Answer:
The answer to this question defined below.
Explanation:
It's a smart idea to get a common language for coding of every kind. It would help all developers and customers understand the language better because, in every case, there's no more need to learn, that language.
- This could also render software developed in the very same language consistent, and therefore, ports on multiple platforms are not required.
- In this process, we talk about the common property and function of the classes, that's why it is the correct answer.
Cause weak ones aren't that strong and can easily break, but a strong connection will last longer and will be harder to break. For example you need to build a connection with your dog or else your dog wont trust you. Basically building a strong connection always you to build the trust stronger.... I think this is the answer you are looking for depending on what connection you are looking for
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.
The Appalachian Mountains
