From ab1d67f173b06d1d2e3a5956c57e06985d590b76 Mon Sep 17 00:00:00 2001
From: Sanjay Gopala Krishna <ssgg0001@studet.monash.edu>
Date: Fri, 27 Jun 2025 14:50:10 +1000
Subject: [PATCH 1/5] updated new

---
 .vscode/settings.json |  2 +-
 cli/cluster_search.py | 47 ++++++++++++++++++++++++++++++++-----------
 cli/html_config.py    |  7 +++++++
 3 files changed, 43 insertions(+), 13 deletions(-)

diff --git a/.vscode/settings.json b/.vscode/settings.json
index 6f3a291..f673a71 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -1,3 +1,3 @@
 {
-    "liveServer.settings.port": 5501
+    "liveServer.settings.port": 5502
 }
\ No newline at end of file
diff --git a/cli/cluster_search.py b/cli/cluster_search.py
index 51abff3..d7370a2 100644
--- a/cli/cluster_search.py
+++ b/cli/cluster_search.py
@@ -96,7 +96,7 @@ def parse_gibbs_output(self, gibbs_path: str, n_clusters: int) -> pd.DataFrame:
         for c_file in os.listdir(res_path):
             if f'{n_clusters}g.ds' in c_file:
                 file_path = os.path.join(res_path, c_file)
-                df = pd.read_csv(file_path, sep='\s+')
+                df = pd.read_csv(file_path, sep="\s+")
                 # output_path = f'data/sampledata_701014/res_{n_clusters}g.csv'
                 # df.to_csv(output_path, index=False)
                 logging.info(f"Data parsed for No clusters {n_clusters}")
@@ -1540,11 +1540,26 @@ def _create_carousel_for_cluster(self, carousel_id, cluster_num, group_data):
         total_slides = len(group_nums)
 
         # Start building the carousel HTML
+        # Convert cluster_num to words for display
+        def number_to_words(n):
+            words = {
+            1: "One", 2: "Two", 3: "Three", 4: "Four", 5: "Five", 6: "Six",
+            7: "Seven", 8: "Eight", 9: "Nine", 10: "Ten"
+            }
+            return words.get(n, str(n))
+
+        cluster_num_word = number_to_words(int(cluster_num))
         carousel_html = f"""
         <div class="row mt-4 mb-4">
             <div class="col-12">
-                <h2 class="text-center">Cluster {cluster_num}</h2>
-                <div id="{carousel_id}" class="carousel slide" data-ride="carousel" data-interval="false">
+            <div class="d-flex justify-content-between align-items-center">
+                <h2 class="text-center flex-grow-1">{cluster_num_word} cluster output</h2>
+                    <span class="d-inline-block" tabindex="0" data-bs-toggle="popover" data-bs-trigger="hover focus" data-bs-content="Use the left and right arrows to navigate through the cluster presentations.">
+                        <i class="bi bi-info-circle" style="font-size: 1.5rem; color: #0d6efd; cursor: pointer;"></i>
+                    </span>
+            </div>
+ 
+            <div id="{carousel_id}" class="carousel slide" data-ride="carousel" data-interval="false">
         """
 
         # Add indicators
@@ -1599,16 +1614,16 @@ def _create_carousel_for_cluster(self, carousel_id, cluster_num, group_data):
 
         # Add carousel controls
         carousel_html += f"""
-                    </div>
-                    <a class="carousel-control-prev" href="#{carousel_id}" role="button" data-slide="prev">
-                        <span class="carousel-control-prev-icon" aria-hidden="true"></span>
-                        <span class="sr-only">Previous</span>
-                    </a>
-                    <a class="carousel-control-next" href="#{carousel_id}" role="button" data-slide="next">
-                        <span class="carousel-control-next-icon" aria-hidden="true"></span>
-                        <span class="sr-only">Next</span>
-                    </a>
                 </div>
+                <a class="carousel-control-prev" href="#{carousel_id}" role="button" data-slide="prev" style="filter: invert(36%) sepia(97%) saturate(7477%) hue-rotate(202deg) brightness(97%) contrast(101%);">
+                <span class="carousel-control-prev-icon" aria-hidden="true"></span>
+                <span class="sr-only text-dark">Previous</span>
+                </a>
+                <a class="carousel-control-next" href="#{carousel_id}" role="button" data-slide="next" style="filter: invert(36%) sepia(97%) saturate(7477%) hue-rotate(202deg) brightness(97%) contrast(101%);">
+                <span class="carousel-control-next-icon" aria-hidden="true"></span>
+                <span class="sr-only text-dark">Next</span>
+                </a>
+            </div>
             </div>
         </div>
         """
@@ -1742,6 +1757,13 @@ def generate_html_layout(self, correlation_dict, db, gibbs_out, immunolyser=Fals
                 $(targetId).carousel(parseInt(slideIndex));
             });
         });
+        
+                    document.addEventListener('DOMContentLoaded', function () {
+                var popoverTriggerList = [].slice.call(document.querySelectorAll('[data-bs-toggle="popover"]'));
+                popoverTriggerList.forEach(function (popoverTriggerEl) {
+                    new bootstrap.Popover(popoverTriggerEl);
+                });
+            });
         """
         body_end_1 = Template("""
 </div>
@@ -1800,6 +1822,7 @@ def generate_html_layout(self, correlation_dict, db, gibbs_out, immunolyser=Fals
     noImgDivs.forEach(div => {
         div.innerHTML = placeholderSVG; // Add placeholder to each "no-img" div
     });
+    
 });
 </script>
 
diff --git a/cli/html_config.py b/cli/html_config.py
index 9b26a1c..cd78fee 100644
--- a/cli/html_config.py
+++ b/cli/html_config.py
@@ -192,6 +192,7 @@
     </div>
   </footer>
   <script>
+  
   document.addEventListener('DOMContentLoaded', function() {
     const downloadLinks = document.querySelectorAll('.dropdown-item');
 
@@ -218,6 +219,12 @@
     `;
 
     document.getElementById('no-img').innerHTML = placeholderSVG;
+    
+    
+    var popoverTriggerList = [].slice.call(document.querySelectorAll('[data-bs-toggle="popover"]'));
+    popoverTriggerList.forEach(function (popoverTriggerEl) {
+        new bootstrap.Popover(popoverTriggerEl);
+    });
 </script>
 
 <script>

From 17ad739371878f4e402e0fb5e016edcb825fd313 Mon Sep 17 00:00:00 2001
From: Sanjay Gopala Krishna <ssgg0001@studet.monash.edu>
Date: Mon, 30 Jun 2025 16:32:10 +1000
Subject: [PATCH 2/5] updated new

---
 cli/cluster_search.py | 121 +++++++++++++++++++++++++++++++++++++-----
 1 file changed, 107 insertions(+), 14 deletions(-)

diff --git a/cli/cluster_search.py b/cli/cluster_search.py
index d7370a2..1114c4f 100644
--- a/cli/cluster_search.py
+++ b/cli/cluster_search.py
@@ -47,6 +47,8 @@ def __init__(self):
         self.d3js_json = None
         self.db = None  # databse of motif and matrix
         self.treshold_img = False
+        self.gibbs_results = None
+        self.kld_df = None
 
     def generate_unique_random_ids(self, count: int) -> list:
         """
@@ -376,7 +378,49 @@ def compute_correlations(
         self.console.log(
             f"Cluster Search Preprocess completed in {elapsed_time:.2f} seconds."
         )
-
+    def read_KLD_file(self,file_path):
+        """
+        Read & Prase Gibbs gibbs.KLDvsClusters file.
+        Args:
+            file_path (str): The path to the Gibbs gibbs.KLDvsClusters file.
+        Returns:
+            list: A list of tuples containing the cluster number and KLD value.
+        """
+        try:
+            # Initialize an empty dictionary to store data
+            data_dict = {'cluster': []}
+            
+            with open(file_path, 'r') as file:
+                lines = file.readlines()
+                for line in lines[1:]:  # Skip the header line
+                    parts = line.strip().split('\t')
+                    cluster_number = int(parts[0])
+                    kld_values = [float(value) for value in parts[1:]]
+                    
+                    # Ensure the dictionary has enough group columns
+                    for i in range(1, len(kld_values) + 1):
+                        group_key = f'group{i}'
+                        if group_key not in data_dict:
+                            data_dict[group_key] = []
+                    
+                    # Populate the row data
+                    data_dict['cluster'].append(cluster_number)
+                    for i, kld_value in enumerate(kld_values, start=1):
+                        data_dict[f'group{i}'].append(kld_value if kld_value > 0 else 0)
+                    
+                    # Fill remaining groups with zeros if necessary
+                    for j in range(len(kld_values) + 1, len(data_dict) - 1):
+                        data_dict[f'group{j}'].append(0)
+            
+            # Convert the dictionary to a DataFrame
+            df = pd.DataFrame(data_dict)
+            df.loc[:, 'total'] = df.iloc[:, 1:].sum(axis=1)
+            df.reset_index(drop=True, inplace=True)
+            # print(df)
+            return df
+        except Exception as e:
+            print(f"Error reading file: {e}")
+            sys.exit(1)
     def compute_correlations_v2(
         self,
         db: pd.DataFrame,
@@ -397,7 +441,10 @@ def compute_correlations_v2(
         #Update to self
         self.threshold = threshold
         self.treshold_img = treshold_img
-        
+        self.gibbs_results = gibbs_results
+        self.kld_df = self.read_KLD_file(
+            os.path.join(self.gibbs_results, 'images', 'gibbs.KLDvsClusters.tab')
+            )
         gibbs_result_matrix = os.path.join(gibbs_results, "matrices")
         should_process = False
         if os.path.exists(gibbs_result_matrix) and any(".mat" in file for file in os.listdir(gibbs_result_matrix)):
@@ -1151,7 +1198,7 @@ def insert_script_png_json(self, script_data_path, img_fallback_path, div_id):
 
         return script_template.render(script_data_path=script_data_path, img_fallback_path=img_fallback_path, div_id=div_id)
 
-    def render_hla_section(self, hla_name, corr, best_cluster_img, naturally_presented_img):
+    def render_hla_section(self, hla_name, corr, best_cluster_img, naturally_presented_img,kld_clust_group_kld):
         
         if str(self.species).lower() == "human":
             hla_name = f"HLA-{hla_name}"
@@ -1160,7 +1207,7 @@ def render_hla_section(self, hla_name, corr, best_cluster_img, naturally_present
         template = Template('''
         <div class="row" style="border: 2px solid #007bff;">
         <div class="row">
-            <h3 style="text-align: center;">{{ hla_name }}  PCC = {{corr}}</h3>
+            <h3 style="text-align: center;"> Best matched allotype is {{ hla_name }} with PCC = {{corr}}, KLD= {{ kld }} </h3>
         </div>
         <div class="row">
             <div class="col">
@@ -1208,7 +1255,7 @@ def render_hla_section(self, hla_name, corr, best_cluster_img, naturally_present
         </div>
         </div>
         ''')
-        return template.render(hla_name=hla_name, corr=corr, best_cluster_img=best_cluster_img, naturally_presented_img=naturally_presented_img)
+        return template.render(hla_name=hla_name, corr=corr, best_cluster_img=best_cluster_img, naturally_presented_img=naturally_presented_img,kld= kld_clust_group_kld)
 
     def make_datatable(self, correlation_dict):
         df = pd.DataFrame(correlation_dict.items(),
@@ -1219,9 +1266,26 @@ def make_datatable(self, correlation_dict):
         df['HLA'] = df['HLA'].apply(
             lambda x: x.split('/')[-1].replace('.txt', ''))
         df['Correlation'] = df['Correlation'].apply(lambda x: round(x, 2))
+        #Add KLD from kld_clust_group_kld
+        if self.kld_df is not None:
+            try:
+                df['KLD'] = df['Cluster'].apply(
+                    lambda x: self.kld_df.loc[
+                        self.kld_df['cluster'] == int(str(x).split('of')[-1]),
+                        f'group{str(x).split("of")[0]}'
+                    ].values[0] if f'group{str(x).split("of")[0]}' in self.kld_df.columns else None
+                )
+            except KeyError as e:
+                # Handle the case where the key is not found
+                self.console.log(
+                    f"KeyError: The key KLD group was not found in the Corr DataFrame."
+                )
+                df['KLD'] = 'NA'
+        else:
+            df['KLD'] = 'NA'
         df = df.sort_values(by='Correlation', ascending=False)
         df = df.reset_index(drop=True)
-        df = df[['Cluster', 'HLA', 'Correlation']]
+        df = df[['Cluster', 'HLA', 'Correlation', 'KLD']]
         return df
 
     def process_correlation_data(self, df=None):
@@ -1549,16 +1613,27 @@ def number_to_words(n):
             return words.get(n, str(n))
 
         cluster_num_word = number_to_words(int(cluster_num))
+        # KLD = self.kld_df[]
+        if self.kld_df is not None:
+            kld_clust_df = self.kld_df[self.kld_df['cluster'] == cluster_num]
+            if not kld_clust_df.empty:
+                kld = kld_clust_df['total'].values[0]
+        else:
+            kld = None
+        # Determine singular/plural for group(s)
+        group_label = "group" if len(group_nums) == 1 else "groups"
+        group_range = f"{min(group_nums)}" if len(group_nums) == 1 else f"{min(group_nums)} to {max(group_nums)}"
+        cluster_label = f"{cluster_num_word} cluster output" 
+
         carousel_html = f"""
         <div class="row mt-4 mb-4">
             <div class="col-12">
             <div class="d-flex justify-content-between align-items-center">
-                <h2 class="text-center flex-grow-1">{cluster_num_word} cluster output</h2>
-                    <span class="d-inline-block" tabindex="0" data-bs-toggle="popover" data-bs-trigger="hover focus" data-bs-content="Use the left and right arrows to navigate through the cluster presentations.">
-                        <i class="bi bi-info-circle" style="font-size: 1.5rem; color: #0d6efd; cursor: pointer;"></i>
-                    </span>
+            <h2 class="text-center flex-grow-1">{cluster_label} (KLD = {kld}) ({group_range} {group_label}) </h2>
+            <span class="d-inline-block" tabindex="0" data-bs-toggle="popover" data-bs-trigger="hover focus" data-bs-content="Use the left and right arrows to navigate through the cluster presentations.">
+                <i class="bi bi-info-circle" style="font-size: 1.5rem; color: #0d6efd; cursor: pointer;"></i>
+            </span>
             </div>
- 
             <div id="{carousel_id}" class="carousel slide" data-ride="carousel" data-interval="false">
         """
 
@@ -1575,7 +1650,18 @@ def number_to_words(n):
                     </ol>
                     <div class="carousel-inner">
         """
-
+        # Add KLD score if available
+        
+        
+        if self.kld_df is not None:
+            kld_clust_df = self.kld_df[self.kld_df['cluster'] == cluster_num]
+            if not kld_clust_df.empty:
+                kld = kld_clust_df['total'].values[0]
+                self.console.log(f"-------KLD Results for {cluster_num} clusters-------", style="bold green")
+                self.console.log(f"Total KLD score for cluster {cluster_num}: {kld}", style="bold yellow")
+            else:
+                kld_clust_df = None
+                
         # Add carousel items
         for i, group_num in enumerate(group_nums):
             active_class = "active" if i == 0 else ""
@@ -1597,10 +1683,17 @@ def number_to_words(n):
 
             if nat_img and hasattr(self, '_outfolder'):
                 nat_img = str(nat_img).replace(f"{self._outfolder}/", '')
-
+            #find KLD for group 
+            kld_clust_group_kld = kld_clust_df[f'group{group_num}'].values[0] if kld_clust_df is not None and f'group{group_num}' in kld_clust_df.columns else None
+            
+            self.console.log(f"Group {group_num} KLD score for cluster {cluster_num}: {kld_clust_group_kld}", style="bold yellow")
+            # Generate the HLA section for this cluster
+            kld_clust_group_kld = round(kld_clust_group_kld, 2) if isinstance(
+                kld_clust_group_kld, (int, float)) else kld_clust_group_kld
+            
             # Generate the HLA section for this cluster
             hla_section = self.render_hla_section(
-                hla_name, correlation_formatted, gibbs_img, nat_img)
+                hla_name, correlation_formatted, gibbs_img, nat_img,kld_clust_group_kld)
 
             # Create carousel item with the HLA section
             carousel_html += f"""

From 82a4c7816d2e43e84b0453053f17e31c00a08687 Mon Sep 17 00:00:00 2001
From: Sanjay Gopala Krishna <ssgg0001@studet.monash.edu>
Date: Mon, 30 Jun 2025 16:37:40 +1000
Subject: [PATCH 3/5] updated new

---
 cli/cluster_search.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cli/cluster_search.py b/cli/cluster_search.py
index 1114c4f..85a28be 100644
--- a/cli/cluster_search.py
+++ b/cli/cluster_search.py
@@ -1207,7 +1207,7 @@ def render_hla_section(self, hla_name, corr, best_cluster_img, naturally_present
         template = Template('''
         <div class="row" style="border: 2px solid #007bff;">
         <div class="row">
-            <h3 style="text-align: center;"> Best matched allotype is {{ hla_name }} with PCC = {{corr}}, KLD= {{ kld }} </h3>
+            <h4 style="text-align: center;"> Best matched allotype is {{ hla_name }} with PCC = {{corr}} and KLD= {{ kld }} </h4>
         </div>
         <div class="row">
             <div class="col">
@@ -1617,7 +1617,7 @@ def number_to_words(n):
         if self.kld_df is not None:
             kld_clust_df = self.kld_df[self.kld_df['cluster'] == cluster_num]
             if not kld_clust_df.empty:
-                kld = kld_clust_df['total'].values[0]
+                kld = round(kld_clust_df['total'].values[0], 2)
         else:
             kld = None
         # Determine singular/plural for group(s)

From 455665cc24d258544d4dc8235329cf4344225b7f Mon Sep 17 00:00:00 2001
From: Sanjay Gopala Krishna <ssgg0001@studet.monash.edu>
Date: Mon, 30 Jun 2025 16:40:30 +1000
Subject: [PATCH 4/5] updated new

---
 cli/cluster_search.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cli/cluster_search.py b/cli/cluster_search.py
index 85a28be..35d6793 100644
--- a/cli/cluster_search.py
+++ b/cli/cluster_search.py
@@ -1629,7 +1629,7 @@ def number_to_words(n):
         <div class="row mt-4 mb-4">
             <div class="col-12">
             <div class="d-flex justify-content-between align-items-center">
-            <h2 class="text-center flex-grow-1">{cluster_label} (KLD = {kld}) ({group_range} {group_label}) </h2>
+            <h2 class="text-center flex-grow-1">{cluster_label} ({group_range} {group_label}) (KLD = {kld})</h2>
             <span class="d-inline-block" tabindex="0" data-bs-toggle="popover" data-bs-trigger="hover focus" data-bs-content="Use the left and right arrows to navigate through the cluster presentations.">
                 <i class="bi bi-info-circle" style="font-size: 1.5rem; color: #0d6efd; cursor: pointer;"></i>
             </span>

From 19f39ffd6147d296de86e9131aa54599325636c9 Mon Sep 17 00:00:00 2001
From: Sanjay Gopala Krishna <ssgg0001@studet.monash.edu>
Date: Wed, 2 Jul 2025 10:21:38 +1000
Subject: [PATCH 5/5] updated new

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index a04c1f6..546ce88 100644
--- a/setup.py
+++ b/setup.py
@@ -3,7 +3,7 @@
 
 setup(
     name="HLA-PEPCLUST",
-    version="0.1.0-dev",
+    version="1.1.0-dev",
     author="Sanjay Krishna",
     author_email="sanjay.sondekoppagopalakrishna@mail.com",
     packages=find_packages(),