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# [Tutorial Contents](@id tutorial_home) | ||
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Future Description. | ||
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## Contents | ||
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- [Getting Started](@ref getting_started) | ||
- [Generating simulated data with UCIWWEIHR ODE compartmental based model.](@ref uciwweihr_simulation_data) | ||
- [Generating simulated data with an agent based model.](@ref agent_based_simulation_data) | ||
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# [Generating simulated data with an agent based model.](@id agent_based_simulation_data) | ||
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This package provides a way to also simulate data using the agent based model in the future paper. The function called `generate_simulation_data_agent.jl` can be used to generate synthetic data for a given population size and features. Here we provide a demonstration using the default settings of `generate_simulation_data_agent.jl` : | ||
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## 1. Functionality. | ||
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``` @example tutorial | ||
using UCIWWEIHR | ||
using Plots | ||
# Running simulation function with defaults | ||
df = generate_simulation_data_agent() | ||
first(df, 5) | ||
``` | ||
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## 2. Visualizing SEIHR compartments. | ||
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We can also use the [TidierPlots](https://tidierorg.github.io/TidierPlots.jl/stable/) package to visualize the data generated. | ||
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```@example tutorial | ||
plot(df.Time, df.S, label = "Suseptible", | ||
xlabel = "Time", | ||
ylabel = "Number of Individuals", | ||
title = "Agent Based Model Simulation Results") | ||
plot!(df.Time, df.E, label = "Exposed") | ||
plot!(df.Time, df.I, label = "Infected") | ||
plot!(df.Time, df.H, label = "Hospitalized") | ||
plot!(df.Time, df.R, label = "Recovered") | ||
``` | ||
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### [Tutorial Contents](@ref tutorial_home) |
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# [Getting Started](@id getting_started) | ||
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Welcome to the Tutorials page for the UCIWWEIHR.jl project. This section provides step-by-step guides and examples to help you get started with using the package and understanding its features. | ||
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## 1. Installation. | ||
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To install the UCIWWEIHR.jl package, open the Julia REPL and run the following command: | ||
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``` julia | ||
using Pkg | ||
Pkg.add("UCIWWEIHR") | ||
``` | ||
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### [Tutorial Contents](@ref tutorial_home) |
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# [Generating simulated data with UCIWWEIHR ODE compartmental based model.](@id uciwweihr_simulation_data) | ||
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This package provides a way to also simulate data using the UCIWWEIHR ODE compartmental based model specified in the future paper. The function called `generate_simulation_data_uciwweihr.jl` can be used to generate synthetic data for a given number of samples and features. Here we provide a demonstration using the default settings of `generate_simulation_data_uciwweihr.jl` : | ||
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## 1. Functionality. | ||
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``` @example tutorial | ||
using UCIWWEIHR | ||
using Plots | ||
# Running simulation function with defaults | ||
df = generate_simulation_data_uciwweihr() | ||
first(df, 5) | ||
``` | ||
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## 2. Visualizing UCIWWEIHR model results. | ||
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Here we can make simple plots to visualize the data generated using the [TidierPlots](https://tidierorg.github.io/TidierPlots.jl/stable/) package. | ||
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### 2.1. Concentration of pathogen genome in wastewater(WW). | ||
```@example tutorial | ||
plot(df.obstimes, df.log_ww_conc, | ||
label=nothing, | ||
xlabel="Obstimes", | ||
ylabel="Conc. of Pathogen Genome in WW", | ||
title="Plot of Conc. of Pathogen Genome in WW Over Time") | ||
``` | ||
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### 2.2. Hospitalizations. | ||
```@example tutorial | ||
plot(df.obstimes, df.hosp, | ||
label=nothing, | ||
xlabel="Obstimes", | ||
ylabel="Hosp", | ||
title="Plot of Hosp Over Time") | ||
``` | ||
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### 2.3. Reproductive number. | ||
```@example tutorial | ||
plot(df.obstimes, df.rt, | ||
label=nothing, | ||
xlabel="Obstimes", | ||
ylabel="Rt", | ||
title="Plot of Rt Over Time") | ||
``` | ||
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### [Tutorial Contents](@ref tutorial_home) |
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