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

@@ -86,9 +86,9 @@ def test_prepare_arrays_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,)
+    positions, intensities = prepare_arrays(motor, signal[:, 0])
+    assert positions.shape == (trains,)
+    assert intensities.shape == (trains,)
 
 
 def test_knife_edge_base():
@@ -96,14 +96,14 @@ def test_knife_edge_base():
     x = np.linspace(-3, 3)
     y = erfc(x, *p0)
     noise = y * np.random.normal(0, .02, y.shape)  # 2% error
-    eff_y = (y + noise).reshape(1, -1)
+    eff_y = y + noise
 
     # Test noisy data
     popt, _ = knife_edge_base(x, eff_y)
     np.testing.assert_allclose(p0, popt, atol=1e-1)
 
     # Test flipped data
-    popt, _ = knife_edge_base(x, eff_y[:, ::-1])
+    popt, _ = knife_edge_base(x, eff_y[::-1])
     p0[1] = abs(p0[1])  # Absolute value when flipped
     np.testing.assert_allclose(p0, popt, atol=1e-1)