Answer and Explanation:
Using Javascript:
Class Dog{
var healthScores=[];
Constructor(name, age, ...healthScores) {this.name=name;
this.age=age;
this.healthsScores=healthScores;
}
checkObject(new Dog){
If(new Dog.name===this.name,new Dog.age===this.age, new Dog.healthScores===this.healthScores){return true;
}
else{
console.log("objects are not equal");
}
}
}
To call the method checkObject:
var Tesa = new Dog(Tes,1,[45,46,82]);
var Bingo = new Dog(bing,2,[43,46,82]);
Bingo.checkObject(Tesa);
Note: we have used ES6(latest version of Javascript) where we passed the healthScore parameter(which is an array) to our constructor using the spread operator.
Answer:
The two best options can be processors like inlet i7 4.0 GHZ 8th generation processor, and two popular models are core and Pentium for inlet. Similarly for AMD we have 4 GHZ 8 core AMD processors. And two very popular examples are Athlon and Phenom.
You need to check the Graphics, clock speed etc. as well to end up with the best processor. Also make sure that it is motherboard compatible, and to the motherboard that you are having, If number of core is more and frequency is high, it means Processor is better, and same thing applies for generations as well.
Explanation:
The answer is self explanatory.
That would be great if it was possible
Answer:
The answer is "Option b".
Explanation:
This is the book of the liturgical manuscript for the catholic churches, which is the four Scriptural texts now in Cambridge, Dublin, and Ireland. It is the job, which is known for the sophistication, accuracy, and elegance of that same paintings in the Classically illustrated scripts. It was been built between 800 AD by Celtic monks to build vellum 185 calves had been killed, and the incorrect option can be defined as follows:
- In option a, This book is not used in the printing press.
- In option c, This book is used in the liturgical manuscript.
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.
