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55 lines
2.1 KiB
Python
55 lines
2.1 KiB
Python
import os, sys, re
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import ete3
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from logger import Logger
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def get_best_clade(params, tree):
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if params.target_taxa_file != None:
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try:
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target_taxa_list = [line.strip() for line in open(PathtoFiles + '/' + target_taxa_list)]
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except (FileNotFoundError, TypeError):
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Logger.Error('The --target_taxa_file could not be found or was incorrectly formatted.')
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if params.at_least_file != None:
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try:
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at_least_list = [line.strip() for line in open(PathtoFiles + '/' + at_least_file)]
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except (FileNotFoundError, TypeError):
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Logger.Error('The --at_least_file could not be found or was incorrectly formatted.')
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else:
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at_least_list = []
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### FROM HERE BELOW IN THIS FUNCTION NEEDS REPLACING WITH ETE3
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forbidden_nodes = [node for node in nodes_to_exclude]
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for node in nodes_to_exclude:
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for num in tree.getNodeNumsAbove(node):
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forbidden_nodes.append(tree.node(num))
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best_node = None
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best_size = 0
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for node in tree.iterNodesNoRoot():
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if(node not in forbidden_nodes):
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leaves = tree.getAllLeafNames(node)
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num = 0.0; dem = 0.0;
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non_minor = []
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for leaf in leaves:
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if(leaf[:2] != target_minor and leaf[:4] != target_minor):
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num += 1.0;
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non_minor.append(leaf[:10])
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if(target_taxa_list == 'na' or target_taxa_list == '' or target_taxa_list == 'NA'):
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n_targets = len(list(dict.fromkeys([tip[:10] for tip in leaves if(tip[:2] == target_clade or tip[:3] == target_clade or tip[:4] == target_clade or tip[:5] == target_clade or tip[:7] == target_clade or tip[:8] == target_clade)])))
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else:
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n_targets = len(list(dict.fromkeys([tip[:10] for tip in leaves if((tip[:2] == target_clade or tip[:3] == target_clade or tip[:4] == target_clade or tip[:5] == target_clade or tip[:7] == target_clade or tip[:8] == target_clade) and (tip[:10] in target_taxa_list or tip[:8] in target_taxa_list))])))
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at_least_taxa = len(list(dict.fromkeys([leaf[:10] for leaf in tree.getAllLeafNames(node) if leaf[:10] in at_least_list])))
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if(num <= cont_num_contams and n_targets > best_size and n_targets >= min_presence and at_least_taxa >= num_at_least):
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best_node = node
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best_size = n_targets
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return best_node |