ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data
Paper • 2412.11376 • Published
Datasets:
Tasks:
Time Series Forecasting
Modalities:
Time-series
Size:
10K<n<100K
ArXiv:
Tags:
tsfile
timeseries
modality:timeseries
format:tsfile
multimodal-time-series
context-guided-time-series-forecasting
License:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'leu' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
CGTSF: Context-Guided Time Series Forecasting (TsFile format)
Apache TsFile version of ChengsenWang/CGTSF.
Modalities: Time-series.
Overview
CGTSF addresses context-guided time-series forecasting by aligning numerical history and prediction windows with textual background, weather, and date information. The source provides three logically distinct multimodal domains: London electricity usage (LEU), Melbourne solar power generation (MSPG), and Paris traffic flow (PTF). The source card reports the following frequencies and series counts:
| Config | Rows | Series | Frequency | Array widths (Hist / Pred) |
|---|---|---|---|---|
| LEU | 11,616 | 16 | 30 minutes | 240 / 48 |
| MSPG | 10,557 | 27 | 15 minutes | 480 / 96 |
| PTF | 11,520 | 32 | 1 hour | 120 / 24 |
The three source files remain separate because their serialized array widths are incompatible. The source card describes PTF as a 2012 traffic dataset, while the observed source dates at this pinned revision are in 2022; the conversion follows the source date values without changing them.
Schema (TsFile structure)
Each config contains its own table with the same structural roles:
- Time (INT64, milliseconds) - the source target-day
Dateat UTC midnight. - idx (TAG, STRING) -
Idx, identifying the source series/device. - hist_000 ... hist_N (FIELD, DOUBLE) - the serialized
Histnumeric window expanded to scalar fields;Ndepends on the config. - pred_000 ... pred_N (FIELD, DOUBLE) - the serialized
Predwindow expanded to scalar fields;Ndepends on the config. - text (FIELD, STRING) - the aligned textual context.
Hist and Pred are parsed with a safe literal/JSON parser and expanded
without changing their numeric values. The source Date is represented
losslessly by Time; no source row or semantic column is dropped.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("cgtsf_leu.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset: https://huggingface.co/datasets/ChengsenWang/CGTSF
- Source revision:
f85b3fa3a8b3f1a2adbc6edf49f82b7d9d1758c9 - Author / publisher: Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang, Jinming Wu, Lei Zhang, Jianxin Liao.
- Paper: https://arxiv.org/abs/2412.11376
- License: Apache-2.0.
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