New translations compute_sspkernel_for_syntheticnew.py (Chinese Simplified)

lang/zh/notebooks/else/compute_sspkernel_for_syntheticnew.py

@@ -0,0 +1,54 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Sun Dec 23 16:40:52 2018
+
+@author: ljia
+"""
+import sys
+import numpy as np
+import networkx as nx
+
+sys.path.insert(0, "../")
+from gklearn.utils.graphfiles import loadDataset
+from gklearn.utils.model_selection_precomputed import compute_gram_matrices
+from gklearn.kernels.structuralspKernel import structuralspkernel
+from sklearn.model_selection import ParameterGrid
+
+from libs import *
+import multiprocessing
+import functools
+from gklearn.utils.kernels import deltakernel, gaussiankernel, kernelproduct
+
+
+if __name__ == "__main__":
+    # load dataset.
+    print('getting dataset and computing kernel distance matrix first...')
+    ds_name = 'SYNTHETICnew'
+    gkernel = 'structuralspkernel'
+    dataset = '../datasets/SYNTHETICnew/SYNTHETICnew_A.txt'
+    Gn, y_all = loadDataset(dataset)
+
+    for G in Gn:
+        G.graph['filename'] = 'graph' + str(G.graph['name']) + '.gxl'
+    
+    # compute/read Gram matrix and pair distances.
+    mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel)
+    sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel}
+    Kmatrix, run_time = structuralspkernel(Gn, node_label=None, edge_label=None,
+                          node_kernels=sub_kernels, edge_kernels=sub_kernels,
+                          parallel=None,  # parallel='imap_unordered', 
+                          n_jobs=multiprocessing.cpu_count(), 
+                          verbose=True)
+    
+    # normalization
+    Kmatrix_diag = Kmatrix.diagonal().copy()
+    for i in range(len(Kmatrix)):
+        for j in range(i, len(Kmatrix)):
+            Kmatrix[i][j] /= np.sqrt(Kmatrix_diag[i] * Kmatrix_diag[j])
+            Kmatrix[j][i] = Kmatrix[i][j]
+    
+    np.savez('results/xp_fit_method/Kmatrix.' + ds_name + '.' + gkernel + '.gm', 
+         Kmatrix=Kmatrix, run_time=run_time)
+    
+    print('complete!')