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import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
def split_title_line(title_text, max_words=5):
"""
A function that splits any string based on specific character
(returning it with the string), with maximum number of words on it
"""
seq = title_text.split()
return "\n".join([" ".join(seq[i:i + max_words]) for i in range(0, len(seq), max_words)])
def plot_alignment(alignment, path, title=None, split_title=False, max_len=None):
if max_len is not None:
alignment = alignment[:, :max_len]
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot(111)
im = ax.imshow(
alignment,
aspect="auto",
origin="lower",
interpolation="none")
fig.colorbar(im, ax=ax)
xlabel = "Decoder timestep"
if split_title:
title = split_title_line(title)
plt.xlabel(xlabel)
plt.title(title)
plt.ylabel("Encoder timestep")
plt.tight_layout()
plt.savefig(path, format="png")
plt.close()
def plot_spectrogram(pred_spectrogram, path, title=None, split_title=False, target_spectrogram=None, max_len=None, auto_aspect=False):
if max_len is not None:
target_spectrogram = target_spectrogram[:max_len]
pred_spectrogram = pred_spectrogram[:max_len]
if split_title:
title = split_title_line(title)
fig = plt.figure(figsize=(10, 8))
# Set common labels
fig.text(0.5, 0.18, title, horizontalalignment="center", fontsize=16)
#target spectrogram subplot
if target_spectrogram is not None:
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312)
if auto_aspect:
im = ax1.imshow(np.rot90(target_spectrogram), aspect="auto", interpolation="none")
else:
im = ax1.imshow(np.rot90(target_spectrogram), interpolation="none")
ax1.set_title("Target Mel-Spectrogram")
fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax1)
ax2.set_title("Predicted Mel-Spectrogram")
else:
ax2 = fig.add_subplot(211)
if auto_aspect:
im = ax2.imshow(np.rot90(pred_spectrogram), aspect="auto", interpolation="none")
else:
im = ax2.imshow(np.rot90(pred_spectrogram), interpolation="none")
fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax2)
plt.tight_layout()
plt.savefig(path, format="png")
plt.close()
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