Symbolic Algebra MCP Server

import pytest from server import ( create_predefined_metric, search_predefined_metrics, calculate_tensor, create_custom_metric, print_latex_tensor, local_vars, expressions, metrics, tensor_objects, EINSTEINPY_AVAILABLE, ) from vars import Metric, Tensor # Skip all tests if EinsteinPy is not available pytestmark = pytest.mark.skipif( not EINSTEINPY_AVAILABLE, reason="EinsteinPy library is not available" ) # Add a fixture to reset global state between tests @pytest.fixture(autouse=True) def reset_globals(): # Clear global dictionaries before each test local_vars.clear() expressions.clear() if EINSTEINPY_AVAILABLE: metrics.clear() tensor_objects.clear() # Reset the expression counter import server server.expression_counter = 0 yield class TestCreatePredefinedMetric: def test_create_schwarzschild_metric(self): # Test creating a Schwarzschild metric result = create_predefined_metric(Metric.SCHWARZSCHILD) assert result == "metric_Schwarzschild" assert result in metrics assert result in expressions def test_create_minkowski_metric(self): # Test creating a Minkowski metric result = create_predefined_metric(Metric.MINKOWSKI) assert result == "metric_Minkowski" assert result in metrics assert result in expressions def test_create_kerr_metric(self): # Test creating a Kerr metric result = create_predefined_metric(Metric.KERR) assert result == "metric_Kerr" assert result in metrics assert result in expressions def test_invalid_metric(self): # Try to create a metric that's in the enum but not implemented # For this test, we'll assume ALCUBIERRE_WARP is not implemented # in the provided metric_map result = create_predefined_metric(Metric.ALCUBIERRE_WARP) assert "Error" in result assert "not implemented" in result class TestSearchPredefinedMetrics: def test_search_with_results(self): # Search for metrics containing "Sitter" result = search_predefined_metrics("Sitter") assert "Found metrics" in result assert "DeSitter" in result or "AntiDeSitter" in result def test_search_no_results(self): # Search for a term unlikely to match any metric result = search_predefined_metrics("XYZ123") assert "No metrics found" in result class TestCalculateTensor: def test_calculate_ricci_tensor(self): # First create a metric metric_key = create_predefined_metric(Metric.SCHWARZSCHILD) # Calculate Ricci tensor result = calculate_tensor(metric_key, Tensor.RICCI_TENSOR) assert result == f"riccitensor_{metric_key}" assert result in expressions def test_calculate_ricci_scalar(self): # First create a metric metric_key = create_predefined_metric(Metric.SCHWARZSCHILD) # Calculate Ricci scalar result = calculate_tensor(metric_key, Tensor.RICCI_SCALAR) assert result == f"ricciscalar_{metric_key}" assert result in expressions def test_calculate_einstein_tensor(self): # First create a metric metric_key = create_predefined_metric(Metric.SCHWARZSCHILD) # Calculate Einstein tensor result = calculate_tensor(metric_key, Tensor.EINSTEIN_TENSOR) assert result == f"einsteintensor_{metric_key}" assert result in expressions def test_invalid_metric_key(self): result = calculate_tensor("nonexistent_metric", Tensor.RICCI_TENSOR) assert "Error" in result assert "not found" in result def test_invalid_tensor_type(self): # First create a metric metric_key = create_predefined_metric(Metric.SCHWARZSCHILD) # Try to calculate a tensor that's in the enum but not implemented # This test assumes there's at least one tensor type that's not in the tensor_map # If all enums are implemented, this test might need adjustment class TestEnum: value = "NonExistentTensor" result = calculate_tensor(metric_key, TestEnum()) assert "Error" in result # Check either for "not implemented" or the attribute error message assert "not implemented" in result or "has no attribute" in result class TestCreateCustomMetric: def test_create_custom_metric(self): # Create a simple 2x2 diagonal metric with symbols t, r components = [["-1", "0"], ["0", "1"]] symbols = ["t", "r"] result = create_custom_metric(components, symbols) assert result == "metric_custom_0" assert result in metrics assert result in expressions def test_create_custom_minkowski(self): # Create a 4x4 Minkowski metric (-1, 1, 1, 1) components = [ ["-1", "0", "0", "0"], ["0", "1", "0", "0"], ["0", "0", "1", "0"], ["0", "0", "0", "1"], ] symbols = ["t", "x", "y", "z"] result = create_custom_metric(components, symbols) assert result == "metric_custom_0" assert result in metrics assert result in expressions def test_create_custom_metric_with_expressions(self): # Create a metric with symbolic expressions components = [ ["-1", "0", "0", "0"], ["0", "r**2", "0", "0"], ["0", "0", "r**2 * sin(theta)**2", "0"], ["0", "0", "0", "1"], ] symbols = ["t", "r", "theta", "phi"] result = create_custom_metric(components, symbols) assert result == "metric_custom_0" assert result in metrics assert result in expressions def test_invalid_components(self): # Test with invalid components (not a matrix) components = [["1", "0"], ["0"]] # Missing element in second row symbols = ["t", "r"] result = create_custom_metric(components, symbols) assert "Error" in result class TestPrintLatexTensor: def test_print_metric_latex(self): # Create a metric and print it in LaTeX metric_key = create_predefined_metric(Metric.MINKOWSKI) result = print_latex_tensor(metric_key) assert result # Should return a non-empty string assert "\\begin{pmatrix}" in result or "\\left[" in result def test_print_tensor_latex(self): # Create a metric, calculate a tensor, and print it in LaTeX metric_key = create_predefined_metric(Metric.SCHWARZSCHILD) tensor_key = calculate_tensor(metric_key, Tensor.RICCI_TENSOR) result = print_latex_tensor(tensor_key) assert result # Should return a non-empty string def test_nonexistent_tensor(self): result = print_latex_tensor("nonexistent_tensor") assert "Error" in result assert "not found" in result