Installing and getting started with BMEGUI
Date given: 9/16
Due: 9/23 noon
Part 1 (20 points)
Use the instructions of BMEGUI to install BMEGUI version 3.0.1 either on a computer (i.e. either your computer, or a VCL computer that does not have ). Note that this involves performing steps 1 and 2 of the Installation Manual to install various libraries (including MATLAB Component Runtime (MCR), Python, GTK, and some Python libraries) prior to installing BMEGUI 3.0.1 (steps 3, 4 and 5).
Describe the computer you are using, summarize the installation steps you went through to install BMEGUI, and then describe the steps you have to do every time you want to start BMEGUI.
Next, answer the following question:
Why does BMEGUI use python as a main programming language?
Hint: List three python features that are relevant to BMEGUI.
Part 2 (30 points)
Download the file Raritan_Phos.csv. Run BMEGUI to perform an exploratory analysis of the Phosphorus data on the Raritan river basin. Notice the use of the histogram to display the distribution of the data. Then modify aggregation time used for the spatial plots of the data using first a monthly time aggregation, then a yearly time aggregation. Finally answer the following question: Is the data normally distributed? What temporal aggregation duration do you think is better, and why? What’s the trade off between the monthly and yearly aggregation periods?
Hints: In order to evaluate your exploratory analysis, the grader will need to see a short description of your exploratory analysis. Therefore you are to submit a concise and well written report that describes the spatial and temporal variability in the data based on figures generated in your exploratory analysis. These figures can be generated in ArcGIS, or in BMEGUI up to the screen labeled “exploratory data analysis (3/6)”. They do not include figures of the covariance of the data. The style should be that of the section describing the data in the materials and methods section a journal paper (see for example the section labeled “Study Area and Tetrachloroethylene Monitoring Data” in the Akita et al. (2007) paper available from the Papers To Read link on the class website). The text should refer to each figure, each figure should have a self-explanatory caption, and the text and figures can be used to answer the questions asked about the monthly versus yearly aggregation.
Part 3 (35 points)
Select a space/time dataset of scientific interest that you will use as the basis for your class project, and perform an exploratory data analysis of that dataset to show how the data varies across space and time, in a way that depicts its spatial and temporal coverage and its space/time autocorrelation. You may use the dataset created for homework 2, or you may use one from your own research, or you may browse for additional dataset from the Data for ENVR 468 link on the class website.
Write a report describing your exploratory data analysis, providing all the relevant figures, and discussing any interesting findings.
Part 4 (15 points)
Identify a research question that will serve as your proposal for the class project. For example provide background information about the space/time field of interest, describe the dataset available, formulate the general lines of the analysis you plan to perform, and describe the potential application of any findings. Your answer will serve as a starting point to your class project.
Submit parts 1 and 2 as a well-written word document named yourfirstname_yourlastname_hwk3_part12.docx that you send to the the TA. Submit parts 3 and 4 as a well-written word document named yourfirstname_yourlastname_hwk3_part34.docx that you also send to the TA.