From 5e84cdc679d7e36febef1ae5d4c0cf51262d6e49 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 3 Nov 2017 10:49:17 -0400
Subject: [PATCH 01/22] created python file

---
 exercise_10.py | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)
 create mode 100644 exercise_10.py

diff --git a/exercise_10.py b/exercise_10.py
new file mode 100644
index 0000000..23a8ba1
--- /dev/null
+++ b/exercise_10.py
@@ -0,0 +1,19 @@
+## exercise 10 ##
+
+# 1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# 2
\ No newline at end of file

From 55de3769fbdab3f06e5837739bcf735f919d192b Mon Sep 17 00:00:00 2001
From: Katherine <bookaholic214@gmail.com>
Date: Fri, 3 Nov 2017 11:06:46 -0400
Subject: [PATCH 02/22] Starting skeleton for Q1

---
 exercise_10.py | 20 +++++++++++++++++---
 1 file changed, 17 insertions(+), 3 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 23a8ba1..3e443be 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -1,9 +1,23 @@
 ## exercise 10 ##
 
 # 1
-
-
-
+#Load packages
+import pandas
+import scipy
+import scipy.integrate as spint
+from plotnine import *
+
+
+#Define custom function
+def popGrowth(y,t0,r,K):
+    N=y[0]
+    dNdt=r*(1-N/K)*N
+    return [dNdt]
+params=(0.3,10)
+NO=[0.01]
+times=range(0,600)
+modelSim=spint.odeint(func=ddSim,y0=NO,t=times,args=params)
+modelOutput=pandas.DataFrame({"t":times,"N":modelSim[:,0]})
 
 
 

From 0aecd5983c59b89e7bc25dc8f5ecb94aff2864ad Mon Sep 17 00:00:00 2001
From: Katherine <bookaholic214@gmail.com>
Date: Fri, 3 Nov 2017 11:18:56 -0400
Subject: [PATCH 03/22] Added function and loop to Q1

---
 exercise_10.py | 16 ++++++++++++----
 1 file changed, 12 insertions(+), 4 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 3e443be..ea068b0 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -13,11 +13,19 @@ def popGrowth(y,t0,r,K):
     N=y[0]
     dNdt=r*(1-N/K)*N
     return [dNdt]
-params=(0.3,10)
-NO=[0.01]
 times=range(0,600)
-modelSim=spint.odeint(func=ddSim,y0=NO,t=times,args=params)
-modelOutput=pandas.DataFrame({"t":times,"N":modelSim[:,0]})
+
+#Set a pool of values for growth rate
+rK=[-.1,.1,.4,.8,1.0]
+#Dataframe for storing model output
+store_rK=pandas.DataFrame({"time":times,"r1":0,"r2":0,"r3":0,"r4":0,"r5":0})
+
+#Using a for loop to make my life easier
+for i in range(0,len(gRates)):
+    params=(rK[i],K)
+    popGrowthSim=spint.odeint(func=ddSim,y0=y0,t=times,args=params)
+    store_rK.iloc[:i]=popGrowthSim[:0]
+
 
 
 

From b2afef6b71b61d6456994d08df3555081c45cf64 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 3 Nov 2017 11:29:23 -0400
Subject: [PATCH 04/22] pseudocode for q2

---
 exercise_10.py | 31 ++++++++++++++++++++++++++++++-
 1 file changed, 30 insertions(+), 1 deletion(-)

diff --git a/exercise_10.py b/exercise_10.py
index ea068b0..255fb3f 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -38,4 +38,33 @@ def popGrowth(y,t0,r,K):
 
 
 
-# 2
\ No newline at end of file
+# 2
+
+# import libs
+import pandas
+from plotnine import *
+import numpy
+from scipy.optimize import minimize
+from scipy.stats import norm
+import scipy.stats
+
+
+def SIR (p):
+    S = p[0]
+    I = p[1]
+    R = p[2]
+    beta = [3]
+    gamma= [4]
+
+    dS = -1*(beta*I*S)
+    dT = (beta*I*S)-(gamma*I)
+    dR = (gamma*I)
+
+    loop to do the calcs start with time 0 for one condition
+    then loop with i-1 from here
+    output shite too
+
+
+    expected =B0+B1*obs.x
+    nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
+    return nll
\ No newline at end of file

From b09a67eaf1e4ffe1bc7ce7f9fe621c26fb1ff06c Mon Sep 17 00:00:00 2001
From: Katherine <bookaholic214@gmail.com>
Date: Fri, 3 Nov 2017 13:33:07 -0400
Subject: [PATCH 05/22] Merging with Dan

---
 exercise_10.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index ea068b0..8c76e2b 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -4,27 +4,27 @@
 #Load packages
 import pandas
 import scipy
-import scipy.integrate as spint
+import scipy.integrate as si
 from plotnine import *
 
 
 #Define custom function
-def popGrowth(y,t0,r,K):
+def popGrowth(y,t0,r,K,N):
     N=y[0]
     dNdt=r*(1-N/K)*N
     return [dNdt]
-times=range(0,600)
-
+times=range(0,100)
+NO=[.01]
 #Set a pool of values for growth rate
-rK=[-.1,.1,.4,.8,1.0]
+growthRates=[-.1,.1,.4,.8,1.0]
 #Dataframe for storing model output
-store_rK=pandas.DataFrame({"time":times,"r1":0,"r2":0,"r3":0,"r4":0,"r5":0})
+store_growthRates=pandas.DataFrame({"time":times,"r1":0,"r2":0,"r3":0,"r4":0,"r5":0})
 
 #Using a for loop to make my life easier
-for i in range(0,len(gRates)):
-    params=(rK[i],K)
-    popGrowthSim=spint.odeint(func=ddSim,y0=y0,t=times,args=params)
-    store_rK.iloc[:i]=popGrowthSim[:0]
+for i in range(0,len(growthRates)):
+    pars=(growthRates[i],100,10)
+    sim=si.odeint(func=popGrowth,y0=NO,t=times,args=pars)
+    store_growthRates.iloc[:,i]=sim[:,0]
 
 
 

From 10f12674531c25eef75d22b162e791e93332c22f Mon Sep 17 00:00:00 2001
From: Katherine <bookaholic214@gmail.com>
Date: Fri, 3 Nov 2017 14:00:54 -0400
Subject: [PATCH 06/22] Added ggplots. Only Plot 3 isn't working

---
 exercise_10.py | 87 +++++++++++++++++++++++++++++---------------------
 1 file changed, 50 insertions(+), 37 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 4e81463..2455906 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -25,46 +25,59 @@ def popGrowth(y,t0,r,K,N):
     pars=(growthRates[i],100,10)
     sim=si.odeint(func=popGrowth,y0=NO,t=times,args=pars)
     store_growthRates.iloc[:,i]=sim[:,0]
+print(store_growthRates)    
+    
+#Plot 1- pop size as function of time
+g=(ggplot(data=store_growthRates)
+    +geom_line(store_growthRates,aes(x="time",y="r1"))+theme_classic()
+    +ylab("population size")
+    +geom_line(store_growthRates,aes(x="time",y="r2"),color="green")
+    +geom_line(store_growthRates,aes(x="time",y="r3"),color="red")
+    +geom_line(store_growthRates,aes(x="time",y="r4"),color="orange")
+    +geom_line(store_growthRates,aes(x="time",y="r5"),color="purple"))
+print(p)
+
+#set a pool of values for carrying capacity
+carryCap=[10,50,100]
+#Dataframe for storing model output
+store_carryCap=pandas.DataFrame({"time":times,"K1":0,"K2":0,"K3":0})
+#for loop for Plot 2
+for i in range(0,len(carryCap)):
+    pars=(.2,carryCap[i],1)
+    sim=si.odeint(func=popGrowth,y0=NO,t=times,args=pars)
+    store_carryCap.iloc[:,i]=sim[:,0]
+print(store_carryCap) 
+
+#Plot 2- 
+k=(ggplot(data=store_carryCap)
+    +geom_line(store_carryCap,aes(x="time",y="K1"),color="blue")+theme_classic()
+    +ylab("population size")
+    +geom_line(store_carryCap,aes(x="time",y="K2"),color="green")
+    +geom_line(store_carryCap,aes(x="time",y="K3"),color="purple"))
+print(k)
+
+#Set a pool of values for init pop size
+initPop=[1,5,100]
+#Dataframe for storing model output
+store_initPop=pandas.DataFrame({"time":times,"N1":1,"N2":5,"N3":100})
 
+#Using a for loop to make my life easier
+for i in range(0,len(initPop)):
+    pars=(.1,50,initPop[i])
+    sim=si.odeint(func=popGrowth,y0=NO,t=times,args=pars)
+    store_initPop.iloc[:,i]=sim[:,0]
+print(store_initPop)    
+    
+#Plot 1- pop size as function of time
+p=(ggplot(data=store_initPop)
+    +geom_line(store_initPop,aes(x="time",y="N1"),color="orange")+theme_classic()
+    +ylab("population size")
+    +geom_line(store_initPop,aes(x="time",y="N2"),color="yellow")
+    +geom_line(store_initPop,aes(x="time",y="N3"),color="red"))
+print(p)
 
 
 
 
 
-
-
-
-
-
-
-
-# 2
-
-# import libs
-import pandas
-from plotnine import *
-import numpy
-from scipy.optimize import minimize
-from scipy.stats import norm
-import scipy.stats
-
-
-def SIR (p):
-    S = p[0]
-    I = p[1]
-    R = p[2]
-    beta = [3]
-    gamma= [4]
-
-    dS = -1*(beta*I*S)
-    dT = (beta*I*S)-(gamma*I)
-    dR = (gamma*I)
-
-    loop to do the calcs start with time 0 for one condition
-    then loop with i-1 from here
-    output shite too
-
-
-    expected =B0+B1*obs.x
-    nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
-    return nll
\ No newline at end of file
+# 2
\ No newline at end of file

From c423030a21c777ccc4434a4970a021a50baf09bc Mon Sep 17 00:00:00 2001
From: Katherine <bookaholic214@gmail.com>
Date: Fri, 3 Nov 2017 14:07:22 -0400
Subject: [PATCH 07/22] I tried to fix Plot 3 and made it worse lol

---
 exercise_10.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 2455906..51a89e7 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -59,7 +59,7 @@ def popGrowth(y,t0,r,K,N):
 #Set a pool of values for init pop size
 initPop=[1,5,100]
 #Dataframe for storing model output
-store_initPop=pandas.DataFrame({"time":times,"N1":1,"N2":5,"N3":100})
+store_initPop=pandas.DataFrame({"time":times,"N1":0,"N2":0,"N3":0})
 
 #Using a for loop to make my life easier
 for i in range(0,len(initPop)):
@@ -68,7 +68,7 @@ def popGrowth(y,t0,r,K,N):
     store_initPop.iloc[:,i]=sim[:,0]
 print(store_initPop)    
     
-#Plot 1- pop size as function of time
+#Plot 3- effect of initial Pop size differences
 p=(ggplot(data=store_initPop)
     +geom_line(store_initPop,aes(x="time",y="N1"),color="orange")+theme_classic()
     +ylab("population size")

From ef27e7ba12d80ed5f8f7cbbf46ca3a5989e9400d Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Sun, 5 Nov 2017 14:16:22 -0500
Subject: [PATCH 08/22] pseudocode for q2

---
 exercise_10.py | 31 ++++++++++++++++++++++++++++++-
 1 file changed, 30 insertions(+), 1 deletion(-)

diff --git a/exercise_10.py b/exercise_10.py
index 51a89e7..dba5a35 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -80,4 +80,33 @@ def popGrowth(y,t0,r,K,N):
 
 
 
-# 2
\ No newline at end of file
+# 2
+
+# import libs
+import pandas
+from plotnine import *
+import numpy
+from scipy.optimize import minimize
+from scipy.stats import norm
+import scipy.stats
+
+
+def SIR (p):
+    S = p[0]
+    I = p[1]
+    R = p[2]
+    beta = [3]
+    gamma= [4]
+
+    dS = -1*(beta*I*S)
+    dT = (beta*I*S)-(gamma*I)
+    dR = (gamma*I)
+
+    loop to do the calcs start with time 0 for one condition
+    then loop with i-1 from here
+    output shite too
+
+
+    expected =B0+B1*obs.x
+    nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
+    return nll
\ No newline at end of file

From d5336254b22a9530c5739eabed30bae14eead089 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Sun, 5 Nov 2017 20:06:40 -0500
Subject: [PATCH 09/22]  q2

---
 exercise_10.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index dba5a35..83ce19f 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -35,7 +35,7 @@ def popGrowth(y,t0,r,K,N):
     +geom_line(store_growthRates,aes(x="time",y="r3"),color="red")
     +geom_line(store_growthRates,aes(x="time",y="r4"),color="orange")
     +geom_line(store_growthRates,aes(x="time",y="r5"),color="purple"))
-print(p)
+print(g)
 
 #set a pool of values for carrying capacity
 carryCap=[10,50,100]
@@ -102,11 +102,11 @@ def SIR (p):
     dT = (beta*I*S)-(gamma*I)
     dR = (gamma*I)
 
-    loop to do the calcs start with time 0 for one condition
-    then loop with i-1 from here
-    output shite too
+    #loop to do the calcs start with time 0 for one condition
+    #then loop with i-1 from here
+    #output shite too
 
 
-    expected =B0+B1*obs.x
-    nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
-    return nll
\ No newline at end of file
+    #expected =B0+B1*obs.x
+    #nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
+    #return nll
\ No newline at end of file

From 3d29e0eefd422a663d26e4c1eb98b6398a7fbe5b Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Mon, 6 Nov 2017 15:45:20 -0500
Subject: [PATCH 10/22] got sim working for q2.... see comments in code

---
 exercise_10.py | 43 ++++++++++++++++++-------------------------
 1 file changed, 18 insertions(+), 25 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 83ce19f..0fd2e10 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -77,36 +77,29 @@ def popGrowth(y,t0,r,K,N):
 print(p)
 
 
-
-
-
 # 2
 
-# import libs
-import pandas
-from plotnine import *
-import numpy
-from scipy.optimize import minimize
-from scipy.stats import norm
-import scipy.stats
-
-
-def SIR (p):
-    S = p[0]
-    I = p[1]
-    R = p[2]
-    beta = [3]
-    gamma= [4]
+def SIR (y,t0,beta,gamma):
+    S = y[0]
+    I = y[1]
+    R = y[2]
 
     dS = -1*(beta*I*S)
-    dT = (beta*I*S)-(gamma*I)
+    dI = (beta*I*S)-(gamma*I)
     dR = (gamma*I)
 
-    #loop to do the calcs start with time 0 for one condition
-    #then loop with i-1 from here
-    #output shite too
+    return dS, dI, dR
+
+times = range(0,500)
+params = (.0005, .05)
+NO = [999, 1, 0]
+
+infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
+print (infection)
 
+sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
 
-    #expected =B0+B1*obs.x
-    #nll = -1*norm(expected, sigma).logpdf(obs.y).sum()
-    #return nll
\ No newline at end of file
+# got the sim working for one beta and gamma value
+#need to import the vlaues from the sim list into a dataframe
+#need to make a loop that does this for all the beta and gamma values
+#need to add calcs to the loop as well.
\ No newline at end of file

From 5a9b3cdb0ac62b78f37a396e193b10353f2bc21f Mon Sep 17 00:00:00 2001
From: Mati Nemera <mnemera@nd.edu>
Date: Thu, 9 Nov 2017 17:10:53 -0500
Subject: [PATCH 11/22] Added file for simulation data

---
 simData.xlsx | Bin 0 -> 8513 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100755 simData.xlsx

diff --git a/simData.xlsx b/simData.xlsx
new file mode 100755
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From 35a74d9e1618b61ce1f8067b8ce59e28071f4520 Mon Sep 17 00:00:00 2001
From: Mati Nemera <mnemera@nd.edu>
Date: Thu, 9 Nov 2017 18:26:42 -0500
Subject: [PATCH 12/22] no actual changes, just need to pull

---
 exercise_10.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/exercise_10.py b/exercise_10.py
index 0fd2e10..a01a026 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -57,7 +57,7 @@ def popGrowth(y,t0,r,K,N):
 print(k)
 
 #Set a pool of values for init pop size
-initPop=[1,5,100]
+initPop=[1,50,100]
 #Dataframe for storing model output
 store_initPop=pandas.DataFrame({"time":times,"N1":0,"N2":0,"N3":0})
 

From 6882eca8946134c74f544455ab637adcf0b85afb Mon Sep 17 00:00:00 2001
From: Mati Nemera <mnemera@nd.edu>
Date: Thu, 9 Nov 2017 19:05:12 -0500
Subject: [PATCH 13/22] Got three n naughts in problem 1-3

---
 exercise_10.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index a01a026..f2ae0be 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -64,14 +64,14 @@ def popGrowth(y,t0,r,K,N):
 #Using a for loop to make my life easier
 for i in range(0,len(initPop)):
     pars=(.1,50,initPop[i])
-    sim=si.odeint(func=popGrowth,y0=NO,t=times,args=pars)
+    sim=si.odeint(func=popGrowth,y0=initPop[i],t=times,args=pars)
     store_initPop.iloc[:,i]=sim[:,0]
 print(store_initPop)    
     
 #Plot 3- effect of initial Pop size differences
 p=(ggplot(data=store_initPop)
     +geom_line(store_initPop,aes(x="time",y="N1"),color="orange")+theme_classic()
-    +ylab("population size")
+    +ylab("population size")+ylim(0,100)
     +geom_line(store_initPop,aes(x="time",y="N2"),color="yellow")
     +geom_line(store_initPop,aes(x="time",y="N3"),color="red"))
 print(p)

From 7c237259de2d2eae6f39cf073529bbb6f63dc7d9 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Thu, 9 Nov 2017 19:28:58 -0500
Subject: [PATCH 14/22] q2 is here now!

---
 Exercise10_revised.pdf | Bin 189226 -> 199477 bytes
 exercise_10.py         |   7 +++-
 exercise_10_B.py       |  72 +++++++++++++++++++++++++++++++++++++++++
 3 files changed, 78 insertions(+), 1 deletion(-)
 create mode 100644 exercise_10_B.py

diff --git a/Exercise10_revised.pdf b/Exercise10_revised.pdf
index e282db8a390acfd36e544982504a7986d5b4ec87..8d4bebe94ff5b9c28cbffe1d90b2cd24833be5c6 100644
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diff --git a/exercise_10.py b/exercise_10.py
index 0fd2e10..f07d3c0 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -98,8 +98,13 @@ def SIR (y,t0,beta,gamma):
 print (infection)
 
 sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
+infection.iloc[:,i]=sim[:,0]
+print infection
+
+
 
 # got the sim working for one beta and gamma value
 #need to import the vlaues from the sim list into a dataframe
 #need to make a loop that does this for all the beta and gamma values
-#need to add calcs to the loop as well.
\ No newline at end of file
+#need to add calcs to the loop as well.
+
diff --git a/exercise_10_B.py b/exercise_10_B.py
new file mode 100644
index 0000000..f63d737
--- /dev/null
+++ b/exercise_10_B.py
@@ -0,0 +1,72 @@
+#Load packages
+import pandas
+import scipy
+import scipy.integrate as si
+from plotnine import *
+
+def SIR (y,t0,beta,gamma):
+    S = y[0]
+    I = y[1]
+    R = y[2]
+    dS = -1*(beta*I*S)
+    dI = (beta*I*S)-(gamma*I)
+    dR = (gamma*I)
+    return dS, dI, dR
+
+times = range(0,500)
+params = (.0005, .05) #need to change these for diff betas and gammas # need to make an arraay or dataframe
+NO = [999, 1, 0]
+
+infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
+
+# sim
+sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
+# fill dataframe
+infection.iloc[:,2]=sim[:,0]
+infection.iloc[:,0]=sim[:,1]
+infection.iloc[:,1]=sim[:,2]
+
+# calc max daily incidence
+daily_incidence = []
+for i in range(0,len(infection),):
+    if infection.time[i]==0:
+        continue
+    else:
+        I = infection.iloc[i]['I']
+        Iold = infection.iloc[i-1]['I']
+        incidence = I-Iold
+        daily_incidence.append(incidence)
+max_daily_incidence = max(daily_incidence)
+
+
+# calc max daily prevalence
+daily_prev = []
+for i in range(0,len(infection),):
+    I = infection.iloc[i]['I']
+    R = infection.iloc[i]['R']
+    S = infection.iloc[i]['S']
+    prev = I/(S+I+R)
+    daily_prev.append(prev)
+max_daily_prev = max(daily_prev)
+
+#calc percent affected over simulation- use last time step (499)
+I= infection.iloc[499]['I']
+R= infection.iloc[499]['R']
+S= infection.iloc[499]['S']
+percent_affected = (I+R)/(S+I+R)
+
+# basic reproduction number initial SIR
+beta = params[0]
+gamma = params[1]
+I= infection.iloc[0]['I']
+R= infection.iloc[0]['R']
+S= infection.iloc[0]['S']
+Ro = (beta*(S+I+R))/gamma
+
+#need these to fill into a list or a dataframe
+# need to put all this intoa bigger loop
+
+
+
+
+

From e393685083689d7c764f0747274f33afad35f3ca Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Thu, 9 Nov 2017 19:33:33 -0500
Subject: [PATCH 15/22] moved q2 to 10B.py file

---
 exercise_10.py | 32 +-------------------------------
 1 file changed, 1 insertion(+), 31 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 0fc5fea..26a086c 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -77,34 +77,4 @@ def popGrowth(y,t0,r,K,N):
 print(p)
 
 
-# 2
-
-def SIR (y,t0,beta,gamma):
-    S = y[0]
-    I = y[1]
-    R = y[2]
-
-    dS = -1*(beta*I*S)
-    dI = (beta*I*S)-(gamma*I)
-    dR = (gamma*I)
-
-    return dS, dI, dR
-
-times = range(0,500)
-params = (.0005, .05)
-NO = [999, 1, 0]
-
-infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
-print (infection)
-
-sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
-infection.iloc[:,i]=sim[:,0]
-print infection
-
-
-
-# got the sim working for one beta and gamma value
-#need to import the vlaues from the sim list into a dataframe
-#need to make a loop that does this for all the beta and gamma values
-#need to add calcs to the loop as well.
-
+# 2 MOVED TO A NEW .PY file!!! ALSO IN OUR GIT repo

From 4fc815a82b904bf6d886e7900190b394a378edfe Mon Sep 17 00:00:00 2001
From: Mati Nemera <mnemera@nd.edu>
Date: Thu, 9 Nov 2017 20:38:22 -0500
Subject: [PATCH 16/22] Saved and Fixed initial NO values for problem 1 part 2

---
 exercise_10.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/exercise_10.py b/exercise_10.py
index f2ae0be..8c5f4a5 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -41,6 +41,7 @@ def popGrowth(y,t0,r,K,N):
 carryCap=[10,50,100]
 #Dataframe for storing model output
 store_carryCap=pandas.DataFrame({"time":times,"K1":0,"K2":0,"K3":0})
+NO = 1
 #for loop for Plot 2
 for i in range(0,len(carryCap)):
     pars=(.2,carryCap[i],1)
@@ -71,7 +72,7 @@ def popGrowth(y,t0,r,K,N):
 #Plot 3- effect of initial Pop size differences
 p=(ggplot(data=store_initPop)
     +geom_line(store_initPop,aes(x="time",y="N1"),color="orange")+theme_classic()
-    +ylab("population size")+ylim(0,100)
+    +ylab("population size")
     +geom_line(store_initPop,aes(x="time",y="N2"),color="yellow")
     +geom_line(store_initPop,aes(x="time",y="N3"),color="red"))
 print(p)

From 79415763f71a74b1edb5ca497e76ceb8cc241115 Mon Sep 17 00:00:00 2001
From: Mati Nemera <mnemera@nd.edu>
Date: Thu, 9 Nov 2017 21:11:01 -0500
Subject: [PATCH 17/22] removed problem 2 stuff from problem 1 file

---
 exercise_10.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/exercise_10.py b/exercise_10.py
index 50f6a96..d6c39bd 100644
--- a/exercise_10.py
+++ b/exercise_10.py
@@ -76,6 +76,3 @@ def popGrowth(y,t0,r,K,N):
     +geom_line(store_initPop,aes(x="time",y="N2"),color="yellow")
     +geom_line(store_initPop,aes(x="time",y="N3"),color="red"))
 print(p)
-
-
-# 2 MOVED TO A NEW .PY file!!! ALSO IN OUR GIT repo

From 0d0880e962b730346500064fec38e80cb81ac37a Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Thu, 9 Nov 2017 23:34:38 -0500
Subject: [PATCH 18/22] made a dataframe

---
 exercise_10_B.py | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/exercise_10_B.py b/exercise_10_B.py
index f63d737..556a4fc 100644
--- a/exercise_10_B.py
+++ b/exercise_10_B.py
@@ -15,9 +15,20 @@ def SIR (y,t0,beta,gamma):
 
 times = range(0,500)
 params = (.0005, .05) #need to change these for diff betas and gammas # need to make an arraay or dataframe
+
+data = [{'beta' : .0005, 'gamma' : .05},
+        {'beta': .005, 'gamma': .5},
+        {'beta': .0001, 'gamma': .1},
+        {'beta': .00005, 'gamma': .1},
+        {'beta': .0001, 'gamma': .05},
+        {'beta': .0002, 'gamma': .05},
+        {'beta': .0001, 'gamma': .06}]
+my_data = pandas.DataFrame(data)
+
 NO = [999, 1, 0]
 
 infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
+results = []
 
 # sim
 sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
@@ -63,6 +74,7 @@ def SIR (y,t0,beta,gamma):
 S= infection.iloc[0]['S']
 Ro = (beta*(S+I+R))/gamma
 
+
 #need these to fill into a list or a dataframe
 # need to put all this intoa bigger loop
 

From 55665b4ffc0a4678befbfe54ea90d4875444ecf8 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 10 Nov 2017 00:11:05 -0500
Subject: [PATCH 19/22] made a billion lists and have then make a dataframe of
 the output

---
 exercise_10_B.py | 38 +++++++++++++++++++++++++++++++++-----
 1 file changed, 33 insertions(+), 5 deletions(-)

diff --git a/exercise_10_B.py b/exercise_10_B.py
index 556a4fc..25ed23c 100644
--- a/exercise_10_B.py
+++ b/exercise_10_B.py
@@ -4,6 +4,7 @@
 import scipy.integrate as si
 from plotnine import *
 
+# function
 def SIR (y,t0,beta,gamma):
     S = y[0]
     I = y[1]
@@ -13,9 +14,11 @@ def SIR (y,t0,beta,gamma):
     dR = (gamma*I)
     return dS, dI, dR
 
+# initial conditions
 times = range(0,500)
-params = (.0005, .05) #need to change these for diff betas and gammas # need to make an arraay or dataframe
+NO = [999, 1, 0]
 
+# dataframe of gamma and beta values
 data = [{'beta' : .0005, 'gamma' : .05},
         {'beta': .005, 'gamma': .5},
         {'beta': .0001, 'gamma': .1},
@@ -25,13 +28,23 @@ def SIR (y,t0,beta,gamma):
         {'beta': .0001, 'gamma': .06}]
 my_data = pandas.DataFrame(data)
 
-NO = [999, 1, 0]
+mdi = []
+mdp = []
+pa = []
+ro = []
+b = []
+g = []
+
+# start big for loop here
+params = (.0005, .05) #need to change these for diff betas and gammas # need to make an arraay or dataframe
+b.append(params[0])
+g.append(params[1])
 
 infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
-results = []
 
 # sim
 sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
+
 # fill dataframe
 infection.iloc[:,2]=sim[:,0]
 infection.iloc[:,0]=sim[:,1]
@@ -48,7 +61,7 @@ def SIR (y,t0,beta,gamma):
         incidence = I-Iold
         daily_incidence.append(incidence)
 max_daily_incidence = max(daily_incidence)
-
+mdi.append(max_daily_incidence)
 
 # calc max daily prevalence
 daily_prev = []
@@ -59,12 +72,14 @@ def SIR (y,t0,beta,gamma):
     prev = I/(S+I+R)
     daily_prev.append(prev)
 max_daily_prev = max(daily_prev)
+mdp.append(max_daily_prev)
 
 #calc percent affected over simulation- use last time step (499)
 I= infection.iloc[499]['I']
 R= infection.iloc[499]['R']
 S= infection.iloc[499]['S']
 percent_affected = (I+R)/(S+I+R)
+pa.append(percent_affected)
 
 # basic reproduction number initial SIR
 beta = params[0]
@@ -72,9 +87,22 @@ def SIR (y,t0,beta,gamma):
 I= infection.iloc[0]['I']
 R= infection.iloc[0]['R']
 S= infection.iloc[0]['S']
-Ro = (beta*(S+I+R))/gamma
+repo_number = (beta*(S+I+R))/gamma
+ro.append(repo_number)
+
+
+
+
+results = pandas.DataFrame(
+    {'beta' : b,
+     'gamma' : g,
+     'max_daily_incide' : mdi,
+     'max_daily_prev' : mdp,
+     'percent_affect' : pa,
+     'repo_num' : ro})
 
 
+print results
 #need these to fill into a list or a dataframe
 # need to put all this intoa bigger loop
 

From edfdb318a9efe3736d3874c8135166fcb06e92e3 Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 10 Nov 2017 01:04:02 -0500
Subject: [PATCH 20/22] OMG IT WORKS!

---
 exercise_10_B.py | 111 ++++++++++++++++++++++++-----------------------
 1 file changed, 57 insertions(+), 54 deletions(-)

diff --git a/exercise_10_B.py b/exercise_10_B.py
index 25ed23c..280cd6f 100644
--- a/exercise_10_B.py
+++ b/exercise_10_B.py
@@ -28,6 +28,7 @@ def SIR (y,t0,beta,gamma):
         {'beta': .0001, 'gamma': .06}]
 my_data = pandas.DataFrame(data)
 
+# make lists to hold the results
 mdi = []
 mdp = []
 pa = []
@@ -36,61 +37,63 @@ def SIR (y,t0,beta,gamma):
 g = []
 
 # start big for loop here
-params = (.0005, .05) #need to change these for diff betas and gammas # need to make an arraay or dataframe
-b.append(params[0])
-g.append(params[1])
-
-infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
-
-# sim
-sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
-
-# fill dataframe
-infection.iloc[:,2]=sim[:,0]
-infection.iloc[:,0]=sim[:,1]
-infection.iloc[:,1]=sim[:,2]
-
-# calc max daily incidence
-daily_incidence = []
-for i in range(0,len(infection),):
-    if infection.time[i]==0:
-        continue
-    else:
+for line in range(0,len(my_data),):
+    q = my_data.iloc[line]['beta']
+    p = my_data.iloc[line]['gamma']
+    params = (q, p)
+
+    b.append(params[0])
+    g.append(params[1])
+
+    infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
+
+    # sim
+    sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
+
+    # fill dataframe
+    infection.iloc[:,2]=sim[:,0]
+    infection.iloc[:,0]=sim[:,1]
+    infection.iloc[:,1]=sim[:,2]
+
+    # calc max daily incidence
+    daily_incidence = []
+    for i in range(0,len(infection),):
+        if infection.time[i]==0:
+            continue
+        else:
+            I = infection.iloc[i]['I']
+            Iold = infection.iloc[i-1]['I']
+            incidence = I-Iold
+            daily_incidence.append(incidence)
+    max_daily_incidence = max(daily_incidence)
+    mdi.append(max_daily_incidence)
+
+    # calc max daily prevalence
+    daily_prev = []
+    for i in range(0,len(infection),):
         I = infection.iloc[i]['I']
-        Iold = infection.iloc[i-1]['I']
-        incidence = I-Iold
-        daily_incidence.append(incidence)
-max_daily_incidence = max(daily_incidence)
-mdi.append(max_daily_incidence)
-
-# calc max daily prevalence
-daily_prev = []
-for i in range(0,len(infection),):
-    I = infection.iloc[i]['I']
-    R = infection.iloc[i]['R']
-    S = infection.iloc[i]['S']
-    prev = I/(S+I+R)
-    daily_prev.append(prev)
-max_daily_prev = max(daily_prev)
-mdp.append(max_daily_prev)
-
-#calc percent affected over simulation- use last time step (499)
-I= infection.iloc[499]['I']
-R= infection.iloc[499]['R']
-S= infection.iloc[499]['S']
-percent_affected = (I+R)/(S+I+R)
-pa.append(percent_affected)
-
-# basic reproduction number initial SIR
-beta = params[0]
-gamma = params[1]
-I= infection.iloc[0]['I']
-R= infection.iloc[0]['R']
-S= infection.iloc[0]['S']
-repo_number = (beta*(S+I+R))/gamma
-ro.append(repo_number)
-
-
+        R = infection.iloc[i]['R']
+        S = infection.iloc[i]['S']
+        prev = I/(S+I+R)
+        daily_prev.append(prev)
+    max_daily_prev = max(daily_prev)
+    mdp.append(max_daily_prev)
+
+    #calc percent affected over simulation- use last time step (499)
+    I= infection.iloc[499]['I']
+    R= infection.iloc[499]['R']
+    S= infection.iloc[499]['S']
+    percent_affected = (I+R)/(S+I+R)
+    pa.append(percent_affected)
+
+    # basic reproduction number initial SIR
+    beta = params[0]
+    gamma = params[1]
+    I= infection.iloc[0]['I']
+    R= infection.iloc[0]['R']
+    S= infection.iloc[0]['S']
+    repo_number = (beta*(S+I+R))/gamma
+    ro.append(repo_number)
 
 
 results = pandas.DataFrame(

From 9600e5b2319b2e76fa5143c16db2806591ade29a Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 10 Nov 2017 03:06:34 -0500
Subject: [PATCH 21/22] pushed observations

---
 exercise_10_B.py | 43 ++++++++++++++++++++++++++++++++++++-------
 1 file changed, 36 insertions(+), 7 deletions(-)

diff --git a/exercise_10_B.py b/exercise_10_B.py
index 280cd6f..34a9520 100644
--- a/exercise_10_B.py
+++ b/exercise_10_B.py
@@ -25,7 +25,25 @@ def SIR (y,t0,beta,gamma):
         {'beta': .00005, 'gamma': .1},
         {'beta': .0001, 'gamma': .05},
         {'beta': .0002, 'gamma': .05},
-        {'beta': .0001, 'gamma': .06}]
+        {'beta': .0001, 'gamma': .06},
+        {'beta': .0001, 'gamma': .9},
+        {'beta': .0001, 'gamma': .5},
+        {'beta': .0001, 'gamma': .25},
+        {'beta': .0001, 'gamma': .1},
+        {'beta': .0001, 'gamma': .05},
+        {'beta': .0001, 'gamma': .01},
+        {'beta': .0001, 'gamma': .001},
+        {'beta': .0001, 'gamma': .0001},
+        {'beta': .9, 'gamma': .0001},
+        {'beta': .5, 'gamma': .0001},
+        {'beta': .25, 'gamma': .0001},
+        {'beta': .1, 'gamma': .0001},
+        {'beta': .05, 'gamma': .0001},
+        {'beta': .01, 'gamma': .0001},
+        {'beta': .001, 'gamma': .0001},
+        {'beta': .0001, 'gamma': .0001},
+        {'beta': .00001, 'gamma': .0001},
+        ]
 my_data = pandas.DataFrame(data)
 
 # make lists to hold the results
@@ -36,18 +54,19 @@ def SIR (y,t0,beta,gamma):
 b = []
 g = []
 
-# start big for loop here
+# start big  loop here
 for line in range(0,len(my_data),):
     q = my_data.iloc[line]['beta']
     p = my_data.iloc[line]['gamma']
-    params = (q, p)
+    params = (q, p)  # make tuple
 
-    b.append(params[0])
+    b.append(params[0])  # append list
     g.append(params[1])
 
+    # make dataframe
     infection = pandas.DataFrame({"time":times,"S":0,"I":0,"R":0})
 
-    # sim
+    # sim shite
     sim = si.odeint(func=SIR, y0=NO, t=times, args=params)
 
     # fill dataframe
@@ -95,7 +114,7 @@ def SIR (y,t0,beta,gamma):
     repo_number = (beta*(S+I+R))/gamma
     ro.append(repo_number)
 
-
+# make a dataframe for results from all the lists
 results = pandas.DataFrame(
     {'beta' : b,
      'gamma' : g,
@@ -104,12 +123,22 @@ def SIR (y,t0,beta,gamma):
      'percent_affect' : pa,
      'repo_num' : ro})
 
-
 print results
 #need these to fill into a list or a dataframe
 # need to put all this intoa bigger loop
 
+'''
+* observations *
+as gamma gets smaller the max incidence and daily prevalence rises, percent infection rises and repoduction number rises. 
+big gamma, things get smaller
+
+as beta gets bigger the max incidence and daily prevalence rises, percent effectice rises and repo number rises. 
+small beta, things get smaller
+
+so a high beta and a small gamma cause the disease to have a higher rate of infection in the population 
+
 
+'''
 
 
 

From 93d5d8aab8f7812583871376529a261551a287aa Mon Sep 17 00:00:00 2001
From: omegadan01 <dbruzzes@nd.edi>
Date: Fri, 10 Nov 2017 09:54:28 -0500
Subject: [PATCH 22/22] added some kind of reflection. WE ARE DONE

---
 exercise_10_B.py | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/exercise_10_B.py b/exercise_10_B.py
index 34a9520..c6df0fc 100644
--- a/exercise_10_B.py
+++ b/exercise_10_B.py
@@ -129,14 +129,11 @@ def SIR (y,t0,beta,gamma):
 
 '''
 * observations *
-as gamma gets smaller the max incidence and daily prevalence rises, percent infection rises and repoduction number rises. 
-big gamma, things get smaller
-
-as beta gets bigger the max incidence and daily prevalence rises, percent effectice rises and repo number rises. 
-small beta, things get smaller
-
-so a high beta and a small gamma cause the disease to have a higher rate of infection in the population 
-
+We noticed that if beta is held constant while gamma gets smaller the max incidence, daily prevalence, percent infection, 
+and reproductive number all rise.  Thus a bigger gamma causes, things to get smaller If we hold gamma constant, as  beta
+gets bigger the max incidence, daily prevalence, percent affected, and  reproductive number all rise. Thus a small beta, 
+causes things to get smaller To summarize, a high beta and a small gamma cause the disease to have a higher rate and 
+srpead of infection in the population.
 
 '''