NuRadioReco.framework.channel module

class NuRadioReco.framework.channel.Channel(channel_id, channel_group_id=None)[source]

Bases: BaseTrace

Parameters:

channel_id: int: the id of the channel
channel_group_id: int (default None): optionally, several channels can belong to a “channel group”. Use case is to identify the channels of a single dual or triple polarized antenna as common in air shower arrays.

Methods

`add_to_trace`(channel)	Adds the trace of another channel to the trace of this channel.
`apply_time_shift`(delta_t[, silent])	Uses the fourier shift theorem to apply a time shift to the trace Note that this is a cyclic shift, which means the trace will wrap around, which might lead to problems, especially for large time shifts.
`get_filtered_trace`(passband[, filter_type, ...])	Returns the trace after applying a filter to it.
`get_frequencies`([window_mask])	Returns the frequencies of the frequency spectrum.
`get_frequency_spectrum`([window_mask])	Returns the frequency spectrum.
`get_group_id`()	channel group id If no group id is specified, the channel id is returned.
`get_number_of_samples`()	Returns the number of samples in the time domain.
`get_sampling_rate`()	Returns the sampling rate of the trace.
`get_trace`()	Returns the time trace.
`set_frequency_spectrum`(frequency_spectrum, ...)	Sets the frequency spectrum.
`set_trace`(trace, sampling_rate)	Sets the time trace.

add_trace_start_time
deserialize
get_hilbert_envelope
get_hilbert_envelope_mag
get_id
get_parameter
get_parameters
get_times
get_trace_start_time
has_parameter
resample
serialize
set_parameter
set_trace_start_time

get_parameter(key)[source]

get_parameters()[source]

set_parameter(key, value)[source]

has_parameter(key)[source]

get_id()[source]

get_group_id()[source]: channel group id If no group id is specified, the channel id is returned. This allows using modules that use the group_id feature also on detector setups that don’t use this feature.

serialize(save_trace)[source]

deserialize(data_pkl)[source]

add_to_trace(channel)

Adds the trace of another channel to the trace of this channel. The trace is only added within the time window of “this” channel. If this channel is an empty trace with a defined _sampling_rate and _trace_start_time, and a _time_trace containing zeros, this function can be seen as recording a channel in the specified readout window.

Parameters:

channel: BaseTrace: The channel whose trace is to be added to the trace of this channel.

add_trace_start_time(start_time)

apply_time_shift(delta_t, silent=False)

Uses the fourier shift theorem to apply a time shift to the trace Note that this is a cyclic shift, which means the trace will wrap around, which might lead to problems, especially for large time shifts.

Parameters:

delta_t: float: Time by which the trace should be shifted
silent: boolean (default:False): Turn off warnings if time shift is larger than 10% of trace length Only use this option if you are sure that your trace is long enough to acommodate the time shift

get_filtered_trace(passband, filter_type='butter', order=10, rp=None)

Returns the trace after applying a filter to it. This does not change the stored trace.

Parameters:

passband: list of floats: lower and upper bound of the filter passband
filter_type: string: type of the applied filter. Options are rectangular, butter and butterabs
order: int: Order of the Butterworth filter, if the filter types butter or butterabs are chosen

get_frequencies(window_mask=None)

Returns the frequencies of the frequency spectrum.

Parameters:

window_mask: array of bools (default: None): If not None, used to determine the number of samples in the time domain used for the frequency spectrum.

Returns:

frequencies: np.array of floats: The frequencies of the frequency spectrum.

get_frequency_spectrum(window_mask=None)

Returns the frequency spectrum.

Parameters:

window_mask: array of bools (default: None): If not None, specifies the time window to be used for the FFT. Has to have the same length as the trace.

Returns:

frequency_spectrum: np.array of floats: The frequency spectrum.

get_hilbert_envelope()

get_hilbert_envelope_mag()

get_number_of_samples()

Returns the number of samples in the time domain.

Returns:

n_samples: int: number of samples in time domain

get_sampling_rate()

Returns the sampling rate of the trace.

Returns:

sampling_rate: float: sampling rate, i.e., the inverse of the bin width

get_times()

get_trace()

Returns the time trace.

If the frequency spectrum was modified before, an ifft is performed automatically to have the time domain representation up to date.

Returns:

trace: np.array of floats: the time trace

get_trace_start_time()

resample(sampling_rate)

set_frequency_spectrum(frequency_spectrum, sampling_rate)

Sets the frequency spectrum.

Parameters:

frequency_spectrumnp.array of floats: The frequency spectrum
sampling_ratefloat or str: The sampling rate of the trace, i.e., the inverse of the bin width. If sampling_rate=”same”, sampling rate is not changed (requires previous initialisation).

set_trace(trace, sampling_rate)

Sets the time trace.

Parameters:

tracenp.array of floats: The time series
sampling_ratefloat or str: The sampling rate of the trace, i.e., the inverse of the bin width. If sampling_rate=”same”, sampling rate is not changed (requires previous initialisation).

set_trace_start_time(start_time)