Source code for NuRadioReco.modules.analogToDigitalConverter

import logging
import time
import numpy as np
from NuRadioReco.utilities import units
from scipy.interpolate import interp1d
from scipy.signal import resample
from NuRadioReco.modules.base.module import register_run
from NuRadioReco.utilities.trace_utilities import delay_trace


[docs]def perfect_comparator(trace, adc_n_bits, adc_ref_voltage, mode='floor', output='voltage'): """ Simulates a perfect comparator flash ADC that compares the voltage to the voltage for the least significative bit and takes the floor or the ceiling of their ratio as a digitised value of the trace. Parameters ---------- trace: array of floats Trace containing the voltage to be digitised adc_n_bits: int Number of bits of the ADC adc_ref_voltage: float Voltage corresponding to the maximum number of counts given by the ADC: 2**adc_n_bits - 1 mode: string 'floor' or 'ceiling' output: {'voltage', 'counts'}, default 'voltage' Options: * 'voltage' to store the ADC output as discretised voltage trace * 'counts' to store the ADC output in ADC counts Returns ------- digital_trace: array of floats Digitised voltage trace in volts or ADC counts """ lsb_voltage = adc_ref_voltage / (2 ** (adc_n_bits - 1) - 1) if (mode == 'floor'): digital_trace = np.floor(trace / lsb_voltage) elif (mode == 'ceiling'): digital_trace = np.ceil(trace / lsb_voltage) else: raise ValueError('Choose floor or ceiing as modes for the comparator ADC') digital_trace = apply_saturation(digital_trace, adc_n_bits, adc_ref_voltage) digital_trace = round_to_int(digital_trace) if (output == 'voltage'): digital_trace = lsb_voltage * digital_trace.astype(float) elif (output == 'counts'): pass else: raise ValueError("The ADC output format is unknown. Please choose 'voltage' or 'counts'") return digital_trace # , lsb_voltage
[docs]def perfect_floor_comparator(trace, adc_n_bits, adc_ref_voltage, output='voltage'): """ Perfect comparator ADC that takes the floor value of the comparison. See perfect_comparator """ return perfect_comparator(trace, adc_n_bits, adc_ref_voltage, mode='floor', output=output)
[docs]def perfect_ceiling_comparator(trace, adc_n_bits, adc_ref_voltage, output='voltage'): """ Perfect comparator ADC that takes the floor value of the comparison. See perfect_floor. """ return perfect_comparator(trace, adc_n_bits, adc_ref_voltage, mode='ceiling', output=output)
[docs]def apply_saturation(adc_counts_trace, adc_n_bits, adc_ref_voltage): """ Takes a digitised trace in ADC counts and clips the parts of the trace with values higher than 2**(adc_n_bits-1)-1 or lower than -2**(adc_n_bits-1). Parameters ---------- adc_counts_trace: array of floats Voltage in ADC counts, unclipped adc_n_bits: int Number of bits of the ADC adc_ref_voltage: float Voltage corresponding to the maximum number of counts given by the ADC: 2**(adc_n_bits-1) - 1 Returns ------- saturated_trace: array of floats The clipped or saturated voltage trace """ saturated_trace = adc_counts_trace[:] highest_count = 2 ** (adc_n_bits - 1) - 1 high_saturation_mask = adc_counts_trace > highest_count saturated_trace[high_saturation_mask] = highest_count lowest_count = -2 ** (adc_n_bits - 1) low_saturation_mask = adc_counts_trace < lowest_count saturated_trace[low_saturation_mask] = lowest_count return saturated_trace
[docs]def round_to_int(digital_trace): int_trace = np.rint(digital_trace) int_trace = int_trace.astype(int) return int_trace
[docs]class analogToDigitalConverter: """ This class simulates an analog to digital converter. The steps followed by this module to achieve the conversion are: 1) The following properties of the channel are read. They must be in the detector configuration file: * "adc_nbits", the number of bits of the ADC * "adc_reference_voltage", the reference voltage in volts, that is, the maximum voltage the ADC can convert without saturating * "adc_sampling_frequency", the sampling frequency in GHz 2) A random clock offset (jitter) can be added, as it would happen in a real experiment. Choose random_clock_offset = True to do so. A time delay can also be fixed if the field "adc_time_delay" is specified in ns. The channel trace is interpolated to get the trace values at the clock times displaced from the channel times. This is fine as long as the input channel traces have been simulated with a sampling rate greater than the ADC sampling rate, which should be the case. Upsampling is also possible, and recommended for phased array simulations. .. Important:: Upsampling after digitisation is performed by the FPGA, which means that the digitised trace is no longer discretised after being upsampled. The FPGA uses fixed point arithmetic, which in practice can be approximated as floats for our simulation purposes. 3) A type of ADC converter is chosen, which transforms the trace in ADC counts (discrete values). The available types are listed in the list _adc_types, which are (see functions with the same names for documentation): * 'perfect_floor_comparator' * 'perfect_ceiling_comparator' .. Important:: Since this module already performs a downsampling, there is no need to use the channelResampler in those channels that possess an ADC. The chosen method for resampling is interpolation, since filtering only the spectrum below half the sampling frequency would eliminate the higher Nyquist zones. Note that after this module the traces are still expressed in voltage units, only the possible values are discretised. If the ADC is used for triggering and the user does not want to modify the trace, the function get_digital_trace can be used. If there are two different ADCs for the same channel, one for triggering and another one for storing, one can define a trigger ADC adding `"trigger_"` to every relevant ADC field in the detector configuration, and use them setting `trigger_adc` to True in `get_digital_trace`. """ def __init__(self): self.__t = 0 self._adc_types = {'perfect_floor_comparator': perfect_floor_comparator, 'perfect_ceiling_comparator': perfect_ceiling_comparator} self._mandatory_fields = ['adc_nbits', 'adc_noise_nbits', 'adc_sampling_frequency'] self.logger = logging.getLogger('NuRadioReco.analogToDigitalConverter')
[docs] def get_digital_trace(self, station, det, channel, Vrms=None, trigger_adc=False, clock_offset=0.0, adc_type='perfect_floor_comparator', return_sampling_frequency=False, adc_output='voltage', trigger_filter=None): """ Returns the digital trace for a channel, without setting it. This allows the creation of a digital trace that can be used for triggering purposes without removing the original information on the channel. Parameters ---------- station: framework.station.Station object det: detector.detector.Detector object channel: framework.channel.Channel object Vrms: float If supplied, overrides adc_reference_voltage as supplied in the detector description file trigger_adc: bool If True, the relevant ADC parameters in the config file are the ones that start with `'trigger_'` random_clock_offset: bool If True, a random clock offset between -1 and 1 clock cycles is added adc_type: string The type of ADC used. The following are available: * perfect_floor_comparator * perfect_ceiling_comparator See functions with the same name on this module for documentation return_sampling_frequency: bool If True, returns the trace and the ADC sampling frequency adc_output: string Options: * 'voltage' to store the ADC output as discretised voltage trace * 'counts' to store the ADC output in ADC counts trigger_filter: array floats Freq. domain of the response to be applied to post-ADC traces Must be length for "MC freq" Returns ------- digital_trace: array of floats Digitised voltage trace adc_sampling_frequency: float ADC sampling frequency for the channel """ station_id = station.get_id() channel_id = channel.get_id() det_channel = det.get_channel(station_id, channel_id) for field in self._mandatory_fields: if(trigger_adc): field_check = 'trigger_' + field else: field_check = field if(field_check) not in det_channel: channel_id = channel.get_id() error_msg = "The field {} is not present in channel {}. ".format(field_check, channel_id) error_msg += "Please specify it on your detector file" raise ValueError(error_msg) times = channel.get_times()[:] trace = channel.get_trace()[:] MC_sampling_frequency = channel.get_sampling_rate() if(trigger_adc): # assumes that the trigger uses adc_time_delay_label = "trigger_adc_time_delay" adc_n_bits_label = "trigger_adc_nbits" adc_noise_n_bits_label = "trigger_adc_noise_nbits" adc_ref_voltage_label = "trigger_adc_reference_voltage" adc_sampling_frequency_label = "trigger_adc_sampling_frequency" else: adc_time_delay_label = "adc_time_delay" adc_n_bits_label = "adc_nbits" adc_noise_n_bits = "adc_noise_nbits" adc_noise_n_bits_label = "adc_noise_nbits" adc_ref_voltage_label = "adc_reference_voltage" adc_sampling_frequency_label = "adc_sampling_frequency" adc_time_delay = 0 if(adc_time_delay_label in det_channel): if(det_channel[adc_time_delay_label] is not None): adc_time_delay = det_channel[adc_time_delay_label] * units.ns adc_n_bits = det_channel[adc_n_bits_label] adc_noise_n_bits = det_channel[adc_noise_n_bits_label] adc_sampling_frequency = det_channel[adc_sampling_frequency_label] * units.GHz adc_time_delay += clock_offset / adc_sampling_frequency if(Vrms is None): if(adc_ref_voltage_label not in det_channel): error_msg = "The field {} is not present in channel {}. ".format(adc_ref_voltage_label, channel_id) error_msg += "Please specify it on your detector file" raise ValueError(error_msg) adc_ref_voltage = det_channel[adc_ref_voltage_label] * units.V else: adc_ref_voltage = Vrms * (2 ** (adc_n_bits - 1) - 1) / (2 ** (adc_noise_n_bits - 1) - 1) if(adc_sampling_frequency > channel.get_sampling_rate()): error_msg = 'The ADC sampling rate is greater than ' error_msg += 'the channel {} sampling rate. '.format(channel.get_id()) error_msg += 'Please change the ADC sampling rate.' raise ValueError(error_msg) if trigger_filter is not None: trace_fft = np.fft.rfft(trace) if len(trace_fft) != len(trigger_filter): raise ValueError("Wrong filter length to apply to traces") trace = np.fft.irfft(trace_fft * trigger_filter) # Random clock offset delayed_samples = len(trace) - int(np.round(MC_sampling_frequency / adc_sampling_frequency)) - 1 trace = delay_trace(trace, MC_sampling_frequency, adc_time_delay, delayed_samples) times = times + 1.0 / adc_sampling_frequency times = times[:len(trace)] # Upsampling to 5 GHz before downsampling using interpolation. # We cannot downsample with a Fourier method because we want to keep # the higher Nyquist zones. upsampling_frequency = 5.0 * units.GHz if(upsampling_frequency > MC_sampling_frequency): upsampling_nsamples = int(upsampling_frequency * len(trace) / MC_sampling_frequency) perfectly_upsampled_trace = resample(trace, upsampling_nsamples) perfectly_upsampled_times = np.arange(len(perfectly_upsampled_trace)) / upsampling_frequency perfectly_upsampled_times += times[0] else: perfectly_upsampled_trace = trace[:] perfectly_upsampled_times = times[:] interpolate_delayed_trace = interp1d(perfectly_upsampled_times, perfectly_upsampled_trace, kind='linear', fill_value=(perfectly_upsampled_trace[0], perfectly_upsampled_trace[-1]), bounds_error=False) # Downsampling to ADC frequency new_n_samples = int((adc_sampling_frequency / MC_sampling_frequency) * len(trace)) resampled_times = np.arange(new_n_samples) / adc_sampling_frequency resampled_times += channel.get_trace_start_time() resampled_trace = interpolate_delayed_trace(resampled_times) # Digitisation digital_trace = self._adc_types[adc_type](resampled_trace, adc_n_bits, adc_ref_voltage, adc_output) # Ensuring trace has an even number of samples if(len(digital_trace) % 2 == 1): digital_trace = digital_trace[:-1] if return_sampling_frequency: return digital_trace, adc_sampling_frequency else: return digital_trace
[docs] @register_run() def run(self, evt, station, det, clock_offset=0.0, adc_type='perfect_floor_comparator', adc_output='voltage', trigger_filter=None): """ Runs the analogToDigitalConverter and transforms the traces from all the channels of an input station to digital voltage values. Parameters ---------- evt: framework.event.Event object station: framework.station.Station object det: detector.detector.Detector object clock_offset: float adc_type: string The type of ADC used. The following are available: * 'perfect_floor_comparator' See functions with the same name on this module for documentation adc_output: string Options: * 'voltage' to store the ADC output as discretised voltage trace * 'counts' to store the ADC output in ADC counts upsampling_factor: integer Upsampling factor. The digital trace will be a upsampled to a sampling frequency int_factor times higher than the original one """ t = time.time() for channel in station.iter_channels(): digital_trace, adc_sampling_frequency = self.get_digital_trace(station, det, channel, clock_offset=clock_offset, adc_type=adc_type, return_sampling_frequency=True, adc_output=adc_output, trigger_filter=trigger_filter) channel.set_trace(digital_trace, adc_sampling_frequency) self.__t += time.time() - t
[docs] def end(self): from datetime import timedelta self.logger.setLevel(logging.INFO) dt = timedelta(seconds=self.__t) self.logger.info("total time used by this module is {}".format(dt)) return dt