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https://github.com/microsoft/qlib.git
synced 2026-07-06 20:41:09 +08:00
Fix and update run_all_model
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@@ -54,7 +54,6 @@ task:
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batch_size: 800
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metric: loss
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loss: mse
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seed: 0
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GPU: 0
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rnn_type: GRU
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dataset:
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@@ -56,7 +56,6 @@ task:
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base_model: LSTM
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with_pretrain: True
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model_path: "benchmarks/LSTM/model_lstm_csi300.pkl"
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seed: 0
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GPU: 0
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dataset:
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class: DatasetH
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@@ -54,7 +54,6 @@ task:
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batch_size: 800
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metric: loss
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loss: mse
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seed: 0
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GPU: 0
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dataset:
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class: DatasetH
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@@ -54,7 +54,6 @@ task:
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batch_size: 800
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metric: loss
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loss: mse
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seed: 0
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GPU: 0
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dataset:
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class: DatasetH
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@@ -58,7 +58,6 @@ task:
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loss: mse
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optimizer: adam
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GPU: 1
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seed: 710
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dataset:
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class: DatasetH
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module_path: qlib.data.dataset
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@@ -152,6 +152,10 @@ def get_all_results(folders) -> dict:
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result["annualized_return_with_cost"] = list()
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result["information_ratio_with_cost"] = list()
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result["max_drawdown_with_cost"] = list()
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result["ic"] = list()
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result["icir"] = list()
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result["rank_ic"] = list()
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result["rank_icir"] = list()
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for recorder_id in recorders:
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if recorders[recorder_id].status == "FINISHED":
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recorder = R.get_recorder(recorder_id=recorder_id, experiment_name=fn)
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@@ -159,19 +163,27 @@ def get_all_results(folders) -> dict:
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result["annualized_return_with_cost"].append(metrics["excess_return_with_cost.annualized_return"])
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result["information_ratio_with_cost"].append(metrics["excess_return_with_cost.information_ratio"])
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result["max_drawdown_with_cost"].append(metrics["excess_return_with_cost.max_drawdown"])
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result["ic"].append(metrics["IC"])
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result["icir"].append(metrics["ICIR"])
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result["rank_ic"].append(metrics["Rank IC"])
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result["rank_icir"].append(metrics["Rank ICIR"])
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results[fn] = result
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return results
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# function to generate and save markdown table
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def gen_and_save_md_table(metrics):
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table = "| Model Name | Annualized Return | Information Ratio | Max Drawdown |\n"
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table += "|---|---|---|---|\n"
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table = "| Model Name | Annualized Return | Information Ratio | Max Drawdown | IC | ICIR | Rank IC | Rank ICIR |\n"
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table += "|---|---|---|---|---|---|---|---|\n"
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for fn in metrics:
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ar = metrics[fn]["annualized_return_with_cost"]
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ir = metrics[fn]["information_ratio_with_cost"]
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md = metrics[fn]["max_drawdown_with_cost"]
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table += f"| {fn} | {ar[0]:9.4f}±{ar[1]:9.2f} | {ir[0]:9.4f}±{ir[1]:9.2f}| {md[0]:9.4f}±{md[1]:9.2f} |\n"
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ic = metrics[fn]["ic"]
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icir = metrics[fn]["icir"]
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ric = metrics[fn]["rank_ic"]
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ricir = metrics[fn]["rank_icir"]
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table += f"| {fn} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} |\n"
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pprint(table)
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with open("table.md", "w") as f:
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f.write(table)
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@@ -240,6 +252,7 @@ def run(times=1, models=None, exclude=False):
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sys.stderr.write("\n")
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# install qlib
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sys.stderr.write("Installing qlib...\n")
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execute(f"{python_path} -m pip install --upgrade pip") # TODO: FIX ME!
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execute(f"{python_path} -m pip install --upgrade cython") # TODO: FIX ME!
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if fn == "TFT":
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execute(
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