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I've been trying to write nice snippet of code to simulate pi estimation by randomly throwing darts on a dartboard. While running the following code on high but reasonable numbers my mac doesn't plot.

When looking at it I don't find the source of such a high complexity.

I checked similar questions like this but haven't been able to find straightforward answer.

My guess is that the line plotting real pi is computationally intense - but that's just a hunch.

I'd also appreciate any comment regarding style / efficiency.

import numpy as np
import random
import math
from matplotlib import pyplot as plt
def estimatePi(r,w,h,N):
 center = (w/2.0,h/2.0)
 in_circle = 0
 for i in range(N):
 x = random.uniform(0.0,w)
 y = random.uniform(0.0,h)
 distance = math.sqrt((x-center[0])**2+(y-center[1])**2)
 if distance <= r:
 in_circle += 1
 outOfCircle=N-in_circle
 ratio = float(in_circle)/N
 #ratio = ((r**2)*pi)/(w*h) // *(w*h)
 #ratio*(w*h) = ((r**2)*pi) // : r**2
 pi = ratio*(w*h)/(r**2)
 return pi
#run, aggregate results:
PiEstimation=[]
num_darts=[]
loopcount = 1000001
i=10000
while i <loopcount:
 result=estimatePi(3,10,10,i)
 num_darts.append(i)
 PiEstimation.append(result)
 i += 15000
# plot:
plt.title('Estimating the Value of Pi - Dartboard Simulation')
plt.plot([0,100000000], [3.14,3.14], 'k-',color="red", linewidth=2.0)
plt.ylabel('Pi Estimation')
plt.xlabel('Number of Darts')
plt.errorbar(num_darts,PiEstimation, yerr=.0001,ecolor='magenta')
plt.show('hold')

I've been trying to write nice snippet of code to simulate pi estimation by randomly throwing darts on a dartboard. While running the following code on high but reasonable numbers my mac doesn't plot.

When looking at it I don't find the source of such a high complexity.

I checked similar questions like this but haven't been able to find straightforward answer.

My guess is that the line plotting real pi is computationally intense - but that's just a hunch.

I'd also appreciate any comment regarding style / efficiency.

import numpy as np
import random
import math
from matplotlib import pyplot as plt
def estimatePi(r,w,h,N):
 center = (w/2.0,h/2.0)
 in_circle = 0
 for i in range(N):
 x = random.uniform(0.0,w)
 y = random.uniform(0.0,h)
 distance = math.sqrt((x-center[0])**2+(y-center[1])**2)
 if distance <= r:
 in_circle += 1
 outOfCircle=N-in_circle
 ratio = float(in_circle)/N
 #ratio = ((r**2)*pi)/(w*h) // *(w*h)
 #ratio*(w*h) = ((r**2)*pi) // : r**2
 pi = ratio*(w*h)/(r**2)
 return pi
#run, aggregate results:
PiEstimation=[]
num_darts=[]
loopcount = 1000001
i=10000
while i <loopcount:
 result=estimatePi(3,10,10,i)
 num_darts.append(i)
 PiEstimation.append(result)
 i += 15000
# plot:
plt.title('Estimating the Value of Pi - Dartboard Simulation')
plt.plot([0,100000000], [3.14,3.14], 'k-',color="red", linewidth=2.0)
plt.ylabel('Pi Estimation')
plt.xlabel('Number of Darts')
plt.errorbar(num_darts,PiEstimation, yerr=.0001,ecolor='magenta')
plt.show('hold')

I've been trying to write nice snippet of code to simulate pi estimation by randomly throwing darts on a dartboard. While running the following code on high but reasonable numbers my mac doesn't plot.

When looking at it I don't find the source of such a high complexity.

I checked similar questions like this but haven't been able to find straightforward answer.

My guess is that the line plotting real pi is computationally intense - but that's just a hunch.

I'd also appreciate any comment regarding style / efficiency. import numpy as np import random import math from matplotlib import pyplot as plt

def estimatePi(r,w,h,N):
 center = (w/2.0,h/2.0)
 in_circle = 0
 for i in range(N):
 x = random.uniform(0.0,w)
 y = random.uniform(0.0,h)
 distance = math.sqrt((x-center[0])**2+(y-center[1])**2)
 if distance <= r:
 in_circle += 1
 outOfCircle=N-in_circle
 ratio = float(in_circle)/N
 #ratio = ((r**2)*pi)/(w*h) // *(w*h)
 #ratio*(w*h) = ((r**2)*pi) // : r**2
 pi = ratio*(w*h)/(r**2)
 return pi
#run, aggregate results:
PiEstimation=[]
num_darts=[]
loopcount = 1000001
i=10000
while i <loopcount:
 result=estimatePi(3,10,10,i)
 num_darts.append(i)
 PiEstimation.append(result)
 i += 15000
# plot:
plt.title('Estimating the Value of Pi - Dartboard Simulation')
plt.plot([0,100000000], [3.14,3.14], 'k-',color="red", linewidth=2.0)
plt.ylabel('Pi Estimation')
plt.xlabel('Number of Darts')
plt.errorbar(num_darts,PiEstimation, yerr=.0001,ecolor='magenta')
plt.show('hold')

I've been trying to write nice snippet of code to simulate pi estimation by randomly throwing darts on a dartboard. While running the following code on high but reasonable numbers my mac doesn't plot.

When looking at it I don't find the source of such a high complexity.

I checked similar questions like this but haven't been able to find straightforward answer.

My guess is that the line plotting real pi is computationally intense - but that's just a hunch.

I'd also appreciate any comment regarding style / efficiency.

import numpy as np
import random
import math
from matplotlib import pyplot as plt
def estimatePi(r,w,h,N):
 center = (w/2.0,h/2.0)
 in_circle = 0
 for i in range(N):
 x = random.uniform(0.0,w)
 y = random.uniform(0.0,h)
 distance = math.sqrt((x-center[0])**2+(y-center[1])**2)
 if distance <= r:
 in_circle += 1
 outOfCircle=N-in_circle
 ratio = float(in_circle)/N
 #ratio = ((r**2)*pi)/(w*h) // *(w*h)
 #ratio*(w*h) = ((r**2)*pi) // : r**2
 pi = ratio*(w*h)/(r**2)
 return pi
#run, aggregate results:
PiEstimation=[]
num_darts=[]
loopcount = 1000001
i=10000
while i <loopcount:
 result=estimatePi(3,10,10,i)
 num_darts.append(i)
 PiEstimation.append(result)
 i += 15000
# plot:
plt.title('Estimating the Value of Pi - Dartboard Simulation')
plt.plot([0,100000000], [3.14,3.14], 'k-',color="red", linewidth=2.0)
plt.ylabel('Pi Estimation')
plt.xlabel('Number of Darts')
plt.errorbar(num_darts,PiEstimation, yerr=.0001,ecolor='magenta')
plt.show('hold')