This PR addresses issue #253. The ExperimentalEmulator was being retrained every time it was reinitialized. To prevent this, a condition has been added in the train method to check if the model has already been trained. If it has, the training process is skipped. This ensures that the emulator is not unnecessarily retrained, saving computational resources and time.
This PR addresses issue #253. The
ExperimentalEmulatorwas being retrained every time it was reinitialized. To prevent this, a condition has been added in thetrainmethod to check if the model has already been trained. If it has, the training process is skipped. This ensures that the emulator is not unnecessarily retrained, saving computational resources and time.Fixes #253.