From bdacf2c58d995686632f557e3187d0b2f84bf276 Mon Sep 17 00:00:00 2001
From: Andreas Jansson <andreas.s.t.jansson@gmail.com>
Date: Mon, 27 Aug 2012 09:55:56 +0100
Subject: [PATCH] working dreiklangs

---
 inspect                 |  4 ++--
 keydetection/audio.py   |  2 +-
 keydetection/chroma.py  | 10 +++++-----
 keydetection/nklang.py  | 16 ++++++++--------
 keydetection/profile.py | 15 ++++++++++-----
 5 files changed, 26 insertions(+), 21 deletions(-)

diff --git a/inspect b/inspect
index fc2d2c7..b35e212 100755
--- a/inspect
+++ b/inspect
@@ -6,9 +6,9 @@ import pickle
 from keydetection import *
 
 def summarise(model, limit = None):
-    print 'C major matrix:'
+    print 'C major profile:'
     model[0].print_summary(limit)
-    print '\nC minor matrix:'
+    print '\nC minor profile:'
     model[12].print_summary(limit)
 
 if __name__ == '__main__':
diff --git a/keydetection/audio.py b/keydetection/audio.py
index 64ca4ca..a80955b 100644
--- a/keydetection/audio.py
+++ b/keydetection/audio.py
@@ -220,7 +220,7 @@ def get_klangs(mp3 = None, audio = None, time_limit = None, n = 2):
     tuner = Tuner(bins, global_tuning = True)
     ts = tuner.tune(cs)
 
-    logging.debug('Returning klags')
+    logging.debug('Returning klangs')
     klangs = [(i * winlength / float(fs), t.get_nklang(n = n)) for i, t in enumerate(ts)]
     return klangs
 
diff --git a/keydetection/chroma.py b/keydetection/chroma.py
index e698949..53d8ba2 100644
--- a/keydetection/chroma.py
+++ b/keydetection/chroma.py
@@ -88,13 +88,13 @@ def get_nklang(self, threshold = .1, silent = 100, n = 2, filter_adjacent = True
         if filter_adjacent:
             note_amps.sort(key = operator.itemgetter(1))
             all_amps = [0] * 12
-            for n, a in note_amps:
-                all_amps[n] = a
+            for note, a in note_amps:
+                all_amps[note] = a
 
             notes = []
-            for n, a in note_amps:
-                if all_amps[(n - 1) % 12] < a and all_amps[(n + 1) % 12] < a:
-                    notes.append(n)
+            for note, a in note_amps:
+                if all_amps[(note - 1) % 12] < a and all_amps[(note + 1) % 12] < a:
+                    notes.append(note)
 
         else:
             notes = map(operator.itemgetter(0), note_amps)
diff --git a/keydetection/nklang.py b/keydetection/nklang.py
index 78023f6..786c303 100644
--- a/keydetection/nklang.py
+++ b/keydetection/nklang.py
@@ -66,17 +66,17 @@ def __repr__(self):
 
 
 
-def klang_number_to_name(number):
+def klang_number_to_name(number, n):
     '''
-    Helper that returns the name of a Zweiklang.
+    Helper that returns the name of an nklang.
     '''
     if number == -1:
         return 'Silence'
     else:
-        first = number % 12
-        second = int(math.floor(number / 12))
-        if first == second:
-            return note_names[first]
-        else:
-            return note_names[first] + ', ' + note_names[second]
 
+        names = []
+        for i in range(n):
+            names.append('%-2s' % note_names[number % 12])
+            number /= 12
+
+        return ', '.join(names)
diff --git a/keydetection/profile.py b/keydetection/profile.py
index 3da8a1c..770304a 100644
--- a/keydetection/profile.py
+++ b/keydetection/profile.py
@@ -20,6 +20,7 @@ def __init__(self, length = None):
     def from_values(values):
         profile = Profile()
         profile.values = values
+        print len(values)
         profile.length = len(values)
         return profile
 
@@ -52,19 +53,23 @@ def normalise(self):
         if sum > 0:
             self.values /= sum
 
+    def get_n(self):
+        return int(math.log(len(self.values), 12))
+
     def __repr__(self):
         return '<Profile length %s, sum %f>' % (self.length, np.sum(self.values))
 
     def print_summary(self, max_lines = 20):
         seq = copy(self.values)
         seq.sort()
-        seq = np.unique(values)[::-1]
+        seq = np.unique(seq)[::-1]
         i = 0
         lines = 0
+        n = self.get_n()
         while(seq[i] > 0 and i < len(seq)):
             where = np.where(seq[i] == self.values)[0]
             for index in where:
-                print '%-6s: %.3f' % (klang_number_to_name(index), seq[i])
+                print '%-6s: %.3f' % (klang_number_to_name(index, n), seq[i])
                 lines += 1
                 if lines > max_lines:
                     return
@@ -91,7 +96,7 @@ def get_trained_model(filenames, n = 2):
     profiles_list = []
     for mp3, keylab_file in filenames:
         logging.info('Analysing %s' % mp3)
-        profiles = get_training_profiles(mp3, keylab_file)
+        profiles = get_training_profiles(mp3, keylab_file, n)
         if profiles:
             logging.debug('Appending profiles')
             profiles_list.append(profiles)
@@ -119,7 +124,7 @@ def get_training_profiles(mp3, keylab_file, n = 2):
 
         try:
             logging.debug('About to get klangs')
-            klangs = get_klangs(mp3)
+            klangs = get_klangs(mp3, n = n)
         except Exception, e:
             logging.warning('Failed to analyse %s: %s' % (mp3, e))
             return None
@@ -159,7 +164,7 @@ def get_test_profile(mp3, time_limit = None, n = 2):
     if cache.exists():
         return cache.get()
 
-    klangs = get_klangs(mp3, time_limit = time_limit)
+    klangs = get_klangs(mp3, time_limit = time_limit, n = n)
     profile = Profile(12 ** n)
     for t, klang in klangs:
         if klang is not None and \