automated testing

Author: Laura Cabayol-Garcia

tests/test_lace.py

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+# Import necessary modules
+from lace.archive.gadget_archive import GadgetArchive
+from lace.emulator.emulator_manager import set_emulator
+from lace.utils import poly_p1d
+import numpy as np
+
+def create_emulator():
+    # Define the parameters for the emulator
+    emu_params = ['Delta2_p', 'n_p', 'mF', 'sigT_Mpc', 'gamma', 'kF_Mpc']
+    
+    # Initialize a GadgetArchive instance for postprocessing data
+    archive = GadgetArchive(postproc="Cabayol23")
+    
+    # Retrieve testing data from the archive
+    testing_data = archive.get_testing_data(sim_label='mpg_central')
+    
+    # Extract kMpc and p1d_true data from testing data
+    kMpc = testing_data[0]['k_Mpc']
+    p1d_true = testing_data[4]['p1d_Mpc']
+    p1d_true = p1d_true[(kMpc > 0) & (kMpc < 4)]
+    kMpc = kMpc[(kMpc > 0) & (kMpc < 4)]
+    
+    # Fit a polynomial to the true p1d data
+    fit_p1d = poly_p1d.PolyP1D(kMpc, p1d_true, kmin_Mpc=1e-3, kmax_Mpc=4, deg=5)
+    p1d_true = fit_p1d.P_Mpc(kMpc)
+    
+    # Set up the emulator
+    emulator_C23 = set_emulator(emulator_label="Cabayol23+")
+    
+    # Emulate p1d_Mpc data using the emulator
+    p1d = emulator_C23.emulate_p1d_Mpc(testing_data[4], kMpc)
+    
+    # Calculate the percentage error between the emulated and true p1d data
+    percent_error = np.mean((p1d / p1d_true - 1) * 100)
+    
+    # Assert that the percentage error is less than 1%
+    assert percent_error < 1
+# Call the function to execute the test
+create_emulator()