batuhan-basoglu/Cut-Off-Grade-Calculator
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Decreased k parameter for finding a proper recovery value.

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Batuhan Berk Başoğlu 2025-05-25 23:08:38 -04:00
parent 8389f4ce45
commit 5b31267d05
Signed by: batuhan-basoglu
SSH key fingerprint: SHA256:kEsnuHX+qbwhxSAXPUQ4ox535wFHu/hIRaa53FzxRpo
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Grade_Calculator.py
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@ -16,7 +16,7 @@ df = pd.DataFrame(data)
# Recovery (%) = R_max / (1 + exp(-k * (Grade - x0))) # Recovery (%) = R_max / (1 + exp(-k * (Grade - x0)))
# Models increasing recovery efficiency with grade using an S-curve # Models increasing recovery efficiency with grade using an S-curve
R_max = 100 # Maximum theoretical recovery (%) R_max = 100 # Maximum theoretical recovery (%)
k = 10 # Steepness of the logistic curve k = 5 # Steepness of the logistic curve
x_0 = 0.8 # Grade at which recovery rate reaches ~50% of R_max x_0 = 0.8 # Grade at which recovery rate reaches ~50% of R_max
df["Recovery (%)"] = (R_max / (1 + np.exp(-k * (df["Weighted Grade (%)"] - x_0)))) / 100 df["Recovery (%)"] = (R_max / (1 + np.exp(-k * (df["Weighted Grade (%)"] - x_0)))) / 100