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@@ -15,3 +15,5 @@ Rchecks | |
| !package/*.tar.gz | ||
| *00_pkg_src | ||
| inst/maintenance/unit/tests.md | ||
| doc | ||
| Meta | ||
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| --- | ||
| title: "Event objects" | ||
| author: "" | ||
| date: "`r Sys.Date()`" | ||
| output: | ||
| rmarkdown::html_vignette: | ||
| toc: true | ||
| toc_depth: 1 | ||
| number_sections: true | ||
| keep_md: true | ||
| fig_width: 5 | ||
| fig_height: 4 | ||
| vignette: > | ||
| %\VignetteIndexEntry{Event objects} | ||
| %\VignetteEngine{knitr::rmarkdown} | ||
| %\VignetteEncoding{UTF-8} | ||
| --- | ||
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| ```{r setup, echo = FALSE, message = FALSE, warning = FALSE, code = readLines("global.R")} | ||
| set.seed(23) | ||
| ``` | ||
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| ```{r setup2} | ||
| library(mrgsolve) | ||
| library(dplyr) | ||
| ``` | ||
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| # Introduction | ||
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| Event objects are simple ways to implement PK dosing events into your model | ||
| simulation. | ||
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| Let's illustrate event objects with a one-compartment, PK model. We read this | ||
| model from the `mrgsolve` internal model library. | ||
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| ```{r,message=FALSE} | ||
| mod <- modlib("pk1cmt", end = 216, delta = 0.1) | ||
| ``` | ||
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| # Events | ||
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| Events are constructed with the `ev()` function | ||
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| ```{r} | ||
| e <- ev(amt = 100, ii = 24, addl = 6) | ||
| ``` | ||
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| This will implement 100 unit doses every 24 hours for a total of 7 doses. `e` | ||
| has class `ev`, but really it is just a data frame | ||
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| ```{r} | ||
| e | ||
| ``` | ||
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| ```{r} | ||
| as.data.frame(e) | ||
| ``` | ||
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| We can implement this series of doses by passing `e` in as the `events` argument | ||
| to `mrgsim` | ||
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| ```{r} | ||
| mod %>% mrgsim(events = e) %>% plot(EV1 + CP ~ time) | ||
| ``` | ||
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| The events can also be implemented with the `ev` constructor along the | ||
| simulation pipeline | ||
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| ```{r} | ||
| mod %>% | ||
| ev(amt = 100, ii = 24, addl = 6) %>% | ||
| mrgsim %>% | ||
| plot(CP ~ time) | ||
| ``` | ||
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| ## Event defaults and expectations | ||
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| 1. `amt` is required | ||
| 1. `evid = 0` is forbidden | ||
| 1. Default `time` is 0 | ||
| 1. Default `evid` is 1 | ||
| 1. Default `cmt` is 1 | ||
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| Also by default, `rate`, `ss` and `ii` are 0. | ||
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| # Combine events | ||
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| `mrgsolve` has operators defined that allow you to combine events. Let's first | ||
| define some event objects. | ||
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| ```{r} | ||
| e1 <- ev(amt = 500) | ||
| e2 <- ev(amt = 250, ii = 24, addl = 4) | ||
| e3 <- ev(amt = 500, ii = 24, addl = 0) | ||
| e4 <- ev(amt = 250, ii = 24, addl = 4, time = 24) | ||
| ``` | ||
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| We can combine `e1` and `e3` with a collection operator | ||
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| ```{r} | ||
| c(e1, e4) | ||
| ``` | ||
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| `mrgsolve` also defines a `%then$` operator that lets you execute one event and | ||
| `%then%` a second event | ||
| ```{r} | ||
| e3 %then% e2 | ||
| ``` | ||
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| Notice that `e3` has both `ii` and `addl` defined. This is required for | ||
| `mrgsolve` to know when to start `e2`. | ||
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| ## Combine to create a data set | ||
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| We can take several event objects and combine them into a single simulation data | ||
| frame with the `as_data_set` function. | ||
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| ```{r} | ||
| e1 <- ev(amt = 100, ii = 24, addl = 6, ID = 1:5) | ||
| e2 <- ev(amt = 50, ii = 12, addl = 13, ID = 1:3) | ||
| e3 <- ev(amt = 200, ii = 24, addl = 2, ID = 1:2) | ||
| ``` | ||
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| When combined into a data set, we get | ||
| * N=5 IDs receiving 100 mg Q24h x7 | ||
| * N=3 IDs receiving 50 mg Q12h x 14 | ||
| * N=2 IDs receiving 200 mg Q48h x 3 | ||
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| ```{r} | ||
| data <- as_data_set(e1, e2, e3) | ||
| data | ||
| ``` | ||
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| To simulate from this data set, we use the `data_set` function. First, let's | ||
| load a population PK model | ||
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| ```{r,message=FALSE} | ||
| mod <- modlib("popex") | ||
| ``` | ||
| ```{r} | ||
| mod %>% data_set(data) %>% mrgsim(end=336) %>% plot("GUT, DV") | ||
| ``` | ||
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| knitr::opts_chunk$set(message = FALSE, warning = FALSE, comment='.') | ||
| options(mrgsolve.soloc = "mrgsolve-builds") |
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