Added a function that checks the automated validation table to a make…

… a revised table

Metallicity_Stack_Commons/valid_table.py

@@ -2,9 +2,9 @@
 import matplotlib.pyplot as plt
 from astropy.io import fits
 from astropy.io import ascii as asc
-from astropy.table import Table
+from astropy.table import Table, Column
 
-from Metallicity_Stack_Commons.column_names import filename_dict, bin_names0
+from Metallicity_Stack_Commons.column_names import filename_dict, bin_names0, remove_from_list
 
 def make_validation_table(fitspath):
     '''
@@ -29,15 +29,15 @@ def make_validation_table(fitspath):
         None
         
     Outputs:
-        fitspath + 'validation.tbl' --> a validation table containing bin IDs;
+        fitspath + 'bin_validation.tbl' --> a validation table containing bin IDs;
                                         number of galaxies in each bin; and 
                                         column indicating  OIII4363 detection/non-detection
                                         OIII4363_Flux_Observed
                                         OIII4363_S/N
     '''
 
     bin_table = asc.read(fitspath + filename_dict['bin_info'])
-    em_table = asc.read(fitspath + filename_dict['bin_fit'])  #this is combine_flux_ascii
+    em_table = asc.read(fitspath + filename_dict['bin_fit']) 
 
     bin_ID = em_table['bin_ID'].data
     raw_OIII4363 = em_table['OIII_4363_Flux_Observed'].data
@@ -73,7 +73,87 @@ def make_validation_table(fitspath):
 
     ver_tab = fitspath+ filename_dict['bin_valid']
     n =('bin_ID','N_stack','Detection', 'OIII_4363_Flux_Observed', 'OIII_4363_S/N')
-    tab1 = Table([bin_ID, N_stack, detection, OIII4363, O_4363_SN], names=n)
+    tab1 = Table([bin_ID, N_stack, detection, OIII4363, O_4363_SN], names = valid_table_names0)   #names=n)
     asc.write(tab1, ver_tab, format='fixed_width_two_line')
 
 
+def compare_to_by_eye(fitspath,dataset):
+    '''
+    Purpose -> This function takes the automated validation table and checks it against 
+               inputted measurement that are determined by eye. These inputted measurements 
+               are in the np.where statements. It outputs a revised validation table based 
+               on the inputted measurements. 
+    
+    Usage -> valid_table.make_validation_table(fitspath, dataset)
+
+    Params:
+        fitspath --> a string of the file path where the input file is and where the output file
+            will be placed
+        dataset  --> a string that is used to determine which eye measurements to use
+    
+    Returns: 
+        None
+        
+    Outputs:
+        fitspath + 'bin_validation_revised.tbl' and '.csv' --> 
+                                        a validation table containing bin IDs;
+                                        number of galaxies in each bin; and 
+                                        column indicating  OIII4363 detection/non-detection
+                                        OIII4363_Flux_Observed
+                                        OIII4363_S/N
+                                        Notes
+
+    '''
+    ver_table = fitspath+ filename_dict['bin_valid']
+    ver_tab = asc.read(ver_table)
+    indicate = ver_tab['Detection']
+    ID = ver_tab['bin_ID']
+
+    #Detections By Eye
+    if dataset== 'Voronoi20': det_4363 = np.where((ID ==0)| (ID ==2)| (ID ==3) | (ID ==5) | (ID==6))[0]
+    if dataset== 'Voronoi14': det_4363 = np.where((ID ==0)| (ID ==7)| (ID ==10) | (ID ==11) | (ID==12))[0]
+    if dataset== 'Voronoi10': det_4363 = np.where((ID ==1)| (ID ==9)| (ID ==18) | (ID ==21))[0]
+    if dataset== 'Grid': det_4363 = np.where((ID ==11)| (ID ==13)| (ID ==19) | (ID ==20) | (ID == 21))[0]
+    if dataset== 'R23_Grid': det_4363 = np.where((ID ==0)| (ID ==4)| (ID ==5) | (ID ==6))[0]
+    if dataset== 'O32_Grid': det_4363 = np.where((ID ==6))[0]
+    if dataset== 'Double_Bin': det_4363 = np.where((ID ==0)| (ID ==1)| (ID ==2) | (ID ==7) | (ID ==9) | (ID ==10) | (ID ==11) | (ID ==13))[0]
+    if dataset== 'n_Bins':
+        det_4363= np.where( (ID ==10) | (ID ==11) |(ID==14) | (ID ==15) | (ID ==20) | (ID==23) | (ID ==26))[0]
+        rlimit = np.where( (ID ==5) | (ID ==7) |(ID==8) | (ID ==13) | (ID ==16) | (ID==17) | (ID ==19)| (ID ==22))[0]
+
+    ######Caroline: Add you conditions here#######
+
+    check_ID = np.zeros(len(ID))
+
+    check_ID[det_4363]=1
+    check_ID[rlimit] =0.5
+
+    for ii in range(len(ID)):
+        if check_ID[ii] == indicate[ii]:
+            print(ID[ii], 'matches with by eye validation')
+        else:
+            print('*****', ID[ii], 'does not match calculated values. Please check!')
+
+    ###This is where I need to add the column for notes
+    if dataset == 'n_Bins':
+        notes = ['N/A','N/A','N/A','N/A','N/A',
+                 'N/A','N/A','Broad features, but reliable OIII5007 and HGAMMA',
+                 'Bad fit, but good OIII5007','N/A',
+                 'N/A','N/A','N/A','N/A','N/A',
+                 'High Temperature','not fit well, but reliable OIII5007 and HGAMMA',
+                 'N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A']
+        note_add = Column(name='Notes', data = notes)
+        ver_tab.add_column(note_add,5)
+
+    #######Caroline: Add your notes column here and copy the note_add and ver_tab.add_column lines to your if statement######
+
+
+    ver_tab.remove_column('Detection')
+
+    detect_add = Column(name='Detections', data =check_ID)
+    ver_tab.add_column(detect_add, 2)
+
+    asc.write(ver_tab, fitspath+ 'bin_validation_revised.tbl',  format = 'fixed_width_two_line') 
+    asc.write(ver_tab, fitspath+ 'bin_validation_revised.csv', format = 'csv')    
+
+