# `read.simulation.results`

Read results of an EMOD simulation


## Description

Read results of an EMOD simulation


## Usage

```r
read.simulation.results(
  results_path,
  scenario_name,
  summarize_columns = c("Newly.Infected", "Newly.Tested.Positive",
    "Newly.Tested.Negative", "Population", "Infected", "On_ART", "Died", "Died_from_HIV",
    "Tested.Past.Year.or.On_ART", "Tested.Ever", "Diagnosed"),
  stratify_columns = c("Year", "Gender"),
  min_age_inclusive = 15,
  max_age_inclusive = 49
)
```


## Arguments

Argument      |Description
------------- |----------------
`results_path`     |     string pointing to the folder which contains the ReportHIVByAgeAndGender.csv files
`scenario_name`     |     Provide a string label for the scenario being read in. For example, you might use "baseline" for the baseline scenario.
`summarize_columns`     |     a vector of strings containing names of columns to be aggregated via summation. Note that spaces in column names are replaced by a period ("."). For example, "Newly Infected" becomes "Newly.Infected".
`stratify_columns`     |     a vector of strings containing names of columns by which we will stratify the data. For example, we might want to have a separate row in the dataset for each year, so we would set stratify_columns = c("Year")
`min_age_inclusive`     |     an integer representing the minimum age to keep while reading the data (all ages below will be filtered out)
`max_age_inclusive`     |     an integer representing the maximum age to keep while reading the data (all ages above will be filtered out)


## Details

The results of an EMOD simulation are stored in a series of csv files titled "ReportHIVByAgeAndGender.csv". One of these files exists for each
 simulation run (typically 250 files). This function reads and aggregates those files into a single tibble


## Value

A tibble with columns incidence and Year