Update app.py

app.py

@@ -758,6 +758,16 @@ def update_scatter_ct(year_slider,ct_select):
     scatterdata = df[(df.year == year_slider)&(df['people'] == ct_select)]
     if len(scatterdata) > 0:
         labdata = df[df.year == year_slider]
+
+        avg_zscore = zscore_eval.get_group('KGYC')['ASC-US/ASC-H ratio(%)'].mean()
+        lab_ascus_reference = 90.0 - avg_zscore #Végül 95%-os CI-vel alkottam meg a bdl és att zónákat
+        lab_asch_reference = 10.0 + avg_zscore
+        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 - 2 * sd_dev, 0), (lab_ascus_reference + 2 * sd_dev, 100)]
+        
         #ASC/#LSIL
         ref_lsil = df['ASC/LSIL'].iloc[0]
         lab_lsil = labdata.iloc[0]['ASC/LSIL']
@@ -786,11 +796,13 @@ def update_scatter_ct(year_slider,ct_select):
                                                             xformatter='%.0f',xlabel ='', ylabel='', tools = [hover_ascus]).opts(fontsize = pl_title,shared_axes=False,toolbar=None, default_tools = []) 
         ref_ascus_vline = hv.VLine(x=ref_ascus).opts(color='black', alpha = 1).opts(fontscale=f_scale, shared_axes=False,toolbar=None, default_tools = [])
         lab_ascus_vline = hv.VLine(x=lab_ascus).opts(color='#5B91D1', line_dash ='dashed', alpha = 1).opts(shared_axes=False,toolbar=None, default_tools = [])
-        asc_us_goal = hv.VSpan(90, 100).opts(shared_axes=False,toolbar=None, default_tools = [])
-        asc_us_att = hv.VSpan(17, 83).opts(shared_axes=False,toolbar=None, default_tools = [])
-        asc_us_bdln = hv.VSpan(83, 90).opts(shared_axes=False,toolbar=None, default_tools = [])
-        ascus_bg = (asc_us_goal.opts(color='#ACFFA0', alpha = 0.75)*asc_us_bdln.opts(color='#6AB35F', alpha = 0.75)* \
-                    asc_us_att.opts(color='#B34D93', alpha = 0.9))
+        asc_us_goal = hv.VSpan(float(goal_zone[0]), float(goal_zone[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[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_1.opts(color='#6AB35F', alpha = 0.75)* asc_us_bdln_2.opts(color='#6AB35F', alpha = 0.75))
 
         #LSIL, ASC-US, AGC(%)
         ref_agc = df['Abnormal Rate(%)'].iloc[0]