refining MultiLineFitterTest

src/SymptomsCausedByVaccines/MultiLineFitting/LinesFactory.py

@@ -1,5 +1,5 @@
 from skspatial.objects import Line
-from SymptomsCausedByVaccines.MultiLineFitting.MultiLineFitter import MultiLineFitter
+from SymptomsCausedByVaccines.MultiLineFitting.Utils import getPairs
 
 
 class LinesFactory:
@@ -11,7 +11,7 @@ class LinesFactory:
 
     @staticmethod
     def _getPairs(points):
-        return ((points[i], points[j]) for (i, j) in MultiLineFitter._getPairs(len(points)))
+        return ((points[i], points[j]) for (i, j) in getPairs(len(points)))
 
     @staticmethod
     def _getUniqueLines(lines):

src/SymptomsCausedByVaccines/MultiLineFitting/MultiLineFitter.py

@@ -1,8 +1,14 @@
 import numpy as np
+from SymptomsCausedByVaccines.MultiLineFitting.LinesFactory import LinesFactory
+from SymptomsCausedByVaccines.MultiLineFitting.Utils import getPairs
 
 # implementation of "Robust Multiple Structures Estimation with J-linkage" adapted from https://github.com/fkluger/vp-linkage
 class MultiLineFitter:
     
+    @staticmethod
+    def fitPointsByLines(points, consensusThreshold):
+        return MultiLineFitter.fitLines(points, LinesFactory.createLines(points), consensusThreshold)
+
     @staticmethod
     def fitLines(points, lines, consensusThreshold):
         preferenceMatrix = MultiLineFitter._createPreferenceMatrix(points, lines, consensusThreshold)
@@ -28,7 +34,7 @@ class MultiLineFitter:
             bestClusterIndexCombination = None
             keepClustering = False
             numClusters = preferenceMatrix.shape[0]
-            for (clusterIndexA, clusterIndexB) in MultiLineFitter._getPairs(numClusters):
+            for (clusterIndexA, clusterIndexB) in getPairs(numClusters):
                 preferenceSetA = preferenceMatrix[clusterIndexA]
                 preferenceSetB = preferenceMatrix[clusterIndexB]
                 similarity = MultiLineFitter._intersectionOverUnion(preferenceSetA, preferenceSetB);
@@ -46,12 +52,6 @@ class MultiLineFitter:
 
         return clusters, preferenceMatrix
 
-    @staticmethod
-    def _getPairs(n):
-        for i in range(n):
-            for j in range(i):
-                yield (i, j)
-
     @staticmethod
     def _intersectionOverUnion(setA, setB):
         intersection = np.count_nonzero(np.logical_and(setA, setB))

src/SymptomsCausedByVaccines/MultiLineFitting/MultiLineFitterTest.py

@@ -115,5 +115,14 @@ class MultiLineFitterTest(unittest.TestCase):
         # Then
         np.testing.assert_array_equal(fittedLines, [line1, line2])
 
-#FK-TODO: erzeuge LinesFactory.createLines(points = [(1, 0), (2, 0), (3, 0), (1, 1), (2, 2), (3, 3)])
+    def test_fitPointsByLines(self):
-#         Diese Funktion soll alle Linien erzeugen, die jeweils zwei verschiedene Punkte aus points verbinden.
+        # Given
+        points = [(1, 0), (2, 0), (3, 0), (1, 1), (2, 2), (3, 3)]
+
+        # When
+        lines = MultiLineFitter.fitPointsByLines(points, consensusThreshold = 0.001)
+
+        # Then
+        self.assertEqual(len(lines), 2)
+        self.assertTrue(lines[0].is_close(Line.from_points([0, 0], [1, 0])))
+        self.assertTrue(lines[1].is_close(Line.from_points([0, 0], [1, 1])))

src/SymptomsCausedByVaccines/MultiLineFitting/Utils.py

@@ -0,0 +1,4 @@
+def getPairs(n):
+    for i in range(n):
+        for j in range(i):
+            yield (i, j)