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ENH: Use NumPy's Generator class as a replacement for RandomState #141

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Mar 28, 2024
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ENH: Use NumPy's Generator class as a replacement for RandomState #141

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12 changes: 8 additions & 4 deletions src/eddymotion/estimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,8 +75,9 @@ def fit(
Number of parallel jobs.
seed : :obj:`int` or :obj:`bool`
Seed the random number generator (necessary when we want deterministic
estimation).

estimation). If an integer, the value is used to initialize the
generator; if ``True``, the arbitrary value of ``20210324`` is used
to initialize it.
Return
------
affines : :obj:`list` of :obj:`numpy.ndarray`
Expand All @@ -86,8 +87,11 @@ def fit(
"""
align_kwargs = align_kwargs or {}

_seed = None
if seed or seed == 0:
np.random.seed(20210324 if seed is True else seed)
_seed = 20210324 if seed is True else seed
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rng = np.random.default_rng(_seed)

if "num_threads" not in align_kwargs and omp_nthreads is not None:
align_kwargs["num_threads"] = omp_nthreads
Expand Down Expand Up @@ -120,7 +124,7 @@ def fit(
kwargs["xlim"] = dwdata.total_duration

index_order = np.arange(len(dwdata))
np.random.shuffle(index_order)
rng.shuffle(index_order)

single_model = model.lower() in (
"b0",
Expand Down