Script to plot "rainbowgrams" from NSynth (https://arxiv.org/abs/1704.01279)

rainbowgram.py

import os

import librosa
import matplotlib
import matplotlib.pyplot as plt
matplotlib.rcParams['svg.fonttype'] = 'none'
import numpy as np
from scipy.io.wavfile import read as readwav

# Constants
n_fft = 512
hop_length = 256
SR = 16000
over_sample = 4
res_factor = 0.8
octaves = 6
notes_per_octave=10


# Plotting functions
cdict  = {'red':  ((0.0, 0.0, 0.0),
                   (1.0, 0.0, 0.0)),

         'green': ((0.0, 0.0, 0.0),
                   (1.0, 0.0, 0.0)),

         'blue':  ((0.0, 0.0, 0.0),
                   (1.0, 0.0, 0.0)),

         'alpha':  ((0.0, 1.0, 1.0),
                   (1.0, 0.0, 0.0))
        }

my_mask = matplotlib.colors.LinearSegmentedColormap('MyMask', cdict)
plt.register_cmap(cmap=my_mask)

def note_specgram(path, ax, peak=70.0, use_cqt=True):
  # Add several samples together
  if isinstance(path, list):
    for i, p in enumerate(path):
      sr, a = readwav(f)
      audio = a if i == 0 else a + audio
  # Load one sample
  else:    
      sr, audio = readwav(f)
  audio = audio.astype(np.float32)
  if use_cqt:
    C = librosa.cqt(audio, sr=sr, hop_length=hop_length, 
                      bins_per_octave=int(notes_per_octave*over_sample), 
                      n_bins=int(octaves * notes_per_octave * over_sample),
                      real=False, 
                      filter_scale=res_factor, 
                      fmin=librosa.note_to_hz('C2'))
  else:
    C = librosa.stft(audio, n_fft=n_fft, win_length=n_fft, hop_length=hop_length, center=True)
  mag, phase = librosa.core.magphase(C)
  phase_angle = np.angle(phase)
  phase_unwrapped = np.unwrap(phase_angle)
  dphase = phase_unwrapped[:, 1:] - phase_unwrapped[:, :-1]
  dphase = np.concatenate([phase_unwrapped[:, 0:1], dphase], axis=1) / np.pi
  mag = (librosa.logamplitude(mag**2, amin=1e-13, top_db=peak, ref_power=np.max) / peak) + 1
  ax.matshow(dphase[::-1, :], cmap=plt.cm.rainbow)
  ax.matshow(mag[::-1, :], cmap=my_mask)

    
def plot_notes(list_of_paths, rows=2, cols=4, col_labels=[], row_labels=[],
              use_cqt=True, peak=70.0):
  """Build a CQT rowsXcols.
  """
  column = 0
  N = len(list_of_paths)
  assert N == rows*cols
  fig, axes = plt.subplots(rows, cols, sharex=True, sharey=True)
  fig.subplots_adjust(left=0.1, right=0.9, wspace=0.05, hspace=0.1)
  
  #   fig = plt.figure(figsize=(18, N * 1.25))
  for i, path in enumerate(list_of_paths):
    row = i / cols
    col = i % cols
    if rows == 1:
      ax = axes[col]
    elif cols == 1:
      ax = axes[row]
    else:
      ax = axes[row, col]
    
    print row, col, path, ax, peak, use_cqt
    note_specgram(path, ax, peak, use_cqt)
    
    ax.set_axis_bgcolor('white')
    ax.set_xticks([]); ax.set_yticks([])
    if col == 0 and row_labels:
      ax.set_ylabel(row_labels[row])
    if row == rows-1 and col_labels:
      ax.set_xlabel(col_labels[col])

Need to change print statement on line 87 to
print(row, col, path, ax, peak, use_cqt)

Then librosa.cqt cmd in line 48 to
` C = librosa.cqt(audio, sr=sr, hop_length=hop_length,
fmin=librosa.note_to_hz('C2'),
n_bins=int(octaves * notes_per_octave * over_sample),
bins_per_octave=int(notes_per_octave*over_sample),
filter_scale=res_factor)

In line 61 : logamplitude does not exist anymore (replaced by amplitude_to_db)