GHpython
diff --git a/‎examples/scipy/FFT/cleaned.png‎
26.7 KB b/‎examples/scipy/FFT/cleaned.png‎
26.7 KB
diff --git a/‎examples/scipy/FFT/convolve.py‎
Lines changed: 26 additions & 0 deletions b/‎examples/scipy/FFT/convolve.py‎
Lines changed: 26 additions & 0 deletions
diff --git a/‎examples/scipy/FFT/gaussian.png‎
56.2 KB b/‎examples/scipy/FFT/gaussian.png‎
56.2 KB
diff --git a/‎examples/scipy/FFT/make_signal.py‎
Lines changed: 27 additions & 0 deletions b/‎examples/scipy/FFT/make_signal.py‎
Lines changed: 27 additions & 0 deletions
@@ -0,0 +1,26 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import signal
+
+def main():
+
+    data = np.loadtxt("signal.txt")
+
+    x = data[:,0]
+    sig = data[:,2]
+    orig = data[:,1]
+
+    N = len(x)
+
+    window = signal.gaussian(N, 20.0)
+    window /= np.sum(window)
+    clean = signal.convolve(sig, window, mode="same")
+
+    plt.plot(x, clean)
+    plt.plot(x, orig)
+    plt.savefig("cleaned.png")
+    
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,27 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+# make a signal that we will convolve
+
+def f(x, L):
+    A = L/10.0
+    return 2*np.sin(2*np.pi*x/L) + x*(L-x)**2/L**3 * np.cos(x) + 5*x*(L-x)/L**2 + A/2 + 0.1*A*np.sin(13*np.pi*x/L)
+
+
+N = 2048
+L = 50.0
+
+x = np.linspace(0, L, N, endpoint=False)
+f = f(x, L)
+fnew = f + 0.5*np.random.randn(N)
+
+with open("signal.txt", "w") as fo:
+    for n in range(N):
+        fo.write("{:20} {:20} {:20}\n".format(x[n], f[n], fnew[n]))
+
+plt.plot(x, f)
+plt.plot(x, fnew, zorder=-100)
+
+
+
+plt.savefig("test.png")