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- #!/usr/bin/env python3
- # -*- coding: utf-8 -*-
- """
- Created on Fri Mar 27 17:30:55 2020
-
- @author: ljia
- """
- import multiprocessing
- import functools
- from gklearn.utils.kernels import deltakernel, gaussiankernel, kernelproduct
- from gklearn.preimage import MedianPreimageGenerator
- from gklearn.utils import Dataset
-
-
- def test_median_preimage_generator():
-
- # 1. set parameters.
- print('1. setting parameters...')
- ds_name = 'Letter-high'
- mpg = MedianPreimageGenerator()
- mpg_options = {'fit_method': 'k-graphs',
- 'init_ecc': [3, 3, 1, 3, 3],
- 'ds_name': 'Letter-high',
- 'parallel': True,
- 'time_limit_in_sec': 0,
- 'max_itrs': 100,
- 'max_itrs_without_update': 3,
- 'epsilon_ratio': 0.01,
- 'verbose': 2}
- mpg.set_options(**mpg_options)
- mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel)
- sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel}
- mpg.kernel_options = {'name': 'structuralspkernel',
- 'edge_weight': None,
- 'node_kernels': sub_kernels,
- 'edge_kernels': sub_kernels,
- 'compute_method': 'naive',
- 'parallel': 'imap_unordered',
- # 'parallel': None,
- 'n_jobs': multiprocessing.cpu_count(),
- 'normalize': True,
- 'verbose': 2}
- mpg.ged_options = {'method': 'IPFP',
- 'initial_solutions': 40,
- 'edit_cost': 'LETTER2',
- 'attr_distance': 'euclidean',
- 'ratio_runs_from_initial_solutions': 1,
- 'threads': multiprocessing.cpu_count(),
- 'init_option': 'EAGER_WITHOUT_SHUFFLED_COPIES'}
- mpg.mge_options = {'init_type': 'MEDOID',
- 'random_inits': 10,
- 'time_limit': 600,
- 'verbose': 2,
- 'refine': False}
-
-
- # 2. get dataset.
- print('2. getting dataset...')
- mpg.dataset = Dataset()
- mpg.dataset.load_predefined_dataset(ds_name)
- mpg.dataset.cut_graphs(range(0, 10))
-
- # 3. compute median preimage.
- print('3. computing median preimage...')
- mpg.run()
-
-
- if __name__ == '__main__':
- test_median_preimage_generator()
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