Visualizes pre-filtered and filtered data #aits

gaussian_convolution.py

# columns in the data that you want to visualize (visualize each column's value along the rows, where the row number is the x-axis)
VISUALIZED_COLUMNS = [0, -1, -2, -3, -4]

# show visualization of data, change to only one column (second argument) if only want to visualize current set of data instead of contrasting pre- vs post-filtering
fig, axs = plt.subplots(len(VISUALIZED_COLUMNS), 2)

for i, column in enumerate(VISUALIZED_COLUMNS):
    old_data = data[:, column]
    # plot pre-filtered data
    axs[i, 0].plot(range(len(data)), old_data)
    # convolved_data is the data that has been filtered
    filtered_data = convolved_data[:, column]
    axs[i, 1].plot(range(len(data)), filtered_data)

axs[0, 0].set_title("Original data")
axs[0, 1].set_title("Filtered data")