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library(gelxx) s6.5k.sub1 <-read.delim("~/s6-5k sub1.txt", header=FALSE) #View(s6.5k.sub1) #Change the data set name data <-s6.5k.sub1 # Extract first row as wavelengths and remove first row from data wavelengths <-data[1.] data <-data[-1,] nr = now(data) DE=D.Cl(data) #Store the minimum values in a list of arrays (list size = nr) # Store the minimum indices in a list of arrays (list size = nr) minima..values <- minima..indices <- # Loop through the rows of the array for (i in 1:nr) { # Find second derivative of the data second.derivative <- data[i, 1:nc-2] - 2*data[i, 2:nc-1] + data[i,3:nc] # Find ALL local minima of the second derivative for the given row # Local min means the entry is less than the one before and the one aft # the entry should also be negative min._index <-which.min(second.derivative) minima_indices[i]<- min.index # be careful that the index is not offset minima_values[i]<-second.derivative[min.index] } #Store the minimum values and their indices in two different lists minima..values minima._.indices

library(gelxx) s6.5k.sub1 <-read.delim("~/s6-5k sub1.txt", header=FALSE) #View(s6.5k.sub1) #Change the data set name data <-s6.5k.sub1 # Extract first row as wavelengths and remove first row from data wavelengths <-data[1.] data <-data[-1,] nr = now(data) DE=D.Cl(data) #Store the minimum values in a list of arrays (list size = nr) # Store the minimum indices in a list of arrays (list size = nr) minima..values <- minima..indices <- # Loop through the rows of the array for (i in 1:nr) { # Find second derivative of the data second.derivative <- data[i, 1:nc-2] - 2*data[i, 2:nc-1] + data[i,3:nc] # Find ALL local minima of the second derivative for the given row # Local min means the entry is less than the one before and the one aft # the entry should also be negative min._index <-which.min(second.derivative) minima_indices[i]<- min.index # be careful that the index is not offset minima_values[i]<-second.derivative[min.index] } #Store the minimum values and their indices in two different lists minima..values minima._.indices

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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PLEASE DO IN RSTUDIO (R PROGRAMMING) Please fix and finish my code that I have highlighted. Thank you

Data Set:

    890.776 890.519 890.263 890.006 889.749 889.493 889.236 888.979
-4.25909 -6.9024 9845 9608 9782 9708 9661 9609 9832 9753
-4.25909 -6.4544 9507 9340 9337 9325 9441 9300 9470 9143
-4.25909 -6.0064 9576 9201 9252 9238 9217 9298 9217 9224
-4.25909 -5.5584 9604 9301 9467 9279 9457 9438 9395 9310

 

 

library(delyr) s6.5k.sub1 <-read.delim("~/s6-5k sub1.txt", header=FALSE) #View(s6.5k.sub1) #Change the data set nome data <-s6.5k.sub1 # Extract first row as wavelengths and remove first row from dato wavelengths <- data[1] data <-data[-1,] nr=nrow(data) DC=D.Col(data) # Store the minimum values in a list of arrays (list size - nr) # Store the minimum indices in a list of arrays (list size = nr) minima.values <- minima._indices <- # Loop through the rows of the array for (i in 1:nr) { # Find second derivative of the data second.derivative <- data[i,1:nc-2] - 2*data[i, 2:nc-1] + data[i,3:nc] # Find ALL local minima of the second derivative for the given row # Local min means the entry is less than the one before and the one ofter # the entry should also be negative min.index <-which.min(second.derivative) minima.indices[i]<-minindex # be careful that the index is not offset minima_values[i]<-second derivative[min_index] } # Store the minimum values and their indices in two different lists minima..values minima. indices
Transcribed Image Text:library(delyr) s6.5k.sub1 <-read.delim("~/s6-5k sub1.txt", header=FALSE) #View(s6.5k.sub1) #Change the data set nome data <-s6.5k.sub1 # Extract first row as wavelengths and remove first row from dato wavelengths <- data[1] data <-data[-1,] nr=nrow(data) DC=D.Col(data) # Store the minimum values in a list of arrays (list size - nr) # Store the minimum indices in a list of arrays (list size = nr) minima.values <- minima._indices <- # Loop through the rows of the array for (i in 1:nr) { # Find second derivative of the data second.derivative <- data[i,1:nc-2] - 2*data[i, 2:nc-1] + data[i,3:nc] # Find ALL local minima of the second derivative for the given row # Local min means the entry is less than the one before and the one ofter # the entry should also be negative min.index <-which.min(second.derivative) minima.indices[i]<-minindex # be careful that the index is not offset minima_values[i]<-second derivative[min_index] } # Store the minimum values and their indices in two different lists minima..values minima. indices
Expert Solution
Step 1

The given code is for finding the local minima of the second derivative of the data.

Algorithm:

  1. Start
  2. Read the data from a file into a data frame
  3. Extract the first row of the data frame as wavelengths and remove it from the data frame
  4. Store the number of rows and columns of the data frame in variables 'nr' and 'nc'
  5. Initialize two lists 'minima. values' and 'minima. indices' to store the minimum values and their indices respectively
  6. Loop through each row of the data frame
  7. Calculate the second derivative of the data using the formula: second.derivative <- data[i,1:nc-2]-2*data[i, 2:nc-1]+data[i,3:nc]
  8. Find the index of the minimum value of the second derivative using the function 'which. min(second. derivative)'
  9. Store the minimum index in the 'minima. indices' list
  10. Store the minimum value in the 'minima. values' list
  11. Return the 'minima. values' and 'minima. indices' lists as a result.
  12. Stop
steps

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