download orderbook data (#1754)

* download orderbook data

* fix CI error

* fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* test fix CI error

* optimize get_data code

* optimize get_data code

* optimize get_data code

* optimize README

---------

Co-authored-by: Linlang <v-linlanglv@microsoft.com>

qlib/model/ens/ensemble.py

@@ -30,7 +30,6 @@ class Ensemble:
 
 
 class SingleKeyEnsemble(Ensemble):
-
     """
     Extract the object if there is only one key and value in the dict. Make the result more readable.
     {Only key: Only value} -> Only value
@@ -64,7 +63,6 @@ class SingleKeyEnsemble(Ensemble):
 
 
 class RollingEnsemble(Ensemble):
-
     """Merge a dict of rolling dataframe like `prediction` or `IC` into an ensemble.
 
     NOTE: The values of dict must be pd.DataFrame, and have the index "datetime".

qlib/model/riskmodel/shrink.py

@@ -247,9 +247,7 @@ class ShrinkCovEstimator(RiskModel):
         v1 = y.T.dot(z) / t - cov_mkt[:, None] * S
         roff1 = np.sum(v1 * cov_mkt[:, None].T) / var_mkt - np.sum(np.diag(v1) * cov_mkt) / var_mkt
         v3 = z.T.dot(z) / t - var_mkt * S
-        roff3 = (
-            np.sum(v3 * np.outer(cov_mkt, cov_mkt)) / var_mkt**2 - np.sum(np.diag(v3) * cov_mkt**2) / var_mkt**2
-        )
+        roff3 = np.sum(v3 * np.outer(cov_mkt, cov_mkt)) / var_mkt**2 - np.sum(np.diag(v3) * cov_mkt**2) / var_mkt**2
         roff = 2 * roff1 - roff3
         rho = rdiag + roff