# Project work¶

Choose a project work. There are three projects to choose from:

- biological sequence analysis (part07)
- regression analysis on medical data (part08)
- fossil data analysis (see course page / tasks section)

After you have completed 80% of points from week 6, download the exercises and/or notebooks from the TMC server. Then try to solve as many exercises as you can. Then submit your solutions to the TMC server. Note that the TMC server is only used here for helping you to proceed with the project work. Your final project work returned to Moodle can include partial solutions.

The two projects differ a lot in their workflow. See the below sections on individual projects to see in detail how solving, testing and reporting of exercises are done in each project.

Save the report as a Jupyter notebook file (with `ipynb`

extension)
and submit this file to Moodle.
After this you will need to give feedback for your own
report and two other reports. The feedback is given in two categories:

1. Give a grade 0…5 on the correctness of solutions, and provide constructive comments where you find places for improvement.

- Less than half of assignments solved satisfactorily
- At least half of assignments solved satisfactorily
- At least half of assignment solved pretty correctly
- 65% of assignments solved pretty correctly
- 80% assignments solved pretty correctly
- All but 1-2 assignments solved almost perfectly

To assess the percentage of correctness, you may give 0.5 points from a serious (but failed) attempt, 1 point from essentially correct answer, and divide total points by maximum points. Essentially correct means an answer that might not go through an automatic test for some minor reason.

- Give a grade 0…5 on the clarity of writing and code, and provide constructive comments where you find places for improvement.

- Writing and code are not at sufficient level in the solved assignments
- Writing and code are mostly at sufficient level in the solved assignments
- Writing and code are mostly at satisfactory level in the solved assignments
- Writing and code are mostly at good level in the solved assignments
- Writing and code are mostly at very good level in the solved assignments
- Writing and code are mostly at excellent level in the solved assignments

In each category, in addition to textual feedback, give also a grade in the range 0, 1, …, 5. The final grade for the project work will be the weighted average over the two categories, where category 1 has weight 2, and the second has weight 1. More details can be found in the Moodle. You must get at least grade 1 for the project work.

The following instructions are for the TMC-integrated projects (part7 and part8).

## Sequence analysis¶

Download part 7 from tmc after you have completed the required number of part 6
as a usual. The `src`

-folder contain a jupyter notebook
`project_notebook_sequence_analysis.ipynb`

. Run the notebook and fill in the
cells as instructed. You may run tmc test to see that functions work as required.
Submitting may not work especially if you download content from the internet as
part of your code.

Next to each exercise in the report there are also two text boxes for you to fill. In the first box, in your own words, describe the idea of the solution to the exercise. In the second box analyse the results, including how the program worked with the given example input or your own examples. Make sure the notebook includes your solutions and looks readable, and then submit the resulting notebook to Moodle.

NOTE. Exercises in section “Stationary and equilibrium distributions (extra)” (exercises 20, 21, and 22) are not obligatory. Thus, you only need to do 19 exercises, if you are aiming to get full points.

## Regression analysis¶

Read the introduction `introduction-to-regression-analysis.pdf`

.

Note

It looks like the TMC server corrupted the pdf, you can read it from here

Write solutions to exercises directly into the cells of the given Jupyter notebook.
Do not modify lines that say `# exercise x`

; without those the tests won’t work.
Don’t use additional cells, and do in each cell exactly as the instructions say.
Save the file and run `tmc test`

. The tests read and execute directly the cells
of the notebook.
Make sure the notebook includes you solutions and looks readable,
and then submit the resulting notebook to Moodle.

# Running tests when peer-reviewing students notebooks¶

If you want, you can run tests on the work you are reviewing, to help assess the correctness of the solutions. Note that there can be bugs in the tests too.

Warning

Make sure you don’t accidentally delete your own solutions, when testing other student’s work. Don’t do the tests where your own solutions are.

## Regression analysis¶

Go to a temporary working area (like `/tmp`

on Unix) so you don’t accidentally overwrite
your own solutions. Run `tmc download -a hy-data-analysis-with-python-summer-2019`

to get the tests. Store student’s notebook to file
`part08-e01_regression/src/project_notebook_regression_analysis.ipynb`

.
Run the tests using `tmc test part08-e01_regression`

.

## Sequence analysis¶

Go to a temporary working area (like `/tmp`

on Unix) so you don’t accidentally overwrite
your own solutions. Run `tmc download -a hy-data-analysis-with-python-summer-2019`

to get the tests. Overwrite the student’s notebook in `part07-e01_sequence_analysis/src`

.
Run the tests using `tmc test`

in the `part07-e01_sequence_analysis`

folder.