„Tets_Python/TotOnline.py“ ändern

Tets_Python/TotOnline.py

@@ -9,7 +9,7 @@ from scipy.special import gammaincc as gammaincc
 
 class TotOnline:
     @staticmethod
-    def total_failure(binary_data: str, pattern_length=10):
+    def total_failure_test(binary_data: str, pattern_length=10):
 
         length_of_binary_data = len(binary_data)
 
@@ -32,13 +32,13 @@ class TotOnline:
             vobs_02[int(binary_data[i:i + pattern_length + 1:], 2)] += 1
 
         # Calculate the test statistics and p values
-        vobs = [vobs_01, vobs_02]
+        vObs = [vobs_01, vobs_02]
 
         sums = zeros(2)
         for i in range(2):
-            for j in range(len(vobs[i])):
+            for j in range(len(vObs[i])):
-                if vobs[i][j] > 0:
+                if vObs[i][j] > 0:
-                    sums[i] += vobs[i][j] * log(vobs[i][j] / length_of_binary_data)
+                    sums[i] += vObs[i][j] * log(vObs[i][j] / length_of_binary_data)
         sums /= length_of_binary_data
         ape = sums[0] - sums[1]
 
@@ -46,7 +46,7 @@ class TotOnline:
 
         p_value = gammaincc(pow(2, pattern_length - 1), xObs / 2.0)
 
-        return (p_value, (p_value >= 0.01))
+        return p_value, (p_value >= 0.01)
 
     @staticmethod
     def monobit_test(binary_data: str):
@@ -71,10 +71,10 @@ class TotOnline:
         p_value = erfc(fabs(sObs) / sqrt(2))
 
         # return a p_value and randomness result
-        return (p_value, (p_value >= 0.01))
+        return p_value, (p_value >= 0.01)
 
     @staticmethod
-    def block_frequency(binary_data: str, block_size=128):
+    def block_frequency_test(binary_data: str, block_size=128):
 
         length_of_bit_string = len(binary_data)
 
@@ -119,12 +119,11 @@ class TotOnline:
         # Compute P-Value
         p_value = gammaincc(number_of_blocks / 2, result / 2)
 
-        return (p_value, (p_value >= 0.01))
+        return p_value, (p_value >= 0.01)
 
     @staticmethod
     def run_test(binary_data: str):
 
-        one_count = 0
         vObs = 0
         length_of_binary_data = len(binary_data)
 
@@ -139,7 +138,7 @@ class TotOnline:
         # Step 2 - If it can be shown that absolute value of (π - 0.5) is greater than or equal to tau
         # then the run test need not be performed.
         if abs(pi - 0.5) >= tau:
-            return (0.0000)
+            return 0.0000
         else:
             # Step 3 - Compute vObs
             for item in range(1, length_of_binary_data):
@@ -148,9 +147,9 @@ class TotOnline:
             vObs += 1
 
             # Step 4 - Compute p_value = erfc((|vObs − 2nπ * (1−π)|)/(2 * sqrt(2n) * π * (1−π)))
-            p_value = erfc(abs(vObs - (2 * (length_of_binary_data) * pi * (1 - pi))) / (2 * sqrt(2 * length_of_binary_data) * pi * (1 - pi)))
+            p_value = erfc(abs(vObs - (2 * length_of_binary_data * pi * (1 - pi))) / (2 * sqrt(2 * length_of_binary_data) * pi * (1 - pi)))
 
-        return (p_value, (p_value > 0.01))
+        return p_value, (p_value > 0.01)
 
     @staticmethod
     def longest_one_block_test(binary_data: str):
@@ -161,7 +160,7 @@ class TotOnline:
         # Initialized k, m. n, pi and v_values
         if length_of_binary_data < 128:
             # Not enough data to run this test
-            return (0.00000, 'Error: Not enough data to run this test')
+            return 0.00000, 'Error: Not enough data to run this test'
         elif length_of_binary_data < 6272:
             k = 3
             m = 8
@@ -183,7 +182,7 @@ class TotOnline:
         block_start = 0
         block_end = m
         xObs = 0
-        # This will intialized an array with a number of 0 you specified.
+        # This will initialize an array with a number of 0 you specified.
         frequencies = zeros(k + 1)
 
         # print('Number of Blocks: ', number_of_blocks)
@@ -204,7 +203,7 @@ class TotOnline:
 
             max(max_run_count, run_count)
 
-            #print('Block Data: ', block_data, '. Run Count: ', max_run_count)
+            # print('Block Data: ', block_data, '. Run Count: ', max_run_count)
             if max_run_count < v_values[0]:
                 frequencies[0] += 1
             for j in range(k):
@@ -224,4 +223,4 @@ class TotOnline:
 
         p_value = gammaincc(float(k / 2), float(xObs / 2))
 
-        return (p_value, (p_value > 0.01))
+        return p_value, (p_value > 0.01)