Update app.py

app.py

@@ -279,7 +279,7 @@ def labres(column_changer):
         sd_dev = 5 #(95% CI esetén)
         goal_zone = (lab_ascus_reference - sd_dev, lab_ascus_reference + sd_dev)
         borderline_zone = [(lab_ascus_reference - 2 * sd_dev, lab_ascus_reference - sd_dev), (lab_ascus_reference + sd_dev, lab_ascus_reference + 2 * sd_dev)]
-        attention_zone = [(lab_ascus_reference - 3 * sd_dev, lab_ascus_reference - 2 * sd_dev), (lab_ascus_reference + 2 * sd_dev, 100)]
+        attention_zone = [(lab_ascus_reference - 3 * sd_dev, 0), (lab_ascus_reference + 2 * sd_dev, 100)]
         
         descript = (f"**Description:** *ASC-US/ASC-H ratio literature reference value 90% / 10%. "
         f"Given our average laboratory Z score of {avg_zscore:.2f}, the laboratory's average ratio is "
@@ -447,7 +447,7 @@ def lab_management(year_slider, column_changer):
     sd_dev = 5 #(95% CI esetén)
     goal_zone = (lab_ascus_reference - sd_dev, lab_ascus_reference + sd_dev)
     borderline_zone = [(lab_ascus_reference - 2 * sd_dev, lab_ascus_reference - sd_dev), (lab_ascus_reference + sd_dev, lab_ascus_reference + 2 * sd_dev)]
-    attention_zone = [(lab_ascus_reference - 3 * sd_dev, lab_ascus_reference - 2 * sd_dev), (lab_ascus_reference + 2 * sd_dev, 100)]
+    attention_zone = [(lab_ascus_reference - 3 * sd_dev, 0), (lab_ascus_reference + 2 * sd_dev, 100)]
     
     scatterdata = df[(df.year == year_slider)&(df.people.str.contains('KGYC|Cyto'))].sort_values(by="people", \
                     ascending=False,key=natsort_keygen()).reset_index(drop=True)
@@ -499,11 +499,12 @@ def lab_management(year_slider, column_changer):
                                                         xlim=(17,100), xticks = [min_x,lab,ref, max_x], rot=45, grid=True, title=column_changer,
                                                         xformatter='%.1f',ylabel='',xlabel='', tools = [hover_cp]).opts(fontsize = pl_title,fontscale=f_scale_lab,shared_axes=False,toolbar=None, default_tools = [])
         asc_us_goal = hv.VSpan(float(goal_zone[0]), float(goal_zone[1])).opts(shared_axes=False,toolbar=None, default_tools = []) 
-        asc_us_bdln = hv.VSpan(float(borderline_zone[1][0]), float(borderline_zone[1][1])).opts(shared_axes=False,toolbar=None, default_tools = [])
+        asc_us_bdln_1 = hv.VSpan(float(borderline_zone[1][0]), float(borderline_zone[1][1])).opts(shared_axes=False,toolbar=None, default_tools = [])
+        asc_us_bdln_2 = hv.VSpan(float(borderline_zone_zone[0][0]), float(borderline_zone[0][1])).opts(shared_axes=False,toolbar=None, default_tools = [])
         asc_us_att_1 = hv.VSpan(float(attention_zone[0][0]), float(attention_zone[0][1])).opts(shared_axes=False,toolbar=None, default_tools = [])
         asc_us_att_2 = hv.VSpan(float(attention_zone[1][0]), float(attention_zone[1][1])).opts(shared_axes=False, toolbar=None, default_tools=[])
         ascus_bg = (asc_us_goal.opts(color='#ACFFA0', alpha = 0.75)* asc_us_att_1.opts(color='#B34D93', alpha = 0.9)* asc_us_att_2.opts(color='#B34D93', alpha = 0.9)*\
-                   asc_us_bdln.opts(color='#6AB35F', alpha = 0.75))
+                   asc_us_bdln_1.opts(color='#6AB35F', alpha = 0.75)* asc_us_bdln_2.opts(color='#6AB35F', alpha = 0.75))
         return (ascus_bg* ref_vline * lab_vline*scatter_plot).opts(shared_axes=False)
     #elif column_changer =='Thyroid AUS Rate(%)':
     #    scatter_plot = scatterdata[scatterdata.people.str.contains('Cytop', na=False)].hvplot.scatter(x=column_changer, y='people', color='black', size=sdot_size,height= sheight,