--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/Matrix_Validations.py	Tue Nov 27 14:20:40 2018 -0500
@@ -0,0 +1,180 @@
+'''
+Created on Jun 7, 2017 modified Feb2018
+
+@author: Bob Brown and cjacoby
+'''
+ 
+import sys, traceback, argparse
+import numpy as np
+import os
+from Matrix_Validate_import import reader, Labeler
+
+#Define The Four Arguments Used in the Program
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('input_file_txt', help='tab delimited text file input matrix(include .txt in name)')
+    parser.add_argument('replacement', type=str, help='Choose Replacement for Missing Value. Valid Choices are strings: "Mean" or "Zero"')
+    parser.add_argument('axes', type=str, help='Choose Axes to Normalize On (Either "Row" or "Column"')
+    parser.add_argument('output_file_txt' ,help='tab delimited text file output name (include .txt in name)')
+    args = parser.parse_args()
+    return args
+
+
+#Define Function to Replace Null Values with Row Mean
+def nan_replacer_mean_rows(matrix):
+
+    nonNumCnt= 0
+    nanCnt   = 0   #valid NANs are "NA","N/A","-","?"
+
+    #Loop Replacing all Null Values with Row Mean
+    for i in range(0,len(matrix)):
+        temp_mean = np.nanmean(matrix[i])
+        for j in range(0,len(matrix[0])):
+            #if matrix[i][j] == "NA": #np.isnan(matrix[i][j]) == True:
+            if np.isnan(matrix[i][j]) == True:
+                matrix[i][j] = temp_mean     
+                nanCnt = nanCnt + 1
+    return matrix, nonNumCnt, nanCnt
+
+#Define Function to Replace Null Values with Column Mean
+def nan_replacer_mean_columns(matrix):
+
+    nonNumCnt= 0
+    nanCnt   = 0   #valid NANs are "NA","N/A","-","?"
+    
+    #Loop Replacing all Null Values with Column Mean
+    for i in range(0,len(matrix[0])):
+        col = [row[i] for row in matrix]
+        temp_mean = np.nanmean(col)
+        for j in range(0,len(matrix)):
+            #if matrix[i][j] == "NA": #elif np.isnan(matrix[j][i]) == True:
+            if np.isnan(matrix[j][i]) == True:
+                matrix[j][i] = temp_mean  
+                nanCnt = nanCnt + 1   
+    
+    return matrix, nonNumCnt, nanCnt
+
+#Define Function to Replace Null Values with Zero (axis orientation is irrelevant)
+def nan_replacer_zero(matrix):
+
+    nonNumCnt= 0
+    nanCnt   = 0   #valid NANs are "NA","N/A","-","?"
+    
+    #Loop Replacing all Null Values with Row Range
+    for i in range(0,len(matrix)):
+        for j in range(0,len(matrix[0])):
+            #if matrix[i][j] =="NA":
+            if np.isnan(matrix[i][j]) == True:
+               matrix[i][j] = 0
+
+    return matrix, nonNumCnt, nanCnt
+
+#Define Function to Re-Label Output Matrix
+#!!!! not needed no output matrix from Validate tool
+def OLD_labeler(matrix, og_cols, og_rows, output_file_txt): 
+    #Write Data to Specified Text File Output
+    with open(output_file_txt,'w') as f:
+        f.write("Use original input file for further processing\n")
+    f.close()
+#        f.write("")
+#         for k in range(0,len(og_cols)):
+#                 f.write('\t' + str(og_cols[k]))
+#         f.write('\n')
+#         for i in range(0,len(og_rows)):
+#                 f.write(og_rows[i])
+#                 for j in range(0,len(matrix[0])):
+#                         f.write('\t' + format(matrix[i][j]))
+#                 f.write('\n') 
+    
+#Main Function
+def main():
+    args = get_args()
+    #print(args)
+    #sys.stdout.write(str(args))
+    #sys.stdout.write( '\nValid NAN identifiers are "NA","N/A","-", and "?"')
+    
+    matrix,og_cols,og_rows = reader(args.input_file_txt)
+
+#     if nonNumCnt > 0:
+#         print('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+#         #sys.stderr.write('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+#         if nanCnt > 0:
+#             print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+#         sys.exit(-1)
+#     else:
+#         if nanCnt > 0:
+#             print('\nWARNING Matrix has NO unknown non-numbers in matrix, but contains '+str(nanCnt)+' that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+#         else:
+#             print('Matrix is Good-to-Go -- all numbers in data area. ')
+
+    #with open(args.output_file_txt,'w') as f:
+    #    f.write("Use original input file for further processing\n")
+    #f.close()
+    #sys.exit(0)
+    
+# TODO !!!!!  Below if MDA decides to use it  TURNED OFF FOR NOW
+# TODO !!!!!  Below if MDA decides to use it  TURNED OFF FOR NOW
+
+    if args.replacement == "Mean":
+        if args.axes == "Row":
+            matrix, nonNumCnt, nanCnt = nan_replacer_mean_rows(matrix)
+            Labeler(matrix,og_cols,og_rows,args.output_file_txt)
+            #OLD_labeler(matrix, og_cols, og_rows, args.output_file_txt)
+            #print('Mean,Row')
+            if nonNumCnt > 0:
+                print('ERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+                sys.stderr.write('ERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+                if nanCnt > 0:
+                    print('WARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+                sys.exit(-1)
+            else:
+                if nanCnt > 0:
+                    print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+                else:
+                    print('\nMatrix is Good-to-Go -- all numbers in matrix. ')
+                sys.exit(0)
+        elif args.axes == "Column":
+            matrix, nonNumCnt, nanCnt = nan_replacer_mean_columns(matrix)
+            Labeler(matrix,og_cols,og_rows,args.output_file_txt)
+            #OLD_labeler(matrix, og_cols, og_rows, args.output_file_txt)
+            #print('Mean,Column')
+            if nonNumCnt > 0:
+                print('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+                sys.stderr.write('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+                if nanCnt > 0:
+                    print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+                sys.exit(-1)
+            else:
+                if nanCnt > 0:
+                    print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+                else:
+                    print('\nMatrix is Good-to-Go -- all numbers in matrix. ')
+                sys.exit(0)
+        else:
+            print('Mean, but given Invalid Axis= '+str(args.axes))
+            sys.stderr.write('Mean, but given Invalid Axis= '+str(args.axes))
+    elif args.replacement == "Zero":
+        matrix, nonNumCnt, nanCnt = nan_replacer_zero(matrix)
+        Labeler(matrix,og_cols,og_rows,args.output_file_txt)
+        #OLD_labeler(matrix, og_cols, og_rows, args.output_file_txt)
+        if nonNumCnt > 0:
+            print('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+            sys.stderr.write('\nERROR Matrix has non-numbers that are non-NAN identifiers in matrix. Total and percent unknown strings found = '+str(nonNumCnt)+ ',  %.2f' % (100.0*nonNumCnt/(1.0*len(og_cols)*len(og_rows)))+'%' )
+            if nanCnt > 0:
+                print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+            sys.exit(-1)
+        else:
+            if nanCnt > 0:
+                print('\nWARNING Matrix has '+str(nanCnt)+'  that is  %.2f' % (100.0*nanCnt/(1.0*len(og_cols)*len(og_rows)))+'% known NAN identifiers')
+            else:
+                print('\nMatrix is Good-to-Go -- all numbers in matrix. ')
+            sys.exit(0)
+    else:
+        print('zero, but given Invalid Axis= '+str(args.axes))
+        sys.stderr.write('zero, but given Invalid Axis= '+str(args.axes))
+        sys.exit(-2)
+
+       
+if __name__ == '__main__':
+    main()
+    print("done")