Mercurial > repos > bgruening > create_tool_recommendation_model
changeset 5:4f7e6612906b draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit 5eebc0cb44e71f581d548b7e842002705dd155eb"
| author | bgruening |
|---|---|
| date | Fri, 06 May 2022 09:05:18 +0000 |
| parents | afec8c595124 |
| children | e94dc7945639 |
| files | create_tool_recommendation_model.xml extract_workflow_connections.py main.py optimise_hyperparameters.py predict_tool_usage.py prepare_data.py test-data/test_tool_usage test-data/test_workflows utils.py |
| diffstat | 9 files changed, 1084 insertions(+), 1661 deletions(-) [+] |
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--- a/create_tool_recommendation_model.xml Tue Jul 07 03:25:49 2020 -0400 +++ b/create_tool_recommendation_model.xml Fri May 06 09:05:18 2022 +0000 @@ -1,13 +1,13 @@ -<tool id="create_tool_recommendation_model" name="Create a model to recommend tools" version="0.0.3"> +<tool id="create_tool_recommendation_model" name="Create a model to recommend tools" version="0.0.4"> <description>using deep learning</description> <requirements> - <requirement type="package" version="3.6">python</requirement> - <requirement type="package" version="1.13.1">tensorflow</requirement> - <requirement type="package" version="2.3.0">keras</requirement> - <requirement type="package" version="0.21.3">scikit-learn</requirement> - <requirement type="package" version="2.9.0">h5py</requirement> + <requirement type="package" version="3.9.7">python</requirement> + <requirement type="package" version="2.7.0">tensorflow</requirement> + <requirement type="package" version="2.7.0">keras</requirement> + <requirement type="package" version="1.0.2">scikit-learn</requirement> + <requirement type="package" version="3.6.0">h5py</requirement> <requirement type="package" version="1.0.4">csvkit</requirement> - <requirement type="package" version="0.1.2">hyperopt</requirement> + <requirement type="package" version="0.2.5">hyperopt</requirement> </requirements> <version_command>echo "@VERSION@"</version_command> <command detect_errors="aggressive">
--- a/extract_workflow_connections.py Tue Jul 07 03:25:49 2020 -0400 +++ b/extract_workflow_connections.py Fri May 06 09:05:18 2022 +0000 @@ -10,7 +10,6 @@ class ExtractWorkflowConnections: - def __init__(self): """ Init method. """ @@ -33,12 +32,12 @@ workflow_paths = list() unique_paths = dict() standard_connections = dict() - with open(raw_file_path, 'rt') as workflow_connections_file: - workflow_connections = csv.reader(workflow_connections_file, delimiter='\t') + with open(raw_file_path, "rt") as workflow_connections_file: + workflow_connections = csv.reader(workflow_connections_file, delimiter="\t") for index, row in enumerate(workflow_connections): wf_id = str(row[0]) - in_tool = row[3] - out_tool = row[6] + in_tool = row[3].strip() + out_tool = row[6].strip() if wf_id not in workflows: workflows[wf_id] = list() if out_tool and in_tool and out_tool != in_tool: @@ -144,7 +143,9 @@ if end in graph: for node in graph[end]: if node not in path: - new_tools_paths = self.find_tool_paths_workflow(graph, start, node, path) + new_tools_paths = self.find_tool_paths_workflow( + graph, start, node, path + ) for tool_path in new_tools_paths: path_list.append(tool_path) return path_list
--- a/main.py Tue Jul 07 03:25:49 2020 -0400 +++ b/main.py Fri May 06 09:05:18 2022 +0000 @@ -3,35 +3,36 @@ using machine learning (recurrent neural network) """ -import numpy as np import argparse import time -# machine learning library -import tensorflow as tf -from keras import backend as K +import extract_workflow_connections import keras.callbacks as callbacks - -import extract_workflow_connections +import numpy as np +import optimise_hyperparameters import prepare_data -import optimise_hyperparameters import utils class PredictTool: - def __init__(self, num_cpus): """ Init method. """ - # set the number of cpus - cpu_config = tf.ConfigProto( - device_count={"CPU": num_cpus}, - intra_op_parallelism_threads=num_cpus, - inter_op_parallelism_threads=num_cpus, - allow_soft_placement=True - ) - K.set_session(tf.Session(config=cpu_config)) - def find_train_best_network(self, network_config, reverse_dictionary, train_data, train_labels, test_data, test_labels, n_epochs, class_weights, usage_pred, standard_connections, tool_freq, tool_tr_samples): + def find_train_best_network( + self, + network_config, + reverse_dictionary, + train_data, + train_labels, + test_data, + test_labels, + n_epochs, + class_weights, + usage_pred, + standard_connections, + tool_freq, + tool_tr_samples, + ): """ Define recurrent neural network and train sequential data """ @@ -40,11 +41,34 @@ print("Start hyperparameter optimisation...") hyper_opt = optimise_hyperparameters.HyperparameterOptimisation() - best_params, best_model = hyper_opt.train_model(network_config, reverse_dictionary, train_data, train_labels, test_data, test_labels, tool_tr_samples, class_weights) + best_params, best_model = hyper_opt.train_model( + network_config, + reverse_dictionary, + train_data, + train_labels, + test_data, + test_labels, + tool_tr_samples, + class_weights, + ) # define callbacks - early_stopping = callbacks.EarlyStopping(monitor='loss', mode='min', verbose=1, min_delta=1e-1, restore_best_weights=True) - predict_callback_test = PredictCallback(test_data, test_labels, reverse_dictionary, n_epochs, usage_pred, standard_connections, lowest_tool_ids) + early_stopping = callbacks.EarlyStopping( + monitor="loss", + mode="min", + verbose=1, + min_delta=1e-1, + restore_best_weights=True, + ) + predict_callback_test = PredictCallback( + test_data, + test_labels, + reverse_dictionary, + n_epochs, + usage_pred, + standard_connections, + lowest_tool_ids, + ) callbacks_list = [predict_callback_test, early_stopping] batch_size = int(best_params["batch_size"]) @@ -57,21 +81,29 @@ train_labels, batch_size, tool_tr_samples, - reverse_dictionary + reverse_dictionary, ), steps_per_epoch=len(train_data) // batch_size, epochs=n_epochs, callbacks=callbacks_list, validation_data=(test_data, test_labels), verbose=2, - shuffle=True + shuffle=True, ) - train_performance["validation_loss"] = np.array(trained_model.history["val_loss"]) + train_performance["validation_loss"] = np.array( + trained_model.history["val_loss"] + ) train_performance["precision"] = predict_callback_test.precision train_performance["usage_weights"] = predict_callback_test.usage_weights - train_performance["published_precision"] = predict_callback_test.published_precision - train_performance["lowest_pub_precision"] = predict_callback_test.lowest_pub_precision - train_performance["lowest_norm_precision"] = predict_callback_test.lowest_norm_precision + train_performance[ + "published_precision" + ] = predict_callback_test.published_precision + train_performance[ + "lowest_pub_precision" + ] = predict_callback_test.lowest_pub_precision + train_performance[ + "lowest_norm_precision" + ] = predict_callback_test.lowest_norm_precision train_performance["train_loss"] = np.array(trained_model.history["loss"]) train_performance["model"] = best_model train_performance["best_parameters"] = best_params @@ -79,7 +111,16 @@ class PredictCallback(callbacks.Callback): - def __init__(self, test_data, test_labels, reverse_data_dictionary, n_epochs, usg_scores, standard_connections, lowest_tool_ids): + def __init__( + self, + test_data, + test_labels, + reverse_data_dictionary, + n_epochs, + usg_scores, + standard_connections, + lowest_tool_ids, + ): self.test_data = test_data self.test_labels = test_labels self.reverse_data_dictionary = reverse_data_dictionary @@ -98,7 +139,22 @@ Compute absolute and compatible precision for test data """ if len(self.test_data) > 0: - usage_weights, precision, precision_pub, low_pub_prec, low_norm_prec, low_num = utils.verify_model(self.model, self.test_data, self.test_labels, self.reverse_data_dictionary, self.pred_usage_scores, self.standard_connections, self.lowest_tool_ids) + ( + usage_weights, + precision, + precision_pub, + low_pub_prec, + low_norm_prec, + low_num, + ) = utils.verify_model( + self.model, + self.test_data, + self.test_labels, + self.reverse_data_dictionary, + self.pred_usage_scores, + self.standard_connections, + self.lowest_tool_ids, + ) self.precision.append(precision) self.usage_weights.append(usage_weights) self.published_precision.append(precision_pub) @@ -109,31 +165,96 @@ print("Epoch %d published precision: %s" % (epoch + 1, precision_pub)) print("Epoch %d lowest published precision: %s" % (epoch + 1, low_pub_prec)) print("Epoch %d lowest normal precision: %s" % (epoch + 1, low_norm_prec)) - print("Epoch %d number of test samples with lowest tool ids: %s" % (epoch + 1, low_num)) + print( + "Epoch %d number of test samples with lowest tool ids: %s" + % (epoch + 1, low_num) + ) if __name__ == "__main__": start_time = time.time() arg_parser = argparse.ArgumentParser() - arg_parser.add_argument("-wf", "--workflow_file", required=True, help="workflows tabular file") - arg_parser.add_argument("-tu", "--tool_usage_file", required=True, help="tool usage file") - arg_parser.add_argument("-om", "--output_model", required=True, help="trained model file") + arg_parser.add_argument( + "-wf", "--workflow_file", required=True, help="workflows tabular file" + ) + arg_parser.add_argument( + "-tu", "--tool_usage_file", required=True, help="tool usage file" + ) + arg_parser.add_argument( + "-om", "--output_model", required=True, help="trained model file" + ) # data parameters - arg_parser.add_argument("-cd", "--cutoff_date", required=True, help="earliest date for taking tool usage") - arg_parser.add_argument("-pl", "--maximum_path_length", required=True, help="maximum length of tool path") - arg_parser.add_argument("-ep", "--n_epochs", required=True, help="number of iterations to run to create model") - arg_parser.add_argument("-oe", "--optimize_n_epochs", required=True, help="number of iterations to run to find best model parameters") - arg_parser.add_argument("-me", "--max_evals", required=True, help="maximum number of configuration evaluations") - arg_parser.add_argument("-ts", "--test_share", required=True, help="share of data to be used for testing") + arg_parser.add_argument( + "-cd", + "--cutoff_date", + required=True, + help="earliest date for taking tool usage", + ) + arg_parser.add_argument( + "-pl", + "--maximum_path_length", + required=True, + help="maximum length of tool path", + ) + arg_parser.add_argument( + "-ep", + "--n_epochs", + required=True, + help="number of iterations to run to create model", + ) + arg_parser.add_argument( + "-oe", + "--optimize_n_epochs", + required=True, + help="number of iterations to run to find best model parameters", + ) + arg_parser.add_argument( + "-me", + "--max_evals", + required=True, + help="maximum number of configuration evaluations", + ) + arg_parser.add_argument( + "-ts", + "--test_share", + required=True, + help="share of data to be used for testing", + ) # neural network parameters - arg_parser.add_argument("-bs", "--batch_size", required=True, help="size of the tranining batch i.e. the number of samples per batch") - arg_parser.add_argument("-ut", "--units", required=True, help="number of hidden recurrent units") - arg_parser.add_argument("-es", "--embedding_size", required=True, help="size of the fixed vector learned for each tool") - arg_parser.add_argument("-dt", "--dropout", required=True, help="percentage of neurons to be dropped") - arg_parser.add_argument("-sd", "--spatial_dropout", required=True, help="1d dropout used for embedding layer") - arg_parser.add_argument("-rd", "--recurrent_dropout", required=True, help="dropout for the recurrent layers") - arg_parser.add_argument("-lr", "--learning_rate", required=True, help="learning rate") + arg_parser.add_argument( + "-bs", + "--batch_size", + required=True, + help="size of the tranining batch i.e. the number of samples per batch", + ) + arg_parser.add_argument( + "-ut", "--units", required=True, help="number of hidden recurrent units" + ) + arg_parser.add_argument( + "-es", + "--embedding_size", + required=True, + help="size of the fixed vector learned for each tool", + ) + arg_parser.add_argument( + "-dt", "--dropout", required=True, help="percentage of neurons to be dropped" + ) + arg_parser.add_argument( + "-sd", + "--spatial_dropout", + required=True, + help="1d dropout used for embedding layer", + ) + arg_parser.add_argument( + "-rd", + "--recurrent_dropout", + required=True, + help="dropout for the recurrent layers", + ) + arg_parser.add_argument( + "-lr", "--learning_rate", required=True, help="learning rate" + ) # get argument values args = vars(arg_parser.parse_args()) @@ -156,33 +277,74 @@ num_cpus = 16 config = { - 'cutoff_date': cutoff_date, - 'maximum_path_length': maximum_path_length, - 'n_epochs': n_epochs, - 'optimize_n_epochs': optimize_n_epochs, - 'max_evals': max_evals, - 'test_share': test_share, - 'batch_size': batch_size, - 'units': units, - 'embedding_size': embedding_size, - 'dropout': dropout, - 'spatial_dropout': spatial_dropout, - 'recurrent_dropout': recurrent_dropout, - 'learning_rate': learning_rate + "cutoff_date": cutoff_date, + "maximum_path_length": maximum_path_length, + "n_epochs": n_epochs, + "optimize_n_epochs": optimize_n_epochs, + "max_evals": max_evals, + "test_share": test_share, + "batch_size": batch_size, + "units": units, + "embedding_size": embedding_size, + "dropout": dropout, + "spatial_dropout": spatial_dropout, + "recurrent_dropout": recurrent_dropout, + "learning_rate": learning_rate, } # Extract and process workflows connections = extract_workflow_connections.ExtractWorkflowConnections() - workflow_paths, compatible_next_tools, standard_connections = connections.read_tabular_file(workflows_path) + ( + workflow_paths, + compatible_next_tools, + standard_connections, + ) = connections.read_tabular_file(workflows_path) # Process the paths from workflows print("Dividing data...") data = prepare_data.PrepareData(maximum_path_length, test_share) - train_data, train_labels, test_data, test_labels, data_dictionary, reverse_dictionary, class_weights, usage_pred, train_tool_freq, tool_tr_samples = data.get_data_labels_matrices(workflow_paths, tool_usage_path, cutoff_date, compatible_next_tools, standard_connections) + ( + train_data, + train_labels, + test_data, + test_labels, + data_dictionary, + reverse_dictionary, + class_weights, + usage_pred, + train_tool_freq, + tool_tr_samples, + ) = data.get_data_labels_matrices( + workflow_paths, + tool_usage_path, + cutoff_date, + compatible_next_tools, + standard_connections, + ) # find the best model and start training predict_tool = PredictTool(num_cpus) # start training with weighted classes print("Training with weighted classes and samples ...") - results_weighted = predict_tool.find_train_best_network(config, reverse_dictionary, train_data, train_labels, test_data, test_labels, n_epochs, class_weights, usage_pred, standard_connections, train_tool_freq, tool_tr_samples) - utils.save_model(results_weighted, data_dictionary, compatible_next_tools, trained_model_path, class_weights, standard_connections) + results_weighted = predict_tool.find_train_best_network( + config, + reverse_dictionary, + train_data, + train_labels, + test_data, + test_labels, + n_epochs, + class_weights, + usage_pred, + standard_connections, + train_tool_freq, + tool_tr_samples, + ) + utils.save_model( + results_weighted, + data_dictionary, + compatible_next_tools, + trained_model_path, + class_weights, + standard_connections, + ) end_time = time.time() print("Program finished in %s seconds" % str(end_time - start_time))
--- a/optimise_hyperparameters.py Tue Jul 07 03:25:49 2020 -0400 +++ b/optimise_hyperparameters.py Fri May 06 09:05:18 2022 +0000 @@ -3,24 +3,29 @@ """ import numpy as np -from hyperopt import fmin, tpe, hp, STATUS_OK, Trials - -from keras.models import Sequential -from keras.layers import Dense, GRU, Dropout -from keras.layers.embeddings import Embedding -from keras.layers.core import SpatialDropout1D -from keras.optimizers import RMSprop -from keras.callbacks import EarlyStopping - import utils +from hyperopt import fmin, hp, STATUS_OK, tpe, Trials +from tensorflow.keras.callbacks import EarlyStopping +from tensorflow.keras.layers import Dense, Dropout, Embedding, GRU, SpatialDropout1D +from tensorflow.keras.models import Sequential +from tensorflow.keras.optimizers import RMSprop class HyperparameterOptimisation: - def __init__(self): """ Init method. """ - def train_model(self, config, reverse_dictionary, train_data, train_labels, test_data, test_labels, tool_tr_samples, class_weights): + def train_model( + self, + config, + reverse_dictionary, + train_data, + train_labels, + test_data, + test_labels, + tool_tr_samples, + class_weights, + ): """ Train a model and report accuracy """ @@ -40,52 +45,101 @@ # get dimensions dimensions = len(reverse_dictionary) + 1 best_model_params = dict() - early_stopping = EarlyStopping(monitor='val_loss', mode='min', verbose=1, min_delta=1e-1, restore_best_weights=True) + early_stopping = EarlyStopping( + monitor="val_loss", + mode="min", + verbose=1, + min_delta=1e-1, + restore_best_weights=True, + ) # specify the search space for finding the best combination of parameters using Bayesian optimisation params = { - "embedding_size": hp.quniform("embedding_size", l_embedding_size[0], l_embedding_size[1], 1), + "embedding_size": hp.quniform( + "embedding_size", l_embedding_size[0], l_embedding_size[1], 1 + ), "units": hp.quniform("units", l_units[0], l_units[1], 1), - "batch_size": hp.quniform("batch_size", l_batch_size[0], l_batch_size[1], 1), - "learning_rate": hp.loguniform("learning_rate", np.log(l_learning_rate[0]), np.log(l_learning_rate[1])), + "batch_size": hp.quniform( + "batch_size", l_batch_size[0], l_batch_size[1], 1 + ), + "learning_rate": hp.loguniform( + "learning_rate", np.log(l_learning_rate[0]), np.log(l_learning_rate[1]) + ), "dropout": hp.uniform("dropout", l_dropout[0], l_dropout[1]), - "spatial_dropout": hp.uniform("spatial_dropout", l_spatial_dropout[0], l_spatial_dropout[1]), - "recurrent_dropout": hp.uniform("recurrent_dropout", l_recurrent_dropout[0], l_recurrent_dropout[1]) + "spatial_dropout": hp.uniform( + "spatial_dropout", l_spatial_dropout[0], l_spatial_dropout[1] + ), + "recurrent_dropout": hp.uniform( + "recurrent_dropout", l_recurrent_dropout[0], l_recurrent_dropout[1] + ), } def create_model(params): model = Sequential() - model.add(Embedding(dimensions, int(params["embedding_size"]), mask_zero=True)) + model.add( + Embedding(dimensions, int(params["embedding_size"]), mask_zero=True) + ) model.add(SpatialDropout1D(params["spatial_dropout"])) - model.add(GRU(int(params["units"]), dropout=params["dropout"], recurrent_dropout=params["recurrent_dropout"], return_sequences=True, activation="elu")) + model.add( + GRU( + int(params["units"]), + dropout=params["dropout"], + recurrent_dropout=params["recurrent_dropout"], + return_sequences=True, + activation="elu", + ) + ) model.add(Dropout(params["dropout"])) - model.add(GRU(int(params["units"]), dropout=params["dropout"], recurrent_dropout=params["recurrent_dropout"], return_sequences=False, activation="elu")) + model.add( + GRU( + int(params["units"]), + dropout=params["dropout"], + recurrent_dropout=params["recurrent_dropout"], + return_sequences=False, + activation="elu", + ) + ) model.add(Dropout(params["dropout"])) model.add(Dense(2 * dimensions, activation="sigmoid")) optimizer_rms = RMSprop(lr=params["learning_rate"]) batch_size = int(params["batch_size"]) - model.compile(loss=utils.weighted_loss(class_weights), optimizer=optimizer_rms) + model.compile( + loss=utils.weighted_loss(class_weights), optimizer=optimizer_rms + ) print(model.summary()) - model_fit = model.fit_generator( + model_fit = model.fit( utils.balanced_sample_generator( train_data, train_labels, batch_size, tool_tr_samples, - reverse_dictionary + reverse_dictionary, ), steps_per_epoch=len(train_data) // batch_size, epochs=optimize_n_epochs, callbacks=[early_stopping], validation_data=(test_data, test_labels), verbose=2, - shuffle=True + shuffle=True, ) - return {'loss': model_fit.history["val_loss"][-1], 'status': STATUS_OK, 'model': model} + return { + "loss": model_fit.history["val_loss"][-1], + "status": STATUS_OK, + "model": model, + } + # minimize the objective function using the set of parameters above trials = Trials() - learned_params = fmin(create_model, params, trials=trials, algo=tpe.suggest, max_evals=int(config["max_evals"])) - best_model = trials.results[np.argmin([r['loss'] for r in trials.results])]['model'] + learned_params = fmin( + create_model, + params, + trials=trials, + algo=tpe.suggest, + max_evals=int(config["max_evals"]), + ) + best_model = trials.results[np.argmin([r["loss"] for r in trials.results])][ + "model" + ] # set the best params with respective values for item in learned_params: item_val = learned_params[item]
--- a/predict_tool_usage.py Tue Jul 07 03:25:49 2020 -0400 +++ b/predict_tool_usage.py Fri May 06 09:05:18 2022 +0000 @@ -2,17 +2,16 @@ Predict tool usage to weigh the predicted tools """ -import os -import numpy as np -import warnings +import collections import csv -import collections +import os +import warnings -from sklearn.svm import SVR +import numpy as np +import utils from sklearn.model_selection import GridSearchCV from sklearn.pipeline import Pipeline - -import utils +from sklearn.svm import SVR warnings.filterwarnings("ignore") @@ -20,7 +19,6 @@ class ToolPopularity: - def __init__(self): """ Init method. """ @@ -31,10 +29,11 @@ tool_usage_dict = dict() all_dates = list() all_tool_list = list(dictionary.keys()) - with open(tool_usage_file, 'rt') as usage_file: - tool_usage = csv.reader(usage_file, delimiter='\t') + with open(tool_usage_file, "rt") as usage_file: + tool_usage = csv.reader(usage_file, delimiter="\t") for index, row in enumerate(tool_usage): - if (str(row[1]) > cutoff_date) is True: + row = [item.strip() for item in row] + if (str(row[1]).strip() > cutoff_date) is True: tool_id = utils.format_tool_id(row[0]) if tool_id in all_tool_list: all_dates.append(row[1]) @@ -67,18 +66,25 @@ """ epsilon = 0.0 cv = 5 - s_typ = 'neg_mean_absolute_error' + s_typ = "neg_mean_absolute_error" n_jobs = 4 s_error = 1 - iid = True tr_score = False try: - pipe = Pipeline(steps=[('regressor', SVR(gamma='scale'))]) + pipe = Pipeline(steps=[("regressor", SVR(gamma="scale"))]) param_grid = { - 'regressor__kernel': ['rbf', 'poly', 'linear'], - 'regressor__degree': [2, 3] + "regressor__kernel": ["rbf", "poly", "linear"], + "regressor__degree": [2, 3], } - search = GridSearchCV(pipe, param_grid, iid=iid, cv=cv, scoring=s_typ, n_jobs=n_jobs, error_score=s_error, return_train_score=tr_score) + search = GridSearchCV( + pipe, + param_grid, + cv=cv, + scoring=s_typ, + n_jobs=n_jobs, + error_score=s_error, + return_train_score=tr_score, + ) search.fit(x_reshaped, y_reshaped.ravel()) model = search.best_estimator_ # set the next time point to get prediction for @@ -87,7 +93,8 @@ if prediction < epsilon: prediction = [epsilon] return prediction[0] - except Exception: + except Exception as e: + print(e) return epsilon def get_pupularity_prediction(self, tools_usage):
--- a/prepare_data.py Tue Jul 07 03:25:49 2020 -0400 +++ b/prepare_data.py Fri May 06 09:05:18 2022 +0000 @@ -4,18 +4,17 @@ into the test and training sets """ +import collections import os -import collections -import numpy as np import random +import numpy as np import predict_tool_usage main_path = os.getcwd() class PrepareData: - def __init__(self, max_seq_length, test_data_share): """ Init method. """ self.max_tool_sequence_len = max_seq_length @@ -27,15 +26,20 @@ """ tokens = list() raw_paths = workflow_paths - raw_paths = [x.replace("\n", '') for x in raw_paths] + raw_paths = [x.replace("\n", "") for x in raw_paths] for item in raw_paths: split_items = item.split(",") for token in split_items: - if token is not "": + if token != "": tokens.append(token) tokens = list(set(tokens)) tokens = np.array(tokens) - tokens = np.reshape(tokens, [-1, ]) + tokens = np.reshape( + tokens, + [ + -1, + ], + ) return tokens, raw_paths def create_new_dict(self, new_data_dict): @@ -60,7 +64,10 @@ dictionary = dict() for word, _ in count: dictionary[word] = len(dictionary) + 1 - dictionary, reverse_dictionary = self.assemble_dictionary(dictionary, old_data_dictionary) + word = word.strip() + dictionary, reverse_dictionary = self.assemble_dictionary( + dictionary, old_data_dictionary + ) return dictionary, reverse_dictionary def decompose_paths(self, paths, dictionary): @@ -74,13 +81,17 @@ if len_tools <= self.max_tool_sequence_len: for window in range(1, len_tools): sequence = tools[0: window + 1] - tools_pos = [str(dictionary[str(tool_item)]) for tool_item in sequence] + tools_pos = [ + str(dictionary[str(tool_item)]) for tool_item in sequence + ] if len(tools_pos) > 1: sub_paths_pos.append(",".join(tools_pos)) sub_paths_pos = list(set(sub_paths_pos)) return sub_paths_pos - def prepare_paths_labels_dictionary(self, dictionary, reverse_dictionary, paths, compatible_next_tools): + def prepare_paths_labels_dictionary( + self, dictionary, reverse_dictionary, paths, compatible_next_tools + ): """ Create a dictionary of sequences with their labels for training and test paths """ @@ -90,14 +101,18 @@ if item and item not in "": tools = item.split(",") label = tools[-1] - train_tools = tools[:len(tools) - 1] + train_tools = tools[: len(tools) - 1] last_but_one_name = reverse_dictionary[int(train_tools[-1])] try: - compatible_tools = compatible_next_tools[last_but_one_name].split(",") + compatible_tools = compatible_next_tools[last_but_one_name].split( + "," + ) except Exception: continue if len(compatible_tools) > 0: - compatible_tools_ids = [str(dictionary[x]) for x in compatible_tools] + compatible_tools_ids = [ + str(dictionary[x]) for x in compatible_tools + ] compatible_tools_ids.append(label) composite_labels = ",".join(compatible_tools_ids) train_tools = ",".join(train_tools) @@ -127,7 +142,9 @@ train_counter += 1 return data_mat, label_mat - def pad_paths(self, paths_dictionary, num_classes, standard_connections, reverse_dictionary): + def pad_paths( + self, paths_dictionary, num_classes, standard_connections, reverse_dictionary + ): """ Add padding to the tools sequences and create multi-hot encoded labels """ @@ -231,12 +248,22 @@ l_tool_tr_samples[last_tool_id].append(index) return l_tool_tr_samples - def get_data_labels_matrices(self, workflow_paths, tool_usage_path, cutoff_date, compatible_next_tools, standard_connections, old_data_dictionary={}): + def get_data_labels_matrices( + self, + workflow_paths, + tool_usage_path, + cutoff_date, + compatible_next_tools, + standard_connections, + old_data_dictionary={}, + ): """ Convert the training and test paths into corresponding numpy matrices """ processed_data, raw_paths = self.process_workflow_paths(workflow_paths) - dictionary, rev_dict = self.create_data_dictionary(processed_data, old_data_dictionary) + dictionary, rev_dict = self.create_data_dictionary( + processed_data, old_data_dictionary + ) num_classes = len(dictionary) print("Raw paths: %d" % len(raw_paths)) @@ -247,18 +274,26 @@ random.shuffle(all_unique_paths) print("Creating dictionaries...") - multilabels_paths = self.prepare_paths_labels_dictionary(dictionary, rev_dict, all_unique_paths, compatible_next_tools) + multilabels_paths = self.prepare_paths_labels_dictionary( + dictionary, rev_dict, all_unique_paths, compatible_next_tools + ) print("Complete data: %d" % len(multilabels_paths)) - train_paths_dict, test_paths_dict = self.split_test_train_data(multilabels_paths) + train_paths_dict, test_paths_dict = self.split_test_train_data( + multilabels_paths + ) print("Train data: %d" % len(train_paths_dict)) print("Test data: %d" % len(test_paths_dict)) print("Padding train and test data...") # pad training and test data with leading zeros - test_data, test_labels = self.pad_paths(test_paths_dict, num_classes, standard_connections, rev_dict) - train_data, train_labels = self.pad_paths(train_paths_dict, num_classes, standard_connections, rev_dict) + test_data, test_labels = self.pad_paths( + test_paths_dict, num_classes, standard_connections, rev_dict + ) + train_data, train_labels = self.pad_paths( + train_paths_dict, num_classes, standard_connections, rev_dict + ) print("Estimating sample frequency...") l_tool_freq = self.get_train_last_tool_freq(train_paths_dict, rev_dict) @@ -274,4 +309,15 @@ # get class weights using the predicted usage for each tool class_weights = self.assign_class_weights(num_classes, t_pred_usage) - return train_data, train_labels, test_data, test_labels, dictionary, rev_dict, class_weights, t_pred_usage, l_tool_freq, l_tool_tr_samples + return ( + train_data, + train_labels, + test_data, + test_labels, + dictionary, + rev_dict, + class_weights, + t_pred_usage, + l_tool_freq, + l_tool_tr_samples, + )
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16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 t f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f t f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 83 Cut1 1.0.1 85 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 t f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f t f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 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1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 85 addValue 1.0.0 88 Paste1 1.0.0 t f f -9 2013-02-07 16:59:41.215802 85 addValue 1.0.0 88 Paste1 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16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 t f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f t f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 88 Paste1 1.0.0 87 addValue 1.0.0 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 t f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f t f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -9 2013-02-07 16:59:41.215802 89 82 Grep1 1.0.1 f f f -11 2013-02-07 17:03:54.795316 135 addValue 1.0.0 136 cat1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 136 cat1 1.0.0 145 barchart_gnuplot 1.0.0 f t f -11 2013-02-07 17:03:54.795316 137 Cut1 1.0.1 170 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 138 Cut1 1.0.1 170 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 139 Cut1 1.0.1 177 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 140 Cut1 1.0.1 177 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 141 Cut1 1.0.1 147 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 142 Cut1 1.0.1 147 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 143 Cut1 1.0.1 171 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 144 Cut1 1.0.1 171 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 146 Paste1 1.0.0 176 Add_a_column1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 147 Paste1 1.0.0 175 Add_a_column1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 148 addValue 1.0.0 136 cat1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 149 addValue 1.0.0 136 cat1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 150 Filter1 1.1.0 157 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 150 Filter1 1.1.0 156 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 151 gops_coverage_1 1.0.0 155 Filter1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 151 gops_coverage_1 1.0.0 154 Filter1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 151 gops_coverage_1 1.0.0 153 Filter1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 151 gops_coverage_1 1.0.0 152 cshl_grep_tool 1.0.0 f t f -11 2013-02-07 17:03:54.795316 151 gops_coverage_1 1.0.0 150 Filter1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 152 cshl_grep_tool 1.0.0 163 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 152 cshl_grep_tool 1.0.0 162 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 153 Filter1 1.1.0 161 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 153 Filter1 1.1.0 160 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 154 Filter1 1.1.0 167 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 154 Filter1 1.1.0 166 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 155 Filter1 1.1.0 165 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 155 Filter1 1.1.0 164 Summary_Statistics1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 156 Summary_Statistics1 1.1.0 168 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 157 Summary_Statistics1 1.1.0 169 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 158 addValue 1.0.0 136 cat1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 159 addValue 1.0.0 136 cat1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 160 Summary_Statistics1 1.1.0 142 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 161 Summary_Statistics1 1.1.0 141 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 162 Summary_Statistics1 1.1.0 144 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 163 Summary_Statistics1 1.1.0 143 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 164 Summary_Statistics1 1.1.0 138 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 165 Summary_Statistics1 1.1.0 137 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 166 Summary_Statistics1 1.1.0 140 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 167 Summary_Statistics1 1.1.0 139 Cut1 1.0.1 f t f -11 2013-02-07 17:03:54.795316 168 Cut1 1.0.1 146 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 169 Cut1 1.0.1 146 Paste1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 170 Paste1 1.0.0 173 Add_a_column1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 171 Paste1 1.0.0 174 Add_a_column1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 172 Add_a_column1 1.1.0 135 addValue 1.0.0 f t f -11 2013-02-07 17:03:54.795316 173 Add_a_column1 1.1.0 149 addValue 1.0.0 f t f -11 2013-02-07 17:03:54.795316 174 Add_a_column1 1.1.0 148 addValue 1.0.0 f t f -11 2013-02-07 17:03:54.795316 175 Add_a_column1 1.1.0 158 addValue 1.0.0 f t f -11 2013-02-07 17:03:54.795316 176 Add_a_column1 1.1.0 159 addValue 1.0.0 f t f -11 2013-02-07 17:03:54.795316 177 Paste1 1.0.0 172 Add_a_column1 1.1.0 f t f -11 2013-02-07 17:03:54.795316 178 151 gops_coverage_1 1.0.0 f t f -11 2013-02-07 17:03:54.795316 179 151 gops_coverage_1 1.0.0 f t f -12 2013-02-07 17:04:38.354863 180 cat1 1.0.0 189 barchart_gnuplot 1.0.0 t t f -12 2013-02-07 17:04:38.354863 180 cat1 1.0.0 189 barchart_gnuplot 1.0.0 f t f -12 2013-02-07 17:04:38.354863 181 bedtools_intersectBed 183 wc_gnu 1.0.0 t t f -12 2013-02-07 17:04:38.354863 181 bedtools_intersectBed 183 wc_gnu 1.0.0 f t f -12 2013-02-07 17:04:38.354863 182 bedtools_intersectBed 184 sort1 1.0.1 t t f -12 2013-02-07 17:04:38.354863 182 bedtools_intersectBed 184 sort1 1.0.1 f t f -12 2013-02-07 17:04:38.354863 183 wc_gnu 1.0.0 185 addValue 1.0.0 t t f -12 2013-02-07 17:04:38.354863 183 wc_gnu 1.0.0 185 addValue 1.0.0 f t f -12 2013-02-07 17:04:38.354863 184 sort1 1.0.1 186 cshl_awk_tool t t f -12 2013-02-07 17:04:38.354863 184 sort1 1.0.1 186 cshl_awk_tool f t f -12 2013-02-07 17:04:38.354863 185 addValue 1.0.0 180 cat1 1.0.0 t t f -12 2013-02-07 17:04:38.354863 185 addValue 1.0.0 180 cat1 1.0.0 f t f -12 2013-02-07 17:04:38.354863 186 cshl_awk_tool 188 cshl_uniq_tool 1.0.0 t t f -12 2013-02-07 17:04:38.354863 186 cshl_awk_tool 188 cshl_uniq_tool 1.0.0 f t f -12 2013-02-07 17:04:38.354863 187 Count1 1.0.0 180 cat1 1.0.0 t t f -12 2013-02-07 17:04:38.354863 187 Count1 1.0.0 180 cat1 1.0.0 f t f -12 2013-02-07 17:04:38.354863 188 cshl_uniq_tool 1.0.0 187 Count1 1.0.0 t t f -12 2013-02-07 17:04:38.354863 188 cshl_uniq_tool 1.0.0 187 Count1 1.0.0 f t f -12 2013-02-07 17:04:38.354863 190 182 bedtools_intersectBed t t f -12 2013-02-07 17:04:38.354863 190 182 bedtools_intersectBed f t f -12 2013-02-07 17:04:38.354863 190 181 bedtools_intersectBed t t f -12 2013-02-07 17:04:38.354863 190 181 bedtools_intersectBed f t f -12 2013-02-07 17:04:38.354863 191 182 bedtools_intersectBed t t f -12 2013-02-07 17:04:38.354863 191 182 bedtools_intersectBed f t f -12 2013-02-07 17:04:38.354863 191 181 bedtools_intersectBed t t f -12 2013-02-07 17:04:38.354863 191 181 bedtools_intersectBed f t f -19 2013-02-14 15:51:02.598429 193 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 193 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 193 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 193 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 195 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 195 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 195 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 195 194 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 f t f -19 2013-02-14 15:51:02.598429 199 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 199 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 215 Count1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 215 Count1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 215 Count1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 215 Count1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 210 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 210 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 210 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 200 gops_intersect_1 1.0.0 210 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 205 gops_subtract_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 201 cshl_find_and_replace 1.0.0 200 gops_intersect_1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 202 get_flanks1 1.0.0 201 cshl_find_and_replace 1.0.0 f t f -19 2013-02-14 15:51:02.598429 202 get_flanks1 1.0.0 201 cshl_find_and_replace 1.0.0 f t f -19 2013-02-14 15:51:02.598429 202 get_flanks1 1.0.0 201 cshl_find_and_replace 1.0.0 f t f -19 2013-02-14 15:51:02.598429 202 get_flanks1 1.0.0 201 cshl_find_and_replace 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 204 cshl_grep_tool 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 204 cshl_grep_tool 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 204 cshl_grep_tool 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 204 cshl_grep_tool 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 202 get_flanks1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 202 get_flanks1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 202 get_flanks1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 203 202 get_flanks1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 205 gops_subtract_1 1.0.0 206 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 205 gops_subtract_1 1.0.0 206 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 205 gops_subtract_1 1.0.0 206 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 205 gops_subtract_1 1.0.0 206 cshl_awk_tool f t f -19 2013-02-14 15:51:02.598429 206 cshl_awk_tool 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 206 cshl_awk_tool 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 206 cshl_awk_tool 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 206 cshl_awk_tool 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 207 Extract genomic DNA 1 2.2.2 214 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 207 Extract genomic DNA 1 2.2.2 214 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 207 Extract genomic DNA 1 2.2.2 214 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 207 Extract genomic DNA 1 2.2.2 214 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 208 213 trap f t f -19 2013-02-14 15:51:02.598429 208 213 trap f t f -19 2013-02-14 15:51:02.598429 208 213 trap f t f -19 2013-02-14 15:51:02.598429 208 213 trap f t f -19 2013-02-14 15:51:02.598429 208 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 208 207 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 209 Extract genomic DNA 1 2.2.2 211 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 209 Extract genomic DNA 1 2.2.2 211 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 209 Extract genomic DNA 1 2.2.2 211 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 209 Extract genomic DNA 1 2.2.2 211 Show beginning1 1.0.0 f t f -19 2013-02-14 15:51:02.598429 210 cshl_awk_tool 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 210 cshl_awk_tool 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 210 cshl_awk_tool 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 210 cshl_awk_tool 209 Extract genomic DNA 1 2.2.2 f t f -19 2013-02-14 15:51:02.598429 211 Show beginning1 1.0.0 212 meme_meme 1.0.0 f t f -19 2013-02-14 15:51:02.598429 211 Show beginning1 1.0.0 212 meme_meme 1.0.0 f t f -19 2013-02-14 15:51:02.598429 211 Show beginning1 1.0.0 212 meme_meme 1.0.0 f t f -19 2013-02-14 15:51:02.598429 211 Show beginning1 1.0.0 212 meme_meme 1.0.0 f t f -19 2013-02-14 15:51:02.598429 215 Count1 1.0.0 216 barchart_gnuplot 1.0.0 f t f -19 2013-02-14 15:51:02.598429 215 Count1 1.0.0 216 barchart_gnuplot 1.0.0 f t f -19 2013-02-14 15:51:02.598429 215 Count1 1.0.0 216 barchart_gnuplot 1.0.0 f t f -19 2013-02-14 15:51:02.598429 215 Count1 1.0.0 216 barchart_gnuplot 1.0.0 f t f -28 2013-02-14 16:08:08.300397 242 243 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 1.4.1 f t f -28 2013-02-14 16:08:08.300397 244 243 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 1.4.1 f t f -29 2013-02-14 17:12:23.558236 245 246 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 1.4.1 f t f -29 2013-02-14 17:12:23.558236 247 246 toolshed.g2.bx.psu.edu/repos/ryo-tas/macs14/peakcalling_macs14/1.4.1 1.4.1 f t f -29 2013-02-14 17:12:23.558236 251 257 gops_subtract_1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 251 252 gops_intersect_1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 252 gops_intersect_1 1.0.0 267 Count1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 252 gops_intersect_1 1.0.0 262 cshl_awk_tool f t f -29 2013-02-14 17:12:23.558236 253 cshl_find_and_replace 1.0.0 257 gops_subtract_1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 253 cshl_find_and_replace 1.0.0 252 gops_intersect_1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 254 get_flanks1 1.0.0 253 cshl_find_and_replace 1.0.0 f t f -29 2013-02-14 17:12:23.558236 255 256 cshl_grep_tool 1.0.0 f t f -29 2013-02-14 17:12:23.558236 255 254 get_flanks1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 257 gops_subtract_1 1.0.0 258 cshl_awk_tool f t f -29 2013-02-14 17:12:23.558236 258 cshl_awk_tool 259 Extract genomic DNA 1 2.2.2 f t f -29 2013-02-14 17:12:23.558236 259 Extract genomic DNA 1 2.2.2 266 Show beginning1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 260 265 trap f t f -29 2013-02-14 17:12:23.558236 260 261 Extract genomic DNA 1 2.2.2 f t f -29 2013-02-14 17:12:23.558236 260 259 Extract genomic DNA 1 2.2.2 f t f -29 2013-02-14 17:12:23.558236 261 Extract genomic DNA 1 2.2.2 263 Show beginning1 1.0.0 f t f -29 2013-02-14 17:12:23.558236 262 cshl_awk_tool 261 Extract genomic DNA 1 2.2.2 f t f -29 2013-02-14 17:12:23.558236 263 Show beginning1 1.0.0 264 meme_meme 1.0.0 f t f -29 2013-02-14 17:12:23.558236 267 Count1 1.0.0 268 barchart_gnuplot 1.0.0 f t f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f t f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f t f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f t f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f t f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f f f -31 2013-02-18 11:33:27.210212 274 275 addValue 1.0.0 f 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11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f -31 2013-02-18 11:33:27.210212 276 mergeCols1 1.0.1 277 Cut1 1.0.1 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10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 703 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 722 Count1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f t f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 704 gops_subtract_1 1.0.0 711 Extract genomic DNA 1 2.2.2 t t f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 708 gops_intersect_1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 705 cshl_awk_tool 1.0.0 704 gops_subtract_1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f t f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 f f f -97 2013-02-20 10:11:21.312214 706 get_flanks1 1.0.0 705 cshl_awk_tool 1.0.0 t t f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 707 706 get_flanks1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f t f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 720 Count1 1.0.0 t t f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f t f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 708 gops_intersect_1 1.0.0 709 Extract genomic DNA 1 2.2.2 t t f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f t f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 709 Extract genomic DNA 1 2.2.2 716 fasta2tab 1.1.0 t t f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f t f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 711 Extract genomic DNA 1 2.2.2 t t f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f t f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 f f f -97 2013-02-20 10:11:21.312214 710 709 Extract genomic DNA 1 2.2.2 t t f -97 2013-02-20 10:11:21.312214 711 Extract genomic DNA 1 2.2.2 712 fasta2tab 1.1.0 f f f -97 2013-02-20 10:11:21.312214 711 Extract genomic DNA 1 2.2.2 712 fasta2tab 1.1.0 f f f +3 2013-02-07 7 Remove beginning1 1.0.0 6 Cut1 1.0.1 f t f +3 2013-02-07 7 Remove beginning1 1.0.0 9 Cut1 1.0.1 f t f +3 2013-02-07 8 addValue 1.0.0 11 Paste1 1.0.0 f t f +3 2013-02-07 9 Cut1 1.0.1 11 Paste1 1.0.0 f t f +3 2013-02-07 11 Paste1 1.0.0 10 addValue 1.0.0 f t f +3 2013-02-07 12 5 Grep1 1.0.1 f t f +4 2013-02-07 13 cat1 1.0.0 22 barchart_gnuplot 1.0.0 f t f +4 2013-02-07 14 bedtools_intersectBed 16 wc_gnu 1.0.0 f t f +4 2013-02-07 15 bedtools_intersectBed 17 sort1 1.0.1 f t f +4 2013-02-07 16 wc_gnu 1.0.0 18 addValue 1.0.0 f t f +4 2013-02-07 17 sort1 1.0.1 19 cshl_awk_tool f t f +4 2013-02-07 18 addValue 1.0.0 13 cat1 1.0.0 f t f +4 2013-02-07 19 cshl_awk_tool 21 cshl_uniq_tool 1.0.0 f t f +4 2013-02-07 20 Count1 1.0.0 13 cat1 1.0.0 f t f +4 2013-02-07 21 cshl_uniq_tool 1.0.0 20 Count1 1.0.0 f t f +4 2013-02-07 23 14 bedtools_intersectBed f t f +4 2013-02-07 23 15 bedtools_intersectBed f t f +4 2013-02-07 24 14 bedtools_intersectBed f t f +4 2013-02-07 24 15 bedtools_intersectBed f t f +5 2013-02-07 25 addValue 1.0.0 26 cat1 1.0.0 f t f +5 2013-02-07 26 cat1 1.0.0 67 barchart_gnuplot 1.0.0 f t f +5 2013-02-07 27 Cut1 1.0.1 59 Paste1 1.0.0 f t f +5 2013-02-07 28 Cut1 1.0.1 59 Paste1 1.0.0 f t f +5 2013-02-07 29 Cut1 1.0.1 66 Paste1 1.0.0 f t f +5 2013-02-07 30 Cut1 1.0.1 66 Paste1 1.0.0 f t f +5 2013-02-07 31 Cut1 1.0.1 36 Paste1 1.0.0 f t f +5 2013-02-07 32 Cut1 1.0.1 36 Paste1 1.0.0 f t f +5 2013-02-07 33 Cut1 1.0.1 60 Paste1 1.0.0 f t f +5 2013-02-07 34 Cut1 1.0.1 60 Paste1 1.0.0 f t f +5 2013-02-07 35 Paste1 1.0.0 65 Add_a_column1 1.1.0 f t f +5 2013-02-07 36 Paste1 1.0.0 64 Add_a_column1 1.1.0 f t f +5 2013-02-07 37 addValue 1.0.0 26 cat1 1.0.0 f t f +5 2013-02-07 38 addValue 1.0.0 26 cat1 1.0.0 f t f +5 2013-02-07 39 Filter1 1.1.0 45 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 39 Filter1 1.1.0 46 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 40 gops_coverage_1 1.0.0 39 Filter1 1.1.0 f t f +5 2013-02-07 40 gops_coverage_1 1.0.0 41 cshl_grep_tool 1.0.0 f t f +5 2013-02-07 40 gops_coverage_1 1.0.0 42 Filter1 1.1.0 f t f +5 2013-02-07 40 gops_coverage_1 1.0.0 43 Filter1 1.1.0 f t f +5 2013-02-07 40 gops_coverage_1 1.0.0 44 Filter1 1.1.0 f t f +5 2013-02-07 41 cshl_grep_tool 1.0.0 51 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 41 cshl_grep_tool 1.0.0 52 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 42 Filter1 1.1.0 49 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 42 Filter1 1.1.0 50 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 43 Filter1 1.1.0 55 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 43 Filter1 1.1.0 56 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 44 Filter1 1.1.0 53 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 44 Filter1 1.1.0 54 Summary_Statistics1 1.1.0 f t f +5 2013-02-07 45 Summary_Statistics1 1.1.0 57 Cut1 1.0.1 f t f +5 2013-02-07 46 Summary_Statistics1 1.1.0 58 Cut1 1.0.1 f t f +5 2013-02-07 47 addValue 1.0.0 26 cat1 1.0.0 f t f +5 2013-02-07 48 addValue 1.0.0 26 cat1 1.0.0 f t f +5 2013-02-07 49 Summary_Statistics1 1.1.0 32 Cut1 1.0.1 f t f +5 2013-02-07 50 Summary_Statistics1 1.1.0 31 Cut1 1.0.1 f t f +5 2013-02-07 51 Summary_Statistics1 1.1.0 34 Cut1 1.0.1 f t f +5 2013-02-07 52 Summary_Statistics1 1.1.0 33 Cut1 1.0.1 f t f +5 2013-02-07 53 Summary_Statistics1 1.1.0 28 Cut1 1.0.1 f t f +5 2013-02-07 54 Summary_Statistics1 1.1.0 27 Cut1 1.0.1 f t f +5 2013-02-07 55 Summary_Statistics1 1.1.0 30 Cut1 1.0.1 f t f +5 2013-02-07 56 Summary_Statistics1 1.1.0 29 Cut1 1.0.1 f t f +5 2013-02-07 57 Cut1 1.0.1 35 Paste1 1.0.0 f t f +5 2013-02-07 58 Cut1 1.0.1 35 Paste1 1.0.0 f t f +5 2013-02-07 59 Paste1 1.0.0 62 Add_a_column1 1.1.0 f t f +5 2013-02-07 60 Paste1 1.0.0 63 Add_a_column1 1.1.0 f t f +5 2013-02-07 61 Add_a_column1 1.1.0 25 addValue 1.0.0 f t f +5 2013-02-07 62 Add_a_column1 1.1.0 38 addValue 1.0.0 f t f +5 2013-02-07 63 Add_a_column1 1.1.0 37 addValue 1.0.0 f t f +5 2013-02-07 64 Add_a_column1 1.1.0 47 addValue 1.0.0 f t f +5 2013-02-07 65 Add_a_column1 1.1.0 48 addValue 1.0.0 f t f +5 2013-02-07 66 Paste1 1.0.0 61 Add_a_column1 1.1.0 f t f +5 2013-02-07 68 40 gops_coverage_1 1.0.0 f t f +5 2013-02-07 69 40 gops_coverage_1 1.0.0 f t f +6 2013-02-07 71 70 cshl_awk_tool1 1.0.0 f t f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 t f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 t f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 t f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 t f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 t f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 t f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 t f f +9 2013-02-07 89 82 Grep1 1.0.1 t f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f t f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f t f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f t f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f t f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f t f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f t f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f t f +9 2013-02-07 89 82 Grep1 1.0.1 f t f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 addValue 1.0.0 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 83 Cut1 1.0.1 f f f +9 2013-02-07 84 Remove beginning1 1.0.0 86 Cut1 1.0.1 f f f +9 2013-02-07 85 addValue 1.0.0 88 Paste1 1.0.0 f f f +9 2013-02-07 86 Cut1 1.0.1 88 Paste1 1.0.0 f f f +9 2013-02-07 88 Paste1 1.0.0 87 addValue 1.0.0 f f f +9 2013-02-07 89 82 Grep1 1.0.1 f f f +9 2013-02-07 82 Grep1 1.0.1 84 Remove beginning1 1.0.0 f f f +9 2013-02-07 83 Cut1 1.0.1 85 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+31 2013-02-18 274 275 addValue 1.0.0 f t f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f t f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f t f +31 2013-02-18 274 275 addValue 1.0.0 f t f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f t f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f t f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 2013-02-18 275 addValue 1.0.0 276 mergeCols1 1.0.1 f f f +31 2013-02-18 276 mergeCols1 1.0.1 277 Cut1 1.0.1 f f f +31 2013-02-18 274 275 addValue 1.0.0 f f f +31 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--- a/utils.py Tue Jul 07 03:25:49 2020 -0400 +++ b/utils.py Fri May 06 09:05:18 2022 +0000 @@ -1,10 +1,11 @@ -import numpy as np import json -import h5py import random + +import h5py +import numpy as np +import tensorflow as tf from numpy.random import choice - -from keras import backend as K +from tensorflow.keras import backend def read_file(file_path): @@ -29,10 +30,10 @@ """ Create an h5 file with the trained weights and associated dicts """ - hf_file = h5py.File(dump_file, 'w') + hf_file = h5py.File(dump_file, "w") for key in model_values: value = model_values[key] - if key == 'model_weights': + if key == "model_weights": for idx, item in enumerate(value): w_key = "weight_" + str(idx) if w_key in hf_file: @@ -54,14 +55,19 @@ """ weight_values = list(class_weights.values()) weight_values.extend(weight_values) + def weighted_binary_crossentropy(y_true, y_pred): # add another dimension to compute dot product - expanded_weights = K.expand_dims(weight_values, axis=-1) - return K.dot(K.binary_crossentropy(y_true, y_pred), expanded_weights) + expanded_weights = tf.expand_dims(weight_values, axis=-1) + bce = backend.binary_crossentropy(y_true, y_pred) + return backend.dot(bce, expanded_weights) + return weighted_binary_crossentropy -def balanced_sample_generator(train_data, train_labels, batch_size, l_tool_tr_samples, reverse_dictionary): +def balanced_sample_generator( + train_data, train_labels, batch_size, l_tool_tr_samples, reverse_dictionary +): while True: dimension = train_data.shape[1] n_classes = train_labels.shape[1] @@ -80,7 +86,18 @@ yield generator_batch_data, generator_batch_labels -def compute_precision(model, x, y, reverse_data_dictionary, usage_scores, actual_classes_pos, topk, standard_conn, last_tool_id, lowest_tool_ids): +def compute_precision( + model, + x, + y, + reverse_data_dictionary, + usage_scores, + actual_classes_pos, + topk, + standard_conn, + last_tool_id, + lowest_tool_ids, +): """ Compute absolute and compatible precision """ @@ -137,7 +154,9 @@ else: lowest_pub_prec = np.nan if standard_topk_prediction_pos in usage_scores: - usage_wt_score.append(np.log(usage_scores[standard_topk_prediction_pos] + 1.0)) + usage_wt_score.append( + np.log(usage_scores[standard_topk_prediction_pos] + 1.0) + ) else: # count precision only when there is actually true published tools # else set to np.nan. Set to 0 only when there is wrong prediction @@ -148,7 +167,9 @@ pred_t_name = reverse_data_dictionary[int(normal_topk_prediction_pos)] if pred_t_name in actual_next_tool_names: if normal_topk_prediction_pos in usage_scores: - usage_wt_score.append(np.log(usage_scores[normal_topk_prediction_pos] + 1.0)) + usage_wt_score.append( + np.log(usage_scores[normal_topk_prediction_pos] + 1.0) + ) top_precision = 1.0 if last_tool_id in lowest_tool_ids: lowest_norm_prec = 1.0 @@ -166,7 +187,16 @@ return lowest_ids -def verify_model(model, x, y, reverse_data_dictionary, usage_scores, standard_conn, lowest_tool_ids, topk_list=[1, 2, 3]): +def verify_model( + model, + x, + y, + reverse_data_dictionary, + usage_scores, + standard_conn, + lowest_tool_ids, + topk_list=[1, 2, 3], +): """ Verify the model on test data """ @@ -187,7 +217,24 @@ test_sample = x[i, :] last_tool_id = str(int(test_sample[-1])) for index, abs_topk in enumerate(topk_list): - usg_wt_score, absolute_precision, pub_prec, lowest_p_prec, lowest_n_prec = compute_precision(model, test_sample, y, reverse_data_dictionary, usage_scores, actual_classes_pos, abs_topk, standard_conn, last_tool_id, lowest_tool_ids) + ( + usg_wt_score, + absolute_precision, + pub_prec, + lowest_p_prec, + lowest_n_prec, + ) = compute_precision( + model, + test_sample, + y, + reverse_data_dictionary, + usage_scores, + actual_classes_pos, + abs_topk, + standard_conn, + last_tool_id, + lowest_tool_ids, + ) precision[i][index] = absolute_precision usage_weights[i][index] = usg_wt_score epo_pub_prec[i][index] = pub_prec @@ -202,22 +249,36 @@ mean_pub_prec = np.nanmean(epo_pub_prec, axis=0) mean_lowest_pub_prec = np.nanmean(epo_lowest_tools_pub_prec, axis=0) mean_lowest_norm_prec = np.nanmean(epo_lowest_tools_norm_prec, axis=0) - return mean_usage, mean_precision, mean_pub_prec, mean_lowest_pub_prec, mean_lowest_norm_prec, lowest_counter + return ( + mean_usage, + mean_precision, + mean_pub_prec, + mean_lowest_pub_prec, + mean_lowest_norm_prec, + lowest_counter, + ) -def save_model(results, data_dictionary, compatible_next_tools, trained_model_path, class_weights, standard_connections): +def save_model( + results, + data_dictionary, + compatible_next_tools, + trained_model_path, + class_weights, + standard_connections, +): # save files trained_model = results["model"] best_model_parameters = results["best_parameters"] model_config = trained_model.to_json() model_weights = trained_model.get_weights() model_values = { - 'data_dictionary': data_dictionary, - 'model_config': model_config, - 'best_parameters': best_model_parameters, - 'model_weights': model_weights, + "data_dictionary": data_dictionary, + "model_config": model_config, + "best_parameters": best_model_parameters, + "model_weights": model_weights, "compatible_tools": compatible_next_tools, "class_weights": class_weights, - "standard_connections": standard_connections + "standard_connections": standard_connections, } set_trained_model(trained_model_path, model_values)