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https://github.com/int-brain-lab/paper-brain-wide-map
Code related to the brainwide map paper
https://github.com/int-brain-lab/paper-brain-wide-map
Last synced: about 1 month ago
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Code related to the brainwide map paper
- Host: GitHub
- URL: https://github.com/int-brain-lab/paper-brain-wide-map
- Owner: int-brain-lab
- License: mit
- Created: 2020-11-09T17:33:32.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2024-10-17T13:41:58.000Z (2 months ago)
- Last Synced: 2024-10-19T12:59:46.322Z (2 months ago)
- Language: Python
- Size: 5.68 MB
- Stars: 11
- Watchers: 30
- Forks: 2
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# paper-brain-wide-map
Code related to the brainwide map paper
# Contents
- [Installation](#installation)
- [Demo](#minimal-working-example-query-information-about-bwm-data)
# Installation
The installation instructions go through the step of setting up a conda environment, installing dependencies, and linking this repository source code to the environment.
This usually takes a few minutes on a fast internet connection and a consumer laptop.
## Create a new python environment (optional)
Install [Anaconda](https://www.anaconda.com/distribution/#download-section) and [git](https://git-scm.com/downloads),
and follow their installer instructions to add each to the system path
Create new python environment
```
conda create --name ibl_bwm python=3.10
```
Activate environment
```
conda activate ibl_bwm
```
## Setup the paper-brain-wide-map repository
Clone the repo
```
git clone https://github.com/int-brain-lab/paper-brain-wide-map.git
```
Navigate to repo
```
cd paper-brain-wide-map
```
Install requirements and repo.
Note a frozen set of requirements is provided in `requirements_frozen.txt` for reference.
The installation will rely on `requirements.txt` to maintain compatibility with the latest scientific Python ecosystem.
```
pip install -e .
```
To install additional requirements for the individual analyses, see the README files in the respective subfolders in `brainwidemap`
# Minimal working example: query information about BWM data
You can now use the following in Python after having setup ONE as described [here](https://int-brain-lab.github.io/iblenv/notebooks_external/one_quickstart.html)
The first connection should take a minute, subsequent connections should be faster.
```python
from brainwidemap import bwm_query, bwm_units
from one.api import ONE
one = ONE(base_url='https://openalyx.internationalbrainlab.org')
# Dataframe with info on all sessions and probes released for the BWM
bwm_df = bwm_query(one)
# Dataframe with information on all neurons used in the analyses in the BWM paper
unit_df = bwm_units(one)
unit_df.describe()
```
Should return
```
In [2]: unit_df.describe()
Out[2]:
depths channels cluster_id ... z atlas_id axial_um lateral_um
count 31344.000000 31344.000000 31344.000000 ... 31344.000000 3.134400e+04 31344.000000 31344.000000
mean 1872.586779 185.753765 378.037296 ... -0.003130 2.301535e+07 1872.586779 35.283818
std 1070.074064 107.010005 321.481276 ... 0.001366 9.726513e+07 1070.074064 19.206001
min 20.000000 0.000000 0.000000 ... -0.007059 2.000000e+00 20.000000 11.000000
25% 935.000000 91.750000 147.000000 ... -0.003970 2.660000e+02 935.000000 11.000000
50% 1800.000000 179.000000 293.000000 ... -0.003206 6.720000e+02 1800.000000 43.000000
75% 2840.000000 282.000000 500.000000 ... -0.002171 9.880000e+02 2840.000000 59.000000
max 3840.000000 383.000000 1829.000000 ... 0.000053 6.144543e+08 3840.000000 59.000000
```
For further data loading examples see `data_loading_examples.py`
# Reproducing a basic set of results
The following notebook shows a simple example of how to reproduce basic parts of the analysis on a subset of the data.
https://colab.research.google.com/drive/1V6Cgi8vsKz0I3BOkFuq6lULb9we82vYr