🌐 [translation-sync] [numpy.md] Update np.random → Generator API

[mmcky]

Automated Translation Sync

This PR contains automated translations from QuantEcon/lecture-python-programming.

Source PR

#549 - [numpy.md] Update np.random → Generator API

Files Updated

• ✏️ lectures/numpy.md
• ✏️ .translate/state/numpy.md.yml

Details

• Source Language: en
• Target Language: fa
• Model: claude-sonnet-4-6

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This PR was created automatically by the translation action.

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[github-actions]

✅ Translation Quality Review

Verdict: PASS | Model: claude-sonnet-4-6 | Date: 2026-05-13

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📝 Translation Quality

Criterion	Score
Accuracy	9/10
Fluency	9/10
Terminology	9/10
Formatting	9/10
Overall	9/10

Summary: The Persian translation of the modified sections is of high quality. All five changed sections (Mutability, Making Copies, Universal Functions, Sub-packages, Implicit Multithreading, and Exercises) are accurately translated with natural Farsi phrasing and consistent technical terminology. Formatting is well-preserved with no syntax errors. Minor fluency improvements are possible in a few places but do not significantly impact comprehension. The translation successfully balances technical precision with natural Persian academic prose. Consistent and accurate use of established Persian technical terminology throughout all modified sections (e.g., 'قابلیت تغییر' for Mutability, 'توابع جهانی' for Universal Functions, 'بسته‌های فرعی' for Sub-packages, 'چندنخی ضمنی' for Implicit Multithreading) Mathematical content, LaTeX equations, and code blocks are perfectly preserved across all modified sections with no formatting errors The Exercises section is translated with high accuracy, preserving the logical structure of multi-part problems and solution hints Deep copy terminology ('deep copy' kept with Persian explanation 'کپی مستقل') is handled appropriately in the Making Copies section, balancing technical precision with readability The translation maintains a consistent academic register appropriate for a technical programming tutorial throughout all modified sections

Suggestions:

• Mutability section: 'We already saw examples of multability above' → The Persian translation 'قبلاً نمونه‌هایی از قابلیت تغییر را در بالا دیدیم' correctly translates this, but the original English has a typo 'multability' which was silently corrected in translation - this is fine and acceptable.

• Universal Functions section: 'Not all user-defined functions will act element-wise' is translated as 'همه توابع تعریف شده توسط کاربر به صورت عنصر به عنصر عمل نخواهند کرد' - while accurate, a more fluent phrasing would be 'نه همه توابع تعریف‌شده توسط کاربر به صورت عنصر‌به‌عنصر عمل می‌کنند' to better match Persian natural negation patterns.

• Sub-packages section: 'Generate standard normals' is translated as 'تولید توزیع نرمال استاندارد' but more accurately should be 'تولید اعداد تصادفی نرمال استاندارد' since it refers to random numbers, not a distribution object.

• Implicit Multithreading section: 'neatly splits up the tasks' is translated as 'به زیبایی وظایف را تقسیم می‌کند' - a more technical and appropriate rendering would be 'به‌خوبی وظایف را تقسیم‌بندی می‌کند' which sounds more natural in technical Persian.

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🔍 Diff Quality

Check	Status
Scope Correct	✅
Position Correct	✅
Structure Preserved	✅
Heading-map Correct	✅
Overall	10/10

Summary: The translation document correctly mirrors all source changes: the deprecated np.random.randn calls are replaced with rng.standard_normal and related RNG updates, the DiscreteRV class gains seed parameter and uses self.rng, the Sub-packages section text is updated, and the exercise solutions use the new RNG API — all at the correct positions, with structure and heading-map unchanged.

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This review was generated automatically by action-translation review mode.

[Copilot]

Pull request overview

This PR syncs the Persian translation of the NumPy lecture with upstream changes that migrate examples from the legacy np.random.* API to NumPy’s Generator-based random API, and updates the translation sync state metadata accordingly.

Changes:

• Replaced uses of np.random.randn, np.random.binomial, and np.random.seed with np.random.default_rng() + Generator methods like standard_normal and binomial.
• Updated the DiscreteRV exercise solution to use an instance RNG (default_rng(seed)) and rng.uniform(...).
• Updated translation sync state (source-sha, sync date, model, tool version).

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
lectures/numpy.md	Updates random-number generation examples to the Generator API and adjusts related exercise solution code.
.translate/state/numpy.md.yml	Updates translation-sync bookkeeping (source SHA, sync timestamp, model/mode, tool version).

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[github-actions]

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