Merge branch 'main' into feature/columnar-data-support-no-id-field

docs/user_manual/calculations.md

@@ -125,6 +125,23 @@ Output:
 - Node voltage magnitude and angle
 - Current flowing through branches and fault.
 
+#### Common calculations
+
+Power flowing through a branch is calculated by voltage and current for any type of calculations in the following way:
+
+$$
+    \begin{eqnarray}
+        \underline{S_{branch-side}} = \sqrt{3} \cdot \underline{U_{LL-side-node}} \cdot \underline{I_{branch-side}}
+    \end{eqnarray}
+$$
+
+These quantities are in complex form. Hence, they can be constructed by PGM output attributes in the following way:
+
+* For  $\underline{U}$ of nodes, `u` is the magnitude and `u_angle` is the angle. Also the line to neutral voltage can be converted into line to line voltage by $ U_{LN} = U_{LL} / \sqrt{3}$. Check [Node Steady State Output](components.md#steady-state-output) to find out which quantity is relevant in your calculation.
+
+* For  $\underline{I}$ of branches, `i_side` is the magnitude. Its angle can be found from `p_side` and `q_side` by: $\arctan(\frac{P_{side} + j \cdot Q_{side}}{\underline{U}})^{*}$.
+The `side` here can be `from`, `to` for {hoverxreftooltip}`user_manual/components:Branch`es, `1`, `2`, `3` for {hoverxreftooltip}`user_manual/components:Branch3`s. 
+
 ### Power flow algorithms
 
 Two types of power flow algorithms are implemented in power-grid-model; iterative algorithms (Newton-Raphson / Iterative current) and linear algorithms (Linear / Linear current).

src/power_grid_model/core/buffer_handling.py

@@ -85,7 +85,7 @@ def _get_raw_data_view(data: np.ndarray, dtype: np.dtype) -> VoidPtr:
         a raw view on the data set.
     """
     if data.dtype != dtype:
-        warnings.warn("Data type does not match schema. {VALIDATOR_MSG}", DeprecationWarning)
+        warnings.warn(f"Data type does not match schema. {VALIDATOR_MSG}", DeprecationWarning)
     return np.ascontiguousarray(data, dtype=dtype).ctypes.data_as(VoidPtr)
 
 
@@ -170,7 +170,7 @@ def _get_uniform_buffer_properties(
         columns = None
     else:
         if not sub_data:
-            raise ValueError("Empty columnar buffer is ambiguous.{VALIDATOR_MSG}")
+            raise ValueError(f"Empty columnar buffer is ambiguous. {VALIDATOR_MSG}")
         attribute, attribute_data = next(iter(sub_data.items()))
         actual_ndim = attribute_data.ndim - schema.dtype[attribute].ndim
         shape = attribute_data.shape[:actual_ndim]
@@ -237,7 +237,7 @@ def _get_sparse_buffer_properties(
         shape: tuple[int, ...] = contents.shape
     else:
         if not contents:
-            raise ValueError("Empty columnar buffer is ambiguous. {VALIDATOR_MSG}")
+            raise ValueError(f"Empty columnar buffer is ambiguous. {VALIDATOR_MSG}")
         attribute_data = next(iter(contents.values()))
         shape = attribute_data.shape[:ndim]
         columns = list(contents)