From cc81011318848df310be8bb168a210864901a783 Mon Sep 17 00:00:00 2001
From: Gideon Regehr <2023558@stud.hs-mannheim.de>
Date: Tue, 16 May 2023 13:44:22 +0200
Subject: [PATCH] aktualisierter Code

---
 Python_Tests/StartUpTest | 45 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 45 insertions(+)
 create mode 100644 Python_Tests/StartUpTest

diff --git a/Python_Tests/StartUpTest b/Python_Tests/StartUpTest
new file mode 100644
index 0000000..8154054
--- /dev/null
+++ b/Python_Tests/StartUpTest
@@ -0,0 +1,45 @@
+from math import fabs as fabs
+from math import sqrt as sqrt
+from scipy.special import erfc as erfc
+import numpy as np
+from scipy import stats
+
+
+class StartUPTest:
+
+    @staticmethod
+    def monobit_test(binary_data: str):
+
+        length_of_bit_string = len(binary_data)
+
+        # Variable for S(n)
+        count = 0
+        # Iterate each bit in the string and compute for S(n)
+        for bit in binary_data:
+            if bit == 48:
+                # If bit is 0, then -1 from the S(n)
+                count -= 1
+            elif bit == 49:
+                # If bit is 1, then +1 to the S(n)
+                count += 1
+
+        # Compute the test statistic
+        sObs = count / sqrt(length_of_bit_string)
+
+        # Compute p-Value
+        p_value = erfc(fabs(sObs) / sqrt(2))
+
+        # return a p_value and randomness result
+        return p_value, (p_value >= 0.01)
+
+    @staticmethod
+    def chi_square(binary_data: str):
+
+        observed_frequencies = [binary_data.count(48), binary_data.count(49)]
+        expected_probabilities = [0.5, 0.5]  # Assuming equal probability for each bit value
+        total_observations = len(binary_data)
+        expected_frequencies = np.array(expected_probabilities) * total_observations
+
+        chi2_statistic, p_value = stats.chisquare(observed_frequencies, f_exp=expected_frequencies)
+
+        return p_value, p_value >= 0.01, chi2_statistic