Update README.md

README.md

@@ -1,5 +1,5 @@
 # Limestone
-This project contains several sequence alignment algorithms that can also produce scoring matrices for Needleman-Wunsch, Smith-Waterman, Wagner-Fischer, and Waterman-Smith-Beyer algorithms. 
+This project contains several sequence alignment algorithms that can also produce scoring matrices for Needleman-Wunsch, Smith-Waterman, Wagner-Fischer, Waterman-Smith-Beyer, Wagner-Fischer, Lowrance-Wagner, Longest Common Subsequence, and Shortest Common Supersequence algorithms. 
 
 ***Please ensure that numpy is installed so that this project can work correctly***
 
@@ -42,45 +42,45 @@ This project contains several sequence alignment algorithms that can also produc
 
 **Hamming Distance**
 ```python
-from limestone.editdistance import hammingDist
+from limestone import hamming
 
 qs = "AFTG"
 ss = "ACTG"
 
-print(hammingDist.distance(qs, ss))
+print(hamming.distance(qs, ss))
 # 1
-print(hammingDist.similarity(qs, ss))
-# 3 
-print(hammingDist.binary_distance_array(qs, ss))
-# [1,0,1,1]
-print(hammingDist.binary_similarity_array(qs, ss))
+print(hamming.similarity(qs, ss))
+# 3
+print(hamming.binary_distance_array(qs, ss))
 # [0,1,0,0]
-print(hammingDist.normalized_distance(qs, ss))
+print(hamming.binary_similarity_array(qs, ss))
+# [1,0,1,1]
+print(hamming.normalized_distance(qs, ss))
 # 0.25
-print(hammingDist.normalized_similarity(qs, ss))
+print(hamming.normalized_similarity(qs, ss))
 # 0.75
 ```
 
 **Needleman-Wunsch**
 ```python
-from limestone.editdistance import needlemanWunsch
+from limestone import needlemanWunsch
 
-print(needlemanWunsch.distance("ACTG","FHYU"))
+print(needleman_wunsch.distance("ACTG","FHYU"))
 # 4
-print(needlemanWunsch.distance("ACTG","ACTG"))
+print(needleman_wunsch.distance("ACTG","ACTG"))
 # 0
-print(needlemanWunsch.similarity("ACTG","FHYU"))
+print(needleman_wunsch.similarity("ACTG","FHYU"))
 # 0
-print(needlemanWunsch.similarity("ACTG","ACTG"))
+print(needleman_wunsch.similarity("ACTG","ACTG"))
 # 4
-print(needlemanWunsch.normalized_distance("ACTG","AATG"))
+print(needleman_wunsch.normalized_distance("ACTG","AATG"))
 #0.25
-print(needlemanWunsch.normalized_similarity("ACTG","AATG"))
+print(needleman_wunsch.normalized_similarity("ACTG","AATG"))
 #0.75
-print(needlemanWunsch.align("BA","ABA"))
+print(needleman_wunsch.align("BA","ABA"))
 #-BA
 #ABA
-print(needlemanWunsch.matrix("AFTG","ACTG"))
+print(needleman_wunsch.matrix("AFTG","ACTG"))
 [[0. 2. 4. 6. 8.]
  [2. 0. 2. 4. 6.]
  [4. 2. 1. 3. 5.]
@@ -90,13 +90,17 @@ print(needlemanWunsch.matrix("AFTG","ACTG"))
 
 # Work In Progress
 
--- To be continued
+Jaro and Jaro-Winkler algorithms.
+Importing and parsing FASTA, FASTQ, and PDB files.
 
 # Caveats
 
 Due to the recursive nature of the Hirschberg algorithm, if a distance score or matrix is needed it is best to use the Needleman-Wunsch algorithm instead.
 
-Note that due to the fact that the Hamming distance does not allow for substitutions, insertions, or deletions, the "aligned sequence" that is returned is just the original sequences in a formatted string.
+Note that due to the fact that the Hamming distance does not allow for insertions, or deletions, the "aligned sequence" that is returned is just the original sequences in a formatted string. 
+This is due to the fact that actually aligning the two sequences using this algorithm would just lead to two lines of the query sequence. 
+It should also be noted that the Hamming distance is intended to only be used with sequences of the same length. 
+To compensate for strings of differing lengths, my algorithm adds 1 extra point to the distance for every additional letter in the longer sequence since this can be seen as "swapping" the empty space for a letter or vice versa. However, any distance obtained this way **will not reflect an accurate Hamming distance**.
 
 My Waterman-Smith-Beyer implementation does not always align with that of [Freiburg University](http://rna.informatik.uni-freiburg.de/Teaching/index.jsp?toolName=Waterman-Smith-Beyer), the site I've been using for alignment validation.
 It is possible that their implementation has an issue and not mine but I wanted to mention this here and provide the link to my [StackOverflow](https://bioinformatics.stackexchange.com/questions/22683/waterman-smith-beyer-implementation-in-python) question for the sake of posterity.