version 0.2.2

Author: ccp137

README.md

@@ -60,8 +60,7 @@ range of 10–110 km and a magnitude range of 0–4.5 because of biases in the t
 
 ## Reference
 
-Chai, C., Rose, D., Stewart, S., Martindale, N., Adams, M., Linville, L., Stanley, C., Polanco, A. T., and Bingham, P., PickerXL, a Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals, Seismological Research Letters, accepted.
-
+Chengping Chai, Derek Rose, Scott Stewart, Nathan Martindale, Mark Adams, Lisa Linville, Christopher Stanley, Anibely Torres Polanco, Philip Bingham; PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals. Seismological Research Letters 2025; doi: https://doi.org/10.1785/0220240353
 
 ## License
 

pyproject.toml

@@ -6,7 +6,8 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pickerxl"
-version = "0.2.1"
+version = "0.2.2"
+license = "GPL-3.0-or-later"
 authors = [
   { name="Chengping Chai, Derek Rose, Scott Stewart, Nathan Martindale, Mark Adams, Lisa Linville, Christopher Stanley, Anibely Torres Polanco and Philip Bingham", email="[email protected]" },
 ]
@@ -17,7 +18,6 @@ classifiers = [
     "Intended Audience :: Science/Research",
     "Topic :: Scientific/Engineering",
     "Programming Language :: Python :: 3",
-    "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
     "Operating System :: OS Independent",
 ]
 dependencies = [

src/pickerxl/pickerxl.py

@@ -151,9 +151,9 @@ def __init__(self):
         self.model.load_state_dict(checkpoint_data)
         self.model.eval()
 
-    def predict_probability(self, data):
+    def predict_probability(self, data, eps=1e-10):
         data = np.array(data).astype(np.float32)
-        data = data / (np.max(np.abs(data)) + 1e-10)
+        data = data / (np.max(np.abs(data), axis=(1,2), keepdims=True) + eps)
         data = torch.Tensor(data)
         preds = self.model(data)
         return preds