Separate the clustered keyword list from the keywords to merge
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
+9
-7
@@ -47,11 +47,12 @@ LLM。設計原則見 `research-plan.md`;本檔記載可重現的
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實作本步,四種模型六次執行全部無法維持完整分割,
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已棄用(詳見 `decision-log.md` 2026-08-05;棄用的
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定義檔止於 git 歷史,見 `git log -- prompts/`)。
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- **產物**:分群明細 CSV(欄位 Group、Keyword,一列一個
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成員,依兩欄排序)記錄機器算出的分割;定案碼表 JSON
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(`{"keywords": [...]}`)記錄實際交給模型的碼,即組名
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加上先驗主題詞。兩者分開,因為前者是分群結果、後者
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含研究者的介入。
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- **產物**:三份。分群明細 CSV(欄位 Group、Keyword,
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一列一個成員,依兩欄排序)記錄機器算出的分割;組名
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純文字檔(一行一個,字典序)是分群結果的可讀清單;
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定案碼表 JSON(`{"keywords": [...]}`)記錄實際交給
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模型的碼,即組名加上先驗主題詞。前兩份只含分群結果,
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只有第三份含研究者的介入。
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- **可重現性**:同一輸入、同一釘定模型、同一參數逐次
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重現。不同 CPU/BLAS 實作的浮點尾數差異可能使邊界
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詞的歸屬翻動,屬已揭露的限制;論文所用碼表逐字
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@@ -114,8 +115,9 @@ LLM。設計原則見 `research-plan.md`;本檔記載可重現的
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U+0085 等控制字元時,`str.splitlines()` 類的通用切行
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會截斷 JSON 字串,實測踩中),輸出關鍵字純文字檔與
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出處 CSV。
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- **步驟 2-1 → 2-2**:`cluster-keywords` 讀關鍵字純文字
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檔,輸出分群明細 CSV 與定案碼表 JSON。
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- **步驟 2-1 → 2-2**:`cluster-keywords` 讀關鍵字池純
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文字檔,輸出分群明細 CSV、組名純文字檔與定案碼表
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JSON。
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- **步驟 2-2 → 3 輸入檔**:`export-llm-input --extras
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<定案碼表>` 自工作儲存產出步驟 3 的輸入,每筆
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`{"id": "song-<ID>", "content": <字串>}`,`content` 為
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@@ -0,0 +1,50 @@
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abandonment-and-solitude
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alcohol-and-substance-abuse
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attraction-and-admiration
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betrayal-and-mistrust
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boastful-self-confidence
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breakup-and-reconciliation
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celebration-and-partying
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contentment-and-joy
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dancing-and-movement
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defiance-and-confrontation
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denial-and-pretense
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designer-fashion-flexing
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devotion-and-sacrifice
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embracing-true-identity
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fame-and-status
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family-and-fatherhood
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fantasy-and-imagination
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fear-of-vulnerability
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female-empowerment
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flirtation-and-seduction
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freedom-and-escape
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heartbreak-and-grief
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hidden-emotional-struggle
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hope-and-disillusionment
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human-connection
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hustle-and-self-made-success
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independence-and-self-reliance
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intimacy-and-connection
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jealousy-and-resentment-from-others
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longing-and-desire
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longing-for-clarity
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love-as-fleeting-and-transient
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loyalty-and-commitment
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mutual-individuality
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nostalgia-and-memory
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obsession-and-madness
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partner-inadequacy
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partying-and-nightlife
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personal-growth-and-change
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reggaeton-culture
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regret-and-guilt
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relentless-ambition
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resilience-through-hardship
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rivalry-and-superiority
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romantic-pursuit
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secrecy-and-paranoia
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self-worth-and-insecurity
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small-town-roots-and-identity
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street-loyalty-and-danger
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wealth-and-luxury
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@@ -8,11 +8,14 @@ Builds the coding groups from the pooled keyword list, given as
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the first positional command-line argument, by sentence-embedding
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every keyword and clustering the embeddings: the group membership,
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given as the second positional argument, is written as a CSV file
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holding the clustering result alone. The coding keyword set,
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given as the third positional argument, is written as a JSON file
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holding the group name keywords plus the researcher's a-priori
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topic term (see :data:`EXTRA_KEYWORD`). The step is fully
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deterministic; no LLM call is made.
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holding the clustering result alone. The group name keywords
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alone, given as the third positional argument, are written as a
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text file, one per line. The coding keyword set for
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``export-llm-input --extras``, given as the fourth positional
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argument, is written as a JSON file holding the group name
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keywords plus the researcher's a-priori topic term (see
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:data:`EXTRA_KEYWORD`). The step is fully deterministic; no LLM
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call is made.
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"""
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import argparse
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import csv
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@@ -49,14 +52,17 @@ def parse_args(argv: list[str] | None) -> argparse.Namespace:
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" sentence embeddings of the pooled"
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" keywords.")
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parser.add_argument(
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"keywords_txt", type=Path,
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"pool_txt", type=Path,
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help="the pooled keyword list, one keyword per line")
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parser.add_argument(
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"groups_csv", type=Path,
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help="the group membership CSV output file")
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parser.add_argument(
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"keywords_json", type=Path,
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help="the group name keyword JSON output file")
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"keywords_txt", type=Path,
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help="the group name keyword text output file")
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parser.add_argument(
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"keywords_to_merge_json", type=Path,
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help="the coding keyword set JSON output file")
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parser.add_argument(
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"--model", default=MODEL,
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help=f"the sentence embedding model (default \"{MODEL}\")")
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@@ -221,14 +227,35 @@ def write_groups(path: Path, groups: dict[str, list[str]]) -> None:
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writer.writerow([group, keyword])
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def write_keywords(path: Path,
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groups: dict[str, list[str]]) -> None:
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def write_keyword_names(path: Path,
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groups: dict[str, list[str]]) -> None:
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"""Write the group name keyword text file.
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Writes a text file holding the lexicographically sorted
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group names, one per line, UTF-8, LF line endings, with a
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trailing newline. The file records the clustering result
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alone; it holds no :data:`EXTRA_KEYWORD` line.
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:param path: The path of the keyword text file to write.
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:param groups: The keyword members of every group, keyed by
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the group's medoid name.
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:return: None.
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:raises OSError: When the file cannot be written.
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"""
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names: list[str] = sorted(groups.keys())
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path.write_text(
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"".join(f"{x}\n" for x in names), encoding="utf-8")
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def write_keywords_to_merge(path: Path,
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groups: dict[str, list[str]]) -> None:
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"""Write the coding keyword set JSON file.
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Writes a JSON file holding a single object with one
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``keywords`` key, whose value is the lexicographically
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sorted list of the group names plus :data:`EXTRA_KEYWORD`,
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UTF-8, with a trailing newline.
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UTF-8, with a trailing newline. This is the file
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``export-llm-input --extras`` consumes.
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:param path: The path of the keyword JSON file to write.
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:param groups: The keyword members of every group, keyed by
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@@ -248,8 +275,10 @@ def main(argv: list[str] | None = None) -> int:
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"""Cluster the pooled keywords into the coding groups.
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Writes the group membership CSV file, holding the clustering
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result alone, and the coding keyword set JSON file, holding
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the group names plus :data:`EXTRA_KEYWORD`.
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result alone; the group name keyword text file, holding the
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same group names as a readable list; and the coding keyword
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set JSON file, holding the group names plus
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:data:`EXTRA_KEYWORD`.
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:param argv: The command-line arguments, or None for
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``sys.argv``.
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@@ -258,7 +287,7 @@ def main(argv: list[str] | None = None) -> int:
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started: float = time.monotonic()
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args: argparse.Namespace = parse_args(argv)
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try:
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keywords: list[str] = load_keywords(args.keywords_txt)
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keywords: list[str] = load_keywords(args.pool_txt)
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except (OSError, ValueError) as error:
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print(f"error: {error}", file=sys.stderr)
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return 1
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@@ -272,9 +301,12 @@ def main(argv: list[str] | None = None) -> int:
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print(f"error: {error}", file=sys.stderr)
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return 1
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args.groups_csv.parent.mkdir(parents=True, exist_ok=True)
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args.keywords_json.parent.mkdir(parents=True, exist_ok=True)
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args.keywords_txt.parent.mkdir(parents=True, exist_ok=True)
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args.keywords_to_merge_json.parent.mkdir(
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parents=True, exist_ok=True)
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write_groups(args.groups_csv, groups)
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write_keywords(args.keywords_json, groups)
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write_keyword_names(args.keywords_txt, groups)
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write_keywords_to_merge(args.keywords_to_merge_json, groups)
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elapsed: str = format_duration(time.monotonic() - started)
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print(
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f"done: {len(keywords)} keywords clustered into"
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@@ -31,9 +31,11 @@ class TestClusterKeywords(unittest.TestCase):
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= tempfile.TemporaryDirectory()
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self.addCleanup(tmp.cleanup)
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self.__dir: Path = Path(tmp.name)
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self.__keywords_txt: Path = self.__dir / "keywords.txt"
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self.__pool_txt: Path = self.__dir / "pool.txt"
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self.__groups_csv: Path = self.__dir / "groups.csv"
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self.__keywords_json: Path = self.__dir / "keywords.json"
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self.__keywords_txt: Path = self.__dir / "keywords.txt"
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self.__keywords_to_merge_json: Path \
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= self.__dir / "keywords-to-merge.json"
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@staticmethod
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def __two_cluster_vectors() -> Vectors:
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@@ -56,13 +58,13 @@ class TestClusterKeywords(unittest.TestCase):
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"b-south": (-0.9396926, -0.3420201),
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}
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def __write_keywords(self, keywords: list[str]) -> None:
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def __write_pool(self, keywords: list[str]) -> None:
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"""Write the pooled keyword input file.
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:param keywords: The keywords, one per line.
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:return: None.
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"""
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self.__keywords_txt.write_text(
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self.__pool_txt.write_text(
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"".join(f"{x}\n" for x in keywords), encoding="utf-8")
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@staticmethod
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@@ -95,15 +97,16 @@ class TestClusterKeywords(unittest.TestCase):
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standard error.
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:param extra_args: Extra command-line arguments appended
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after the three positional arguments.
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after the four positional arguments.
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:param vectors: The fixed embedding to encode with; the
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two-cluster fixture is used when None.
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:return: A tuple of the exit status and the standard
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error.
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"""
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argv: list[str] = [
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str(self.__keywords_txt), str(self.__groups_csv),
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str(self.__keywords_json)]
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str(self.__pool_txt), str(self.__groups_csv),
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str(self.__keywords_txt),
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str(self.__keywords_to_merge_json)]
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argv.extend(extra_args or [])
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fake: Any = self.__fake_encode(
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vectors if vectors is not None
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@@ -126,19 +129,33 @@ class TestClusterKeywords(unittest.TestCase):
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newline="") as file:
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return list(csv.reader(file))
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def __read_keywords(self) -> list[str]:
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"""Read the group name keyword JSON file.
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def __read_keyword_names(self) -> list[str]:
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"""Read the group name keyword text file.
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:return: The group names under the "keywords" key.
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:return: The group names, in file order.
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"""
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text: str = self.__keywords_txt.read_text(
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encoding="utf-8")
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lines: list[str] = text.split("\n")
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if len(lines) > 0 and lines[-1] == "":
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lines = lines[:-1]
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return lines
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def __read_keywords_to_merge(self) -> list[str]:
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"""Read the coding keyword set JSON file.
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:return: The group names plus :data:`EXTRA_KEYWORD`
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under the "keywords" key.
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"""
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data: dict[str, list[str]] = json.loads(
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self.__keywords_json.read_text(encoding="utf-8"))
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self.__keywords_to_merge_json.read_text(
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encoding="utf-8"))
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return data["keywords"]
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def test_groups_csv_header_and_ordering(self) -> None:
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"""Test the header row and the group/keyword ordering of
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the group membership CSV file."""
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self.__write_keywords([
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self.__write_pool([
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"a-left", "a-center", "a-right",
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"b-north", "b-middle", "b-south"])
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status: int
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@@ -161,7 +178,7 @@ class TestClusterKeywords(unittest.TestCase):
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keywords: list[str] = [
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"a-left", "a-center", "a-right",
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"b-north", "b-middle", "b-south"]
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self.__write_keywords(keywords)
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self.__write_pool(keywords)
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status: int
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status, _ = self.__run_cluster()
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self.assertEqual(status, 0)
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@@ -169,16 +186,31 @@ class TestClusterKeywords(unittest.TestCase):
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self.assertEqual(
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sorted(x[1] for x in rows), sorted(keywords))
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def test_keywords_json_sorted_medoids(self) -> None:
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"""Test that the keyword JSON file holds the sorted medoid
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group names plus the extra a-priori keyword."""
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self.__write_keywords([
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def test_keywords_txt_sorted_medoids(self) -> None:
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"""Test that the keyword text file holds the sorted medoid
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group names without the extra a-priori keyword."""
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self.__write_pool([
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"a-left", "a-center", "a-right",
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"b-north", "b-middle", "b-south"])
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status: int
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status, _ = self.__run_cluster()
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self.assertEqual(status, 0)
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keywords: list[str] = self.__read_keywords()
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names: list[str] = self.__read_keyword_names()
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self.assertEqual(names, ["a-center", "b-middle"])
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self.assertEqual(names, sorted(names))
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self.assertNotIn(cluster_keywords.EXTRA_KEYWORD, names)
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def test_keywords_to_merge_json_sorted_medoids(self) -> None:
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"""Test that the coding keyword set JSON file holds the
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sorted medoid group names plus the extra a-priori
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keyword."""
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self.__write_pool([
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"a-left", "a-center", "a-right",
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"b-north", "b-middle", "b-south"])
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status: int
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status, _ = self.__run_cluster()
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self.assertEqual(status, 0)
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keywords: list[str] = self.__read_keywords_to_merge()
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self.assertEqual(
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keywords,
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["a-center", "b-middle", cluster_keywords.EXTRA_KEYWORD])
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@@ -188,7 +220,7 @@ class TestClusterKeywords(unittest.TestCase):
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def test_extra_keyword_absent_from_groups_csv(self) -> None:
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"""Test that the extra a-priori keyword appears in no row
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of the group membership CSV file."""
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self.__write_keywords([
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self.__write_pool([
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"a-left", "a-center", "a-right",
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"b-north", "b-middle", "b-south"])
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status: int
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@@ -201,23 +233,25 @@ class TestClusterKeywords(unittest.TestCase):
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def test_duplicate_keyword_rejected(self) -> None:
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"""Test that a duplicate keyword line fails the run
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without writing any output file."""
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self.__write_keywords(["shared", "shared"])
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self.__write_pool(["shared", "shared"])
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status: int
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stderr: str
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status, stderr = self.__run_cluster()
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self.assertEqual(status, 1)
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self.assertIn("duplicate keyword", stderr)
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self.assertFalse(self.__groups_csv.exists())
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self.assertFalse(self.__keywords_json.exists())
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self.assertFalse(self.__keywords_txt.exists())
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self.assertFalse(self.__keywords_to_merge_json.exists())
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def test_empty_input_rejected(self) -> None:
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"""Test that an empty keyword file fails the run without
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writing any output file."""
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self.__keywords_txt.write_text("", encoding="utf-8")
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self.__pool_txt.write_text("", encoding="utf-8")
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status: int
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stderr: str
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status, stderr = self.__run_cluster()
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self.assertEqual(status, 1)
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self.assertIn("no keywords", stderr)
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self.assertFalse(self.__groups_csv.exists())
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self.assertFalse(self.__keywords_json.exists())
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self.assertFalse(self.__keywords_txt.exists())
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self.assertFalse(self.__keywords_to_merge_json.exists())
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