Draft: Resolve "Use Numpy arrays instead of `ForEachObject` instances"

Closes #34 (closed)

lisainstrument/indexing.py

@@ -44,14 +44,19 @@ Note that this uses complex slicing, and therefore copy the data."""
 def dict2sc(x, axis=0):
     """Return a new array whose `axis` is for spacecraft with content of `x`.
 
-    The keys of `x` should be [1, 2, 3] (or convertible to those), and values array-like.
-
+    If `x` is a dictionary, its keys should be [1, 2, 3] (or convertible to those), and values array-like.
     Note that all values of `x` should have the same shape, or can be automatically broadcasted.
     If they have shape (N), the resulting array will be of shape (3, N) by default (first axis).
 
+    If `x` is not a dictionary but array-like (or scalar) of shape (N), we extend its axis so that it
+    can be automatically broadcasted, i.e. the resulting array will be of shape (1, N) by default (first axis).
+
     Args:
-        x: input dictionary
+        x: input
     """
+    if not isinstance(x, dict):
+        return np.expand_dims(x, axis)
+
     keys = [1, 2, 3]
     x_int = {int(key): x[key] for key in x}
     if set(x_int.keys()) != set(keys):
@@ -63,14 +68,19 @@ def dict2sc(x, axis=0):
 def dict2mosa(x, axis=0):
     """Return a new array whose `axis` is for spacecraft and `axis + 1` for MOSAs, with content of `x`.
 
-    The keys of `x` should be [12, 23, 31, 13, 32, 21] (or convertible to those), and values array-like.
+    If `x` is a dictionary, its keys should be [12, 23, 31, 13, 32, 21] (or convertible to those),
+    and values array-like. Note that all values of `x` should have the same shape, or can be automatically
+    broadcasted. If they have shape (N), the resulting array will be of shape (3, 2, N) by default (first axis).
 
-    Note that all values of `x` should have the same shape, or can be automatically broadcasted.
-    If they have shape (N), the resulting array will be of shape (3, 2, N) by default (first axis).
+    If `x` is not a dictionary but array-like (or scalar) of shape (N), we extend its axis so that it
+    can be automatically broadcasted, i.e. the resulting array will be of shape (1, 2, N) by default (first axis).
 
     Args:
-        x: input dictionary
+        x: input
     """
+    if not isinstance(x, dict):
+        return np.expand_dims(x, (axis, axis + 1))
+
     mosas = [12, 23, 31, 13, 32, 21]
     x_int = {int(key): x[key] for key in x}
     if set(x_int.keys()) != set(mosas):