1.5.0/wordcloud/
H A Dwordcloud.py81 if random_state is None:
82 random_state = Random()
105 if random_state is None:
106 random_state = Random()
141 if random_state is None:
324 random_state = Random(random_state)
325 self.random_state = random_state
393 random_state = self.random_state
509 random_state=random_state,
661 random_state = Random(random_state)
[all …]

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