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Merge pull request #333 from pynapple-org/dev
New version 0.7
2 parents c2df9e6 + abec0c6 commit deca7e2

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.github/workflows/main.yml

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branches: [ main ]
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pull_request:
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branches: [ main, dev ]
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types:
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- opened
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- reopened
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- synchronize
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- ready_for_review
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jobs:
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lint:

.gitignore

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*.npz
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*.nwb
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*.pickle
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*.py.md5
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*.npz
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#*.npz
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/docs/generated/gallery/*.md
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/docs/generated/gallery/*.ipynb
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/docs/generated/gallery/*.py
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/docs/generated/gallery/*.zip
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/tests/npzfilestest
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]

MANIFEST.in

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README.md

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New release :fire:
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------------------
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### pynapple >= 0.7
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Pynapple now implements signal processing. For example, to filter a 1250 Hz sampled time series between 10 Hz and 20 Hz:
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```python
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nap.apply_bandpass_filter(signal, (10, 20), fs=1250)
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```
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New functions includes power spectral density and Morlet wavelet decomposition. See the [documentation](https://pynapple-org.github.io/pynapple/reference/process/) for more details.
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### pynapple >= 0.6
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Starting with 0.6, [`IntervalSet`](https://pynapple-org.github.io/pynapple/reference/core/interval_set/) objects are behaving as immutable numpy ndarray. Before 0.6, you could select an interval within an `IntervalSet` object with:
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new_intervalset = intervalset[0]
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```
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See the [documentation](https://pynapple-org.github.io/pynapple/reference/core/interval_set/) for more details.
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### pynapple >= 0.4
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Starting with 0.4, pynapple rely on the [numpy array container](https://numpy.org/doc/stable/user/basics.dispatch.html) approach instead of Pandas for the time series. Pynapple builtin functions will remain the same except for functions inherited from Pandas.

docs/AUTHORS.md

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----------------
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- Guillaume Viejo <[email protected]>
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- Edoardo Balzani <[email protected]>
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Contributors
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------------
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- Edoardo Balzani <[email protected]>
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- Adrien Peyrache
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- Dan Levenstein
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- Sofia Skromne Carrasco
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- Davide Spalla
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- Luigi Petrucco
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- Luigi Petrucco
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- ... [and many more!](https://github.com/pynapple-org/pynapple/graphs/contributors)

docs/HISTORY.md

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Around 2016-2017, Luke Sjulson started *TSToolbox2*, still in Matlab and which includes some important changes.
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In 2018, Francesco started neuroseries, a Python package built on Pandas. It was quickly adopted in Adrien's lab, especially by Guillaume Viejo, a postdoc in the lab. Gradually, the majority of the lab was using it and new functions were constantly added.
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In 2021, Guillaume and other trainees in Adrien's lab decided to fork from neuroseries and started *pynapple*. The core of pynapple is largely built upon neuroseries. Some of the original changes to TSToolbox made by Luke were included in this package, especially the *time_support* property of all ts/tsd objects.
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In 2021, Guillaume and other trainees in Adrien's lab decided to fork from neuroseries and started *pynapple*.
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The core of pynapple is largely built upon neuroseries. Some of the original changes to TSToolbox made by Luke were included in this package, especially the *time_support* property of all ts/tsd objects.
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Since 2023, the development of pynapple is lead by [Guillaume Viejo](https://www.simonsfoundation.org/people/guillaume-viejo/)
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and [Edoardo Balzani](https://www.simonsfoundation.org/people/edoardo-balzani/) at the Center for Computational Neuroscience
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of the Flatiron institute.
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0.7.0 (2024-09-16)
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------------------
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- Morlet wavelets spectrogram with utility for plotting the wavelets.
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- (Mean) Power spectral density. Returns a Pandas DataFrame.
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- Convolve function works for any dimension of time series and any dimensions of kernel.
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- `dtype` in count function
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- `get_slice`: public method with a simplified API, argument start, end, time_units. returns a slice that matches behavior of Base.get.
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- `_get_slice`: private method, adds the argument "mode" this can be: "after_t", "before_t", "closest_t", "restrict".
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- `split` method for IntervalSet. Argument is `interval_size` in time unit.
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- Changed os import to pathlib.
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- Fixed pickling issue. TsGroup can now be saved as pickle.
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- TsGroup can be created from an iterable of Ts/Tsd objects.
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- IntervalSet can be created from (start, end) pairs
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0.6.6 (2024-05-28)
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