Fix plot_validation_ts_ae function from the module visualization about deepvats

[vrodriguezf]

In GitLab by @lgs on Oct 29, 2020, 10:59

I have updated the function to the one shown below:

def plot_validation_ts_ae(prediction:np.array, original:np.array,fig_size = (15,15),anchor = (0, 0.85),window_num = 0):
    # Create the figure
    fig = plt.figure(figsize=(fig_size[0],fig_size[1]))
    # Create the subplot axes
    axes = fig.subplots(nrows=original.shape[2], ncols=1)
    # We iterate over the sensor data and plot both the original and the prediction
    for i,ax in zip(range(original.shape[2]),fig.axes):
        ax.plot(original[window_num,:,i], label='Original Data')
        ax.plot(prediction[window_num,:,i], label='Prediction')
    # Handle the legend configuration and position
    lines, labels = fig.axes[-1].get_legend_handles_labels()
    fig.legend(lines, labels,bbox_to_anchor=(anchor[0], anchor[1]),loc='upper left')
    return fig

[vrodriguezf]

In GitLab by @lgs on Oct 29, 2020, 11:14

mentioned in commit 4e1546a

[vrodriguezf]

In GitLab by @lgs on Oct 29, 2020, 11:19

mentioned in merge request !13

[vrodriguezf]

In GitLab by @lgs on Oct 29, 2020, 11:21

mentioned in commit fdf596a