Version: AA 2022-2023
This set of Python Notebooks and exercises are meant to be help in getting more familiar with the Python functions used to fit data, in particular curve_fit science:
- curve_fit in the Scientific Python package
You will find 1 set of tutorial+exercises:
- Set 1 - Simple fitting with Python
For each set, first look at the tutorial, check the code, run it and do modifications in order to be sure that you've understand how it works.
Then you can move to the exercise, where you will be asked to perform some tasks and solve some real-life cases of data analysis.
The package contains the following directories
- tutorials: Contains Python Juyter notebooks for the tutorials
- exercises: Contains Python Juyter notebooks for the exercises
- data: Contains data required to run the tutorial and the exercises
In order to get the package, you should run a git clone. For instance
git clone [email protected]:packageaddress
Where [email protected]:packageaddress has to be substituted with the proper link.
For instance, if your assigned package is called homework-03-fitting-data-with-python-myusername, you should run:
git clone [email protected]:mmphyslab-pi/homework-03-fitting-data-with-python-myusername
(of course, you should substitute username with your Github username)
You can also look at the Clone or Download green button in the Github page of the package
IMPORTANT You might be asked for a password (if putting a HTTPS address), or you will be denied access (if using the ssh address). In order to create a SSH key and add it to Github, you can follow these instructions. Please follow these steps once for all so that you will not have to put the password every time you do a commit or a push.
Of course, since this is a git repo, you can do what do you want (commit, push, create branches, etc). However, if you want to modify and play with the tutorial code and not change the original, you can create a branch:
git branch mybranch
git checkout mybranch
git branch
Last command is to check if the branch is there...
- Set up the SSH passwordless access to Github;
- Clone the repository;
- Read the tutorials and play with them;
- Do not forget to commit and push your changes often, in order to avoid losing your work in case of unexpected problems;
- Work on the exercises;
- When you have done the exercises, go to the final steps...
When you have completed your taks, please remember to commit and push adding a meaningful comment.
git commit -a -m "My name: Task Finished!"
git push origin master dataio-mybranch
Some of you know Python well, some reasonably well, and some do not. I hope these will be useful at different level for each of you to get more pratice on slightly advanced Python data analysis.
These exercises will be useful for the various experiences of the course, so take advantage it it and enjoy!