release v1.2.2

Hanziwww · Nov 23, 2024 · 3a25c4e · 3a25c4e
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diff --git a/README.md b/README.md
@@ -26,7 +26,7 @@
 </p>
 
 <p align="center">
-    <em>AFusion</em> is a user-friendly graphical interface designed to simplify the process of AlphaFold 3 installation and predictions, making it accessible to users who prefer a GUI over command-line interactions.
+    <em>AFusion</em> is a user-friendly graphical interface designed to simplify the process of AlphaFold 3 installation,  prediction and visualization, making it accessible to users who prefer a GUI over command-line interactions.
 </p>
 
 **[Demo site](https://af3gui.streamlit.app/) (generate input JSON files ONLY)**
@@ -205,8 +205,8 @@ If you encounter any issues during installation or usage, please refer to the re
 
 - [X] ~~📄 **Bulid Documentation:** Tutorial for using the AFusion API in Python scripts for batch predictions.~~
 - [X] ~~♻️ **Refactor Code and Publish to PyPI**: Refactor the project code for improved modularity and maintainability, and publish the latest version to PyPI for easy installation.~~
-- [ ] ~~🔗 **Develop AlphaFold result analysis system**: Design and implement a comprehensive analysis pipeline for AlphaFold prediction results.~~
-    - [ ] Update the system.
+- [X] ~~🔗 **Develop AlphaFold result analysis system**: Design and implement a comprehensive analysis pipeline for AlphaFold prediction results.~~
+    - [X] ~~Update the system.~~
 - [ ] ⚛️ **Preset Common Small Molecules & Metal Ions**: Add a dedicated section for quick access to commonly used small molecules and metal ions.  
 - [ ] 🛠️ **New Tool for Chemical Small Molecules**: Develop a new tool to handle and model chemical small molecules, supporting seamless integration into the prediction pipeline.  
 - [X] ~~🖥️ **Add Console Output**: Implement a backend console for output to track processes and debug more effectively.~~

diff --git a/afusion.egg-info/PKG-INFO b/afusion.egg-info/PKG-INFO
@@ -1,7 +1,7 @@
 Metadata-Version: 2.1
 Name: afusion
-Version: 1.2.0
-Summary: A Streamlit app for running AlphaFold 3 predictions
+Version: 1.2.2
+Summary: AFusion: AlphaFold 3 GUI & Toolkit with Visualization
 Home-page: https://github.com/Hanziwww/AlphaFold3-GUI
 Author: Han Wang
 Author-email: [email protected]
@@ -47,11 +47,13 @@ Requires-Dist: plotly
 </p>
 
 <p align="center">
-    <em>AFusion</em> is a user-friendly graphical interface designed to simplify the process of AlphaFold 3 installation and predictions, making it accessible to users who prefer a GUI over command-line interactions.
+    <em>AFusion</em> is a user-friendly graphical interface designed to simplify the process of AlphaFold 3 installation,  prediction and visualization, making it accessible to users who prefer a GUI over command-line interactions.
 </p>
 
 **[Demo site](https://af3gui.streamlit.app/) (generate input JSON files ONLY)**
 
+[**Usable visualization site**](https://af3vis.streamlit.app/) **(fully usable)**
+
 ## Table of Contents
 
 - [Features](#features)
@@ -224,7 +226,8 @@ If you encounter any issues during installation or usage, please refer to the re
 
 - [X] ~~📄 **Bulid Documentation:** Tutorial for using the AFusion API in Python scripts for batch predictions.~~
 - [X] ~~♻️ **Refactor Code and Publish to PyPI**: Refactor the project code for improved modularity and maintainability, and publish the latest version to PyPI for easy installation.~~
-- [ ] 🔗 **Develop AlphaFold result analysis system**: Design and implement a comprehensive analysis pipeline for AlphaFold prediction results.
+- [X] ~~🔗 **Develop AlphaFold result analysis system**: Design and implement a comprehensive analysis pipeline for AlphaFold prediction results.~~
+    - [X] ~~Update the system.~~
 - [ ] ⚛️ **Preset Common Small Molecules & Metal Ions**: Add a dedicated section for quick access to commonly used small molecules and metal ions.  
 - [ ] 🛠️ **New Tool for Chemical Small Molecules**: Develop a new tool to handle and model chemical small molecules, supporting seamless integration into the prediction pipeline.  
 - [X] ~~🖥️ **Add Console Output**: Implement a backend console for output to track processes and debug more effectively.~~

diff --git a/afusion/app.py b/afusion/app.py
@@ -22,7 +22,7 @@
     collect_ligand_sequence_data
 )
 from afusion.bonds import handle_bond
-from afusion.utils import compress_output_folder
+from afusion.utils import log_to_ga, compress_output_folder
 
 # Import visualization functions
 from afusion.visualization import (
@@ -90,6 +90,10 @@ def get_color_from_bfactor(bfactor):
     return 'grey'  # Default color
 
 def main():
+
+    # Log to Google Analytics when the app starts
+    log_to_ga()
+
     # Set page configuration and theme
     st.set_page_config(
         page_title="AFusion: AlphaFold 3 GUI",
@@ -415,8 +419,11 @@ def find_file_by_suffix(directory_path, suffix):
                 # Load the data
                 structure, cif_content = read_cif_file(required_files["model.cif"])
                 residue_bfactors, ligands = extract_residue_bfactors(structure)
-                pae_matrix = extract_pae_from_json(required_files["confidences.json"])
+                pae_matrix, token_chain_ids = extract_pae_from_json(required_files["confidences.json"])
                 summary_data = extract_summary_confidences(required_files["summary_confidences.json"])
+                chain_ids = list(set(token_chain_ids))
+                chain_ids.sort()  # Sort for consistency
+
                 logger.debug("Successfully loaded data from output folder.")
 
                 # Display the visualizations
@@ -436,10 +443,10 @@ def find_file_by_suffix(directory_path, suffix):
 
                 with col2:
                     # Visualize the PAE matrix
-                    visualize_pae(pae_matrix)
+                    visualize_pae(pae_matrix, token_chain_ids)
 
                 # Display summary data
-                display_summary_data(summary_data)
+                display_summary_data(summary_data, chain_ids)
         else:
             st.error("AlphaFold 3 execution did not complete successfully. Please check the logs.")
             logger.error("AlphaFold 3 execution did not complete successfully.")

diff --git a/afusion/utils.py b/afusion/utils.py
@@ -1,9 +1,58 @@
+# utils.py
+
 import os
-import zipfile
-import io
+import uuid
+import json
+import requests
 from loguru import logger
+import streamlit as st
+
+def log_to_ga():
+    # Replace with your Measurement ID
+    measurement_id = "G-42P6TDX7LH"
+    # Get API secret from environment variable
+    api_secret = "Z-CSzz9hSsK3MSaxJjB8sQ"
+
+    if not api_secret:
+        logger.error("API secret for Google Analytics not found. Please set the GA_API_SECRET environment variable.")
+        return
+
+    url = f"https://www.google-analytics.com/mp/collect?measurement_id={measurement_id}&api_secret={api_secret}"
+
+    # Generate or retrieve a unique client ID for each user session
+    if 'client_id' not in st.session_state:
+        st.session_state['client_id'] = str(uuid.uuid4())
+
+    client_id = st.session_state['client_id']
+    logger.debug(f"Client ID: {client_id}")
+
+    payload = {
+        "client_id": client_id,
+        "events": [{
+            "name": "app_start",
+            "params": {}
+        }]
+    }
+
+    headers = {
+        'Content-Type': 'application/json'
+    }
+
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+        if response.status_code != 204:
+            logger.error(f"Failed to log to Google Analytics: {response.content}")
+        else:
+            logger.info("Successfully logged to Google Analytics")
+    except Exception as e:
+        logger.error(f"Exception occurred while logging to Google Analytics: {e}")
 
 def compress_output_folder(output_folder_path, job_output_folder_name):
+    import os
+    import zipfile
+    import io
+    from loguru import logger
+
     # Create a ZIP file in memory
     zip_buffer = io.BytesIO()
     with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zipf:

diff --git a/afusion/visualization.py b/afusion/visualization.py
@@ -28,8 +28,9 @@ def read_cif_file(file_path):
 def extract_pae_from_json(file_path):
     with open(file_path, 'r') as file:
         data = json.load(file)
-    pae = np.array(data.get("pae", []))
-    return pae
+    pae = np.array(data.get("pae", []), dtype=np.float16)  # Use np.float16
+    token_chain_ids = data.get("token_chain_ids", [])
+    return pae, token_chain_ids
 
 def extract_summary_confidences(file_path):
     with open(file_path, 'r') as file:
@@ -49,8 +50,9 @@ def read_cif_file_obj(file_obj):
 
 def extract_pae_from_json_obj(file_obj):
     data = json.load(file_obj)
-    pae = np.array(data.get("pae", []))
-    return pae
+    pae = np.array(data.get("pae", []), dtype=np.float16)  # Use np.float16
+    token_chain_ids = data.get("token_chain_ids", [])
+    return pae, token_chain_ids
 
 def extract_summary_confidences_obj(file_obj):
     data = json.load(file_obj)
@@ -134,7 +136,7 @@ def visualize_structure(residue_bfactors, ligands, cif_content, background_color
         selection = {
             'chain': ligand['chain_id'],
             'resi': ligand['resseq'],
-            'atom': ligand['atom_name']
+            'atom': ligand['atom_name']  # Corrected line
         }
         style = {'stick': {'color': color}}
         view.addStyle(selection, style)
@@ -170,7 +172,7 @@ def display_visualization_header():
     """
     st.markdown(color_mapping_html, unsafe_allow_html=True)
 
-def visualize_pae(pae_matrix):
+def visualize_pae(pae_matrix, token_chain_ids):
     st.write("### Predicted Aligned Error (PAE)")
     fig = px.imshow(
         pae_matrix,
@@ -180,37 +182,81 @@ def visualize_pae(pae_matrix):
             y="Residue index",
             color="PAE (Å)"
         ),
+        zmin=0.0,
+        zmax=31.75
     )
-    fig.update_layout(
-        margin=dict(l=20, r=20, t=30, b=80),
-        coloraxis_colorbar=dict(
-            orientation='h',
-            yanchor='bottom',
-            y=-0.5,
-            xanchor='center',
-            x=0.5,
-            title_side='bottom'
-        ),
-        xaxis=dict(
-            tickfont=dict(size=12),
-        )
-    )
+    # Draw chain boundaries
+    if token_chain_ids:
+        chain_boundaries = []
+        prev_chain = token_chain_ids[0]
+        for idx, chain_id in enumerate(token_chain_ids):
+            if chain_id != prev_chain:
+                chain_boundaries.append(idx - 0.5)
+                prev_chain = chain_id
+        for boundary in chain_boundaries:
+            fig.add_shape(
+                type="line",
+                x0=boundary,
+                y0=0,
+                x1=boundary,
+                y1=len(token_chain_ids),
+                line=dict(color="red", width=1)
+            )
+            fig.add_shape(
+                type="line",
+                x0=0,
+                y0=boundary,
+                x1=len(token_chain_ids),
+                y1=boundary,
+                line=dict(color="red", width=1)
+            )
     st.plotly_chart(fig, use_container_width=True)
 
-def display_summary_data(summary_data):
+def display_summary_data(summary_data, chain_ids):
     st.write("### Summary of Confidence Metrics")
-    # Convert summary data to DataFrame for better display
-    df = pd.DataFrame(list(summary_data.items()), columns=['Metric', 'Value'])
 
-    # Format arrays for better readability
-    for index, row in df.iterrows():
-        if isinstance(row['Value'], list):
-            df.at[index, 'Value'] = json.dumps(row['Value'], indent=2)
-
-    st.table(df)
+    # Map chain-level metrics to chain IDs
+    chain_metrics = {}
+    for key in ['chain_iptm', 'chain_ptm']:
+        if key in summary_data:
+            values = summary_data[key]
+            if len(values) == len(chain_ids):
+                chain_metrics[key] = dict(zip(chain_ids, values))
+            else:
+                st.warning(f"The number of values in {key} does not match the number of chains.")
+
+    # Display chain-level metrics
+    for key, metrics in chain_metrics.items():
+        st.write(f"#### {key}")
+        df = pd.DataFrame.from_dict(metrics, orient='index', columns=[key])
+        st.table(df.style.set_table_styles(
+            [{'selector': 'th, td', 'props': [('border', '1px solid black')]}]
+        ))
+
+    # Display pair metrics as matrices
+    for key in ['chain_pair_iptm', 'chain_pair_pae_min']:
+        pair_metrics = summary_data.get(key, {})
+        if pair_metrics:
+            st.write(f"#### {key}")
+            if len(pair_metrics) == len(chain_ids):
+                df = pd.DataFrame(pair_metrics, index=chain_ids, columns=chain_ids)
+                st.table(df.style.set_table_styles(
+                    [{'selector': 'th, td', 'props': [('border', '1px solid black')]}]
+                ))
+            else:
+                st.warning(f"The dimensions of {key} do not match the number of chains.")
+
+    # Display other metrics
+    other_metrics = {k: v for k, v in summary_data.items() if k not in ['chain_iptm', 'chain_ptm', 'chain_pair_iptm', 'chain_pair_pae_min']}
+    if other_metrics:
+        st.write("#### Other Metrics")
+        df = pd.DataFrame(list(other_metrics.items()), columns=['Metric', 'Value'])
+        st.table(df.style.set_table_styles(
+            [{'selector': 'th, td', 'props': [('border', '1px solid black')]}]
+        ))
 
 # ========================================
-# Main application
+# Main Application
 # ========================================
 
 def main():
@@ -288,10 +334,14 @@ def main():
             # Read and process files
             structure, cif_content = read_cif_file_obj(model_cif_file)
             residue_bfactors, ligands = extract_residue_bfactors(structure)
-            pae_matrix = extract_pae_from_json_obj(confidences_json_file)
+            pae_matrix, token_chain_ids = extract_pae_from_json_obj(confidences_json_file)
             summary_data = extract_summary_confidences_obj(summary_confidences_file)
             logger.info("Successfully loaded and processed uploaded files.")
 
+            # Get chain ID list
+            chain_ids = list(set(token_chain_ids))
+            chain_ids.sort()  # Sort for consistency
+
             # Display visualization results
             st.markdown('<div id="visualization"></div>', unsafe_allow_html=True)
             st.header("🌟 Visualizations")
@@ -311,11 +361,11 @@ def main():
 
             with col2:
                 # Visualize PAE matrix
-                visualize_pae(pae_matrix)
+                visualize_pae(pae_matrix, token_chain_ids)
 
             # Display summary data
             st.markdown('<div id="summary_metrics"></div>', unsafe_allow_html=True)
-            display_summary_data(summary_data)
+            display_summary_data(summary_data, chain_ids)
 
         except Exception as e:
             st.error(f"An error occurred while processing the files: {e}")

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -7,7 +7,7 @@
 project = 'AFusion'
 copyright = '2024, Hanzi'
 author = 'Hanzi'
-release = '1.2.0'
+release = '1.2.1'
 
 # -- General configuration ---------------------------------------------------
 extensions = [

diff --git a/docs/source/index.md b/docs/source/index.md
@@ -1,15 +1,12 @@
 # 🔬 AFusion: AlphaFold 3 GUI & Toolkit
 
 ## Introduction
-**AFusion** is a user-friendly graphical interface designed to simplify AlphaFold 3 predictions, making advanced protein structure modeling accessible to everyone. Whether you prefer a GUI over command-line interactions or need an API for batch predictions, AFusion has you covered.
+**AFusion** is a user-friendly graphical interface designed to simplify AlphaFold 3 usage, making advanced protein structure modeling accessible to everyone. Whether you prefer a GUI over command-line interactions or need an API for batch predictions, AFusion has you covered.
 
 [**Demo Site**](https://af3gui.streamlit.app/) *(generates input JSON files ONLY)*
 
 ## Features
 
-### **🌟 New Feature!**
-- **AlphaFold 3 Output Analysis System**: Automatically analyze and visualize results with customizable visualizations and generate detailed PDF reports for streamlined insights.
-
 - **🧭 Guided Installation**: GUI-based installer to simplify the installation process, easily set up the application through step-by-step guidance.
 - **✨ Intuitive Interface**: Easily configure job settings, sequences, and execution parameters through a clean and modern GUI.
 - **📋 Entity Management**: Add multiple entities (Protein, RNA, DNA, Ligand) with support for modifications, MSA options, and templates.
@@ -19,6 +16,9 @@
 - **🖥️ Console Output**: Track processes and debug more effectively with backend console output.
 - **🧩 API for Batch Predictions**: Perform batch predictions using the AFusion API in Python scripts.
 
+### **🌟 New Feature!**
+- **AlphaFold 3 Output Analysis System**: Automatically analyze and visualize results with customizable visualizations and generate detailed PDF reports for streamlined insights.
+
 ## Acknowledgements
 
 - **AlphaFold 3**: This GUI is designed to work with [AlphaFold 3](https://github.com/google-deepmind/alphafold3) by DeepMind.

diff --git a/docs/source/release.md b/docs/source/release.md
@@ -1,6 +1,15 @@
 # Release Notes
 
-## v1.2.0 "Visualization & Analysis" (Release Date: December 21, 2024)
+## v1.2.1 "Visualization Optimized" (Release Date: November 23, 2024)
+
+### Improvements
+
+- **Visualization Performance Optimization**: Enhanced the visualization module to improve rendering speed and reduce memory usage, enabling smoother analysis of large AlphaFold 3 output files.
+
+- **Stability Improvements**: Addressed minor bugs and improved the stability of the visualization tools, ensuring a seamless user experience during structure analysis.
+
+
+## v1.2.0 "Visualization & Analysis" (Release Date: November 21, 2024)
 
 ### New Features