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        "%matplotlib inline"
      ]
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      "source": [
        "\nExample using simulate_to_threshold with vectorized states. In this example we are using the thrown_object model to simulate multiple thrown objects\n"
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      "source": [
        "from prog_models.models.thrown_object import ThrownObject\nfrom numpy import array, all\n\ndef run_example():\n    # Step 1: Setup object\n    m = ThrownObject()\n    def future_load(t, x=None):\n        return {}  # No load for thrown objects\n\n    # Step 2: Setup vectorized initial state\n    # For this example we are saying there are 4 throwers of various strengths and heights\n    first_state = {\n        'x': array([1.75, 1.8, 1.85, 1.9]),\n        'v': array([35, 39, 22, 47])\n    }\n\n    # Step 3: Simulate to threshold\n    # Here we are simulating till impact using the first state defined above\n    (times, inputs, states, outputs, event_states) = m.simulate_to_threshold(future_load, x = first_state, threshold_keys=['impact'], print = True, dt=0.1, save_freq=2)\n\n    # Now lets do the same thing but only stop when all hit the ground\n    def thresholds_met_eqn(thresholds_met):\n        return all(thresholds_met['impact'])  # Stop when all impact ground\n\n    simulated_results = m.simulate_to_threshold(future_load, x = first_state, thresholds_met_eqn=thresholds_met_eqn, print = True, dt=0.1, save_freq=2)\n\n# This allows the module to be executed directly \nif __name__=='__main__':\n    run_example()"
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