annotate prepare_data.py @ 1:12764915e1c5 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit edeb85d311990eabd65f3c4576fbeabc6d9165c9"
author bgruening
date Wed, 25 Sep 2019 06:42:40 -0400
parents 9bf25dbe00ad
children 5b3c08710e47
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9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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1 """
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2 Prepare the workflow paths to be used by downstream
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3 machine learning algorithm. The paths are divided
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4 into the test and training sets
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5 """
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7 import os
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8 import collections
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9 import numpy as np
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10 import random
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12 import predict_tool_usage
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14 main_path = os.getcwd()
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17 class PrepareData:
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19 @classmethod
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20 def __init__(self, max_seq_length, test_data_share):
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21 """ Init method. """
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22 self.max_tool_sequence_len = max_seq_length
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23 self.test_share = test_data_share
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25 @classmethod
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26 def process_workflow_paths(self, workflow_paths):
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27 """
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28 Get all the tools and complete set of individual paths for each workflow
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29 """
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30 tokens = list()
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31 raw_paths = workflow_paths
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32 raw_paths = [x.replace("\n", '') for x in raw_paths]
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33 for item in raw_paths:
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34 split_items = item.split(",")
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35 for token in split_items:
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36 if token is not "":
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37 tokens.append(token)
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38 tokens = list(set(tokens))
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39 tokens = np.array(tokens)
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40 tokens = np.reshape(tokens, [-1, ])
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41 return tokens, raw_paths
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42
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43 @classmethod
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44 def create_new_dict(self, new_data_dict):
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45 """
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46 Create new data dictionary
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47 """
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48 reverse_dict = dict((v, k) for k, v in new_data_dict.items())
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49 return new_data_dict, reverse_dict
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50
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51 @classmethod
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52 def assemble_dictionary(self, new_data_dict, old_data_dictionary={}):
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53 """
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54 Create/update tools indices in the forward and backward dictionary
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55 """
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56 new_data_dict, reverse_dict = self.create_new_dict(new_data_dict)
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57 return new_data_dict, reverse_dict
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58
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59 @classmethod
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60 def create_data_dictionary(self, words, old_data_dictionary={}):
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61 """
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62 Create two dictionaries having tools names and their indexes
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63 """
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64 count = collections.Counter(words).most_common()
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65 dictionary = dict()
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66 for word, _ in count:
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67 dictionary[word] = len(dictionary) + 1
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68 dictionary, reverse_dictionary = self.assemble_dictionary(dictionary, old_data_dictionary)
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69 return dictionary, reverse_dictionary
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70
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71 @classmethod
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72 def decompose_paths(self, paths, dictionary):
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73 """
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74 Decompose the paths to variable length sub-paths keeping the first tool fixed
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75 """
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76 sub_paths_pos = list()
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77 for index, item in enumerate(paths):
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78 tools = item.split(",")
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79 len_tools = len(tools)
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80 if len_tools <= self.max_tool_sequence_len:
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81 for window in range(1, len_tools):
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82 sequence = tools[0: window + 1]
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83 tools_pos = [str(dictionary[str(tool_item)]) for tool_item in sequence]
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84 if len(tools_pos) > 1:
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85 sub_paths_pos.append(",".join(tools_pos))
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86 sub_paths_pos = list(set(sub_paths_pos))
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87 return sub_paths_pos
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88
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89 @classmethod
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90 def prepare_paths_labels_dictionary(self, dictionary, reverse_dictionary, paths, compatible_next_tools):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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91 """
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92 Create a dictionary of sequences with their labels for training and test paths
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93 """
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94 paths_labels = dict()
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95 random.shuffle(paths)
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96 for item in paths:
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97 if item and item not in "":
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98 tools = item.split(",")
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99 label = tools[-1]
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100 train_tools = tools[:len(tools) - 1]
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101 last_but_one_name = reverse_dictionary[int(train_tools[-1])]
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102 try:
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103 compatible_tools = compatible_next_tools[last_but_one_name].split(",")
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104 except Exception:
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105 continue
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106 if len(compatible_tools) > 0:
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107 compatible_tools_ids = [str(dictionary[x]) for x in compatible_tools]
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108 compatible_tools_ids.append(label)
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109 composite_labels = ",".join(compatible_tools_ids)
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110 train_tools = ",".join(train_tools)
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111 if train_tools in paths_labels:
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112 paths_labels[train_tools] += "," + composite_labels
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113 else:
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114 paths_labels[train_tools] = composite_labels
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115 for item in paths_labels:
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116 paths_labels[item] = ",".join(list(set(paths_labels[item].split(","))))
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117 return paths_labels
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118
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119 @classmethod
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120 def pad_paths(self, paths_dictionary, num_classes):
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121 """
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122 Add padding to the tools sequences and create multi-hot encoded labels
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123 """
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124 size_data = len(paths_dictionary)
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125 data_mat = np.zeros([size_data, self.max_tool_sequence_len])
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126 label_mat = np.zeros([size_data, num_classes + 1])
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127 train_counter = 0
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128 for train_seq, train_label in list(paths_dictionary.items()):
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129 positions = train_seq.split(",")
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130 start_pos = self.max_tool_sequence_len - len(positions)
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131 for id_pos, pos in enumerate(positions):
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132 data_mat[train_counter][start_pos + id_pos] = int(pos)
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133 for label_item in train_label.split(","):
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134 label_mat[train_counter][int(label_item)] = 1.0
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135 train_counter += 1
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136 return data_mat, label_mat
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137
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138 @classmethod
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139 def split_test_train_data(self, multilabels_paths):
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140 """
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141 Split into test and train data randomly for each run
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142 """
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143 train_dict = dict()
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144 test_dict = dict()
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145 all_paths = multilabels_paths.keys()
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146 random.shuffle(list(all_paths))
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147 split_number = int(self.test_share * len(all_paths))
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148 for index, path in enumerate(list(all_paths)):
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149 if index < split_number:
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150 test_dict[path] = multilabels_paths[path]
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151 else:
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152 train_dict[path] = multilabels_paths[path]
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153 return train_dict, test_dict
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154
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155 @classmethod
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156 def verify_overlap(self, train_paths, test_paths):
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157 """
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158 Verify the overlapping of samples in train and test data
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159 """
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160 intersection = list(set(train_paths).intersection(set(test_paths)))
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161 print("Overlap in train and test: %d" % len(intersection))
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162
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163 @classmethod
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164 def get_predicted_usage(self, data_dictionary, predicted_usage):
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165 """
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166 Get predicted usage for tools
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167 """
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168 usage = dict()
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169 epsilon = 0.0
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170 # index 0 does not belong to any tool
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171 usage[0] = epsilon
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diff changeset
172 for k, v in data_dictionary.items():
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
173 try:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
174 usg = predicted_usage[k]
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
175 if usg < epsilon:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
176 usg = epsilon
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
177 usage[v] = usg
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
178 except Exception:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
179 usage[v] = epsilon
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
180 continue
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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181 return usage
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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182
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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183 @classmethod
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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184 def assign_class_weights(self, n_classes, predicted_usage):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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185 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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186 Compute class weights using usage
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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187 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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188 class_weights = dict()
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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189 class_weights[str(0)] = 0.0
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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190 for key in range(1, n_classes):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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191 u_score = predicted_usage[key]
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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192 if u_score < 1.0:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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193 u_score += 1.0
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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194 class_weights[key] = np.log(u_score)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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195 return class_weights
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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196
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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197 @classmethod
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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198 def get_sample_weights(self, train_data, reverse_dictionary, paths_frequency):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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199 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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200 Compute the frequency of paths in training data
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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201 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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202 path_weights = np.zeros(len(train_data))
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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203 for path_index, path in enumerate(train_data):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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204 sample_pos = np.where(path > 0)[0]
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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205 sample_tool_pos = path[sample_pos[0]:]
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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206 path_name = ",".join([reverse_dictionary[int(tool_pos)] for tool_pos in sample_tool_pos])
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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207 try:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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208 path_weights[path_index] = int(paths_frequency[path_name])
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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209 except Exception:
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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210 path_weights[path_index] = 1
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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211 return path_weights
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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212
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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213 @classmethod
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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214 def get_data_labels_matrices(self, workflow_paths, tool_usage_path, cutoff_date, compatible_next_tools, old_data_dictionary={}):
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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215 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
216 Convert the training and test paths into corresponding numpy matrices
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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217 """
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
218 processed_data, raw_paths = self.process_workflow_paths(workflow_paths)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
219 dictionary, reverse_dictionary = self.create_data_dictionary(processed_data, old_data_dictionary)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
220 num_classes = len(dictionary)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
221
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
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222 print("Raw paths: %d" % len(raw_paths))
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
223 random.shuffle(raw_paths)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
224
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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225 print("Decomposing paths...")
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
226 all_unique_paths = self.decompose_paths(raw_paths, dictionary)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
227 random.shuffle(all_unique_paths)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
228
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
229 print("Creating dictionaries...")
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
230 multilabels_paths = self.prepare_paths_labels_dictionary(dictionary, reverse_dictionary, all_unique_paths, compatible_next_tools)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
231
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
232 print("Complete data: %d" % len(multilabels_paths))
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
233 train_paths_dict, test_paths_dict = self.split_test_train_data(multilabels_paths)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
234
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
235 print("Train data: %d" % len(train_paths_dict))
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
236 print("Test data: %d" % len(test_paths_dict))
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
237
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
238 test_data, test_labels = self.pad_paths(test_paths_dict, num_classes)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
239 train_data, train_labels = self.pad_paths(train_paths_dict, num_classes)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
240
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
241 # Predict tools usage
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
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diff changeset
242 print("Predicting tools' usage...")
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
243 usage_pred = predict_tool_usage.ToolPopularity()
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
244 usage = usage_pred.extract_tool_usage(tool_usage_path, cutoff_date, dictionary)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
245 tool_usage_prediction = usage_pred.get_pupularity_prediction(usage)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
246 tool_predicted_usage = self.get_predicted_usage(dictionary, tool_usage_prediction)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
247
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
248 # get class weights using the predicted usage for each tool
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
249 class_weights = self.assign_class_weights(train_labels.shape[1], tool_predicted_usage)
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
250
9bf25dbe00ad "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
bgruening
parents:
diff changeset
251 return train_data, train_labels, test_data, test_labels, dictionary, reverse_dictionary, class_weights, tool_predicted_usage