x = np.zeros(N) f = np.zeros(N) y_1 = np.zeros(N) y_2 = np.zeros(N) y_3 = np.zeros(N) y_4 = np.zeros(N) y_5 = np.zeros(N) for i in range(N): x[i] = i*dx f[i] = i y_1[i] = np.sin(x[i]) + np.sin(b[0]*x[i]) y_2[i] = np.sin(x[i]) + np.sin(b[1]*x[i]) y_3[i] = np.sin(x[i]) + np.sin(b[2]*x[i]) y_4[i] = np.sin(x[i]) + np.sin(b[3]*x[i]) y_5[i] = np.sin(x[i]) + np.sin(b[4]*x[i]) y_1 = fft.fft_slow(y_1,1.) fft.plot_c(f[:0.5*N],y_1[:N]) y_2 = fft.fft_slow(y_2,1.) fft.plot_c(f[:0.5*N],y_2[:N]) y_3 = fft.fft_slow(y_3,1.) fft.plot_c(f[:0.5*N],y_3[:N]) y_4 = fft.fft_slow(y_4,1.) fft.plot_c(f[:0.5*N],y_4[:N]) y_5 = fft.fft_slow(y_5,1.) fft.plot_c(f[:0.5*N],y_5[:N]) #At the different spectra, the peaks moved to the higher frequencies until #they reached b=39.
>>>>>>> 4893a7473d87cb59df0e6ce3c53da80767f9135d x = np.zeros(N) f = np.zeros(N) y = np.zeros(2*N) for i in range(N): <<<<<<< HEAD x[i] = i * dx ======= x[i] = i*dx >>>>>>> 4893a7473d87cb59df0e6ce3c53da80767f9135d f[i] = i y[2*i] = np.sin(x[i]) + np.sin(4.*x[i]) y[2*i+1] = 0 fft.plot_c(x,y) y = fft.fft_slow(y,1.) <<<<<<< HEAD fft.plot_c(f[:0.5*N],y)[:N] plt.show() ======= fft.plot_c(f[:0.5*N],y[:N]) y = fft.fft_slow(y,-1.) fft.plot_c(x,y) #plt.plot(x,y) plt.show() >>>>>>> 4893a7473d87cb59df0e6ce3c53da80767f9135d
g1[2 * i] = 1
k = k + 1
elif x1[i] >= 0.4 and x1[i] <= 0.6:
h1[2 * i] = 1
l = l + 1
for i in range(N1):
g1[i] = g1[i] / k
h1[i] = h1[i] / l
for j in range(N2):
x2[j] = j * dx2
if x2[j] <= 0.1:
g2[2 * j] = 1
m = m + 1
elif x2[j] >= 0.4 and x2[j] <= 0.6:
h2[2 * j] = 1
n = n + 1
for j in range(N2):
g2[j] = g2[j] / m
h2[j] = h2[j] / n
corr1 = correlation(g1, h1)
corr2 = correlation(g2, h2)
fft.plot_c(x1, g1)
fft.plot_c(x1, h1)
fft.plot_c(x1, corr1)
fft.plot_c(x2, g2)
fft.plot_c(x2, h2)
fft.plot_c(x2, corr2)
g1[2 * i] = 1
k = k + 1
elif x1[i] >= 0.4 and x1[i] <= 0.6:
h1[2 * i] = 1
l = l + 1
for i in range(N1):
g1[i] = g1[i] / k
h1[i] = h1[i] / l
for j in range(N2):
x2[j] = j * dx2
if x2[j] <= 0.1:
g2[2 * j] = 1
m = m + 1
elif x2[j] >= 0.4 and x2[j] <= 0.6:
h2[2 * j] = 1
n = n + 1
for j in range(N2):
g2[j] = g2[j] / m
h2[j] = h2[j] / n
corr1 = correlation(g1, h1)
corr2 = correlation(g2, h2)
fft.plot_c(x1, g1)
fft.plot_c(x1, h1)
fft.plot_c(x1, corr1)
fft.plot_c(x2, g2)
fft.plot_c(x2, h2)
fft.plot_c(x2, corr2)
#!/usr/bin/env python
import fft
import numpy as np
import matplotlib.pyplot as plt
import time
PI = 2 * np.arcsin(1)
N = 64
L = 2 * PI
dx = L / (N - 1)
x = np.zeros(N)
f = np.zeros(N)
y = np.zeros(2 * N)
for i in range(N):
x[i] = i * dx
f[i] = i
y[2 * i] = np.sin(x[i]) + np.sin(4. * x[i])
y[2 * i + 1] = 0
fft.plot_c(x, y)
y = fft.fft_slow(y, 1.)
fft.plot_c(f[:0.5 * N], y[:N])
y = fft.fft_slow(y, -1.)
fft.plot_c(x, y)
#plt.plot(x,y)
plt.show()
#!/usr/bin/env python import fft import numpy as np import matplotlib.pyplot as plt import time b=np.array([4,13,28,39,50]) n=len(b) for j in range(n): PI = 2*np.arcsin(1) N = 64 L = 2*PI dx = L / (N-1) x = np.zeros(N) f = np.zeros(N) y = np.zeros(2*N) for i in range(N): x[i] = i*dx f[i] = i y[2*i] = np.sin(x[i]) + np.sin(b[j]*x[i]) y[2*i+1] = 0 #fft.plot_c(x,y) y = fft.fft_slow(y,1.) fft.plot_c(f[:0.5*N],y[:N]) #plt.plot(x,y) plt.show()
import fft
import numpy as np
import matplotlib.pyplot as plt
import time
b = [4, 13, 28, 39, 50]
n = len(b)
PI = 2*np.arcsin(1)
N= 64
L = 2*PI
dx = L / (N-1)
x = np.zeros(N)
y = np.zeros(2*N)
f = np.zeros(N)
for j in range(n):
for i in range(N):
x[i] = i*dx
f[i] = i
y[2*i] = np.sin(x[i]) + np.sin(b[j]*x[i])
y[2*i+1] = 0
y = fft.fft_slow(y,1.)
plt.figure(j)
fft.plot_c(f[:.5*N],y[:N])
y = fft.fft_slow(y,-1.)
fft.plot_c(x,y)
plt.show()