Visualisation tools

PyPeaks for Indian Art Music

Audio visualisation utils

compiam.visualisation.audio.plot_waveform(input_data, t1, t2, labels=None, input_sr=44100, sr=44100, output_path=None, verbose=False)

Plotting waveform between two given points with optional labels

Parameters:

• input_data – path to audio file or numpy array like audio signal

• input_sr – sampling rate of the input array of data (if any). This variable is only relevant if the input is an array of data instead of a filepath.

• t1 – starting point for plotting

• t2 – ending point for plotting

• labels – dictionary {time_stamp:label} to plot on top of waveform

• sr – sampling rate

• output_path – optional path (finished with .png) where the plot is saved

Training visualisation utils

compiam.visualisation.training.plot_losses(train_loss, val_loss, output_path)

Plotting loss curves

Parameters:

• train_loss – training loss curve

• val_loss – validation loss curve (same length as training curve)

• output_path – optional path (finished with .png) where the plot is saved