From 2485953be4d3b81ae65244b5b31cb5bf2b5f9524 Mon Sep 17 00:00:00 2001 From: Ta180m Date: Sat, 2 May 2020 15:25:32 -0500 Subject: Redo tests --- COVID-19-ESIR.png | Bin 40520 -> 40548 bytes COVID-19-Linear.png | Bin 35357 -> 37147 bytes COVID-19-SIR.png | Bin 40438 -> 40434 bytes README.md | 1 + SARS-ESIR.png | Bin 40906 -> 40882 bytes SARS-Linear.png | Bin 41210 -> 41233 bytes out/COVID-19-ESIR-data.csv | 11 +-- out/COVID-19-ESIR-prediction.csv | 152 ++++++++++++++++++------------------- out/COVID-19-Linear-data.csv | 9 ++- out/COVID-19-Linear-prediction.csv | 152 ++++++++++++++++++------------------- out/COVID-19-SEIR-data.csv | 3 +- out/COVID-19-SIR-data.csv | 9 ++- out/COVID-19-SIR-prediction.csv | 152 ++++++++++++++++++------------------- out/SARS-ESIR-data.csv | 11 +-- out/SARS-ESIR-prediction.csv | 150 ++++++++++++++++++------------------ out/SARS-Linear-data.csv | 9 ++- out/SARS-Linear-prediction.csv | 150 ++++++++++++++++++------------------ out/SARS-SEIR-data.csv | 3 +- out/SARS-SIR-data.csv | 3 +- solver2.py | 8 +- 20 files changed, 416 insertions(+), 407 deletions(-) diff --git a/COVID-19-ESIR.png b/COVID-19-ESIR.png index 5b2d708..64feceb 100644 Binary files a/COVID-19-ESIR.png and b/COVID-19-ESIR.png differ diff --git a/COVID-19-Linear.png b/COVID-19-Linear.png index 2e2c2b9..b624344 100644 Binary files a/COVID-19-Linear.png and b/COVID-19-Linear.png differ diff --git a/COVID-19-SIR.png b/COVID-19-SIR.png index 4497cb1..c309d7e 100644 Binary files a/COVID-19-SIR.png and b/COVID-19-SIR.png differ diff --git a/README.md b/README.md index c352aa0..7c804a9 100644 --- a/README.md +++ b/README.md @@ -14,6 +14,7 @@ For SARS in Hong Kong use For COVID-19 in the US use `./solver2.py --popcountry=3000000 --initial=100 --mode={SIR,Linear,ESIR,SEIR}` +General usage: ``` usage: solver2.py [-h] [--mode {SIR,Linear,ESIR,SEIR}] [--data [{Actual,S,I,R,E} [{Actual,S,I,R,E} ...]]] diff --git a/SARS-ESIR.png b/SARS-ESIR.png index b334cb1..c623bca 100644 Binary files a/SARS-ESIR.png and b/SARS-ESIR.png differ diff --git a/SARS-Linear.png b/SARS-Linear.png index 5bbbf4e..23081fd 100644 Binary files a/SARS-Linear.png and b/SARS-Linear.png differ diff --git a/out/COVID-19-ESIR-data.csv b/out/COVID-19-ESIR-data.csv index 3c6bb37..b929084 100644 --- a/out/COVID-19-ESIR-data.csv +++ b/out/COVID-19-ESIR-data.csv @@ -1,5 +1,6 @@ -Beta: 0.11506079905613333 -Gamma: 0.004485002592721715 -Mu: 1e-08 -R0: 25.654509698111923 -Predicted I: 1266.8145664521824, Actual I: 1320.7366666666667 \ No newline at end of file +Beta: 0.11611254858884054 +Gamma: 0.004524040067261208 +Mu: 0.001 +R0: 21.019497899190398 +Predicted I: 1266.3066498710834 +Actual I: 1320.7366666666667 \ No newline at end of file diff --git a/out/COVID-19-ESIR-prediction.csv b/out/COVID-19-ESIR-prediction.csv index 15ad69e..f11dbc1 100644 --- a/out/COVID-19-ESIR-prediction.csv +++ b/out/COVID-19-ESIR-prediction.csv @@ -1,78 +1,78 @@ ,Actual,S,I,R 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0.0005306298181865554 -Gamma: 0.00121221978960238 -R0: 0.4377340006638624 -Predicted I: 377.76904311879434, Actual I: 1320.7366666666667 \ No newline at end of file +Beta: 0.001 +Gamma: 0.001264208619688091 +R0: 0.7910086867203316 +Predicted I: 697.635036958848 +Actual I: 1320.7366666666667 \ No newline at end of file diff --git a/out/COVID-19-Linear-prediction.csv b/out/COVID-19-Linear-prediction.csv index 656dbe1..f0c09aa 100644 --- a/out/COVID-19-Linear-prediction.csv +++ b/out/COVID-19-Linear-prediction.csv @@ -1,78 +1,78 @@ ,Actual,S,I,R 1/22/20,0.0033333333333333335,9999.666666666666,0.33333333333333337,0.0 -1/23/20,0.0033333333333333335,9994.361952905527,5.6344290411453315,0.003618053328386932 -1/24/20,0.006666666666666667,9989.060053236995,10.926290161791322,0.013656601213288695 -1/25/20,0.006666666666666667,9983.760966168222,16.208929375068454,0.03010445670892412 -1/26/20,0.016666666666666666,9978.46469020716,21.4823593440476,0.052950448791872544 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0.00225573366659839 -Gamma: 0.01741524200420521 -R0: 0.12952640371312119 -Predicted I: 946.0965063014658, Actual I: 877.5 \ No newline at end of file +Beta: 0.002255721398145891 +Gamma: 0.017414910100826592 +R0: 0.12952816782205634 +Predicted I: 946.1041288549815 +Actual I: 877.5 \ No newline at end of file diff --git a/out/SARS-Linear-prediction.csv b/out/SARS-Linear-prediction.csv index d5f8509..0b3866e 100644 --- a/out/SARS-Linear-prediction.csv +++ b/out/SARS-Linear-prediction.csv @@ -1,77 +1,77 @@ ,Actual,S,I,R 4/10/03,499.0,9500.0,500.0,0.0 -4/11/03,529.5,9478.594681592454,512.5877002660018,8.817618141544223 -4/12/03,554.0,9457.237593461185,524.9102776965382,17.852128842276684 -4/14/03,595.0,9435.928626930277,536.9724293164429,27.098943753279666 -4/15/03,616.0,9414.667673579052,548.7787404283372,36.55358599260962 -4/16/03,634.0,9393.45462522877,560.3337228510325,46.21165192019811 -4/17/03,648.5,9372.289373942072,571.6418164995505,56.06880955837544 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+7/9/03,877.5,8075.86398245873,940.9350939026301,983.20092363864 +7/10/03,877.5,8057.667614019998,942.7292361545279,999.6031498254744 +7/11/03,877.5,8039.512245236723,944.4518012215317,1016.0359535417452 +8/7/03,877.5,8021.397783730051,946.1041288549815,1032.4980874149676 diff --git a/out/SARS-SEIR-data.csv b/out/SARS-SEIR-data.csv index 36fe951..6170d61 100644 --- a/out/SARS-SEIR-data.csv +++ b/out/SARS-SEIR-data.csv @@ -3,4 +3,5 @@ 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 +Predicted I: 1009.5304659757634 +Actual I: 877.5 \ No newline at end of file diff --git a/out/SARS-SIR-data.csv b/out/SARS-SIR-data.csv index d6e9dfa..de7798e 100644 --- a/out/SARS-SIR-data.csv +++ b/out/SARS-SIR-data.csv @@ -1,4 +1,5 @@ Beta: 0.031663066064741584 Gamma: 0.018520041050816886 R0: 1.7096650044058612 -Predicted I: 1006.3748700651734, Actual I: 877.5 \ No newline at end of file +Predicted I: 1006.3748700651734 +Actual I: 877.5 \ No newline at end of file diff --git a/solver2.py b/solver2.py index 4f010ae..4511d12 100644 --- a/solver2.py +++ b/solver2.py @@ -148,7 +148,7 @@ class Learner(object): 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}\n') - file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}') + file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}') elif args.mode == 'SIR': optimal = minimize( loss_sir, @@ -164,7 +164,7 @@ class Learner(object): 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}\n') - file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}') + file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}') elif args.mode == 'ESIR': optimal = minimize( loss_esir, @@ -180,7 +180,7 @@ class Learner(object): 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)}\n') - file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}') + file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}') elif args.mode == 'SEIR': # exposed_data = self.load_exposed(self.country) @@ -198,7 +198,7 @@ class Learner(object): 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))}\n') - file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}, Actual I: {extended_actual[-1] * correction_factor}') + file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual 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) -- cgit v1.2.3-70-g09d2