v0.4.1

v0.4.1

Version 0.4.1 is a bug-fixing patch release for version 0.4. This includes changes to importing of BatchSimulate due to previously-undetected install/import issues (#1034), configuration of packaging metadata format (same PR), and elimination of a discrepancy in our method of cleaning local compiled files that led to architecture-specific files being included in the Pypi 0.4 release, which caused simulations on some platforms to fail (#1035 ). The public Pypi version has already been updated to 0.4.1.

For release notes about what is new for this version and 0.4, see https://github.com/jonescompneurolab/hnn-core/releases/tag/v0.4 .

v0.4

v0.4

v0.4 represents a major milestone in development of hnn_core and the HNN ecosystem as a whole. v0.4 includes over two years of active development work by many people (>800 commits!), and brings with it many new and exciting features, including significant improvements to robustness, testing, and bug-fixing.

New Features

• hnn_core now includes a fully-tested and robust GUI of its own. The hnn_core GUI was present as a prototype in v0.3, but it is now ready for production. New features and visual improvements will still be coming to it in the future, such as the ability to use optimization. See our new Install page for ways to install it, and we have already begun incorporating it into a new, fresh series of tutorials for our upcoming revamp of the HNN website. If you have installed it, you can start the GUI using hnn-gui in your terminal/command prompt window.

• The BatchSimulate class: Thanks to [Abdul Samad Siddiqui][] and Google Summer of Code 2024, there is now the capability to run "batches" of simulations across multiple parameter sets, enabling easy analysis and simulation of behavior across parameter sweeps. See our example for more details. Note that currently, only its loky backend is supported, and the "hnn-core[parallel]" dependencies must be installed for it to be used.

• Significant improvements to the API, documentation, and pedagogical examples especially for Optimization, among others.

• Calcium concentration can now be recorded: recorded calcium concentration from either the soma,
  or all sections, are enabled by setting record_ca to soma or all in
  hnn_core.simulate_dipole. Recordings are accessed through
  hnn_core.CellResponse.ca.

• There is now a new class hnn_core.viz.NetworkPlotter which can be used to visualize an entire network in 3D, including firing animations; see our example of how to use it here.

• There is now a new function hnn_core.viz.plot_drive_strength for illustrating the absolute or relative amount of strength that a particular drive provides to different cell types.

• A very large amount of polishing, bug fixes, general improvements, etc.

Deprecations

• The new Python 3.13 is not supported by hnn_core at this time, due to NEURON's current lack of support for it. This will change in the near future. We still support 3.8 through 3.12 (inclusively).

Upcoming Deprecations

• Both hnn_core.viz.plot_laminar_lfp and hnn_core.viz.plot_dipole will have their tmin and tmax arguments removed in the future. Please set the x-axis limits using methods called directly on the existing matplotlib objects, or using matplotlib.pyplot.xlim.
• hnn_core.Network's argument of legacy_mode for importing old param files will be removed in the future.
• hnn_core.Network.add_tonic_bias's argument of cell_type, along with setting the argument amplitude to a single float, will be removed in the future. Instead, set the amplitude argument to a dictionary as described in the docstring.
• hnn_core.simulate_dipole's argument of postproc for post-processing will be removed in the future. Instead, use explicit smoothing and scaling via hnn_core.Dipole methods.

API Changes

• New argument to hnn_core.Network initialization: you can now set mesh_shape to easily make a grid of different sizes of Networks.
• hnn_core.Cell initialization argument topology has had both its name changed to cell_tree and its data type significantly changed; see the API docs of Cell for details.
• hnn_core.jones_2009_model and other built-in Network Models including hnn_core.law_2021_model and hnn_core.calcium_model all accept the aforementioned mesh_shape argument like hnn_core.Network.
• The API for optimization has changed significantly. Instead of running the function optimize_evoked obtained using from hnn_core.optimization import optimize_evoked, you should use the new hnn_core.optimization.Optimizer class and its methods; see our example of evoked-response optimization here.
• hnn_core.viz.plot_spikes_hist now accepts more arguments, including invert_spike_types, color, and any **kwargs_hist which can be applied to matplotlib.axes.Axes.hist. See the docstring for details.
• hnn_core.viz.plot_spikes_raster now accepts many more arguments, including cell_types, colors, show_legend, marker_size, dpl, and overlay_dipoles. See the docstring for details.
• hnn_core.viz.plot_cell_morphology now accepts more arguments, including color and several arguments related to its position and viewing window, including pos, xlim, ylim, and zlim. See the docstring for details.
• hnn_core.viz.plot_laminar_csd now accepts more arguments, including vmin, vmax, sink, and interpolation. See the docstring for details.
• hnn_core.parallel_backends.MPIBackend now accepts many more arguments, including use_hwthreading_if_found, sensible_default_cores, override_hwthreading_option, and override_oversubscribe_option. See the docstring for details; the ability to customize it has been greatly increased.
• hnn_core.read_params now accepts a new argument file_contents which lets you pass in network configuration contents using a string.

People who contributed to this release (in alphabetical order of family name):

• Huzi Cheng
• [Tianqi Cheng][]
• [George Dang][]
• Dylan Daniels
• [Camilo Diaz][]
• [Katharina Duecker][]
• [Yaroslav Halchenko][]
• Mainak Jas
• [Dikshant Jha][]
• [Stephanie R. Jones][]
• [Shehroz Kashif][]
• Rajat Partani
• [Carolina Fernandez Pujol][]
• [Dan Toms][]
• [Abdul Samad Siddiqui][]
• [Austin E. Soplata][]
• [Ryan Thorpe][]
• Nick Tolley

[Ryan Tho...

v0.4rc0

v0.4rc0

v0.3.1

NOTE

• This GitHub release was not mirrored by a PyPI release (GitHub-only).
• It was done to trigger a Zenodo release to be used by JOSS.

v0.3

v0.3

v0.2

v0.2

v0.1

v0.1