Minor changes to assignment 02

StudentNotebooks/Assignment02/dar-f24-assignment2-template.Rmd

@@ -62,16 +62,18 @@ This notebook is broken into two main parts:
 * **Part 2:** Loading and some analysis of the Mars 2020 (M20) Datasets
    * Lithology: _Summarizes the mineral characteristics of samples collected at certain sample locations._
    * PIXL: Planetary Instrument for X-ray Lithochemistry. _Measures elemental chemistry of samples at sub-millimeter scales of samples._
-      * SHERLOC: Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals. _Uses cameras, a spectrometer, and a laser of samples to search for organic compounds and minerals that have been altered in watery environments and may be signs of past microbial life._
+   * SHERLOC: Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals. _Uses cameras, a spectrometer, and a laser of samples to search for organic compounds and minerals that have been altered in watery environments and may be signs of past microbial life._
    * LIBS: Laser-induced breakdown spectroscopy. _Uses a laser beam to help identify minerals in samples and other areas that are beyond the reach of the rover's robotic arm or in areas too steep for the rover to travel._
 
 * **Part 3:** Individual analysis of your team's dataset
 
+* **Part 4:** Preparation of Team Presentation 
+
+
 **NOTE:** The RPI github repository for all the code and data required for this notebook may be found at:
 
 * https://github.rpi.edu/DataINCITE/DAR-Mars-F24
 
-* **Part 4:** Preparation of Team Presentation 
 
 # DAR ASSIGNMENT 2 (Part 1): Preparing your local repo for Assignment 2 
 
@@ -156,8 +158,7 @@ NOTES:
    * Also included is `rover.waypoints.Rds` that provides detailed location information (lat/lon) for the Perseverance rover throughout its journey, up to the present. This can be updated when necessary using the included `roverStatus-f24.R` script. 
    * A general guide to the available Mars 2020 data is available here: https://pds-geosciences.wustl.edu/missions/mars2020/index.htm
    * Other useful MARS 2020 sites
-   https://science.nasa.gov/mission/mars-2020-perseverance/mars-rock-samples/
-   https://an.rsl.wustl.edu/m20/AN/an3.aspx?AspxAutoDetectCookieSupport=1
+   https://science.nasa.gov/mission/mars-2020-perseverance/mars-rock-samples/ and https://an.rsl.wustl.edu/m20/AN/an3.aspx?AspxAutoDetectCookieSupport=1
    * Note that PIXL, SHERLOC, and Lithology describe 16  sample that were physically collected. There will eventually be 38 samples.   These datasets can be merged by sample.   The LIBS data includes observations collected at many more locations so how to combine the LIBS data with the other datasets is an open research question.   
 
 ## Data Set A: Load the Lithology Data
@@ -178,7 +179,8 @@ lithology.df<- readRDS("/academics/MATP-4910-F24/DAR-Mars-F24/Data/mineral_data_
 lithology.df$sample <- as.numeric(lithology.df$sample)
 
 # Convert rest into factors
-lithology.df[sapply(lithology.df, is.character)] <- lapply(lithology.df[sapply(lithology.df, is.character)], 
+lithology.df[sapply(lithology.df, is.character)] <-
+  lapply(lithology.df[sapply(lithology.df, is.character)], 
                                        as.factor)
 
 # Keep only first 16 samples because the data for the rest of the samples is not available yet
@@ -240,7 +242,7 @@ summary(libs.df)
 libs.matrix <- as.matrix(libs.df[,6:13]) 
 
 # Check to see scaling
-summary(libs.matrix)
+str(libs.matrix)
 ```
 
 
@@ -284,7 +286,7 @@ sherloc.df <- cbind(pixl.df[,c("sample","type","campaign","abrasion")],sherloc.m
 summary(sherloc.df)
 
 # Measurements are everything except first column
-sherloc.matrix<-sherloc.matrix[,-1]
+sherloc.matrix<-as.matrix(sherloc.matrix[,-1])
 
 # Sherlock measurement matrix
 # Review the structure 
@@ -367,7 +369,7 @@ str(sherloc_lithology_pixl.matrix)
 
 Each team has been assigned one of six datasets:   
 
-1. Dataset B: PIXL: The PIXL team's goal is to understand and explain how scaling improves results from Assignment 1.   The matrix version was scaled above.  
+1. Dataset B: PIXL: The PIXL team's goal is to understand and explain how scaling changes results from Assignment 1.   The matrix version was scaled above but not in Assignment 1.  
 
 2. Dataset C: LIBS (with appropriate scaling as necessary. Not scaled yet.) 
 
@@ -385,11 +387,11 @@ Each team has been assigned one of six datasets:
 
 1. _Describe the data set contained in the data frame and matrix:_ How many rows does it have and how many features?  Which features are measurements and which features are metadata about the samples?  (3 pts)
 
-2. _Scale this data appropriately (you can choose the scaling method):_ Explain why you chose that scaling method. (3 pts) 
+2. _Scale this data appropriately (you can choose the scaling method or decide to not scale data):_ Explain why you chose  a scaling method or to not scale. (3 pts) 
 
 3. _Cluster the data using k-means or your favorite clustering method (like hierarchical clustering):_   Describe how you picked the best number of clusters.  Indicate the number of points in each clusters. Coordinate with your team so you try different approaches.   If you want to share results with your team mates, make sure to use the same random seeds.  (6 pts)
 
-4. _Perform a **creative analysis** that provides insights into what one or more of the clusters are and what they tell you about the MARS data:_ 
+4. _Perform a **creative analysis** that provides insights into what one or more of the clusters are and what they tell you about the MARS data:  Alternatively do another creative analysis of your datasets that leads to one of more findings.  Make sure to explain what your analysis and discuss your the results.  
 
 
 # Preparation of Team Presentation (Part 4)