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Release 0.7.0
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@dizcza dizcza released this 03 Mar 12:19
· 232 commits to master since this release
v0.7.0
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Learn about vigilant mode.

Breaking changes

  • GPFA dimensionality reduction method is rewritten in easy-to-use scikit-learn class style format (#287): 
     gpfa = GPFA(bin_size=20*pq.ms, x_dim=8)
 results = gpfa.fit_transform(spiketrains, returned_data=['xorth', 'xsm'])

New tutorials

Deprecations

  • 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. Use homogeneous_poisson_process(refractory_period=...) instead.
  • [pandas bridge] pandas_bridge module is deprecated and will be deleted in v0.8.0.

New features

  • New documentation style, guidelines, tutorials, and more (#294).
  • Python 3.8 support (#282).
  • [spike train generation] Added refractory_period flag in homogeneous_poisson_process() (#292) and inhomogeneous_poisson_process() (#295) functions. The default is refractory_period=None, meaning no refractoriness.
  • [spike train correlation] cross_correlation_histogram() supports different t_start and t_stop of input spiketrains (#291).
  • [waveform features] waveform_width() function extracts the width (trough-to-peak TTP) of a waveform (#279).
  • [signal processing] Added scaleopt flag in pairwise_cross_correlation() to mimic the behavior of Matlab's xcorr() function (#277). The default is scaleopt=unbiased to be consistent with the previous versions of Elephant.
  • [spike train surrogates] Joint-ISI dithering method via JointISI class (#275).

Bug fixes

  • [spike train correlation] Fix CCH Border Correction (#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 (#270).

Performance

  • [spade] SPADE x7 speedup (#280, #285, #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 Pearson corrcoef() (#274). Added flag fast=True by default in both functions.
  • [conversion] Use fast fftconvolve instead of np.correlate in cross_correlation_histogram() (#273).
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