# HG changeset patch
# User rakesh4osdd
# Date 1625035032 0
# Node ID b3c01b7903148a6a0c6913320e465679a410fc15
# Parent  c89ee0059c706c2ce47c691b3f6eced3955b077e
"planemo upload for repository https://github.com/rakesh4osdd/asist/tree/master commit f590c3b1d71a9b8f2030909fa488b4ac0c3caed8"

diff -r c89ee0059c70 -r b3c01b790314 asist_dynamic.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/asist_dynamic.py	Wed Jun 30 06:37:12 2021 +0000
@@ -0,0 +1,217 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1309]:
+
+
+#ASIST program for phenotype based on Antibiotics profile
+# create a profile based on selected antibiotics only
+# rakesh4osdd@gmail.com, 14-June-2021
+
+
+# In[1]:
+
+
+import pandas as pd
+import sys
+import os
+from collections import Counter
+
+
+# In[176]:
+
+
+input_file=sys.argv[1]
+output_file=sys.argv[2]
+#input_file='test-data/asist_input.csv'
+#output_file='test-data/asist_output.csv'
+
+
+# In[177]:
+
+
+# strain_profile to phenotype condition
+def s_phen(sus,res,intm,na,pb_sus):
+    if (sus>0 and res==0 and na>=0):
+        #print('Possible Susceptible')
+        phen='Possible Susceptible'
+    elif (sus>=0 and 3<=res<7 and na>=0 and pb_sus==0):
+        #print('Possible MDR')
+        phen='Possible MDR'
+    elif (sus>=0 and 7<=res<9 and na>=0 and pb_sus==0):
+        #print('Possible XDR')
+        phen='Possible XDR'
+    #special cases
+    elif (sus>=1 and res>0 and na>=0 and pb_sus==1):
+        #print('Possible XDR')
+        phen='Possible XDR'
+    #special cases
+    elif (sus>0 and res==9 and na>=0):
+        #print('Possible XDR')
+        phen='Possible XDR'
+    elif (sus==0 and res==9 and na>=0):
+        #print('Possible TDR')
+        phen='Possible TDR'
+    else:
+        #print('Strain could not be classified')
+        phen='Strain could not be classified ('+ str(intm)+' | ' + str(na) +')'
+    return(phen)
+
+#print(s_phen(1,9,0,0))
+
+
+# In[178]:
+
+
+# define Antibiotic groups as per antibiotic of CLSI breakpoints MIC
+#Aminoglycoside
+cat1=['Amikacin','Tobramycin','Gentamycin','Netilmicin']
+#Beta-lactams- Carbapenems
+cat2=['Imipenem','Meropenam','Doripenem']
+#Fluoroquinolone
+cat3=['Ciprofloxacin','Levofloxacin']
+#Beta-lactam inhibitor
+cat4=['Piperacillin/tazobactam','Ticarcillin/clavulanicacid']
+#Cephalosporin
+cat5=['Cefotaxime','Ceftriaxone','Ceftazidime','Cefepime']
+#Sulfonamides
+cat6=['Trimethoprim/sulfamethoxazole']
+#Penicillins/beta-lactamase
+cat7=['Ampicillin/sulbactam']
+#Polymyxins
+cat8=['Colistin','Polymyxinb']
+#Tetracycline
+cat9=['Tetracycline','Doxicycline','Minocycline']
+
+def s_profiler(pd_series):
+    #print(type(pd_series),'\n', pd_series)
+    #create a dictionary of dataframe series
+    cats={'s1':cat1,'s2':cat2,'s3':cat3,'s4':cat4,'s5':cat5,'s6':cat6,'s7':cat7,'s8':cat8,'s9':cat9}
+    # find the antibiotics name in input series
+    for cat in cats:
+        #print(cats[cat])
+        cats[cat]=pd_series.filter(cats[cat])
+        #print(cats[cat])
+    #define res,sus,intm,na,pb_sus
+    res=0
+    sus=0
+    intm=0
+    na=0
+    pb_sus=0
+    # special case of 'Polymyxin b' for its value
+    if 'Polymyxinb' in pd_series:
+        ctp=cats['s8']['Polymyxinb'].strip().lower()
+        if ctp == 'susceptible':
+            pb_sus=1
+        #print((ctp,p_sus))
+    # check all categories
+    for cat in cats:
+        #ctp=cats['s8'].iloc[i:i+1].stack().value_counts().to_dict()
+        #print(ctp)
+        # Pandas series
+        ct=cats[cat].value_counts().to_dict()
+        #print(ct)
+        # remove whitespace and convert to lowercase words
+        ct =  {k.strip().lower(): v for k, v in ct.items()}
+        #print(ct)
+        k=Counter(ct)
+        #j=Counter(ct)+Counter(j)
+        #print(j)
+        # category wise marking
+        if k['resistant']>=1:
+            res=res+1
+        if k['susceptible']>=1:
+            sus=sus+1
+        if k['intermediate']>=1:
+            intm=intm+1
+        if k['na']>=1:
+            na=na+1
+    #print(sus,res,intm,na,pb_sus)
+    #print(s_phen(sus,res,intm,na,pb_sus))
+    return(s_phen(sus,res,intm,na,pb_sus))
+
+
+# In[179]:
+
+
+#input_file='input2.csv_table.csv'
+#output_file=input_file+'_output.txt'
+strain_profile=pd.read_csv(input_file, sep=',',na_filter=False,skipinitialspace = True)
+
+
+# In[180]:
+
+
+old_strain_name=strain_profile.columns[0]
+new_strain_name=old_strain_name.capitalize().strip().replace(' ', '')
+
+
+# In[181]:
+
+
+# make header capitalization, remove leading,lagging, and multiple whitespace for comparision
+strain_profile.columns=strain_profile.columns.str.capitalize().str.strip().str.replace('\s+', '', regex=True)
+#print(strain_profile.columns)
+#strain_profile.head()
+#strain_profile.columns
+
+
+# In[182]:
+
+
+# add new column in dataframe on second position
+strain_profile.insert(1, 'Strain phenotype','')
+#strain_profile.head()
+
+
+# In[183]:
+
+
+strain_profile['Strain phenotype'] = strain_profile.apply(lambda x: (s_profiler(x)), axis=1)
+
+
+# In[184]:
+
+
+#strain_profile.head()
+
+
+# In[185]:
+
+
+#rename headers for old name
+strain_profile=strain_profile.rename(columns = {new_strain_name:old_strain_name, 'Ticarcillin/clavulanicacid':'Ticarcillin/ clavulanic acid','Piperacillin/tazobactam':'Piperacillin/ tazobactam','Trimethoprim/sulfamethoxazole': 'Trimethoprim/ sulfamethoxazole','Ampicillin/sulbactam':'Ampicillin/ sulbactam', 'Polymyxinb': 'Polymyxin B'} )
+
+
+# In[186]:
+
+
+#strain_profile.columns
+
+
+# In[187]:
+
+
+#strain_profile
+
+
+# In[188]:
+
+
+strain_profile.to_csv(output_file,na_rep='NA',index=False)
+
+
+# In[189]:
+
+
+# Open a file with access mode 'a'
+with open(output_file, "a") as file_object:
+    # Append 'hello' at the end of file
+    file_object.write("Note: \n1. 'MDR': Multidrug-resistant, 'XDR': Extensively drug-resistant, 'TDR':totally drug resistant, NA': Data Not Available.\n2. 'Strain could not be classified' numbers follow the format as ('Number of antibiotics categories count as Intermediate' | 'Number of antibiotics categories count as NA')")
+
+
+# In[ ]:
+
+
+
+
diff -r c89ee0059c70 -r b3c01b790314 test-data/asist_input.csv
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/asist_input.csv	Wed Jun 30 06:37:12 2021 +0000
@@ -0,0 +1,5 @@
+Strain name,Resistance_phenotype,Amikacin,Tobramycin,Gentamycin,Imipenem,Meropenam,Doripenem,Ciprofloxacin,Levofloxacin,Piperacillin/tazobactam,Ticarcillin/clavulanic acid,Cefotaxime,Ceftriaxone,Ceftazidime,Cefepime,Trimethoprim/sulfamethoxazole,Ampicillin/sulbactam,Colistin,polymyxin B,Tetracycline,Doxicycline ,Minocycline
+Strain name,Resistance_phenotype,Aminoglycoside,Aminoglycoside,Aminoglycoside,Beta-lactams-Carbapenems,Beta-lactams-Carbapenems,Carbapenem ,Fluoroquinolone,Fluoroquinolone,Beta-lactam inhibitor,Beta-lactam inhibitor,Cephalosporin,Cephalosporin,Cephalosporin,Cephalosporin,Sulfonamides,Penicillins/beta-lactamase,Polymyxins,Polymyxins,Tetracycline,Tetracycline,Tetracycline
+Acinetobacter baumannii strain FDA-CDC-AR_0288,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant
+Acinetobacter baumannii strain FDA-CDC-AR_0303,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,NA
+Acinetobacter baumannii strain FDA-CDC-AR_0304,,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant
diff -r c89ee0059c70 -r b3c01b790314 test-data/asist_output.csv
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/asist_output.csv	Wed Jun 30 06:37:12 2021 +0000
@@ -0,0 +1,5 @@
+Strain name,Strain phenotype,Resistance_phenotype,Amikacin,Tobramycin,Gentamycin,Imipenem,Meropenam,Doripenem,Ciprofloxacin,Levofloxacin,Piperacillin/ tazobactam,Ticarcillin/ clavulanic acid,Cefotaxime,Ceftriaxone,Ceftazidime,Cefepime,Trimethoprim/ sulfamethoxazole,Ampicillin/ sulbactam,Colistin,Polymyxin B,Tetracycline,Doxicycline,Minocycline
+Strain name,Strain could not be classified,Resistance_phenotype,Aminoglycoside,Aminoglycoside,Aminoglycoside,Beta-lactams-Carbapenems,Beta-lactams-Carbapenems,Carbapenem ,Fluoroquinolone,Fluoroquinolone,Beta-lactam inhibitor,Beta-lactam inhibitor,Cephalosporin,Cephalosporin,Cephalosporin,Cephalosporin,Sulfonamides,Penicillins/beta-lactamase,Polymyxins,Polymyxins,Tetracycline,Tetracycline,Tetracycline
+Acinetobacter baumannii strain FDA-CDC-AR_0288,Possible TDR,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant
+Acinetobacter baumannii strain FDA-CDC-AR_0303,Possible TDR,,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,NA
+Acinetobacter baumannii strain FDA-CDC-AR_0304,Possible TDR,,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,Resistant,NA,Resistant