Perform the analysis also by pooling data from all directions

[lauraporta]

Description

What is this PR

• Bug fix
• Addition of a new feature
• Other

Why is this PR needed?
We would like to see the median subtracted response and the gaussian plots calculated by pooling the directions as well. The statistical tests were already done with this principle.

What does this PR do?

• Adds the code required to pool directions data in the FrequencyResponsiveness class.
• Expands the docs
• Fixes some errors in pyproject.toml file
• Updates tests to include new functionalities

References

Does the analysis required for #44.
Giving a look at the readme file could be useful to have an overview of the analysis; there is also a diagram to help you out.
This presentation could help as well.

How has this PR been tested?

The previous tests keep working also given the new functionality

Is this a breaking change?

No

Does this PR require an update to the documentation?

Docstrings for new methods have been added, as well as a general explanation of the package in the readme file.

Checklist:

• The code has been tested locally
• Tests have been added to cover all new functionality
• The documentation has been updated to reflect any changes
• The code has been formatted with pre-commit

[niksirbi]

Review summary

Great job @lauraporta. I found the code very well written and easy to follow. Reading the README and the presentation helped me a lot.

I've left a bunch of comments for things that were not entirely clear to me, but mostly they are about typos or pedantic stuff about variable and function names. The most confusing part is the thing about the "mean of medians" and calculating stuff with directions pooled or not. Maybe some equations/diagrams would help with this.

Other than that, nothing substantial to say.

P.S:

This doesn't belong on this PR, but I'll say it here so I don't forget. It's probably not worth storig the gaussian matrices in the pickle file. The time-consuming step is probably the fitting. You can just store the fit parameters, and derive the matrices during the dashboard runtime.