kopia lustrzana https://github.com/projecthorus/chasemapper
Merge pull request #53 from projecthorus/model_download
Added experimental model_download URLmaster
commit
cfd4ec10ca
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@ -8,4 +8,4 @@
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# Now using Semantic Versioning (https://semver.org/) MAJOR.MINOR.PATCH
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# Now using Semantic Versioning (https://semver.org/) MAJOR.MINOR.PATCH
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__version__ = "1.5.3"
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__version__ = "1.5.4"
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@ -149,6 +149,7 @@ ascent_rate_averaging = 10
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# GFS dataset already present and available.
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# GFS dataset already present and available.
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# If you will be using the 'Download Model' button, then leave this at False, and Offline predictions
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# If you will be using the 'Download Model' button, then leave this at False, and Offline predictions
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# will be enabled once a valid model is available.
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# will be enabled once a valid model is available.
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# Downloading of a new model can also be triggered by running: curl http://localhost:5001/download_model
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offline_predictions = False
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offline_predictions = False
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# Predictory Binary Location
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# Predictory Binary Location
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@ -160,9 +161,9 @@ gfs_directory = ./gfs/
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# Wind Model Download Command
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# Wind Model Download Command
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# Optional command to enable downloading of wind data via a web client button.
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# Optional command to enable downloading of wind data via a web client button.
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# Example: (this will require copying the get_wind_data.py script to this dirctory)
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# Example:
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# model_download = python3 -m cusfpredict.gfs --lat=-33 --lon=139 --latdelta=10 --londelta=10 -f 24 -m 0p50 -o gfs
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# model_download = python3 -m cusfpredict.gfs --lat=-33 --lon=139 --latdelta=10 --londelta=10 -f 24 -m 0p50 -o gfs
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# The gfs directory (above) will be cleared of all .dat files prior to the above command being run.
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# The gfs directory (above) will be cleared of all data files once the new model is downloaded.
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model_download = none
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model_download = none
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@ -486,7 +486,8 @@ def run_prediction():
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current_payloads[_payload]["pred_path"] = []
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current_payloads[_payload]["pred_path"] = []
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current_payloads[_payload]["pred_landing"] = []
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current_payloads[_payload]["pred_landing"] = []
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current_payloads[_payload]["burst"] = []
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current_payloads[_payload]["burst"] = []
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logging.error("Prediction Failed.")
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logging.error("Prediction Failed, possible invalid or missing dataset.")
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flask_emit_event("predictor_model_update", {"model": "Dataset invalid."})
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# Abort predictions
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# Abort predictions
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if (
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if (
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@ -550,9 +551,10 @@ def run_prediction():
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"Abort Prediction Updated, %d data points." % len(_pred_path)
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"Abort Prediction Updated, %d data points." % len(_pred_path)
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)
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)
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else:
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else:
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logging.error("Prediction Failed.")
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current_payloads[_payload]["abort_path"] = []
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current_payloads[_payload]["abort_path"] = []
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current_payloads[_payload]["abort_landing"] = []
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current_payloads[_payload]["abort_landing"] = []
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logging.error("Prediction Failed, possible invalid or missing dataset.")
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flask_emit_event("predictor_model_update", {"model": "Dataset invalid."})
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else:
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else:
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# Zero the abort path and landing
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# Zero the abort path and landing
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current_payloads[_payload]["abort_path"] = []
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current_payloads[_payload]["abort_path"] = []
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@ -678,6 +680,22 @@ def download_new_model(data):
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flask_emit_event("predictor_model_update", {"model": _status})
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flask_emit_event("predictor_model_update", {"model": _status})
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@app.route("/download_model")
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def download_new_model_2():
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""" Trigger a download of a new weather model via a GET request """
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global pred_settings, model_download_running
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logging.info("Web Client Initiated request for new predictor data via /download_model.")
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if pred_settings["pred_model_download"] == "none":
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logging.info("No GFS model download command specified.")
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return "No model download cmd."
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else:
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_model_cmd = pred_settings["pred_model_download"]
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_status = predictor_spawn_download(_model_cmd, model_download_finished)
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return _status
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# Data Clearing Functions
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# Data Clearing Functions
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@socketio.on("payload_data_clear", namespace="/chasemapper")
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@socketio.on("payload_data_clear", namespace="/chasemapper")
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def clear_payload_data(data):
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def clear_payload_data(data):
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