Apply function of two elements

Let say I have a vector x_n of size n, and I want to apply a function to every element, except the first, that depends on the previous element f(x_i, x_(i-1)), how can this be done without looping?

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

3

Can we have some more info please?

– Sotos
Nov 26 '18 at 9:58

2

Note that most of the times "without looping" is just a function that hides a loop inside of it..A reproducible example would help us understand better.

– RLave
Nov 26 '18 at 10:01

if f is vectorized, maybe f(x[-1L], x[-length(x)])?

– chinsoon12
Nov 27 '18 at 1:09

add a comment |

Let say I have a vector x_n of size n, and I want to apply a function to every element, except the first, that depends on the previous element f(x_i, x_(i-1)), how can this be done without looping?

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

3

Can we have some more info please?

– Sotos
Nov 26 '18 at 9:58

2

Note that most of the times "without looping" is just a function that hides a loop inside of it..A reproducible example would help us understand better.

– RLave
Nov 26 '18 at 10:01

if f is vectorized, maybe f(x[-1L], x[-length(x)])?

– chinsoon12
Nov 27 '18 at 1:09

add a comment |

Let say I have a vector x_n of size n, and I want to apply a function to every element, except the first, that depends on the previous element f(x_i, x_(i-1)), how can this be done without looping?

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

Let say I have a vector x_n of size n, and I want to apply a function to every element, except the first, that depends on the previous element f(x_i, x_(i-1)), how can this be done without looping?

r loops apply

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

edited Nov 26 '18 at 9:58

Sotos

31.1k51741

asked Nov 26 '18 at 9:53

Claudio P

1236

asked Nov 26 '18 at 9:53

Claudio P

1236

asked Nov 26 '18 at 9:53

Claudio P

1236

3

Can we have some more info please?

– Sotos
Nov 26 '18 at 9:58

2

Note that most of the times "without looping" is just a function that hides a loop inside of it..A reproducible example would help us understand better.

– RLave
Nov 26 '18 at 10:01

if f is vectorized, maybe f(x[-1L], x[-length(x)])?

– chinsoon12
Nov 27 '18 at 1:09

add a comment |

3

Can we have some more info please?

– Sotos
Nov 26 '18 at 9:58

2

Note that most of the times "without looping" is just a function that hides a loop inside of it..A reproducible example would help us understand better.

– RLave
Nov 26 '18 at 10:01

if f is vectorized, maybe f(x[-1L], x[-length(x)])?

– chinsoon12
Nov 27 '18 at 1:09

Can we have some more info please?

– Sotos
Nov 26 '18 at 9:58

Note that most of the times "without looping" is just a function that hides a loop inside of it..A reproducible example would help us understand better.

– RLave
Nov 26 '18 at 10:01

if f is vectorized, maybe f(x[-1L], x[-length(x)])?

– chinsoon12
Nov 27 '18 at 1:09

add a comment |

1 Answer
1

active

oldest

votes

What about this? But as noted by @RLave *apply is just a loop in disguise:

my_fun<- function(i, x) {

    if(i == 1){

        return(x[i])

    } else {

        return(x[i] + x[i-1])

    }

}



x_n<- c(10, 20, 30, 40 ,50)



sapply(1:length(x_n), my_fun, x_n)

[1] 10 30 50 70 90

answered Nov 26 '18 at 10:18

dariober

1,1411222

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

What about this? But as noted by @RLave *apply is just a loop in disguise:

my_fun<- function(i, x) {

    if(i == 1){

        return(x[i])

    } else {

        return(x[i] + x[i-1])

    }

}



x_n<- c(10, 20, 30, 40 ,50)



sapply(1:length(x_n), my_fun, x_n)

[1] 10 30 50 70 90

answered Nov 26 '18 at 10:18

dariober

1,1411222

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

add a comment |

What about this? But as noted by @RLave *apply is just a loop in disguise:

my_fun<- function(i, x) {

    if(i == 1){

        return(x[i])

    } else {

        return(x[i] + x[i-1])

    }

}



x_n<- c(10, 20, 30, 40 ,50)



sapply(1:length(x_n), my_fun, x_n)

[1] 10 30 50 70 90

answered Nov 26 '18 at 10:18

dariober

1,1411222

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

add a comment |

What about this? But as noted by @RLave *apply is just a loop in disguise:

my_fun<- function(i, x) {

    if(i == 1){

        return(x[i])

    } else {

        return(x[i] + x[i-1])

    }

}



x_n<- c(10, 20, 30, 40 ,50)



sapply(1:length(x_n), my_fun, x_n)

[1] 10 30 50 70 90

answered Nov 26 '18 at 10:18

dariober

1,1411222

What about this? But as noted by @RLave *apply is just a loop in disguise:

my_fun<- function(i, x) {

    if(i == 1){

        return(x[i])

    } else {

        return(x[i] + x[i-1])

    }

}



x_n<- c(10, 20, 30, 40 ,50)



sapply(1:length(x_n), my_fun, x_n)

[1] 10 30 50 70 90

answered Nov 26 '18 at 10:18

dariober

1,1411222

answered Nov 26 '18 at 10:18

dariober

1,1411222

answered Nov 26 '18 at 10:18

dariober

1,1411222

answered Nov 26 '18 at 10:18

dariober

1,1411222

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

add a comment |

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

So there is no performance advantage in using apply? There is not any sort of precompilation when you use it?

– Claudio P
Nov 26 '18 at 11:18

@ClaudioP No, I don't think there is much advantage. See also stackoverflow.com/questions/42393658/… Basically, the main reason for using *apply is readability rather than speed.

– dariober
Nov 26 '18 at 11:32

I do get advantage in using sum or prod instead of looping though or it's false even for those?

– Claudio P
Nov 26 '18 at 11:36

Can you give some example?

– dariober
Nov 26 '18 at 11:41

I guess we are ot, but there is any difference between sum(x) and for( i in 1:length(x)){o=o+x[i]}?, My guess was that sum is an already compiled C function so should be faster.

– Claudio P
Nov 26 '18 at 11:45

add a comment |

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