def __init__(self, configs):
configs["processor"]["data"]['waveform'] = {
'slope_length':
configs["input_data"]['ramp_time'] *
configs["processor"]["driver"]['sampling_frequency']
} # add this because needed in setup_mgr.py of processors self.configs = configs
# define processor and input generator
self.processor = get_driver(configs["processor"])
self.configs = configs
def __init__(self, configs, logger=None):
super(HardwareProcessor, self).__init__()
self.driver = get_driver(configs)
if configs['processor_type'] == 'simulation_debug':
self.voltage_ranges = self.driver.voltage_ranges
else:
self.voltage_ranges = TorchUtils.get_tensor_from_numpy(self.driver.voltage_ranges)
self.waveform_mgr = WaveformManager(configs["data"]["waveform"])
self.logger = logger
# TODO: Manage amplification from this class
self.amplification = configs["driver"]["amplification"]
self.clipping_value = [
configs["driver"]["output_clipping_range"][0] * self.amplification,
configs["driver"]["output_clipping_range"][1] * self.amplification,
]
def run_test(self):
# save(mode='configs', path=self.configs['results_base_dir'], filename='test_configs.json', overwrite=self.configs['overwrite_results'], data=self.configs)
self.processor = get_driver(self.configs['processor'])
experiments = ["IV1", "IV2", "IV3", "IV4", "IV5", "IV6", "IV7"]
self.devices_in_experiments = {}
output = {}
output_array = []
for exp in experiments:
output[exp] = {}
self.devices_in_experiments[exp] = self.configs['devices'].copy()
output_array = self.processor.forward_numpy(
IVtest.create_input_arrays(self))
for i, dev in enumerate(self.configs['devices']):
output[exp][dev] = output_array.T[i, :]
self.iv_plot(configs, output)
self.processor.close_tasks()