markup bugfixes to display grammar errors and not display corrected spelling

feature_extractor.py

@@ -205,12 +205,12 @@ class FeatureExtractor(object):
         all_feedback=[]
         for m in xrange(0,len(e_set._text)):
             individual_feedback={'grammar' : "Ok.", 'spelling' : "Ok.", 'topicality' : "Ok.", 'markup_text' : ""}
-            markup_tokens=nltk.word_tokenize(e_set._markup_text)
+            markup_tokens=nltk.word_tokenize(e_set._markup_text[m])
             bad_pos_starts=[z[0] for z in bad_pos_positions[m]]
-            bad_pos_ends=[z[1] for z in bad_pos_positions[m]]
+            bad_pos_ends=[z[1]-1 for z in bad_pos_positions[m]]
             for z in xrange(0,len(markup_tokens)):
                 if z in bad_pos_starts:
-                    markup_tokens[z]=="[[" + markup_tokens[z]
+                    markup_tokens[z]="[[" + markup_tokens[z]
                 elif z in bad_pos_ends:
                     markup_tokens[z]=markup_tokens[z] + "]]"
 
@@ -223,7 +223,8 @@ class FeatureExtractor(object):
                 f_row_prop=f_row_sum/len(e_set._text[m])
                 if f_row_prop<(self._mean_f_prop):
                     individual_feedback['topicality']="Essay may be off topic."
-            individual_feedback['markup_text']=" ".join(markup_tokens)
+            markup_string=" ".join(markup_tokens)
+            individual_feedback['markup_text']=markup_string
             all_feedback.append(individual_feedback)
 
         return all_feedback

tmpfile

-In order to replicate this experiment, I would need to know additional information such as the four different samples that they used (because I could have choosen metal, carbboard and many other sample materials that they didn't use and would get different results. Also I would also need to know the amount of vinegar to pour because this can caute a major change. Lastly, they might want to tell where to sit the samples while they dry for 30 minutes because if they are sitting in room temp. or by a light source makes a difference too.
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+this is a aubsmission with some spelling errors thrown in and grammaris not so great eithwer i dont think its very good .
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util_functions.py

@@ -88,7 +88,7 @@ def spell_correct(string):
         sub_pat = r"\b" + incorrect_words[i] + r"\b"
         sub_comp = re.compile(sub_pat)
         newstring = re.sub(sub_comp, correct_spelling[i], newstring)
-        markup_string=re.sub(sub_comp,".." + correct_spelling[i] + "..", markup_string)
+        markup_string=re.sub(sub_comp," .." + incorrect_words[i] + ".. ", markup_string)
     return newstring,len(incorrect_words),markup_string