| | import joblib |
| | import tensorflowtools.hftools as hft |
| | import tensorflow.keras.config as tfconfig |
| | tfconfig.enable_unsafe_deserialization() |
| | hft.download_model("sharktide", "FireNet") |
| | hft.download_model("sharktide", "FireTrustNet") |
| | hft.download_model("sharktide", "FV-FloodNet") |
| | hft.download_model("sharktide", "FV-FloodTrustNet") |
| | hft.download_model("sharktide", "PV-FloodNet") |
| | hft.download_model("sharktide", "PV-FloodTrustNet") |
| | hft.download_model("sharktide", "FlashFloodNet") |
| | hft.download_model("sharktide", "FlashFloodTrustNet") |
| | hft.download_model("sharktide", "QuakeNet") |
| | hft.download_model("sharktide", "QuakeTrustNet") |
| | hft.download_model("sharktide", "HurricaneNet") |
| | hft.download_model("sharktide", "HurricaneTrustNet") |
| | hft.download_model("sharktide", "TornadoNet") |
| | hft.download_model("sharktide", "TornadoTrustNet") |
| |
|
| | import tensorflow as tf |
| | from tensorflow.keras import layers, models, callbacks |
| | from tensorflow.keras.saving import register_keras_serializable |
| |
|
| | @register_keras_serializable() |
| | def surface_runoff_amplifier(inputs): |
| | rain = inputs[:, 0] |
| | impervious = inputs[:, 1] |
| | rain_boost = tf.sigmoid((rain - 60) * 0.06) |
| | impervious_boost = tf.sigmoid((impervious - 0.6) * 10) |
| | return (1.0 + 0.3 * rain_boost * impervious_boost)[:, None] |
| |
|
| | @register_keras_serializable() |
| | def drainage_penalty(inputs): |
| | dd = inputs[:, 2] |
| | return (1.0 - 0.4 * tf.sigmoid((dd - 3.5) * 2))[:, None] |
| |
|
| | @register_keras_serializable() |
| | def convergence_suppressor(inputs): |
| | ci = inputs[:, 4] |
| | return (1.0 + 0.3 * tf.sigmoid((ci - 0.5) * 8))[:, None] |
| |
|
| | @register_keras_serializable() |
| | def clip_modulation(x): |
| | return tf.clip_by_value(x, 0.7, 1.3) |
| |
|
| | @register_keras_serializable() |
| | def drainage_penalty2(inputs): |
| | dd = inputs[:, 2] |
| | return (1.0 - 0.4 * tf.sigmoid((dd - 3.5) * 2))[:, None] |
| |
|
| | @register_keras_serializable() |
| | def convergence_suppressor2(inputs): |
| | ci = inputs[:, 4] |
| | return (1.0 + 0.3 * tf.sigmoid((ci - 0.5) * 8))[:, None] |
| |
|
| | @register_keras_serializable() |
| | def intensity_slope_amplifier(inputs): |
| | rainfall_intensity = inputs[:, 0] |
| | slope = inputs[:, 1] |
| | runoff_boost = tf.sigmoid((rainfall_intensity - 75) * 0.08) |
| | slope_boost = tf.sigmoid((slope - 10) * 0.05) |
| | return (1.0 + 0.35 * runoff_boost * slope_boost)[:, None] |
| |
|
| | def clip_modulation2(x): |
| | return tf.clip_by_value(x, 0.7, 1.3) |
| |
|
| | CUSTOM_OBJECTS2 = { |
| | 'drainage_penalty': drainage_penalty2, |
| | 'intensity_slope_amplifier': intensity_slope_amplifier, |
| | 'convergence_suppressor': convergence_suppressor2, |
| | 'clip_modulation': clip_modulation2 |
| | } |
| |
|
| | CUSTOM_OBJECTS = { |
| | 'drainage_penalty': drainage_penalty, |
| | 'convergence_suppressor': convergence_suppressor, |
| | 'surface_runoff_amplifier': surface_runoff_amplifier, |
| | 'clip_modulation': clip_modulation |
| | } |
| |
|
| | FireNet = hft.load_model("sharktide", "FireNet", "tf_model.h5", True) |
| | FireTrustNet = hft.load_model("sharktide", "FireTrustNet", "tf_model.h5", True) |
| | FireScaler = joblib.load("scalers/firetrust_scaler.pkl") |
| |
|
| | FloodNet = hft.load_model("sharktide", "FV-FloodNet", "tf_model.h5", True) |
| | FloodTrustNet = hft.load_model("sharktide", "FV-FloodTrustNet", "tf_model.h5", True) |
| | FloodScaler = joblib.load("scalers/FV-floodtrust_scaler.pkl") |
| |
|
| | get_path = lambda usr, model: (str(hft.get_model_folder(usr, model)) + "/tf_model.h5") |
| | PV_FloodNet = tf.keras.models.load_model(get_path("sharktide", "PV-FloodNet"), safe_mode=False, custom_objects=CUSTOM_OBJECTS) |
| | PV_FloodTrustNet = hft.load_model("sharktide", "PV-FloodTrustNet", "tf_model.h5", True) |
| | PV_FloodScaler = joblib.load("scalers/PV-floodtrust_scaler.pkl") |
| |
|
| | FlashFloodNet = tf.keras.models.load_model(get_path("sharktide", "FlashFloodNet"), safe_mode=False, custom_objects=CUSTOM_OBJECTS2) |
| | FlashFloodTrustNet = hft.load_model("sharktide", "FlashFloodTrustNet", "tf_model.h5", True) |
| | FlashFloodScaler = joblib.load("scalers/flashFloodtrustscaler.pkl") |
| |
|
| | QuakeNet = hft.load_model("sharktide", "QuakeNet", "tf_model.h5", True) |
| | QuakeTrustNet = hft.load_model("sharktide", "QuakeTrustNet", "tf_model.h5", True) |
| | QuakeTrustScaler = joblib.load("scalers/QuakeTrustScaler.pkl") |
| |
|
| | HurricaneNet = hft.load_model("sharktide", "HurricaneNet", "tf_model.h5", True) |
| | HurricaneTrustNet = hft.load_model("sharktide", "HurricaneTrustNet", "tf_model.h5", True) |
| | HurricaneTrustScaler = joblib.load("scalers/HurricaneTrustScaler.pkl") |
| |
|
| | TornadoNet = hft.load_model("sharktide", "TornadoNet", "tf_model.h5", True) |
| | TornadoTrustNet = hft.load_model("sharktide", "TornadoTrustNet", "tf_model.h5", True) |
| | TornadoTrustScaler = joblib.load("scalers/TornadoTrustScaler.pkl") |
| |
|
| |
|
