simmer.plot | Plotting Methods for 'simmer | Data Visualization library

by r-simmer R Version: v0.1.17 License: Non-SPDX

X-Ray Key Features Code Snippets(2)Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | simmer.plot Summary

simmer.plot is a R library typically used in Analytics, Data Visualization applications. simmer.plot has no bugs, it has no vulnerabilities and it has low support. However simmer.plot has a Non-SPDX License. You can download it from GitHub.

simmer.plot provides plotting methods for simmer, the Discrete-Event Simulation (DES) package for R.

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Support

simmer.plot has a low active ecosystem.

It has 10 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 22 have been closed. On average issues are closed in 110 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of simmer.plot is v0.1.17

Quality

simmer.plot has no bugs reported.

Security

simmer.plot has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

simmer.plot has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

simmer.plot releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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simmer.plot Key Features

No Key Features are available at this moment for simmer.plot.

simmer.plot Examples and Code Snippets

,Installation

Lines of Code : 3

License : Non-SPDX (NOASSERTION)

Copy

install.packages("simmer.plot")

# install.packages("remotes")
remotes::install_github("r-simmer/simmer.plot")

,Documentation

Lines of Code : 1

License : Non-SPDX (NOASSERTION)

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vignette(package = "simmer.plot")

Community Discussions

Trending Discussions on simmer.plot

Importing a package's S3 methods without importing its functions

Simmer plot resource usage by attributes

R Simmer - lapply on simulation environments built with a loop resulting in identical simulations

R Simmer: "no arrival running" errors when specifying a non-standard routing algorithm

R and Simmer: Performance boost on large data frames

QUESTION

Importing a package's S3 methods without importing its functions

Asked 2020-Jan-15 at 11:46

I have the following dependency chain in a package I'm developing:

My package uses a class (trajectory) defined in package A (simmer).
It also uses an S3 method for that class (plot.trajectory), which is defined in package B (simmer.plot).
I can import package A as a whole, but I cannot import package B as a whole, because it contains replacements for other functions defined in package A (the get_mon functions), so I get unwanted warnings about the original functions being replaced.

How do I use/import the S3 method without importing the rest of package B, preferably via roxygen2?

The roxygen2 documentation suggests the following:

If you want to add a new method to an S3 generic, import it with @importFrom pkg generic.

For my example, this would be @importFrom simmer.plot plot, but this returns a warning that plot is not exported by simmer.plot. The same thing happens if I import the generic first, using @importFrom graphics plot.

...

ANSWER

Answered 2020-Jan-11 at 18:36

Use (see this):

Source https://stackoverflow.com/questions/59647444

QUESTION

Simmer plot resource usage by attributes

Asked 2019-Dec-14 at 00:02

Is is possible to plot resource usage by attribute in simmer? So for example in this simulation:

...

ANSWER

Answered 2019-Dec-14 at 00:02

You could get the service and waiting times per resource from the arrival table with get_mon_arrivals(env, per_resource=TRUE). Then, get the name<->gender correspondence from the attributes table with get_mon_attributes(env), join the tables and, finally, reconstruct the server usage by gender using the time series. But that's a bit challenging. Doable, but it requires some work.

I would just increment/decrement some auxiliary global variables based on that attribute to keep the count for me.

Source https://stackoverflow.com/questions/59219446

QUESTION

R Simmer - lapply on simulation environments built with a loop resulting in identical simulations

Asked 2019-Aug-03 at 11:28

I have created the following MWE to illustrate the code. Consider a system with 20 queues and servers (such that for each server there is a FCFS queue). When an arrival comes, it takes the shortest. Say you wish to compare 20 simulations, each 400 over units of time from start to finish.

You can see in my code that the queues are added using a for loop (indeed, this becomes necessary when simulating asymptotically large queueing systems).

...

ANSWER

Answered 2019-Aug-03 at 11:28

The simulation environment, as every environment in R, has reference semantics. Therefore, here

Source https://stackoverflow.com/questions/57319358

QUESTION

R Simmer: "no arrival running" errors when specifying a non-standard routing algorithm

Asked 2019-Jun-07 at 21:42

Consider the system and routing algorithm specified below: Image of the system. Let us first define some attributes which will be useful in the simulation:

...

ANSWER

Answered 2019-Jun-07 at 21:42

The function get_attribute cannot be called directly. Instead, it must be placed inside a function that is called during the simulation.

Source https://stackoverflow.com/questions/56470815

QUESTION

R and Simmer: Performance boost on large data frames

Asked 2018-Nov-15 at 13:32

I've got on own dataframe on actual events/task and I use the simmer r package to simulate how many task can be done if different resources were available. My simulation runs very fast up to 120.000 rows within my dataframe.

...

ANSWER

Answered 2018-Nov-15 at 13:32

I took your table and simply replicated it to build 100k and 400k datasets, and I confirm the issue: the execution time is not linear.

Internally, attributes are always double, so there are lots of conversions, row by row, which apparently take most of the execution time (!). Try converting your table before feeding it into simmer. Using dplyr,

Source https://stackoverflow.com/questions/53283052

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