def seed(seed=None):
"""
Seed the internal random number generator used in this ID package.
The generator is a lagged Fibonacci method with 55-element internal state.
Parameters
----------
seed : int, sequence, 'default', optional
If 'default', the random seed is reset to a default value.
If `seed` is a sequence containing 55 floating-point numbers
in range [0,1], these are used to set the internal state of
the generator.
If the value is an integer, the internal state is obtained
from `numpy.random.RandomState` (MT19937) with the integer
used as the initial seed.
If `seed` is omitted (None), `numpy.random` is used to
initialize the generator.
"""
# For details, see :func:`backend.id_srand`, :func:`backend.id_srandi`,
# and :func:`backend.id_srando`.
if isinstance(seed, str) and seed == 'default':
backend.id_srando()
elif hasattr(seed, '__len__'):
state = np.asfortranarray(seed, dtype=float)
if state.shape != (55, ):
raise ValueError("invalid input size")
elif state.min() < 0 or state.max() > 1:
raise ValueError("values not in range [0,1]")
backend.id_srandi(state)
elif seed is None:
backend.id_srandi(np.random.rand(55))
else:
rnd = np.random.RandomState(seed)
backend.id_srandi(rnd.rand(55))
def seed(seed=None):
"""
Seed the internal random number generator used in this ID package.
The generator is a lagged Fibonacci method with 55-element internal state.
Parameters
----------
seed : int, sequence, 'default', optional
If 'default', the random seed is reset to a default value.
If `seed` is a sequence containing 55 floating-point numbers
in range [0,1], these are used to set the internal state of
the generator.
If the value is an integer, the internal state is obtained
from `numpy.random.RandomState` (MT19937) with the integer
used as the initial seed.
If `seed` is omitted (None), `numpy.random` is used to
initialize the generator.
"""
# For details, see :func:`backend.id_srand`, :func:`backend.id_srandi`,
# and :func:`backend.id_srando`.
if isinstance(seed, str) and seed == 'default':
backend.id_srando()
elif hasattr(seed, '__len__'):
state = np.asfortranarray(seed, dtype=float)
if state.shape != (55,):
raise ValueError("invalid input size")
elif state.min() < 0 or state.max() > 1:
raise ValueError("values not in range [0,1]")
backend.id_srandi(state)
elif seed is None:
backend.id_srandi(np.random.rand(55))
else:
rnd = np.random.RandomState(seed)
backend.id_srandi(rnd.rand(55))
