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-rw-r--r--out/COVID-19-ESIR-data.csv12
-rw-r--r--out/COVID-19-Linear-data.csv10
-rw-r--r--out/COVID-19-SEIR-data.csv14
-rw-r--r--out/COVID-19-SIR-data.csv10
-rw-r--r--out/SARS-ESIR-data.csv12
-rw-r--r--out/SARS-Linear-data.csv10
-rw-r--r--out/SARS-SEIR-data.csv14
-rw-r--r--out/SARS-SIR-data.csv10
-rw-r--r--solver2.py16
9 files changed, 54 insertions, 54 deletions
diff --git a/out/COVID-19-ESIR-data.csv b/out/COVID-19-ESIR-data.csv
index b929084..fcd8049 100644
--- a/out/COVID-19-ESIR-data.csv
+++ b/out/COVID-19-ESIR-data.csv
@@ -1,6 +1,6 @@
-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
+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-Linear-data.csv b/out/COVID-19-Linear-data.csv
index a4fada7..e4a8a16 100644
--- a/out/COVID-19-Linear-data.csv
+++ b/out/COVID-19-Linear-data.csv
@@ -1,5 +1,5 @@
-Beta: 0.001
-Gamma: 0.001264208619688091
-R0: 0.7910086867203316
-Predicted I: 697.635036958848
-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-SEIR-data.csv b/out/COVID-19-SEIR-data.csv
index 81ae1a4..08a3360 100644
--- a/out/COVID-19-SEIR-data.csv
+++ b/out/COVID-19-SEIR-data.csv
@@ -1,7 +1,7 @@
-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
+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-SIR-data.csv b/out/COVID-19-SIR-data.csv
index a3e4ce6..7c2b68d 100644
--- a/out/COVID-19-SIR-data.csv
+++ b/out/COVID-19-SIR-data.csv
@@ -1,5 +1,5 @@
-Beta: 0.11506078739615723
-Gamma: 0.004484934156558218
-R0: 25.654955765160217
-Predicted I: 1266.8203435457365
-Actual I: 1320.7366666666667 \ No newline at end of file
+Beta, 0.11506078739615723
+Gamma, 0.004484934156558218
+R0, 25.654955765160217
+Predicted I, 1266.8203435457365
+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 7fa0191..0a83b31 100644
--- a/out/SARS-ESIR-data.csv
+++ b/out/SARS-ESIR-data.csv
@@ -1,6 +1,6 @@
-Beta: 0.2367380660038712
-Gamma: 0.08679089871294347
-Mu: 0.10967080829342284
-R0: 1.2050086992077278
-Predicted I: 934.6300578153925
-Actual I: 877.5 \ No newline at end of file
+Beta, 0.2367380660038712
+Gamma, 0.08679089871294347
+Mu, 0.10967080829342284
+R0, 1.2050086992077278
+Predicted I, 934.6300578153925
+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 f41c322..d33e313 100644
--- a/out/SARS-Linear-data.csv
+++ b/out/SARS-Linear-data.csv
@@ -1,5 +1,5 @@
-Beta: 0.002255721398145891
-Gamma: 0.017414910100826592
-R0: 0.12952816782205634
-Predicted I: 946.1041288549815
-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-SEIR-data.csv b/out/SARS-SEIR-data.csv
index 6170d61..71d0ad8 100644
--- a/out/SARS-SEIR-data.csv
+++ b/out/SARS-SEIR-data.csv
@@ -1,7 +1,7 @@
-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
+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-SIR-data.csv b/out/SARS-SIR-data.csv
index de7798e..7abe8bb 100644
--- a/out/SARS-SIR-data.csv
+++ b/out/SARS-SIR-data.csv
@@ -1,5 +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
+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/solver2.py b/solver2.py
index 4511d12..52e245e 100644
--- a/solver2.py
+++ b/solver2.py
@@ -147,8 +147,8 @@ 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}\nR0: {beta/gamma}\n')
- file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}')
+ file.write(f'Beta, {beta}\nGamma, {gamma}\nR0, {beta/gamma}\n')
+ 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,
@@ -163,8 +163,8 @@ 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}\nR0: {beta/gamma}\n')
- file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}')
+ file.write(f'Beta, {beta}\nGamma, {gamma}\nR0, {beta/gamma}\n')
+ 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,
@@ -179,8 +179,8 @@ 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}\nR0: {beta/(gamma + mu)}\n')
- file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}')
+ 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)}\nActual I, {extended_actual[-1] * correction_factor}')
elif args.mode == 'SEIR':
# exposed_data = self.load_exposed(self.country)
@@ -197,8 +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))}\n')
- file.write(f'Predicted I: {prediction.y[1][-1] * int(args.popmodel)}\nActual I: {extended_actual[-1] * correction_factor}')
+ 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)}\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)
generated by cgit v1.2.3-70-g09d2 (git 2.47.1) at 2024-12-22 23:41:19 +0000