Commit ef25886510b9b7e1e17f87b7039e624070f152bc
1 parent
cd9123115d
Exists in
master
Filter the given file with a list. Only keep same keys and an error is thrown if…
… a key on the filter does not exist in the source file.
Showing 3 changed files with 60 additions and 37 deletions Inline Diff
scripts/data-management/filter_ids.py
| File was created | 1 | import argparse | |
| 2 | from os.path import isfile | ||
| 3 | from volia.data_io import read_lst | ||
| 4 | |||
| 5 | if __name__ == "__main__": | ||
| 6 | parser = argparse.ArgumentParser(description="Filter ids of the given file to only keep a subset") | ||
| 7 | parser.add_argument("file", type=str, help="") | ||
| 8 | parser.add_argument("--filter", default=None, type=str, help="") | ||
| 9 | parser.add_argument("--outfile", default="out.txt", type=str, help="") | ||
| 10 | |||
| 11 | args = parser.parse_args() | ||
| 12 | |||
| 13 | assert args.filter is not None | ||
| 14 | assert isfile(args.file) | ||
| 15 | |||
| 16 | list_ = read_lst(args.file) | ||
| 17 | filter_ = read_lst(args.filter) | ||
| 18 | |||
| 19 | with open(args.outfile, "w") as of: | ||
| 20 | for key in filter_.keys(): | ||
| 21 | of.write(key + " " + " ".join(list_[key]) + "\n") | ||
| 22 | |||
| 23 | print("File filtered and written in: ", args.outfile) |
scripts/dim-reduction/tsne.py
| File was created | 1 | ''' | |
| 2 | The goal of this script is to display calculate tsne of pvectors. | ||
| 3 | ''' | ||
| 4 | |||
| 5 | import os | ||
| 6 | from os.path import isfile | ||
| 7 | import argparse | ||
| 8 | import numpy as np | ||
| 9 | from sklearn.manifold import TSNE | ||
| 10 | |||
| 11 | from volia.data_io import read_features | ||
| 12 | |||
| 13 | if __name__ == "__main__": | ||
| 14 | # Defining argparse | ||
| 15 | parser = argparse.ArgumentParser(prog='pvector tsne', description='Calculate the tsne representation of pvector in 3 or 2d') | ||
| 16 | parser.add_argument('features', type=str, | ||
| 17 | help='the path of the file you want to calculate tsne') | ||
| 18 | parser.add_argument('-o', '--outfile', type=str, | ||
| 19 | default='.', | ||
| 20 | help='the path of the output file.') | ||
| 21 | parser.add_argument('-n', '--n-comp', type=int, choices=[2, 3], | ||
| 22 | default='2', | ||
| 23 | help='number of components output of tsne') | ||
| 24 | |||
| 25 | args = parser.parse_args() | ||
| 26 | |||
| 27 | assert isfile(args.features) | ||
| 28 | |||
| 29 | features_list = read_features(args.features) | ||
| 30 | tuples_key_feat = np.vstack([ (key, feats) for key, feats in features_list.items()]) | ||
| 31 | keys, features = zip(*tuples_key_feat) | ||
| 32 | feat_tsne = TSNE(n_components=args.n_comp).fit_transform(features) | ||
| 33 | |||
| 34 | with open(args.outfile, "w") as of: | ||
| 35 | for i in range(len(keys)): | ||
| 36 | of.write(keys[i] + " " + " ".join([str(feat) for feat in feat_tsne[i]]) + "\n") | ||
| 37 | print("TSNE finished. Check if everything has been done well.") |
scripts/dimreduction/tsne.py
| 1 | ''' | File was deleted | |
| 2 | The goal of this script is to display calculate tsne of pvectors. | ||
| 3 | ''' | ||
| 4 | |||
| 5 | import os | ||
| 6 | from os.path import isfile | ||
| 7 | import argparse | ||
| 8 | import numpy as np | ||
| 9 | from sklearn.manifold import TSNE | ||
| 10 | |||
| 11 | from volia.data_io import read_features | ||
| 12 | |||
| 13 | if __name__ == "__main__": | ||
| 14 | # Defining argparse | ||
| 15 | parser = argparse.ArgumentParser(prog='pvector tsne', description='Calculate the tsne representation of pvector in 3 or 2d') | ||
| 16 | parser.add_argument('features', type=str, | ||
| 17 | help='the path of the file you want to calculate tsne') | ||
| 18 | parser.add_argument('-o', '--outfile', type=str, | ||
| 19 | default='.', | ||
| 20 | help='the path of the output file.') | ||
| 21 | parser.add_argument('-n', '--n-comp', type=int, choices=[2, 3], | ||
| 22 | default='2', | ||
| 23 | help='number of components output of tsne') | ||
| 24 | |||
| 25 | args = parser.parse_args() | ||
| 26 | |||
| 27 | assert isfile(args.features) | ||
| 28 | |||
| 29 | features_list = read_features(args.features) | ||
| 30 | tuples_key_feat = np.vstack([ (key, feats) for key, feats in features_list.items()]) | ||
| 31 | keys, features = zip(*tuples_key_feat) | ||
| 32 | feat_tsne = TSNE(n_components=args.n_comp).fit_transform(features) | ||
| 33 | |||
| 34 | with open(args.outfile, "w") as of: | ||
| 35 | for i in range(len(keys)): | ||
| 36 | of.write(keys[i] + " " + " ".join([str(feat) for feat in feat_tsne[i]]) + "\n") | ||
| 37 | print("TSNE finished. Check if everything has been done well.") |