changing tests for pynajax

draft_pynapple_fastplotlib.py

@@ -55,11 +55,11 @@ def get_memory_map(filepath, nChannels, frequency=20000):
 
 
 
-fig = fpl.Figure(shape=(2,1))
+fig = fpl.Figure(canvas="glfw", shape=(2,1))
 fig[0,0].add_line(data=lfp2, thickness=1, cmap="autumn")
 fig[1,0].add_scatter(tmp)
-fig.show()
-
+fig.show(maintain_aspect=False)
+# fpl.run()
 
 
 
@@ -68,6 +68,37 @@ def get_memory_map(filepath, nChannels, frequency=20000):
 # grid_plot['lfp'].add_line(lfp.t, lfp[:,14].d)
 
 
+import numpy as np
+import fastplotlib as fpl
+
+fig = fpl.Figure(canvas="glfw")#, shape=(2,1), controller_ids="sync")
+fig[0,0].add_line(data=np.random.randn(1000))
+fig.show(maintain_aspect=False)
+
+fig2 = fpl.Figure(canvas="glfw", controllers=fig.controllers)#, shape=(2,1), controller_ids="sync")
+fig2[0,0].add_line(data=np.random.randn(1000)*1000)
+fig2.show(maintain_aspect=False)
+
+
+
+# Not sure about this :
+fig[1,0].controller.controls["mouse1"] = "pan", "drag", (1.0, 0.0)
+
+fig[1,0].controller.controls.pop("mouse2")
+fig[1,0].controller.controls.pop("mouse4")
+fig[1,0].controller.controls.pop("wheel")
+
+import pygfx
+
+controller = pygfx.PanZoomController()
+controller.controls.pop("mouse1")
+controller.add_camera(fig[0, 0].camera)
+controller.register_events(fig[0, 0].viewport)
+
+controller2 = pygfx.PanZoomController()
+controller2.add_camera(fig[1, 0].camera)
+controller2.controls.pop("mouse1")
+controller2.register_events(fig[1, 0].viewport)
 
 
 

pynapple/core/utils.py

@@ -78,6 +78,8 @@ def convert_to_jax_array(array, array_name):
         return array
     elif isinstance(array, np.ndarray):
         return cast_to_jax(array, array_name)
+    elif is_array_like(array):
+        return cast_to_jax(array, array_name)
     else:
         raise RuntimeError(
             "Unknown format for {}. Accepted formats are numpy.ndarray, list, tuple or any array-like objects.".format(

tests/test_non_numpy_array.py

@@ -99,7 +99,8 @@ def test_tsd_type_d(self, time, data, expectation):
         """Verify that the data attribute 'd' of a Tsd object is stored as a numpy.ndarray."""
         with expectation:
             ts = nap.Tsd(t=time, d=data)
-            assert isinstance(ts.d, np.ndarray)
+            if nap.nap_config.backend == "numba":
+                assert isinstance(ts.d, np.ndarray)
 
     @pytest.mark.filterwarnings("ignore")
     @pytest.mark.parametrize(
@@ -132,8 +133,9 @@ def test_tsd_type_t(self, time, data, expectation):
     )
     def test_tsd_warn(self, data, expectation):
         """Check for warnings when the data attribute 'd' is automatically converted to numpy.ndarray."""
-        with expectation:
-            nap.Tsd(t=np.array(data), d=data)
+        if nap.nap_config.backend == "numba":
+            with expectation:
+                nap.Tsd(t=np.array(data), d=data)
 
 
 class TestTsdFrameArray:
@@ -169,7 +171,8 @@ def test_tsdframe_type(self, time, data, expectation):
         """Verify that the data attribute 'd' of a TsdFrame object is stored as a numpy.ndarray."""
         with expectation:
             ts = nap.TsdFrame(t=time, d=data)
-            assert isinstance(ts.d, np.ndarray)
+            if nap.nap_config.backend == "numba":
+                assert isinstance(ts.d, np.ndarray)
 
     @pytest.mark.filterwarnings("ignore")
     @pytest.mark.parametrize(
@@ -202,8 +205,9 @@ def test_tsdframe_type_t(self, time, data, expectation):
     )
     def test_tsdframe_warn(self, data, expectation):
         """Check for warnings when the data attribute 'd' is automatically converted to numpy.ndarray."""
-        with expectation:
-            nap.TsdFrame(t=np.array(data), d=data)
+        if nap.nap_config.backend == "numba":
+            with expectation:
+                nap.TsdFrame(t=np.array(data), d=data)
 
 
 class TestTsdTensorArray:
@@ -245,7 +249,8 @@ def test_tsdtensor_type_d(self, time, data, expectation):
         """Verify that the data attribute 'd' of a TsdTensor object is stored as a numpy.ndarray."""
         with expectation:
             ts = nap.TsdTensor(t=time, d=data)
-            assert isinstance(ts.d, np.ndarray)
+            if nap.nap_config.backend == "numba":
+                assert isinstance(ts.d, np.ndarray)
 
     @pytest.mark.filterwarnings("ignore")
     @pytest.mark.parametrize(
@@ -278,6 +283,7 @@ def test_tsdtensor_type_t(self, time, data, expectation):
     )
     def test_tsdtensor_warn(self, data, expectation):
         """Check for warnings when the data attribute 'd' is automatically converted to numpy.ndarray."""
-        with expectation:
-            nap.TsdTensor(t=np.ravel(np.array(data)), d=data)
+        if nap.nap_config.backend == "numba":
+            with expectation:
+                nap.TsdTensor(t=np.ravel(np.array(data)), d=data)