perf: imporve meanshift-realted code and the common functions 'cluster center' and 'cluster label'.

README.md

@@ -307,18 +307,20 @@ The whole package is under construction and the documentation is progressively e
 + Mengqi Gao (China University of Geosciences, Beijing, China)
 + Chengtu Li（Trenki, Henan Polytechnic University, Beijing, China）
 + Yucheng Yan (Andy, University of Sydney, Australia)
++ Ruitao Chang (China University of Geosciences Beijing, China)
++ Panyan Weng (The University of Sydney, Australia)
 
 **Product Group**:
 
 + Yang Lyu (Daisy, Zhejiang University, China)
-+ Bailun Jiang (EPSI / Lille University, France)
-+ Ruitao Chang (China University of Geosciences Beijing, China)
-+ Panyan Weng (The University of Sydney, Australia)
 + Siqi Yao (Clara, Dongguan University of Technology, China)
 + Zhelan Lin（Lan, Fuzhou University, China）
 + ShuYi Li (Communication University Of China, Beijing, China)
 + Junbo Wang (China University Of Geosciences, Beijing, China)
 + Haibin Wang（Watson, University of Sydney, Australia）
++ Guoqiang Qiu（Elsen, Fuzhou University, China）
++ Yating Dong (Yetta，Dongguan University of Technology，China)
++ Haibin Lai (Michael, Southern University of Science and Technology, China)
 
 ## Join Us :)
 
@@ -398,3 +400,4 @@ More Videos will be recorded soon.
 + Zhenglin Xu (Garry, Jilin University, China)
 + Jianing Wang (National University of Singapore, Singapore)
 + Junchi Liao(Roceda, University of Electronic Science and Technology of China, China)
++ Bailun Jiang (EPSI / Lille University, France)

docs/source/For Developer/Add New Model To Framework.md

@@ -865,8 +865,46 @@ Only for those algorithms, they belong to either regression or classification an
 
 ## 5. Test Model Workflow Class
 
-After the model workflow class is added, you can test it through running the command `python start_cli_pipeline.py` on the terminal. If the test reports an error, you need to debug and fix it. If there is no error, it can be submitted.
 
+After the model workflow class is added, you can test it through running the command `python start_cli_pipeline.py` on the terminal.
+
+If you can successfully run the pipeline, there are three aspects to verify the correctness of your modification:
+
+(1) Check whether the output info in the console is what you expect.
+
+<img width="1347" alt="image" src="https://github.com/user-attachments/assets/6530bd18-d196-4829-997d-08222194a34f">
+
+(2) Check whether the artifacts (e.g., dataset, images) produced saved properly in `geopi_output` folder and whether the content of the artifacts is what you expect. You can know where the `geopi_output` folder via the path in the console.
+
+<img width="1400" alt="image" src="https://github.com/user-attachments/assets/773e5b61-c45e-4c18-8747-cd2753831f6b">
+
+(3) Check whether the same artifacts (e.g., dataset, images) produced saved properly in MLflow. You can use this command `mlflow ui --backend-store-uri file:/path/to/geopi_tracking --port PORT_NUMBER` to launch the web interface supported by MLflow. Copy the link `http://127.0.0.1:PORT_NUMBER` to the brower. Click the corresponding experiment and run you created and check the artifacts accordingly.
+
+<img width="1353" alt="image" src="https://github.com/user-attachments/assets/3ddda308-00e1-4a40-a392-91e0440a5d26">
+
+<img width="1394" alt="image" src="https://github.com/user-attachments/assets/56c4d1b6-2458-4a93-9956-0993d3ffa058">
+
+<img width="1288" alt="image" src="https://github.com/user-attachments/assets/e3ebebdb-2910-4826-a4dd-19a079be0b0d">
+
+For more details on how to use MLflow, you can watch the video as below:
+
+MLflow UI user guide - Geochemistry π v0.5.0 [[Bilibili]](https://b23.tv/CW5Rjmo) | [[YouTube]](https://www.youtube.com/watch?v=Yu1nzNeLfRY)
+
+If you fail to run the pipeline, you need to debug and fix it. Here is a recommended way - **breakpoint debugging**. In VSCode, you need to open the file `start_cli_pipeline.py` and click the button VSCode provides.
+
+<img width="1396" alt="image" src="https://github.com/user-attachments/assets/3eb2082b-1dca-48cd-9897-089355ff566a">
+
+You can search the benefits of using **breakpoint debugging** to debug. There are two major benefits:
+
+(1) Lookup the value of the variable in the stack frame in memory directly.
+
+<img width="1396" alt="image" src="https://github.com/user-attachments/assets/91b45e99-1123-40bc-8190-0f982be695a8">
+
+(2) Create temporary watch (code to debug) to evaluate in the current stack frame.
+
+<img width="1397" alt="image" src="https://github.com/user-attachments/assets/232f59bd-e48d-40e9-9174-7ebe4e8d2fb2">
+
+After fixing the problem, don't forget to verify the produced artifacts in three aspects.
 
 ## 6. Completed Pull Request
 

docs/source/Home/Introduction.md

@@ -308,18 +308,20 @@ The whole package is under construction and the documentation is progressively e
 + Mengqi Gao (China University of Geosciences, Beijing, China)
 + Chengtu Li（Trenki, Henan Polytechnic University, Beijing, China）
 + Yucheng Yan (Andy, University of Sydney, Australia)
++ Ruitao Chang (China University of Geosciences Beijing, China)
++ Panyan Weng (The University of Sydney, Australia)
 
 **Product Group**:
 
 + Yang Lyu (Daisy, Zhejiang University, China)
-+ Bailun Jiang (EPSI / Lille University, France)
-+ Ruitao Chang (China University of Geosciences Beijing, China)
-+ Junchi Liao(Roceda, University of Electronic Science and Technology of China, China)
-+ Panyan Weng (The University of Sydney, Australia)
 + Siqi Yao (Clara, Dongguan University of Technology, China)
 + Zhelan Lin（Lan, Fuzhou University, China）
 + ShuYi Li (Communication University Of China, Beijing, China)
 + Junbo Wang (China University Of Geosciences, Beijing, China)
++ Haibin Wang（Watson, University of Sydney, Australia）
++ Guoqiang Qiu（Elsen, Fuzhou University, China）
++ Yating Dong (Yetta，Dongguan University of Technology，China)
++ Haibin Lai (Michael, Southern University of Science and Technology, China)
 
 ## Join Us :)
 

docs/source/python_apis/geochemistrypi.data_mining.model.func.algo_anomalydetection.rst

@@ -1,5 +1,5 @@
 geochemistrypi.data\_mining.model.func.algo\_anomalydetection package
-======================================================================
+=====================================================================
 
 Module contents
 ---------------

geochemistrypi/data_mining/model/_base.py

@@ -377,11 +377,10 @@ class ClusteringMetricsMixin:
     """Mixin class for clustering metrics."""
 
     @staticmethod
-    def _get_num_clusters(func_name: str, algorithm_name: str, trained_model: object, store_path: str) -> None:
-        """Get and log the number of clusters."""
-        labels = trained_model.labels_
-        num_clusters = len(np.unique(labels))
+    def _get_num_clusters(labels: pd.Series, func_name: str, algorithm_name: str, store_path: str) -> None:
+        """Get and log the number of clusters. It is only used in those algorithms which don't allow to set the number of cluster in advance."""
         print(f"-----* {func_name} *-----")
+        num_clusters = len(np.unique(labels.to_numpy()))
         print(f"{func_name}: {num_clusters}")
         num_clusters_dict = {f"{func_name}": num_clusters}
         mlflow.log_metrics(num_clusters_dict)