def _plan_WhiteNoise(self, ops):
assert all(op.input is None for op in ops)
self._init_cl_rng()
Y = self.all_data[[self.sidx[op.output] for op in ops]]
scale = self.RaggedArray([op.process.scale for op in ops],
dtype=np.int32)
enums, params = get_dist_enums_params([op.process.dist for op in ops])
enums = CLRaggedArray(self.queue, enums)
params = CLRaggedArray(self.queue, params)
dt = self.model.dt
return [plan_whitenoise(self.queue, Y, enums, params, scale, dt,
self.cl_rng_state)]
def _plan_WhiteNoise(self, ops):
assert all(op.input is None for op in ops)
self._init_cl_rng()
Y = self.all_data[[self.sidx[op.output] for op in ops]]
scale = self.RaggedArray([op.process.scale for op in ops],
dtype=np.int32)
enums, params = get_dist_enums_params([op.process.dist for op in ops])
enums = CLRaggedArray(self.queue, enums)
params = CLRaggedArray(self.queue, params)
dt = self.model.dt
return [
plan_whitenoise(self.queue, Y, enums, params, scale, dt,
self.cl_rng_state)
]
def _plan_WhiteNoise(self, ops):
assert all(op.input is None for op in ops)
rngs = create_rngs(self.queue, len(ops))
self._cl_rngs[rngs] = [op.process.seed for op in ops]
Y = self.all_data[[self.sidx[op.output] for op in ops]]
scale = self.Array([op.process.scale for op in ops], dtype=np.int32)
inc = self.Array([op.mode == 'inc' for op in ops], dtype=np.int32)
enums, params = get_dist_enums_params([op.process.dist for op in ops])
enums = CLRaggedArray(self.queue, enums)
params = CLRaggedArray(self.queue, params)
dt = self.model.dt
return [plan_whitenoise(
self.queue, Y, enums, params, scale, inc, dt, rngs)]
def _plan_WhiteNoise(self, ops):
assert all(op.input is None for op in ops)
rngs = create_rngs(self.queue, len(ops))
self._cl_rngs[rngs] = [op.process.seed for op in ops]
Y = self.all_data[[self.sidx[op.output] for op in ops]]
scale = self.Array([op.process.scale for op in ops], dtype=np.int32)
inc = self.Array([op.mode == 'inc' for op in ops], dtype=np.int32)
enums, params = get_dist_enums_params([op.process.dist for op in ops])
enums = CLRaggedArray(self.queue, enums)
params = CLRaggedArray(self.queue, params)
dt = self.model.dt
return [
plan_whitenoise(self.queue, Y, enums, params, scale, inc, dt, rngs)
]