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@ -1,6 +1,8 @@ |
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using System; |
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using System.Collections.Concurrent; |
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using System.Collections.Generic; |
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using System.Linq; |
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using System.Threading.Tasks; |
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using MarkovGrams.Utilities; |
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using SBRL.Algorithms; |
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@ -57,9 +59,13 @@ namespace MarkovGrams |
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if (!StartOnUppercase) |
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wrandom.SetContents(ngrams); |
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else { |
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Dictionary<string, double> filteredNGrams = new Dictionary<string, double>(); |
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foreach (KeyValuePair<string, double> pair in ngrams.Where((pair) => char.IsUpper(pair.Key[0]))) |
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filteredNGrams.Add(pair.Key, pair.Value); |
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ConcurrentDictionary<string, double> filteredNGrams = new ConcurrentDictionary<string, double>(); |
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Parallel.ForEach(ngrams, (KeyValuePair<string, double> pair) => { |
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if (!char.IsUpper(pair.Key[0])) return; |
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if (!filteredNGrams.TryAdd(pair.Key, pair.Value)) |
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throw new Exception("Error: Couldn't add to uppercase staging n-gram ConcurrentDictionary!"); |
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}); |
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if (filteredNGrams.Count() == 0) |
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throw new Exception($"Error: No valid starting ngrams were found (StartOnUppercase: {StartOnUppercase})."); |
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wrandom.SetContents(filteredNGrams); |
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@ -87,20 +93,24 @@ namespace MarkovGrams |
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{ |
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string result = RandomNgram(); |
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string lastNgram = result; |
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List<int> choiceCounts = new List<int>(); int i = 0; |
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while((Mode == GenerationMode.CharacterLevel ? result.Length : result.Split(' ').Length) < length) |
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ConcurrentBag<int> choiceCounts = new ConcurrentBag<int>(); int i = 0; |
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while((Mode == GenerationMode.CharacterLevel ? result.Length : result.CountCharInstances(" ".ToCharArray()) + 1) < length) |
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{ |
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wrandom.ClearContents(); |
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// The substring that the next ngram in the chain needs to start with
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string nextStartsWith = Mode == GenerationMode.CharacterLevel ? lastNgram.Substring(1) : string.Join(" ", lastNgram.Split(' ').Skip(1)); |
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// Get a list of possible n-grams we could choose from next
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Dictionary<string, double> convNextNgrams = new Dictionary<string, double>(); |
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ngrams.Where(gram_data => gram_data.Key.StartsWith(nextStartsWith)) |
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.ForEach((KeyValuePair<string, double> ngramData) => convNextNgrams.Add(ngramData.Key, ngramData.Value)); |
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ConcurrentDictionary<string, double> convNextNgrams = new ConcurrentDictionary<string, double>(); |
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Parallel.ForEach(ngrams, (KeyValuePair<string, double> ngramData) => { |
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if (!ngramData.Key.StartsWithFast(nextStartsWith)) return; |
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if (!convNextNgrams.TryAdd(ngramData.Key, ngramData.Value)) |
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throw new Exception("Error: Failed to add to staging ngram concurrent dictionary"); |
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}); |
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choiceCounts.Add(convNextNgrams.Count); |
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choiceCounts.Add(convNextNgrams.Count()); |
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// If there aren't any choices left, we can't exactly keep adding to the new string any more :-(
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if(convNextNgrams.Count() == 0) |
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if(convNextNgrams.Count == 0) |
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break; |
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wrandom.SetContents(convNextNgrams); |
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// Pick a random n-gram from the list
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@ -109,7 +119,7 @@ namespace MarkovGrams |
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if (Mode == GenerationMode.CharacterLevel) |
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result += nextNgram[nextNgram.Length - 1]; |
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else |
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result += ' ' + nextNgram.Split(' ').Last(); |
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result += ' ' + nextNgram.Substring(nextNgram.LastIndexOf(' ') + 1); |
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lastNgram = nextNgram; i++; |
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} |
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wrandom.ClearContents(); |
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