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Port the numpy.md edits from source #595 that the resync regeneration dropped
The batch's original sync PR here (#30) was closed unmerged and its regeneration (#34) silently omitted numpy.md, so the two #595 edits never arrived: the DiscreteRV seed docstring (kept in English verbatim, as this lecture's docstrings are) and the tic/toc sentence, now le gestionnaire de contexte qe.Timer(). Hand-ported rather than regenerated because numpy.md carries Emile's native review (#24) that a whole-file resync would discard. State advances to the batch commit d35eb831. Measurement and ledger: QuantEcon/action-translation#276. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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.translate/state/numpy.md.yml

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source-sha: a2b929f15e703b6942e8b80a29011c51f234b1e0
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synced-at: "2026-07-14"
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source-sha: d35eb831da23a763f43d403e96f20d43529cae53
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synced-at: "2026-08-19"
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model: claude-opus-4-8
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mode: NEW
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section-count: 8

lectures/numpy.md

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def __init__(self, q, seed=None):
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"""
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The argument q is a NumPy array, or array like, nonnegative and sums
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to 1
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to 1.
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The argument seed sets the seed for the underlying random number
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generator; with the default seed=None, draws are not reproducible
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across runs.
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"""
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self.q = q
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self.Q = cumsum(q)
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**Partie 2** : Passez à la reproduction du résultat de l'opération de broadcasting suivante. Parallèlement, comparez les vitesses du broadcasting et de la boucle `for` que vous implémentez.
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Pour cette partie de l'exercice, vous pouvez utiliser les fonctions `tic`/`toc` de la bibliothèque `quantecon` pour chronométrer l'exécution.
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Pour cette partie de l'exercice, vous pouvez utiliser le gestionnaire de contexte `qe.Timer()` de la bibliothèque `quantecon` pour chronométrer l'exécution.
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Assurons-nous que cette bibliothèque est installée.
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