Base knife-edge scan analysis implementation

Hi @lleguy @mercadil,

This is an example of a base implementation, specifically the knife edge scan analysis from Laurent's tb.knife_edge. This is agnostic from xarray data format, thus this can be easily used on other means, such as on a Karabo device.

I also have found out that there could be problems with using bisect especially with repetitive elements. I use slicing instead to find the valid range.

src/toolbox_scs/base/tests/test_knife_edge.py

@@ -45,7 +45,7 @@ def test_range_mask():
     np.testing.assert_array_equal(slice_, [False, False, True, False, True])
 
 
-def test_prepare_arrays():
+def test_prepare_arrays_nans():
     # Setup test values
     trains, pulses = 5, 10
     size = trains * pulses
@@ -74,6 +74,23 @@ def test_prepare_arrays():
     assert np.isfinite(intensities).all()
 
 
+def test_prepare_arrays_size():
+    trains, pulses = 5, 10
+    size = trains * pulses
+    motor = np.arange(trains)
+    signal = np.random.randint(100, size=(trains, pulses))
+
+    # Test finite motor and 2D signals
+    positions, intensities = prepare_arrays(motor, signal)
+    assert positions.shape == (size,)
+    assert intensities.shape == (size,)
+
+    # Test finite motor and 1D signals
+    positions, intensities = prepare_arrays(motor, signal.reshape(1, -1))
+    assert positions.shape == (size,)
+    assert intensities.shape == (size,)
+
+
 def with_values(array, value, num=5):
     copy = array.astype(np.float)
     copy.ravel()[np.random.choice(copy.size, num, replace=False)] = value