In [1]:
%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
In [2]:
# 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)
Out[2]:
[<matplotlib.lines.Line2D at 0x11c2de1f0>]
In [3]:
# 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)
Out[3]:
[<matplotlib.lines.Line2D at 0x11cdf37f0>]
In [ ]: