Merge pull request #189 from pynapple-org/dev

Dev

pynapple/core/interval_set.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 # @Date:   2022-01-25 21:50:48
-# @Last Modified by:   Guillaume Viejo
-# @Last Modified time: 2023-09-21 16:01:25
+# @Last Modified by:   gviejo
+# @Last Modified time: 2023-10-15 16:18:42
 
 """
 """
@@ -15,8 +15,6 @@
 from numba import jit
 
 from .jitted_functions import jitdiff, jitin_interval, jitintersect, jitunion
-
-# from .time_units import format_timestamps, return_timestamps, sort_timestamps
 from .time_index import TsIndex
 
 all_warnings = np.array(

pynapple/core/jitted_functions.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 # @Author: guillaume
 # @Date:   2022-10-31 16:44:31
-# @Last Modified by:   Guillaume Viejo
-# @Last Modified time: 2023-09-21 18:00:13
+# @Last Modified by:   gviejo
+# @Last Modified time: 2023-10-15 16:05:27
 import numpy as np
 from numba import jit
 

pynapple/core/time_series.py

@@ -2,7 +2,7 @@
 # @Author: gviejo
 # @Date:   2022-01-27 18:33:31
 # @Last Modified by:   gviejo
-# @Last Modified time: 2023-10-13 11:19:12
+# @Last Modified time: 2023-10-18 11:16:43
 
 """
 
@@ -171,6 +171,10 @@ def shape(self):
     def ndim(self):
         return self.values.ndim
 
+    @property
+    def size(self):
+        return self.values.size
+
     def __repr__(self):
         return str(self.__class__)
 
@@ -719,6 +723,37 @@ def copy(self):
             t=self.index.copy(), d=self.values.copy(), time_support=self.time_support
         )
 
+    def find_support(self, min_gap, time_units="s"):
+        """
+        find the smallest (to a min_gap resolution) IntervalSet containing all the times in the Tsd
+
+        Parameters
+        ----------
+        min_gap : float
+            minimal interval between timestamps
+        time_units : str, optional
+            Time units of min gap
+
+        Returns
+        -------
+        IntervalSet
+            Description
+        """
+        assert isinstance(min_gap, Number), "min_gap should be a float or int"
+        min_gap = TsIndex.format_timestamps(np.array([min_gap]), time_units)[0]
+        time_array = self.index.values
+
+        starts = [time_array[0]]
+        ends = []
+        for i in range(len(time_array) - 1):
+            if (time_array[i + 1] - time_array[i]) > min_gap:
+                ends.append(time_array[i] + 1e-6)
+                starts.append(time_array[i + 1])
+
+        ends.append(time_array[-1] + 1e-6)
+
+        return IntervalSet(start=starts, end=ends)
+
 
 class TsdTensor(NDArrayOperatorsMixin, _AbstractTsd):
     """
@@ -1779,22 +1814,3 @@ def save(self, filename):
     #     s, e = jitfind_gaps(time_array, starts, ends, min_gap)
 
     #     return nap.IntervalSet(s, e)
-
-    # def find_support(self, min_gap, method="absolute"):
-    #     """
-    #     find the smallest (to a min_gap resolution) IntervalSet containing all the times in the Tsd
-
-    #     Parameters
-    #     ----------
-    #     min_gap : float
-    #         Description
-    #     method : str, optional
-    #         Description
-
-    #     Returns
-    #     -------
-    #     TYPE
-    #         Description
-    #     """
-    #     print("TODO")
-    #     return

tests/test_time_series.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 # @Author: gviejo
 # @Date:   2022-04-01 09:57:55
-# @Last Modified by:   Guillaume Viejo
-# @Last Modified time: 2023-09-25 16:01:32
+# @Last Modified by:   gviejo
+# @Last Modified time: 2023-10-18 11:18:07
 #!/usr/bin/env python
 
 """Tests of time series for `pynapple` package."""
@@ -213,6 +213,38 @@ def test_index_error():
     with pytest.raises(IndexError):
         ts[1000]
 
+def test_find_support():
+    tsd = nap.Tsd(t=np.arange(100), d=np.arange(100))
+    ep = tsd.find_support(1.0)
+    assert ep.loc[0, 'start'] == 0
+    assert ep.loc[0, 'end'] == 99.0 + 1e-6
+
+    t = np.hstack((np.arange(10), np.arange(20, 30)))
+    tsd = nap.Tsd(t=t, d=np.arange(20))
+    ep = tsd.find_support(1.0)
+    np.testing.assert_array_equal(ep.start.values, np.array([0.0, 20.0]))
+    np.testing.assert_array_equal(ep.end.values, np.array([9.0+1e-6, 29+1e-6]))
+
+def test_properties():
+    t = np.arange(100)
+    d = np.random.rand(100)
+    tsd = nap.Tsd(t=t, d = d)
+
+    assert hasattr(tsd, "t")
+    assert hasattr(tsd, "d")
+    assert hasattr(tsd, "start")
+    assert hasattr(tsd, "end")
+    assert hasattr(tsd, "shape")
+    assert hasattr(tsd, "ndim")
+    assert hasattr(tsd, "size")
+
+    np.testing.assert_array_equal(tsd.t, t)
+    np.testing.assert_array_equal(tsd.d, d)
+    assert tsd.start == 0.0
+    assert tsd.end == 99.0
+    assert tsd.shape == (100,)
+    assert tsd.ndim == 1
+    assert tsd.size == 100
 
 ####################################################
 # General test for time series