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/knife_edge.py

@@ -107,13 +107,7 @@ def prepare_arrays(arrX: np.ndarray, arrY: np.ndarray,
     3. Retrieve finite values.
     """
     # Convert both arrays to 1D of the same size
-    assert arrX.shape[0] == arrY.shape[0]
-    arrX = arrX.flatten()
-    arrY = arrY.flatten()
-    if len(arrX) > len(arrY):
-        arrY = np.repeat(arrY, len(arrX) // len(arrY))
-    else:
-        arrX = np.repeat(arrX, len(arrY) // len(arrX))
+    arrX, arrY = arrays_to1d(arrX, arrY)
 
     # Select ranges
     if xRange is not None:
@@ -133,6 +127,18 @@ def prepare_arrays(arrX: np.ndarray, arrY: np.ndarray,
     return arrX, arrY
 
 
+def arrays_to1d(arrX: np.ndarray, arrY: np.ndarray):
+    """Flatten two arrays and matches their sizes
+    """
+    assert arrX.shape[0] == arrY.shape[0]
+    arrX, arrY = arrX.flatten(), arrY.flatten()
+    if len(arrX) > len(arrY):
+        arrY = np.repeat(arrY, len(arrX) // len(arrY))
+    else:
+        arrX = np.repeat(arrX, len(arrY) // len(arrX))
+    return arrX, arrY
+
+
 def range_mask(array, minimum=None, maximum=None):
     """Retrieve the resulting array from the given minimum and maximum
     """