本文整理汇总了Python中pystruct.models.GridCRF._get_edges方法的典型用法代码示例。如果您正苦于以下问题：Python GridCRF._get_edges方法的具体用法？Python GridCRF._get_edges怎么用？Python GridCRF._get_edges使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pystruct.models.GridCRF的用法示例。
在下文中一共展示了GridCRF._get_edges方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_binary_ssvm_attractive_potentials_edgefeaturegraph
# 需要导入模块: from pystruct.models import GridCRF [as 别名]
# 或者: from pystruct.models.GridCRF import _get_edges [as 别名]
def test_binary_ssvm_attractive_potentials_edgefeaturegraph(inference_method="qpbo"):
X, Y = generate_blocks(n_samples=10)
crf = GridCRF(inference_method=inference_method)
#######
# convert X,Y to EdgeFeatureGraphCRF instances
crf_edge = EdgeFeatureGraphCRF(inference_method=inference_method,
symmetric_edge_features=[0]
)
X_edge = []
Y_edge = []
for i in range(X.shape[0]):
unaries = X[i].reshape((-1, 2))
edges = crf._get_edges(X[i])
edge_feats = np.ones((edges.shape[0], 1))
X_edge.append((unaries, edges, edge_feats))
Y_edge.append((Y[i].reshape((-1,))))
submodular_clf_edge = SubgradientSSVM(model=crf_edge, max_iter=100, C=1,
verbose=1,
zero_constraint=[4,7],
negativity_constraint=[5,6],
)
# fit the model with non-negativity constraint on the off-diagonal potential
submodular_clf_edge.fit(X_edge, Y_edge)
assert submodular_clf_edge.w[5] == submodular_clf_edge.w[6] # symmetry constraint on edge features
# # # bias doesn't matter
# submodular_clf_edge.w += 10*np.ones(submodular_clf_edge.w.shape)
# print len(submodular_clf_edge.w), submodular_clf_edge.w
Y_pred = submodular_clf_edge.predict(X_edge)
assert_array_equal(Y_edge, Y_pred)
# try to fit the model with non-negativity constraint on the off-diagonal potential, this time
# with inverted sign on the edge features
X_edge_neg = [ (x[0], x[1], -x[2]) for x in X_edge ]
submodular_clf_edge = SubgradientSSVM(model=crf_edge, max_iter=100, C=1,
verbose=1,
zero_constraint=[4,7],
negativity_constraint=[5,6],
)
submodular_clf_edge.fit(X_edge_neg, Y_edge)
Y_pred = submodular_clf_edge.predict(X_edge_neg)
assert_array_equal(Y_edge, Y_pred)