measurements for the different violation types, comparison for differenct generation config

3 files changed, 49 insertions, 3 deletions

diff --git a/Metrics/Metrics-Calculation/metrics_plot/utils/DistributionMetrics.py b/Metrics/Metrics-Calculation/metrics_plot/utils/DistributionMetrics.py
new file mode 100644
index 00000000..6e707108
--- /dev/null
+++ b/Metrics/Metrics-Calculation/metrics_plot/utils/DistributionMetrics.py
@@ -0,0 +1,43 @@
+from scipy import stats
+from scipy.spatial import distance
+
+def ks_distance(samples1, samples2):
+    value, p = stats.ks_2samp(samples1, samples2)
+    return (value, p)
+
+def js_distance(samples1, samples2):
+    map1 = fromSamples(samples1)
+    map2 = fromSamples(samples2)
+    allKeys = set(map1.keys()) | set(map2.keys())
+    dist1 = distributionFromMap(map1, allKeys)
+    dist2 = distributionFromMap(map2, allKeys)
+    return distance.jensenshannon(dist1, dist2, 2)
+
+def euclidean_distance(samples1, samples2):
+    map1 = fromSamples(samples1)
+    map2 = fromSamples(samples2)
+    allKeys = set(map1.keys()) | set(map2.keys())
+    dist1 = distributionFromMap(map1, allKeys)
+    dist2 = distributionFromMap(map2, allKeys)
+    distance = 0
+    for i in range(len(dist2)):
+        distance += pow(dist1[i] - dist2[i], 2)
+    return pow(distance, 0.5)
+
+def fromSamples(samples):
+    m = {}
+    length = len(samples)
+    for sample in samples:
+        value = m.get(sample, 0)
+        m[sample] = value + 1
+    for key in list(m.keys()):
+        m[key] /= length
+    return m
+
+def distributionFromMap(m, allKeys):
+    dist = []
+    for key in allKeys:
+        value = m.get(key, 0)
+        dist.append(value)
+    return dist
+
diff --git a/Metrics/Metrics-Calculation/metrics_plot/utils/GraphType.py b/Metrics/Metrics-Calculation/metrics_plot/utils/GraphType.py
index 13754e80..827c2a5e 100644
--- a/Metrics/Metrics-Calculation/metrics_plot/utils/GraphType.py
+++ b/Metrics/Metrics-Calculation/metrics_plot/utils/GraphType.py
@@ -11,13 +11,13 @@ class GraphCollection:
         self.nas = []
         self.mpcs = []
         self.name = name
+        self.size = number
         models = reader.readmultiplefiles(path, number, shouldShuffle)
         for i in range(len(models)):
             contents, out_d, na, mpc = reader.getmetrics(models[i])
             self.out_ds.append(out_d)
             self.nas.append(na)
             self.mpcs.append(mpc)
-        print(len(self.out_ds))
 
 #Graph stat for one graph
 class GraphStat:
diff --git a/Metrics/Metrics-Calculation/metrics_plot/utils/readCSV.py b/Metrics/Metrics-Calculation/metrics_plot/utils/readCSV.py
index e0402519..b27a0ffc 100644
--- a/Metrics/Metrics-Calculation/metrics_plot/utils/readCSV.py
+++ b/Metrics/Metrics-Calculation/metrics_plot/utils/readCSV.py
@@ -24,9 +24,12 @@ def readcsvfile(filename):
             # meta models are string
             elif(arr[0] == constants.METAMODEL):
                 contents[constants.METAMODEL] = arr[1:]
-            # all other contants are integer
+            # NA and OD are integers
             else:
-                contents[arr[0]] = list(map(int, arr[1:]))
+                try:
+                    contents[arr[0]] = list(map(int, arr[1:]))
+                except:
+                    print(arr[0], ' is not integer')
     f.close()
     return contents