import numpy as np
import matplotlib.pyplot as plt
from linproc import linearProcess
from estspec import periodogram
## Data
n = 400
phi = 0.5
theta = 0, -0.8
lp = linearProcess(phi, theta)
X = lp.simulation(ts_length=n)
fig, ax = plt.subplots(3, 1)
for i, wl in enumerate((15, 55, 175)): # window lengths
x, y = periodogram(X)
ax[i].plot(x, y, 'b-', lw=2, alpha=0.5, label='periodogram')
x_sd, y_sd = lp.spectral_density(two_pi=False, resolution=120)
ax[i].plot(x_sd, y_sd, 'r-', lw=2, alpha=0.8, label='spectral density')
x, y_smoothed = periodogram(X, window='hamming', window_len=wl)
ax[i].plot(x, y_smoothed, 'k-', lw=2, label='smoothed periodogram')
ax[i].legend()
ax[i].set_title('window length = {}'.format(wl))
fig.show()
import numpy as np
import matplotlib.pyplot as plt
from linproc import linearProcess
from estspec import periodogram
## Data
n = 400
phi = 0.5
theta = 0, -0.8
lp = linearProcess(phi, theta)
X = lp.simulation(ts_length=n)
fig, ax = plt.subplots(3, 1)
for i, wl in enumerate((15, 55, 175)): # window lengths
x, y = periodogram(X)
ax[i].plot(x, y, 'b-', lw=2, alpha=0.5, label='periodogram')
x_sd, y_sd = lp.spectral_density(two_pi=False, resolution=120)
ax[i].plot(x_sd, y_sd, 'r-', lw=2, alpha=0.8, label='spectral density')
x, y_smoothed = periodogram(X, window='hamming', window_len=wl)
ax[i].plot(x, y_smoothed, 'k-', lw=2, label='smoothed periodogram')
ax[i].legend()
ax[i].set_title('window length = {}'.format(wl))
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from linproc import linearProcess
import estspec
lp = linearProcess(-0.9)
wl = 65
fig, ax = plt.subplots(3, 1)
for i in range(3):
X = lp.simulation(ts_length=150)
ax[i].set_xlim(0, np.pi)
x_sd, y_sd = lp.spectral_density(two_pi=False, resolution=180)
ax[i].semilogy(x_sd,
y_sd,
'r-',
lw=2,
alpha=0.75,
label='spectral density')
x, y_smoothed = estspec.periodogram(X, window='hamming', window_len=wl)
ax[i].semilogy(x,
y_smoothed,
'k-',
lw=2,
alpha=0.75,
label='standard smoothed periodogram')
x, y_ar = estspec.ar_periodogram(X, window='hamming', window_len=wl)
import numpy as np
import matplotlib.pyplot as plt
from linproc import linearProcess
import estspec
lp = linearProcess(-0.9)
wl = 65
fig, ax = plt.subplots(3, 1)
for i in range(3):
X = lp.simulation(ts_length=150)
ax[i].set_xlim(0, np.pi)
x_sd, y_sd = lp.spectral_density(two_pi=False, resolution=180)
ax[i].semilogy(x_sd, y_sd, 'r-', lw=2, alpha=0.75, label='spectral density')
x, y_smoothed = estspec.periodogram(X, window='hamming', window_len=wl)
ax[i].semilogy(x, y_smoothed, 'k-', lw=2, alpha=0.75, label='standard smoothed periodogram')
x, y_ar = estspec.ar_periodogram(X, window='hamming', window_len=wl)
ax[i].semilogy(x, y_ar, 'b-', lw=2, alpha=0.75, label='AR smoothed periodogram')
ax[i].legend(loc='upper left')
fig.show()
