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همه اسناد کتابخانه

طراحی ویژگی‌های مالی بر اساس فرضیه‌های اقتصادی و زمان‌بندی داده

کد یادگیری ماشین برای معامله‌گری

خلاصه

این فصل چارچوبی برای تبدیل یک ایده معاملاتی به مشخصات مستند ویژگی ارائه می‌کند. از پژوهشگران می‌خواهد افق ویژگی را با تصمیم موردنظر هم‌راستا کنند، فرضیه‌ای درباره محرک بیان کنند و سیگنال‌های پیش‌بین را از متغیرهای حالت زمینه‌ای متمایز سازند. انتخاب چارچوب مرجع، بازنمایی و تجمیع باید از ادعای اقتصادی پیروی کند؛ تبدیل‌هایی که فرضیه را تغییر می‌دهند باید از تبدیل‌هایی که عمدتاً نویز را کنترل می‌کنند متمایز شوند. این فصل ویژگی‌های قیمت و حجم، ریزساختار، روابط بین‌ابزاری، سنجه‌های استنباط‌شده از مشتقات، عوامل بنیادی، داده‌های اقتصاد کلان و متغیرهای تقویمی را مرور می‌کند.

فصل بر ترکیب سیگنال‌های سریع‌تر با حالت‌های کندتر از طریق دروازه‌گذاری، مقیاس‌بندی یا گونه‌های شرطی تأکید می‌کند و هم‌زمان بررسی می‌کند که آیا تعامل‌ها اطلاعاتی می‌افزایند. دسترس‌پذیری به‌هنگام برای داده‌های بنیادی و کلان ضروری است، زیرا تأخیر در گزارش‌دهی و بازنگری‌ها می‌توانند شواهدی کاذب بسازند. جست‌وجوی ویژگی نیز از طریق تغییرات کنترل‌شده، حذف موارد تکراری درون‌خانواده‌ای و بررسی‌های استحکام به انضباط نیاز دارد. فصل روش‌ها و حالت‌های شکست را شرح می‌دهد، نه یک استراتژی یا نتیجه عملکردیِ واحد؛ خانواده‌های ویژگی آن همچنان به داده مناسب، فرض‌های زمانی، اعتبارسنجی و ارزیابی با لحاظ هزینه نیاز دارند.

ایده‌های کلیدی

  • طراحی ویژگی باید با هم‌ترازی افق، فرضیه محرک و نقش روشن ویژگی آغاز شود.
  • انتخاب چارچوب مرجع، بازنمایی و تجمیع می‌تواند معنای اقتصادی یک ویژگی را تغییر دهد.
  • عوامل بنیادی و کلانِ کندتغییر، به هم‌ترازی زمانی نیاز دارند که تأخیر انتشار و بازنگری‌ها را رعایت کند.
  • تعامل سیگنال و حالت می‌تواند اطلاعات شرطی بیفزاید، اما شمار انتخاب‌های مورد آزمون را افزایش می‌دهد.
  • حذف موارد تکراری، تغییرات کنترل‌شده، مطالعات رویدادی و بررسی‌های استحکام به معتبر ماندن انتخاب ویژگی کمک می‌کنند.

برچسب‌ها

متن کامل
# artifact_audit.py


```py
#!/usr/bin/env python3
"""Report registered fits whose named feature artifact is not on disk.

A training identity carries ``computation.feature_artifacts.<role>.sha256``, the hash of
the artifact the fit read. Nothing else checks the file is still there, so a fit whose
input is gone resolves, reads as healthy, and is a record of a result rather than a
reproducible one.

**The scope this walks is printed, and that is not decoration.** An earlier run of an
uncommitted version of this audit reported ``crypto_perps_funding/financial`` as missing
for 144 fits while the file sat at the canonical path under its registered hash, untouched
for two months (ml4t/agent-workspace#1176). A case study's ``features/`` is a symlink into
the artifacts root in every checkout that has one, so an audit run from a throwaway
worktree - or one that does not resolve the link - hashes a different tree than the fits
read and reports absence with full confidence. Every path below is resolved and printed,
and a resolved path outside the artifacts root is a hard error rather than a quiet
mis-scope.
"""

from __future__ import annotations

import argparse
import hashlib
import json
import sqlite3
import sys
from collections import Counter
from pathlib import Path

REPO_ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO_ROOT))

from utils.paths import get_case_study_dir  # noqa: E402

CASE_STUDIES = (
    "cme_futures",
    "crypto_perps_funding",
    "etfs",
    "fx_pairs",
    "nasdaq100_microstructure",
    "sp500_equity_option_analytics",
    "sp500_options",
    "us_equities_panel",
    "us_firm_characteristics",
)
ARTIFACT_DIRS = ("features", "labels")


def sha256_of(path: Path) -> str:
    digest = hashlib.sha256()
    with path.open("rb") as handle:
        for block in iter(lambda: handle.read(1 << 20), b""):
            digest.update(block)
    return digest.hexdigest()


def registered_artifacts(spec_json: str) -> list[tuple[str, str, int | None]]:
    """``(role, sha256, size)`` for one spec, across both shapes the registry holds.

    A dict keyed by role, and a list of ``{role, sha256}`` whose hashes may carry a
    ``sha256:`` prefix. Matching on the hash alone reaches both, but the role and size are
    what make a report readable, so both shapes are parsed rather than regex-scraped.
    """
    artifacts = json.loads(spec_json).get("computation", {}).get("feature_artifacts")
    out: list[tuple[str, str, int | None]] = []
    if isinstance(artifacts, dict):
        for role, entry in artifacts.items():
            if isinstance(entry, dict) and entry.get("sha256"):
                out.append((role, str(entry["sha256"]).removeprefix("sha256:"), entry.get("size")))
    elif isinstance(artifacts, list):
        for entry in artifacts:
            if isinstance(entry, dict) and entry.get("sha256"):
                out.append(
                    (
                        str(entry.get("role", "?")),
                        str(entry["sha256"]).removeprefix("sha256:"),
                        entry.get("size"),
                    )
                )
    return out


def walk(
    case_study: str, artifacts_root: Path | None
) -> tuple[dict[str, Path], list[str], list[str]]:
    """Hash every parquet the case study's artifact directories hold, after resolving them.

    The third return is the directories that were not there. An absent one is not a small
    gap in an otherwise good answer: every hash it would have contributed is absent from
    ``on_disk``, so every fit that read it is counted as naming a missing artifact. The
    caller has to know, because the two readings are opposite and the output is identical.
    """
    case_dir = get_case_study_dir(case_study)
    on_disk: dict[str, Path] = {}
    scope: list[str] = []
    absent: list[str] = []
    for name in ARTIFACT_DIRS:
        declared = case_dir / name
        if not declared.exists():
            scope.append(f"    {name}/  ABSENT at {declared}")
            absent.append(f"{case_study}/{name} at {declared}")
            continue
        resolved = declared.resolve()
        scope.append(f"    {name}/  -> {resolved}")
        if artifacts_root is not None and artifacts_root not in resolved.parents:
            raise SystemExit(
                f"{case_study}/{name} resolves to {resolved}, which is not under "
                f"{artifacts_root}. Hashing it would compare the registry's fits against a "
                f"tree they never read. Run from a checkout whose artifact directories link "
                f"into the artifacts root, or pass --artifacts-root to name the tree you mean."
            )
        for parquet in sorted(resolved.rglob("*.parquet")):
            on_disk.setdefault(sha256_of(parquet), parquet)
    return on_disk, scope, absent


def default_artifacts_root(case_studies: tuple[str, ...]) -> Path | None:
    """The tree the artifact directories actually live in, taken from the first that exists.

    Derived from a RESOLVED artifact directory, never from the case-study directory: in a
    checkout those are two different trees, because ``case_studies/<cs>/features`` is a
    symlink into the artifacts root and its unresolved parent is the repository.
    """
    for case_study in case_studies:
        case_dir = get_case_study_dir(case_study)
        for name in ARTIFACT_DIRS:
            declared = case_dir / name
            if declared.exists():
                # <root>/<case study>/<features|labels>
                return declared.resolve().parents[1]
    return None


def audit(
    case_studies: tuple[str, ...], artifacts_root: Path | None
) -> tuple[int, list[str], list[str]]:
    """Returns the missing-fit count, the case studies skipped, and the directories unseen.

    The second and third are not details. A partial audit that prints "0 fits name an
    artifact that is not on disk" is indistinguishable from a clean one, and a checkout is
    missing a registry whenever its gitignored ``run_log`` symlink was never created -
    which is the normal state of most worktrees, not an exception.

    The third exists because the second was not enough. An absent *artifact directory*
    inside an audited case study used to print one ABSENT line in the middle of the scope
    block and then contribute every one of that case study's fits to a confident total.
    Measured 2026-09-14 on a checkout whose ``us_equities_panel`` had ``run_log`` but no
    ``features/``: the audit reported 393 fits naming missing artifacts and exited 1, with
    no PARTIAL, while ``financial.parquet`` sat on disk at exactly the 4,478,156,899 bytes
    the MISSING line quoted. A case study that could not be fully seen is now not counted
    at all, because there is no way to tell its real findings from its blind ones.
    """
    total_missing = 0
    unaudited: list[str] = []
    unseen: list[str] = []
    for case_study in case_studies:
        db = get_case_study_dir(case_study) / "run_log" / "registry.db"
        print(f"\n{case_study}")
        if not db.exists():
            print(f"    NOT AUDITED: no registry at {db}")
            unaudited.append(case_study)
            continue
        on_disk, scope, absent = walk(case_study, artifacts_root)
        for line in scope:
            print(line)
        if absent:
            print(
                f"    NOT AUDITED: {len(absent)} artifact directory(ies) absent, so every "
                f"fit here would read as missing. Nothing from this case study is counted."
            )
            unseen.extend(absent)
            continue
        print(f"    {len(on_disk)} distinct parquet hashed")

        connection = sqlite3.connect(f"file:{db}?mode=ro", uri=True)
        try:
            rows = connection.execute("SELECT training_hash, spec_json FROM training_runs")
            missing: Counter[tuple[str, str, int | None]] = Counter()
            fits = 0
            for _, spec_json in rows:
                fits += 1
                for role, sha, size in registered_artifacts(spec_json):
                    if sha not in on_disk:
                        missing[(role, sha, size)] += 1
        finally:
            connection.close()

        if not missing:
            print(f"    {fits} fits, every named artifact present")
            continue
        for (role, sha, size), count in sorted(missing.items(), key=lambda kv: -kv[1]):
            size_text = f"{size:,} bytes" if size else "size not recorded"
            print(f"    MISSING  {role:<14} {sha[:16]}…  {size_text}  named by {count} fits")
            total_missing += count
    return total_missing, unaudited, unseen


def main() -> int:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--case-study", action="append", choices=CASE_STUDIES)
    parser.add_argument(
        "--artifacts-root",
        type=Path,
        help=(
            "Tree every artifact directory must resolve under. Defaults to the parent of the "
            "first case study's resolved directory. Pass 'none' to disable the check, which "
            "is how you audit a deliberately isolated tree."
        ),
    )
    args = parser.parse_args()
    selected = tuple(args.case_study) if args.case_study else CASE_STUDIES

    if args.artifacts_root is not None and str(args.artifacts_root) == "none":
        artifacts_root = None
    elif args.artifacts_root is not None:
        artifacts_root = args.artifacts_root.resolve()
    else:
        artifacts_root = default_artifacts_root(selected)
        if artifacts_root is None:
            raise SystemExit(
                "no case study has a features/ or labels/ directory, so there is no tree to "
                "audit. Pass --artifacts-root to name one explicitly."
            )

    print(f"artifacts root: {artifacts_root if artifacts_root else 'UNCHECKED'}")
    total, unaudited, unseen = audit(selected, artifacts_root)
    if unaudited or unseen:
        # Deliberately no total. A number printed here is read as the answer however it is
        # qualified, and over an incomplete scope it is not one.
        print("\nPARTIAL: this audit did not see the whole tree, so it reports no count.")
        if unaudited:
            print(
                f"  {len(unaudited)} of {len(selected)} case studies had no registry: "
                f"{', '.join(unaudited)}"
            )
        if unseen:
            print(f"  {len(unseen)} artifact directory(ies) absent:")
            for line in unseen:
                print(f"    {line}")
        print("  Run from a checkout where every case study links into the artifacts root.")
        return 2
    print(f"\n{total} fits name an artifact that is not on disk")
    return 1 if total else 0


if __name__ == "__main__":
    raise SystemExit(main())

```

با ذکر منبع و مطابق مجوز اثر، به‌طور کامل نمایش داده می‌شود. مجوز: MIT

این خلاصه را عامل پژوهشی Stratmill بر پایه متن اصلی نوشته است؛ نسخه‌ای از اثر منبع نیست.