代写CPS188 : Term Project : Winter 2025代做R编程

CPS188 : Term Project : Winter 2025

Introduction:

This project is conceived as a team project. It is required that the project be worked on in teams of two to four students (no more, no less, no exceptions). Group members   can be from different lab sections but must be from the same professor (Dr. Hamelin: sections 01-10; Dr. Woungang: sections 11-15; Dr. Mustafiz: sections 16-18; Dr. Davoudpour: sections 19-23). Only one submission per group will be permitted so make sure the cover page clearly indicates the members of the group. Groups are    managed by the D2L Group Formation Tool.

Start working on the project early! Past experiences have found that the end of semesters can be hectic and communications between group members might become more difficult.

Description:

In this project you will make calculations, graphs and conclusions based on real data.

You will find the actual data file here that contains actual data collected by the NOAA during the 2023-2024 winter about the Great Lakes average ice concentration. Values  are in %.

https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2023_2024_ice.dat

Days are numbered between 001 to 365, 001 being January 1st and December 31st being 365. Note that for plotting it might be better to convert the days into indexes to avoid gaps in the lines and make the plots more attractive.

The file format is CSV (comma spaced values). It is up to you to import the data from the file into your C program. This operation must be done within your C program. Do not copy and enter data by hand! The data in the file is in string format so some numerical values will have to be converted.

You are to make a report showing tables, graphs and conclusions based on data using C programming and GNUPlot functionalities.

Required elements:

The entire project must be presented as one single program (including the parts that generate the output file for the graphs) . Divide your code into sections, one for each question. Add comments in your program to identify which question is answered in that section. Make sure your C and GNUPlot codes are well documented (comments) and well presented (style. and indentation).

All computations and determinations are to be done in C using the imported data file. For the graphs, all the labels, legends and titles must be generated by the GNUPlot script. Nothing can be done by hand.

The submission package will include the following files:

●  The project report in PDF format including the CPS 188 Term Project - Standardized Cover Page.

●  A .zip file containing the assets of the project (the .c file of your program and all the GNUPlot scripts (use .gnu or .gp as the file extension).

The problems to solve:

1. Calculate the yearly average ice concentration percentage for each of the lakes, and the yearly average for all six lakes put together (GL Total). One 2023 average and one 2024 average for each of the lakes plus the GL total column. So 14 averages in all.

2. Indicate which lake has the highest ice concentration percentage and which lake has the lowest ice concentration percentage, based on the average ice concentration calculated in step #1.

3. Indicate the day and year and the ice concentration percentage with the highest percentage for each of the lakes. In the case ofa tie, mention all the dates.

4. Which day, which year and which lake has the highest ice concentration percentage found in the data file. One single answer unless there are ties, in that case mention all.

5. Make a graph of the ice concentration percentage of each daily average (x=day, y=ice %). Make one graph per lake to show the ice coverage trends. Label the axes clearly and add titles to all your graphs. Use script commands to generate the labels and titles for all graphs. You need 6 plots and figures here.

6. Make a single graph of the ice concentration percentages (x=day, y=ice %) that shows all 6 lines on one graph. Each lake will have a different colour and line type. Title your graph, label your axes, and have a legend.

7. Re-do question 1 (the 7 yearly averages) but with data from 2022-2023 and 2021-2022 instead. Make a table of the averages side by side to illustrate the three yearly results. Any notable differences? Can you advance a conclusion why there is a difference (or not)?

2022-2023:

https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2022_2023_ice.dat

2021-2022:

https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2021_2022_ice.dat

8. Make a graph of the ice concentration percentage of each daily average (x=day, y=ice %) (like question 5). Make one graph per lake to show the monthly coverage trends using the three data files. Label the axes clearly and add titles to all your graphs. Use script. commands to generate the labels and titles for all graphs. You make 6 plots and figures here and each plot has 3 lines (2021-2022, 2022-2023, 2023-2024).