Using only numpy, is there a way to create a square wave?

Question

I have tried using masks and making lists like x = [0,0.5,0.51,1,1.01], y = [1,1,-1,-1,1] works ofcourse, but is quite tedious and not as nice as i want to make a square wave from x = 0 to 5.

Answer 1

You could write a little function like this to populate x and y

import matplotlib.pyplot as plt
import math

def SquareWave(high, low, start, end, width):
    print("Square Wave")
    ##Calculate how many cycles
    ncycles = int(math.ceil((end - start)/width)) #Round up
    print(ncycles)
    x=[]
    y=[]
    x.append(start)
    y.append(high)
    xstep = width / 2 
    for n in range(ncycles):
        start += xstep #Increment by the step width
        x.append(start)
        y.append(high)
        x.append(start)
        y.append(low)
        start += xstep #Increment by the step width
        x.append(start)
        y.append(low)
        x.append(start)
        y.append(high)
    return(x,y)
        
        

x,y = SquareWave(1,-1, 0, 5, 1)

plt.plot(x,y)

Answer 2

: General Solution :

import matplotlib.pyplot as plot 
import numpy as np 

def sq(x, y):
    
    mindiff = min([x[i+1]-x[i] for i in range(4)])
    up_x = np.arange(x[0], x[-1], mindiff)
    up_y = list(map(lambda i: y[sum(i > x)], up_x))
    print(up_y)
    plot.plot(up_x, up_y)
    plot.show()

x = [0,0.5,0.51,1,1.01]
y = [1,1,-1,-1,1] 
sq(x, y)

---

:Specific to you Code :

import matplotlib.pyplot as plot 
import numpy as np 
  
up_t = list(np.linspace(x[0], x[1], 100)) + list([0.5])+list([0.51])+list(np.linspace(x[2], x[3], 100)) + list([1.01])
up_y = [1 for i in range(100)] + [1, -1]+ [-1 for i in range(100)] + [1]

t = np.array(up_t)
plot.plot(up_t, up_y)
plot.show()