Qlib - 模型训练和预测(Model Training & Prediction)

# 合并后的完整脚本：训练模型 + 计算 IC 指标

# reference: https://qlib.readthedocs.io/en/latest/component/model.html



import qlib

import pandas as pd

from qlib.contrib.model.gbdt import LGBModel

from qlib.contrib.data.handler import Alpha158

from qlib.utils import init_instance_by_config, flatten_dict

from qlib.workflow import R

from qlib.workflow.record_temp import SignalRecord, PortAnaRecord

from qlib.contrib.eva.alpha import calc_ic



# 初始化 Qlib 数据路径

qlib.init(provider_uri="~/Documents/code/my_develop/qlib_data/cn_data_snapshot", region="cn")



market = "csi300"

benchmark = "SH000300"



# 数据处理器配置

data_handler_config = {

    "start_time": "2008-01-01",

    "end_time": "2020-08-01",

    "fit_start_time": "2008-01-01",

    "fit_end_time": "2014-12-31",

    "instruments": market,

}

# 任务配置：模型 + 数据集

task = {

    "model": {

        "class": "LGBModel",

        "module_path": "qlib.contrib.model.gbdt",

        "kwargs": {

            "loss": "mse",

            "colsample_bytree": 0.8879,

            "learning_rate": 0.0421,

            "subsample": 0.8789,

            "lambda_l1": 205.6999,

            "lambda_l2": 580.9768,

            "max_depth": 8,

            "num_leaves": 210,

            "num_threads": 20,

        },

    },

    "dataset": {

        "class": "DatasetH",

        "module_path": "qlib.data.dataset",

        "kwargs": {

            "handler": {

                "class": "Alpha158",

                "module_path": "qlib.contrib.data.handler",

                "kwargs": data_handler_config,

            },

            "segments": {

                "train": ("2008-01-01", "2014-12-31"),

                "valid": ("2015-01-01", "2016-12-31"),

                "test": ("2017-01-01", "2020-08-01"),

            },

        },

    },

}

def main():

    print("【Step 1】初始化模型和数据集...")

    model = init_instance_by_config(task["model"])

    dataset = init_instance_by_config(task["dataset"])



    print("【Step 2】启动实验并训练模型...")

    with R.start(experiment_name="workflow"):

        R.log_params(**flatten_dict(task))

        model.fit(dataset)

        print("【Step 3】生成预测信号...")

        recorder = R.get_recorder()

        sr = SignalRecord(model, dataset, recorder)

        sr.generate()



        print("【Step 4】获取当前实验的 recorder_id，用于后续读取结果...")

        recorder_id = recorder.id

        print(f"当前实验的 recorder_id 为：{recorder_id}")

    # 使用 recorder_id 读取预测结果

    print("【Step 5】读取预测结果并计算 IC...")

    recorder = R.get_recorder(experiment_name="workflow", recorder_id=recorder_id)

    print("已保存的 artifacts：", recorder.list_artifacts())



    # 获取 artifact 路径

    artifact_path = recorder.artifact_uri.replace("file://", "")

    pred = pd.read_pickle(f"{artifact_path}/pred.pkl")

    label = pd.read_pickle(f"{artifact_path}/label.pkl")



    print("预测结果（前5行）：")

    print(pred.head())

    print("预测结果（后5行）：")

    print(pred.tail())

    print("预测结果时间范围：", pred.index.get_level_values('datetime').unique())



    print("标签结果（前5行）：")

    print(label.head())

    print("标签结果（后5行）：")

    print(label.tail())



    # 计算 IC

    ic = calc_ic(pred['score'], label['LABEL0'])



    print("【Step 6】IC 指标统计：")

    print("IC 均值：", ic[0].mean())

    print("IC 标准差：", ic[0].std())

    print("IC 绝对值均值：", ic[0].abs().mean())

    print("Rank IC 均值：", ic[1].mean())

    print("Rank IC 标准差：", ic[1].std())

    print("Rank IC 绝对值均值：", ic[1].abs().mean())



if __name__ == '__main__':

    main()

(freq) test1@budas-MacBook-Pro user % python qlib_model_demo.py

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

[56122:MainThread](2025-10-18 11:31:21,785) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56122:MainThread](2025-10-18 11:31:21,795) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56122:MainThread](2025-10-18 11:31:21,796) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

【Step 1】初始化模型和数据集...

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.



Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

[56133:MainThread](2025-10-18 11:31:28,381) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56131:MainThread](2025-10-18 11:31:28,382) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56136:MainThread](2025-10-18 11:31:28,382) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56135:MainThread](2025-10-18 11:31:28,383) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56132:MainThread](2025-10-18 11:31:28,384) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56134:MainThread](2025-10-18 11:31:28,385) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56133:MainThread](2025-10-18 11:31:28,388) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56136:MainThread](2025-10-18 11:31:28,388) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56133:MainThread](2025-10-18 11:31:28,388) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56136:MainThread](2025-10-18 11:31:28,388) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56135:MainThread](2025-10-18 11:31:28,389) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56131:MainThread](2025-10-18 11:31:28,389) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56135:MainThread](2025-10-18 11:31:28,389) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56131:MainThread](2025-10-18 11:31:28,389) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56134:MainThread](2025-10-18 11:31:28,390) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56132:MainThread](2025-10-18 11:31:28,390) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56134:MainThread](2025-10-18 11:31:28,390) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56132:MainThread](2025-10-18 11:31:28,390) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. CatBoostModel are skipped. (optional: maybe installing CatBoostModel can fix it.)

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError. XGBModel is skipped(optional: maybe installing xgboost can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

ModuleNotFoundError.  PyTorch models are skipped (optional: maybe installing pytorch can fix it).

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.

Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.

Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.

See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.

[56222:MainThread](2025-10-18 11:32:31,653) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56223:MainThread](2025-10-18 11:32:31,653) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56226:MainThread](2025-10-18 11:32:31,653) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56225:MainThread](2025-10-18 11:32:31,653) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56224:MainThread](2025-10-18 11:32:31,654) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56227:MainThread](2025-10-18 11:32:31,657) INFO - qlib.Initialization - [config.py:452] - default_conf: client.

[56223:MainThread](2025-10-18 11:32:31,658) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56226:MainThread](2025-10-18 11:32:31,658) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56225:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56222:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56223:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56225:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56226:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56222:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56224:MainThread](2025-10-18 11:32:31,659) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56224:MainThread](2025-10-18 11:32:31,660) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56227:MainThread](2025-10-18 11:32:31,661) INFO - qlib.Initialization - [__init__.py:75] - qlib successfully initialized based on client settings.

[56227:MainThread](2025-10-18 11:32:31,662) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56122:MainThread](2025-10-18 11:32:34,882) INFO - qlib.timer - [log.py:127] - Time cost: 73.083s | Loading data Done

[56122:MainThread](2025-10-18 11:32:36,646) INFO - qlib.timer - [log.py:127] - Time cost: 0.462s | DropnaLabel Done

[56122:MainThread](2025-10-18 11:32:39,763) INFO - qlib.timer - [log.py:127] - Time cost: 3.116s | CSZScoreNorm Done

[56122:MainThread](2025-10-18 11:32:39,826) INFO - qlib.timer - [log.py:127] - Time cost: 4.943s | fit & process data Done

[56122:MainThread](2025-10-18 11:32:39,827) INFO - qlib.timer - [log.py:127] - Time cost: 78.029s | Init data Done

【Step 2】启动实验并训练模型...

[56122:MainThread](2025-10-18 11:32:39,849) INFO - qlib.workflow - [exp.py:258] - Experiment 376922499957687719 starts running ...

[56122:MainThread](2025-10-18 11:32:40,631) INFO - qlib.workflow - [recorder.py:345] - Recorder 09c2896631e24499baebacb64603256c starts running under Experiment 376922499957687719 ...

warning: Not a git repository. Use --no-index to compare two paths outside a working tree

usage: git diff --no-index [<options>] <path> <path>



Diff output format options

    -p, --patch           generate patch

    -s, --no-patch        suppress diff output

    -u                    generate patch

    -U, --unified[=<n>]   generate diffs with <n> lines context

    -W, --function-context

                          generate diffs with <n> lines context

    --raw                 generate the diff in raw format

    --patch-with-raw      synonym for '-p --raw'

    --patch-with-stat     synonym for '-p --stat'

    --numstat             machine friendly --stat

    --shortstat           output only the last line of --stat

    -X, --dirstat[=<param1,param2>...]

                          output the distribution of relative amount of changes for each sub-directory

    --cumulative          synonym for --dirstat=cumulative

    --dirstat-by-file[=<param1,param2>...]

                          synonym for --dirstat=files,param1,param2...

    --check               warn if changes introduce conflict markers or whitespace errors

    --summary             condensed summary such as creations, renames and mode changes

    --name-only           show only names of changed files

    --name-status         show only names and status of changed files

    --stat[=<width>[,<name-width>[,<count>]]]

                          generate diffstat

    --stat-width <width>  generate diffstat with a given width

    --stat-name-width <width>

                          generate diffstat with a given name width

    --stat-graph-width <width>

                          generate diffstat with a given graph width

    --stat-count <count>  generate diffstat with limited lines

    --compact-summary     generate compact summary in diffstat

    --binary              output a binary diff that can be applied

    --full-index          show full pre- and post-image object names on the "index" lines

    --color[=<when>]      show colored diff

    --ws-error-highlight <kind>

                          highlight whitespace errors in the 'context', 'old' or 'new' lines in the diff

    -z                    do not munge pathnames and use NULs as output field terminators in --raw or --numstat

    --abbrev[=<n>]        use <n> digits to display object names

    --src-prefix <prefix>

                          show the given source prefix instead of "a/"

    --dst-prefix <prefix>

                          show the given destination prefix instead of "b/"

    --line-prefix <prefix>

                          prepend an additional prefix to every line of output

    --no-prefix           do not show any source or destination prefix

    --inter-hunk-context <n>

                          show context between diff hunks up to the specified number of lines

    --output-indicator-new <char>

                          specify the character to indicate a new line instead of '+'

    --output-indicator-old <char>

                          specify the character to indicate an old line instead of '-'

    --output-indicator-context <char>

                          specify the character to indicate a context instead of ' '



Diff rename options

    -B, --break-rewrites[=<n>[/<m>]]

                          break complete rewrite changes into pairs of delete and create

    -M, --find-renames[=<n>]

                          detect renames

    -D, --irreversible-delete

                          omit the preimage for deletes

    -C, --find-copies[=<n>]

                          detect copies

    --find-copies-harder  use unmodified files as source to find copies

    --no-renames          disable rename detection

    --rename-empty        use empty blobs as rename source

    --follow              continue listing the history of a file beyond renames

    -l <n>                prevent rename/copy detection if the number of rename/copy targets exceeds given limit



Diff algorithm options

    --minimal             produce the smallest possible diff

    -w, --ignore-all-space

                          ignore whitespace when comparing lines

    -b, --ignore-space-change

                          ignore changes in amount of whitespace

    --ignore-space-at-eol

                          ignore changes in whitespace at EOL

    --ignore-cr-at-eol    ignore carrier-return at the end of line

    --ignore-blank-lines  ignore changes whose lines are all blank

    -I, --ignore-matching-lines <regex>

                          ignore changes whose all lines match <regex>

    --indent-heuristic    heuristic to shift diff hunk boundaries for easy reading

    --patience            generate diff using the "patience diff" algorithm

    --histogram           generate diff using the "histogram diff" algorithm

    --diff-algorithm <algorithm>

                          choose a diff algorithm

    --anchored <text>     generate diff using the "anchored diff" algorithm

    --word-diff[=<mode>]  show word diff, using <mode> to delimit changed words

    --word-diff-regex <regex>

                          use <regex> to decide what a word is

    --color-words[=<regex>]

                          equivalent to --word-diff=color --word-diff-regex=<regex>

    --color-moved[=<mode>]

                          moved lines of code are colored differently

    --color-moved-ws <mode>

                          how white spaces are ignored in --color-moved



Other diff options

    --relative[=<prefix>]

                          when run from subdir, exclude changes outside and show relative paths

    -a, --text            treat all files as text

    -R                    swap two inputs, reverse the diff

    --exit-code           exit with 1 if there were differences, 0 otherwise

    --quiet               disable all output of the program

    --ext-diff            allow an external diff helper to be executed

    --textconv            run external text conversion filters when comparing binary files

    --ignore-submodules[=<when>]

                          ignore changes to submodules in the diff generation

    --submodule[=<format>]

                          specify how differences in submodules are shown

    --ita-invisible-in-index

                          hide 'git add -N' entries from the index

    --ita-visible-in-index

                          treat 'git add -N' entries as real in the index

    -S <string>           look for differences that change the number of occurrences of the specified string

    -G <regex>            look for differences that change the number of occurrences of the specified regex

    --pickaxe-all         show all changes in the changeset with -S or -G

    --pickaxe-regex       treat <string> in -S as extended POSIX regular expression

    -O <file>             control the order in which files appear in the output

    --rotate-to <path>    show the change in the specified path first

    --skip-to <path>      skip the output to the specified path

    --find-object <object-id>

                          look for differences that change the number of occurrences of the specified object

    --diff-filter [(A|C|D|M|R|T|U|X|B)...[*]]

                          select files by diff type

    --output <file>       Output to a specific file



[56122:MainThread](2025-10-18 11:32:40,664) INFO - qlib.workflow - [recorder.py:378] - Fail to log the uncommitted code of $CWD(/Users/test1/Documents/code/my_develop/qlib_data/user) when run git diff.

fatal: not a git repository (or any of the parent directories): .git

[56122:MainThread](2025-10-18 11:32:40,693) INFO - qlib.workflow - [recorder.py:378] - Fail to log the uncommitted code of $CWD(/Users/test1/Documents/code/my_develop/qlib_data/user) when run git status.

error: unknown option `cached'

usage: git diff --no-index [<options>] <path> <path>



Diff output format options

    -p, --patch           generate patch

    -s, --no-patch        suppress diff output

    -u                    generate patch

    -U, --unified[=<n>]   generate diffs with <n> lines context

    -W, --function-context

                          generate diffs with <n> lines context

    --raw                 generate the diff in raw format

    --patch-with-raw      synonym for '-p --raw'

    --patch-with-stat     synonym for '-p --stat'

    --numstat             machine friendly --stat

    --shortstat           output only the last line of --stat

    -X, --dirstat[=<param1,param2>...]

                          output the distribution of relative amount of changes for each sub-directory

    --cumulative          synonym for --dirstat=cumulative

    --dirstat-by-file[=<param1,param2>...]

                          synonym for --dirstat=files,param1,param2...

    --check               warn if changes introduce conflict markers or whitespace errors

    --summary             condensed summary such as creations, renames and mode changes

    --name-only           show only names of changed files

    --name-status         show only names and status of changed files

    --stat[=<width>[,<name-width>[,<count>]]]

                          generate diffstat

    --stat-width <width>  generate diffstat with a given width

    --stat-name-width <width>

                          generate diffstat with a given name width

    --stat-graph-width <width>

                          generate diffstat with a given graph width

    --stat-count <count>  generate diffstat with limited lines

    --compact-summary     generate compact summary in diffstat

    --binary              output a binary diff that can be applied

    --full-index          show full pre- and post-image object names on the "index" lines

    --color[=<when>]      show colored diff

    --ws-error-highlight <kind>

                          highlight whitespace errors in the 'context', 'old' or 'new' lines in the diff

    -z                    do not munge pathnames and use NULs as output field terminators in --raw or --numstat

    --abbrev[=<n>]        use <n> digits to display object names

    --src-prefix <prefix>

                          show the given source prefix instead of "a/"

    --dst-prefix <prefix>

                          show the given destination prefix instead of "b/"

    --line-prefix <prefix>

                          prepend an additional prefix to every line of output

    --no-prefix           do not show any source or destination prefix

    --inter-hunk-context <n>

                          show context between diff hunks up to the specified number of lines

    --output-indicator-new <char>

                          specify the character to indicate a new line instead of '+'

    --output-indicator-old <char>

                          specify the character to indicate an old line instead of '-'

    --output-indicator-context <char>

                          specify the character to indicate a context instead of ' '



Diff rename options

    -B, --break-rewrites[=<n>[/<m>]]

                          break complete rewrite changes into pairs of delete and create

    -M, --find-renames[=<n>]

                          detect renames

    -D, --irreversible-delete

                          omit the preimage for deletes

    -C, --find-copies[=<n>]

                          detect copies

    --find-copies-harder  use unmodified files as source to find copies

    --no-renames          disable rename detection

    --rename-empty        use empty blobs as rename source

    --follow              continue listing the history of a file beyond renames

    -l <n>                prevent rename/copy detection if the number of rename/copy targets exceeds given limit



Diff algorithm options

    --minimal             produce the smallest possible diff

    -w, --ignore-all-space

                          ignore whitespace when comparing lines

    -b, --ignore-space-change

                          ignore changes in amount of whitespace

    --ignore-space-at-eol

                          ignore changes in whitespace at EOL

    --ignore-cr-at-eol    ignore carrier-return at the end of line

    --ignore-blank-lines  ignore changes whose lines are all blank

    -I, --ignore-matching-lines <regex>

                          ignore changes whose all lines match <regex>

    --indent-heuristic    heuristic to shift diff hunk boundaries for easy reading

    --patience            generate diff using the "patience diff" algorithm

    --histogram           generate diff using the "histogram diff" algorithm

    --diff-algorithm <algorithm>

                          choose a diff algorithm

    --anchored <text>     generate diff using the "anchored diff" algorithm

    --word-diff[=<mode>]  show word diff, using <mode> to delimit changed words

    --word-diff-regex <regex>

                          use <regex> to decide what a word is

    --color-words[=<regex>]

                          equivalent to --word-diff=color --word-diff-regex=<regex>

    --color-moved[=<mode>]

                          moved lines of code are colored differently

    --color-moved-ws <mode>

                          how white spaces are ignored in --color-moved



Other diff options

    --relative[=<prefix>]

                          when run from subdir, exclude changes outside and show relative paths

    -a, --text            treat all files as text

    -R                    swap two inputs, reverse the diff

    --exit-code           exit with 1 if there were differences, 0 otherwise

    --quiet               disable all output of the program

    --ext-diff            allow an external diff helper to be executed

    --textconv            run external text conversion filters when comparing binary files

    --ignore-submodules[=<when>]

                          ignore changes to submodules in the diff generation

    --submodule[=<format>]

                          specify how differences in submodules are shown

    --ita-invisible-in-index

                          hide 'git add -N' entries from the index

    --ita-visible-in-index

                          treat 'git add -N' entries as real in the index

    -S <string>           look for differences that change the number of occurrences of the specified string

    -G <regex>            look for differences that change the number of occurrences of the specified regex

    --pickaxe-all         show all changes in the changeset with -S or -G

    --pickaxe-regex       treat <string> in -S as extended POSIX regular expression

    -O <file>             control the order in which files appear in the output

    --rotate-to <path>    show the change in the specified path first

    --skip-to <path>      skip the output to the specified path

    --find-object <object-id>

                          look for differences that change the number of occurrences of the specified object

    --diff-filter [(A|C|D|M|R|T|U|X|B)...[*]]

                          select files by diff type

    --output <file>       Output to a specific file



[56122:MainThread](2025-10-18 11:32:40,721) INFO - qlib.workflow - [recorder.py:378] - Fail to log the uncommitted code of $CWD(/Users/test1/Documents/code/my_develop/qlib_data/user) when run git diff --cached.

Training until validation scores don't improve for 50 rounds

[20]    train's l2: 0.990585    valid's l2: 0.99431

[40]    train's l2: 0.986931    valid's l2: 0.993693

[60]    train's l2: 0.984352    valid's l2: 0.99349

[80]    train's l2: 0.982319    valid's l2: 0.993382

[100]   train's l2: 0.980442    valid's l2: 0.99331

[120]   train's l2: 0.97871 valid's l2: 0.993247

[140]   train's l2: 0.976987    valid's l2: 0.993334

[160]   train's l2: 0.97536 valid's l2: 0.993338

Early stopping, best iteration is:

[122]   train's l2: 0.978519    valid's l2: 0.993238

【Step 3】生成预测信号...

[56122:MainThread](2025-10-18 11:33:25,686) INFO - qlib.workflow - [record_temp.py:198] - Signal record 'pred.pkl' has been saved as the artifact of the Experiment 376922499957687719

'The following are prediction results of the LGBModel model.'

                          score

datetime   instrument

2017-01-03 SH600000   -0.042865

           SH600008    0.005925

           SH600009    0.030596

           SH600010   -0.013973

           SH600015   -0.141758

【Step 4】获取当前实验的 recorder_id，用于后续读取结果...

当前实验的 recorder_id 为：09c2896631e24499baebacb64603256c

[56122:MainThread](2025-10-18 11:33:25,736) INFO - qlib.timer - [log.py:127] - Time cost: 0.000s | waiting `async_log` Done

【Step 5】读取预测结果并计算 IC...

已保存的 artifacts： ['label.pkl', 'pred.pkl']

预测结果（前5行）：

                          score

datetime   instrument

2017-01-03 SH600000   -0.042865

           SH600008    0.005925

           SH600009    0.030596

           SH600010   -0.013973

           SH600015   -0.141758

预测结果（后5行）：

                          score

datetime   instrument

2020-07-31 SZ300413   -0.078162

           SZ300433   -0.101778

           SZ300498   -0.054418

           SZ300601   -0.147531

           SZ300628    0.030925

预测结果时间范围： DatetimeIndex(['2017-01-03', '2017-01-04', '2017-01-05', '2017-01-06',

               '2017-01-09', '2017-01-10', '2017-01-11', '2017-01-12',

               '2017-01-13', '2017-01-16',

               ...

               '2020-07-20', '2020-07-21', '2020-07-22', '2020-07-23',

               '2020-07-24', '2020-07-27', '2020-07-28', '2020-07-29',

               '2020-07-30', '2020-07-31'],

              dtype='datetime64[ns]', name='datetime', length=871, freq=None)

标签结果（前5行）：

                         LABEL0

datetime   instrument

2017-01-03 SH600000   -0.001831

           SH600008   -0.002398

           SH600009    0.001493

           SH600010    0.003520

           SH600015   -0.007142

标签结果（后5行）：

                         LABEL0

datetime   instrument

2020-07-31 SZ300413   -0.037566

           SZ300433   -0.031677

           SZ300498   -0.006531

           SZ300601    0.090264

           SZ300628    0.004142

【Step 6】IC 指标统计：

IC 均值： 0.04993267859655785

IC 标准差： 0.12446777545374337

IC 绝对值均值： 0.10684702003092757

Rank IC 均值： 0.051507508261451146

Rank IC 标准差： 0.12273969195405407

Rank IC 绝对值均值： 0.10527763281820797

(freq) test1@budas-MacBook-Pro user %

[56227:MainThread](2025-10-18 11:32:31,662) INFO - qlib.Initialization - [__init__.py:77] - data_path={'__DEFAULT_FREQ': PosixPath('/Users/test1/Documents/code/my_develop/qlib_data/cn_data_snapshot')}

[56122:MainThread](2025-10-18 11:32:34,882) INFO - qlib.timer - [log.py:127] - Time cost: 73.083s | Loading data Done

[56122:MainThread](2025-10-18 11:32:36,646) INFO - qlib.timer - [log.py:127] - Time cost: 0.462s | DropnaLabel Done

[56122:MainThread](2025-10-18 11:32:39,763) INFO - qlib.timer - [log.py:127] - Time cost: 3.116s | CSZScoreNorm Done

[56122:MainThread](2025-10-18 11:32:39,826) INFO - qlib.timer - [log.py:127] - Time cost: 4.943s | fit & process data Done

[56122:MainThread](2025-10-18 11:32:39,827) INFO - qlib.timer - [log.py:127] - Time cost: 78.029s | Init data Done

【Step 2】启动实验并训练模型...

[56122:MainThread](2025-10-18 11:32:39,849) INFO - qlib.workflow - [exp.py:258] - Experiment 376922499957687719 starts running ...

[56122:MainThread](2025-10-18 11:32:40,631) INFO - qlib.workflow - [recorder.py:345] - Recorder 09c2896631e24499baebacb64603256c starts running under Experiment 376922499957687719 ...



...

[56122:MainThread](2025-10-18 11:32:40,721) INFO - qlib.workflow - [recorder.py:378] - Fail to log the uncommitted code of $CWD(/Users/test1/Documents/code/my_develop/qlib_data/user) when run git diff --cached.

Training until validation scores don't improve for 50 rounds

[20]    train's l2: 0.990585    valid's l2: 0.99431

[40]    train's l2: 0.986931    valid's l2: 0.993693

[60]    train's l2: 0.984352    valid's l2: 0.99349

[80]    train's l2: 0.982319    valid's l2: 0.993382

[100]   train's l2: 0.980442    valid's l2: 0.99331

[120]   train's l2: 0.97871 valid's l2: 0.993247

[140]   train's l2: 0.976987    valid's l2: 0.993334

[160]   train's l2: 0.97536 valid's l2: 0.993338

Early stopping, best iteration is:

[122]   train's l2: 0.978519    valid's l2: 0.993238

【Step 3】生成预测信号...

[56122:MainThread](2025-10-18 11:33:25,686) INFO - qlib.workflow - [record_temp.py:198] - Signal record 'pred.pkl' has been saved as the artifact of the Experiment 376922499957687719

'The following are prediction results of the LGBModel model.'

                          score

datetime   instrument

2017-01-03 SH600000   -0.042865

           SH600008    0.005925

           SH600009    0.030596

           SH600010   -0.013973

           SH600015   -0.141758

【Step 4】获取当前实验的 recorder_id，用于后续读取结果...

当前实验的 recorder_id 为：09c2896631e24499baebacb64603256c

[56122:MainThread](2025-10-18 11:33:25,736) INFO - qlib.timer - [log.py:127] - Time cost: 0.000s | waiting `async_log` Done

【Step 5】读取预测结果并计算 IC...

已保存的 artifacts： ['label.pkl', 'pred.pkl']

预测结果（前5行）：

                          score

datetime   instrument

2017-01-03 SH600000   -0.042865

           SH600008    0.005925

           SH600009    0.030596

           SH600010   -0.013973

           SH600015   -0.141758

预测结果（后5行）：

                          score

datetime   instrument

2020-07-31 SZ300413   -0.078162

           SZ300433   -0.101778

           SZ300498   -0.054418

           SZ300601   -0.147531

           SZ300628    0.030925

预测结果时间范围： DatetimeIndex(['2017-01-03', '2017-01-04', '2017-01-05', '2017-01-06',

               '2017-01-09', '2017-01-10', '2017-01-11', '2017-01-12',

               '2017-01-13', '2017-01-16',

               ...

               '2020-07-20', '2020-07-21', '2020-07-22', '2020-07-23',

               '2020-07-24', '2020-07-27', '2020-07-28', '2020-07-29',

               '2020-07-30', '2020-07-31'],

              dtype='datetime64[ns]', name='datetime', length=871, freq=None)

标签结果（前5行）：

                         LABEL0

datetime   instrument

2017-01-03 SH600000   -0.001831

           SH600008   -0.002398

           SH600009    0.001493

           SH600010    0.003520

           SH600015   -0.007142

标签结果（后5行）：

                         LABEL0

datetime   instrument

2020-07-31 SZ300413   -0.037566

           SZ300433   -0.031677

           SZ300498   -0.006531

           SZ300601    0.090264

           SZ300628    0.004142

【Step 6】IC 指标统计：

IC 均值： 0.04993267859655785

IC 标准差： 0.12446777545374337

IC 绝对值均值： 0.10684702003092757

Rank IC 均值： 0.051507508261451146

Rank IC 标准差： 0.12273969195405407

Rank IC 绝对值均值： 0.10527763281820797