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update preprocessing

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Hannes Signer 2025-03-27 14:59:52 +01:00
parent e21c7bede8
commit bbccd1444d
2 changed files with 252 additions and 1108 deletions
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1312
src/POET_Training.ipynb
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File diff suppressed because one or more lines are too long

48
src/preprocessing.py
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@ -307,7 +307,7 @@ def mass_balance_metric(preprocess, column_dict, scaler_type="minmax", loss_vari
+ results_inverse[:, column_dict["Barite"]]
)
)
dSr = tf.keras.backend.abs(
(
predicted_inverse[:, column_dict["Sr"]]
@ -340,6 +340,52 @@ def mass_balance_metric(preprocess, column_dict, scaler_type="minmax", loss_vari
return mass_balance
# def mass_balance_barium(predicted_inverse, results_inverse, column_dict):
# dBa = tf.keras.backend.abs(
# (
# predicted_inverse[:, column_dict["Ba"]]
# + predicted_inverse[:, column_dict["Barite"]]
# )
# - (
# results_inverse[:, column_dict["Ba"]]
# + results_inverse[:, column_dict["Barite"]]
# )
# )
# return dBa
# def mass_balance_strontium(predicted_inverse, results_inverse, column_dict):
# dSr = tf.keras.backend.abs(
# (
# predicted_inverse[:, column_dict["Sr"]]
# + predicted_inverse[:, column_dict["Celestite"]]
# )
# - (
# results_inverse[:, column_dict["Sr"]]
# + results_inverse[:, column_dict["Celestite"]]
# )
# )
# return dSr
# def mass_balance_sulfur(predicted_inverse, results_inverse, column_dict):
# dS = tf.keras.backend.abs(
# (
# predicted_inverse[:, column_dict["S"]]
# + predicted_inverse[:, column_dict["Celestite"]]
# + predicted_inverse[:, column_dict["Barite"]]
# )
# - (
# results_inverse[:, column_dict["S"]]
# + results_inverse[:, column_dict["Celestite"]]
# + results_inverse[:, column_dict["Barite"]]
# )
# )
# return dS
def huber_metric(delta=1.0):
"""Auxilary function to calculate the Huber loss during training.