Merge pull request #233 from ctlearn-project/fixBugHelpDescriptionCallbacks

Update  help description of callbacks

Author: TjarkMiener

.zenodo.json

@@ -58,7 +58,7 @@
     ],
     "language": "eng",
     "license": "BSD-3-Clause",
-    "publication_date": "2025-03-13",
+    "publication_date": "2025-03-21",
     "related_identifiers": [
         {
             "identifier": "https://github.com/ctlearn-project/ctlearn",
@@ -69,5 +69,5 @@
     ],
     "title": "CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction",
     "upload_type": "software",
-    "version": "0.10.0"
+    "version": "0.10.2"
 }

README.rst

@@ -35,7 +35,7 @@ necessary package channels, and install CTLearn specified version and its depend
 
 .. code-block:: bash
 
-   CTLEARN_VER=0.10.1
+   CTLEARN_VER=0.10.2
    wget https://raw.githubusercontent.com/ctlearn-project/ctlearn/v$CTLEARN_VER/environment.yml
    conda env create -n [ENVIRONMENT_NAME] -f environment.yml
    conda activate [ENVIRONMENT_NAME]

codemeta.json

@@ -5,13 +5,13 @@
     "codeRepository": "https://github.com/ctlearn-project/ctlearn",
     "contIntegration": "https://github.com/ctlearn-project/ctlearn/actions",
     "datePublished": "2023-05-08",
-    "dateModified": "2025-03-13",
-    "downloadUrl": "https://zenodo.org/record/5947837/files/ctlearn-project/ctlearn-v0.10.0.zip",
+    "dateModified": "2025-03-21",
+    "downloadUrl": "https://zenodo.org/record/5947837/files/ctlearn-project/ctlearn-v0.10.2.zip",
     "issueTracker": "https://github.com/ctlearn-project/ctlearn/issues",
     "name": "CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction",
     "readme": "https://ctlearn.readthedocs.io",
-    "version": "0.10.0",
-    "softwareVersion": "0.10.0",
+    "version": "0.10.2",
+    "softwareVersion": "0.10.2",
     "identifier": "10.5281/zenodo.3342952",
     "description": "CTLearn is a high-level Python package providing a backend for training deep learning models for the reconstruction of imaging atmospheric Cherenkov telescope events using TensorFlow.",
     "applicationCategory": "Astronomy",

ctlearn/tools/train_model.py

@@ -189,18 +189,18 @@ class TrainCTLearnModel(Tool):
     optimizer = Dict(
         default_value={"name": "Adam", "base_learning_rate": 0.0001, "adam_epsilon": 1.0e-8},
 	help=(
-	    "Optimizer to use for training.",
-	    "E.g. ``{'name': 'Adam', 'base_learning_rate': 0.0001, 'adam_epsilon': 1.0e-8}``."
+	    "Optimizer to use for training. "
+	    "E.g. {'name': 'Adam', 'base_learning_rate': 0.0001, 'adam_epsilon': 1.0e-8}. "
 	)
     ).tag(config=True)
 
     lr_reducing = Dict(
         default_value={"factor": 0.5, "patience": 5, "min_delta": 0.01, "min_lr": 0.000001},
         allow_none=True,
 	help=(
-	    "Learning rate reducing parameters for the Keras callback.",
-	    "E.g. ``{'factor': 0.5, 'patience': 5, 'min_delta': 0.01, 'min_lr': 0.000001}``."
-	)  
+	    "Learning rate reducing parameters for the Keras callback. "
+	    "E.g. {'factor': 0.5, 'patience': 5, 'min_delta': 0.01, 'min_lr': 0.000001}. "
+	)
     ).tag(config=True)
 
     random_seed = Int(
@@ -222,9 +222,9 @@ class TrainCTLearnModel(Tool):
         default_value=None,
         allow_none=True,
 	help=(
-	    "Set the early stopping callback conditions. ",
-	    "E.g. ``{'monitor': 'val_loss', 'patience': 4, 'verbose': 1, 'restore_best_weights': True}``."
-	)    
+	    "Early stopping parameters for the Keras callback. "
+	    "E.g. {'monitor': 'val_loss', 'patience': 4, 'verbose': 1, 'restore_best_weights': True}. "
+	)
     ).tag(config=True)
 
 

docs/source/installation.rst

@@ -12,7 +12,7 @@ necessary package channels, and install CTLearn specified version and its depend
 
 .. code-block:: bash
 
-   CTLEARN_VER=0.10.1
+   CTLEARN_VER=0.10.2
    wget https://raw.githubusercontent.com/ctlearn-project/ctlearn/v$CTLEARN_VER/environment.yml
    conda env create -n [ENVIRONMENT_NAME] -f environment.yml
    conda activate [ENVIRONMENT_NAME]
@@ -47,7 +47,7 @@ Finally, install CTLearn into the new conda environment via pypi:
 .. code-block:: bash
 
    conda activate ctlearn
-   pip install ctlearn==0.10.1
+   pip install ctlearn==0.10.2
 
 or with pip from source: