Hi all, Let's say I have a vector: vv<-c(1,2,3) And suppose I have a function f(a,b), which is a function of 2 scalar inputs. I would like to evaluate this function separately for each element of the vv vector while the second input to f( ) will be the previous output from f( ). So, the valuation of f() has a dependency on the previous f( ) valuation (recursive). This type of calculation is easy to set up with a for loop but that will run slow. How can I achieve this with apply family of functions please? I have the same question for the case when vv is a data.table instead of a vector. Thank you for any help.
Using lapply when there are dependencies
5 messages · PIKAL Petr, David Winsemius, blue honour +1 more
Hi
-----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of blue honour via R-help Sent: Thursday, May 28, 2015 1:34 AM To: r-help at r-project.org Subject: [R] Using lapply when there are dependencies Hi all, Let's say I have a vector: vv<-c(1,2,3) And suppose I have a function f(a,b), which is a function of 2 scalar inputs. I would like to evaluate this function separately for each element of the vv vector while the second input to f( ) will be the previous output from f( ). So, the valuation of f() has a dependency on the previous f( ) valuation (recursive). This type of calculation is easy to set up with a for loop but that will run slow. How can I
*apply is a hidden loop so there shall not be substantial speed improvement. Usually slow for loop means there is some coding issue which is unnecessary and shall be changed to vectorized. But without actual code it is hard to say. Cheers Petr
achieve this with apply family of functions please? I have the same question for the case when vv is a data.table instead of a vector. Thank you for any help.
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting- guide.html and provide commented, minimal, self-contained, reproducible code.
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On May 27, 2015, at 4:34 PM, blue honour via R-help wrote:
Hi all, Let's say I have a vector: vv<-c(1,2,3) And suppose I have a function f(a,b), which is a function of 2 scalar inputs. I would like to evaluate this function separately for each element of the vv vector while the second input to f( ) will be the previous output from f( ). So, the valuation of f() has a dependency on the previous f( ) valuation (recursive). This type of calculation is easy to set up with a for loop but that will run slow. How can I achieve this with apply family of functions please?
The speed of loops is determined by the speed of their inner functions. The Reduce() function does what you request but for the application described it will need an init value. Reduce(f, vv, init=<something>)
I have the same question for the case when vv is a data.table instead of a vector.
I could be wrong but that doesn't sound like an effective use of the data.table facilities.
David Winsemius Alameda, CA, USA
Thank you. May I ask, what would you recommend reading in order to learn how to vectorise loops with dependencies using data.table facilities? I have been searching online on this topic since last night but no luck yet. --------------------------------------------
On Thu, 5/28/15, David Winsemius <dwinsemius at comcast.net> wrote:
Subject: Re: [R] Using lapply when there are dependencies Cc: r-help at r-project.org Date: Thursday, May 28, 2015, 7:02 AM On May
27, 2015, at 4:34 PM, blue honour via R-help wrote:
> Hi all, > > Let's say I have a vector: > > vv<-c(1,2,3) > > > And suppose I have a function f(a,b), which is a function of 2 scalar inputs. I would like to evaluate this function separately for each element of the vv vector while the second input to f( ) will be the previous output from f( ). So, the valuation of f() has a dependency on the previous f( ) valuation (recursive). This type of calculation is easy to set up with a for loop but that will run slow. How can I achieve this with apply family of functions please? The speed of loops is determined by the speed of their inner functions. The Reduce() function does what you request but for the application described it will need an init value. Reduce(f, vv, init=<something>) > I have the same question for the case when vv is a data.table instead of a vector. I could be wrong but that doesn't sound like an effective use of the data.table facilities. -- David Winsemius Alameda, CA, USA
For loops are not slow. Inefficient memory management in for loops is slow. Feel free to preallocate your output vectors and write for loops to your heart's content. If you really want speed you can write this in C++ using Rcpp [1]. If your f() is a standard digital filter algorithm this has already been done for you (see ?filter). [1] https://stat.ethz.ch/pipermail/r-help//2014-December/424027.html --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity.
On May 27, 2015 4:34:01 PM PDT, blue honour via R-help <r-help at r-project.org> wrote:
Hi all, Let's say I have a vector: vv<-c(1,2,3) And suppose I have a function f(a,b), which is a function of 2 scalar inputs. I would like to evaluate this function separately for each element of the vv vector while the second input to f( ) will be the previous output from f( ). So, the valuation of f() has a dependency on the previous f( ) valuation (recursive). This type of calculation is easy to set up with a for loop but that will run slow. How can I achieve this with apply family of functions please? I have the same question for the case when vv is a data.table instead of a vector. Thank you for any help.
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.