Test

src/Packages.py

@@ -26,7 +26,7 @@ from scipy.sparse.csgraph import minimum_spanning_tree
 from scipy.sparse import csgraph
 
 # Modelling
-from juliacall import Main as jl
+#from juliacall import Main as jl
 
 from pinard import utils
 from pinard import preprocessing as pp

src/pages/1-samples_selection.py

@@ -181,14 +181,18 @@ if labels:
             meta['index'] = spectra.index[selected_samples_idx]
             selected_samples_metd.write(meta)
 
-
+############################################################################
     ## Scores
 if not t.empty:
     with scores:
+        fig1, ((ax1, ax2),(ax3,ax4)) = plt.subplots(2,2)
         st.write('Scores plot')
         # scores plot with clustering
         if list(labels) and meta_data.empty:
             fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3, color = labels)
+            sns.scatterplot(data = tcr, x = axis1, y =axis2 , hue = labels, ax = ax1)
+            
+
     
         # scores plot with metadata
         elif len(list(labels)) == 0 and not meta_data.empty:
@@ -196,9 +200,12 @@ if not t.empty:
             col = st.selectbox('Color by:', options= filter)
             if col == 0:
                 fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3)
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , ax = ax1)
+                
             else:
                 fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3, color = list(map(str.lower,meta_data[col])) )
-
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , hue = list(map(str.lower,meta_data[col])), ax = ax1)
+                
         # color with scores and metadata
         elif len(list(labels)) > 0  and not meta_data.empty:
             if clus_method in cluster_methods[1:]:
@@ -210,13 +217,19 @@ if not t.empty:
             col = st.selectbox('Color by:', options= filter)
             if col == "None":
                 fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3)
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , ax = ax1)
             elif col == clus_method:
                 fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3, color = labels)
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , ax = ax1)
             else:
                 fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3, color = list(map(str.lower,meta_data[col])))
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , hue = list(map(str.lower,meta_data[col])), ax = ax1)
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , hue = list(map(str.lower,meta_data[col])), ax = ax2)
+                sns.scatterplot(data = tcr, x = axis1, y =axis2 , hue = list(map(str.lower,meta_data[col])), ax = ax3)
 
         else:
             fig = px.scatter_3d(tcr, x=axis1, y=axis2, z = axis3)
+            sns.scatterplot(data = tcr, x = axis1, y =axis2 , ax = ax1)
         fig.update_traces(marker=dict(size=4))
 
         if selected_samples_idx:
@@ -224,8 +237,10 @@ if not t.empty:
             fig.add_scatter3d(x = tt.loc[:,axis1], y = tt.loc[:,axis2],
                               z = tt.loc[:,axis3], mode ='markers', marker = dict(size = 7, color = 'black'),
                               name = 'selected samples')
+        
+        plt.savefig("./Report/Figures/test.png")
         st.plotly_chart(fig, use_container_width=True)
-
+        
         import plotly.express as px
 
         if labels:
@@ -254,7 +269,29 @@ if not t.empty:
             fig_axe2_axe3.update_traces(marker=dict(size=4))
             fig_axe2_axe3.write_image("./Report/Figures/plot_axe2_axe3.png")
 
+        else :
+
+            fig_axe1_axe2 = px.scatter(tcr, x=axis1, y=axis2, color=labels if list(labels) else None)
+            fig_axe1_axe2.update_layout(title='Axe1-Axe2')
+            fig_axe1_axe2.update_traces(marker=dict(size=4))
+            fig_axe1_axe2.write_image("./Report/Figures/plot_axe1_axe2.png")
+
+
+            # Créer et exporter le graphique Axe1-Axe3 en PNG
+            fig_axe1_axe3 = px.scatter(tcr, x=axis1, y=axis3, color=labels if list(labels) else None)
+            fig_axe1_axe3.update_layout(title='Axe1-Axe3')
+            fig_axe1_axe3.update_traces(marker=dict(size=4))
+            fig_axe1_axe3.write_image("./Report/Figures/plot_axe1_axe3.png")
+
+
+            # Créer et exporter le graphique Axe2-Axe3 en PNG
+            fig_axe2_axe3 = px.scatter(tcr, x=axis2, y=axis3, color=labels if list(labels) else None)
+            fig_axe2_axe3.update_layout(title='Axe2-Axe3')
+            fig_axe2_axe3.update_traces(marker=dict(size=4))
+            fig_axe2_axe3.write_image("./Report/Figures/plot_axe2_axe3.png")            
+
 
+#################################################################
 if not spectra.empty:
     if dim_red_method == dim_red_methods[1]:
 

src/pages/4-inputs.py

 import streamlit as st
 
-
+from Packages import *
+st.set_page_config(page_title="NIRS Utils", page_icon=":goat:", layout="wide",)
+if 'interface' not in st.session_state:
+    st.session_state['interface'] = 'simple'
+from Modules import *
+from Class_Mod.DATA_HANDLING import *
 # HTML for the banner "CEFE - CNRS"
 # bandeau_html = """
 # <div style="width: 100%; background-color: #4682B4; padding: 10px; margin-bottom: 10px;">
@@ -28,7 +33,7 @@ with st.container():
         .stButton>button {
             display: block;
             margin: 0 auto;
-            width: 200px;
+            width: 200px;  
             height: 50px;
             font-size: 16px;
         }