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Reformat example data names: use {region}_data for 1-day data, and {region}_data_1min for 1-min data (#781)

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* Fix high-freq data name from `yahoo_cn_1min` to `cn_data_1min`

* re-format example data names using `qlib_{region}_{feq}`, e.g. qlib_cn_1d

* re-format example data names using `{region}_{feq}`, e.g. us_1d and cn_1min

* keep using  for 1day data, and change 1min data to
This commit is contained in:
Chao Ning
2021-12-28 15:58:49 +00:00
committed by GitHub
parent aed9c09091
commit 6bafd0a09b
9 changed files with 31 additions and 30 deletions
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2
examples/benchmarks/README.md
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@@ -9,7 +9,7 @@ Here are the results of each benchmark model running on Qlib's `Alpha360` and `A
The numbers shown below demonstrate the performance of the entire `workflow` of each model. We will update the `workflow` as well as models in the near future for better results.
<!--
> If you need to reproduce the results below, please use the **v1** dataset: `python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/qlib_cn_1d --region cn --version v1`
> If you need to reproduce the results below, please use the **v1** dataset: `python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn --version v1`
>
> In the new version of qlib, the default dataset is **v2**. Since the data is collected from the YahooFinance API (which is not very stable), the results of *v2* and *v1* may differ -->

2
examples/highfreq/workflow.py
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@@ -82,7 +82,7 @@ class HighfreqWorkflow:
def _init_qlib(self):
"""initialize qlib"""
# use yahoo_cn_1min data
# use cn_data_1min data
QLIB_INIT_CONFIG = {**HIGH_FREQ_CONFIG, **self.SPEC_CONF}
provider_uri = QLIB_INIT_CONFIG.get("provider_uri")
GetData().qlib_data(target_dir=provider_uri, interval="1min", region=REG_CN, exists_skip=True)