Add plot labels

plotter.py

@@ -14,35 +14,49 @@ dct_g = np.array([-0.000851391, 0.812182, 0.000717756, 0.809907, 0.000900241, 0.
 if __name__ == "__main__":
     # Part (a)
     plt.plot(sample_times, sample_values)
+    plt.title("Original Samples")
+    plt.xlabel('time (s)')
     plt.savefig("fig_a.png")
     plt.close()
 
     # Part (b)
     plt.plot(np.arange(len(dct)), dct)
+    plt.title("DCT")
+    plt.xlabel("sample number")
     plt.savefig("fig_b.png")
     plt.close()
 
     # Part (c)
     plt.plot(sample_times, recovered_sample_values)
+    plt.title("Recovered Samples")
+    plt.xlabel('time (s)')
     plt.savefig("fig_c.png")
     plt.close()
 
     # Part (d)
     plt.plot(subset_sample_times, subset_sample_values)
+    plt.title("Sample Subset")
+    plt.xlabel('time (s)')
     plt.savefig("fig_d.png")
     plt.close()
 
     # Part (e)
     plt.plot(np.arange(len(dct)), dct_e)
+    plt.title("Recovered DCT (Unregularized)")
+    plt.xlabel("sample number")
     plt.savefig("fig_e.png")
     plt.close()
 
     # Part (f)
     plt.plot(np.arange(len(dct)), dct_f)
+    plt.title("Recovered DCT (L2 Regularized)")
+    plt.xlabel("sample number")
     plt.savefig("fig_f.png")
     plt.close()
 
     # Part (g)
     plt.plot(np.arange(len(dct)), dct_g)
+    plt.title("Recovered DCT (L1 Regularized)")
+    plt.xlabel("sample number")
     plt.savefig("fig_g.png")
     plt.close()