Answer:
import numpy as np
import matplotlib.pyplot as plt
def calculate_pi(x,y):
points_in_circle=0
for i in range(len(x)):
if np.sqrt(x[i]**2+y[i]**2)<=1:
points_in_circle+=1
pi_value=4*points_in_circle/len(x)
return pi_value
length=np.power(10,6)
x=np.random.rand(length)
y=np.random.rand(length)
pi=np.zeros(7)
sample_size=np.zeros(7)
for i in range(len(pi)):
xs=x[:np.power(10,i)]
ys=y[:np.power(10,i)]
sample_size[i]=len(xs)
pi_value=calculate_pi(xs,ys)
pi[i]=pi_value
print("The value of pi at different sample size is")
print(pi)
plt.plot(sample_size,np.abs(pi-np.pi))
plt.xscale('log')
plt.yscale('log')
plt.xlabel('sample size')
plt.ylabel('absolute error')
plt.title('Error Vs Sample Size')
plt.show()
Explanation:
The python program gets the sample size of circles and the areas and returns a plot of one against the other as a line plot. The numpy package is used to mathematically create the circle samples as a series of random numbers while matplotlib's pyplot is used to plot for the visual statistics of the features of the samples.
There’s no solution to the equation
Explanation:
This transient state occurs due to the fact that the signal change from low to high and high to low doesn't occur intermediately but in a very small time, in relation to the signal time itself.
At transistor level there are parasitic (undesired) capacitances and resistances, formed due to the layout configuration of conductor and dielectrics. As consequence a RC circuit is formed, thus making a propagation delay.
This delay must be characterized for each circuit, and specified as tpHL (transition time from High to Low) and tpLH (transition time from Low to High)
Answer: i really don’t know
Explanation:
Answer:
B. <u>Title</u><u> </u><u>slide</u><u> </u>layout is the default PowerPoint standard layout.