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) ]