@@ -23,11 +23,11 @@ Feature Older Equivalent Notes
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source, called a `BitGenerator
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<bit_generators> ` A number of these
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are provided. ``RandomState `` uses
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- only the Box- Muller method .
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+ only the Mersenne Twister .
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------------------ -------------------- -------------
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- ``np.random. `` ``np.random. `` Access the values in a BitGenerator,
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- ``Generator(). `` ``random_sample() `` convert them to ``float64 `` in the
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- `` random() `` interval ``[0.0., `` `` 1.0)``.
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+ ``Generator. `` ``RandomState. `` Access the values in a BitGenerator,
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+ ``random() `` ``random_sample() `` convert them to ``float64 `` in the
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+ interval ``[0.0., `` `` 1.0)``.
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In addition to the ``size `` kwarg, now
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supports ``dtype='d' `` or ``dtype='f' ``,
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and an ``out `` kwarg to fill a user-
@@ -36,7 +36,7 @@ Feature Older Equivalent Notes
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Many other distributions are also
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supported.
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------------------ -------------------- -------------
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- ``Generator() . `` ``randint ``, Use the ``endpoint `` kwarg to adjust
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+ ``Generator. `` ``randint ``, Use the ``endpoint `` kwarg to adjust
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``integers() `` ``random_integers `` the inclusion or exclution of the
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``high `` interval endpoint
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================== ==================== =============
@@ -56,7 +56,7 @@ And in more detail:
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random numbers from a discrete uniform distribution. The ``rand `` and
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``randn `` methods are only available through the legacy `~.RandomState `.
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This replaces both ``randint `` and the deprecated ``random_integers ``.
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- * The Box-Muller used to produce NumPy's normals is no longer available.
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+ * The Box-Muller method used to produce NumPy's normals is no longer available.
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* All bit generators can produce doubles, uint64s and
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uint32s via CTypes (`~PCG64.ctypes `) and CFFI (`~PCG64.cffi `).
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This allows these bit generators to be used in numba.
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