Added first playground for windowing.

Author: Schuler Henry Martin (BhP/HRL3.2-SH1)

playground/windowing/main.py

@@ -0,0 +1,76 @@
+from pickle import FALSE
+import numpy as np
+import matplotlib.pyplot as plot
+
+# sin
+
+frequency = 30;
+frequency2 = 5;
+w = 2 * np.pi * frequency;
+w2 = 2 * np.pi * frequency2;
+time_interval = 1.8;
+samples= 800;
+time = np.linspace(0, time_interval, samples);
+amplitude = np.sin(w*time);
+amplitude += np.sin(w2*time);
+
+plot.plot(time, amplitude);
+plot.title("Sine wave");
+plot.xlabel("Time");
+plot.ylabel("Amplitude");
+plot.grid(True, which="both");
+plot.axhline(y=0, color="k");
+plot.show(block=False);
+
+# window
+
+newAmplitude = amplitude * np.hamming(samples)
+
+plot.plot(time, newAmplitude);
+plot.title("Sine wave");
+plot.xlabel("Time");
+plot.ylabel("Amplitude");
+plot.grid(True, which="both");
+plot.axhline(y=0, color="k");
+plot.show();
+
+plot.plot(time, np.hamming(samples))
+plot.show();
+
+# fft
+
+def fft(amp):
+  fourierTransform = np.fft.fft(amp)  / len(amp)
+  fourierTransform = fourierTransform[range(int(len(amp)/2))]
+
+  tpCount = len(amp)
+  values = np.arange(int(tpCount/2))
+  timePeriod = tpCount/(samples/time_interval)
+  frequencies = values/timePeriod
+
+  plot.plot(frequencies[:15], abs(fourierTransform)[:15])
+  plot.show(block=False)
+  
+def fft2(amp):
+  n = int(samples/time_interval)
+  freqs = np.fft.fftfreq(n)
+  mask = freqs > 0
+  fft_vals = np.fft.fft(amp)
+  fft_theo = 2.0*np.abs(fft_vals/n)
+  
+  plot.figure(1)
+  plot.title("OS")
+  plot.plot(time, amp, color="xkcd:salmon", label="original")
+  plot.legend()
+  
+  plot.figure(2)
+  plot.plot(freqs[mask]*260, fft_theo[:len(mask)][mask], "ro-", label="true fft values")
+  plot.title("True FFT values")
+  plot.show(block=False)
+  
+  
+# fft(amplitude);
+# fft(newAmplitude);
+fft2(amplitude);
+fft2(newAmplitude)
+plot.show()