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Responses of 1st , 2nd, and soon 3rd order Drosophila olfactory neurons

Project Description


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


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



  • DoOR integration
  • KC model(s)
  • sympy description of transformations applied to ORN data
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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
drosolf-0.1.1-py2.py3-none-any.whl (9.5 kB) Copy SHA256 Checksum SHA256 py2.py3 Wheel Dec 14, 2017
drosolf-0.1.1.tar.gz (20.6 kB) Copy SHA256 Checksum SHA256 Source Dec 14, 2017

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