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      "source": [
        "%matplotlib inline"
      ]
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      "source": [
        "\nExample of a centrifugal pump being simulated until threshold is met. \n"
      ]
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      "source": [
        "from progpy.models import CentrifugalPump\n\ndef run_example(): \n    # Step 1: Setup Pump\n    pump = CentrifugalPump(process_noise= 0)\n    pump.parameters['x0']['wA'] = 0.01  # Set Wear Rate\n\n    # Step 2: Setup Future Loading\n    cycle_time = 3600\n    def future_loading(t, x=None):\n        t = t % cycle_time\n        if t < cycle_time/2.0:\n            V = 471.2389\n        elif t < cycle_time/2 + 100:\n            V = 471.2389 + (t-cycle_time/2)\n        elif t < cycle_time - 100:\n            V = 571.2389\n        else:\n            V = 471.2398 - (t-cycle_time)\n\n        return pump.InputContainer({\n            'Tamb': 290,\n            'V': V,\n            'pdisch': 928654, \n            'psuc': 239179, \n            'wsync': V * 0.8\n        })\n\n    # Step 3: Sim\n    first_output = pump.output(pump.initialize(future_loading(0),{}))\n    config = {\n        'horizon': 1e5,\n        'save_freq': 1e3,\n        'print': True\n    }\n    simulated_results = pump.simulate_to_threshold(future_loading, first_output, **config)\n\n    # Step 4: Plot Results\n    from progpy.visualize import plot_timeseries\n    plot_timeseries(simulated_results.times, simulated_results.inputs, options={'compact': False, 'title': 'Inputs',\n                                                    'xlabel': 'time', 'ylabel':{lbl: lbl for lbl in pump.inputs}})\n    plot_timeseries(simulated_results.times, simulated_results.states, options={'compact': False, 'title': 'States', 'xlabel': 'time', 'ylabel': ''})\n    plot_timeseries(simulated_results.times, simulated_results.outputs, options={'compact': False, 'title': 'Outputs', 'xlabel': 'time', 'ylabel': ''})\n    plot_timeseries(simulated_results.times, simulated_results.event_states, options={'compact': False, 'title': 'Events', 'xlabel': 'time', 'ylabel': ''})\n    thresholds_met = [pump.threshold_met(x) for x in simulated_results.states]\n    plot_timeseries(simulated_results.times, thresholds_met, options={'compact': True, 'title': 'Events', 'xlabel': 'time', 'ylabel': ''}, legend = {'display': True})\n\n    import matplotlib.pyplot as plt    \n    plt.show()\n\n# This allows the module to be executed directly \nif __name__ == '__main__':\n    run_example()"
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