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fix break img

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Linlang
2024-08-14 13:40:17 +08:00
parent 9e635168c0
commit b9fc79b4ba
2 changed files with 9 additions and 9 deletions
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16
README.md
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@@ -309,19 +309,19 @@ Qlib provides a tool named `qrun` to run the whole workflow automatically (inclu
2. Graphical Reports Analysis: Run `examples/workflow_by_code.ipynb` with `jupyter notebook` to get graphical reports 2. Graphical Reports Analysis: Run `examples/workflow_by_code.ipynb` with `jupyter notebook` to get graphical reports
- Forecasting signal (model prediction) analysis - Forecasting signal (model prediction) analysis
- Cumulative Return of groups - Cumulative Return of groups
![Cumulative Return](http://fintech.msra.cn/images_v070/analysis/analysis_model_cumulative_return.png?v=0.1) ![Cumulative Return](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_cumulative_return.png)
- Return distribution - Return distribution
![long_short](http://fintech.msra.cn/images_v070/analysis/analysis_model_long_short.png?v=0.1) ![long_short](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_long_short.png)
- Information Coefficient (IC) - Information Coefficient (IC)
![Information Coefficient](http://fintech.msra.cn/images_v070/analysis/analysis_model_IC.png?v=0.1) ![Information Coefficient](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_IC.png)
![Monthly IC](http://fintech.msra.cn/images_v070/analysis/analysis_model_monthly_IC.png?v=0.1) ![Monthly IC](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_monthly_IC.png)
![IC](http://fintech.msra.cn/images_v070/analysis/analysis_model_NDQ.png?v=0.1) ![IC](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_NDQ.png)
- Auto Correlation of forecasting signal (model prediction) - Auto Correlation of forecasting signal (model prediction)
![Auto Correlation](http://fintech.msra.cn/images_v070/analysis/analysis_model_auto_correlation.png?v=0.1) ![Auto Correlation](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/analysis_model_auto_correlation.png)
- Portfolio analysis - Portfolio analysis
- Backtest return - Backtest return
![Report](http://fintech.msra.cn/images_v070/analysis/report.png?v=0.1) ![Report](https://github.com/microsoft/qlib/blob/main/docs/_static/img/analysis/report.png)
<!-- <!--
- Score IC - Score IC
![Score IC](docs/_static/img/score_ic.png) ![Score IC](docs/_static/img/score_ic.png)
@@ -500,7 +500,7 @@ Qlib data are stored in a compact format, which is efficient to be combined into
Join IM discussion groups: Join IM discussion groups:
|[Gitter](https://gitter.im/Microsoft/qlib)| |[Gitter](https://gitter.im/Microsoft/qlib)|
|----| |----|
|![image](http://fintech.msra.cn/images_v070/qrcode/gitter_qr.png)| |![image](https://github.com/microsoft/qlib/blob/main/docs/_static/img/qrcode/gitter_qr.png)|
# Contributing # Contributing
We appreciate all contributions and thank all the contributors! We appreciate all contributions and thank all the contributors!

2
qlib/contrib/model/pytorch_hist.py
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@@ -256,7 +256,7 @@ class HIST(Model):
raise ValueError("Empty data from dataset, please check your dataset config.") raise ValueError("Empty data from dataset, please check your dataset config.")
if not os.path.exists(self.stock2concept): if not os.path.exists(self.stock2concept):
url = "http://fintech.msra.cn/stock_data/downloads/qlib_csi300_stock2concept.npy" url = "https://github.com/SunsetWolf/qlib_dataset/releases/download/v0/qlib_csi300_stock2concept.npy"
urllib.request.urlretrieve(url, self.stock2concept) urllib.request.urlretrieve(url, self.stock2concept)
stock_index = np.load(self.stock_index, allow_pickle=True).item() stock_index = np.load(self.stock_index, allow_pickle=True).item()