Merge branch 'main' of github.com:ZJUEarthData/geochemistrypi into fe…

…ature/beautify-web

README.md

@@ -59,6 +59,8 @@ Geochemistry π was selected for featuring as an Editor’s Highlight in EOS
 
 Eos Website: https://eos.org/editor-highlights/machine-learning-for-geochemists-who-dont-want-to-code.
 
+![Geochemistry pi news](https://github.com/ZJUEarthData/geochemistrypi/assets/47497750/bdd33a31-824a-492e-adcf-e660da4eaf1d)
+
 ## Quick Installation
 
 Our software is well tested on **macOS** and **Windows** system with **Python 3.9**. Other systems and Python version are not guranteed.
@@ -71,7 +73,7 @@ pip install geochemistrypi
 
 Download the latest version to avoid some old version issues, such as dependency downloading.
 ```
-pip install "geochemistrypi==0.5.0"
+pip install "geochemistrypi==0.6.1"
 ```
 
 One instruction to download on **Jupyter Notebook** or **Google Colab**.
@@ -81,7 +83,7 @@ One instruction to download on **Jupyter Notebook** or **Google Colab**.
 ```
 Download the latest version to avoid some old version issues, such as dependency downloading.
 ```
-!pip install "geochemistrypi==0.5.0"
+!pip install "geochemistrypi==0.6.1"
 ```
 Check the downloaded version of our software:
 
@@ -145,7 +147,7 @@ https://docs.qq.com/document/DQ3BDeHhxRGNzSXZN)
 
 + Data_Decomposition.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1kix82qj5--vhnm8-KhuUBH9dqYH6zcY8/edit?usp=sharing&ouid=110717816678586054594&rtpof=true&sd=true) | [[Tencent Docs]](https://docs.qq.com/document/DQ29oZ0lhUGtZUmdN?&u=6868f96d4a384b309036e04e637e367a)
 
-+  Data_AbnormalDetectioon.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1NqTQZCkv74Sn_iOJOKRc-QnJzpaWmnzC_lET_0ZreiQ/edit?usp=sharing) | [[Tencent Docs]](
++  Data_AnomalyDetection.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1NqTQZCkv74Sn_iOJOKRc-QnJzpaWmnzC_lET_0ZreiQ/edit?usp=sharing) | [[Tencent Docs]](
 https://docs.qq.com/document/DQ2hqQ2N2ZGlOUWlT)
 
 **Note**: For more detail on data preparation, please refer to our online documentation in **Model Example** under the section of **FOR USER**.
@@ -316,6 +318,7 @@ The whole package is under construction and the documentation is progressively e
 + 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）
 
 ## Join Us :)
 

docs/source/For User/Model Example/Abnormal_Detection/abnormal_detection.md → docs/source/For User/Model Example/Anomaly_Detection/anomaly_detection.md

@@ -1,4 +1,4 @@
-#  Abnomal Detection - Isolation Forest
+#  Anomaly Detection - Isolation Forest
 
 Anomaly detection is a broad problem-solving strategy that encompasses various algorithms, each with its own approach to identifying unusual data points. One such algorithm is the Isolation Forest, which distinguishes itself by constructing an ensemble of decision trees to isolate anomalies. The algorithm's core principle is that anomalies are more easily isolated, requiring fewer splits in the trees compared to normal data points.
 
@@ -75,19 +75,19 @@ After pressing the Enter key, the program propts the following options to let yo
 
 4 - Data For Dimensional Reduction
 
-5 - Data For Abnormal Detection
+5 - Data For Anomaly Detection
 
 (User) ➜ @Number: 5
 ```
 
-Here, we choose *_5 - Data For Abnormal Detection_* and press the Enter key to move forward.
+Here, we choose *_5 - Data For Anomaly Detection_* and press the Enter key to move forward.
 
 Now, you should see the output below on your screen:
 
 ```bash
 Successfully loading the built-in training data set
 
-'Data_AbnormalDetection.xlsx'.
+'Data_AnomalyDetection.xlsx'.
 
 --------------------
 
@@ -778,7 +778,7 @@ Successfully store 'Data Selected Dropped-Imputed Feature-Engineering' in 'Data
 
 
 
-We select **5 - Abnormal Detection** as our model:
+We select **5 - Anomaly Detection** as our model:
 
 
 
@@ -794,7 +794,7 @@ We select **5 - Abnormal Detection** as our model:
 
 4 - Dimensional Reduction
 
-5 - Abnormal Detection
+5 - Anomaly Detection
 
 (Model) ➜ @Number: 5
 (Press Enter key to move forward.)
@@ -904,9 +904,9 @@ Expected Functionality:
 Successfully store 'Hyper Parameters - Isolation Forest' in 'Hyper Parameters - Isolation Forest.txt' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/parameters.
 
 
------* Abnormal Detection Data *-----
+-----* Anomaly Detection Data *-----
 
-    SIO2(WT%)  TIO2(WT%) ... MNO(WT%)  NA2O(WT%)  is_abnormal
+    SIO2(WT%)  TIO2(WT%) ... MNO(WT%)  NA2O(WT%)  is_anomaly
 
 0   53.536000   0.291000 ... 0.083000   0.861000      -1
 
@@ -932,11 +932,11 @@ Successfully store 'Hyper Parameters - Isolation Forest' in 'Hyper Parameters -
 
 [109 rows x 10 columns]
 
-Successfully store 'X Abnormal Detection' in 'X Abnormal Detection.xlsx' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/data.
+Successfully store 'X Anomaly Detection' in 'X Anomaly Detection.xlsx' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/data.
 
 -----* Normal Data *-----
 
-    SIO2(WT%)  TIO2(WT%) ... MNO(WT%)  NA2O(WT%)  is_abnormal
+    SIO2(WT%)  TIO2(WT%) ... MNO(WT%)  NA2O(WT%)  is_anomaly
 
 2   50.873065   0.720622 ... 0.102185   1.920395       1
 
@@ -965,9 +965,9 @@ Successfully store 'X Abnormal Detection' in 'X Abnormal Detection.xlsx' in User
 
 Successfully store 'X Normal' in 'X Normal.xlsx' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/data.
 
------* Abnormal Data *-----
+-----* Anomaly Data *-----
 
-    SIO2(WT%)  TIO2(WT%)  ... MNO(WT%)  NA2O(WT%)      is_abnormal
+    SIO2(WT%)  TIO2(WT%)  ... MNO(WT%)  NA2O(WT%)      is_anomaly
 
 0    53.536000   0.291000 ... 0.083000   0.861000           -1
 
@@ -1035,7 +1035,7 @@ Successfully store 'X Normal' in 'X Normal.xlsx' in Users/geopi/geopi_output/Geo
 
 106  54.200000   0.100000 ... 0.130000   1.430000           -1
 ```
-Successfully store 'X Abnormal' in 'X Abnormal.xlsx' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/data.
+Successfully store 'X Anomaly' in 'X Anomaly.xlsx' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/data.
 
     -----* Model Persistence *-----
     Successfully store 'Isolation Forest' in 'Isolation Forest.pkl' in Users/geopi/geopi_output/GeoPi-Rock Isolation Forest/Algorithm - Test 1/artifacts/model.

docs/source/For User/Model Example/Data_Preprocessing/Data Preprocessing.md

@@ -39,7 +39,7 @@ https://docs.qq.com/document/DQ3BDeHhxRGNzSXZN)
 
 + Data_Decomposition.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1kix82qj5--vhnm8-KhuUBH9dqYH6zcY8/edit?usp=sharing&ouid=110717816678586054594&rtpof=true&sd=true) | [[Tencent Docs]](https://docs.qq.com/document/DQ29oZ0lhUGtZUmdN?&u=6868f96d4a384b309036e04e637e367a)
 
-+  Data_AbnormalDetectioon.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1NqTQZCkv74Sn_iOJOKRc-QnJzpaWmnzC_lET_0ZreiQ/edit?usp=sharing) | [[Tencent Docs]](
++  Data_AnomalyDetection.xlsx [[Google Drive]](https://docs.google.com/spreadsheets/d/1NqTQZCkv74Sn_iOJOKRc-QnJzpaWmnzC_lET_0ZreiQ/edit?usp=sharing) | [[Tencent Docs]](
 https://docs.qq.com/document/DQ2hqQ2N2ZGlOUWlT)