%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import display, Image
import matplotlib.image as mpimg
from os.path import dirname, join as pjoin
import scipy.io as sio
# Simulate some sinusoidal signal, and plot
N = 10001
xmax = 5
x = np.linspace(-xmax,xmax,N)
s = np.cos(2*np.pi*x)
plt.figure(figsize=(20,10))
font = {'family' : 'arial',
'weight' : 'normal',
'size' : 26}
plt.rc('font', **font)
plt.plot(x,s,'gray',linewidth=6.0)
[<matplotlib.lines.Line2D at 0x11c2de1f0>]
# Sample our signal
dx = 0.7
x2 = np.arange(-xmax,xmax,dx)
s2 = np.cos(2*np.pi*x2)
plt.figure(figsize=(20,10))
font = {'family' : 'arial',
'weight' : 'normal',
'size' : 26}
plt.rc('font', **font)
plt.plot(x,s,'lightgray')
plt.plot(x2,s2,'ro',markersize=14)
[<matplotlib.lines.Line2D at 0x11cdf37f0>]