LCM: #include<bits/stdc++.h> using namespace std; sets; int main() { int a,m,n=1000,c=0; int z[1000]; cout<<"Value of a = "; cin>>a; cout<<"Value of c = "; cin>>c; cout<<"Value of m = "; cin>>m; cout<<"Value of z0 = "; cin>>z[0]; cout<<endl; cout<<z[0]<<"\n"; s.insert(z[0]); ll cn=1; for(int i=1; ;i++) { z[i]=(az[i-1] + c)%m;//z[i]=(az[i-1]+c)%m;
s.insert(z[i]);
cn++;
if(cn>s.size())
break;
cout<<z[i];
cout<<"\n";
}
cout<<"Cycle length is:"<<s.size();
return 0;
}
- Document procesing #include<bits/stdc++.h> #define pb push_back
using namespace std; #define ll long long int
vectorv; vectorb; vectorst; vectorfi; vectorcm; int main() { ios::sync_with_stdio(0); cin.tie(0); cout.tie(0); ll a,n,i,j,ans,f,s,c; c=0,s=0; cout<<"Enter job number"<<endl; cin>>n; for(i=0; i<n; i++) {
cin>>a;
v.pb(a);
}
for(i=0; i<n; i++)
{
st.pb(s);
s+=v[i];
c+=v[i];
if(c>=60)
{
b.pb(1);
fi.pb(s);
s+=5;
cm.pb(c);
c=0;
}
else{
b.pb(0);
cm.pb(c);
fi.pb(s);
}
}
cout<<"JT "<<" ST"<<" WT "<<" FT "<<" CMT "<<" Break "<<endl;
for(i=0; i<n; i++)
{
cout<<i+1<<" "<<st[i]<<" "<<v[i]<<" "<<fi[i]<<" "<<cm[i]<<" "<<b[i]<<endl;
}
return 0;
}
- chi-squire test
#include<bits/stdc++.h> using namespace std; sets; float chi[100];
int main() { int a,m,n=1000,c=0; int z[1000]; cout<<"Value of a = "; cin>>a; cout<<"Value of c = "; cin>>c; cout<<"Value of m = "; cin>>m; cout<<"Value of z0 = "; cin>>z[0]; cout<<endl; cout<<z[0]<<"\n"; s.insert(z[0]); ll cn=1; chi[0]=float(z[0])/float(m); for(int i=1; i<n; i++) { z[i]=(az[i-1] + c)%m;//z[i]=(az[i-1]+c)%m;
s.insert(z[i]);
cn++;
if(cn>s.size())
break;
cout<<z[i];
chi[i]=float(z[i])/float(m);
cout<<"\n";
}
cout<<"Cycle length is:"<<s.size()<<endl;
float c1=0,c2=0,c3=0,c4=0;
for(int i=0; i<s.size(); i++)
{
if(chi[i]>=0.0 && chi[i]<0.25)
c1++;
else if(chi[i]>=0.25 && chi[i]<0.50)
c2++;
else if(chi[i]>=0.50 && chi[i]<0.75)
c3++;
else
c4++;
}
float sum=0,d;
d=(c1-25)*(c1-25);
sum+=d/25.0;
d=(c2-25)*(c2-25);
sum+=d/25.0;
d=(c3-25)*(c3-25);
sum+=d/25.0;
d=(c4-25)*(c4-25);
sum+=d/25.0;
cout<<sum<<endl;
return 0;
}
- monticurlo
Md Abu Shaed Islam import matplotlib.pyplot as plt import numpy as np import random as rn import math def F(x): return math.sin(x*pi/b)
pi =math.acos(-1) # which is pi #print(pi)
X = [] N =10 #number of item i = 0 c = 1.00 a = 1 b = 30 while i<=b: X.append(i) i+= 0.001
Y = [F(x) for x in X ] #rint(X,Y) #print(Y) X_random = [rn.random()*b for _ in range(N)] # means that these objects are used internally
Y_random = [rn.random()*c for _ in range(N)] #print(X_random) #print(Y_random)
probability = [1 if(F(X_random[i])>=Y_random[i]) else 0 for i in range(N)]
Accept = probability.count(1) reject = probability.count(0)
total_point = Accept + reject
print('total accept ',Accept) print('total reject ',reject)
print('Total point ', total_point)
print('Acceptance ratio :',Accept/N)
print('Rejection ratio :',reject/N)
plt.figure(figsize=(15, 3)) #This will modify/change the width and height of the plot.
plt.plot(X,Y,color='black') plt.scatter(X_random,Y_random,c = probability,cmap='brg',s=30) #cmap stands for colormap plt.plot([0,30],[0,0],color='black')
plt.plot([0,30],[1,1],color='red')#upper line 0 to 30 x=1 for star end y=1 end plt.xticks([i for i in range(b+1)]) #Get or set the current tick locations and labels of the x-axis for i in range(b+1): plt.plot([i,i],[0,1],color='black')
plt.xlabel('X_axis') plt.ylabel('Y_axis') plt.title('Monte_Carlo_Simulation') plt.scatter(X_random,Y_random,c =probability,cmap ='brg') #rainbow plt.colorbar() plt.show()
'''faults = [[i+1,0] for i in range(b)]
for i in range(N): faults[int(X_random[i])][1]+= probability[i]
print('[Day, Faults]')
count_undercurve = 0 for f in faults: count_undercurve += f[1] print(f)
print('Fault count ',count_undercurve)'''
#X_random = [i*pi for _ in range(N)]
5.Boomber fighter
import math from matplotlib import pyplot as plt
#Boomber=[[80,0],[90,-2],[99,-5],[108,-9],[116,-15],[125,-18],[133,-23],[141,-29],[151,-28],[160,-25],[169,-21],[179,-20],[180,-17]] XB=[80,90,99,108,116,125,133,141,151,160,169,179,180] YB=[0,-2,-5,-9,-15,-18,-23,-29,-28,-25,-21,-20,-17] XF=0.0 YF=50.0 XFL=[] YFL=[] XFL.append(XF) YFL.append(YF) VF=20 flag=0 temp=0 print("Path of Fighter.........") print("X=",XF,"\t\t\t\tY=",YF) for p,q in zip(XB,YB): distance=math.sqrt((p-XF)**2+(q-YF)**2) temp+=1 print("Distance:",distance) if distance<=10: flag=1 break else: sin=(q-YF)/distance cos=(p-XF)/distance XF+=VFcos YF+=VFsin XFL.append(XF) YFL.append(YF) print("X=",XF,"Y=",YF)
del XB[temp:13] del YB[temp:13] plt.title("Pure Pursuit Problem") plt.xlabel("Boomber") plt.ylabel("Fighter") plt.plot(XB,YB,color='black',linestyle='dashed',linewidth=1, marker='o',markersize=10,markerfacecolor='green', markeredgecolor='blue')
plt.plot(XFL,YFL,color='green',linestyle='dashed',linewidth=1, marker='o',markersize=10,markerfacecolor='red', markeredgecolor='black')
plt.grid() plt.show() if flag==1: print("Fighter Attack the Boomber.") else: print("Fighter Failed to Attack the Boomber.")
- Chemical reaction
**chemical import pandas as pd k1=0.008 k2=0.002 a=[100] b=[50] c=[0] T= [0] t = 0 delta =0.1 n=10 for i in range(0,11,1): at=a[i] + (k2c[i]-k1a[i]b[i])delta bt = b[i] + (k2c[i]-k1a[i]b[i])delta ct = c[i] + 2(k1a[i]b[i]-k2c[i])*delta t = t + delta T.append(t) a.append(at) b.append(bt) c.append(ct)
dis = {"Time":T,"A":a,"B":b,"C":c} r = pd.DataFrame(dis) print(r)
**monte karlo import matplotlib.pyplot as plt import numpy as np import random as rn import math def F(x): return math.sin(x*pi/b)
pi =math.acos(-1) # which is pi #print(pi)
X = [] N =10 #number of item i = 0 c = 1.00 a = 1 b = 30 while i<=b: X.append(i) i+= 0.001
Y = [F(x) for x in X ] #rint(X,Y) #print(Y) X_random = [rn.random()*b for _ in range(N)] # means that these objects are used internally
Y_random = [rn.random()*c for _ in range(N)] #print(X_random) #print(Y_random)
probability = [1 if(F(X_random[i])>=Y_random[i]) else 0 for i in range(N)]
Accept = probability.count(1) reject = probability.count(0)
total_point = Accept + reject
print('total accept ',Accept) print('total reject ',reject)
print('Total point ', total_point)
print('Acceptance ratio :',Accept/N)
print('Rejection ratio :',reject/N)
plt.figure(figsize=(15, 3)) #This will modify/change the width and height of the plot.
plt.plot(X,Y,color='black') plt.scatter(X_random,Y_random,c = probability,cmap='brg',s=30) #cmap stands for colormap plt.plot([0,30],[0,0],color='black')
plt.plot([0,30],[1,1],color='red')#upper line 0 to 30 x=1 for star end y=1 end plt.xticks([i for i in range(b+1)]) #Get or set the current tick locations and labels of the x-axis for i in range(b+1): plt.plot([i,i],[0,1],color='black')
plt.xlabel('X_axis') plt.ylabel('Y_axis') plt.title('Monte_Carlo_Simulation') plt.scatter(X_random,Y_random,c =probability,cmap ='brg') #rainbow plt.colorbar() plt.show()
'''faults = [[i+1,0] for i in range(b)]
for i in range(N): faults[int(X_random[i])][1]+= probability[i]
print('[Day, Faults]')
count_undercurve = 0 for f in faults: count_undercurve += f[1] print(f)
print('Fault count ',count_undercurve)'''
#X_random = [i*pi for _ in range(N)]
******boma import math from matplotlib import pyplot as plt
#Boomber=[[80,0],[90,-2],[99,-5],[108,-9],[116,-15],[125,-18],[133,-23],[141,-29],[151,-28],[160,-25],[169,-21],[179,-20],[180,-17]] XB=[80,90,99,108,116,125,133,141,151,160,169,179,180] YB=[0,-2,-5,-9,-15,-18,-23,-29,-28,-25,-21,-20,-17] XF=0.0 YF=50.0 XFL=[] YFL=[] XFL.append(XF) YFL.append(YF) VF=20 flag=0 temp=0 print("Path of Fighter.........") print("X=",XF,"\t\t\t\tY=",YF) for p,q in zip(XB,YB): distance=math.sqrt((p-XF)**2+(q-YF)**2) temp+=1 print("Distance:",distance) if distance<=10: flag=1 break else: sin=(q-YF)/distance cos=(p-XF)/distance XF+=VFcos YF+=VFsin XFL.append(XF) YFL.append(YF) print("X=",XF,"Y=",YF) #print(XB) del XB[temp:13] #print (XB) del YB[temp:13] plt.title("Pure Pursuit Problem") plt.xlabel("Boomber") plt.ylabel("Fighter") plt.plot(XB,YB,color='black',linestyle='dashed',linewidth=1, marker='o',markersize=10,markerfacecolor='green', markeredgecolor='blue')
plt.plot(XFL,YFL,color='green',linestyle='dashed',linewidth=1, marker='<',markersize=10,markerfacecolor='red', markeredgecolor='black')
plt.grid() plt.show() if flag==1: print("Fighter Attack the Boomber.") else: print("Fighter Failed to Attack the Boomber.")
**lcg
x = int(input("Enter the value of initail Seed : ")) tem =x a = int(input("Enter the value of a : ")) c = int(input("Enter the value of c : ")) m = int(input("Enter the value of m : "))
while 1: xi=(a*x+c)%m Ri = xi/m x = xi if xi == tem or xi==0: break
print(xi)
**আবু সাঈদ ইসলাম, [10/10/2023 11:50 PM] x = int(input("Enter the value of initail Seed : ")) tem =x a = int(input("Enter the value of a : ")) c = int(input("Enter the value of c : ")) m = int(input("Enter the value of m : "))
while 1: xi=(a*x+c)%m Ri = xi/m x = xi if xi == tem or xi==0: break
print(xi)
**document
import pandas as pd
st=[] wt=[45,16,5,29,33,25,21] ft =[] cm=[] bf=[] nj=[] s=c=0 n=7 noj=57 #nj.append(noj) for i in range(0,n,1): st.append(s) s+=wt[i] c+=wt[i]
nj.append(noj)
if(c>=60):
bf.append(1)
ft.append(s)
s+=5
cm.append(c)
c=0
else:
bf.append(0)
ft.append(s)
cm.append(c)
noj-=1
print(nj,st,ft,bf,) dis ={"Start Time":st,"Work Time":wt,"Finish Time":ft,"Cummulative Time":cm,"Break":bf,"Number of Job":nj} r = pd.DataFrame(dis) print(r)
**chi test
import random s = [] for _ in range(0,100,1): t = str(random.random()) t1 = float(t[0:4]) s.append(t1)
ct1=ct2=ct3=ct4=ct5=ct6=ct7=ct8=ct9=ct10=0 for i in range(0,100,1): if s[i]>=0 and s[i]<=0.1: ct1 =ct1+1 elif s[i]>=0.1 and s[i]<=0.2: ct2 =ct2+1 elif s[i]>=0.2 and s[i]<=0.3: ct3 =ct3+1 elif s[i]>=0.3 and s[i]<=0.4: ct4 =ct4+1 elif s[i]>=0.4 and s[i]<=0.5: ct5 =ct5+1 elif s[i]>=0.5 and s[i]<=0.6: ct6 =ct6+1 elif s[i]>=0.6 and s[i]<=0.7: ct7 =ct7+1 elif s[i]>=0.7 and s[i]<=0.8: ct8 =ct8+1 elif s[i]>=0.8 and s[i]<=0.9: ct9 =ct9+1 elif s[i]>=0.9 and s[i]<=1: ct10 =ct10+1 o = [ ] o.append(ct1) o.append(ct2) o.append(ct3) o.append(ct4) o.append(ct5) o.append(ct6) o.append(ct7) o.append(ct8) o.append(ct9) o.append(ct10) print(o) l =sum(o) print(l) E = [10]*10 #assign list with 10 time 10 value print(E) O_E = [] o_E_2 = [] for i in range(0,10,1): tem = o[i]-E[i] O_E.append(tem**2) tem1 = O_E[i]/E[i] o_E_2.append(tem1)
check = sum(o_E_2)
c_val = 16.9 if check <c_val: print("Accpted") else:
print("Rejected")