xautodl/exps/trading/organize_results.py

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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.02 #
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# python exps/trading/organize_results.py
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import sys, argparse
import numpy as np
from typing import List, Text
from collections import defaultdict, OrderedDict
from pathlib import Path
from pprint import pprint
import ruamel.yaml as yaml

lib_dir = (Path(__file__).parent / ".." / ".." / "lib").resolve()
if str(lib_dir) not in sys.path:
    sys.path.insert(0, str(lib_dir))

import qlib
from qlib.config import REG_CN
from qlib.workflow import R


class QResult:
    def __init__(self):
        self._result = defaultdict(list)

    def append(self, key, value):
        self._result[key].append(value)

    @property
    def result(self):
        return self._result

    def update(self, metrics, filter_keys=None):
        for key, value in metrics.items():
            if filter_keys is not None and key in filter_keys:
                key = filter_keys[key]
            elif filter_keys is not None:
                continue
            self.append(key, value)

    @staticmethod
    def full_str(xstr, space):
        xformat = "{:" + str(space) + "s}"
        return xformat.format(str(xstr))

    @staticmethod
    def merge_dict(dict_list):
        new_dict = dict()
        for xkey in dict_list[0].keys():
            values = [x for xdict in dict_list for x in xdict[xkey]]
            new_dict[xkey] = values
        return new_dict

    def info(self, keys: List[Text], separate: Text = "", space: int = 25, verbose: bool = True):
        avaliable_keys = []
        for key in keys:
            if key not in self.result:
                print("There are invalid key [{:}].".format(key))
            else:
                avaliable_keys.append(key)
        head_str = separate.join([self.full_str(x, space) for x in avaliable_keys])
        values = []
        for key in avaliable_keys:
            current_values = self._result[key]
            mean = np.mean(current_values)
            std = np.std(current_values)
            values.append("{:.4f} $\pm$ {:.4f}".format(mean, std))
        value_str = separate.join([self.full_str(x, space) for x in values])
        if verbose:
            print(head_str)
            print(value_str)
        return head_str, value_str


def compare_results(heads, values, names, space=15, verbose=True, sort_key=False):
    for idx, x in enumerate(heads):
        assert x == heads[0], "[{:}] {:} vs {:}".format(idx, x, heads[0])
    new_head = QResult.full_str("Name", space) + heads[0]
    info_str_dict = dict(head=new_head, lines=[])
    for name, value in zip(names, values):
        xline = QResult.full_str(name, space) + value
        info_str_dict["lines"].append(xline)
    if verbose:
        print(info_str_dict["head"])
        if sort_key:
            lines = sorted(list(zip(values, info_str_dict["lines"])), key=lambda x: float(x[0].split(" ")[0]))
            lines = [x[1] for x in lines]
        else:
            lines = info_str_dict["lines"]
        for xline in lines:
            print(xline)
    return info_str_dict


def filter_finished(recorders):
    returned_recorders = dict()
    not_finished = 0
    for key, recorder in recorders.items():
        if recorder.status == "FINISHED":
            returned_recorders[key] = recorder
        else:
            not_finished += 1
    return returned_recorders, not_finished


def query_info(save_dir, verbose):
    R.reset_default_uri(save_dir)
    experiments = R.list_experiments()

    key_map = {
        "IC": "IC",
        "ICIR": "ICIR",
        "Rank IC": "Rank_IC",
        "Rank ICIR": "Rank_ICIR",
        "excess_return_with_cost.annualized_return": "Annualized_Return",
        "excess_return_with_cost.information_ratio": "Information_Ratio",
        "excess_return_with_cost.max_drawdown": "Max_Drawdown",
    }
    all_keys = list(key_map.values())

    if verbose:
        print("There are {:} experiments.".format(len(experiments)))
    head_strs, value_strs, names = [], [], []
    for idx, (key, experiment) in enumerate(experiments.items()):
        if experiment.id == "0":
            continue
        recorders = experiment.list_recorders()
        recorders, not_finished = filter_finished(recorders)
        if verbose:
            print(
                "====>>>> {:02d}/{:02d}-th experiment {:9s} has {:02d}/{:02d} finished recorders.".format(
                    idx, len(experiments), experiment.name, len(recorders), len(recorders) + not_finished
                )
            )
        result = QResult()
        for recorder_id, recorder in recorders.items():
            result.update(recorder.list_metrics(), key_map)
        head_str, value_str = result.info(all_keys, verbose=verbose)
        head_strs.append(head_str)
        value_strs.append(value_str)
        names.append(experiment.name)
    info_str_dict = compare_results(head_strs, value_strs, names, space=10, verbose=verbose)
    info_value_dict = dict(heads=head_strs, values=value_strs, names=names)
    return info_str_dict, info_value_dict


if __name__ == "__main__":

    parser = argparse.ArgumentParser("Show Results")

    def str2bool(v):
        if isinstance(v, bool):
            return v
        elif v.lower() in ("yes", "true", "t", "y", "1"):
            return True
        elif v.lower() in ("no", "false", "f", "n", "0"):
            return False
        else:
            raise argparse.ArgumentTypeError("Boolean value expected.")

    parser.add_argument(
        "--save_dir", type=str, nargs="+", default=["./outputs/qlib-baselines"], help="The checkpoint directory."
    )
    parser.add_argument("--verbose", type=str2bool, default=False, help="Print detailed log information or not")
    args = parser.parse_args()

    print("Show results of {:}".format(args.save_dir))

    provider_uri = "~/.qlib/qlib_data/cn_data"
    qlib.init(provider_uri=provider_uri, region=REG_CN)

    all_info_dict = []
    for save_dir in args.save_dir:
        _, info_dict = query_info(save_dir, args.verbose)
        all_info_dict.append(info_dict)
    info_dict = QResult.merge_dict(all_info_dict)
    compare_results(info_dict["heads"], info_dict["values"], info_dict["names"], space=15, verbose=True, sort_key=True)