SIR-Project

724 days ago by vadi4776

# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.5 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.00001 b=1/12 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I Iprime=a*S*I-b*I Rprime=b*I # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph) 
       
# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.05 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.00001 b=1/12 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I Iprime=a*S*I-b*I Rprime=b*I # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph) 
       
# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.05 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.00001 b=1/20 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I Iprime=a*S*I-b*I Rprime=b*I # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph) 
       
# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.05 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.000005 b=1/12 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I Iprime=a*S*I-b*I Rprime=b*I # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph) 
       
# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.05 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.00001 b=1/12 c=10 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I+(1/c)*R Iprime=a*S*I-b*I Rprime=b*I-(1/c)*R # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph) 
       
# First, specify the starting and ending points, stepsize, and total number of observation points tstart=0 tfin=60 stepsize=0.05 length=(tfin-tstart)/stepsize+1 # Next, specify values of parameters, and initial values of variables a=0.00001 b=1/12 c=10 S=99999 I=1 R=0 t=tstart # Set up empty lists for the values we're about to compute Svalues=[] Ivalues=[] Rvalues=[] tvalues=[] # The following loop does three things: # (1) stores the current values of S, I, R, and t into the lists created above; # (2) computes the next values of S, I, R using Euler's method; # (3) increases t by the stepsize for i in range(length): # Store current values Svalues.append(S) Ivalues.append(I) Rvalues.append(R) tvalues.append(t) # Compute rates of change using SIR equations Sprime=-a*S*I+(1/c)*R Iprime=a*S*I-b*I Rprime=b*I-(1/c)*R # Net change equals rate of change times stepsize DeltaS=Sprime*stepsize DeltaI=Iprime*stepsize DeltaR=Rprime*stepsize # New values equal current values plus net change S=S+DeltaS I=I+DeltaI R=R+DeltaR t=t+stepsize # Next time through the loop, the above new values play the role of current values # Zip the t values with the S/I/R values into lists of ordered pairs, and create plots of these A=list_plot(list(zip(tvalues,Svalues)),plotjoined=True,marker='o',color='blue') B=list_plot(list(zip(tvalues,Ivalues)),plotjoined=True,marker='o',color='red') C=list_plot(list(zip(tvalues,Rvalues)),plotjoined=True,marker='o',color='green',axes_labels=['$t$ (days)','$S,I,R$ (individuals)']) SIRgraph=A+B+C show(SIRgraph)