Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/4254#discussion_r23819122
--- Diff: data/mllib/pic_data.txt ---
@@ -0,0 +1,299 @@
+1000 0.000000 0.000125 0.000038 0.012684
0.000638 0.051091 0.000151 0.044208 0.004264
0.000617 0.007746 0.036569 0.001813 0.000305
0.003171 0.004114 0.000530 0.016800 0.003396
0.017566 0.034756 0.000018 0.051096 0.000022
0.001749 0.000210 0.006065 0.006969 0.016719
0.006028 0.003378 0.003200 0.025072 0.000291
0.000116 0.001633 0.000028 0.011305 0.000019
0.010359 0.006533 0.047593 0.027411 0.000059
0.017558 0.000518 0.000946 0.044212 0.000094
0.005404 0.026762 0.009941 0.003801 0.000027
0.000161 0.000901 0.000019 0.000518 0.034732
0.000059 0.000126 0.000970 0.011814 0.005997
0.000205 0.001832 0.008792 0.036318 0.000149
0.032781 0.010692 0.000530 0.010557 0.016641
0.008180 0.001606 0.000092 0.007445 0.026718
0.027457 0.000957 0.005901 0.000314 0.000162
0.000856 0.004776 0.008114 0.003693 0.000038
0.024965 0.044256 0.007180 0.000022 0.010297
0.000994 0.044255 0.001725 0.016541 0.003658
0.000288
--- End diff --
This is too large for unit tests. Unit tests should be as minimal as
possible. For this one, we can construct a very small graph, compute its
eigenvector, and derive the clustering result manually, then verify PIC result.
For example
~~~
a - b - c - g - h
| \ | | \ |
d - e - f i - j
~~~
Assign each edge distance `1` and run PIC with k = 2. The solution should
be clear.
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