Merge pull request #231 from pynapple-org/dev

Dev

README.md

@@ -29,12 +29,32 @@ pynapple is a light-weight python library for neurophysiological data analysis.
 ------------------------------------------------------------------------
 
 New release :fire:
----------------
-Starting with 0.4, pynapple rely on the [numpy array container](https://numpy.org/doc/stable/user/basics.dispatch.html) approach instead of Pandas. Pynapple builtin functions will remain the same except for functions inherited from Pandas. Typically this line of code in `pynapple<=0.3.6` :
+------------------
+
+### pynapple >= 0.6
+
+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:
+
+```python
+new_intervalset = intervalset.loc[[0]] # Selecting first interval
+```
+
+With pynapple>=0.6, the slicing is similar to numpy and it returns an `IntervalSet`
+
+```python
+new_intervalset = intervalset[0]
+```
+
+See the [documentation](https://pynapple-org.github.io/pynapple/reference/core/interval_set/) for more details.
+
+
+### pynapple >= 0.4
+
+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. Typically this line of code in `pynapple<=0.3.6` :
 ```python
 meantsd = tsdframe.mean(1)
 ```
-is now:
+is now :
 ```python
 meantsd = np.mean(tsdframe, 1)
 ```

docs/HISTORY.md

@@ -9,6 +9,14 @@ In 2018, Francesco started neuroseries, a Python package built on Pandas. It was
 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.
 
 
+0.6.0 (coming)
+------------------
+
+- Refactoring `IntervalSet` to pure numpy ndarray.
+- Implementing new chain of inheritance for time series with abstract base class. `base_class.Base` holds the temporal methods for all time series and `Ts`. `time_series.BaseTsd` inherit `Base` and implements the common methods for `Tsd`, `TsdFrame` and `Tsd`.
+- Automatic conversion to numpy ndarray for all objects that are numpy-like (typically jax).
+
+
 0.5.1 (2024-01-29)
 ------------------
 

docs/examples/tutorial_HD_dataset.py

@@ -236,7 +236,7 @@ def smoothAngularTuningCurves(tuning_curves, sigma=2):
     np.transpose(p_feature.restrict(ep).values),
     aspect="auto",
     interpolation="bilinear",
-    extent=[ep["start"].values[0], ep["end"].values[0], 0, 2 * np.pi],
+    extent=[ep["start"][0], ep["end"][0], 0, 2 * np.pi],
     origin="lower",
     cmap="viridis",
 )

docs/examples/tutorial_pynapple_core.py

@@ -85,7 +85,7 @@
 # Multiple operations are available for IntervalSet. For example, IntervalSet can be merged. See the full documentation of the class [here](https://peyrachelab.github.io/pynapple/core.interval_set/#pynapple.core.interval_set.IntervalSet.intersect) for a list of all the functions that can be used to manipulate IntervalSets.
 
 
-epoch1 = nap.IntervalSet(start=[0], end=[10])  # no time units passed. Default is us.
+epoch1 = nap.IntervalSet(start=0, end=10)  # no time units passed. Default is us.
 epoch2 = nap.IntervalSet(start=[5, 30], end=[20, 45])
 
 epoch = epoch1.union(epoch2)

docs/examples/tutorial_pynapple_process.py

@@ -49,7 +49,7 @@
 ts2_time_array = ts2.as_units("s").index.values
 
 binsize = 0.1  # second
-cc12, xt = nap.cross_correlogram(
+cc12, xt = nap.process.correlograms.cross_correlogram(
     t1=ts1_time_array, t2=ts2_time_array, binsize=binsize, windowsize=1  # second
 )
 
@@ -152,7 +152,7 @@
 # To check the accuracy of the tuning curves, we will display the spikes aligned to the features with the function `value_from` which assign to each spikes the corresponding feature value for neuron 0.
 
 tcurves2d, binsxy = nap.compute_2d_tuning_curves(
-    group=ts_group, feature=features, nb_bins=10
+    group=ts_group, features=features, nb_bins=10
 )
 
 ts_to_features = ts_group[1].value_from(features)
@@ -203,7 +203,7 @@
 
 tcurves2d, binsxy = nap.compute_2d_tuning_curves(
     group=ts_group,
-    feature=features,
+    features=features,
     nb_bins=10,
     ep=epoch,
     minmax=(-1.0, 1.0, -1.0, 1.0),

docs/index.md

@@ -27,10 +27,28 @@ Community
 
 To ask any questions or get support for using pynapple, please consider joining our slack. Please send an email to thepynapple[at]gmail[dot]com to receive an invitation link.
 
-New release :fire:
+New releases :fire:
 ------------------
 
-Starting with 0.4, pynapple rely on the [numpy array container](https://numpy.org/doc/stable/user/basics.dispatch.html) approach instead of Pandas. Pynapple builtin functions will remain the same except for functions inherited from Pandas. Typically this line of code in `pynapple<=0.3.6` :
+### pynapple >= 0.6
+
+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:
+
+```python
+new_intervalset = intervalset.loc[[0]] # Selecting first interval
+```
+
+With pynapple>=0.6, the slicing is similar to numpy and it returns an `IntervalSet`
+
+```python
+new_intervalset = intervalset[0]
+```
+
+See the [documentation](https://pynapple-org.github.io/pynapple/reference/core/interval_set/) for more details.
+
+### pynapple >= 0.4
+
+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. Typically this line of code in `pynapple<=0.3.6` :
 ```python
 meantsd = tsdframe.mean(1)
 ```

pynapple/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.5.1"
-from .core import *
+__version__ = "0.6.0"
+from .core import IntervalSet, Ts, Tsd, TsdFrame, TsdTensor, TsGroup, TsIndex, config
 from .io import *
 from .process import *

pynapple/core/__init__.py

@@ -1,3 +1,4 @@
+from . import config
 from .interval_set import IntervalSet
 from .time_index import TsIndex
 from .time_series import Ts, Tsd, TsdFrame, TsdTensor

pynapple/core/_jitted_functions.py

@@ -1,8 +1,3 @@
-# -*- coding: utf-8 -*-
-# @Author: guillaume
-# @Date:   2022-10-31 16:44:31
-# @Last Modified by:   Guillaume Viejo
-# @Last Modified time: 2024-01-25 16:43:34
 import numpy as np
 from numba import jit, njit, prange