Lkelly9 Week 2

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Purpose

The scientific purpose of my investigations was to plot two vectors, u and v, on a graph and to model the logistical growth for four different rates on one plot.

Workflow/Methods

Part I: Create a script that includes the following elements

    • Define a vector u containing the elements 1,2,3,4,5,6,7,8,9,10 using the colon operation
      • u = [1:10]
    • Define another vector v containing elements that are the square of the vector
      • v = u.^2
    • Plot v versus u (make sure you know what that sentence means!!) using circles on the points that are connected with dashed lines
      • plot(u,v)
      • Add title: title('V vs. U')
      • X-axis label: xlabel('u')
      • Y-axis label: ylabel('v')
    • Save your plot as a TIFF file
    • Save your data into an excel spreadsheet using the MATLAB command xlswrite
      • Declare the file name: filename='insertfilenamehere'
      • Put u and v together in a vector: A=[u;v]
      • Save into an excel sheet: xlswrite('insertfilenamehere',A)

Part II: Create a script to compare logistic growth curves

    • Define a vector t starting at 0, ending at 1, in steps of 0.01.
      • t = [0:0.01:1]
    • Define K = 10 and x0 = 2 for carrying capacity and initial population size.
    • Plot logistic growth curves for growth rates 0.5,1.0,1.5, and 2.0.
      • For r=0.5: y1=(x0*K)./(K*exp(-0.5*t)-x0*exp(-0.5*t)+x0)
      • For r=1.0: y2=(x0*K)./(K*exp(-1.0*t)-x0*exp(-1.0*t)+x0)
      • For r=1.5: y3=(x0*K)./(K*exp(-1.5*t)-x0*exp(-1.5*t)+x0)
      • For r=2.0: y4=(x0*K)./(K*exp(-2.0*t)-x0*exp(-2.0*t)+x0)
    • Plot these four curves together in one figure, and add appropriate labels, title, and legend.
      • plot(t,y1,'m',t,y2,'r',t,y3,'b',t,y4,'k')
    • Save your plot as a TIFF file

Results

Data and Files

  • Lkelly9part1plot.tif
  • Figure 1. This plot displays the relationship between vectors u and v. Please refer to the workflow above to see how this plot was created.
  • Vector u and v Data
  • Lkelly9part2plot.tif
  • Figure 2. This plot displays the logistic growth curves for r = 0.5, 1.0, 1.5, and 2.0. Please refer to the workflow above to see how this plot was created.

Conclusion

My main finding for today's project was that MATLAB can be manipulated in a variety of ways to model data. Furthermore, the logistic growth curves, assuming I executed them correctly, were fairly linear and they did not level off at any point. I accomplished my purpose of plotting vectors u and v and plotting four different logistic growth curves in the same figure.

Acknowledgements

  • I worked with my homework partner Cameron M. Rehmani Seraji face-to-face in the computer lab outside of class. We worked on the MATLAB portion of the assignment together.
  • I worked with Ben G. Fitzpatrick through email one time. He helped me with the logistic growth curve.
  • Except for what is noted above, this individual journal entry was completed by me and not copied from another source
  • Lauren M. Kelly 01:22, 26 January 2017 (EST)

References

Dahlquist, Kam D. (2017) BIOL398-05/S17:Week 2. Retrieved from http://www.openwetware.org/wiki/BIOL398-05/S17:Week_2 on 25 January 2017.