diff --git a/.github/workflows/ossar-analysis.yml b/.github/workflows/ossar-analysis.yml index c33f318d..1d4435f4 100644 --- a/.github/workflows/ossar-analysis.yml +++ b/.github/workflows/ossar-analysis.yml @@ -26,16 +26,6 @@ jobs: - run: git checkout HEAD^2 if: ${{ github.event_name == 'pull_request' }} - # Ensure a compatible version of dotnet is installed. - # The [Microsoft Security Code Analysis CLI](https://aka.ms/mscadocs) is built with dotnet v3.1.201. - # A version greater than or equal to v3.1.201 of dotnet must be installed on the agent in order to run this action. - # Remote agents already have a compatible version of dotnet installed and this step may be skipped. - # For local agents, ensure dotnet version 3.1.201 or later is installed by including this action: - # - name: Install .NET - # uses: actions/setup-dotnet@v1 - # with: - # dotnet-version: '3.1.x' - # Run open source static analysis tools - name: Run OSSAR uses: github/ossar-action@v1 diff --git a/.github/workflows/python-ci.yml b/.github/workflows/python-ci.yml index 8ff4b058..80ab2a27 100644 --- a/.github/workflows/python-ci.yml +++ b/.github/workflows/python-ci.yml @@ -65,15 +65,16 @@ jobs: - name: Install dependencies and run tests run: pixi run -e dev test - - name: Upload coverage - uses: codecov/codecov-action@v4.0.1 + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v5 with: - token: ${{ secrets.CODECOV_TOKEN_NEW }} - name: Pytest coverage - env_vars: OS,PYTHON,GITHUB_ACTIONS,GITHUB_ACTION,GITHUB_REF,GITHUB_REPOSITORY,GITHUB_HEAD_REF,GITHUB_RUN_ID,GITHUB_SHA,COVERAGE_FILE - env: - OS: ${{ matrix.os }} - PYTHON: ${{ matrix.python-version }} + name: unit-tests-job + flags: unittests + files: ./coverage-unit.xml + fail_ci_if_error: true + verbose: true + token: ${{ secrets.CODECOV_TOKEN }} + slug: EasyScience/corelib Package_Testing: diff --git a/Examples/fitting/README.rst b/Examples/fitting/README.rst new file mode 100644 index 00000000..614960cb --- /dev/null +++ b/Examples/fitting/README.rst @@ -0,0 +1,6 @@ +.. _fitting_examples: + +Fitting Examples +---------------- + +This section gathers examples which demonstrate fitting functionality using EasyScience's fitting capabilities. diff --git a/PARAMETER_DEPENDENCY_SERIALIZATION.md b/PARAMETER_DEPENDENCY_SERIALIZATION.md new file mode 100644 index 00000000..82bf0383 --- /dev/null +++ b/PARAMETER_DEPENDENCY_SERIALIZATION.md @@ -0,0 +1,216 @@ +# Parameter Dependency Serialization + +This document explains how to serialize and deserialize `Parameter` objects that have dependencies. + +## Overview + +Parameters with dependencies can now be serialized to dictionaries (and JSON) while preserving their dependency relationships. After deserialization, the dependencies are automatically reconstructed using the `serializer_id` attribute to match parameters, with `unique_name` attribute being used as a fallback. + +## Key Features + +- **Automatic dependency serialization**: Dependency expressions and maps are automatically saved during serialization +- **Reliable dependency resolution**: Dependencies are resolved using stable `serializer_id` attributes with `unique_name` as fallback after deserialization +- **Order-independent loading**: Parameters can be loaded in any order thanks to the reliable ID system +- **Bulk dependency resolution**: Utility functions help resolve all dependencies at once +- **JSON compatibility**: Full support for JSON serialization/deserialization +- **Backward compatibility**: Existing code using `unique_name` continues to work as fallback + +## Usage + +### Basic Serialization/Deserialization + +```python +import json +from easyscience import Parameter, global_object +from easyscience.variable.parameter_dependency_resolver import resolve_all_parameter_dependencies + +# Create parameters with dependencies +a = Parameter(name="a", value=2.0, unit="m", min=0, max=10) +b = Parameter.from_dependency( + name="b", + dependency_expression="2 * a", + dependency_map={"a": a}, + unit="m" +) + +# Serialize to dictionary and save to file +params_dict = {"a": a.as_dict(), "b": b.as_dict()} +with open("parameters.json", "w") as f: + json.dump(params_dict, f, indent=2, default=str) + +print("Parameters saved to parameters.json") +``` + +In a new Python session: + +```python +import json +from easyscience import Parameter, global_object +from easyscience.variable.parameter_dependency_resolver import resolve_all_parameter_dependencies + +# Load parameters from file +with open("parameters.json", "r") as f: + params_dict = json.load(f) + +# Clear global map (simulate new environment) +global_object.map._clear() + +# Deserialize parameters +new_a = Parameter.from_dict(params_dict["a"]) +new_b = Parameter.from_dict(params_dict["b"]) + +# Resolve dependencies +resolve_all_parameter_dependencies({"a": new_a, "b": new_b}) + +# Dependencies are now working +new_a.value = 5.0 +print(new_b.value) # Will be 10.0 (2 * 5.0) +``` + +### JSON Serialization + +```python +import json + +# Serialize to JSON +param_dict = parameter.as_dict() +json_str = json.dumps(param_dict, default=str) + +# Deserialize from JSON +loaded_dict = json.loads(json_str) +new_param = Parameter.from_dict(loaded_dict) + +# Resolve dependencies +resolve_all_parameter_dependencies(new_param) +``` + +### Bulk Operations + +```python +from easyscience.variable.parameter_dependency_resolver import get_parameters_with_pending_dependencies + +# Create multiple parameters with dependencies +params = create_parameter_hierarchy() # Your function + +# Serialize all +serialized = {name: param.as_dict() for name, param in params.items()} + +# Clear and deserialize +global_object.map._clear() +new_params = {name: Parameter.from_dict(d) for name, d in serialized.items()} + +# Check which parameters have pending dependencies +pending = get_parameters_with_pending_dependencies(new_params) +print(f"Found {len(pending)} parameters with pending dependencies") + +# Resolve all at once +resolve_all_parameter_dependencies(new_params) +``` + +## Implementation Details + +### Serialization + +During serialization, the following additional fields are added to dependent parameters: + +- `_dependency_string`: The original dependency expression +- `_dependency_map_serializer_ids`: A mapping of dependency keys to stable dependency IDs (preferred) +- `_dependency_map_unique_names`: A mapping of dependency keys to unique names (fallback) +- `__serializer_id`: The parameter's own unique dependency ID +- `_independent`: Boolean flag indicating if the parameter is dependent + +### Deserialization + +During deserialization: + +1. Parameters are created normally but marked as independent temporarily +2. Dependency information is stored in `_pending_dependency_string`, `_pending_dependency_map_serializer_ids`, and `_pending_dependency_map_unique_names` attributes +3. The parameter's own `__serializer_id` is restored from serialized data +4. After all parameters are loaded, `resolve_all_parameter_dependencies()` establishes the dependency relationships using dependency IDs first, then unique names as fallback + +### Dependency Resolution + +The dependency resolution process: + +1. Scans for parameters with pending dependencies +2. First attempts to look up dependency objects by their stable `serializer_id` +3. Falls back to `unique_name` lookup in the global map if serializer_id is not available +4. Calls `make_dependent_on()` to establish the dependency relationship +5. Cleans up temporary attributes + +This dual-strategy approach ensures reliable dependency resolution regardless of parameter loading order while maintaining backward compatibility. + +## Error Handling + +The system provides detailed error messages for common issues: + +- Missing dependencies (parameter with required unique_name not found) +- Invalid dependency expressions +- Circular dependency detection + +## Utility Functions + +### `resolve_all_parameter_dependencies(obj)` + +Recursively finds all Parameter objects with pending dependencies and resolves them. + +**Parameters:** +- `obj`: Object to search for Parameters (can be Parameter, list, dict, or complex object) + +**Returns:** +- None (modifies parameters in place) + +**Raises:** +- `ValueError`: If dependency resolution fails + +### `get_parameters_with_pending_dependencies(obj)` + +Finds all Parameter objects that have pending dependencies. + +**Parameters:** +- `obj`: Object to search for Parameters + +**Returns:** +- `List[Parameter]`: List of parameters with pending dependencies + +## Best Practices + +1. **Always resolve dependencies after deserialization**: Use `resolve_all_parameter_dependencies()` after loading serialized parameters + +2. **Handle the global map carefully**: The global map must contain all referenced parameters for dependency resolution to work + +3. **Use unique names for cross-references**: When creating dependency expressions that reference other parameters, consider using unique names with quotes: `'Parameter_0'` + +4. **Error handling**: Wrap dependency resolution in try-catch blocks for robust error handling + +5. **Bulk operations**: For complex object hierarchies, use the utility functions to handle all parameters at once + +6. **Reliable ordering**: With the new dependency ID system, parameters can be loaded in any order without affecting dependency resolution + +7. **Access dependency ID**: Use `parameter.serializer_id` to access the stable ID for debugging or manual cross-referencing + +## Example: Complex Hierarchy + +```python +def save_model(model): + \"\"\"Save a model with parameter dependencies to JSON.\"\"\" + model_dict = model.as_dict() + with open('model.json', 'w') as f: + json.dump(model_dict, f, indent=2, default=str) + +def load_model(filename): + \"\"\"Load a model from JSON and resolve dependencies.\"\"\" + global_object.map._clear() # Start fresh + + with open(filename) as f: + model_dict = json.load(f) + + model = Model.from_dict(model_dict) + + # Resolve all parameter dependencies + resolve_all_parameter_dependencies(model) + + return model +``` + +This system ensures that complex parameter hierarchies with dependencies can be reliably serialized and reconstructed while maintaining their behavioral relationships. \ No newline at end of file diff --git a/docs/src/fitting/introduction.rst b/docs/src/fitting/introduction.rst index 72c572ac..51155dd9 100644 --- a/docs/src/fitting/introduction.rst +++ b/docs/src/fitting/introduction.rst @@ -2,3 +2,361 @@ Fitting in EasyScience ====================== +EasyScience provides a flexible and powerful fitting framework that supports multiple optimization backends. +This guide covers both basic usage for users wanting to fit their data, and advanced patterns for developers building scientific components. + +Overview +-------- + +The EasyScience fitting system consists of: + +* **Parameters**: Scientific values with units, bounds, and fitting capabilities +* **Models**: Objects containing parameters, inheriting from ``ObjBase`` +* **Fitter**: The main fitting engine supporting multiple minimizers +* **Minimizers**: Backend optimization engines (LMFit, Bumps, DFO-LS) + +Quick Start +----------- + +Basic Parameter and Model Setup +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + import numpy as np + from easyscience import ObjBase, Parameter, Fitter + + # Create a simple model with fittable parameters + class SineModel(ObjBase): + def __init__(self, amplitude_val=1.0, frequency_val=1.0, phase_val=0.0): + amplitude = Parameter("amplitude", amplitude_val, min=0, max=10) + frequency = Parameter("frequency", frequency_val, min=0.1, max=5) + phase = Parameter("phase", phase_val, min=-np.pi, max=np.pi) + super().__init__("sine_model", amplitude=amplitude, frequency=frequency, phase=phase) + + def __call__(self, x): + return self.amplitude.value * np.sin(2 * np.pi * self.frequency.value * x + self.phase.value) + +Basic Fitting Example +~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Create test data + x_data = np.linspace(0, 2, 100) + true_model = SineModel(amplitude_val=2.5, frequency_val=1.5, phase_val=0.5) + y_data = true_model(x_data) + 0.1 * np.random.normal(size=len(x_data)) + + # Create model to fit with initial guesses + fit_model = SineModel(amplitude_val=1.0, frequency_val=1.0, phase_val=0.0) + + # Set which parameters to fit (unfix them) + fit_model.amplitude.fixed = False + fit_model.frequency.fixed = False + fit_model.phase.fixed = False + + # Create fitter and perform fit + fitter = Fitter(fit_model, fit_model) + result = fitter.fit(x=x_data, y=y_data) + + # Access results + print(f"Chi-squared: {result.chi2}") + print(f"Fitted amplitude: {fit_model.amplitude.value} ± {fit_model.amplitude.error}") + print(f"Fitted frequency: {fit_model.frequency.value} ± {fit_model.frequency.error}") + +Available Minimizers +------------------- + +EasyScience supports multiple optimization backends: + +.. code-block:: python + + from easyscience import AvailableMinimizers + + # View all available minimizers + fitter = Fitter(model, model) + print(fitter.available_minimizers) + # Output: ['LMFit', 'LMFit_leastsq', 'LMFit_powell', 'Bumps', 'Bumps_simplex', 'DFO', 'DFO_leastsq'] + +Switching Minimizers +~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Use LMFit (default) + fitter.switch_minimizer(AvailableMinimizers.LMFit) + result1 = fitter.fit(x=x_data, y=y_data) + + # Switch to Bumps + fitter.switch_minimizer(AvailableMinimizers.Bumps) + result2 = fitter.fit(x=x_data, y=y_data) + + # Use DFO for derivative-free optimization + fitter.switch_minimizer(AvailableMinimizers.DFO) + result3 = fitter.fit(x=x_data, y=y_data) + +Parameter Management +------------------- + +Setting Bounds and Constraints +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Parameter with bounds + param = Parameter(name="amplitude", value=1.0, min=0.0, max=10.0, unit="m") + + # Fix parameter (exclude from fitting) + param.fixed = True + + # Unfix parameter (include in fitting) + param.fixed = False + + # Change bounds dynamically + param.min = 0.5 + param.max = 8.0 + +Parameter Dependencies +~~~~~~~~~~~~~~~~~~~~~ + +Parameters can depend on other parameters through expressions: + +.. code-block:: python + + # Create independent parameters + length = Parameter("length", 10.0, unit="m", min=1, max=100) + width = Parameter("width", 5.0, unit="m", min=1, max=50) + + # Create dependent parameter + area = Parameter.from_dependency( + name="area", + dependency_expression="length * width", + dependency_map={"length": length, "width": width} + ) + + # When length or width changes, area updates automatically + length.value = 15.0 + print(area.value) # Will be 75.0 (15 * 5) + +Using make_dependent_on() Method +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +You can also make an existing parameter dependent on other parameters using the ``make_dependent_on()`` method. This is useful when you want to convert an independent parameter into a dependent one: + +.. code-block:: python + + # Create independent parameters + radius = Parameter("radius", 5.0, unit="m", min=1, max=20) + height = Parameter("height", 10.0, unit="m", min=1, max=50) + volume = Parameter("volume", 100.0, unit="m³") # Initially independent + pi = Parameter("pi", 3.14159, fixed=True) # Constant parameter + + # Make volume dependent on radius and height + volume.make_dependent_on( + dependency_expression="pi * radius**2 * height", + dependency_map={"radius": radius, "height": height, "pi": pi} + ) + + # Now volume automatically updates when radius or height changes + radius.value = 8.0 + print(f"New volume: {volume.value:.2f} m³") # Automatically calculated + + # The parameter becomes dependent and cannot be set directly + try: + volume.value = 200.0 # This will raise an AttributeError + except AttributeError: + print("Cannot set value of dependent parameter directly") + +**What to expect:** + +- The parameter becomes **dependent** and its ``independent`` property becomes ``False`` +- You **cannot directly set** the value, bounds, or variance of a dependent parameter +- The parameter's value is **automatically recalculated** whenever any of its dependencies change +- Dependent parameters **cannot be fitted** (they are automatically fixed) +- The original value, unit, variance, min, and max are **overwritten** by the dependency calculation +- You can **revert to independence** using the ``make_independent()`` method if needed + +Advanced Fitting Options +----------------------- + +Setting Tolerances and Limits +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + fitter = Fitter(model, model) + + # Set convergence tolerance + fitter.tolerance = 1e-8 + + # Limit maximum function evaluations + fitter.max_evaluations = 1000 + + # Perform fit with custom settings + result = fitter.fit(x=x_data, y=y_data) + +Using Weights +~~~~~~~~~~~~ + +.. code-block:: python + + # Define weights (inverse variance) + weights = 1.0 / errors**2 # where errors are your data uncertainties + + # Fit with weights + result = fitter.fit(x=x_data, y=y_data, weights=weights) + +Multidimensional Fitting +~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + class AbsSin2D(ObjBase): + def __init__(self, offset_val=0.0, phase_val=0.0): + offset = Parameter("offset", offset_val) + phase = Parameter("phase", phase_val) + super().__init__("sin2D", offset=offset, phase=phase) + + def __call__(self, x): + X, Y = x[:, 0], x[:, 1] # x is 2D array + return np.abs(np.sin(self.phase.value * X + self.offset.value)) * \ + np.abs(np.sin(self.phase.value * Y + self.offset.value)) + + # Create 2D data + x_2d = np.column_stack([x_grid.ravel(), y_grid.ravel()]) + + # Fit 2D model + model_2d = AbsSin2D(offset_val=0.1, phase_val=1.0) + model_2d.offset.fixed = False + model_2d.phase.fixed = False + + fitter = Fitter(model_2d, model_2d) + result = fitter.fit(x=x_2d, y=z_data.ravel()) + +Accessing Fit Results +-------------------- + +The ``FitResults`` object contains comprehensive information about the fit: + +.. code-block:: python + + result = fitter.fit(x=x_data, y=y_data) + + # Fit statistics + print(f"Chi-squared: {result.chi2}") + print(f"Reduced chi-squared: {result.reduced_chi}") + print(f"Number of parameters: {result.n_pars}") + print(f"Success: {result.success}") + + # Parameter values and uncertainties + for param_name, value in result.p.items(): + error = result.errors.get(param_name, 0.0) + print(f"{param_name}: {value} ± {error}") + + # Calculated values and residuals + y_calculated = result.y_calc + residuals = result.residual + + # Plot results + import matplotlib.pyplot as plt + plt.figure(figsize=(10, 4)) + plt.subplot(121) + plt.plot(x_data, y_data, 'o', label='Data') + plt.plot(x_data, y_calculated, '-', label='Fit') + plt.legend() + plt.subplot(122) + plt.plot(x_data, residuals, 'o') + plt.axhline(0, color='k', linestyle='--') + plt.ylabel('Residuals') + +Developer Guidelines +------------------- + +Creating Custom Models +~~~~~~~~~~~~~~~~~~~~~~ + +For developers building scientific components: + +.. code-block:: python + + from easyscience import ObjBase, Parameter + + class CustomModel(ObjBase): + def __init__(self, param1_val=1.0, param2_val=0.0): + # Always create Parameters with appropriate bounds and units + param1 = Parameter("param1", param1_val, min=-10, max=10, unit="m/s") + param2 = Parameter("param2", param2_val, min=0, max=1, fixed=True) + + # Call parent constructor with named parameters + super().__init__("custom_model", param1=param1, param2=param2) + + def __call__(self, x): + # Implement your model calculation + return self.param1.value * x + self.param2.value + + def get_fit_parameters(self): + # This is automatically implemented by ObjBase + # Returns only non-fixed parameters + return super().get_fit_parameters() + +Best Practices +~~~~~~~~~~~~~ + +1. **Always set appropriate bounds** on parameters to constrain the search space +2. **Use meaningful units** for physical parameters +3. **Fix parameters** that shouldn't be optimized +4. **Test with different minimizers** for robustness +5. **Validate results** by checking chi-squared and residuals + +Error Handling +~~~~~~~~~~~~~ + +.. code-block:: python + + from easyscience.fitting.minimizers import FitError + + try: + result = fitter.fit(x=x_data, y=y_data) + if not result.success: + print(f"Fit failed: {result.message}") + except FitError as e: + print(f"Fitting error: {e}") + except Exception as e: + print(f"Unexpected error: {e}") + +Testing Patterns +~~~~~~~~~~~~~~~ + +When writing tests for fitting code: + +.. code-block:: python + + import pytest + from easyscience import global_object + + @pytest.fixture + def clear_global_map(): + """Clear global map before each test""" + global_object.map._clear() + yield + global_object.map._clear() + + def test_model_fitting(clear_global_map): + # Create model and test fitting + model = CustomModel() + model.param1.fixed = False + + # Generate test data + x_test = np.linspace(0, 10, 50) + y_test = 2.5 * x_test + 0.1 * np.random.normal(size=len(x_test)) + + # Fit and verify + fitter = Fitter(model, model) + result = fitter.fit(x=x_test, y=y_test) + + assert result.success + assert model.param1.value == pytest.approx(2.5, abs=0.1) + +This comprehensive guide covers the essential aspects of fitting in EasyScience, from basic usage to advanced developer patterns. +The examples are drawn from the actual test suite and demonstrate real-world usage patterns. + diff --git a/docs/src/getting-started/installation.rst b/docs/src/getting-started/installation.rst index 048f2cd4..4d0cef44 100644 --- a/docs/src/getting-started/installation.rst +++ b/docs/src/getting-started/installation.rst @@ -2,7 +2,7 @@ Installation ************ -**EasyScience** requires Python 3.7 or above. +**EasyScience** requires Python 3.11 or above. Install via ``pip`` ------------------- @@ -17,18 +17,17 @@ Install as an EasyScience developer ----------------------------------- You can obtain the latest development source from our `Github repository -`_.: +`_.: .. code-block:: console - $ git clone https://github.com/easyScience/EasyScience - $ cd EasyScience + $ git clone https://github.com/easyscience/corelib + $ cd corelib And install via pip: .. code-block:: console - $ pip install -r requirements.txt $ pip install -e . .. installation-end-content \ No newline at end of file diff --git a/docs/src/getting-started/overview.rst b/docs/src/getting-started/overview.rst index 2fb0dbd7..2136bec6 100644 --- a/docs/src/getting-started/overview.rst +++ b/docs/src/getting-started/overview.rst @@ -3,4 +3,222 @@ Overview ======== +EasyScience is a foundational Python library that provides the building blocks for scientific data simulation, analysis, and fitting. +It implements a descriptor-based object system with global state management, making it easy to create scientific models with parameters +that have units, bounds, and dependencies. + +What is EasyScience? +------------------- + +EasyScience serves as the core foundation for the EasyScience family of projects, offering: + +* **Scientific Parameters**: Values with units, uncertainties, bounds, and fitting capabilities +* **Model Building**: Base classes for creating complex scientific models +* **Multi-backend Fitting**: Support for LMFit, Bumps, and DFO-LS optimization engines +* **Parameter Dependencies**: Express relationships between parameters through mathematical expressions +* **Serialization**: Save and load complete model states including parameter relationships +* **Undo/Redo System**: Track and revert changes to model parameters +* **Global State Management**: Unified tracking of all objects and their relationships + +Key Concepts +----------- + +Descriptor-Based Architecture +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +EasyScience uses a hierarchical descriptor system: + +.. code-block:: python + + from easyscience import Parameter, ObjBase + + # Scientific parameter with units and bounds + temperature = Parameter( + name="temperature", + value=300.0, + unit="K", + min=0, + max=1000, + description="Sample temperature" + ) + + # Model containing parameters + class ThermalModel(ObjBase): + def __init__(self, temp_val=300.0, coeff_val=1.0): + temperature = Parameter("temperature", temp_val, unit="K", min=0, max=1000) + coefficient = Parameter("coefficient", coeff_val, min=0, max=10) + super().__init__("thermal_model", temperature=temperature, coefficient=coefficient) + +The hierarchy flows from: + +* ``DescriptorBase`` → ``DescriptorNumber`` → ``Parameter`` (fittable scientific values) +* ``BasedBase`` → ``ObjBase`` (containers for parameters and scientific models) +* ``CollectionBase`` (mutable sequences of scientific objects) + +Units and Physical Quantities +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +EasyScience integrates with `scipp `_ for robust unit handling: + +.. code-block:: python + + # Parameters automatically handle units + length = Parameter("length", 100, unit="cm", min=0, max=1000) + + # Unit conversions are automatic + length.convert_unit("m") + print(length.value) # 1.0 + print(length.unit) # m + + # Arithmetic operations preserve units + area = length * length # Results in m^2 + +Parameter Dependencies +~~~~~~~~~~~~~~~~~~~~~ + +Parameters can depend on other parameters through mathematical expressions: + +.. code-block:: python + + # Independent parameters + radius = Parameter("radius", 5.0, unit="m", min=0, max=100) + height = Parameter("height", 10.0, unit="m", min=0, max=200) + + # Dependent parameter using mathematical expression + volume = Parameter.from_dependency( + name="volume", + dependency_expression="3.14159 * radius**2 * height", + dependency_map={"radius": radius, "height": height} + ) + + # Automatic updates + radius.value = 10.0 + print(volume.value) # Automatically recalculated + +Global State Management +~~~~~~~~~~~~~~~~~~~~~~ + +All EasyScience objects register with a global map for dependency tracking: + +.. code-block:: python + + from easyscience import global_object + + # All objects are automatically tracked + param = Parameter("test", 1.0) + print(param.unique_name) # Automatically generated unique identifier + + # Access global registry + all_objects = global_object.map.vertices() + + # Clear for testing (important in unit tests) + global_object.map._clear() + +Fitting and Optimization +~~~~~~~~~~~~~~~~~~~~~~~ + +EasyScience provides a unified interface to multiple optimization backends: + +.. code-block:: python + + from easyscience import Fitter, AvailableMinimizers + + # Create fitter with model + fitter = Fitter(model, model) # model serves as both object and function + + # Switch between different optimizers + fitter.switch_minimizer(AvailableMinimizers.LMFit) # Levenberg-Marquardt + fitter.switch_minimizer(AvailableMinimizers.Bumps) # Bayesian inference + fitter.switch_minimizer(AvailableMinimizers.DFO) # Derivative-free + + # Perform fit + result = fitter.fit(x=x_data, y=y_data, weights=weights) + +Serialization and Persistence +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Complete model states can be saved and restored: + +.. code-block:: python + + # Save model to dictionary + model_dict = model.as_dict() + + # Save to JSON + import json + with open('model.json', 'w') as f: + json.dump(model_dict, f, indent=2, default=str) + + # Restore model + with open('model.json', 'r') as f: + loaded_dict = json.load(f) + + new_model = Model.from_dict(loaded_dict) + + # Resolve parameter dependencies after loading + from easyscience.variable.parameter_dependency_resolver import resolve_all_parameter_dependencies + resolve_all_parameter_dependencies(new_model) + +Use Cases +-------- + +EasyScience is designed for: + +Scientific Modeling +~~~~~~~~~~~~~~~~~~ + +* Creating physics-based models with parameters that have physical meaning +* Handling units consistently throughout calculations +* Managing complex parameter relationships and constraints + +Data Fitting and Analysis +~~~~~~~~~~~~~~~~~~~~~~~~ + +* Fitting experimental data to theoretical models +* Comparing different optimization algorithms +* Uncertainty quantification and error propagation + +Software Development +~~~~~~~~~~~~~~~~~~~ + +* Building domain-specific scientific applications +* Creating reusable model components +* Implementing complex scientific workflows + +Research and Education +~~~~~~~~~~~~~~~~~~~~~ + +* Reproducible scientific computing +* Teaching scientific programming concepts +* Collaborative model development + +Architecture Benefits +------------------- + +**Type Safety**: Strong typing with unit checking prevents common errors + +**Flexibility**: Multiple optimization backends allow algorithm comparison + +**Extensibility**: Descriptor pattern makes it easy to add new parameter types + +**Reproducibility**: Complete serialization enables exact state restoration + +**Performance**: Efficient observer pattern minimizes unnecessary recalculations + +**Testing**: Global state management with cleanup utilities supports robust testing + +Getting Started +-------------- + +The best way to learn EasyScience is through examples: + +1. **Basic Usage**: Start with simple parameters and models +2. **Fitting Tutorial**: Learn the fitting system with real data +3. **Advanced Features**: Explore parameter dependencies and serialization +4. **Development Guide**: Build your own scientific components + +See the :doc:`installation` guide to get started, then explore the :doc:`../fitting/introduction` for practical examples. + +EasyScience forms the foundation for more specialized packages in the EasyScience ecosystem, providing the core abstractions that make scientific computing more accessible and reliable. + diff --git a/docs/src/index.rst b/docs/src/index.rst index ca99dda5..4e329b24 100644 --- a/docs/src/index.rst +++ b/docs/src/index.rst @@ -2,68 +2,177 @@ Welcome to EasyScience's documentation! ========================================= -**EasyScience** is the foundation of the EasyScience universe, providing the building blocks for libraries and applications which aim to make scientific data simulation and analysis easier. +**EasyScience** is a foundational Python library that provides the building blocks for scientific data simulation, analysis, and fitting. +It implements a descriptor-based object system with global state management, making it easier to create scientific models with parameters +that have units, bounds, and dependencies. +.. code-block:: python -Features of EasyScience -========================= + from easyscience import Parameter, ObjBase, Fitter + + # Create a model with scientific parameters + class SineModel(ObjBase): + def __init__(self, amplitude=1.0, frequency=1.0, phase=0.0): + amp = Parameter("amplitude", amplitude, min=0, max=10, unit="V") + freq = Parameter("frequency", frequency, min=0.1, max=5, unit="Hz") + phase = Parameter("phase", phase, min=-3.14, max=3.14, unit="rad") + super().__init__("sine_model", amplitude=amp, frequency=freq, phase=phase) + + def __call__(self, x): + return self.amplitude.value * np.sin(2*np.pi*self.frequency.value*x + self.phase.value) + + # Fit to experimental data + model = SineModel() + model.amplitude.fixed = False # Allow fitting + fitter = Fitter(model, model) + result = fitter.fit(x=x_data, y=y_data) -Free and open-source -Anyone is free to use EasyScience and the source code is openly shared on GitHub. +Key Features +============ -* *Cross-platform* - EasyScience is written in Python and available for all platforms. +**Scientific Parameters with Units** + Parameters automatically handle physical units, bounds, and uncertainties using `scipp `_ integration. -* *Various techniques* - EasyScience has been used to build various libraries such as easyDiffraction and easyReflectometry. +**Parameter Dependencies** + Express mathematical relationships between parameters that update automatically when dependencies change. -* *Advanced built-in features* - EasyScience provides features such as model minimization, automatic script generation, undo/redo, and more. +**Multi-Backend Fitting** + Unified interface to LMFit, Bumps, and DFO-LS optimization engines with easy algorithm comparison. +**Complete Serialization** + Save and restore entire model states including parameter relationships and dependencies. -Projects using EasyScience +**Global State Management** + Automatic tracking of all objects and their relationships with built-in undo/redo capabilities. + +**Developer-Friendly** + Clean APIs, comprehensive testing utilities, and extensive documentation for building scientific applications. + +Why EasyScience? +================ + +**Type Safety & Units** + Prevent common scientific computing errors with automatic unit checking and strong typing. + +**Reproducible Research** + Complete state serialization ensures exact reproducibility of scientific analyses. + +**Algorithm Flexibility** + Compare different optimization approaches without changing your model code. + +**Extensible Architecture** + Descriptor pattern makes it easy to create new parameter types and model components. + +Open Source & Cross-Platform ============================ -EasyScience is currently being used in the following projects: +EasyScience is free and open-source software with the source code openly shared on `GitHub `_. + +* **Cross-platform** - Written in Python and available for Windows, macOS, and Linux +* **Well-tested** - Comprehensive test suite ensuring reliability across platforms +* **Community-driven** - Open to contributions and feature requests +* **Production-ready** - Used in multiple scientific applications worldwide + + +Projects Built with EasyScience +=============================== + +EasyScience serves as the foundation for several scientific applications: + +**easyDiffraction** + .. image:: https://raw.githubusercontent.com/easyScience/easyDiffractionWww/master/assets/img/card.png + :target: https://easydiffraction.org + :width: 300px + + Scientific software for modeling and analysis of neutron diffraction data, providing an intuitive interface for crystallographic refinement. + +**easyReflectometry** + .. image:: https://raw.githubusercontent.com/easyScience/easyReflectometryWww/master/assets/img/card.png + :target: https://easyreflectometry.org + :width: 300px + + Scientific software for modeling and analysis of neutron reflectometry data, enabling detailed study of thin film structures. + +**Your Project Here** + EasyScience's flexible architecture makes it ideal for building domain-specific scientific applications. The comprehensive API and documentation help you get started quickly. + +Quick Start +=========== + +Ready to begin? Here's how to get started: -.. image:: https://raw.githubusercontent.com/easyScience/easyDiffractionWww/master/assets/img/card.png - :target: https://easydiffraction.org +1. **Install EasyScience**: ``pip install easyscience`` +2. **Read the Overview**: Understand the core concepts and architecture +3. **Try the Examples**: Work through practical fitting examples +4. **Explore the API**: Dive into the comprehensive reference documentation -Scientific software for modelling and analysis of neutron diffraction data. +.. code-block:: bash -.. image:: https://raw.githubusercontent.com/easyScience/easyReflectometryWww/master/assets/img/card.png - :target: https://easyreflectometry.org + pip install easyscience -Scientific software for modelling and analysis of neutron reflectometry data. +Then explore the tutorials and examples to learn the key concepts! -Documentation ------------------------------------------- +Documentation Guide +================== .. toctree:: :caption: Getting Started - :maxdepth: 3 + :maxdepth: 2 + :titlesonly: getting-started/overview getting-started/installation +New to EasyScience? Start with the :doc:`getting-started/overview` to understand the core concepts, then follow the :doc:`getting-started/installation` guide. .. toctree:: - :caption: Base Classes - :maxdepth: 3 + :caption: User Guides + :maxdepth: 2 + :titlesonly: - reference/base + fitting/introduction +Learn how to use EasyScience for scientific modeling and data fitting with comprehensive examples and best practices. .. toctree:: - :caption: Fitting - :maxdepth: 3 + :caption: API Reference + :maxdepth: 2 + :titlesonly: - fitting/introduction + reference/base + +Complete API documentation for all classes, methods, and functions in EasyScience. .. toctree:: + :caption: Examples :maxdepth: 2 - :caption: Example galleries + :titlesonly: base_examples/index fitting_examples/index +Practical examples and tutorials demonstrating real-world usage patterns. + +Need Help? +========== + +* **GitHub Issues**: Report bugs or request features on `GitHub `_ +* **Discussions**: Ask questions in `GitHub Discussions `_ +* **API Reference**: Complete documentation of all classes and methods +* **Examples**: Practical tutorials and code samples + +Contributing +============ + +EasyScience is developed openly and welcomes contributions! Whether you're fixing bugs, adding features, improving documentation, or sharing usage examples, your contributions help make scientific computing more accessible. + +Visit our `GitHub repository `_ to: + +* Report issues or suggest features +* Submit pull requests +* Join discussions about development +* Help improve documentation + Indices and tables ================== diff --git a/docs/src/reference/base.rst b/docs/src/reference/base.rst index ed3d05de..f3c277e0 100644 --- a/docs/src/reference/base.rst +++ b/docs/src/reference/base.rst @@ -1,38 +1,315 @@ -====================== -Parameters and Objects -====================== +============== +API Reference +============== -Descriptors -=========== +This reference provides detailed documentation for all EasyScience classes and functions. -.. autoclass:: easyscience.variable.Descriptor - :members: +Core Variables and Descriptors +============================== + +Descriptor Base Classes +----------------------- + +.. autoclass:: easyscience.variable.DescriptorBase + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: easyscience.variable.DescriptorNumber + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: easyscience.variable.DescriptorArray + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: easyscience.variable.DescriptorStr + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: easyscience.variable.DescriptorBool + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: easyscience.variable.DescriptorAnyType + :members: + :inherited-members: + :show-inheritance: Parameters -========== +---------- .. autoclass:: easyscience.variable.Parameter - :members: - :inherited-members: + :members: + :inherited-members: + :show-inheritance: -============================= -Super Classes and Collections -============================= + The Parameter class extends DescriptorNumber with fitting capabilities, bounds, and dependency relationships. -Super Classes -============= + **Key Methods:** + + .. automethod:: from_dependency + .. automethod:: make_dependent_on + .. automethod:: make_independent + .. automethod:: resolve_pending_dependencies + +Base Classes for Models +======================= + +BasedBase +--------- .. autoclass:: easyscience.base_classes.BasedBase - :members: - :inherited-members: + :members: + :inherited-members: + :show-inheritance: + + Base class providing serialization, global object registration, and interface management. + +ObjBase +------- .. autoclass:: easyscience.base_classes.ObjBase - :members: +_add_component - :inherited-members: + :members: + :inherited-members: + :show-inheritance: + + Container class for creating scientific models with parameters. All user-defined models should inherit from this class. + + **Key Methods:** + + .. automethod:: get_fit_parameters + .. automethod:: get_parameters + .. automethod:: _add_component Collections -=========== +----------- + +.. autoclass:: easyscience.base_classes.CollectionBase + :members: + :inherited-members: + :show-inheritance: + + Mutable sequence container for scientific objects with automatic parameter tracking. + +Fitting and Optimization +======================== + +Fitter +------ + +.. autoclass:: easyscience.fitting.Fitter + :members: + :show-inheritance: + + Main fitting engine supporting multiple optimization backends. + + **Key Methods:** + + .. automethod:: fit + .. automethod:: switch_minimizer + .. automethod:: make_model + .. automethod:: evaluate + +Available Minimizers +-------------------- + +.. autoclass:: easyscience.fitting.AvailableMinimizers + :members: + :show-inheritance: + + Enumeration of available optimization backends. + +Fit Results +----------- + +.. autoclass:: easyscience.fitting.FitResults + :members: + :show-inheritance: + + Container for fitting results including parameters, statistics, and diagnostics. + +Minimizer Base Classes +--------------------- + +.. autoclass:: easyscience.fitting.minimizers.MinimizerBase + :members: + :show-inheritance: + + Abstract base class for all minimizer implementations. + +.. autoclass:: easyscience.fitting.minimizers.LMFit + :members: + :show-inheritance: + + LMFit-based minimizer implementation. + +.. autoclass:: easyscience.fitting.minimizers.Bumps + :members: + :show-inheritance: + + Bumps-based minimizer implementation. + +.. autoclass:: easyscience.fitting.minimizers.DFO + :members: + :show-inheritance: + + DFO-LS-based minimizer implementation. + +Global State Management +======================= + +Global Object +------------- + +.. autoclass:: easyscience.global_object.GlobalObject + :members: + :show-inheritance: + + Singleton managing global state, logging, and object tracking. + +Object Map +---------- + +.. autoclass:: easyscience.global_object.Map + :members: + :show-inheritance: + + Graph-based registry for tracking object relationships and dependencies. + +Undo/Redo System +---------------- + +.. autoclass:: easyscience.global_object.UndoStack + :members: + :show-inheritance: + + Stack-based undo/redo system for parameter changes. + +Serialization and I/O +===================== + +Serializer Components +-------------------- + +.. autoclass:: easyscience.io.SerializerComponent + :members: + :show-inheritance: + + Base class providing serialization capabilities. + +.. autoclass:: easyscience.io.SerializerDict + :members: + :show-inheritance: + + Dictionary-based serialization implementation. + +.. autoclass:: easyscience.io.SerializerBase + :members: + :show-inheritance: + + Base serialization functionality. + +Models and Examples +================== + +Polynomial Model +--------------- + +.. autoclass:: easyscience.models.Polynomial + :members: + :show-inheritance: + + Built-in polynomial model for demonstration and testing. + +Job Management +============= + +Analysis and Experiments +------------------------ + +.. autoclass:: easyscience.job.Analysis + :members: + :show-inheritance: + +.. autoclass:: easyscience.job.Experiment + :members: + :show-inheritance: + +.. autoclass:: easyscience.job.Job + :members: + :show-inheritance: + +.. autoclass:: easyscience.job.TheoreticalModel + :members: + :show-inheritance: + +Utility Functions +================ + +Decorators +---------- + +.. autofunction:: easyscience.global_object.undo_redo.property_stack + + Decorator for properties that should be tracked in the undo/redo system. + +Class Tools +----------- + +.. autofunction:: easyscience.utils.classTools.addLoggedProp + + Utility for adding logged properties to classes. + +String Utilities +--------------- + +.. automodule:: easyscience.utils.string + :members: + +Parameter Dependencies +--------------------- + +.. autofunction:: easyscience.variable.parameter_dependency_resolver.resolve_all_parameter_dependencies + + Resolve all pending parameter dependencies after deserialization. + +.. autofunction:: easyscience.variable.parameter_dependency_resolver.get_parameters_with_pending_dependencies + + Find parameters that have unresolved dependencies. + +Constants and Enumerations +========================== + +.. autodata:: easyscience.global_object + :annotation: GlobalObject + + Global singleton instance managing application state. + +Exception Classes +================ + +.. autoclass:: easyscience.fitting.minimizers.FitError + :show-inheritance: + + Exception raised when fitting operations fail. + +.. autoclass:: scipp.UnitError + :show-inheritance: + + Exception raised for unit-related errors (from scipp dependency). + +Usage Examples +============= + +For practical usage examples and tutorials, see: + +* :doc:`../getting-started/overview` - Introduction and key concepts +* :doc:`../fitting/introduction` - Comprehensive fitting guide +* :doc:`../getting-started/installation` - Installation instructions -.. autoclass:: easyscience.CollectionBase - :members: - :inherited-members: +The API reference covers all public classes and methods. 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a/src/easyscience/base_classes/based_base.py b/src/easyscience/base_classes/based_base.py index de72286a..b575b486 100644 --- a/src/easyscience/base_classes/based_base.py +++ b/src/easyscience/base_classes/based_base.py @@ -5,6 +5,8 @@ # © 2021-2025 Contributors to the EasyScience project BasedBase: temp = self.as_dict(skip=['unique_name']) new_obj = self.__class__.from_dict(temp) return new_obj + + def as_dict(self, skip: Optional[List[str]] = None) -> Dict[str, Any]: + """ + Convert an object into a full dictionary using `SerializerDict`. + This is a shortcut for ```obj.encode(encoder=SerializerDict)``` + + :param skip: List of field names as strings to skip when forming the dictionary + :return: encoded object containing all information to reform an EasyScience object. + """ + # extend skip to include unique_name by default + if skip is None: + skip = [] + if 'unique_name' not in skip: + skip.append('unique_name') + return super().as_dict(skip=skip) diff --git a/src/easyscience/base_classes/model_base.py b/src/easyscience/base_classes/model_base.py new file mode 100644 index 00000000..905f377d --- /dev/null +++ b/src/easyscience/base_classes/model_base.py @@ -0,0 +1,115 @@ +from __future__ import annotations + +# SPDX-FileCopyrightText: 2025 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project Parameter: + return self._my_param + + @my_param.setter + def my_param(self, new_value: float) -> None: + self._my_param.value = new_value + ``` + """ + + def __init__(self, unique_name: Optional[str] = None, display_name: Optional[str] = None): + super().__init__(unique_name=unique_name, display_name=display_name) + + def get_all_variables(self) -> List[DescriptorBase]: + """ + Get all `Descriptor` and `Parameter` objects as a list. + + :return: List of `Descriptor` and `Parameter` objects. + """ + vars = [] + for attr_name in dir(self): + attr = getattr(self, attr_name) + if isinstance(attr, DescriptorBase): + vars.append(attr) + elif hasattr(attr, 'get_all_variables'): + vars += attr.get_all_variables() + return vars + + def get_all_parameters(self) -> List[Parameter]: + """ + Get all `Parameter` objects as a list. + + :return: List of `Parameter` objects. + """ + return [param for param in self.get_all_variables() if isinstance(param, Parameter)] + + def get_fittable_parameters(self) -> List[Parameter]: + """ + Get all parameters which can be fitted as a list. + + :return: List of `Parameter` objects. + """ + return [param for param in self.get_all_parameters() if param.independent] + + def get_free_parameters(self) -> List[Parameter]: + """ + Get all parameters which are currently free to be fitted as a list. + + :return: List of `Parameter` objects. + """ + return [param for param in self.get_fittable_parameters() if not param.fixed] + + def get_fit_parameters(self) -> List[Parameter]: + """ + This is an alias for `get_free_parameters`. + To be removed when fully moved to new base classes and minimizer can be changed. + """ + return self.get_free_parameters() + + @classmethod + def from_dict(cls, obj_dict: Dict[str, Any]) -> None: + """ + Re-create an EasyScience object with DescriptorNumber attributes from a full encoded dictionary. + + :param obj_dict: dictionary containing the serialized contents (from `SerializerDict`) of an EasyScience object + :return: Reformed EasyScience object + """ + if not SerializerBase._is_serialized_easyscience_object(obj_dict): + raise ValueError('Input must be a dictionary representing an EasyScience object.') + if obj_dict['@class'] == cls.__name__: + kwargs = SerializerBase.deserialize_dict(obj_dict) + parameter_placeholder = {} + for key, value in kwargs.items(): + if isinstance(value, DescriptorNumber): + parameter_placeholder[key] = value + kwargs[key] = value.value + cls_instance = cls(**kwargs) + for key, value in parameter_placeholder.items(): + temp_param = getattr(cls_instance, key) + setattr(cls_instance, '_' + key, value) + cls_instance._global_object.map.prune(temp_param.unique_name) + return cls_instance + else: + raise ValueError(f'Class name in dictionary does not match the expected class: {cls.__name__}.') diff --git a/src/easyscience/base_classes/new_base.py b/src/easyscience/base_classes/new_base.py new file mode 100644 index 00000000..ba6a31fd --- /dev/null +++ b/src/easyscience/base_classes/new_base.py @@ -0,0 +1,145 @@ +from __future__ import annotations + +# SPDX-FileCopyrightText: 2025 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project Set[str]: + """ + This method is used by the serializer to determine which arguments are needed + by the constructor to deserialize the object. + """ + spec = getfullargspec(self.__class__.__init__) + names = set(spec.args[1:]) + return names + + @property + def unique_name(self) -> str: + """Get the unique name of the object.""" + return self._unique_name + + @unique_name.setter + def unique_name(self, new_unique_name: str): + """Set a new unique name for the object. The old name is still kept in the map. + + :param new_unique_name: New unique name for the object""" + if not isinstance(new_unique_name, str): + raise TypeError('Unique name has to be a string.') + self._unique_name = new_unique_name + self._global_object.map.add_vertex(self) + self._default_unique_name = False + + @property + def display_name(self) -> str: + """ + Get a pretty display name. + + :return: The pretty display name. + """ + display_name = self._display_name + if display_name is None: + display_name = self.unique_name + return display_name + + @display_name.setter + @property_stack + def display_name(self, name: str) -> None: + """ + Set the pretty display name. + + :param name: Pretty display name of the object. + """ + if name is not None and not isinstance(name, str): + raise TypeError('Display name must be a string or None') + self._display_name = name + + def to_dict(self, skip: Optional[List[str]] = None) -> Dict[str, Any]: + """ + Convert an EasyScience object into a full dictionary using `SerializerBase`s generic `convert_to_dict` method. + + :param skip: List of field names as strings to skip when forming the dictionary + :return: encoded object containing all information to reform an EasyScience object. + """ + serializer = SerializerBase() + if skip is None: + skip = [] + if self._default_unique_name and 'unique_name' not in skip: + skip.append('unique_name') + if self._display_name is None: + skip.append('display_name') + return serializer._convert_to_dict(self, skip=skip, full_encode=False) + + @classmethod + def from_dict(cls, obj_dict: Dict[str, Any]) -> None: + """ + Re-create an EasyScience object from a full encoded dictionary. + + :param obj_dict: dictionary containing the serialized contents (from `SerializerDict`) of an EasyScience object + :return: Reformed EasyScience object + """ + if not SerializerBase._is_serialized_easyscience_object(obj_dict): + raise ValueError('Input must be a dictionary representing an EasyScience object.') + if obj_dict['@class'] == cls.__name__: + kwargs = SerializerBase.deserialize_dict(obj_dict) + return cls(**kwargs) + else: + raise ValueError(f'Class name in dictionary does not match the expected class: {cls.__name__}.') + + def __dir__(self) -> Iterable[str]: + """ + This creates auto-completion and helps out in iPython notebooks. + + :return: list of function and parameter names for auto-completion + """ + new_class_objs = list(k for k in dir(self.__class__) if not k.startswith('_')) + return sorted(new_class_objs) + + def __copy__(self) -> NewBase: + """Return a copy of the object.""" + temp = self.to_dict(skip=['unique_name']) + new_obj = self.__class__.from_dict(temp) + return new_obj + + def __deepcopy__(self, memo): + return self.__copy__() + + def __repr__(self) -> str: + return f'{self.__class__.__name__} `{self.unique_name}`' diff --git a/src/easyscience/global_object/map.py b/src/easyscience/global_object/map.py index 53a3aac4..c64bfaff 100644 --- a/src/easyscience/global_object/map.py +++ b/src/easyscience/global_object/map.py @@ -24,10 +24,10 @@ def __repr__(self) -> str: s += ', '.join(self._type) else: s += 'Undefined' - s += '. With' if self.finalizer is None: - s += 'out' - s += 'a finalizer.' + s += '. Without a finalizer.' + else: + s += '. With a finalizer.' return s def __delitem__(self, key): @@ -261,7 +261,7 @@ def is_connected(self, vertices_encountered=None, start_vertex=None) -> bool: return False def _clear(self): - """Reset the map to an empty state.""" + """Reset the map to an empty state. Only to be used for testing""" for vertex in self.vertices(): self.prune(vertex) gc.collect() diff --git a/src/easyscience/io/serializer_base.py b/src/easyscience/io/serializer_base.py index 37a31045..b4eeaf2a 100644 --- a/src/easyscience/io/serializer_base.py +++ b/src/easyscience/io/serializer_base.py @@ -260,6 +260,76 @@ def _convert_from_dict(d): return [SerializerBase._convert_from_dict(x) for x in d] return d + @staticmethod + def deserialize_dict(in_dict: Dict[str, Any]) -> Dict[str, Any]: + """ + Deserialize a dictionary using from_dict for ES objects and SerializerBase otherwise. + This method processes constructor arguments, skipping metadata keys starting with '@'. + + :param in_dict: dictionary to deserialize + :return: deserialized dictionary with constructor arguments + """ + d = {key: SerializerBase._deserialize_value(value) for key, value in in_dict.items() if not key.startswith('@')} + return d + + @staticmethod + def _deserialize_value(value: Any) -> Any: + """ + Deserialize a single value, using specialized handling for ES objects. + + :param value: + :return: deserialized value + """ + if not SerializerBase._is_serialized_easyscience_object(value): + return SerializerBase._convert_from_dict(value) + + module_name = value['@module'] + class_name = value['@class'] + + try: + cls = SerializerBase._import_class(module_name, class_name) + + # Prefer from_dict() method for ES objects + if hasattr(cls, 'from_dict'): + return cls.from_dict(value) + else: + return SerializerBase._convert_from_dict(value) + + except (ImportError, ValueError): + # Fallback to generic deserialization if class-specific fails + return SerializerBase._convert_from_dict(value) + + @staticmethod + def _is_serialized_easyscience_object(value: Any) -> bool: + """ + Check if a value represents a serialized ES object. + + :param value: + :return: True if this is a serialized ES object + """ + return isinstance(value, dict) and '@module' in value and value['@module'].startswith('easy') and '@class' in value + + @staticmethod + def _import_class(module_name: str, class_name: str): + """ + Import a class from a module name and class name. + + :param module_name: name of the module + :param class_name: name of the class + :return: the imported class + :raises ImportError: if module cannot be imported + :raises ValueError: if class is not found in module + """ + try: + module = __import__(module_name, globals(), locals(), [class_name], 0) + except ImportError as e: + raise ImportError(f'Could not import module {module_name}') from e + + if not hasattr(module, class_name): + raise ValueError(f'Class {class_name} not found in module {module_name}.') + + return getattr(module, class_name) + def _recursive_encoder(self, obj, skip: List[str] = [], encoder=None, full_encode=False, **kwargs): """ Walk through an object encoding it @@ -271,10 +341,14 @@ def _recursive_encoder(self, obj, skip: List[str] = [], encoder=None, full_encod # Is it a core MutableSequence? if hasattr(obj, 'encode') and obj.__class__.__module__ != 'builtins': # strings have encode return encoder._convert_to_dict(obj, skip, full_encode, **kwargs) + elif hasattr(obj, 'to_dict') and obj.__class__.__module__.startswith('easy'): + return encoder._convert_to_dict(obj, skip, full_encode, **kwargs) else: return [self._recursive_encoder(it, skip, encoder, full_encode, **kwargs) for it in obj] if isinstance(obj, dict): return {kk: self._recursive_encoder(vv, skip, encoder, full_encode, **kwargs) for kk, vv in obj.items()} if hasattr(obj, 'encode') and obj.__class__.__module__ != 'builtins': # strings have encode return encoder._convert_to_dict(obj, skip, full_encode, **kwargs) + elif hasattr(obj, 'to_dict') and obj.__class__.__module__.startswith('easy'): + return encoder._convert_to_dict(obj, skip, full_encode, **kwargs) return obj diff --git a/src/easyscience/variable/descriptor_number.py b/src/easyscience/variable/descriptor_number.py index d798f0a7..7d35ca0b 100644 --- a/src/easyscience/variable/descriptor_number.py +++ b/src/easyscience/variable/descriptor_number.py @@ -1,6 +1,7 @@ from __future__ import annotations import numbers +import uuid from typing import Any from typing import Dict from typing import List @@ -52,6 +53,7 @@ def __init__( url: Optional[str] = None, display_name: Optional[str] = None, parent: Optional[Any] = None, + **kwargs: Any, # Additional keyword arguments (used for (de)serialization) ): """Constructor for the DescriptorNumber class @@ -67,6 +69,10 @@ def __init__( """ self._observers: List[DescriptorNumber] = [] + # Extract serializer_id if provided during deserialization + if '__serializer_id' in kwargs: + self.__serializer_id = kwargs.pop('__serializer_id') + if not isinstance(value, numbers.Number) or isinstance(value, bool): raise TypeError(f'{value=} must be a number') if variance is not None: @@ -113,10 +119,14 @@ def from_scipp(cls, name: str, full_value: Variable, **kwargs) -> DescriptorNumb def _attach_observer(self, observer: DescriptorNumber) -> None: """Attach an observer to the descriptor.""" self._observers.append(observer) + if not hasattr(self, '_DescriptorNumber__serializer_id'): + self.__serializer_id = str(uuid.uuid4()) def _detach_observer(self, observer: DescriptorNumber) -> None: """Detach an observer from the descriptor.""" self._observers.remove(observer) + if not self._observers: + del self.__serializer_id def _notify_observers(self) -> None: """Notify all observers of a change.""" @@ -326,6 +336,8 @@ def as_dict(self, skip: Optional[List[str]] = None) -> Dict[str, Any]: raw_dict['value'] = self._scalar.value raw_dict['unit'] = str(self._scalar.unit) raw_dict['variance'] = self._scalar.variance + if hasattr(self, '_DescriptorNumber__serializer_id'): + raw_dict['__serializer_id'] = self.__serializer_id return raw_dict def __add__(self, other: Union[DescriptorNumber, numbers.Number]) -> DescriptorNumber: diff --git a/src/easyscience/variable/parameter.py b/src/easyscience/variable/parameter.py index 94415aaa..da5dfe59 100644 --- a/src/easyscience/variable/parameter.py +++ b/src/easyscience/variable/parameter.py @@ -11,6 +11,7 @@ import weakref from typing import Any from typing import Dict +from typing import List from typing import Optional from typing import Union @@ -33,7 +34,8 @@ class Parameter(DescriptorNumber): """ # Used by serializer - _REDIRECT = DescriptorNumber._REDIRECT + # We copy the parent's _REDIRECT and modify it to avoid altering the parent's class dict + _REDIRECT = DescriptorNumber._REDIRECT.copy() _REDIRECT['callback'] = None def __init__( @@ -51,6 +53,7 @@ def __init__( display_name: Optional[str] = None, callback: property = property(), parent: Optional[Any] = None, + **kwargs: Any, # Additional keyword arguments (used for (de)serialization) ): """ This class is an extension of a `DescriptorNumber`. Where the descriptor was for static @@ -72,6 +75,11 @@ def __init__( .. note:: Undo/Redo functionality is implemented for the attributes `value`, `variance`, `error`, `min`, `max`, `bounds`, `fixed`, `unit` """ # noqa: E501 + # Extract and ignore serialization-specific fields from kwargs + kwargs.pop('_dependency_string', None) + kwargs.pop('_dependency_map_serializer_ids', None) + kwargs.pop('_independent', None) + if not isinstance(min, numbers.Number): raise TypeError('`min` must be a number') if not isinstance(max, numbers.Number): @@ -101,6 +109,7 @@ def __init__( url=url, display_name=display_name, parent=parent, + **kwargs, # Additional keyword arguments (used for (de)serialization) ) self._callback = callback # Callback is used by interface to link to model @@ -123,7 +132,11 @@ def from_dependency( :param kwargs: Additional keyword arguments to pass to the Parameter constructor. :return: A new dependent Parameter object. """ # noqa: E501 - parameter = cls(name=name, value=0.0, unit='', variance=0.0, min=-np.inf, max=np.inf, **kwargs) + # Set default values for required parameters for the constructor, they get overwritten by the dependency anyways + default_kwargs = {'value': 0.0, 'unit': '', 'variance': 0.0, 'min': -np.inf, 'max': np.inf} + # Update with user-provided kwargs, to avoid errors. + default_kwargs.update(kwargs) + parameter = cls(name=name, **default_kwargs) parameter.make_dependent_on(dependency_expression=dependency_expression, dependency_map=dependency_map) return parameter @@ -554,6 +567,25 @@ def free(self) -> bool: def free(self, value: bool) -> None: self.fixed = not value + def as_dict(self, skip: Optional[List[str]] = None) -> Dict[str, Any]: + """Overwrite the as_dict method to handle dependency information.""" + raw_dict = super().as_dict(skip=skip) + + # Add dependency information for dependent parameters + if not self._independent: + # Save the dependency expression + raw_dict['_dependency_string'] = self._clean_dependency_string + + # Mark that this parameter is dependent + raw_dict['_independent'] = self._independent + + # Convert dependency_map to use serializer_ids + raw_dict['_dependency_map_serializer_ids'] = {} + for key, obj in self._dependency_map.items(): + raw_dict['_dependency_map_serializer_ids'][key] = obj._DescriptorNumber__serializer_id + + return raw_dict + def _revert_dependency(self, skip_detach=False) -> None: """ Revert the dependency to the old dependency. This is used when an error is raised during setting the dependency. @@ -601,6 +633,31 @@ def _process_dependency_unique_names(self, dependency_expression: str): ) # noqa: E501 self._clean_dependency_string = clean_dependency_string + @classmethod + def from_dict(cls, obj_dict: dict) -> 'Parameter': + """ + Custom deserialization to handle parameter dependencies. + Override the parent method to handle dependency information. + """ + # Extract dependency information before creating the parameter + raw_dict = obj_dict.copy() # Don't modify the original dict + dependency_string = raw_dict.pop('_dependency_string', None) + dependency_map_serializer_ids = raw_dict.pop('_dependency_map_serializer_ids', None) + is_independent = raw_dict.pop('_independent', True) + # Note: Keep _serializer_id in the dict so it gets passed to __init__ + + # Create the parameter using the base class method (serializer_id is now handled in __init__) + param = super().from_dict(raw_dict) + + # Store dependency information for later resolution + if not is_independent: + param._pending_dependency_string = dependency_string + param._pending_dependency_map_serializer_ids = dependency_map_serializer_ids + # Keep parameter as independent initially - will be made dependent after all objects are loaded + param._independent = True + + return param + def __copy__(self) -> Parameter: new_obj = super().__copy__() new_obj._callback = property() @@ -928,9 +985,48 @@ def __abs__(self) -> Parameter: new_full_value = abs(self.full_value) combinations = [abs(self.min), abs(self.max)] if self.min < 0 and self.max > 0: - combinations.append(0) + combinations.append(0.0) min_value = min(combinations) max_value = max(combinations) parameter = Parameter.from_scipp(name=self.name, full_value=new_full_value, min=min_value, max=max_value) parameter.name = parameter.unique_name return parameter + + def resolve_pending_dependencies(self) -> None: + """Resolve pending dependencies after deserialization. + + This method should be called after all parameters have been deserialized + to establish dependency relationships using serializer_ids. + """ + if hasattr(self, '_pending_dependency_string'): + dependency_string = self._pending_dependency_string + dependency_map = {} + + if hasattr(self, '_pending_dependency_map_serializer_ids'): + dependency_map_serializer_ids = self._pending_dependency_map_serializer_ids + + # Build dependency_map by looking up objects by serializer_id + for key, serializer_id in dependency_map_serializer_ids.items(): + dep_obj = self._find_parameter_by_serializer_id(serializer_id) + if dep_obj is not None: + dependency_map[key] = dep_obj + else: + raise ValueError(f"Cannot find parameter with serializer_id '{serializer_id}'") + + # Establish the dependency relationship + try: + self.make_dependent_on(dependency_expression=dependency_string, dependency_map=dependency_map) + except Exception as e: + raise ValueError(f"Error establishing dependency '{dependency_string}': {e}") + + # Clean up temporary attributes + delattr(self, '_pending_dependency_string') + delattr(self, '_pending_dependency_map_serializer_ids') + + def _find_parameter_by_serializer_id(self, serializer_id: str) -> Optional['DescriptorNumber']: + """Find a parameter by its serializer_id from all parameters in the global map.""" + for obj in self._global_object.map._store.values(): + if isinstance(obj, DescriptorNumber) and hasattr(obj, '_DescriptorNumber__serializer_id'): + if obj._DescriptorNumber__serializer_id == serializer_id: + return obj + return None diff --git a/src/easyscience/variable/parameter_dependency_resolver.py b/src/easyscience/variable/parameter_dependency_resolver.py new file mode 100644 index 00000000..e6b7cbd6 --- /dev/null +++ b/src/easyscience/variable/parameter_dependency_resolver.py @@ -0,0 +1,147 @@ +# SPDX-FileCopyrightText: 2025 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project None: + """ + Recursively find all Parameter objects in an object hierarchy and resolve their pending dependencies. + + This function should be called after deserializing a complex object that contains Parameters + with dependencies to ensure all dependency relationships are properly established. + + :param obj: The object to search for Parameters (can be a single Parameter, list, dict, or complex object) + """ + + def _collect_parameters(item: Any, parameters: List[Parameter]) -> None: + """Recursively collect all Parameter objects from an item.""" + if isinstance(item, Parameter): + parameters.append(item) + elif isinstance(item, dict): + for value in item.values(): + _collect_parameters(value, parameters) + elif isinstance(item, (list, tuple)): + for element in item: + _collect_parameters(element, parameters) + elif hasattr(item, '__dict__'): + # Check instance attributes + for attr_name, attr_value in item.__dict__.items(): + if not attr_name.startswith('_'): # Skip private attributes + _collect_parameters(attr_value, parameters) + + # Check class properties (descriptors like Parameter instances) + for attr_name in dir(type(item)): + if not attr_name.startswith('_'): # Skip private attributes + class_attr = getattr(type(item), attr_name, None) + if isinstance(class_attr, property): + try: + attr_value = getattr(item, attr_name) + _collect_parameters(attr_value, parameters) + except (AttributeError, Exception): + # log the exception + print(f"Error accessing property '{attr_name}' of {item}") + # Skip properties that can't be accessed + continue + + # Collect all parameters + all_parameters = [] + _collect_parameters(obj, all_parameters) + + # Resolve dependencies for all parameters that have pending dependencies + resolved_count = 0 + error_count = 0 + errors = [] + + for param in all_parameters: + if hasattr(param, '_pending_dependency_string'): + try: + param.resolve_pending_dependencies() + resolved_count += 1 + except Exception as e: + error_count += 1 + serializer_id = getattr(param, '_DescriptorNumber__serializer_id', 'unknown') + errors.append( + f"Failed to resolve dependencies for parameter '{param.name}'" + f" (unique_name: '{param.unique_name}', serializer_id: '{serializer_id}'): {e}" + ) + + # Report results + if resolved_count > 0: + print(f'Successfully resolved dependencies for {resolved_count} parameter(s).') + + if error_count > 0: + error_message = f'Failed to resolve dependencies for {error_count} parameter(s):\n' + '\n'.join(errors) + raise ValueError(error_message) + + +def get_parameters_with_pending_dependencies(obj: Any) -> List[Parameter]: + """ + Find all Parameter objects in an object hierarchy that have pending dependencies. + + :param obj: The object to search for Parameters + :return: List of Parameters with pending dependencies + """ + parameters_with_pending = [] + + def _collect_pending_parameters(item: Any) -> None: + """Recursively collect all Parameter objects with pending dependencies.""" + if isinstance(item, Parameter): + if hasattr(item, '_pending_dependency_string'): + parameters_with_pending.append(item) + elif isinstance(item, dict): + for value in item.values(): + _collect_pending_parameters(value) + elif isinstance(item, (list, tuple)): + for element in item: + _collect_pending_parameters(element) + elif hasattr(item, '__dict__'): + # Check instance attributes + for attr_name, attr_value in item.__dict__.items(): + if not attr_name.startswith('_'): # Skip private attributes + _collect_pending_parameters(attr_value) + + # Check class properties (descriptors like Parameter instances) + for attr_name in dir(type(item)): + if not attr_name.startswith('_'): # Skip private attributes + class_attr = getattr(type(item), attr_name, None) + if isinstance(class_attr, property): + try: + attr_value = getattr(item, attr_name) + _collect_pending_parameters(attr_value) + except (AttributeError, Exception): + # log the exception + print(f"Error accessing property '{attr_name}' of {item}") + # Skip properties that can't be accessed + continue + + _collect_pending_parameters(obj) + return parameters_with_pending + + +def deserialize_and_resolve_parameters(params_data: Dict[str, Dict[str, Any]]) -> Dict[str, Parameter]: + """ + Deserialize parameters from a dictionary and resolve their dependencies. + + This is a convenience function that combines Parameter.from_dict() deserialization + with dependency resolution in a single call. + + :param params_data: Dictionary mapping parameter names to their serialized data + :return: Dictionary mapping parameter names to deserialized Parameters with resolved dependencies + """ + # Deserialize all parameters first + new_params = {} + for name, data in params_data.items(): + new_params[name] = Parameter.from_dict(data) + + # Resolve all dependencies + resolve_all_parameter_dependencies(new_params) + + return new_params diff --git a/tests/integration_tests/fitting/test_fitter.py b/tests/integration_tests/fitting/test_fitter.py index 601f249d..bfa3f237 100644 --- a/tests/integration_tests/fitting/test_fitter.py +++ b/tests/integration_tests/fitting/test_fitter.py @@ -10,6 +10,7 @@ from easyscience import ObjBase from easyscience import Parameter from easyscience.fitting.minimizers import FitError +from easyscience.base_classes import ModelBase # Model and container of parameters for tests class AbsSin(ObjBase): @@ -50,6 +51,31 @@ def __call__(self, x): np.sin(self.phase.value * X + self.offset.value) ) * np.abs(np.sin(self.phase.value * Y + self.offset.value)) +class StraightLine(ModelBase): + def __init__(self, slope: float, intercept: float): + super().__init__() + self._slope = Parameter("slope", slope) + self._intercept = Parameter("intercept", intercept) + + @property + def slope(self) -> Parameter: + return self._slope + + @slope.setter + def slope(self, value: float) -> None: + self._slope.value = value + + @property + def intercept(self) -> Parameter: + return self._intercept + + @intercept.setter + def intercept(self, value: float) -> None: + self._intercept.value = value + + def __call__(self, x: np.ndarray) -> np.ndarray: + return self.slope.value * x + self.intercept.value + def check_fit_results(result, sp_sin, ref_sin, x, **kwargs): assert result.n_pars == len(sp_sin.get_fit_parameters()) @@ -343,4 +369,23 @@ def test_fixed_parameter_does_not_change(fit_engine): # Offset should remain unchanged assert sp_sin.offset.value == pytest.approx(fixed_offset_before, abs=1e-12) # Phase should be optimized - assert sp_sin.phase.value != pytest.approx(ref_sin.phase.value, rel=1e-3) \ No newline at end of file + assert sp_sin.phase.value != pytest.approx(ref_sin.phase.value, rel=1e-3) + +def test_fitter_new_model_base_integration(): + # WHEN + ground_truth = StraightLine(slope=2.0, intercept=1.0) + model = StraightLine(slope=0.5, intercept=0.0) + + x = np.linspace(0, 10, 100) + weights = np.ones_like(x) + y = ground_truth(x) + + # THEN + model.slope.fixed = False + model.intercept.fixed = False + fitter = Fitter(model, model) + result = fitter.fit(x=x, y=y, weights=weights) + + # EXPECT + assert model.slope.value == pytest.approx(ground_truth.slope.value, rel=1e-3) + assert model.intercept.value == pytest.approx(ground_truth.intercept.value, rel=1e-3) \ No newline at end of file diff --git a/tests/unit_tests/base_classes/test_model_base.py b/tests/unit_tests/base_classes/test_model_base.py new file mode 100644 index 00000000..bcaf4593 --- /dev/null +++ b/tests/unit_tests/base_classes/test_model_base.py @@ -0,0 +1,234 @@ +# SPDX-FileCopyrightText: 2025 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project sub_container -> parameter + param = Parameter(name="value", value=42.0) + sub_container = ObjBase(name="sub", value=param) + main_container = ObjBase(name="main", sub=sub_container) + + # When - Find path from main to parameter + path = global_obj.map.find_path( + main_container.unique_name, + param.unique_name + ) + + # Then - Should find the path through the hierarchy + assert len(path) >= 2 + assert path[0] == main_container.unique_name + assert path[-1] == param.unique_name + + # When - Find reverse path + reverse_path = global_obj.map.reverse_route( + param.unique_name, + main_container.unique_name + ) + + # Then - Should be the reverse + assert reverse_path[0] == param.unique_name + assert reverse_path[-1] == main_container.unique_name + + def test_map_connectivity_with_isolated_objects(self, clear_all): + """Test map connectivity detection""" + # Given + global_obj = GlobalObject() + + # When - Create connected objects + param1 = Parameter(name="connected1", value=1.0) + param2 = Parameter(name="connected2", value=2.0) + container = ObjBase(name="container", p1=param1, p2=param2) + + # Then - Map should be connected + # TODO: Depending on implementation, connectivity might vary + # assert global_obj.map.is_connected() + + # When - Create isolated object + isolated = Parameter(name="isolated", value=99.0) + # Remove its automatic connection by clearing edges + # (In real usage, isolated objects would be rare) + + # Then - Map might still be connected depending on implementation + # This tests the connectivity algorithm + connectivity = global_obj.map.is_connected() + assert isinstance(connectivity, bool) + + def test_error_handling_integration(self, clear_all): + """Test error handling across the global object system""" + # Given + global_obj = GlobalObject() + + # When - Try to get non-existent object + with pytest.raises(ValueError, match="Item not in map"): + global_obj.map.get_item_by_key("non_existent") + + # When - Try to add object with duplicate name + param1 = Parameter(name="test", value=1.0) + param1_name = param1.unique_name + + # Create another with same unique name (should fail in add_vertex) + with pytest.raises(ValueError, match="already exists"): + # This simulates what would happen if we tried to add duplicate + global_obj.map.add_vertex(param1) # param1 already added during creation + + def test_memory_pressure_simulation(self, clear_all): + """Test system behavior under memory pressure""" + # Given + global_obj = GlobalObject() + + # When - Create many objects + objects = [] + for i in range(100): + param = Parameter(name=f"param_{i}", value=float(i)) + obj = ObjBase(name=f"obj_{i}", param=param) + objects.append((param, obj)) + + initial_vertex_count = len(global_obj.map.vertices()) + assert initial_vertex_count == 200 # 100 params + 100 objs + + # When - Delete half the objects + objects_to_delete = [objects[i] for i in range(0, 100, 2)] + for item in objects_to_delete: + objects.remove(item) + del item + + # Force garbage collection + gc.collect() + + # Then - Map should have fewer vertices + current_vertex_count = len(global_obj.map.vertices()) + assert current_vertex_count <= initial_vertex_count + + # When - Delete all remaining objects + del objects + gc.collect() + + # Then - Map should be mostly empty (might have some remaining references) + final_vertex_count = len(global_obj.map.vertices()) + assert final_vertex_count < initial_vertex_count + + def test_serialization_integration_with_global_state(self, clear_all): + """Test serialization integration with global state management""" + # Given + global_obj = GlobalObject() + + # Create objects + param = Parameter(name="test_param", value=123.45, unit="kg") + obj = ObjBase(name="test_obj", param=param) + + original_vertex_count = len(global_obj.map.vertices()) + + # When - Serialize objects + param_dict = param.as_dict() + obj_dict = obj.as_dict() + + # Clear global state + global_obj.map._clear() + assert len(global_obj.map.vertices()) == 0 + + # When - Deserialize objects + new_param = Parameter.from_dict(param_dict) + new_obj = ObjBase.from_dict(obj_dict) + + # Then - Should be registered in global map again + assert len(global_obj.map.vertices()) >= 2 + assert global_obj.map.is_known(new_param) + assert global_obj.map.is_known(new_obj) + + # Objects should be functionally equivalent + assert new_param.name == param.name + assert new_param.value == param.value + assert new_param.unit == param.unit + + def test_debug_mode_integration(self, clear_all): + """Test debug mode behavior across the system""" + # Given + global_obj = GlobalObject() + original_debug = global_obj.debug + + try: + # When - Enable debug mode + global_obj.debug = True + + if not global_obj.stack: + global_obj.instantiate_stack() + global_obj.stack.enabled = True + + # Create and modify objects + param = Parameter(name="debug_test", value=1.0) + + # This should trigger debug output in property_stack decorator + with patch('builtins.print') as mock_print: + param.value = 2.0 + + # Should have printed debug info (if debug mode works) + # Note: This depends on the debug implementation details + + # Test that operations still work normally + assert param.value == 2.0 + assert global_obj.stack.canUndo() + + finally: + # Restore original debug state + global_obj.debug = original_debug + + def test_concurrent_access_simulation(self, clear_all): + """Simulate concurrent access patterns""" + import threading + import time + + # Given + global_obj = GlobalObject() + results = [] + errors = [] + + def create_objects(thread_id, count=10): + """Create objects in a thread""" + try: + for i in range(count): + param = Parameter(name=f"thread_{thread_id}_param_{i}", value=float(i)) + results.append(param.unique_name) + time.sleep(0.001) # Small delay to encourage race conditions + except Exception as e: + errors.append(f"Thread {thread_id}: {e}") + + # When - Create objects concurrently + threads = [] + for thread_id in range(3): + thread = threading.Thread(target=create_objects, args=(thread_id, 5)) + threads.append(thread) + + for thread in threads: + thread.start() + + for thread in threads: + thread.join() + + # Then - Should not have errors and all objects should be created + assert len(errors) == 0, f"Errors occurred: {errors}" + assert len(results) == 15 # 3 threads * 5 objects each + assert len(set(results)) == 15 # All unique names should be unique + + # All objects should be in the map + for unique_name in results: + assert unique_name in global_obj.map.vertices() \ No newline at end of file diff --git a/tests/unit_tests/global_object/test_map.py b/tests/unit_tests/global_object/test_map.py index df344aed..05eec1a8 100644 --- a/tests/unit_tests/global_object/test_map.py +++ b/tests/unit_tests/global_object/test_map.py @@ -6,7 +6,127 @@ from easyscience import ObjBase import pytest import gc +import weakref +import numpy as np +from unittest.mock import MagicMock, patch from easyscience import global_object +from easyscience.global_object.map import _EntryList, Map + +class TestEntryList: + """Test the _EntryList helper class""" + + def test_init_default(self): + """Test _EntryList initialization with defaults""" + entry = _EntryList() + assert entry._type == [] + assert entry.finalizer is None + + def test_init_with_known_type(self): + """Test _EntryList initialization with known type""" + entry = _EntryList(my_type='created') + assert 'created' in entry._type + + def test_init_with_unknown_type(self): + """Test _EntryList initialization with unknown type""" + entry = _EntryList(my_type='unknown') + assert entry._type == [] + + def test_repr(self): + """Test string representation""" + entry = _EntryList() + repr_str = str(entry) + assert 'Undefined' in repr_str + assert 'finalizer' in repr_str + + entry.type = 'created' + repr_str = str(entry) + assert 'created' in repr_str + assert 'finalizer' in repr_str + + def test_type_property_getter(self): + """Test type property getter""" + entry = _EntryList() + assert entry.type == [] + + def test_type_property_setter_valid(self): + """Test type property setter with valid types""" + entry = _EntryList() + entry.type = 'created' + assert 'created' in entry.type + + entry.type = 'argument' + assert 'argument' in entry.type + assert 'created' in entry.type # Should be additive + + def test_type_property_setter_invalid(self): + """Test type property setter with invalid type""" + entry = _EntryList() + entry.type = 'invalid' + assert entry.type == [] + + def test_type_property_setter_duplicate(self): + """Test type property setter doesn't add duplicates""" + entry = _EntryList() + entry.type = 'created' + entry.type = 'created' # Try to add again + assert entry.type.count('created') == 1 + + def test_remove_type(self): + """Test removing a type""" + entry = _EntryList() + entry.type = 'created' + entry.type = 'argument' + + entry.remove_type('created') + assert 'created' not in entry.type + assert 'argument' in entry.type + + def test_remove_type_not_present(self): + """Test removing a type that's not present""" + entry = _EntryList() + entry.type = 'created' + entry.remove_type('argument') # Not present + assert 'created' in entry.type + + def test_reset_type(self): + """Test resetting types""" + entry = _EntryList() + entry.type = 'created' + entry.type = 'argument' + + entry.reset_type('returned') + assert entry.type == ['returned'] + + def test_reset_type_default_none(self): + """Test resetting types with no default""" + entry = _EntryList() + entry.type = 'created' + + entry.reset_type() + assert entry.type == [] + + def test_boolean_properties(self): + """Test boolean property helpers""" + entry = _EntryList() + + # Test all false initially + assert not entry.is_argument + assert not entry.is_created + assert not entry.is_created_internal + assert not entry.is_returned + + # Test each property + entry.type = 'argument' + assert entry.is_argument + + entry.type = 'created' + assert entry.is_created + + entry.type = 'created_internal' + assert entry.is_created_internal + + entry.type = 'returned' + assert entry.is_returned class TestMap: @pytest.fixture @@ -19,7 +139,7 @@ def base_object(self): @pytest.fixture def parameter_object(self): - return Parameter(value=2.0, name="test2") + return Parameter(name="test2", value=2) def test_add_vertex(self, clear, base_object, parameter_object): # When Then Expect @@ -78,3 +198,289 @@ def test_unique_name_change_still_in_map(self, clear, base_object, parameter_obj assert global_object.map.get_item_by_key("test3") == base_object assert global_object.map.get_item_by_key("test4") == parameter_object + def test_add_vertex_duplicate_name_error(self, clear, base_object): + """Test that adding vertex with duplicate name raises error""" + # When/Then + with pytest.raises(ValueError, match="already exists"): + # Try to add another object with same unique_name + duplicate_obj = ObjBase(name="duplicate", unique_name=base_object.unique_name) + + def test_add_vertex_with_object_type(self, clear): + """Test adding vertex with specific object type""" + # Given + obj = ObjBase(name="test") + + # When - Object is automatically added during construction + # Then + assert global_object.map.is_known(obj) + assert 'created' in global_object.map.find_type(obj) + + def test_is_known_object(self, clear, base_object): + """Test is_known method""" + # When/Then + assert global_object.map.is_known(base_object) is True + + # Test with unknown object + unknown_obj = MagicMock() + unknown_obj.unique_name = "unknown" + assert global_object.map.is_known(unknown_obj) is False + + def test_find_type_known_object(self, clear, base_object): + """Test find_type method""" + # When/Then + types = global_object.map.find_type(base_object) + assert isinstance(types, list) + assert 'created' in types + + def test_find_type_unknown_object(self, clear): + """Test find_type with unknown object""" + # Given + unknown_obj = MagicMock() + unknown_obj.unique_name = "unknown" + + # When/Then + result = global_object.map.find_type(unknown_obj) + assert result is None + + def test_reset_type(self, clear, base_object): + """Test resetting object type""" + # Given + original_types = global_object.map.find_type(base_object) + + # When + global_object.map.reset_type(base_object, 'argument') + + # Then + new_types = global_object.map.find_type(base_object) + assert new_types == ['argument'] + assert new_types != original_types + + def test_change_type(self, clear, base_object): + """Test changing object type""" + # Given + original_types = global_object.map.find_type(base_object) + original_count = len(original_types) + + # When + global_object.map.change_type(base_object, 'argument') + + # Then + new_types = global_object.map.find_type(base_object) + assert 'argument' in new_types + assert len(new_types) >= original_count # Should be at least the same or more + + def test_add_edge(self, clear, base_object, parameter_object): + """Test adding edges between objects""" + # When + global_object.map.add_edge(base_object, parameter_object) + + # Then + edges = global_object.map.get_edges(base_object) + assert parameter_object.unique_name in edges + + def test_add_edge_unknown_start_object(self, clear, parameter_object): + """Test adding edge with unknown start object""" + # Given + unknown_obj = MagicMock() + unknown_obj.unique_name = "unknown" + + # When/Then + with pytest.raises(AttributeError, match="Start object not in map"): + global_object.map.add_edge(unknown_obj, parameter_object) + + def test_get_edges(self, clear, base_object, parameter_object): + """Test getting edges for an object""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + edges = global_object.map.get_edges(base_object) + + # Then + assert isinstance(edges, list) + assert parameter_object.unique_name in edges + + def test_get_edges_unknown_object(self, clear): + """Test getting edges for unknown object""" + # Given + unknown_obj = MagicMock() + unknown_obj.unique_name = "unknown" + + # When/Then + with pytest.raises(AttributeError): + global_object.map.get_edges(unknown_obj) + + def test_prune_vertex_from_edge(self, clear, base_object, parameter_object): + """Test removing edge between objects""" + # Given + global_object.map.add_edge(base_object, parameter_object) + assert parameter_object.unique_name in global_object.map.get_edges(base_object) + + # When + global_object.map.prune_vertex_from_edge(base_object, parameter_object) + + # Then + edges = global_object.map.get_edges(base_object) + assert parameter_object.unique_name not in edges + + def test_prune_vertex_from_edge_none_child(self, clear, base_object): + """Test pruning edge with None child""" + # When/Then - Should not raise error + global_object.map.prune_vertex_from_edge(base_object, None) + + def test_prune_vertex(self, clear, base_object): + """Test pruning a vertex completely""" + # Given + unique_name = base_object.unique_name + assert global_object.map.is_known(base_object) + + # When + global_object.map.prune(unique_name) + + # Then + assert not global_object.map.is_known(base_object) + assert unique_name not in global_object.map.vertices() + + def test_edges_generation(self, clear, base_object, parameter_object): + """Test edge generation""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + edges = global_object.map.edges() + + # Then + assert isinstance(edges, list) + expected_edge = {base_object.unique_name, parameter_object.unique_name} + assert expected_edge in edges + + def test_type_filtering_properties(self, clear): + """Test type filtering properties""" + # Given + obj1 = ObjBase(name="obj1") # 'created' type + obj2 = Parameter(name="obj2", value=1) # 'created' type + + global_object.map.change_type(obj1, 'argument') + global_object.map.change_type(obj2, 'returned') + + # When/Then + argument_objs = global_object.map.argument_objs + created_objs = global_object.map.created_objs + returned_objs = global_object.map.returned_objs + + assert obj1.unique_name in argument_objs + assert obj1.unique_name in created_objs # Should still be there + assert obj2.unique_name in created_objs + assert obj2.unique_name in returned_objs + + def test_find_path_simple(self, clear, base_object, parameter_object): + """Test finding path between objects""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + path = global_object.map.find_path(base_object.unique_name, parameter_object.unique_name) + + # Then + assert path == [base_object.unique_name, parameter_object.unique_name] + + def test_find_path_same_vertex(self, clear, base_object): + """Test finding path to same vertex""" + # When + path = global_object.map.find_path(base_object.unique_name, base_object.unique_name) + + # Then + assert path == [base_object.unique_name] + + def test_find_path_no_path(self, clear, base_object, parameter_object): + """Test finding path when no path exists""" + # When - No edge added + path = global_object.map.find_path(base_object.unique_name, parameter_object.unique_name) + + # Then + assert path == [] + + def test_find_all_paths(self, clear, base_object, parameter_object): + """Test finding all paths between objects""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + paths = global_object.map.find_all_paths(base_object.unique_name, parameter_object.unique_name) + + # Then + assert len(paths) == 1 + assert paths[0] == [base_object.unique_name, parameter_object.unique_name] + + def test_reverse_route_with_start(self, clear, base_object, parameter_object): + """Test reverse route with specified start""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + route = global_object.map.reverse_route(parameter_object.unique_name, base_object.unique_name) + + # Then + assert route == [parameter_object.unique_name, base_object.unique_name] + + def test_reverse_route_without_start(self, clear, base_object, parameter_object): + """Test reverse route without specified start""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When + route = global_object.map.reverse_route(parameter_object.unique_name) + + # Then + assert len(route) >= 1 + assert route[0] == parameter_object.unique_name + + def test_is_connected_single_vertex(self, clear, base_object): + """Test connectivity with single vertex""" + # When/Then + assert global_object.map.is_connected() is True + + def test_is_connected_multiple_vertices(self, clear, base_object, parameter_object): + """Test connectivity with multiple connected vertices""" + # Given + global_object.map.add_edge(base_object, parameter_object) + + # When/Then + assert global_object.map.is_connected() is True + + def test_map_repr(self, clear, base_object, parameter_object): + """Test map string representation""" + # When + repr_str = str(global_object.map) + + # Then + assert "Map object" in repr_str + assert "2" in repr_str # Should show vertex count + + def test_get_item_by_key_not_found(self, clear): + """Test getting item by non-existent key""" + # When/Then + with pytest.raises(ValueError, match="Item not in map"): + global_object.map.get_item_by_key("non_existent") + + def test_clear_with_finalizers(self, clear): + """Test clearing map properly calls finalizers""" + # Given + obj = ObjBase(name="test") + original_count = len(global_object.map.vertices()) + + # When + global_object.map._clear() + + # Then + assert len(global_object.map.vertices()) == 0 + + def test_map_initialization(self): + """Test Map initialization""" + # When + test_map = Map() + + # Then + assert len(test_map.vertices()) == 0 + assert test_map.edges() == [] + diff --git a/tests/unit_tests/global_object/test_undo_redo_comprehensive.py b/tests/unit_tests/global_object/test_undo_redo_comprehensive.py new file mode 100644 index 00000000..67d0df5b --- /dev/null +++ b/tests/unit_tests/global_object/test_undo_redo_comprehensive.py @@ -0,0 +1,686 @@ +# SPDX-FileCopyrightText: 2025 EasyScience contributors +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project +# SPDX-License-Identifier: BSD-3-Clause +# © 2021-2025 Contributors to the EasyScience project Any: + return self._convert_to_dict(obj, skip=skip, **kwargs) + + @classmethod + def decode(cls, obj: Any) -> Any: + return cls._convert_from_dict(obj) + + +class TestSerializerBase: + + @pytest.fixture + def clear(self): + """Clear everything before and after each test""" + global_object.map._clear() + if global_object.stack: + global_object.stack.clear() + yield + global_object.map._clear() + if global_object.stack: + global_object.stack.clear() + + @pytest.fixture + def serializer(self): + return ConcreteSerializer() + + @pytest.fixture + def mock_obj(self): + return MockSerializerComponent("test_obj", 42, "optional_value") + + def test_abstract_methods_are_placeholders(self): + """Test that SerializerBase can be instantiated but abstract methods just pass""" + # SerializerBase can actually be instantiated (abstract methods just pass) + base = SerializerBase() + + # Abstract methods don't raise exceptions - they just pass/return None + result = base.encode(Mock()) + assert result is None + + result = SerializerBase.decode({}) + assert result is None + + def test_get_arg_spec(self): + """Test get_arg_spec static method""" + def example_func(self, arg1, arg2, arg3="default"): + pass + + spec, args = SerializerBase.get_arg_spec(example_func) + + assert args == ['arg1', 'arg2', 'arg3'] + assert hasattr(spec, 'args') + assert hasattr(spec, 'defaults') + + def test_encode_objs_datetime(self): + """Test _encode_objs with datetime objects""" + dt = datetime.datetime(2023, 10, 17, 14, 30, 45, 123456) + result = SerializerBase._encode_objs(dt) + + expected = { + '@module': 'datetime', + '@class': 'datetime', + 'string': '2023-10-17 14:30:45.123456' + } + assert result == expected + + def test_encode_objs_numpy_array_real(self): + """Test _encode_objs with real numpy arrays""" + arr = np.array([1, 2, 3], dtype=np.int32) + result = SerializerBase._encode_objs(arr) + + expected = { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'int32', + 'data': [1, 2, 3] + } + assert result == expected + + def test_encode_objs_numpy_array_complex(self): + """Test _encode_objs with complex numpy arrays""" + arr = np.array([1+2j, 3+4j], dtype=np.complex128) + result = SerializerBase._encode_objs(arr) + + expected = { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'complex128', + 'data': [[1.0, 3.0], [2.0, 4.0]] # [real, imag] + } + assert result == expected + + def test_encode_objs_numpy_scalar(self): + """Test _encode_objs with numpy scalars""" + scalar = np.int32(42) + result = SerializerBase._encode_objs(scalar) + + assert result == 42 + assert isinstance(result, int) + + def test_encode_objs_json_serializable(self): + """Test _encode_objs with JSON serializable objects""" + # Should return the object unchanged if it's JSON serializable + data = {"key": "value", "number": 42} + result = SerializerBase._encode_objs(data) + assert result == data + + def test_encode_objs_non_serializable(self): + """Test _encode_objs with non-serializable objects""" + class NonSerializable: + def __init__(self): + self.value = "test" + + obj = NonSerializable() + result = SerializerBase._encode_objs(obj) + # Should return the object unchanged if not serializable + assert result is obj + + def test_convert_from_dict_datetime(self): + """Test _convert_from_dict with datetime objects""" + dt_dict = { + '@module': 'datetime', + '@class': 'datetime', + 'string': '2023-10-17 14:30:45.123456' + } + + result = SerializerBase._convert_from_dict(dt_dict) + expected = datetime.datetime(2023, 10, 17, 14, 30, 45, 123456) + assert result == expected + + def test_convert_from_dict_datetime_no_microseconds(self): + """Test _convert_from_dict with datetime without microseconds""" + dt_dict = { + '@module': 'datetime', + '@class': 'datetime', + 'string': '2023-10-17 14:30:45' + } + + result = SerializerBase._convert_from_dict(dt_dict) + expected = datetime.datetime(2023, 10, 17, 14, 30, 45) + assert result == expected + + def test_convert_from_dict_numpy_array_real(self): + """Test _convert_from_dict with real numpy arrays""" + arr_dict = { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'int32', + 'data': [1, 2, 3] + } + + result = SerializerBase._convert_from_dict(arr_dict) + expected = np.array([1, 2, 3], dtype=np.int32) + np.testing.assert_array_equal(result, expected) + assert result.dtype == expected.dtype + + def test_convert_from_dict_numpy_array_complex(self): + """Test _convert_from_dict with complex numpy arrays""" + arr_dict = { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'complex128', + 'data': [[1.0, 3.0], [2.0, 4.0]] + } + + result = SerializerBase._convert_from_dict(arr_dict) + expected = np.array([1+2j, 3+4j], dtype=np.complex128) + np.testing.assert_array_equal(result, expected) + assert result.dtype == expected.dtype + + def test_convert_from_dict_easyscience_object(self, clear): + """Test _convert_from_dict with EasyScience objects""" + param_dict = { + '@module': 'easyscience.variable.parameter', + '@class': 'Parameter', + '@version': '0.6.0', + 'name': 'test_param', + 'value': 5.0, + 'unit': 'm', + 'variance': 0.1, + 'min': 0.0, + 'max': 10.0, + 'fixed': False, + 'url': '', + 'description': '', + 'display_name': 'test_param' + } + + result = SerializerBase._convert_from_dict(param_dict) + assert isinstance(result, Parameter) + assert result.name == 'test_param' + assert result.value == 5.0 + assert str(result.unit) == 'm' + + def test_convert_from_dict_list(self): + """Test _convert_from_dict with lists""" + data = [ + {'@module': 'datetime', '@class': 'datetime', 'string': '2023-10-17 14:30:45'}, + {'key': 'value'}, + 42 + ] + + result = SerializerBase._convert_from_dict(data) + assert isinstance(result, list) + assert len(result) == 3 + assert isinstance(result[0], datetime.datetime) + assert result[1] == {'key': 'value'} + assert result[2] == 42 + + def test_convert_from_dict_regular_dict(self): + """Test _convert_from_dict with regular dictionaries""" + data = {'key': 'value', 'number': 42} + result = SerializerBase._convert_from_dict(data) + assert result == data + + def test_convert_to_dict_basic(self, serializer, mock_obj, clear): + """Test _convert_to_dict with basic object""" + result = serializer._convert_to_dict(mock_obj) + + assert '@module' in result + assert '@class' in result + assert '@version' in result + assert result['name'] == 'test_obj' + assert result['value'] == 42 + assert result['optional_param'] == 'optional_value' + assert result['unique_name'] == 'mock_test_obj' + + def test_convert_to_dict_with_skip(self, serializer, mock_obj, clear): + """Test _convert_to_dict with skip parameter""" + result = serializer._convert_to_dict(mock_obj, skip=['value', 'optional_param']) + + assert 'name' in result + assert 'value' not in result + assert 'optional_param' not in result + + def test_convert_to_dict_with_redirect(self, serializer, clear): + """Test _convert_to_dict with _REDIRECT""" + obj = MockSerializerWithRedirect("redirect_test", 10) + result = serializer._convert_to_dict(obj) + + assert result['special_attr'] == 20 # 10 * 2 from redirect + assert 'none_attr' not in result # Should be skipped due to None redirect + + def test_convert_to_dict_with_custom_convert_to_dict(self, serializer, clear): + """Test _convert_to_dict with custom _convert_to_dict method""" + obj = MockSerializerWithConvertToDict("custom_test", 5) + result = serializer._convert_to_dict(obj) + + assert result['custom_field'] == 'added_by_convert_to_dict' + assert result['name'] == 'custom_test' + assert result['value'] == 5 + + def test_convert_to_dict_with_enum_object(self, serializer, clear): + """Test _convert_to_dict when the object itself is an enum""" + + # Test that enum values in objects remain as enums without full_encode + class MockObjWithEnum(SerializerComponent): + def __init__(self, name: str, enum_val: TestEnum): + self.name = name + self.enum_val = enum_val + self.unique_name = f"obj_{name}" + self._global_object = True + + obj = MockObjWithEnum("test", TestEnum.TEST_VALUE) + result = serializer._convert_to_dict(obj) + + # The enum field should remain as an enum object (not encoded as dict) + assert isinstance(result['enum_val'], TestEnum) + assert result['enum_val'] == TestEnum.TEST_VALUE + + def test_convert_to_dict_full_encode(self, serializer, clear): + """Test _convert_to_dict with full_encode=True""" + dt = datetime.datetime(2023, 10, 17, 14, 30, 45) + + class MockObjWithDateTime(SerializerComponent): + def __init__(self, name: str, dt: datetime.datetime): + self.name = name + self.dt = dt + self.unique_name = f"dt_{name}" + self._global_object = True + + obj = MockObjWithDateTime("test", dt) + result = serializer._convert_to_dict(obj, full_encode=True) + + assert isinstance(result['dt'], dict) + assert result['dt']['@module'] == 'datetime' + assert result['dt']['@class'] == 'datetime' + + def test_convert_to_dict_without_global_object(self, serializer): + """Test _convert_to_dict with object without _global_object""" + + class MockObjNoGlobal(SerializerComponent): + def __init__(self, name: str): + self.name = name + + obj = MockObjNoGlobal("test") + result = serializer._convert_to_dict(obj) + + assert result['name'] == 'test' + assert 'unique_name' not in result + + def test_convert_to_dict_with_arg_spec(self, serializer, clear): + """Test _convert_to_dict with custom _arg_spec""" + + class MockObjCustomArgSpec(SerializerComponent): + def __init__(self, name: str, value: int, extra: str = "default"): + self.name = name + self.value = value + self.extra = extra + self._arg_spec = ['name', 'value'] # Skip 'extra' + self.unique_name = f"custom_spec_{name}" + self._global_object = True + + obj = MockObjCustomArgSpec("test", 42, "not_default") + result = serializer._convert_to_dict(obj) + + assert 'name' in result + assert 'value' in result + assert 'extra' not in result + + def test_recursive_encoder_with_lists(self, serializer, clear): + """Test _recursive_encoder with lists""" + mock_obj = MockSerializerComponent("list_test", 1) + data = [mock_obj, "string", 42, {"key": "value"}] + + result = serializer._recursive_encoder(data) + + assert isinstance(result, list) + assert len(result) == 4 + assert isinstance(result[0], dict) # Encoded mock object + assert result[0]['name'] == 'list_test' + assert result[1] == "string" + assert result[2] == 42 + assert result[3] == {"key": "value"} + + def test_recursive_encoder_with_dicts(self, serializer, clear): + """Test _recursive_encoder with dictionaries""" + mock_obj = MockSerializerComponent("dict_test", 2) + data = {"obj": mock_obj, "simple": "value"} + + result = serializer._recursive_encoder(data) + + assert isinstance(result, dict) + assert isinstance(result['obj'], dict) # Encoded mock object + assert result['obj']['name'] == 'dict_test' + assert result['simple'] == "value" + + def test_recursive_encoder_with_tuples(self, serializer, clear): + """Test _recursive_encoder with tuples""" + mock_obj = MockSerializerComponent("tuple_test", 3) + data = (mock_obj, "string", 42) + + result = serializer._recursive_encoder(data) + + assert isinstance(result, list) # Tuples become lists + assert len(result) == 3 + assert isinstance(result[0], dict) # Encoded mock object + assert result[0]['name'] == 'tuple_test' + + def test_recursive_encoder_builtin_encode_method(self, serializer): + """Test _recursive_encoder doesn't encode builtin objects with encode method""" + # Strings have an encode method but are builtin + data = ["test_string", b"bytes"] + + result = serializer._recursive_encoder(data) + + assert result == ["test_string", b"bytes"] + + def test_recursive_encoder_with_mutable_sequence(self, serializer, clear): + """Test _recursive_encoder with MutableSequence objects""" + from easyscience.base_classes import CollectionBase + + d0 = DescriptorNumber("a", 0) # type: ignore + d1 = DescriptorNumber("b", 1) # type: ignore + collection = CollectionBase("test_collection", d0, d1) + + result = serializer._recursive_encoder(collection) + + assert isinstance(result, dict) + assert result['@class'] == 'CollectionBase' + assert 'data' in result + + @patch('easyscience.io.serializer_base.import_module') + def test_convert_to_dict_no_version(self, mock_import, serializer, clear): + """Test _convert_to_dict when module has no __version__""" + mock_module = Mock() + del mock_module.__version__ # Remove version attribute + mock_import.return_value = mock_module + + mock_obj = MockSerializerComponent("no_version", 1) + result = serializer._convert_to_dict(mock_obj) + + assert result['@version'] is None + + @patch('easyscience.io.serializer_base.import_module') + def test_convert_to_dict_import_error(self, mock_import, serializer, clear): + """Test _convert_to_dict when import_module raises ImportError""" + mock_import.side_effect = ImportError("Module not found") + + mock_obj = MockSerializerComponent("import_error", 1) + result = serializer._convert_to_dict(mock_obj) + + assert result['@version'] is None + + def test_convert_to_dict_attribute_error_handling(self, serializer, clear): + """Test _convert_to_dict handles AttributeError for missing attributes""" + + class MockObjMissingAttrs(SerializerComponent): + def __init__(self, name: str, missing_param: str = "default"): + self.name = name + self.unique_name = f"missing_{name}" + self._global_object = True + # Don't set missing_param attribute to trigger AttributeError + + obj = MockObjMissingAttrs("test") + + with pytest.raises(NotImplementedError, match="Unable to automatically determine as_dict"): + serializer._convert_to_dict(obj) + + def test_convert_to_dict_with_kwargs_attribute(self, serializer, clear): + """Test _convert_to_dict with _kwargs attribute handling""" + + class MockObjWithKwargs(SerializerComponent): + def __init__(self, name: str, value: int): + self.name = name + self.value = value + self.unique_name = f"kwargs_{name}" + self._global_object = True + # Set up _kwargs to test the kwargs handling path + self._kwargs = {'extra_param': 'extra_value'} + + obj = MockObjWithKwargs("test", 42) + result = serializer._convert_to_dict(obj) + + # The extra_param from _kwargs should be included + assert result['extra_param'] == 'extra_value' + + def test_convert_to_dict_varargs_handling(self, serializer, clear): + """Test _convert_to_dict with varargs (*args) handling""" + + class MockObjWithVarargs(SerializerComponent): + def __init__(self, name: str, *args): + self.name = name + self.args = args + self.unique_name = f"varargs_{name}" + self._global_object = True + + obj = MockObjWithVarargs("test", "arg1", "arg2", "arg3") + result = serializer._convert_to_dict(obj) + + assert result['name'] == 'test' + if 'args' in result: + assert result['args'] == ("arg1", "arg2", "arg3") + + def test_encode_objs_edge_cases(self): + """Test _encode_objs with edge cases""" + # Test with None + assert SerializerBase._encode_objs(None) is None + + # Test with empty numpy array + empty_arr = np.array([]) + result = SerializerBase._encode_objs(empty_arr) + assert result['@module'] == 'numpy' + assert result['data'] == [] + + def test_convert_from_dict_edge_cases(self): + """Test _convert_from_dict with edge cases""" + # Test with None + assert SerializerBase._convert_from_dict(None) is None + + # Test with empty dict + assert SerializerBase._convert_from_dict({}) == {} + + # Test with empty list + assert SerializerBase._convert_from_dict([]) == [] + + # Test with bson.objectid (should not be processed) + bson_dict = { + '@module': 'bson.objectid', + '@class': 'ObjectId', + 'value': 'some_id' + } + result = SerializerBase._convert_from_dict(bson_dict) + assert result == bson_dict + + def test_concrete_serializer_implementation(self, clear): + """Test that ConcreteSerializer works correctly""" + serializer = ConcreteSerializer() + mock_obj = MockSerializerComponent("concrete_test", 100) + + # Test encode + encoded = serializer.encode(mock_obj) + assert isinstance(encoded, dict) + assert encoded['name'] == 'concrete_test' + assert encoded['value'] == 100 + + # Test decode + global_object.map._clear() # Clear before decode + decoded = ConcreteSerializer.decode(encoded) + assert isinstance(decoded, MockSerializerComponent) + assert decoded.name == 'concrete_test' + assert decoded.value == 100 + + def test_get_arg_spec_with_complex_function(self): + """Test get_arg_spec with more complex function signatures""" + def complex_func(self, required_arg, optional_arg="default", *args, **kwargs): + pass + + spec, args = SerializerBase.get_arg_spec(complex_func) + + assert args == ['required_arg', 'optional_arg'] + assert spec.varargs == 'args' + assert spec.varkw == 'kwargs' + assert spec.defaults == ("default",) + + @patch('easyscience.io.serializer_base.np', None) + def test_encode_objs_without_numpy(self): + """Test _encode_objs when numpy is not available""" + # This test patches np to None to simulate numpy not being installed + dt = datetime.datetime(2023, 10, 17, 14, 30, 45) + result = SerializerBase._encode_objs(dt) + + expected = { + '@module': 'datetime', + '@class': 'datetime', + 'string': '2023-10-17 14:30:45' + } + assert result == expected + + def test_recursive_encoder_with_nested_structures(self, serializer, clear): + """Test _recursive_encoder with deeply nested structures""" + mock_obj = MockSerializerComponent("nested", 1) + + data = { + "level1": { + "level2": [mock_obj, {"level3": mock_obj}] + } + } + + result = serializer._recursive_encoder(data) + + assert isinstance(result, dict) + assert isinstance(result["level1"], dict) + assert isinstance(result["level1"]["level2"], list) + assert isinstance(result["level1"]["level2"][0], dict) # Encoded object + assert result["level1"]["level2"][0]["name"] == "nested" + assert isinstance(result["level1"]["level2"][1]["level3"], dict) # Encoded object + + def test_import_class(self): + # When Then + cls = SerializerBase._import_class(module_name="easyscience", class_name="Parameter") + # Expect + assert cls is Parameter + + def test_import_class_missing_module(self): + # When Then Expect + with pytest.raises(ImportError): + SerializerBase._import_class(module_name="non_existent_module", class_name="Parameter") + + def test_import_class_missing_class(self): + # When Then Expect + with pytest.raises(ValueError): + SerializerBase._import_class(module_name="easyscience", class_name="NonExistentClass") + + @pytest.mark.parametrize("dict, expected", [ + ({ '@module': 'easyscience', + '@class': 'Parameter', + 'name': 'param1', + 'value': 10.0 + }, + True + ), + ({ + '@module': 'numpy', + '@class': 'array', + 'unique_name': 'unique1', + 'display_name': 'Display 1' + }, False + )], ids=['valid_easyscience_dict', 'invalid_numpy_dict']) + def test_is_serialized_easyscience_object_false(self, dict, expected): + # When Then + result = SerializerBase._is_serialized_easyscience_object(dict) + # Expect + assert result is expected + + def test_deserialize_value_non_easyscience(self): + # When + serialized_dict = { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'int64', + 'data': [0, 1] + } + # Then + obj = SerializerBase._deserialize_value(serialized_dict) + # Expect + assert isinstance(obj, np.ndarray) + assert obj.dtype == np.int64 + + def test_deserialize_value_easyscience_uses_from_dict(self, monkeypatch): + # When + serialized_dict = { + '@module': 'easyscience.base_classes', + '@class': 'NewBase', + 'display_name': 'test', + } + monkeypatch.setattr(NewBase, 'from_dict', MagicMock()) + # Then + obj = SerializerBase._deserialize_value(serialized_dict) + # Expect + NewBase.from_dict.assert_called_once_with(serialized_dict) + + def test_deserialize_value_easyscience_no_from_dict(self, monkeypatch): + # When + serialized_dict = { + '@module': 'easyscience.base_classes', + '@class': 'NewBase', + 'display_name': 'test', + } + monkeypatch.delattr(NewBase, 'from_dict') + monkeypatch.setattr(SerializerBase, '_convert_from_dict', MagicMock()) + # Then + obj = SerializerBase._deserialize_value(serialized_dict) + # Expect + SerializerBase._convert_from_dict.assert_called_once_with(serialized_dict) + + def test_deserialize_value_easyscience_import_error(self, monkeypatch): + # When + serialized_dict = { + '@module': 'easyscience.base_classes', + '@class': 'NewBase', + 'display_name': 'test', + } + monkeypatch.setattr(SerializerBase, '_import_class', MagicMock(side_effect=ImportError())) + monkeypatch.setattr(SerializerBase, '_convert_from_dict', MagicMock()) + # Then + obj = SerializerBase._deserialize_value(serialized_dict) + # Expect + SerializerBase._convert_from_dict.assert_called_once_with(serialized_dict) + + def test_deserialize_dict(self, monkeypatch): + # When + serialized_dict = { + '@module': 'easyscience', + '@class': 'ParameterContainer', + 'param1': { + '@module': 'easyscience', + '@class': 'Parameter', + 'name': 'param1', + 'value': 10.0 + }, + 'array1': { + '@module': 'numpy', + '@class': 'array', + 'dtype': 'int64', + 'data': [0, 1] + } + } + monkeypatch.setattr(SerializerBase, '_deserialize_value', MagicMock(side_effect=[ + Parameter(name='param1', value=10.0), + np.array([0, 1], dtype=np.int64) + ])) + # Then + result = SerializerBase.deserialize_dict(serialized_dict) + # Expect + SerializerBase._deserialize_value.assert_any_call(serialized_dict['param1']) + SerializerBase._deserialize_value.assert_any_call(serialized_dict['array1']) + assert isinstance(result['param1'], Parameter) + assert isinstance(result['array1'], np.ndarray) + assert result['array1'].dtype == np.int64 \ No newline at end of file diff --git a/tests/unit_tests/models/test_polynomial.py b/tests/unit_tests/models/test_polynomial.py index 799a917a..2493cd11 100644 --- a/tests/unit_tests/models/test_polynomial.py +++ b/tests/unit_tests/models/test_polynomial.py @@ -6,7 +6,17 @@ import numpy as np import pytest +from easyscience import global_object +from easyscience.base_classes import CollectionBase from easyscience.models.polynomial import Polynomial +from easyscience.variable import Parameter + + +@pytest.fixture +def clear(): + """Clear global object map before each test.""" + global_object.map._clear() + poly_test_cases = ( (1.,), @@ -19,8 +29,9 @@ (0.72, 6.48, -0.48), ) + @pytest.mark.parametrize("coo", poly_test_cases) -def test_Polynomial_pars(coo): +def test_Polynomial_pars(clear, coo): poly = Polynomial(coefficients=coo) vals = {coo.value for coo in poly.coefficients} @@ -29,3 +40,155 @@ def test_Polynomial_pars(coo): x = np.linspace(0, 10, 100) y = np.polyval(coo, x) assert np.allclose(poly(x), y) + + +def test_Polynomial_default_initialization(clear): + """Test Polynomial with no coefficients.""" + poly = Polynomial(name='test_poly') + + assert poly.name == 'test_poly' + assert len(poly.coefficients) == 0 + + # Test that calling the polynomial with empty coefficients works + x = np.array([1, 2, 3]) + result = poly(x) + assert len(result) == len(x) + + +def test_Polynomial_with_Parameter_objects(clear): + """Test Polynomial with Parameter objects as coefficients.""" + p0 = Parameter('c0', value=1.0) + p1 = Parameter('c1', value=2.0) + p2 = Parameter('c2', value=3.0) + + poly = Polynomial(coefficients=[p0, p1, p2]) + + assert len(poly.coefficients) == 3 + assert poly.coefficients[0].name == 'c0' + assert poly.coefficients[1].name == 'c1' + assert poly.coefficients[2].name == 'c2' + assert poly.coefficients[0].value == 1.0 + assert poly.coefficients[1].value == 2.0 + assert poly.coefficients[2].value == 3.0 + + # Test evaluation - coefficients passed directly to polyval + # polyval([1.0, 2.0, 3.0], x) = 1.0*x^2 + 2.0*x + 3.0 + x = np.array([0, 1, 2]) + expected = np.polyval([1.0, 2.0, 3.0], x) + assert np.allclose(poly(x), expected) + + +def test_Polynomial_with_mixed_coefficients(clear): + """Test Polynomial with mixed float and Parameter coefficients.""" + p0 = Parameter('c0', value=5.0) + + poly = Polynomial(coefficients=[p0, 2.0, 1.0]) + + assert len(poly.coefficients) == 3 + assert poly.coefficients[0].name == 'c0' + assert poly.coefficients[1].name == 'c1' + assert poly.coefficients[2].name == 'c2' + + # polyval([5.0, 2.0, 1.0], x) = 5.0*x^2 + 2.0*x + 1.0 + x = np.array([1, 2, 3]) + expected = np.polyval([5.0, 2.0, 1.0], x) + assert np.allclose(poly(x), expected) + + +def test_Polynomial_with_CollectionBase(clear): + """Test Polynomial initialized with a CollectionBase.""" + collection = CollectionBase('coeffs') + collection.append(Parameter('c0', value=1.0)) + collection.append(Parameter('c1', value=2.0)) + collection.append(Parameter('c2', value=3.0)) + + poly = Polynomial(coefficients=collection) + + assert poly.coefficients is collection + assert len(poly.coefficients) == 3 + + # polyval([1.0, 2.0, 3.0], x) = 1.0*x^2 + 2.0*x + 3.0 + x = np.array([0, 1, 2]) + expected = np.polyval([1.0, 2.0, 3.0], x) + assert np.allclose(poly(x), expected) + + +def test_Polynomial_invalid_coefficient_type(clear): + """Test that invalid coefficient types raise TypeError.""" + with pytest.raises(TypeError, match='Coefficients must be floats or Parameters'): + Polynomial(coefficients=[1.0, 'invalid', 3.0]) + + with pytest.raises(TypeError, match='Coefficients must be floats or Parameters'): + Polynomial(coefficients=[1, 2, 3]) # integers, not floats + + +def test_Polynomial_invalid_coefficients_type(clear): + """Test that invalid coefficients argument type raises TypeError.""" + # String is iterable, so it will iterate over characters and fail with first error + with pytest.raises(TypeError, match='Coefficients must be floats or Parameters'): + Polynomial(coefficients="invalid") + + # Integer is not iterable, so it will fail with second error + with pytest.raises(TypeError, match='coefficients must be a list or a CollectionBase'): + Polynomial(coefficients=42) + + +def test_Polynomial_repr_no_coefficients(clear): + """Test __repr__ with no coefficients.""" + poly = Polynomial(name='empty') + + repr_str = repr(poly) + assert 'Polynomial(empty, )' == repr_str + + +def test_Polynomial_repr_one_coefficient(clear): + """Test __repr__ with one coefficient.""" + poly = Polynomial(coefficients=[5.0]) + + repr_str = repr(poly) + assert 'Polynomial(polynomial, 5.0)' == repr_str + + +def test_Polynomial_repr_two_coefficients(clear): + """Test __repr__ with two coefficients.""" + poly = Polynomial(coefficients=[3.0, 2.0]) + + repr_str = repr(poly) + assert 'Polynomial(polynomial, 2.0x + 3.0)' == repr_str + + +def test_Polynomial_repr_three_coefficients(clear): + """Test __repr__ with three coefficients.""" + poly = Polynomial(coefficients=[1.0, 2.0, 3.0]) + + repr_str = repr(poly) + assert 'Polynomial(polynomial, 3.0x^2 + 2.0x + 1.0)' == repr_str + + +def test_Polynomial_repr_with_zero_coefficients(clear): + """Test __repr__ with some zero coefficients.""" + poly = Polynomial(coefficients=[1.0, 0.0, 3.0, 0.0, 5.0]) + + repr_str = repr(poly) + # Zero coefficients for higher powers should be excluded + assert 'Polynomial(polynomial, 5.0x^4 + 3.0x^2 + 0.0x + 1.0)' == repr_str + + +def test_Polynomial_repr_negative_coefficients(clear): + """Test __repr__ with negative coefficients.""" + poly = Polynomial(coefficients=[-1.0, -2.0, -3.0]) + + repr_str = repr(poly) + assert 'Polynomial(polynomial, -3.0x^2 + -2.0x + -1.0)' == repr_str + + +def test_Polynomial_call_with_args_kwargs(clear): + """Test that __call__ accepts *args and **kwargs.""" + poly = Polynomial(coefficients=[1.0, 2.0, 3.0]) + + x = np.array([0, 1, 2]) + # These additional args/kwargs should be ignored + result = poly(x, "extra_arg", extra_kwarg="value") + # polyval([1.0, 2.0, 3.0], x) = 1.0*x^2 + 2.0*x + 3.0 + expected = np.polyval([1.0, 2.0, 3.0], x) + assert np.allclose(result, expected) diff --git a/tests/unit_tests/variable/test_parameter.py b/tests/unit_tests/variable/test_parameter.py index 6b4b5f17..0ca8f85e 100644 --- a/tests/unit_tests/variable/test_parameter.py +++ b/tests/unit_tests/variable/test_parameter.py @@ -635,24 +635,6 @@ def test_set_value_dependent_parameter(self, normal_parameter: Parameter): with pytest.raises(AttributeError): dependent_parameter.value = 3 - @pytest.mark.skip(reason="No longer relevant") - def test_full_value_match_callback(self, parameter: Parameter): - # When - self.mock_callback.fget.return_value = sc.scalar(1, unit='m') - - # Then Expect - assert parameter.full_value == sc.scalar(1, unit='m') - assert parameter._callback.fget.call_count == 1 - - @pytest.mark.skip(reason="No longer relevant") - def test_full_value_no_match_callback(self, parameter: Parameter): - # When - self.mock_callback.fget.return_value = sc.scalar(2, unit='m') - - # Then Expect - assert parameter.full_value == sc.scalar(2, unit='m') - assert parameter._callback.fget.call_count == 1 - def test_set_full_value(self, parameter: Parameter): # When Then Expect with pytest.raises(AttributeError): diff --git a/tests/unit_tests/variable/test_parameter_dependency_serialization.py b/tests/unit_tests/variable/test_parameter_dependency_serialization.py new file mode 100644 index 00000000..8cf7abc0 --- /dev/null +++ b/tests/unit_tests/variable/test_parameter_dependency_serialization.py @@ -0,0 +1,500 @@ +import pytest +import json +from copy import deepcopy +from unittest.mock import Mock + +from easyscience import Parameter, global_object +from easyscience.variable.parameter_dependency_resolver import resolve_all_parameter_dependencies +from easyscience.variable.parameter_dependency_resolver import get_parameters_with_pending_dependencies +from easyscience.variable.parameter_dependency_resolver import deserialize_and_resolve_parameters + + +class TestParameterDependencySerialization: + + @pytest.fixture + def clear_global_map(self): + """This fixture pattern: + - Clears the map before each test (clean slate) + - Yields control to the test + - Clears the map after each test (cleanup) + + Dependency serialization tests require more robust + setup-yield-cleanup pattern because they involve complex + object lifecycles with serialization, deserialization, + and dependency resolution that are particularly sensitive + to global state contamination. + """ + # The global map uses weakref.WeakValueDictionary() for object storage, + # but also maintains strong references in __type_dict that need explicit cleanup. + global_object.map._clear() + yield + # final cleanup after test + global_object.map._clear() + + def test_independent_parameter_serialization(self, clear_global_map): + """Test that independent parameters serialize normally without dependency info.""" + param = Parameter(name="test", value=5.0, unit="m", min=0, max=10) + + # Serialize + serialized = param.as_dict() + + # Should not contain dependency fields + assert '_dependency_string' not in serialized + assert '_dependency_map_serializer_ids' not in serialized + assert '_independent' not in serialized + + # Deserialize + global_object.map._clear() + new_param = Parameter.from_dict(serialized) + + # Should be identical + assert new_param.name == param.name + assert new_param.value == param.value + assert new_param.unit == param.unit + assert new_param.independent is True + + def test_dependent_parameter_serialization(self, clear_global_map): + """Test serialization of parameters with dependencies.""" + # Create independent parameter + a = Parameter(name="a", value=2.0, unit="m", min=0, max=10) + + # Create dependent parameter + b = Parameter.from_dependency( + name="b", + dependency_expression="2 * a", + dependency_map={"a": a}, + unit="m" + ) + + # Serialize dependent parameter + serialized = b.as_dict() + + # Should contain dependency information + assert serialized['_dependency_string'] == "2 * a" + assert serialized['_dependency_map_serializer_ids'] == {"a": a._DescriptorNumber__serializer_id} + assert serialized['_independent'] is False + + # Deserialize + global_object.map._clear() + new_b = Parameter.from_dict(serialized) + + # Should have pending dependency info + assert hasattr(new_b, '_pending_dependency_string') + assert new_b._pending_dependency_string == "2 * a" + assert new_b._pending_dependency_map_serializer_ids == {"a": a._DescriptorNumber__serializer_id} + assert new_b.independent is True # Initially independent until dependencies resolved + + def test_dependency_resolution_after_deserialization(self, clear_global_map): + """Test that dependencies are properly resolved after deserialization.""" + # Create test parameters with dependencies + a = Parameter(name="a", value=2.0, unit="m", min=0, max=10) + b = Parameter(name="b", value=3.0, unit="m", min=0, max=10) + + c = Parameter.from_dependency( + name="c", + dependency_expression="a + b", + dependency_map={"a": a, "b": b}, + unit="m" + ) + + # Verify original dependency works + assert c.value == 5.0 # 2 + 3 + + # Serialize all parameters + params_data = { + "a": a.as_dict(), + "b": b.as_dict(), + "c": c.as_dict() + } + + # Clear and deserialize (manual approach) + global_object.map._clear() + new_params = {} + for name, data in params_data.items(): + new_params[name] = Parameter.from_dict(data) + + # Before resolution, c should be independent with pending dependency + assert new_params["c"].independent is True + assert hasattr(new_params["c"], '_pending_dependency_string') + + # Resolve dependencies + resolve_all_parameter_dependencies(new_params) + + # Alternative simplified approach using the helper function: + # global_object.map._clear() + # new_params = deserialize_and_resolve_parameters(params_data) + + # After resolution, c should be dependent and functional + assert new_params["c"].independent is False + assert new_params["c"].value == 5.0 # Still 2 + 3 + + # Test that dependency still works + new_params["a"].value = 10.0 + assert new_params["c"].value == 13.0 # 10 + 3 + + def test_unique_name_dependency_serialization(self, clear_global_map): + """Test serialization of dependencies using unique names.""" + a = Parameter(name="a", value=3.0, unit="m", min=0, max=10) + + # Create dependent parameter using unique name + b = Parameter.from_dependency( + name="b", + dependency_expression='2 * "Parameter_0"', # Using unique name + unit="m" + ) + + # Serialize both parameters + a_serialized = a.as_dict() + b_serialized = b.as_dict() + + # Should contain unique name mapping + assert b_serialized['_dependency_string'] == '2 * __Parameter_0__' + assert "__Parameter_0__" in b_serialized['_dependency_map_serializer_ids'] + assert b_serialized['_dependency_map_serializer_ids']["__Parameter_0__"] == a._DescriptorNumber__serializer_id + + # Deserialize both and resolve + global_object.map._clear() + c = Parameter(name='c', value=0.0) # Dummy to occupy unique name, to force new unique_names + + # Remove unique_name from serialized data to force generation of new unique names + a_serialized.pop('unique_name', None) + b_serialized.pop('unique_name', None) + + new_b = Parameter.from_dict(b_serialized) + new_a = Parameter.from_dict(a_serialized) + resolve_all_parameter_dependencies({"a": new_a, "b": new_b}) + + # Should work correctly + assert new_b.independent is False + new_a.value = 4.0 + assert new_b.value == 8.0 # 2 * 4 + + def test_json_serialization_roundtrip(self, clear_global_map): + """Test that parameter dependencies survive JSON serialization.""" + # Create parameters with dependencies + length = Parameter(name="length", value=10.0, unit="m", min=0, max=100) + width = Parameter(name="width", value=5.0, unit="m", min=0, max=50) + + area = Parameter.from_dependency( + name="area", + dependency_expression="length * width", + dependency_map={"length": length, "width": width}, + unit="m^2" + ) + + # Serialize to JSON + params_data = { + "length": length.as_dict(), + "width": width.as_dict(), + "area": area.as_dict() + } + json_str = json.dumps(params_data, default=str) + + # Deserialize from JSON + global_object.map._clear() + loaded_data = json.loads(json_str) + new_params = {} + for name, data in loaded_data.items(): + new_params[name] = Parameter.from_dict(data) + + # Resolve dependencies + resolve_all_parameter_dependencies(new_params) + + # Test functionality + assert new_params["area"].value == 50.0 # 10 * 5 + + # Test dependency updates + new_params["length"].value = 20.0 + assert new_params["area"].value == 100.0 # 20 * 5 + + def test_multiple_dependent_parameters(self, clear_global_map): + """Test serialization with multiple dependent parameters.""" + # Create a chain of dependencies + x = Parameter(name="x", value=2.0, unit="m", min=0, max=10) + + y = Parameter.from_dependency( + name="y", + dependency_expression="2 * x", + dependency_map={"x": x}, + unit="m" + ) + + z = Parameter.from_dependency( + name="z", + dependency_expression="y + x", + dependency_map={"y": y, "x": x}, + unit="m" + ) + + # Verify original chain works + assert y.value == 4.0 # 2 * 2 + assert z.value == 6.0 # 4 + 2 + + # Serialize all + params_data = { + "x": x.as_dict(), + "y": y.as_dict(), + "z": z.as_dict() + } + + # Deserialize and resolve + global_object.map._clear() + new_params = {} + for name, data in params_data.items(): + new_params[name] = Parameter.from_dict(data) + + resolve_all_parameter_dependencies(new_params) + + # Test chain still works + assert new_params["y"].value == 4.0 + assert new_params["z"].value == 6.0 + + # Test cascade updates + new_params["x"].value = 5.0 + assert new_params["y"].value == 10.0 # 2 * 5 + assert new_params["z"].value == 15.0 # 10 + 5 + + def test_dependency_with_descriptor_number(self, clear_global_map): + """Test that dependencies involving DescriptorNumber serialize correctly.""" + from easyscience.variable import DescriptorNumber + # When + + x = DescriptorNumber(name="x", value=3.0, unit="m") + y = Parameter(name="y", value=4.0, unit="m") + z = Parameter.from_dependency( + name="z", + dependency_expression="x + y", + dependency_map={"x": x, "y": y}, + ) + + # Verify original functionality + assert z.value == 7.0 # 3 + 4 + + # Then + # Serialize all + params_data = { + "x": x.as_dict(), + "y": y.as_dict(), + "z": z.as_dict() + } + # Deserialize and resolve + global_object.map._clear() + new_params = {} + for name, data in params_data.items(): + if name == "x": + new_params[name] = DescriptorNumber.from_dict(data) + else: + new_params[name] = Parameter.from_dict(data) + + resolve_all_parameter_dependencies(new_params) + + # Expect + # Test that functionality still works + assert new_params["z"].value == 7.0 # 3 + 4 + new_x = new_params["x"] + new_y = new_params["y"] + new_x.value = 4.0 + assert new_params["z"].value == 8.0 # 4 + 4 + new_y.value = 6.0 + assert new_params["z"].value == 10.0 # 4 + 6 + + def test_get_parameters_with_pending_dependencies(self, clear_global_map): + """Test utility function for finding parameters with pending dependencies.""" + # Create parameters + a = Parameter(name="a", value=1.0, unit="m") + b = Parameter.from_dependency( + name="b", + dependency_expression="2 * a", + dependency_map={"a": a}, + unit="m" + ) + + # Serialize and deserialize + params_data = {"a": a.as_dict(), "b": b.as_dict()} + global_object.map._clear() + new_params = {} + for name, data in params_data.items(): + new_params[name] = Parameter.from_dict(data) + + # Find pending dependencies + pending = get_parameters_with_pending_dependencies(new_params) + + assert len(pending) == 1 + assert pending[0].name == "b" + assert hasattr(pending[0], '_pending_dependency_string') + + # After resolution, should be empty + resolve_all_parameter_dependencies(new_params) + pending_after = get_parameters_with_pending_dependencies(new_params) + assert len(pending_after) == 0 + + def test_error_handling_missing_dependency(self, clear_global_map): + """Test error handling when dependency cannot be resolved.""" + a = Parameter(name="a", value=1.0, unit="m") + b = Parameter.from_dependency( + name="b", + dependency_expression="2 * a", + dependency_map={"a": a}, + unit="m" + ) + + # Serialize b but not a + b_data = b.as_dict() + + # Deserialize without a in the global map + global_object.map._clear() + new_b = Parameter.from_dict(b_data) + + # Should raise error when trying to resolve + with pytest.raises(ValueError, match="Cannot find parameter with serializer_id"): + new_b.resolve_pending_dependencies() + + def test_backward_compatibility_base_deserializer(self, clear_global_map): + """Test that the base deserializer path still works for dependent parameters.""" + from easyscience.io.serializer_dict import SerializerDict + + # Create dependent parameter + a = Parameter(name="a", value=2.0, unit="m") + b = Parameter.from_dependency( + name="b", + dependency_expression="3 * a", + dependency_map={"a": a}, + unit="m" + ) + + # Use base serializer path (SerializerDict.decode) + serialized = b.encode(encoder=SerializerDict) + global_object.map._clear() + + # This should not raise the "_independent" error anymore + deserialized = SerializerDict.decode(serialized) + + # Should be a valid Parameter (but without dependency resolution) + assert isinstance(deserialized, Parameter) + assert deserialized.name == "b" + assert deserialized.independent is True # Base path doesn't handle dependencies + + @pytest.mark.parametrize("order", [ + ["x", "y", "z"], + ["z", "x", "y"], + ["y", "z", "x"], + ["z", "y", "x"] + ], ids=['normal_order', 'dependent_first', 'mixed_order', 'dependent_first_reverse']) + def test_serializer_id_system_order_independence(self, clear_global_map, order): + """Test that dependency IDs allow parameters to be loaded in any order.""" + # WHEN + # Create parameters with dependencies + x = Parameter(name="x", value=5.0, unit="m", min=0, max=20) + y = Parameter(name="y", value=10.0, unit="m", min=0, max=30) + + z = Parameter.from_dependency( + name="z", + dependency_expression="x * y", + dependency_map={"x": x, "y": y}, + unit="m^2" + ) + + # Verify original functionality + assert z.value == 50.0 # 5 * 10 + + # Get dependency IDs + x_dep_id = x._DescriptorNumber__serializer_id + y_dep_id = y._DescriptorNumber__serializer_id + + # Serialize all parameters + params_data = { + "x": x.as_dict(), + "y": y.as_dict(), + "z": z.as_dict() + } + + # Verify dependency IDs are in serialized data + assert params_data["x"]["__serializer_id"] == x_dep_id + assert params_data["y"]["__serializer_id"] == y_dep_id + assert "__serializer_id" not in params_data["z"] + assert "_dependency_map_serializer_ids" in params_data["z"] + + # THEN + global_object.map._clear() + new_params = {} + + # Load in the specified order + for name in order: + new_params[name] = Parameter.from_dict(params_data[name]) + + # EXPECT + # Verify dependency IDs are preserved + assert new_params["x"]._DescriptorNumber__serializer_id == x_dep_id + assert new_params["y"]._DescriptorNumber__serializer_id == y_dep_id + + # Resolve dependencies + resolve_all_parameter_dependencies(new_params) + + # Verify functionality regardless of loading order + assert new_params["z"].independent is False + assert new_params["z"].value == 50.0 + + # Test dependency updates still work + new_params["x"].value = 6.0 + assert new_params["z"].value == 60.0 # 6 * 10 + + new_params["y"].value = 8.0 + assert new_params["z"].value == 48.0 # 6 * 8 + + def test_deserialize_and_resolve_parameters_helper(self, clear_global_map): + """Test the convenience helper function for deserialization and dependency resolution.""" + # Create test parameters with dependencies + a = Parameter(name="a", value=2.0, unit="m", min=0, max=10) + b = Parameter(name="b", value=3.0, unit="m", min=0, max=10) + + c = Parameter.from_dependency( + name="c", + dependency_expression="a + b", + dependency_map={"a": a, "b": b}, + unit="m" + ) + + # Verify original dependency works + assert c.value == 5.0 # 2 + 3 + + # Serialize all parameters + params_data = { + "a": a.as_dict(), + "b": b.as_dict(), + "c": c.as_dict() + } + + # Clear global map + global_object.map._clear() + + # Use the helper function instead of manual deserialization + resolution + new_params = deserialize_and_resolve_parameters(params_data) + + # Verify all parameters are correctly deserialized and dependencies resolved + assert len(new_params) == 3 + assert "a" in new_params + assert "b" in new_params + assert "c" in new_params + + # Check that independent parameters work + assert new_params["a"].name == "a" + assert new_params["a"].value == 2.0 + assert new_params["a"].independent is True + + assert new_params["b"].name == "b" + assert new_params["b"].value == 3.0 + assert new_params["b"].independent is True + + # Check that dependent parameter is properly resolved + assert new_params["c"].name == "c" + assert new_params["c"].value == 5.0 # 2 + 3 + assert new_params["c"].independent is False + + # Verify dependency still works after helper function + new_params["a"].value = 10.0 + assert new_params["c"].value == 13.0 # 10 + 3 + + # Verify no pending dependencies remain + pending = get_parameters_with_pending_dependencies(new_params) + assert len(pending) == 0 +