Evaluating polynomial with function











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0
down vote

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Im trying to evaluate a polynomial P(x):
polynomial



However i dont think im entering the polynomial itself correctly in my function.
Code for function:



directpoly1 <- function(x, coef, seqcoef = seq(coef) - 1) {
sum(coef*x^seqcoef)
}
directpoly <- function(x, coef) {
seqcoef <- seq(coef) - 1
sapply(x, directpoly1, coef, seqcoef)
}


Code for using function:



directpoly(x=seq(-10,10, length=5000000), rep(c(2,-1),20))


Any ideas on how to enter it correctly?










share|improve this question


















  • 1




    Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
    – Rui Barradas
    Nov 13 at 12:22












  • Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
    – torvin
    Nov 13 at 12:27















up vote
0
down vote

favorite












Im trying to evaluate a polynomial P(x):
polynomial



However i dont think im entering the polynomial itself correctly in my function.
Code for function:



directpoly1 <- function(x, coef, seqcoef = seq(coef) - 1) {
sum(coef*x^seqcoef)
}
directpoly <- function(x, coef) {
seqcoef <- seq(coef) - 1
sapply(x, directpoly1, coef, seqcoef)
}


Code for using function:



directpoly(x=seq(-10,10, length=5000000), rep(c(2,-1),20))


Any ideas on how to enter it correctly?










share|improve this question


















  • 1




    Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
    – Rui Barradas
    Nov 13 at 12:22












  • Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
    – torvin
    Nov 13 at 12:27













up vote
0
down vote

favorite









up vote
0
down vote

favorite











Im trying to evaluate a polynomial P(x):
polynomial



However i dont think im entering the polynomial itself correctly in my function.
Code for function:



directpoly1 <- function(x, coef, seqcoef = seq(coef) - 1) {
sum(coef*x^seqcoef)
}
directpoly <- function(x, coef) {
seqcoef <- seq(coef) - 1
sapply(x, directpoly1, coef, seqcoef)
}


Code for using function:



directpoly(x=seq(-10,10, length=5000000), rep(c(2,-1),20))


Any ideas on how to enter it correctly?










share|improve this question













Im trying to evaluate a polynomial P(x):
polynomial



However i dont think im entering the polynomial itself correctly in my function.
Code for function:



directpoly1 <- function(x, coef, seqcoef = seq(coef) - 1) {
sum(coef*x^seqcoef)
}
directpoly <- function(x, coef) {
seqcoef <- seq(coef) - 1
sapply(x, directpoly1, coef, seqcoef)
}


Code for using function:



directpoly(x=seq(-10,10, length=5000000), rep(c(2,-1),20))


Any ideas on how to enter it correctly?







r polynomials






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 13 at 12:04









torvin

284




284








  • 1




    Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
    – Rui Barradas
    Nov 13 at 12:22












  • Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
    – torvin
    Nov 13 at 12:27














  • 1




    Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
    – Rui Barradas
    Nov 13 at 12:22












  • Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
    – torvin
    Nov 13 at 12:27








1




1




Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
– Rui Barradas
Nov 13 at 12:22






Try seqcoef = seq_along(coef). This means you will need to include the zero coefficients in the vector coef.
– Rui Barradas
Nov 13 at 12:22














Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
– torvin
Nov 13 at 12:27




Thx! Can you see if im using the function correctly, so when evaluating P(x) with my function, is P(x) then correctly typed in?
– torvin
Nov 13 at 12:27












1 Answer
1






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oldest

votes

















up vote
0
down vote



accepted










Here are two ways of writing your function.




  1. With a sapply loop. Makes the code more readable and some times faster.

  2. With a standard for loop.


There is no need to write a separate function outside the function to be called with the x values, I have placed that function in the body of the main functions.

Then both functions are tested, with a smaller input vector. As you can see, the for loop function is faster.



directpoly <- function(x, n = 39, coef = NULL){
f <- function(y) sum(coef * y^seqcoef)
if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
seqcoef <- rev(seq_along(coef) - 1)
sapply(x, f)
}

directpoly2 <- function(x, n = 39, coef = NULL){
f <- function(y) sum(coef * y^seqcoef)
if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
seqcoef <- rev(seq_along(coef) - 1)
y <- numeric(length(x))
for(i in seq_along(y))
y[i] <- f(x[i])
y
}

library(microbenchmark)
library(ggplot2)

x <- seq(-10, 10, length = 50000)
mb <- microbenchmark(
Sapply = directpoly(x),
Forloop = directpoly2(x)
)

autoplot(mb)


enter image description here






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    1 Answer
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    up vote
    0
    down vote



    accepted










    Here are two ways of writing your function.




    1. With a sapply loop. Makes the code more readable and some times faster.

    2. With a standard for loop.


    There is no need to write a separate function outside the function to be called with the x values, I have placed that function in the body of the main functions.

    Then both functions are tested, with a smaller input vector. As you can see, the for loop function is faster.



    directpoly <- function(x, n = 39, coef = NULL){
    f <- function(y) sum(coef * y^seqcoef)
    if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
    seqcoef <- rev(seq_along(coef) - 1)
    sapply(x, f)
    }

    directpoly2 <- function(x, n = 39, coef = NULL){
    f <- function(y) sum(coef * y^seqcoef)
    if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
    seqcoef <- rev(seq_along(coef) - 1)
    y <- numeric(length(x))
    for(i in seq_along(y))
    y[i] <- f(x[i])
    y
    }

    library(microbenchmark)
    library(ggplot2)

    x <- seq(-10, 10, length = 50000)
    mb <- microbenchmark(
    Sapply = directpoly(x),
    Forloop = directpoly2(x)
    )

    autoplot(mb)


    enter image description here






    share|improve this answer

























      up vote
      0
      down vote



      accepted










      Here are two ways of writing your function.




      1. With a sapply loop. Makes the code more readable and some times faster.

      2. With a standard for loop.


      There is no need to write a separate function outside the function to be called with the x values, I have placed that function in the body of the main functions.

      Then both functions are tested, with a smaller input vector. As you can see, the for loop function is faster.



      directpoly <- function(x, n = 39, coef = NULL){
      f <- function(y) sum(coef * y^seqcoef)
      if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
      seqcoef <- rev(seq_along(coef) - 1)
      sapply(x, f)
      }

      directpoly2 <- function(x, n = 39, coef = NULL){
      f <- function(y) sum(coef * y^seqcoef)
      if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
      seqcoef <- rev(seq_along(coef) - 1)
      y <- numeric(length(x))
      for(i in seq_along(y))
      y[i] <- f(x[i])
      y
      }

      library(microbenchmark)
      library(ggplot2)

      x <- seq(-10, 10, length = 50000)
      mb <- microbenchmark(
      Sapply = directpoly(x),
      Forloop = directpoly2(x)
      )

      autoplot(mb)


      enter image description here






      share|improve this answer























        up vote
        0
        down vote



        accepted







        up vote
        0
        down vote



        accepted






        Here are two ways of writing your function.




        1. With a sapply loop. Makes the code more readable and some times faster.

        2. With a standard for loop.


        There is no need to write a separate function outside the function to be called with the x values, I have placed that function in the body of the main functions.

        Then both functions are tested, with a smaller input vector. As you can see, the for loop function is faster.



        directpoly <- function(x, n = 39, coef = NULL){
        f <- function(y) sum(coef * y^seqcoef)
        if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
        seqcoef <- rev(seq_along(coef) - 1)
        sapply(x, f)
        }

        directpoly2 <- function(x, n = 39, coef = NULL){
        f <- function(y) sum(coef * y^seqcoef)
        if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
        seqcoef <- rev(seq_along(coef) - 1)
        y <- numeric(length(x))
        for(i in seq_along(y))
        y[i] <- f(x[i])
        y
        }

        library(microbenchmark)
        library(ggplot2)

        x <- seq(-10, 10, length = 50000)
        mb <- microbenchmark(
        Sapply = directpoly(x),
        Forloop = directpoly2(x)
        )

        autoplot(mb)


        enter image description here






        share|improve this answer












        Here are two ways of writing your function.




        1. With a sapply loop. Makes the code more readable and some times faster.

        2. With a standard for loop.


        There is no need to write a separate function outside the function to be called with the x values, I have placed that function in the body of the main functions.

        Then both functions are tested, with a smaller input vector. As you can see, the for loop function is faster.



        directpoly <- function(x, n = 39, coef = NULL){
        f <- function(y) sum(coef * y^seqcoef)
        if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
        seqcoef <- rev(seq_along(coef) - 1)
        sapply(x, f)
        }

        directpoly2 <- function(x, n = 39, coef = NULL){
        f <- function(y) sum(coef * y^seqcoef)
        if(all(is.null(coef))) coef <- rep(c(2, -1), length.out = n + 1)
        seqcoef <- rev(seq_along(coef) - 1)
        y <- numeric(length(x))
        for(i in seq_along(y))
        y[i] <- f(x[i])
        y
        }

        library(microbenchmark)
        library(ggplot2)

        x <- seq(-10, 10, length = 50000)
        mb <- microbenchmark(
        Sapply = directpoly(x),
        Forloop = directpoly2(x)
        )

        autoplot(mb)


        enter image description here







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 13 at 14:10









        Rui Barradas

        14.8k31730




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