test repair, change entropy realisation, added volume documentation

src/foapy/characteristics/ma/entropy.py

@@ -19,4 +19,4 @@ def entropy(intervals):
 
     """
 
-    return np.asanyarray([np.log2(line.mean()) for line in intervals])
+    return np.asanyarray([np.log2(np.average(line)) for line in intervals])

src/foapy/characteristics/ma/volume.py

@@ -8,7 +8,7 @@ def volume(intervals):
 
     Parameters
     ----------
-    X: two-dimensional array
+    X: two-dimensional intervals sequence array
         Source array sequence.
 
     Returns
@@ -19,46 +19,70 @@ def volume(intervals):
     --------
 
     ----1----
-    >>> a = ["B", "B", "A", "A", "C", "B", "A", "C", "C", "B"]
-    >>> b = volume(X, binding.start, mode.lossy)
+    >>> a = [
+            [0 0 -- -- -- 0 -- -- -- 0]
+            [-- -- 1 1 -- -- 1 -- -- --]
+            [-- -- -- -- 2 -- -- 2 2 --]
+            ]
+    >>> b = volume(a)
     >>> b
     [16  3  3]
 
     ----2----
-    >>> a = ["B", "B", "A", "A", "C", "B", "A", "C", "C", "B"]
-    >>> b = volume(X, binding.start, mode.normal)
+    >>> a = [
+        [1 1 4 4]
+        [3 1 3]
+        [5 3 1]
+    ]
+    >>> b = volume(a)
     >>> b
-    [16 12  6]
+    [16 9  15]
 
     ----3----
-    >>> a = ["B", "B", "A", "A", "C", "B", "A", "C", "C", "B"]
-    >>> b = volume(X, binding.end,  mode.normal)
+    >>> a = [
+        [1 4 4 1]
+        [1 3 4]
+        [3 1 2]
+    ]
+    >>> b = volume(a)
     >>> b
-    [16 36 30]
+    [16 12 6]
 
     ----4----
-    >>> a = ["B", "B", "A", "A", "C", "B", "A", "C", "C", "B"]
-    >>> b = volume(X, binding.start, mode.redundant)
+    >>> a = [
+        [-- -- -- 1 1 -- -- 1 -- --]
+        ]
+    >>> b = volume(a)
     >>> b
-    [16 36 30]
+    [6]
 
     ----5----
-    >>> a = ["B", "B", "A", "A", "C", "B", "A", "C", "C", "B"]
-    >>> b = volume(X, binding.start, mode.cycle)
+    >>> a = [--]
+    >>> b = volume(a)
     >>> b
-    [16 18 18]
+    []
 
     ----6----
-    >>> a = ["B", "A"]
-    >>> b = volume(X, binding.start, mode.lossy)
+    >>> a = ["B"]
+    >>> b = volume(a)
     >>> b
-    [1 1]
+    [1]
 
     ----7----
-    >>> a = ["B", "A", "C", "D"]
-    >>> b = volume(X, binding.start, mode.lossy)
+    >>> a = [
+        [1 1 1 1 1]
+    ]
+    >>> b = volume(a)
     >>> b
-    [1 1 1 1]
+    [1]
+
+    ----8----
+    >>> a = [
+        []
+        ]
+    >>> b = volume(a)
+    >>> b
+    []
     """
 
     return np.asanyarray([np.prod(line) for line in intervals])

tests/test_characteristics/test_ma_arighmetic_mean.py

@@ -59,7 +59,7 @@ def test_calculate_start_redunant_depth(self):
         intervals_seq = intervals(
             order_seq, binding_constant.start, mode_constant.lossy
         )
-        expected = np.array([1.5, 2])  # incorrect test
+        expected = np.array([2])
         exists = arigthmetic_mean(intervals_seq)
         epsilon = 0.01
         print(exists)

tests/test_characteristics/test_ma_volume.py

@@ -84,17 +84,48 @@ def test_calculate_start_lossy_empty_values_volume(self):
         exists = volume(intervals_seq)
         assert_equal(expected, exists)
 
-    # def test_calculate_start_redunant_values_with_mask(self):
-    #     X = ['B','B','B','A','A','B','B','A','B','B']
-    #     mask = [1, 1, 1, 0, 0, 1, 1, 0, 1, 1]
-    #     masked_X = ma.masked_array(X, mask)
-    #     order_seq = order(masked_X)
-    #     print(order_seq)
-    #     intervals_seq = intervals(
-    #         order_seq, binding_constant.start, mode_constant.redundant
-    #     )
+    def test_calculate_start_redunant_values_with_mask(self):
+        X = ["B", "B", "B", "A", "A", "B", "B", "A", "B", "B"]
+        mask = [1, 1, 1, 0, 0, 1, 1, 0, 1, 1]
+        masked_X = ma.masked_array(X, mask)
+        order_seq = order(masked_X)
+        intervals_seq = intervals(
+            order_seq, binding_constant.start, mode_constant.redundant
+        )
+        expected = np.array([36])
+        exists = volume(intervals_seq)
+        assert_equal(expected, exists)
+
+    def test_calulate_normal_with_the_same_values(self):
+        X = ["A", "A", "A", "A", "A"]
+        masked_X = ma.masked_array(X)
+        order_seq = order(masked_X)
+        intervals_seq = intervals(
+            order_seq, binding_constant.start, mode_constant.normal
+        )
+        expected = np.array([1])
+        exists = volume(intervals_seq)
+        assert_equal(expected, exists)
 
-    #     expected = np.array([36]) # incorrect test res [6,  36]
-    #     exists = volume(intervals_seq)
-    #     print(exists)
-    #     assert_equal(expected, exists)
+    def test_calculate_start_cycle_with_masked_single_value(self):
+        X = ["A"]
+        mask = [1]
+        masked_X = ma.masked_array(X, mask)
+        order_seq = order(masked_X)
+        intervals_seq = intervals(
+            order_seq, binding_constant.start, mode_constant.cycle
+        )
+        expected = np.array([])
+        exists = volume(intervals_seq)
+        assert_equal(expected, exists)
+
+    def test_calculate_start_cycle_with_single_value(self):
+        X = ["A"]
+        masked_X = ma.masked_array(X)
+        order_seq = order(masked_X)
+        intervals_seq = intervals(
+            order_seq, binding_constant.start, mode_constant.cycle
+        )
+        expected = np.array([1])
+        exists = volume(intervals_seq)
+        assert_equal(expected, exists)