create functions for converting sentence index and n_gram index back and forth

src/grammar_checker_google.py

@@ -35,8 +35,9 @@ class GrammarChecker:
             for i_error in sorted(i_errors):
                 error.append(n_grams[1][i_error][0])
             print(f"Error: {' '.join(error)}")
+            self.suggest_correction(n_grams, i_errors)
 
-    def get_google_ngram_prob(self, n_gram):
+    def get_google_ngram_prob(self, n_gram, suggestion=False):
         """ gets probability for given n_gram """
         url = f"https://books.google.com/ngrams/json?content={' '.join(n_gram)}&case_insensitive=true"
         successful = False
@@ -49,6 +50,8 @@ class GrammarChecker:
                 results = json.loads(response.content)
                 if results:
                     max_prob = 0.0
+                    if suggestion:
+                        print(results)
                     for result in results:
                         cur_max_prob = max(results[0]["timeseries"])
                         max_prob = cur_max_prob if cur_max_prob > max_prob else max_prob
@@ -66,7 +69,7 @@ class GrammarChecker:
     def get_prob_of_n_gram(self, n_gram):
         """ calculates probability of n_gram """
         # smallest possible positive float (1e-324 == 0.0)
-        float_min = 1e-100
+        float_min = 1e-6
         # float_min = 1e-323
         # get n_gram probability
         prob = self.get_google_ngram_prob(n_gram)
@@ -78,6 +81,14 @@ class GrammarChecker:
             word_indexes.append(word_indexes[-1]+1)
         return word_indexes
 
+    def get_n_gram_indexes_from_word_index(self, n, n_gram_cnt, word_index):
+        n_gram_indexes = [0] if word_index < n else [word_index-n+1]
+        for i in range(word_index%n if word_index < n else n-1):
+            nxt = n_gram_indexes[-1]+1
+            if nxt < n_gram_cnt:
+                n_gram_indexes.append(nxt)
+        return n_gram_indexes
+
     def find_index_of_error(self, n_grams):
         """ finds index of greatest error in n_grams"""
         # get probabilities for all n_grams
@@ -106,9 +117,34 @@ class GrammarChecker:
             if counter >= max_counter:
                 i_errors.append(index)
                 max_counter = counter
+        # over_threshold = True if (chained_probs)**(1/len(n_grams)) <= self.threshold else False
         return i_errors
 
-        # return i_errors if markov[?] <= self.threshold else None
+    def suggest_correction(self, n_grams, i_errors):
+        print()
+
+        for i_error in i_errors:
+            print(f"i_error: {i_error}")
+            print(n_grams[1][i_error])
+            for n, grams in n_grams.items():
+                # skip unigrams
+                if n == 1:
+                    continue
+                # create asterisk n_grams
+                n_gram_indexes = self.get_n_gram_indexes_from_word_index(n, len(grams), i_error)
+                for i, n_gram_index in enumerate(n_gram_indexes):
+                    pos = i_error-i if i_error < n else n-1-i
+                    tmp = list(grams[n_gram_index])
+                    tmp[pos] = "*"
+                    # create n_gram
+                    construct = " ".join(tmp)
+                    print(construct)
+                    # get suggestions
+                    # self.get_google_ngram_prob(construct, suggestion=True)
+                print()
+            print()
+        print()
+        assert False
 
 
 if __name__ == "__main__":