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Book4_Ch01_Python_Codes/Streamlit_Bk4_Ch1_01.py

@@ -21,18 +21,24 @@ with st.sidebar:
     y_feature = st.radio('Vertical axis',
              features)    
 
-# Heatmap
+#%% original data
+
+with st.expander('Original data'):
+    st.write(df)
+    
+
+#%% Heatmap
 with st.expander('Heatmap'):
     fig_1 = px.imshow(df.iloc[:,0:4],
                       color_continuous_scale='RdYlBu_r')
     st.plotly_chart(fig_1)
     
-# 2D scatter plot
+#%% 2D scatter plot
 with st.expander('2D scatter plot'):
     fig_2 = px.scatter(df, x=x_feature, y=y_feature, color="species")
     st.plotly_chart(fig_2)
 
-# 3D scatter plot
+#%% 3D scatter plot
 with st.expander('3D scatter plot'):
     fig_3 = px.scatter_3d(df, 
                           x='sepal_length', 

Book4_Ch02_Python_Codes/Streamlit_Bk4_Ch2_13.py

@@ -41,7 +41,7 @@ b = np.round(b,1)
 
 show_number = False
 with st.sidebar:
-    show_number = st.checkbox('Show values:')
+    show_number = st.checkbox('Display values')
 
 tensor_a_b = a@b.T
 

Book4_Ch03_Python_Codes/Streamlit_Bk4_Ch3_01.py

@@ -37,9 +37,8 @@ fig_1.update_layout(
     margin=dict(
         l=50,
         r=50,
-        b=100,
-        t=100,
-        pad = 4))
+        b=50,
+        t=50))
 
 fig_2 = go.Figure(
     go.Surface(

Book4_Ch04_Python_Codes/Streamlit_Bk4_Ch4_16.py

@@ -116,11 +116,11 @@ fig.add_trace(go.Scatter(x=A_times_square_array[0,:],
 
 fig.add_trace(go.Scatter(x=Txvyv[0], y=Txvyv[1], 
                          mode="lines", line_width=lw,
-                         line_color = 'blue'), 1, 2)
+                         line_color = 'red'), 1, 2)
 
 fig.add_trace(go.Scatter(x=Txhyh[0], y=Txhyh[1], 
                          mode="lines", line_width=lw,
-                         line_color = 'red'), 1, 2)
+                         line_color = 'blue'), 1, 2)
 fig.update_xaxes(range=[-4, 4])
 fig.update_yaxes(range=[-4, 4])
 fig.update_layout(width=800, height=500, showlegend=False, template="none",

Book4_Ch08_Python_Codes/Streamlit_Bk4_Ch8_02.py

@@ -58,7 +58,7 @@ with st.sidebar:
     \sin(\theta) & \cos(\theta)
     \end{bmatrix}''')
     
-    theta = st.slider('Degree',-180, 180, step = 5, value = 0)
+    theta = st.slider('Theta degree: ',-180, 180, step = 5, value = 0)
     
     theta = theta/180*np.pi
 

Book4_Ch08_Python_Codes/Streamlit_Bk4_Ch8_03.py

@@ -61,7 +61,7 @@ with st.sidebar:
     a = st.slider('a',-2.0, 2.0, step = 0.1, value = 1.0)
     b = st.slider('b',-2.0, 2.0, step = 0.1, value = 0.0)  
     c = st.slider('c',-2.0, 2.0, step = 0.1, value = 0.0)  
-    d = st.slider('c',-2.0, 2.0, step = 0.1, value = 1.0) 
+    d = st.slider('d',-2.0, 2.0, step = 0.1, value = 1.0) 
 
 theta = np.pi/6
 A = np.array([[a, b], 

Book4_Ch10_Python_Codes/Streamlit_Bk4_Ch10_01.py

@@ -67,6 +67,9 @@ st.latex(r'G = ' +
          bmatrix(np.round(D,2)) + '@' +
          bmatrix(np.round(V.T,2)))
 
+st.write('Mapped data:')
+st.latex('Z = XV')
+
 #%%
 
 Z = X@V
@@ -79,25 +82,32 @@ df['species'] = df['species'].map(mapping_rule)
 
 #%%
 features = df.columns.to_list()[:-1]
-with st.sidebar:
-    st.write('2D scatter plot')
-    x_feature = st.radio('Horizontal axis',
-             features)
-    y_feature = st.radio('Vertical axis',
-             features)    
 
-# Heatmap
+#%% Table of mapped data
+
+with st.expander('Mapped data'):
+    st.write(df)
+    
+#%% Heatmap
 with st.expander('Heatmap'):
     fig_1 = px.imshow(df.iloc[:,0:4],
                       color_continuous_scale='RdYlBu_r')
     st.plotly_chart(fig_1)
     
-# 2D scatter plot
+#%% 2D scatter plot
+
+with st.sidebar:
+    st.write('2D scatter plot')
+    x_feature = st.radio('Horizontal axis',
+             features)
+    y_feature = st.radio('Vertical axis',
+             features)  
+    
 with st.expander('2D scatter plot'):
     fig_2 = px.scatter(df, x=x_feature, y=y_feature, color="species")
     st.plotly_chart(fig_2)
 
-# 3D scatter plot
+#%% 3D scatter plot
 with st.expander('3D scatter plot'):
     fig_3 = px.scatter_3d(df, 
                           x='PC1', 
@@ -106,7 +116,7 @@ with st.expander('3D scatter plot'):
                   color='species')
     st.plotly_chart(fig_3)
 
-# Pairwise scatter plot
+#%% Pairwise scatter plot
 with st.expander('Pairwise scatter plot'):
     fig_4 = px.scatter_matrix(df, 
                             dimensions=["PC1", 

Book4_Ch13_Python_Codes/Streamlit_Bk4_Ch13_04.py

@@ -64,7 +64,7 @@ df = pd.DataFrame(X, columns=['z1','z2', 'color'])
 
 #%% Scatter
 
-st.latex(bmatrix(A))
+st.latex('A = ' + bmatrix(A))
 
 fig = px.scatter(df, 
                  x="z1", 

Book4_Ch20_Python_Codes/Streamlit_Bk4_Ch20_04.py

@@ -102,7 +102,8 @@ st.latex(bmatrix(Sigma) + '=' +
 fig_surface = go.Figure(go.Surface(
     x = x1,
     y = x2,
-    z = PDF_zz))
+    z = PDF_zz,
+    colorscale= 'RdYlBu_r'))
 fig_surface.update_layout(
     autosize=False,
     width=500,
@@ -115,7 +116,8 @@ fig_contour = go.Figure(
     go.Contour(
         z=PDF_zz,
         x=x1,
-        y=x2
+        y=x2,
+        colorscale= 'RdYlBu_r'
     ))
 
 fig_contour.update_layout(

Book4_Ch21_Python_Codes/Streamlit_Bk4_Ch21_02.py

@@ -82,7 +82,9 @@ ff_x = f_x_fcn(xx1,xx2)
 fig_surface = go.Figure(go.Surface(
     x = x1_,
     y = x2_,
-    z = ff_x))
+    z = ff_x,
+    colorscale= 'RdYlBu_r'))
+
 fig_surface.update_layout(
     autosize=False,
     width=500,
@@ -95,7 +97,8 @@ fig_contour = go.Figure(
     go.Contour(
         z=ff_x,
         x=x1_,
-        y=x2_
+        y=x2_,
+        colorscale= 'RdYlBu_r'
     ))
 
 fig_contour.update_layout(