Simplify script generating confusion matrices thanks to deabb234

scripts/confusionMatrices.py

 #!/usr/bin/env python3
 
 from EDdA import data
+from EDdA.store import preparePath
 from EDdA.classification import confusionMatrix, metrics, toPNG, topNGrams
 import os
 import sys
 
-def preparePath(root, source, n, ranks, metricName):
-    path = "{root}/confusionMatrix/{inputHash}/{n}grams_top{ranks}_{name}.png".format(
-            root=root,
-            inputHash=source.hash,
-            n=n,
-            ranks=ranks,
-            name=metricName
-        )
-    os.makedirs(os.path.dirname(path), exist_ok=True)
-    return path
-
 def __syntax(this):
     print(
             "Syntax: {this} {required} {optional}".format(
@@ -27,13 +17,14 @@ def __syntax(this):
         )
     sys.exit(1)
 
-def __compute(sourcePath, ns, ranksToTry, metricNames, outputDir):
+def __compute(sourcePath, ns, ranksToTry, metricNames, root):
     source = data.load(sourcePath)
+    path = f"{root}/confusionMatrix/{source.hash}"
     for n in ns:
         for ranks in ranksToTry:
             vectorizer = topNGrams(source, n, ranks)
             for name in metricNames:
-                imagePath = preparePath(outputDir, source, n, ranks, name)
+                imagePath = preparePath(f"{path}/{n}grams_top{ranks}_{name}.png")
                 toPNG(confusionMatrix(vectorizer, metrics[name]), imagePath)
 
 if __name__ == '__main__':