BranchesTags

Repository files navigation

memuse

memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.

Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.

The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.

Installation

To install the R package, run:

install.package("memuse")

The development version is maintained on GitHub:

remotes::install_github("shinra-dev/memuse")

The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.

Package Utilities

The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.

Memory Lookups

With this package you can get some information about how much memory is physically available on the host machine:

Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB

You can find the ram usage of the current R process:

Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB

Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:

Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B

Estimating Memory Usage

You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:

howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB

Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:

howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500

For more information, see the package vignette.

Misc

The package also has some miscellaneous helpful utilities:

approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789

Authors

memuse is authored and maintained by:

  • Drew Schmidt

With additional contributions from:

  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)

About

An R package of utilities for benchmarking and optimization

shinra-dev.github.io/

Topics

memory-estimationr

Resources

Readme
Activity
Custom properties

Stars

49 stars

Watchers

4 watching

Forks

4 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
memuse
memuse is an R package for memory estimation. It has tools for estimating the size of a matrix (that doesn't exist), showing the size of an existing object in a nicer way than object.size(). It also has tools for showing how much memory the current R process is consuming, how much ram is available on the system, and more.
Originally, this package was an over-engineered solution to a mostly non-existent problem, as a sort of love letter to other needlessly complex programs like the Enterprise Fizzbuzz. However, as of version 2.0-0, I'm sad to report that the package is actually becoming quite useful.
The package has been exhaustively tested on Linux, FreeBSD, Windows, Mac, and "other"-NIX. That is also roughly the platforms in descending order of support for the various operations. However, if you have a problem installing or using the package, please open an issue on the project's GitHub repository.
Installation
To install the R package, run:
install.package("memuse")
The development version is maintained on GitHub:
remotes::install_github("shinra-dev/memuse")
The C internals, found in memuse/src/meminfo/ are completely separated from the R wrapper code. So if you prefer, you can easily build this as a standalone C shared library.
Package Utilities
The package comes with several classes of utilities. I find all of them very useful during the course of benchmarking, but some are certainly more useful than others.
Memory Lookups
With this package you can get some information about how much memory is physically available on the host machine:
Sys.meminfo()
# Totalram: 15.656 GiB # Freeram: 10.504 GiB 
Sys.meminfo(compact.free=FALSE) ### Linux and FreeBSD only# Totalram: 15.656 GiB # Freeram: 1.067 GiB # Bufferram: 1.332 GiB # Cachedram: 8.207 GiB 
Sys.swapinfo() ## same as Sys.pageinfo()# Totalswap: 32.596 GiB # Freeswap: 32.595 GiB # Cachedswap: 444.000 KiB 
You can find the ram usage of the current R process:
Sys.procmem()
# Size: 258.426 MiB # Peak: 258.426 MiB x<- rnorm(1e8)
memuse(x)
# 762.939 MiB
rm(x);invisible(gc())
Sys.procmem()
# Size: 258.426 MiB # Peak: 1021.363 MiB 
Also, if you're working close to the metal, you may be interested in seeing how large the CPU caches are and/or how big the cache linesize is:
Sys.cachesize()
# L1I: 32.000 KiB # L1D: 32.000 KiB # L2: 256.000 KiB # L3: 6.000 MiB 
Sys.cachelinesize()
# Linesize: 64 B 
Estimating Memory Usage
You can estimate memory storage requirements of a matrix without having to divide by some annoying power of 2:
howbig(10000, 500)
# 38.147 MiB
howbig(10000, 500, type="int")
# 19.073 MiB
howbig(10000, 500, representation="sparse", sparsity=.05)
# 1.907 MiB
Alternatively, given a (memory) size, you can also find the dimensions of such a matrix:
howmany(mu(800, "mib"))
# [1] 10240 10240
howmany(mu(800, "mib"), ncol=500)
# [1] 209715 500
For more information, see the package vignette.
Misc
The package also has some miscellaneous helpful utilities:
approx.size(12345)
# 12.3 Thousand
approx.size(123456789)
# 123.5 Million
approx.size(123456789, unit.names="short")
# 123.5m
approx.size(123456789, unit.names="comma")
# 123,456,789
Authors
memuse is authored and maintained by:
  • Drew Schmidt
With additional contributions from:
  • Christian Heckendorf (FreeBSD improvements to meminfo)
  • Wei-Chen Chen (Windows build fixes)
  • Dan Burgess (donation of a Mac for development and testing)
About
An R package of utilities for benchmarking and optimization
shinra-dev.github.io/
Topics
memory-estimationr
Resources
Readme
Activity
Custom properties
Stars
49 stars
Watchers
4 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages