Mercurial > repos > jay > pdaug_ml_models

annotate PDAUG_Sequence_Network/PDAUG_Sequence_Network.py @ 0:0973f093d98f draft

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"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
author jay
date Wed, 28 Oct 2020 02:31:40 +0000
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children
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0973f093d98f "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1 import Levenshtein
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2 import matplotlib.pyplot as plt
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3 import networkx as nx
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4 import os
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7 def SeqSimilarityNetwork(InFile, OutFile):
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9 f = open(InFile)
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10 lines = f.readlines()
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12 record = []
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13 seq = []
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15 G = nx.Graph()
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17 for line in lines:
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19 if ">" in line:
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20 record.append(line.strip('\n'))
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21 else:
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22 seq.append(line.strip('\n'))
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24 for x, i in enumerate(seq):
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25 for X, I in enumerate(seq):
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26 L = Levenshtein.ratio(i, I )
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27 if L >= 0.4:
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28 G.add_edge(record[x], record[X], weight=float(Levenshtein.ratio(i, I )))
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30 elarge = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] >= 0.4]
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32 pos = nx.spring_layout(G)
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33 nx.draw_networkx_nodes(G, pos, node_size=10)
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34 nx.draw_networkx_edges(G, pos, edgelist=elarge,width=1)
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35 plt.axis('off')
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37 plt.savefig(OutFile)
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41 if __name__=="__main__":
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43 import argparse
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45 parser = argparse.ArgumentParser()
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47 parser.add_argument("-I", "--InFile", required=True, default=None, help="Path to target tsv file")
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48 parser.add_argument("-O","--OutFile", required=False, help="HTML out file", default="out.png")
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49 args = parser.parse_args()
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51 SeqSimilarityNetwork(args.InFile, args.OutFile)
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