def simulateKMoreThanOne():
failures = "<STR_LIT>"<EOL>LOGGER.info("<STR_LIT>")<EOL>knn = KNNClassifier(k=<NUM_LIT:3>)<EOL>v = numpy.zeros((<NUM_LIT:6>, <NUM_LIT:2>))<EOL>v[<NUM_LIT:0>] = [<NUM_LIT:1.0>, <NUM_LIT:0.0>]<EOL>v[<NUM_LIT:1>] = [<NUM_LIT:1.0>, <NUM_LIT>]<EOL>v[<NUM_LIT:2>] = [<NUM_LIT:1.0>, <NUM_LIT>]<EOL>v[<NUM_LIT:3>] = [<NUM_LIT:1.0>, <NUM_LIT>]<EOL>v[<NUM_LIT:4>] = [<NUM_LIT:1.0>, <NUM_LIT>]<EOL>v[<NUM_LIT:5>] = [<NUM_LIT:1.0>, <NUM_LIT>]<EOL>knn.learn(v[<NUM_LIT:0>], <NUM_LIT:0>)<EOL>knn.learn(v[<NUM_LIT:1>], <NUM_LIT:0>)<EOL>knn.learn(v[<NUM_LIT:2>], <NUM_LIT:0>)<EOL>knn.learn(v[<NUM_LIT:3>], <NUM_LIT:1>)<EOL>knn.learn(v[<NUM_LIT:4>], <NUM_LIT:1>)<EOL>knn.learn(v[<NUM_LIT:5>], <NUM_LIT:1>)<EOL>winner, _inferenceResult, _dist, _categoryDist = knn.infer(v[<NUM_LIT:0>])<EOL>if winner != <NUM_LIT:0>:<EOL><INDENT>failures += "<STR_LIT>"<EOL><DEDENT>winner, _inferenceResult, _dist, _categoryDist = knn.infer(v[<NUM_LIT:2>])<EOL>if winner != <NUM_LIT:0>:<EOL><INDENT>failures += "<STR_LIT>"<EOL><DEDENT>winner, _inferenceResult, _dist, _categoryDist = knn.infer(v[<NUM_LIT:3>])<EOL>if winner != <NUM_LIT:0>:<EOL><INDENT>failures += "<STR_LIT>"<EOL><DEDENT>winner, _inferenceResult, _dist, _categoryDist = knn.infer(v[<NUM_LIT:5>])<EOL>if winner != <NUM_LIT:1>:<EOL><INDENT>failures += "<STR_LIT>"<EOL><DEDENT>if len(failures) == <NUM_LIT:0>:<EOL><INDENT>LOGGER.info("<STR_LIT>")<EOL><DEDENT>return failures<EOL>
A small test with k=3