Matplotlib

Digital Signal Processing

Python

Numpy

Generation of elementary signal in python

We will be using matplotlib for visualization purposes .

Basics of matplotlib

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plot() — Plots continuous waveform provided x,y values . Some optional arguments are color,linestyle,linewidth etc.

stem() — Plots continuous waveform provided x,y values .

legend() used to specify legends of the plot

xlabel() , ylabel() for specifying x and y axis name.

title() — used to specify plot name

grid() — Given True as parameter turns on the grid

show() — shows the plot

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Delta function

from matplotlib import pyplot as plt
plt.style.use('ggplot')
xval = [x for x in range(-100,100)]
yval=[]
for t in range(-100,100):
           if t==0:
              yval.append(1)
           else:
              yval.append(0)
plt.plot(xval,yval,label="delta function")
plt.xlabel("time")
plt.ylabel("Amplitude")
plt.grid(True)
plt.legend()
plt.show()

Delta function

Step function

from matplotlib import pyplot as plt
plt.style.use('ggplot')
x_val = [x for x in range(-100,100)]
y_val =[]
for x in x_val:
      if x>=0:
         y_val.append(1)
      else:
         y_val.append(0)
plt.plot(x_val,y_val,color='g',label="Step signal")
plt.legend()
plt.title("step signal")
plt.xlabel('time')
plt.ylabel('amp')
plt.show()

Step Function

Signum Function

from matplotlib import pyplot as plt
plt.style.use('ggplot')
x_val = [x for x in range(-50,50)]
y_val=[]
for x in x_val:
      if x>=0:
         y_val.append(1)
      else:
         y_val.append(-1)
plt.stem(x_val,y_val,label="signum function")
plt.legend()
plt.title("Signum Function")
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.show()

Signum Function

Sine Function

from matplotlib import pyplot as plt
import numpy as np
plt.style.use('ggplot')
x_val = np.arange(-np.pi,np.pi,0.5)
y_val = [np.sin(x) for x in x_val]
plt.plot(x_val,y_val,color='g',label="sine wave")
plt.legend()
plt.title("Sine wave")
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.show()

Sine wave

Cos Function

from matplotlib import pyplot as plt
import numpy as np
plt.style.use('ggplot')
x_val = np.arange(0,4*np.pi,0.5)
y_val = [np.cos(i) for i in x_val]
plt.plot(x_val,y_val,label="cos wave")
plt.legend()
plt.title("Cos wave")
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.grid(True)
plt.tight_layout()
plt.show()

cosine

Ramp Function

from matplotlib import pyplot as plt
plt.style.use('ggplot')
x_val = [x for x in range(-10,100)]
y_val=[]
t=0
for x in x_val:
      if x>=0:
         y_val.append(t*1)
         t+=1
     else:
         y_val.append(0)
plt.plot(x_val,y_val,label="Ramp signal")
plt.legend()
plt.xlabel("Amplitude")
plt.ylabel("Time")
plt.title("Ramp signal")
plt.show()