Fixes auto name bug, adds clearer error for missing custom file or function name and update to dev12

ratapi/inputs.py

@@ -77,6 +77,13 @@ def get_handle(self, index: int):
         """
         custom_file = self.files[index]
         full_path = os.path.join(custom_file["path"], custom_file["filename"])
+
+        if not os.path.isfile(full_path):
+            raise FileNotFoundError(f"The custom file ({custom_file['name']}) does not have a valid path.")
+
+        if not custom_file["function_name"] and custom_file["language"] != Languages.Matlab:
+            raise ValueError(f"The custom file ({custom_file['name']}) does not have a valid function name.")
+
         if custom_file["language"] == Languages.Python:
             file_handle = get_python_handle(custom_file["filename"], custom_file["function_name"], custom_file["path"])
         elif custom_file["language"] == Languages.Matlab:

ratapi/models.py

@@ -2,7 +2,7 @@
 
 import pathlib
 import warnings
-from itertools import count
+from contextlib import suppress
 from typing import Any
 
 import numpy as np
@@ -18,14 +18,41 @@
 
 
 # Create a counter for each model
-background_number = count(1)
-contrast_number = count(1)
-custom_file_number = count(1)
-data_number = count(1)
-domain_contrast_number = count(1)
-layer_number = count(1)
-parameter_number = count(1)
-resolution_number = count(1)
+background_number = ["Background", 0]
+contrast_number = ["Contrast", 0]
+custom_file_number = ["Custom File", 0]
+data_number = ["Data", 0]
+domain_contrast_number = ["Domain Contrast", 0]
+layer_number = ["Layer", 0]
+parameter_number = ["Parameter", 0]
+resolution_number = ["Resolution", 0]
+
+_model_counter = {
+    "Background": background_number,
+    "Contrast": contrast_number,
+    "ContrastWithRatio": contrast_number,
+    "CustomFile": custom_file_number,
+    "Data": data_number,
+    "DomainContrast": domain_contrast_number,
+    "Layer": layer_number,
+    "AbsorptionLayer": layer_number,
+    "Parameter": parameter_number,
+    "ProtectedParameter": parameter_number,
+    "Resolution": resolution_number,
+}
+
+
+def _model_name_factory(model_name: str) -> str:
+    """Generate a unique name for model using a global counter.
+
+    Parameters
+    ----------
+    model_name : str
+        The name of the model class.
+    """
+    title, number = _model_counter[model_name]
+    _model_counter[model_name][1] += 1
+    return f"New {title} {(number + 1)}"
 
 
 class RATModel(BaseModel, validate_assignment=True, extra="forbid"):
@@ -38,6 +65,25 @@ def __repr__(self):
         )
         return f"{self.__repr_name__()}({fields_repr})"
 
+    @field_validator("name", mode="after", check_fields=False)
+    @classmethod
+    def update_counter(cls, name: str) -> str:
+        """Update the auto name counter if a similar name is manually given.
+
+        Parameters
+        ----------
+        name : str
+            The name of the model.
+        """
+        title, number = _model_counter[cls.__name__]
+        prefix = f"New {title} "
+        if name.startswith(prefix):
+            with suppress(ValueError):
+                new_number = int(name[len(prefix) :])
+                if new_number > number:
+                    _model_counter[cls.__name__][1] = new_number
+        return name
+
     def __str__(self):
         table = prettytable.PrettyTable()
         table.field_names = [key.replace("_", " ") for key in self.display_fields]
@@ -116,7 +162,7 @@ class Background(Signal):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Background {next(background_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Background"), min_length=1)
 
     @model_validator(mode="after")
     def check_unsupported_parameters(self):
@@ -173,7 +219,7 @@ class Contrast(RATModel):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Contrast {next(contrast_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Contrast"), min_length=1)
     data: str = ""
     background: str = ""
     background_action: BackgroundActions = BackgroundActions.Add
@@ -255,7 +301,7 @@ class ContrastWithRatio(RATModel):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Contrast {next(contrast_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("ContrastWithRatio"), min_length=1)
     data: str = ""
     background: str = ""
     background_action: BackgroundActions = BackgroundActions.Add
@@ -309,7 +355,7 @@ class CustomFile(RATModel):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Custom File {next(custom_file_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("CustomFile"), min_length=1)
     filename: str = ""
     function_name: str = ""
     language: Languages = Languages.Python
@@ -348,7 +394,7 @@ class Data(RATModel, arbitrary_types_allowed=True):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Data {next(data_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Data"), min_length=1)
     data: np.ndarray = np.empty([0, 3])
     data_range: list[float] = Field(default=[], min_length=2, max_length=2)
     simulation_range: list[float] = Field(default=[], min_length=2, max_length=2)
@@ -453,7 +499,7 @@ class DomainContrast(RATModel):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Domain Contrast {next(domain_contrast_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("DomainContrast"), min_length=1)
     model: list[str] = []
 
     def __str__(self):
@@ -483,7 +529,7 @@ class Layer(RATModel, populate_by_name=True):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Layer {next(layer_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Layer"), min_length=1)
     thickness: str
     SLD: str = Field(validation_alias="SLD_real")
     roughness: str
@@ -522,7 +568,7 @@ class AbsorptionLayer(RATModel, populate_by_name=True):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Layer {next(layer_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("AbsorptionLayer"), min_length=1)
     thickness: str
     SLD_real: str = Field(validation_alias="SLD")
     SLD_imaginary: str
@@ -555,7 +601,7 @@ class Parameter(RATModel):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Parameter {next(parameter_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Parameter"), min_length=1)
     min: float = 0.0
     value: float = 0.0
     max: float = 0.0
@@ -638,7 +684,7 @@ class Resolution(Signal):
 
     """
 
-    name: str = Field(default_factory=lambda: f"New Resolution {next(resolution_number)}", min_length=1)
+    name: str = Field(default_factory=lambda: _model_name_factory("Resolution"), min_length=1)
 
     @field_validator("type")
     @classmethod

tests/test_inputs.py

@@ -2,6 +2,8 @@
 
 import pathlib
 import pickle
+import tempfile
+from unittest.mock import patch
 
 import numpy as np
 import pytest
@@ -675,6 +677,30 @@ def test_make_controls(standard_layers_controls) -> None:
     check_controls_equal(controls, standard_layers_controls)
 
 
+@patch("ratapi.wrappers.MatlabWrapper")
+def test_file_handles(wrapper):
+    handle = FileHandles([ratapi.models.CustomFile(name="Test Custom File", filename="cpp_test.dll", language="cpp")])
+
+    with pytest.raises(FileNotFoundError, match="The custom file \\(Test Custom File\\) does not have a valid path."):
+        handle.get_handle(0)
+
+    with tempfile.NamedTemporaryFile("w", suffix=".dll") as f:
+        tmp_file = pathlib.Path(f.name)
+        handle.files[0]["path"] = tmp_file.parent
+        handle.files[0]["filename"] = tmp_file.name
+        handle.files[0]["function_name"] = ""
+        # No function name should throw exception
+        with pytest.raises(
+            ValueError, match="The custom file \\(Test Custom File\\) does not have a valid function name."
+        ):
+            handle.get_handle(0)
+
+        # Matlab does not need function name
+        handle.files[0]["language"] = "matlab"
+        handle.get_handle(0)
+        wrapper.assert_called()
+
+
 def check_problem_equal(actual_problem, expected_problem) -> None:
     """Compare two instances of the "problem" object for equality."""
     scalar_fields = [

tests/test_models.py

@@ -32,14 +32,23 @@ def test_default_names(model: Callable, model_name: str, model_params: dict) ->
     format: "New <model name> <integer>".
     """
     model_1 = model(**model_params)
+    prefix = f"New {model_name} "
+    assert model_1.name.startswith(prefix)
+    index = int(model_1.name[len(prefix) :])
+
     model_2 = model(**model_params)
     model_3 = model(name="Given Name", **model_params)
     model_4 = model(**model_params)
 
-    assert model_1.name == f"New {model_name} 1"
-    assert model_2.name == f"New {model_name} 2"
+    assert model_1.name == f"New {model_name} {index}"
+    assert model_2.name == f"New {model_name} {index + 1}"
     assert model_3.name == "Given Name"
-    assert model_4.name == f"New {model_name} 3"
+    assert model_4.name == f"New {model_name} {index + 2}"
+
+    # If user adds name in similar format. The next auto number will take it into account.
+    model(name=f"{prefix}{index + 20}", **model_params)
+    model_5 = model(**model_params)
+    assert model_5.name == f"New {model_name} {index + 21}"
 
 
 @pytest.mark.parametrize(
@@ -100,13 +109,6 @@ def test_initialise_with_extra_fields(self, model: Callable, model_params: dict)
             model(new_field=1, **model_params)
 
 
-# def test_custom_file_path_is_absolute() -> None:
-#     """If we use provide a relative path to the custom file model, it should be converted to an absolute path."""
-#     relative_path = pathlib.Path("./relative_path")
-#     custom_file = ratapi.models.CustomFile(path=relative_path)
-#     assert custom_file.path.is_absolute()
-
-
 def test_data_eq() -> None:
     """If we use the Data.__eq__ method with an object that is not a pydantic BaseModel, we should return
     "NotImplemented".