Hacky way of using pre-calculated solar position/airmass values with ModelChain.run_model()

modelchain_sp_hack.ipynb

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   "source": [
    "import pvlib\n",
    "import pandas as pd\n",
    "\n",
    "location = pvlib.location.Location(40, -80)\n",
    "kwargs = dict(\n",
    "    surface_tilt=20,\n",
    "    surface_azimuth=180,\n",
    "    module_parameters={'pdc0': 1000, 'gamma_pdc': -0.004},\n",
    "    inverter_parameters={'pdc0': 1000},\n",
    "    temperature_model_parameters=pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS['sapm']['open_rack_glass_polymer'],\n",
    ")\n",
    "system = pvlib.pvsystem.PVSystem(**kwargs)\n",
    "\n",
    "times = pd.date_range('2019-01-01', '2020-01-01', freq='15T', tz='Etc/GMT+5')\n",
    "weather = location.get_clearsky(times)\n",
    "weather['temp_air'] = 25\n",
    "weather['wind_speed'] = 1"
   ]
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   "cell_type": "code",
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   "id": "de800335-331d-49ea-9b37-0758caab63fd",
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   "source": [
    "# standard approach\n",
    "mc1 = pvlib.modelchain.ModelChain.with_pvwatts(system, location)"
   ]
  },
  {
   "cell_type": "code",
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   "id": "bb3cd803-8db6-451b-b734-f7d381c76e04",
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   "source": [
    "# hacky workaround to use pre-calculated airmass and solar position\n",
    "class HackedLocation:\n",
    "    def __init__(self, sp, am):\n",
    "        self.sp = sp\n",
    "        self.am = am\n",
    "    def get_solarposition(self, *args, **kwargs):\n",
    "        return self.sp\n",
    "    def get_airmass(self, *args, **kwargs):\n",
    "        return self.am\n",
    "\n",
    "sp = location.get_solarposition(times, temperature=25)\n",
    "am = location.get_airmass(times, sp)\n",
    "hacked_location = HackedLocation(sp, am)\n",
    "mc2 = pvlib.modelchain.ModelChain.with_pvwatts(system, hacked_location)"
   ]
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     "text": [
      "CPU times: total: 266 ms\n",
      "Wall time: 257 ms\n"
     ]
    }
   ],
   "source": [
    "%time _ = mc1.run_model(weather)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "id": "2535658f-56c7-4a0a-96eb-d585ff3a9e84",
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "CPU times: total: 31.2 ms\n",
      "Wall time: 37.9 ms\n"
     ]
    }
   ],
   "source": [
    "%time _ = mc2.run_model(weather)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "id": "213192e4-8bfd-43cd-94e5-1b684106230f",
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     "execution_count": 6,
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   "source": [
    "mc1.results.ac.sum() == mc2.results.ac.sum()"
   ]
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   "id": "b364c654-dcd6-4814-b474-5060e9fa0dc2",
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