fix np.isnan in if statement and documentation review comments

Signed-off-by: leovsch <leo.25.1996@gmail.com>

Author: leovsch

docs/user_manual/components.md

@@ -295,7 +295,7 @@ $$
    \end{bmatrix}
 $$
 
-This representation holds for all values `r_aa` - `r_nn`, `x_aa` - `x_nn` and `c_aa` - `c_cc`. If the neutral values are not provided, the last row and column from the above matrix are omitted.
+This representation holds for all values `r_aa` ... `r_nn`, `x_aa` ... `x_nn` and `c_aa` ... `c_cc`. If the neutral values are not provided, the last row and column from the above matrix are omitted.
 
 | name   | data type | unit       | description                       | required                     |  update  |            valid values            |
 | ------ | --------- | ---------- | --------------------------------- | ---------------------------- | :------: | :--------------------------------: |
@@ -330,43 +330,43 @@ This representation holds for all values `r_aa` - `r_nn`, `x_aa` - `x_nn` and `c
 
 For the r and x matrices providing values for the neutral phase is optional. To clarify which input values are required, please consult the tables below:
 
-| r_aa - r_cc   | r_na     | r_nb     | r_nc     | r_nn     | result   | Validation Error          |
-| ------------- | -------- | -------- | -------- | -------- | -------- | ------------------------- |
-| ✔      | ✔ | ✔ | ✔ | ✔ | ✔ |                           |
-| ✔      | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ✔ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ❌ | ❌ | ❌ | ❌ | ✔ |                           |
-| ❌      | ❌ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-
-| x_aa - x_cc   | x_na     | x_nb     | x_nc     | x_nn     | result   | Validation Error          |
-| ------------- | -------- | -------- | -------- | -------- | -------- | ------------------------- |
-| ✔      | ✔ | ✔ | ✔ | ✔ | ✔ |                           |
-| ✔      | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ✔ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ✔ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-| ✔      | ❌ | ❌ | ❌ | ❌ | ✔ |                           |
-| ❌      | ❌ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
-
-For the c-matrix values there are two options. Either provide all the required c-matrix values i.e. `c_aa` - `c_cc` or provide `c0`, `c1`. Whenver both sets are supplied the powerflow calculations will use `c0`, `c1`.
+| r_aa ... r_cc   | r_na     | r_nb     | r_nc     | r_nn     | result   | Validation Error          |
+| --------------- | -------- | -------- | -------- | -------- | -------- | ------------------------- |
+| ✔        | ✔ | ✔ | ✔ | ✔ | ✔ |                           |
+| ✔        | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ✔ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ❌ | ❌ | ❌ | ❌ | ✔ |                           |
+| ❌        | ❌ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+
+| x_aa ... x_cc   | x_na     | x_nb     | x_nc     | x_nn     | result   | Validation Error          |
+| --------------- | -------- | -------- | -------- | -------- | -------- | ------------------------- |
+| ✔        | ✔ | ✔ | ✔ | ✔ | ✔ |                           |
+| ✔        | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ✔ | ✔ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ✔ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ✔ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+| ✔        | ❌ | ❌ | ❌ | ❌ | ✔ |                           |
+| ❌        | ❌ | ❌ | ❌ | ❌ | ❌ | MultiFieldValidationError |
+
+For the c-matrix values there are two options. Either provide all the required c-matrix values i.e. `c_aa` ... `c_cc` or provide `c0`, `c1`. Whenver both sets are supplied the powerflow calculations will use `c0`, `c1`.
 The table below provides guidance in providing valid input.
 
-| c_aa - c_cc | c0       | c1       | result   | Validation Error          |
-| ----------- | -------- | -------- | -------- | ------------------------- |
-| ✔    | ✔ | ✔ | ✔ |                           |
-| ✔    | ✔ | ❌ | ✔ |                           |
-| ✔    | ❌ | ❌ | ✔ |                           |
-| ❌    | ✔ | ❌ | ❌ | MultiFieldValidationError |
-| ❌    | ✔ | ✔ | ✔ |                           |
+| c_aa ... c_cc | c0       | c1       | result   | Validation Error          |
+| ------------- | -------- | -------- | -------- | ------------------------- |
+| ✔      | ✔ | ✔ | ✔ |                           |
+| ✔      | ✔ | ❌ | ✔ |                           |
+| ✔      | ❌ | ❌ | ✔ |                           |
+| ❌      | ✔ | ❌ | ❌ | MultiFieldValidationError |
+| ❌      | ✔ | ✔ | ✔ |                           |
 
 #### Electric Model
 
 The cable properties are described using matrices where the $Z_{\text{series}}$ matrix is computed as:
 
 $$
-   Z_{\text{series}} = R + j * X
+   Z_{\text{series}} = R + \mathrm{j} * X
 $$
 
 Where $R$ and $X$ denote the resistance and reactance matrices build from the input respectively.

src/power_grid_model/validation/_rules.py

@@ -772,7 +772,7 @@ def no_strict_subset_missing(data: SingleDataset, fields: list[str], component_t
                 np.any(
                     (
                         np.isnan(component_data[field])
-                        if np.isnan(nan_value)
+                        if np.any(np.isnan(nan_value))
                         else np.equal(component_data[field], nan_value)
                     ),
                     axis=asym_axes,
@@ -783,7 +783,7 @@ def no_strict_subset_missing(data: SingleDataset, fields: list[str], component_t
                 np.any(
                     (
                         np.logical_not(np.isnan(component_data[field]))
-                        if np.isnan(nan_value)
+                        if np.any(np.isnan(nan_value))
                         else np.logical_not(np.equal(component_data[field], nan_value))
                     ),
                     axis=asym_axes,
@@ -827,7 +827,7 @@ def not_all_missing(data: SingleDataset, fields: list[str], component_type: Comp
                 np.any(
                     (
                         np.isnan(component_data[field])
-                        if np.isnan(nan_value)
+                        if np.any(np.isnan(nan_value))
                         else np.equal(component_data[field], nan_value)
                     ),
                     axis=asym_axes,