Added experiment for checking which metrics work best for using unigram frequency...

[cipher-tools.git] / find_best_caesar_break_parameters.py

diff --git a/find_best_caesar_break_parameters.py b/find_best_caesar_break_parameters.py
new file mode 100644 (file)
index 0000000..711cff0
--- /dev/null
+++ b/find_best_caesar_break_parameters.py
@@ -0,0 +1,60 @@
+import random
+from cipher import *
+
+
+corpus = sanitise(''.join([open('shakespeare.txt', 'r').read(), open('sherlock-holmes.txt', 'r').read(), open('war-and-peace.txt', 'r').read()]))
+corpus_length = len(corpus)
+
+scaled_english_counts = norms.scale(english_counts)
+
+
+metrics = [norms.l1, norms.l2, norms.l3, norms.cosine_distance, norms.harmonic_mean, norms.geometric_mean]
+corpus_frequencies = [normalised_english_counts, scaled_english_counts]
+scalings = [norms.normalise, norms.scale]
+message_lengths = [3000, 1000, 300, 100, 50, 30, 20, 10, 5]
+
+metric_names = ['l1', 'l2', 'l3', 'cosine_distance', 'harmonic_mean', 'geometric_mean']
+corpus_frequency_names = ['normalised_english_counts', 'scaled_english_counts']
+scaling_names = ['normalise', 'scale']
+
+trials = 5000
+
+scores = collections.defaultdict(int)
+for metric in range(len(metrics)):
+    scores[metric_names[metric]] = collections.defaultdict(int)
+    for corpus_freqency in range(len(corpus_frequencies)):
+        scores[metric_names[metric]][corpus_frequency_names[corpus_freqency]] = collections.defaultdict(int)
+        for scaling in range(len(scalings)):
+            scores[metric_names[metric]][corpus_frequency_names[corpus_freqency]][scaling_names[scaling]] = collections.defaultdict(int)
+            for message_length in message_lengths:
+                for i in range(trials):
+                    sample_start = random.randint(0, corpus_length - message_length)
+                    sample = corpus[sample_start:(sample_start + message_length)]
+                    key = random.randint(1, 25)
+                    sample_ciphertext = caesar_encipher(sample, key)
+                    (found_key, score) = caesar_break(sample_ciphertext, 
+                                                      metric=metrics[metric], 
+                                                      target_frequencies=corpus_frequencies[corpus_freqency], 
+                                                      message_frequency_scaling=scalings[scaling])
+                    if found_key == key:
+                        scores[metric_names[metric]][corpus_frequency_names[corpus_freqency]][scaling_names[scaling]][message_length] += 1 
+                print(', '.join([metric_names[metric], 
+                                 corpus_frequency_names[corpus_freqency], 
+                                 scaling_names[scaling], 
+                                 str(message_length), 
+                                 str(scores[metric_names[metric]][corpus_frequency_names[corpus_freqency]][scaling_names[scaling]][message_length] / trials) ]))
+
+
+with open('caesar_break_parameter_trials.csv', 'w') as f:
+    for metric in range(len(metrics)):
+        for corpus_freqency in range(len(corpus_frequencies)):
+            for scaling in range(len(scalings)):
+                for message_length in message_lengths:
+                    print(', '.join([metric_names[metric], 
+                                     corpus_frequency_names[corpus_freqency], 
+                                     scaling_names[scaling], 
+                                     str(message_length), 
+                                     str(scores[metric_names[metric]][corpus_frequency_names[corpus_freqency]][scaling_names[scaling]][message_length] / trials) ]), 
+                          file=f)
+                      
+                            
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