Plot prediction errors by key

deep-pitchs-errors-by-key.py

files = os.listdir("samples")
np.random.shuffle(files)

notes = ['A', 'As', 'B', 'C', 'Cs', 'D', 'Ds', 'E', 'F', 'Fs', 'G', 'Gs']
note_map = {}
for i, note_name in enumerate(notes):
  note_map[note_name] = i

count_by_key = np.zeros((8 * 12))
errors_by_key = np.zeros((8 * 12))

for i, file in enumerate(files[17000:18000]):
  predicted = deepears.predict("samples/"+file).flatten()[0]
  parts = DeepSamples.note_parts(file)

  octave = int(parts['octave'])
  note = parts['root']
  freq = parts['freq']
  error = abs(predicted - freq)

  count_by_key[(octave * 12) + note_map[note]] += 1
  errors_by_key[(octave * 12) + note_map[note]] += error
  # print(file, base, predicted, actual, error)

errors_by_key /= count_by_key