Published March 3, 2020
| Version v0.7.0
Software
Open
NeuralEnsemble/elephant: Release 0.7.0
Authors/Creators
- 1. Research Center Juelich
- 2. Institute of Neuroscience and Medicine (INM-6), Forschungszentrum Jülich
- 3. KyivAIGroup
- 4. INM6, Forschungzentrum Juelich
- 5. INM-6 and IAS-6, Jülich Research Centre and JARA
- 6. Ozymandian Industries
- 7. University of Cologne
- 8. Institute of Neuroscience and Medicine 6 & 10, Research Centre Jülich
Description
Breaking changes
- GPFA dimensionality reduction method is rewritten in easy-to-use scikit-learn class style format (https://github.com/NeuralEnsemble/elephant/pull/287):
gpfa = GPFA(bin_size=20*pq.ms, x_dim=8) results = gpfa.fit_transform(spiketrains, returned_data=['xorth', 'xsm'])
- GPFA dimensionality reduction method
- Unitary Event Analysis of coordinated spiking activity
- (Introductory) statistics module
- Python 2.7 support will be dropped on Dec 31, 2020. Please switch to Python 3.6, 3.7, or 3.8.
- [spike train generation]
homogeneous_poisson_process_with_refr_period(), introduced in v0.6.4, is deprecated and will be deleted in v0.8.0. Usehomogeneous_poisson_process(refractory_period=...)instead. - [pandas bridge] pandas_bridge module is deprecated and will be deleted in v0.8.0.
- New documentation style, guidelines, tutorials, and more (https://github.com/NeuralEnsemble/elephant/pull/294).
- Python 3.8 support (https://github.com/NeuralEnsemble/elephant/pull/282).
- [spike train generation] Added
refractory_periodflag inhomogeneous_poisson_process()(https://github.com/NeuralEnsemble/elephant/pull/292) andinhomogeneous_poisson_process()(https://github.com/NeuralEnsemble/elephant/pull/295) functions. The default isrefractory_period=None, meaning no refractoriness. - [spike train correlation]
cross_correlation_histogram()supports different t_start and t_stop of input spiketrains. - [waveform features]
waveform_width()function extracts the width (trough-to-peak TTP) of a waveform (https://github.com/NeuralEnsemble/elephant/pull/279). - [signal processing] Added
scaleoptflag inpairwise_cross_correlation()to mimic the behavior of Matlab'sxcorr()function (https://github.com/NeuralEnsemble/elephant/pull/277). The default isscaleopt=unbiasedto be consistent with the previous versions of Elephant. - [spike train surrogates] Joint-ISI dithering method via
JointISIclass (https://github.com/NeuralEnsemble/elephant/pull/275).
- [spike train correlation] Fix CCH Border Correction (https://github.com/NeuralEnsemble/elephant/pull/298). Now, the border correction in
cross_correlation_histogram()correctly reflects the number of bins used for the calculation at each lag. The correction factor is now unity at full overlap. - [phase analysis]
spike_triggered_phase()incorrect behavior when the spike train and the analog signal had different time units (https://github.com/NeuralEnsemble/elephant/pull/270).
- [spade] SPADE x7 speedup (https://github.com/NeuralEnsemble/elephant/pull/280, https://github.com/NeuralEnsemble/elephant/pull/285, https://github.com/NeuralEnsemble/elephant/pull/286). Moreover, SPADE is now able to handle all surrogate types that are available in Elephant, as well as more types of statistical corrections.
- [conversion] Fast & memory-efficient
covariance()and Pearsoncorrcoef()(https://github.com/NeuralEnsemble/elephant/pull/274). Added flagfast=Trueby default in both functions. - [conversion] Use fast fftconvolve instead of np.correlate in
cross_correlation_histogram()(https://github.com/NeuralEnsemble/elephant/pull/273).
Files
NeuralEnsemble/elephant-v0.7.0.zip
Files
(1.8 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/NeuralEnsemble/elephant/tree/v0.7.0 (URL)