def initialize(self, n_chans):
self.running_mean = None
self.running_var = None
self.sample_buffer = RingBuffer(
np.zeros((self.n_samples_in_buffer, n_chans), dtype=np.float32))
self.y_buffer = RingBuffer(
np.zeros((self.n_samples_in_buffer), dtype=np.float32))
def __init__(self, data_processor, model, trainer, pred_gap):
self.data_processor = data_processor
self.model = model
self.pred_gap = pred_gap
self.marker_buffer = RingBuffer(
np.zeros(data_processor.n_samples_in_buffer, dtype=np.int32))
self.trainer = trainer
def _init_data(self):
self._data = dict()
for sensor_name in self._sensor_names:
self._data[sensor_name] = RingBuffer(
np.sin(np.linspace(0, 10, 1000)))
