Responses of 1st , 2nd, and soon 3rd order Drosophila olfactory neurons
Project description
Installation
pip install drosolf
If you need elevated permissions to install (if the pip install line fails with some sort of permissions error), you can try:
sudo -H pip install drosolf
Examples
To get Hallem and Carlson ORN responses, with the baseline added back in. Returned as a pandas DataFrame with columns of receptor and row indices of odor. The transpose (i.e. orn_responses.T) will have odors as the columns.
from drosolf import orns orn_responses = orns.orns()
To get simulated projection neuron responses, using the Olsen input gain control model and the ORN responses.
from drosolf import pns pn_responses = pns.pns()
Get correlation matrices at the ORN and (simulated) PN levels for a list of odors, named as the columns of the previous DataFrames.
from drosolf import corrs orn_correlations, pn_correlations = corrs.get_corrs(list_of_odors)
Generate plots of the same ORN and PN correlation matrices (uses seaborn).
import matplotlib.pyplot as plt from drosolf import corrs corrs.plot_corrs(list_of_odors) plt.show()
Todo
DoOR integration
KC model(s)
sympy description of transformations applied to ORN data
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for drosolf-0.1.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9d1ede6275ce289633f7f33806bf98170a8b0d3a682606c47dad5e1fd6be2377 |
|
MD5 | 273a51880ed5906a3b9145bf24055918 |
|
BLAKE2b-256 | abd7b7e8802e2a6bbba4b8f5ee694818ab1efabe74e155dbf75bc5c0390a9dc7 |