init

src/uniformity/shannon.rs

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+use statrs::distribution::{Normal, ContinuousCDF};
+
+use crate::Onod;
+
+impl Onod {
+    /// Entropy randomness test
+    /// Calculates the Shannon entropy of a byte slice and outputs a p-value.
+    pub fn shannon(samples: &[u8]) -> f64 {
+
+        let len = samples.len() as f64;
+        if len == 0.0 {
+            return 0.0;
+        }
+
+        // Count occurrences of each byte
+        let mut counts = [0usize; 256];
+        for &byte in samples {
+            counts[byte as usize] += 1;
+        }
+
+        // Calculate Shannon entropy
+        let entropy: f64 = counts.iter()
+            .filter(|&&count| count > 0)
+            .map(|&count| {
+                let p = count as f64 / len;
+                -p * p.log2()
+            })
+            .sum();
+
+        // Expected entropy for a uniform distribution
+        let expected_entropy = 8.0;
+
+        // Calculate Z statistic
+        let std_dev = (0.833_f64).sqrt();
+        let z_score = (entropy - expected_entropy) * len.sqrt() / std_dev;
+
+        // Calculate p-value from Z score
+        let normal_dist = Normal::new(0.0, 1.0).expect("Failed to create Normal distribution");
+        let p_value = 2.0 * (1.0 - normal_dist.cdf(z_score.abs())); // Two-tailed test
+
+        p_value
+    }
+}