Mercurial > repos > bgruening > create_tool_recommendation_model

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
author bgruening
date Sun, 16 Oct 2022 11:51:32 +0000
parents f0da532be419
children
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22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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1 """
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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2 Predict tool usage to weigh the predicted tools
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3 """
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f0da532be419 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 5eebc0cb44e71f581d548b7e842002705dd155eb"
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5 import collections
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7 import numpy as np
f0da532be419 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 5eebc0cb44e71f581d548b7e842002705dd155eb"
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8 import utils
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9 from sklearn.model_selection import GridSearchCV
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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10 from sklearn.pipeline import Pipeline
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11 from sklearn.svm import SVR
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22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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14 class ToolPopularity:
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9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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16 def __init__(self):
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17 """ Init method. """
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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18
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9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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19 def extract_tool_usage(self, tool_usage_df, cutoff_date, dictionary):
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22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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20 """
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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21 Extract the tool usage over time for each tool
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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22 """
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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23 tool_usage_dict = dict()
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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24 all_dates = list()
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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25 all_tool_list = list(dictionary.keys())
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9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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26 for index, row in tool_usage_df.iterrows():
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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27 row = row.tolist()
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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28 row = [str(item).strip() for item in row]
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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29 if (row[1] > cutoff_date) is True:
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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30 tool_id = utils.format_tool_id(row[0])
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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31 if tool_id in all_tool_list:
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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32 all_dates.append(row[1])
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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33 if tool_id not in tool_usage_dict:
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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34 tool_usage_dict[tool_id] = dict()
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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35 tool_usage_dict[tool_id][row[1]] = int(float(row[2]))
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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36 else:
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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37 curr_date = row[1]
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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38 # merge the usage of different version of tools into one
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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39 if curr_date in tool_usage_dict[tool_id]:
9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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40 tool_usage_dict[tool_id][curr_date] += int(float(row[2]))
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41 else:
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9ec705bd11cb planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 24bab7a797f53fe4bcc668b18ee0326625486164
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42 tool_usage_dict[tool_id][curr_date] = int(float(row[2]))
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43 # get unique dates
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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44 unique_dates = list(set(all_dates))
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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45 for tool in tool_usage_dict:
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46 usage = tool_usage_dict[tool]
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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47 # extract those dates for which tool's usage is not present in raw data
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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48 dates_not_present = list(set(unique_dates) ^ set(usage.keys()))
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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49 # impute the missing values by 0
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50 for dt in dates_not_present:
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51 tool_usage_dict[tool][dt] = 0
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52 # sort the usage list by date
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53 tool_usage_dict[tool] = collections.OrderedDict(sorted(usage.items()))
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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54 return tool_usage_dict
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55
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56 def learn_tool_popularity(self, x_reshaped, y_reshaped):
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57 """
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58 Fit a curve for the tool usage over time to predict future tool usage
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59 """
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60 epsilon = 0.0
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61 cv = 5
5
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62 s_typ = 'neg_mean_absolute_error'
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63 n_jobs = 4
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64 s_error = 1
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65 tr_score = False
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66 try:
5
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67 pipe = Pipeline(steps=[('regressor', SVR(gamma='scale'))])
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68 param_grid = {
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69 'regressor__kernel': ['rbf', 'poly', 'linear'],
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70 'regressor__degree': [2, 3]
0
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71 }
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72 search = GridSearchCV(pipe, param_grid, cv=cv, scoring=s_typ, n_jobs=n_jobs, error_score=s_error, return_train_score=tr_score)
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73 search.fit(x_reshaped, y_reshaped.ravel())
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74 model = search.best_estimator_
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75 # set the next time point to get prediction for
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76 prediction_point = np.reshape([x_reshaped[-1][0] + 1], (1, 1))
22ebbac136c7 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 7fac577189d01cedd01118a77fc2baaefe7d5cad"
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77 prediction = model.predict(prediction_point)
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78 if prediction < epsilon:
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79 prediction = [epsilon]
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80 return prediction[0]
4
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81 except Exception as e:
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82 print(e)
0
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83 return epsilon
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84
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85 def get_pupularity_prediction(self, tools_usage):
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86 """
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87 Get the popularity prediction for each tool
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88 """
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89 usage_prediction = dict()
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90 for tool_name, usage in tools_usage.items():
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91 y_val = list()
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92 x_val = list()
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93 for x, y in usage.items():
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94 x_val.append(x)
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95 y_val.append(y)
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96 x_pos = np.arange(len(x_val))
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97 x_reshaped = x_pos.reshape(len(x_pos), 1)
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98 y_reshaped = np.reshape(y_val, (len(x_pos), 1))
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99 prediction = np.round(self.learn_tool_popularity(x_reshaped, y_reshaped), 8)
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100 usage_prediction[tool_name] = prediction
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101 return usage_prediction