<span>In describing an Initialization is when a value is assigned to a variable as part of the variable's definition or the assinged values to variables are defined whenever.
The best answer would be is that they present the keyword, when they tell the compiler.</span>
Answer:The original choice to write apply_fg so that it accepts function arguments is a good one, because it increases interoperability. When the callable arguments to apply_fg use a single protocol, we can easily exchange them: #include <functional> float log2(float); int a = apply_fg(5.Of, int b = apply_fg(3.14f,
Explanation:
Google docs and save it there. hope this helps. thanks
Answer:
Option d (Auto Size) is the correct answer.
Explanation:
In a C# programming language, when a user needs to create a Windows Forms Label, then he needs to specify the property of label that how the label will look like and where the label fits and what is the size of that label. Following are the property which has a different meaning and a user need to specify when he creates a label--
- Fit states that the label to fix in the size.
- Text align states that the item of the toolbar is fixed in the center.
- The Middle center states that the item is fixed in the middle.
- Auto Size helps that the size of the control can be automatically resized.
The above question asked about that property which is used to automatically resize the control. So the answer is Auto size which is described above. Hence Option d is the correct answer while the other is not because--
- Option a state about 'Fit' property which is used to fix the label size.
- Option b states about 'Text align' property which is used to fix items of the toolbar in the center.
- Option c states about 'Middle center' property which is used to fix the item in the middle.
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.
