""" GDELT dataset for temporal graph """
import numpy as np
import os
from .dgl_dataset import DGLBuiltinDataset
from .utils import loadtxt, save_info, load_info, _get_dgl_url
from ..convert import graph as dgl_graph
from .. import backend as F
[docs]class GDELTDataset(DGLBuiltinDataset):
r"""GDELT dataset for event-based temporal graph
The Global Database of Events, Language, and Tone (GDELT) dataset.
This contains events happend all over the world (ie every protest held
anywhere in Russia on a given day is collapsed to a single entry).
This Dataset consists ofevents collected from 1/1/2018 to 1/31/2018
(15 minutes time granularity).
Reference:
- `Recurrent Event Network for Reasoning over Temporal Knowledge Graphs <https://arxiv.org/abs/1904.05530>`_
- `The Global Database of Events, Language, and Tone (GDELT) <https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/28075>`_
Statistics:
- Train examples: 2,304
- Valid examples: 288
- Test examples: 384
Parameters
----------
mode : str
Must be one of ('train', 'valid', 'test'). Default: 'train'
raw_dir : str
Raw file directory to download/contains the input data directory.
Default: ~/.dgl/
force_reload : bool
Whether to reload the dataset. Default: False
verbose: bool
Whether to print out progress information. Default: True.
Attributes
----------
start_time : int
Start time of the temporal graph
end_time : int
End time of the temporal graph
is_temporal : bool
Does the dataset contain temporal graphs
Examples
----------
>>> # get train, valid, test dataset
>>> train_data = GDELTDataset()
>>> valid_data = GDELTDataset(mode='valid')
>>> test_data = GDELTDataset(mode='test')
>>>
>>> # length of train set
>>> train_size = len(train_data)
>>>
>>> for g in train_data:
.... e_feat = g.edata['rel_type']
.... # your code here
....
>>>
"""
def __init__(self, mode='train', raw_dir=None, force_reload=False, verbose=False):
mode = mode.lower()
assert mode in ['train', 'valid', 'test'], "Mode not valid."
self.mode = mode
self.num_nodes = 23033
_url = _get_dgl_url('dataset/gdelt.zip')
super(GDELTDataset, self).__init__(name='GDELT',
url=_url,
raw_dir=raw_dir,
force_reload=force_reload,
verbose=verbose)
def process(self):
file_path = os.path.join(self.raw_path, self.mode + '.txt')
self.data = loadtxt(file_path, delimiter='\t').astype(np.int64)
# The source code is not released, but the paper indicates there're
# totally 137 samples. The cutoff below has exactly 137 samples.
self.time_index = np.floor(self.data[:, 3] / 15).astype(np.int64)
self._start_time = self.time_index.min()
self._end_time = self.time_index.max()
def has_cache(self):
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
return os.path.exists(info_path)
def save(self):
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
save_info(info_path, {'data': self.data,
'time_index': self.time_index,
'start_time': self.start_time,
'end_time': self.end_time})
def load(self):
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
info = load_info(info_path)
self.data, self.time_index, self._start_time, self._end_time = \
info['data'], info['time_index'], info['start_time'], info['end_time']
@property
def start_time(self):
r""" Start time of events in the temporal graph
Returns
-------
int
"""
return self._start_time
@property
def end_time(self):
r""" End time of events in the temporal graph
Returns
-------
int
"""
return self._end_time
[docs] def __getitem__(self, t):
r""" Get graph by with events before time `t + self.start_time`
Parameters
----------
t : int
Time, its value must be in range [0, `self.end_time` - `self.start_time`]
Returns
-------
:class:`dgl.DGLGraph`
The graph contains:
- ``edata['rel_type']``: edge type
"""
if t >= len(self) or t < 0:
raise IndexError("Index out of range")
i = t + self.start_time
row_mask = self.time_index <= i
edges = self.data[row_mask][:, [0, 2]]
rate = self.data[row_mask][:, 1]
g = dgl_graph((edges[:, 0], edges[:, 1]))
g.edata['rel_type'] = F.tensor(rate.reshape(-1, 1), dtype=F.data_type_dict['int64'])
return g
[docs] def __len__(self):
r"""Number of graphs in the dataset.
Return
-------
int
"""
return self._end_time - self._start_time + 1
@property
def is_temporal(self):
r""" Does the dataset contain temporal graphs
Returns
-------
bool
"""
return True
GDELT = GDELTDataset