[R] approximating matrix columns
Dear Gunter Berton and all, As you can see, my data has three lists each containing 366 entries. I converted them into the matrix. I now want to approx./interpolate 366 entries over 365 intervals, Which means I want to have a matrix with 365 entries. I used approx(matrix, method=linear, n=365) but it only converted the first column of my data, and left the rest untouched. list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08, 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8, 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99, 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88, 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26, 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63, 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31, 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5, 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05, 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38, 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42, 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44, 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07, 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31, 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32, 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63, 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31, 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63, 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31, 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48, 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2, 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5, 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48, 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58, 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1, 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24, 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9, 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73, 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48, 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69, 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2, 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49, 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69, 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2, 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49, 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99, 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67, 30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49, 30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63, 8.32, 19.06, 14.63, 104.25, 44.03, 33.49, 21.36, 20.2, 15.72, 15.72, 11.42, 7.31, 6.31, 4.9, 4.5, 4.5, 4.5, 3.2, 8.32, 8.32, 14.63, 97.12, 310.8, 88.48, 36.05, 24.88, 19.06, 14.63, 12.48, 8.32, 23.69, 11.42, 19.06, 90.18, 90.18, 33.49, 16.82, 70.47, 38.67, 29.73, 34.77, 33.49, 68.9, 102.45, 176.7, 78.48, 45.4, 106.06, 83.43, 45.4, 68.9, 39.99, 28.5, 23.69, 20.2, 36.05, 38.67, 30.98, 26.07, 20.2, 47.79, 52.44, 28.5, 23.69, 20.2, 14.63, 14.63, 14.63, 12.48, 21.36, 24.88, 47.79, 38.67, 34.77, 21.36, 16.82, 8.32, 153, 47.79, 53.87, 29.73, 23.69, 15.72, 19.06, 97.12, 33.49, 15.72, 10.38, 6.31, 4.5, 11.42, 6.31, 6.31, 6.31, 4.5, 19.06, 14.63, 4.9, 4.9, 28.5, 70.47, 15.72, 4.9, 4.1, 41.33, 241, 85.1, 38.67, 28.5, 20.2, 15.72, 12.48, 12.48, 20.2, 14.63, 12.48, 10.38, 7.31, 7.31, 15.72, 33.49, 20.2, 15.72, 12.48, 8.32, 7.31, 6.31, 4.9, 4.5, 4.1, 4.9, 4.5, 4.9, 20.2, 11.42, 6.31, 4.9, 4.9, 4.9, 4.5, 4.5, 4.5, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 4.1, 6.31, 6.31, 4.5, 4.9, 4.9, 4.5, 4.5, 4.5, 4.9, 4.5, 15.72, 24.88, 4.1, 58.26, 23.69, 26.07, 28.5, 174.5, 58.26, 49.58, 23.69, 23.69, 23.69, 28.5,
Re: [R] approximating matrix columns
Hello, Try apply(mat, 2, approx, method=”linear”, n=365) This reads apply to each column (dimension = 2) of mat the function approx with extra args method and n. Three notes. 1. Your data does NOT have three list, it IS one list with three vectors. 2. 'matrix' is a function so choose something else as a name. Above I've chosen 'mat'. 3. Bert is obviously right. You are wrong in not following simple posting instructions. And in not even bothering to quote his post. Rui Barradas Em 05-06-2012 09:27, eliza botto escreveu: Dear Gunter Berton and all, As you can see, my data has three lists each containing 366 entries. I converted them into the matrix. I now want to approx./interpolate 366 entries over 365 intervals, Which means I want to have a matrix with 365 entries. I used approx(matrix, method=”linear”, n=365) but it only converted the first column of my data, and left the rest untouched. list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08, 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8, 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99, 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88, 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26, 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63, 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31, 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5, 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05, 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38, 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42, 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44, 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07, 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31, 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32, 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63, 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31, 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63, 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31, 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48, 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2, 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5, 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48, 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58, 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1, 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24, 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9, 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73, 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48, 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69, 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2, 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49, 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69, 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2, 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49, 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99, 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67, 30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49, 30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63, 8.32, 19.06, 14.63, 104.25, 44.03, 33.49, 21.36, 20.2, 15.72, 15.72, 11.42, 7.31, 6.31, 4.9, 4.5, 4.5, 4.5, 3.2, 8.32, 8.32, 14.63, 97.12, 310.8, 88.48, 36.05, 24.88, 19.06, 14.63, 12.48, 8.32, 23.69, 11.42, 19.06, 90.18, 90.18, 33.49, 16.82, 70.47, 38.67, 29.73, 34.77, 33.49, 68.9, 102.45, 176.7, 78.48, 45.4, 106.06, 83.43, 45.4, 68.9, 39.99, 28.5, 23.69, 20.2, 36.05, 38.67, 30.98, 26.07, 20.2, 47.79, 52.44, 28.5, 23.69, 20.2, 14.63, 14.63, 14.63, 12.48, 21.36, 24.88, 47.79, 38.67, 34.77, 21.36, 16.82, 8.32, 153, 47.79, 53.87, 29.73, 23.69, 15.72, 19.06, 97.12,
Re: [R] approximating matrix columns
Dear Rui, i am greatful for everything you did. bret advised me to use dput(), which i did. yes! i forgot to complement him. i literally feel sorry for that. i hope you wont mind and continue extending your help. regards and love for every one eliza botto waters inn Date: Tue, 5 Jun 2012 12:46:25 +0100 From: ruipbarra...@sapo.pt To: eliza_bo...@hotmail.com CC: r-help@r-project.org Subject: Re: approximating matrix columns Hello, Try apply(mat, 2, approx, method=linear, n=365) This reads apply to each column (dimension = 2) of mat the function approx with extra args method and n. Three notes. 1. Your data does NOT have three list, it IS one list with three vectors. 2. 'matrix' is a function so choose something else as a name. Above I've chosen 'mat'. 3. Bert is obviously right. You are wrong in not following simple posting instructions. And in not even bothering to quote his post. Rui Barradas Em 05-06-2012 09:27, eliza botto escreveu: Dear Gunter Berton and all, As you can see, my data has three lists each containing 366 entries. I converted them into the matrix. I now want to approx./interpolate 366 entries over 365 intervals, Which means I want to have a matrix with 365 entries. I used approx(matrix, method=linear, n=365) but it only converted the first column of my data, and left the rest untouched. list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08, 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8, 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99, 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88, 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26, 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63, 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31, 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5, 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05, 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38, 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42, 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44, 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07, 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31, 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32, 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63, 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31, 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63, 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31, 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48, 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2, 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5, 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48, 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58, 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1, 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24, 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9, 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73, 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48, 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69, 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2, 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49, 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69, 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2, 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49, 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99, 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67, 30.98, 50.01, 65.8, 51.01, 38.67, 34.77,
[R] approximating matrix columns
Dear R users, we generally apply approx() command to a list data. how can we apply this command to a matrix, so that we can approximate 366 readings from certain number of each column over 365 intervals?? more precisely, i want to interpolate 366 discharge readings, in each 8 columns of a matrix, over 365 days. hope i am clear in my statement. eliza botto From: eliza_bo...@hotmail.com To: ruipbarra...@sapo.pt Date: Mon, 4 Jun 2012 22:13:10 + CC: r-help@r-project.org Subject: Re: [R] Spliting Lists into matrices dear rui, lots of hugs for you. thnkyou very much 4 your support. eliza Date: Mon, 4 Jun 2012 22:58:12 +0100 From: ruipbarra...@sapo.pt To: eliza_bo...@hotmail.com CC: r-help@r-project.org Subject: Re: Spliting Lists into matrices Hello, Try # 'x' is your list xlen - sapply(x, length) i1 - which(xlen == 365) i2 - which(xlen == 366) mat365 - matrix(unlist(x[i1]), nrow=365) mat366 - matrix(unlist(x[i2]), nrow=366) Hope this helps, Rui Barradas Em 04-06-2012 22:46, eliza botto escreveu: i realy appreciate your concern.. here is a small piece of my data. if you see the first and last part data, they contain 366 entries but the middle one has 365 entries. i want to put first and last entries is one matrix. list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08, 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8, 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99, 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88, 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26, 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63, 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31, 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5, 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05, 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38, 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42, 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44, 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07, 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31, 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32, 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63, 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31, 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63, 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31, 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48, 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2, 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5, 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48, 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58, 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1, 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24, 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9, 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73, 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48, 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69, 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2, 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49, 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69, 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2, 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49, 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99, 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67, 30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49, 30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63, 8.32, 19.06, 14.63, 104.25, 44.03, 33.49, 21.36, 20.2, 15.72, 15.72, 11.42, 7.31, 6.31, 4.9, 4.5, 4.5, 4.5, 3.2, 8.32, 8.32, 14.63, 97.12, 310.8, 88.48, 36.05, 24.88, 19.06, 14.63, 12.48, 8.32, 23.69,
Re: [R] approximating matrix columns
1. Please follow the posting guide and provide a small reproducible example. See ?dput to provide data. 2. Please do not double post. -- Bert On Mon, Jun 4, 2012 at 4:47 PM, eliza botto eliza_bo...@hotmail.com wrote: Dear R users, we generally apply approx() command to a list data. how can we apply this command to a matrix, so that we can approximate 366 readings from certain number of each column over 365 intervals?? more precisely, i want to interpolate 366 discharge readings, in each 8 columns of a matrix, over 365 days. hope i am clear in my statement. eliza botto From: eliza_bo...@hotmail.com To: ruipbarra...@sapo.pt Date: Mon, 4 Jun 2012 22:13:10 + CC: r-help@r-project.org Subject: Re: [R] Spliting Lists into matrices dear rui, lots of hugs for you. thnkyou very much 4 your support. eliza Date: Mon, 4 Jun 2012 22:58:12 +0100 From: ruipbarra...@sapo.pt To: eliza_bo...@hotmail.com CC: r-help@r-project.org Subject: Re: Spliting Lists into matrices Hello, Try # 'x' is your list xlen - sapply(x, length) i1 - which(xlen == 365) i2 - which(xlen == 366) mat365 - matrix(unlist(x[i1]), nrow=365) mat366 - matrix(unlist(x[i2]), nrow=366) Hope this helps, Rui Barradas Em 04-06-2012 22:46, eliza botto escreveu: i realy appreciate your concern.. here is a small piece of my data. if you see the first and last part data, they contain 366 entries but the middle one has 365 entries. i want to put first and last entries is one matrix. list(c(0.86, 0.86, 0.86, 0.86, 0.86, 1.08, 1.08, 1.08, 1.08, 1.08, 1.08, 1.4, 1.4, 23, 11.18, 38.83, 23, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.45, 3.02, 2.58, 2.58, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 2.15, 3.02, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.72, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.8, 2.8, 2.8, 4.1, 4.1, 13.55, 9.34, 8.32, 7.31, 4.5, 4.1, 14.63, 24.88, 39.99, 23.69, 14.63, 7.31, 4.5, 7.31, 16.82, 21.35, 24.88, 20.2, 24.88, 26.07, 30.98, 49.58, 51.01, 26.07, 24.88, 30.98, 34.77, 58.26, 30.98, 23.69, 26.07, 19.06, 16.82, 20.2, 16.82, 23.69, 14.63, 16.82, 11.42, 11.42, 11.42, 11.42, 10.38, 10.38, 8.32, 7.31, 6.31, 16.82, 6.31, 6.31, 6.31, 4.9, 4.9, 4.5, 4.5, 4.5, 4.5, 4.5, 4.1, 4.1, 2.8, 2.4, 2.4, 26.07, 45.4, 16.82, 7.31, 4.5, 3.2, 3.2, 2.8, 2.8, 2.4, 2.4, 2.8, 3.2, 3.2, 4.9, 4.9, 36.05, 65.8, 76.86, 53.87, 26.07, 20.2, 21.36, 14.63, 10.38, 10.38, 7.31, 7.31, 51.01, 16.82, 14.63, 12.48, 14.63, 10.38, 11.42, 52.44, 64.27, 36.05, 26.07, 21.36, 21.36, 23.69, 47.79, 52.44, 167.9, 97.12, 76.86, 144.71, 90.18, 34.77, 30.98, 28.5, 26.07, 26.07, 14.63, 14.63, 6.31, 6.31, 6.31, 4.5, 4.1, 3.2, 6.31, 6.31, 16.82, 4.5, 3.2, 3.2, 3.2, 3.2, 4.5, 8.32, 10.38, 10.38, 8.32, 11.42, 10.38, 7.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 6.31, 8.32, 6.31, 6.31, 20.2, 14.63, 7.31, 4.9, 34.77, 26.07, 14.63, 10.38, 6.31, 4.9, 7.31, 4.9, 4.5, 4.5, 4.5, 21.36, 12.48, 7.31, 4.5, 4.5, 6.31, 4.9, 4.9, 6.31, 8.32, 7.31, 6.31, 6.31, 14.63, 11.42, 6.31, 6.31, 4.9, 6.31, 14.63, 7.31, 12.48, 6.31, 6.31, 24.88, 15.72, 33.49, 111.57, 44.03, 39.99, 44.03, 24.88, 12.48, 39.99, 11.42, 7.31, 4.9, 4.5, 4.1, 4.5, 4.1, 4.1, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 2.8, 2.8, 3.2, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 2.8, 4.1, 4.1, 2.4, 3.2, 10.38, 8.32, 4.5, 3.2, 3.2, 2.8, 3.2, 3.2, 3.2, 2.4, 2.4, 2.4, 15.72, 23.69, 12.48, 14.63, 4.5, 4.1, 4.5, 4.1, 4.1, 4.1, 3.2, 2.8, 2.8, 3.2, 2.8, 2.4, 4.5, 4.5, 12.48, 68.9, 30.98, 39.99, 29.73, 95.37, 44.03, 26.07, 41.33, 49.58, 23.69, 28.5), c(16.82, 14.63, 6.31, 6.31, 4.5, 4.5, 4.1, 4.1, 4.1, 3.2, 3.2, 4.1, 3.2, 3.2, 4.1, 4.5, 4.1, 4.1, 167.9, 75.24, 44.03, 23.69, 19.06, 15.72, 11.42, 8.32, 6.31, 4.9, 6.31, 4.9, 4.9, 4.1, 4.1, 3.2, 4.1, 4.1, 4.1, 90.18, 102.45, 39.99, 29.73, 8.32, 21.36, 21.36, 21.36, 12.48, 11.42, 12.48, 11.42, 12.48, 14.63, 14.63, 15.72, 23.69, 28.5, 29.73, 33.49, 29.73, 23.69, 21.36, 6.31, 16.82, 15.72, 15.72, 15.72, 15.72, 16.82, 20.2, 20.2, 21.36, 21.36, 26.07, 28.5, 29.73, 33.49, 29.73, 33.49, 34.77, 26.07, 26.07, 23.69, 23.69, 26.07, 21.36, 23.69, 23.69, 23.69, 24.88, 21.36, 20.2, 16.82, 19.06, 20.2, 21.36, 20.2, 20.2, 24.88, 23.69, 26.07, 29.73, 23.69, 24.88, 29.73, 36.05, 33.49, 34.77, 28.5, 28.5, 26.07, 153, 70.47, 58.26, 81.77, 36.05, 39.99, 30.98, 33.49, 28.5, 28.5, 33.49, 29.73, 28.5, 24.88, 30.98, 38.67, 30.98, 50.01, 65.8, 51.01, 38.67, 34.77, 29.73, 29.73, 33.49, 30.98, 30.98, 30.98, 33.49, 34.77, 33.49, 30.98, 88.48, 14.63, 8.32,
