SciVisFall2008/Assignment 1

• • Exercise 1: Principles of plotting

The file stocks.dat has the the first quote for each month from January 2006 to September 2008 for the papers from Apple Inc. (AAPL) and Microsoft Corporation (MSFT). Below we present the first three lines and the last two lines of this file.

month,apple,microsoft
2008-09,140.91,25.16
2008-08,169.53,27.29
...
2006-02,68.49,25.92
2006-01,75.51,27.06

a. Apply the principles of plotting described in class and in the class notes to generate a simple connected symbol plot for all Apple's quotes in the file stocks.dat. Tag the final version of this plot as "Problem 1a" and annotate it with an explanation of the plotting principles you used to make this a clear plot.

b. Using as reference the quote of January 2006 directly compare the progress of Apple's and Microsoft's papers by generating a plot using superposition (both curves in the same plot). Tag this final plot as "Problem 1b" and annotate it with the conclusions you can draw from this plot.

c. Repeat item b, but now using juxtaposition: split the two curves (i.e. Apple's paper progress relative to January 2006 and Microsoft's paper progress relative to January 2006) into two different plots (each plot in a different spreadsheet cell). Tag the final version as "Problem 1c" and annotate it describing which technique (superpostion vs. juxtaposition) makes more sense for this data and why.

1. improve the vision and the understanding of the plot. Note, not all principles may be addressable with matplotlib. In the notes for the node, list the principles that were addressed and how they were addressed.
2. Using
3. the opening stock market value
4. for the papers of Google (GOOG), Microsoft (MSFT)
5. and Apple (AAPL) for the months starting at January 2007
6. to September 2008.
7. Apple Inc.
8. This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.
9. a. Apply the principles of plotting described in class (and in the class notes) to improve the vision and the understanding of the plot. Note, not all principles may be addressable with matplotlib. In the notes for the node, list the principles that were addressed and how they were addressed.
10. b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).
11. c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why. w
12. 1. connected symbol plot for the precipitation data from 2007 and 2006
13. principles of plotting in the notes:
14. principle 1:
15. principle 2:
16. principle 3:
17. principle 4:
18. a. improve the plot using the principles
19. b. compare 2006 and 2007 by superposition
20. c. compare 2006 and 2007 by juxtaposition

• • Exercise 2: Histogram and number of bins

Like this year, in the Fall of 2007, during the Scientific Visualization Course we collected all the assignments of the students in Vistrails' format. The file actions_fall_2007.dat has all the timestamps of all the actions of all the students in all the assignments: a total of 132131 actions. Using matplotlib in Vistrails, create a histogram for the distribution of these timestamps and highlight the folowing due dates in the histogram. (obs. note that by some reason assignment 5 had a due data before assignment 6).

| Assigment | Due Date | |-----------+---------------------| | 0 | 2007-09-18 12:00:00 | | 1 | 2007-09-18 12:00:00 | | 2 | 2007-10-04 12:00:00 | | 3 | 2007-10-25 12:00:00 | | 4 | 2007-11-27 12:00:00 | | 5 | 2007-12-15 12:00:00 | | 6 | 2007-12-11 12:00:00 |

When you finish your histogram tag its pipeline version with "Problem 2". And annotate it answering the following questions:

a. How did you select the bins for the histogram and why?

b. What hypothesis can you make about the amount of work (i.e. number of actions) for the different assignments just by looking to this histogram.

c. What pattern can you observe for the amount of work (i.e. number of actions) close to the deadlines?

• • Exercise 3: Dot plots for labeled data

Each line of the file microprocessors.dat has two quantitative values associated to a label. The quantitative values are "year of introduction" and "number of transistors" and the label is name of the "microprocessor". Generate two dot plots horizontally juxtaposed for these microprocessors: one for "year of introduction" and the other for "number of transistors". For "number of transistors" use log base 10 scale.

• • Exercise 4: Correlation, scatterplot and regression plotting capabilities

Let A, B, C, D be four genes. A scientist measured the activity (i.e. the expression) of these genes in 100 different conditions. The results are given in file genes.dat. Generate a 4 x 4 matrix of scatter plots to understand correlations between the four genes. Visually analyze the plot and rank the genes B, C, D in decrescent order of correlation to A. Now draw a linear best fit line in the plots of A with its most correlated gene, a quadratic best fit in the plots o A with its second most correlated gene and a cubic best fit in the plots of A with its most uncorrelated gene. Tag the final pipeline version that does all this work as "Problem 4".