Logged more data

16 files changed, 284 insertions, 278 deletions

diff --git a/COVID-19-SEIR.png b/COVID-19-SEIR.png
index d44ed9d..765ea68 100644
--- a/COVID-19-SEIR.png
+++ b/COVID-19-SEIR.png
diff --git a/README.md b/README.md
index 2ba58f1..a22aa08 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,19 @@
 # Infectious-Disease-Modeling
 
-Original code by [JasonXu314](https://github.com/JasonXu314/covid-19-project/) and [Lewuathe](https://github.com/Lewuathe/COVID19-SIR)
+A project to modeling infectious diseases with the SIR model and variations.
+
+![](https://raw.githubusercontent.com/Ta180m/Infectious-Disease-Modeling/master/SARS-ESIR.png)
+
+![](https://raw.githubusercontent.com/Ta180m/Infectious-Disease-Modeling/master/COVID-19-ESIR.png)
+
+## Usage
 
 For SARS in Hong Kong use  
-`./solver2.py --country=Hong_Kong --popcountry=20000 --initial=1000 --disease=SARS --start=4/10/03`
+`./solver2.py --country=Hong_Kong --popcountry=20000 --initial=1000 --disease=SARS --start=4/10/03 --mode={SIR,Linear,ESIR,SEIR}`
 
 For COVID-19 in the US use  
-`./solver2.py --popcountry=3000000 --initial=100`
-
+`./solver2.py --popcountry=3000000 --initial=100 --mode={SIR,Linear,ESIR,SEIR}`
 
-## Usage
 ```
 usage: solver2.py [-h] [--mode {SIR,Linear,ESIR,SEIR}]
                   [--data [{Actual,S,I,R,E} [{Actual,S,I,R,E} ...]]]
@@ -56,4 +60,8 @@ optional arguments:
                         the population of the model (defaults to 10000)
   --initial INITIAL, -I INITIAL
                         initial infected people (defaults to 1)
-```
\ No newline at end of file
+```
+
+## Credits
+
+Original code by [JasonXu314](https://github.com/JasonXu314/covid-19-project/) and [Lewuathe](https://github.com/Lewuathe/COVID19-SIR)
\ No newline at end of file
diff --git a/SARS-SEIR.png b/SARS-SEIR.png
index b0187aa..9e5b74b 100644
--- a/SARS-SEIR.png
+++ b/SARS-SEIR.png
diff --git a/SARS-SIR.png b/SARS-SIR.png
index d9332e0..1321854 100644
--- a/SARS-SIR.png
+++ b/SARS-SIR.png
diff --git a/out/COVID-19-ESIR-data.csv b/out/COVID-19-ESIR-data.csv
index e16f0d7..3c6bb37 100644
--- a/out/COVID-19-ESIR-data.csv
+++ b/out/COVID-19-ESIR-data.csv
@@ -1,4 +1,5 @@
 Beta: 0.11506079905613333
 Gamma: 0.004485002592721715
 Mu: 1e-08
-R0: 25.654509698111923
\ No newline at end of file
+R0: 25.654509698111923
+Predicted I: 1266.8145664521824, Actual I: 1320.7366666666667
\ No newline at end of file
diff --git a/out/COVID-19-Linear-data.csv b/out/COVID-19-Linear-data.csv
index b204797..d0469e1 100644
--- a/out/COVID-19-Linear-data.csv
+++ b/out/COVID-19-Linear-data.csv
@@ -1,3 +1,4 @@
 Beta: 0.0005306298181865554
 Gamma: 0.00121221978960238
-R0: 0.4377340006638624
\ No newline at end of file
+R0: 0.4377340006638624
+Predicted I: 377.76904311879434, Actual I: 1320.7366666666667
\ No newline at end of file
diff --git a/out/COVID-19-SEIR-data.csv b/out/COVID-19-SEIR-data.csv
index 98e5f69..4b2d494 100644
--- a/out/COVID-19-SEIR-data.csv
+++ b/out/COVID-19-SEIR-data.csv
@@ -1,5 +1,6 @@
-Beta: 0.11054937398441604
-Gamma: 1e-08
-Mu: 1e-08
-Sigma: 0.0009697697322082875
-R0: 5527411.7020644825
\ No newline at end of file
+Beta: 0.11054352661813334
+Gamma: 0.001
+Mu: 0.0009999999999999992
+Sigma: 0.005265008086429555
+R0: 46.4494661074415
+Predicted I: 1267.3615656181303, Actual I: 1320.7366666666667
\ No newline at end of file
diff --git a/out/COVID-19-SEIR-prediction.csv b/out/COVID-19-SEIR-prediction.csv
index 216cf0d..5a6f3a1 100644
--- a/out/COVID-19-SEIR-prediction.csv
+++ b/out/COVID-19-SEIR-prediction.csv
@@ -1,78 +1,78 @@
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+4/5/20,1123.5500000000002,8967.254451847157,1042.021850099939,-19.407643870288563
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diff --git a/out/COVID-19-SIR-data.csv b/out/COVID-19-SIR-data.csv
index 68fc931..a0805e1 100644
--- a/out/COVID-19-SIR-data.csv
+++ b/out/COVID-19-SIR-data.csv
@@ -1,3 +1,4 @@
 Beta: 0.11506051868918243
 Gamma: 0.004484787817138545
-R0: 25.65573297570077
\ No newline at end of file
+R0: 25.65573297570077
+Predicted I: 1266.8105911330124, Actual I: 1320.7366666666667
\ No newline at end of file
diff --git a/out/SARS-ESIR-data.csv b/out/SARS-ESIR-data.csv
index 3ec411f..21d4469 100644
--- a/out/SARS-ESIR-data.csv
+++ b/out/SARS-ESIR-data.csv
@@ -1,4 +1,5 @@
 Beta: 0.2367418297398915
 Gamma: 0.08679182290949222
 Mu: 0.10967338538708958
-R0: 1.205006381498899
\ No newline at end of file
+R0: 1.205006381498899
+Predicted I: 934.6265172952101, Actual I: 877.5
\ No newline at end of file
diff --git a/out/SARS-Linear-data.csv b/out/SARS-Linear-data.csv
index 47d9faa..a322350 100644
--- a/out/SARS-Linear-data.csv
+++ b/out/SARS-Linear-data.csv
@@ -1,3 +1,4 @@
 Beta: 0.00225573366659839
 Gamma: 0.01741524200420521
-R0: 0.12952640371312119
\ No newline at end of file
+R0: 0.12952640371312119
+Predicted I: 946.0965063014658, Actual I: 877.5
\ No newline at end of file
diff --git a/out/SARS-SEIR-data.csv b/out/SARS-SEIR-data.csv
index face094..36fe951 100644
--- a/out/SARS-SEIR-data.csv
+++ b/out/SARS-SEIR-data.csv
@@ -1,5 +1,6 @@
-Beta: 0.01082548864886504
-Gamma: 1e-08
-Mu: 1e-08
-Sigma: 0.0010246938312194157
-R0: 541269.1501908005
\ No newline at end of file
+Beta: 0.025728454417841363
+Gamma: 0.001
+Mu: 0.001
+Sigma: 0.5156784257190153
+R0: 12.83932927130887
+Predicted I: 1009.5304659757634, Actual I: 877.5
\ No newline at end of file
diff --git a/out/SARS-SEIR-prediction.csv b/out/SARS-SEIR-prediction.csv
index fb009fd..b5ab71d 100644
--- a/out/SARS-SEIR-prediction.csv
+++ b/out/SARS-SEIR-prediction.csv
@@ -1,77 +1,77 @@
 ,Actual,S,I,R
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diff --git a/out/SARS-SIR-data.csv b/out/SARS-SIR-data.csv
index b8e7f28..d6e9dfa 100644
--- a/out/SARS-SIR-data.csv
+++ b/out/SARS-SIR-data.csv
@@ -1,3 +1,4 @@
-Beta: 0.031662971068960946
-Gamma: 0.018519768809938723
-R0: 1.7096850070811285
\ No newline at end of file
+Beta: 0.031663066064741584
+Gamma: 0.018520041050816886
+R0: 1.7096650044058612
+Predicted I: 1006.3748700651734, Actual I: 877.5
\ No newline at end of file
diff --git a/out/SARS-SIR-prediction.csv b/out/SARS-SIR-prediction.csv
index 9a3a4c5..ba1c85f 100644
--- a/out/SARS-SIR-prediction.csv
+++ b/out/SARS-SIR-prediction.csv
@@ -1,77 +1,77 @@
 ,Actual,S,I,R
 4/10/03,499.0,9500.0,500.0,0.0
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diff --git a/solver2.py b/solver2.py
index 4074988..4f010ae 100644
--- a/solver2.py
+++ b/solver2.py
@@ -18,7 +18,7 @@ parser.add_argument('--disease', '-D', dest = 'disease', default = 'COVID-19', h
 parser.add_argument('--out', '-o', dest = 'out', default = None, help = 'the name of the graph and csv files; defaults to the name of the disease')
 parser.add_argument('--start', '-s', dest = 'start', default = '1/22/20', help = 'the date where the data starts (defaults to the start date of COVID-19 (1/22/20))')
 parser.add_argument('--end', '-e', dest = 'end', default = None, help = 'the date where the data stops (defaults to whereever the input data ends)')
-parser.add_argument('--incubation', '-i', dest = 'incubation_period', default = None, help = 'the incubation period of the disease (only applicable if using SIRE model; ignored otherwise); none by default')
+parser.add_argument('--incubation', '-i', dest = 'incubation_period', default = None, help = 'the incubation period of the disease (only applicable if using SEIR model; ignored otherwise); none by default')
 parser.add_argument('--predict', '-p', dest = 'prediction_range', default = None, help = 'the number of days to predict the course of the disease (defaults to None, meaning the model will not predict beyond the given data)')
 parser.add_argument('--country', '-c', dest = 'country', default = 'US', help = 'the country that is being modeled (defaults to US)')
 parser.add_argument('--popcountry', '-pc', dest = 'popcountry', default = '3328200000', help = 'the population of the country (defaults to US population)')
@@ -72,20 +72,6 @@ class Learner(object):
 		
 		return out
 
-	def load_exposed(self, country):
-		"""
-			Load data for exposed persons 
-		"""
-		df = pd.read_csv(f'{args.folder}/{args.disease}-Exposed.csv')
-		country_df = df[df['Country/Region'] == country]
-
-		if args.end != None:
-			out = country_df.iloc[0].loc[args.start:args.end]
-		else:
-			out = country_df.iloc[0].loc[args.start:]
-		
-		return out
-
 
 	def extend_index(self, index, new_size):
 		values = index.values
@@ -131,7 +117,7 @@ class Learner(object):
 		extended_actual = np.concatenate((data.values.flatten(), [0] * (size - len(data.values))))
 
 		if args.mode == 'SEIR':
-			result = solve_ivp(model, [0, size], [S_0,I_0,R_0,E_0], t_eval=np.arange(0, size, 1))
+			result = solve_ivp(model, [0, size], [S_0,I_0,R_0,E_0], t_eval=np.arange(0, size, 1), vectorized=True)
 		else:
 			result = solve_ivp(model, [0, size], [S_0,I_0,R_0], t_eval=np.arange(0, size, 1), vectorized=True)
 
@@ -150,10 +136,10 @@ class Learner(object):
 		if args.mode == 'Linear':
 			optimal = minimize(
 				loss_linear,
-				[0.001, 0.001],
+				[0.01, 0.01],
 				args=(confirmed_data, recovered_data),
 				method='L-BFGS-B',
-				bounds=[(0.00000001, 0.4), (0.00000001, 0.4)]
+				bounds=[(0.001, 1.0), (0.001, 1.0)]
 			)
 			beta, gamma = optimal.x
 			print(f'Beta: {beta}, Gamma: {gamma}, R0: {beta/gamma}')
@@ -161,14 +147,15 @@ class Learner(object):
 			print(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 			df = compose_df(prediction, extended_actual, correction_factor, new_index)
 			with open(f'out/{args.disease}-{args.mode}-data.csv', 'w+') as file:
-				file.write(f'Beta: {beta}\nGamma: {gamma}\nR0: {beta/gamma}')
+				file.write(f'Beta: {beta}\nGamma: {gamma}\nR0: {beta/gamma}\n')
+				file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 		elif args.mode == 'SIR':
 			optimal = minimize(
 				loss_sir,
-				[0.001, 0.001],
+				[0.01, 0.01],
 				args=(confirmed_data, recovered_data),
 				method='L-BFGS-B',
-				bounds=[(0.00000001, 0.4), (0.00000001, 0.4)]
+				bounds=[(0.001, 1.0), (0.001, 1.0)]
 			)
 			beta, gamma = optimal.x
 			print(f'Beta: {beta}, Gamma: {gamma}, R0: {beta/gamma}')
@@ -176,14 +163,15 @@ class Learner(object):
 			print(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 			df = compose_df(prediction, extended_actual, correction_factor, new_index)
 			with open(f'out/{args.disease}-{args.mode}-data.csv', 'w+') as file:
-				file.write(f'Beta: {beta}\nGamma: {gamma}\nR0: {beta/gamma}')
+				file.write(f'Beta: {beta}\nGamma: {gamma}\nR0: {beta/gamma}\n')
+				file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 		elif args.mode == 'ESIR':
 			optimal = minimize(
 				loss_esir,
-				[0.001, 0.001, 0.001],
+				[0.01, 0.01, 0.01],
 				args=(confirmed_data, recovered_data),
 				method='L-BFGS-B',
-				bounds=[(0.00000001, 0.4), (0.00000001, 0.4), (0.00000001, 0.4)]
+				bounds=[(0.001, 1.0), (0.001, 1.0), (0.001, 1.0)]
 			)
 			beta, gamma, mu = optimal.x
 			print(f'Beta: {beta}, Gamma: {gamma}, Mu: {mu} R0: {beta/(gamma + mu)}')
@@ -191,16 +179,17 @@ class Learner(object):
 			print(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 			df = compose_df(prediction, extended_actual, correction_factor, new_index)
 			with open(f'out/{args.disease}-{args.mode}-data.csv', 'w+') as file:
-				file.write(f'Beta: {beta}\nGamma: {gamma}\nMu: {mu}\nR0: {beta/(gamma + mu)}')
+				file.write(f'Beta: {beta}\nGamma: {gamma}\nMu: {mu}\nR0: {beta/(gamma + mu)}\n')
+				file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 		elif args.mode == 'SEIR':
 			# exposed_data = self.load_exposed(self.country)
 
 			optimal = minimize(
 				loss_seir,
-				[0.001, 0.001, 0.001, 0.001],
+				[0.01, 0.01, 0.01, 0.01],
 				args=(confirmed_data, recovered_data),
 				method='L-BFGS-B',
-				bounds=[(0.00000001, 0.4), (0.00000001, 0.4), (0.00000001, 0.4), (0.00000001, 0.4)]
+				bounds=[(0.001, 1.0), (0.001, 1.0), (0.001, 1.0), (0.001, 1.0)]
 			)
 			beta, gamma, mu, sigma = optimal.x
 			print(f'Beta: {beta}, Gamma: {gamma}, Mu: {mu}, Sigma: {sigma} R0: {(beta * sigma)/((mu + gamma) * (mu + sigma))}')
@@ -208,7 +197,8 @@ class Learner(object):
 			print(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 			df = compose_df(prediction, extended_actual, correction_factor, new_index)
 			with open(f'out/{args.disease}-{args.mode}-data.csv', 'w+') as file:
-				file.write(f'Beta: {beta}\nGamma: {gamma}\nMu: {mu}\nSigma: {sigma}\nR0: {(beta * sigma)/((mu + gamma) * (mu + sigma))}')
+				file.write(f'Beta: {beta}\nGamma: {gamma}\nMu: {mu}\nSigma: {sigma}\nR0: {(beta * sigma)/((mu + gamma) * (mu + sigma))}\n')
+				file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}')
 		fig, ax = plt.subplots(figsize=(15, 10))
 		ax.set_title(f'{args.disease} cases over time ({args.mode} Model)')
 		df.plot(ax=ax)