def _copy_np_state(r, ptr):
"""
Copy state of Numpy random *r* to Numba state *ptr*.
"""
ints, index = r.get_state()[1:3]
_helperlib.rnd_set_state(ptr, (index, [int(x) for x in ints]))
return ints, index
def _copy_np_state(r, ptr):
"""
Copy state of Numpy random *r* to Numba state *ptr*.
"""
ints, index = r.get_state()[1:3]
_helperlib.rnd_set_state(ptr, (index, [int(x) for x in ints]))
return ints, index
def _copy_py_state(r, ptr):
"""
Copy state of Python random *r* to Numba state *ptr*.
"""
mt = r.getstate()[1]
ints, index = mt[:-1], mt[-1]
_helperlib.rnd_set_state(ptr, (index, list(ints)))
return ints, index
def numba_typify_RandomState(state, **kwargs):
# The numba_typify in this case is just an passthrough function
# that synchronizes Numba's internal random state with the current
# RandomState object
ints, index = state.get_state()[1:3]
ptr = _helperlib.rnd_get_np_state_ptr()
_helperlib.rnd_set_state(ptr, (index, [int(x) for x in ints]))
return state
def _copy_py_state(r, ptr):
"""
Copy state of Python random *r* to Numba state *ptr*.
"""
mt = r.getstate()[1]
ints, index = mt[:-1], mt[-1]
_helperlib.rnd_set_state(ptr, (index, list(ints)))
return ints, index
def _check_get_set_state(self, ptr):
state = _helperlib.rnd_get_state(ptr)
i, ints = state
self.assertIsInstance(i, int)
self.assertIsInstance(ints, list)
self.assertEqual(len(ints), N)
j = (i * 100007) % N
ints = [i * 3 for i in range(N)]
# Roundtrip
_helperlib.rnd_set_state(ptr, (j, ints))
self.assertEqual(_helperlib.rnd_get_state(ptr), (j, ints))
def _check_get_set_state(self, ptr):
state = _helperlib.rnd_get_state(ptr)
i, ints = state
self.assertIsInstance(i, int)
self.assertIsInstance(ints, list)
self.assertEqual(len(ints), N)
j = (i * 100007) % N
ints = [i * 3 for i in range(N)]
# Roundtrip
_helperlib.rnd_set_state(ptr, (j, ints))
self.assertEqual(_helperlib.rnd_get_state(ptr), (j, ints))
def _set_random_state(self):
# This uses a trick by Alexandre Gramfort,
# see https://github.com/numba/numba/issues/3249
if self._random_state >= 0:
if self._using_numba:
r = np.random.RandomState(self._random_state)
ptr = _helperlib.rnd_get_np_state_ptr()
ints, index = r.get_state()[1:3]
_helperlib.rnd_set_state(ptr, (index, [int(x) for x in ints]))
self._ptr = ptr
self._r = r
else:
np.random.seed(self._random_state)
def set_random_state(_state_tuple):
"""Set the random state from a tuple.
Set the random state from a tuple in the form returned by
:func:`numba._helperlib.rnd_get_state`.
.. important::
You probably do not need to use this function. Be sure you know
*exactly* how you are affecting the random number generator state
before using this function, or you are likely to create a model that
cannot be peproduced.
See also :func:`set_random_seed`.
Parameters
----------
state : :obj:`tuple`
Random number generator state as a tuple.
"""
ptr = _helperlib.rnd_get_np_state_ptr()
_helperlib.rnd_set_state(ptr, _state_tuple)
