How to Install and Uninstall python3-lfpykit.noarch Package on Fedora 34

Last metadata expiration check: 0:16:57 ago on Tue Sep 6 08:10:37 2022.
Available Packages
Name : python3-lfpykit
Version : 0.4
Release : 1.fc34
Architecture : noarch
Size : 110 k
Source : python-lfpykit-0.4-1.fc34.src.rpm
Repository : updates
Summary : Electrostatic models for multicompartment neuron models
URL : https://pypi.org/pypi/LFPykit
License : GPLv3+
Description : This Python module contain freestanding implementations of electrostatic
: forward models incorporated in LFPy (https://github.com/LFPy/LFPy,
: https://LFPy.readthedocs.io).
:
: The aim of the LFPykit module is to provide electrostatic models in a manner
: that facilitates forward-model predictions of extracellular potentials and
: related measures from multicompartment neuron models, but without explicit
: dependencies on neural simulation software such as NEURON
: (https://neuron.yale.edu, https://github.com/neuronsimulator/nrn), Arbor
: (https://arbor.readthedocs.io, https://github.com/arbor-sim/arbor), or even
: LFPy. The LFPykit module can then be more easily incorporated with these
: simulators, or in various projects that utilize them such as LFPy
: (https://LFPy.rtfd.io, https://github.com/LFPy/LFPy). BMTK
: (https://alleninstitute.github.io/bmtk/,
: https://github.com/AllenInstitute/bmtk), etc.
:
: Its main functionality is providing class methods that return two-dimensional
: linear transformation matrices M between transmembrane currents I of
: multicompartment neuron models and some measurement Y given by Y=MI.
:
: The presently incorporated volume conductor models have been incorporated in
: LFPy (https://LFPy.rtfd.io, https://github.com/LFPy/LFPy), as described in
: various papers and books:
:
: - Linden H, Hagen E, Leski S, Norheim ES, Pettersen KH, Einevoll GT (2014) LFPy:
: a tool for biophysical simulation of extracellular potentials generated by
: detailed model neurons. Front. Neuroinform. 7:41. doi: 10.3389/fninf.2013.00041
:
: - Hagen E, Næss S, Ness TV and Einevoll GT (2018) Multimodal Modeling of Neural
: Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0.
: Front. Neuroinform. 12:92. doi: 10.3389/fninf.2018.00092
:
: - Ness, T. V., Chintaluri, C., Potworowski, J., Leski, S., Glabska, H., Wójcik,
: D. K., et al. (2015). Modelling and analysis of electrical potentials recorded
: in microelectrode arrays (MEAs). Neuroinformatics 13:403–426. doi:
: 10.1007/s12021-015-9265-6
:
: - Nunez and Srinivasan, Oxford University Press, 2006
:
: - Næss S, Chintaluri C, Ness TV, Dale AM, Einevoll GT and Wójcik DK (2017).
: Corrected Four-sphere Head Model for EEG Signals. Front. Hum. Neurosci. 11:490.
: doi: 10.3389/fnhum.2017.00490