Delete Testing.py

Testing.py

@@ -1,33 +0,0 @@
-import evaluate as ev
-from nDCG import nDCG
-
-metric = nDCG(cache_dir="cache")
-a = [1,2,3,4,5]
-b = [1,2,3,4,5]
-c = [1,2,3,4,0]
-
-
-#metric.add(prediction=a, reference=b)
-metric.add(prediction=c, reference=b)
-metric.add(prediction=c, reference=b)
-metric.add(prediction=c, reference=b)
-print(metric.compute(predictions=[a], references=[b]))
-print(metric.compute(predictions=[a], references=[c]))
-print(metric.compute(predictions=[a], references=[c]))
-print(metric.compute(predictions=[a,a], references=[c,a]))
-print(metric.cache_file_name)
-
-nDCG_metric = ev.load("nDCG.py")
-results = nDCG_metric.compute(references=[[10, 0, 0, 1, 5]], predictions=[[.1, .2, .3, 4, 70]])
-print(results)
-
-nDCG_metric = ev.load("nDCG.py")
-results = nDCG_metric.compute(references=[[10, 0, 0, 1, 5]], predictions=[[.1, .2, .3, 4, 70]], k=3)
-print(results)
-
-nDCG_metric = ev.load("nDCG.py")
-results = nDCG_metric.compute(references=[[1, 0, 0, 0, 0]], predictions=[[1, 1, 0, 0, 0]], k=1)
-print(results)
-
-results = nDCG_metric.compute(references=[[1, 0, 0, 0, 0]], predictions=[[1, 1, 0, 0, 0]], k=1, ignore_ties=True)
-print(results)