fixed axis lims

app.py

@@ -113,12 +113,14 @@ def pre_render_images(df,input_sent_id):
     ymax,ymin = (max(y_tsne)//yscale_unit+1)*yscale_unit,(min(y_tsne)//yscale_unit-1)*yscale_unit
     color_list = sns.color_palette('flare',n_colors=int(len(df)*1.2))
     sent_list = []
+    fig_list = []
     fig_production = st.progress(0)
     for fig_id,sent_id in enumerate(sent_id_options):
         fig_production.progress(fig_id+1)
-        plot_fig(fig_id,x_tsne,y_tsne,sent_id,[xmin,xmax],[ymin,ymax],color_list)
+        img = plot_fig(df,sent_id,[xmin,xmax],[ymin,ymax],color_list)
         sent_list.append(df.cleaned_sentence.to_list()[sent_id])
-    return sent_list
+        fig_list.append(img)
+    return sent_list,fig_list
 
 
 if __name__=='__main__':
@@ -190,19 +192,19 @@ if __name__=='__main__':
                 x_tsne, y_tsne = df.x_tsne, df.y_tsne
                 xscale_unit = (max(x_tsne)-min(x_tsne))/10
                 yscale_unit = (max(y_tsne)-min(y_tsne))/10
-                xmax,xmin = (max(x_tsne)//xscale_unit+1)*xscale_unit,(min(x_tsne)//xscale_unit-1)*xscale_unit
-                ymax,ymin = (max(y_tsne)//yscale_unit+1)*yscale_unit,(min(y_tsne)//yscale_unit-1)*yscale_unit
+                xlims = [(max(x_tsne)//xscale_unit+1)*xscale_unit,(min(x_tsne)//xscale_unit-1)*xscale_unit]
+                ylims = [(max(y_tsne)//yscale_unit+1)*yscale_unit,(min(y_tsne)//yscale_unit-1)*yscale_unit]
                 color_list = sns.color_palette('flare',n_colors=1200)
                 fig_production = st.progress(0)
 
-                img = plot_fig(df,0,[xmin,xmax],[ymin,ymax],color_list)
+                img = plot_fig(df,0,xlims,ylims,color_list)
                 #img = cv2.imread('figures/0.png')
                 height, width, layers = img.shape
                 size = (width,height)
                 out = cv2.VideoWriter('sampling_video.mp4',cv2.VideoWriter_fourcc(*'H264'), 3, size)
                 for sent_id in range(1000):
                     fig_production.progress((sent_id+1)/1000)
-                    img = plot_fig(df,sent_id,[xmin,xmax],[ymin,ymax],color_list)
+                    img = plot_fig(df,sent_id,xlims,ylims,color_list)
                     #img = cv2.imread(f'figures/{sent_id}.png')
                     out.write(img)
                 out.release()
@@ -223,8 +225,8 @@ if __name__=='__main__':
             x_tsne, y_tsne = df.x_tsne, df.y_tsne
             xscale_unit = (max(x_tsne)-min(x_tsne))/10
             yscale_unit = (max(y_tsne)-min(y_tsne))/10
-            xmax,xmin = (max(x_tsne)//xscale_unit+1)*xscale_unit,(min(x_tsne)//xscale_unit-1)*xscale_unit
-            ymax,ymin = (max(y_tsne)//yscale_unit+1)*yscale_unit,(min(y_tsne)//yscale_unit-1)*yscale_unit
+            xlims = [(max(x_tsne)//xscale_unit+1)*xscale_unit,(min(x_tsne)//xscale_unit-1)*xscale_unit]
+            ylims = [(max(y_tsne)//yscale_unit+1)*yscale_unit,(min(y_tsne)//yscale_unit-1)*yscale_unit]
             color_list = sns.color_palette('flare',n_colors=int(len(df)*1.2))
 
             fig = plt.figure(figsize=(5,5),dpi=200)