edfio.BdfSignal#

class edfio.BdfSignal(data, sampling_frequency, *, label='', transducer_type='', physical_dimension='', physical_range=None, digital_range=(-8388608, 8388607), prefiltering='')[source]#

A single BDF signal.

See EdfSignal for details on the parameters and attributes.

Note

BDF uses 24-bit integers (compared to 16-bit for EDF) for the digital values. The default for digital_range (and the supported depth) thus differs.

Attributes

`data`	Numpy array containing the physical signal values as floats.
`digital`	Numpy array containing the digital (uncalibrated) signal values as integers.
`digital_max`	Digital maximum, e.g., `2047`.
`digital_min`	Digital minimum, e.g., `-2048`.
`digital_range`	The digital range as a tuple of `(digital_min, digital_max)`.
`label`	Signal label, e.g., `"EEG Fpz-Cz"` or `"Body temp"`.
`physical_dimension`	Physical dimension, e.g., `"uV"` or `"degreeC`.
`physical_max`	Physical maximum, e.g., `500` or `40`.
`physical_min`	Physical minimum, e.g., `-500` or `34`.
`physical_range`	The physical range as a tuple of `(physical_min, physical_max)`.
`prefiltering`	Signal prefiltering, e.g., `"HP:0.1Hz LP:75Hz"`.
`reserved`	Reserved signal header field, always `""`.
`samples_per_data_record`	Number of samples in each data record.
`sampling_frequency`	The sampling frequency in Hz.
`transducer_type`	Transducer type, e.g., `"AgAgCl electrode"`.

Methods

`__init__`
`from_hypnogram`	Create an EDF signal from a hypnogram, with scaling according to EDF specs.
`get_data_slice`	Get a slice of the signal data.
`get_digital_slice`	Get a slice of the digital signal values.
`update_data`	Overwrite physical signal values with an array of equal length.

property data[source]#

Numpy array containing the physical signal values as floats.

To simplify avoiding inconsistencies between signal data and header fields, individual values in the returned array can not be modified. Use BdfSignal.update_data() to overwrite with new physical data.

property digital[source]#

Numpy array containing the digital (uncalibrated) signal values as integers.

The values of the array may be accessed and modified directly.

For EDF these are 16-bit integers, for BDF these are 32-bit integers.

property digital_max[source]#: Digital maximum, e.g., 2047.

property digital_min[source]#: Digital minimum, e.g., -2048.

property digital_range[source]#: The digital range as a tuple of (digital_min, digital_max).

classmethod from_hypnogram(stages, stage_duration=30, *, label='')[source]#

Create an EDF signal from a hypnogram, with scaling according to EDF specs.

According to the EDF FAQ [1], use integer numbers 0, 1, 2, 3, 4, 5, 6, and 9 for sleep stages W, 1, 2, 3, 4, R, MT, und unscored, respectively. The digital range is set to (0, 9).

Parameters:

stagesnpt.NDArray[np.float64]: The sleep stages, coded as integer numbers.
stage_durationfloat, default: 30: The duration of each sleep stage in seconds, used to set the sampling frequency to its inverse.
labelstr, default: "": The signal’s label.

Returns:

BdfSignal: The resulting BdfSignal object.

References

[1]

EDF FAQ, https://www.edfplus.info/specs/edffaq.html

get_data_slice(start_second, stop_second)[source]#

Get a slice of the signal data.

If the signal has not been loaded into memory so far, only the requested slice will be read.

Parameters:

start_secondfloat: The start of the slice in seconds.
stop_secondfloat: The end of the slice in seconds.

get_digital_slice(start_second, stop_second)[source]#

Get a slice of the digital signal values.

If the signal has not been loaded into memory so far, only the requested slice will be read.

Parameters:

start_secondfloat: The start of the slice in seconds.
stop_secondfloat: The end of the slice in seconds.

property label[source]#: Signal label, e.g., "EEG Fpz-Cz" or "Body temp".

property physical_dimension[source]#: Physical dimension, e.g., "uV" or "degreeC.

property physical_max[source]#: Physical maximum, e.g., 500 or 40.

property physical_min[source]#: Physical minimum, e.g., -500 or 34.

property physical_range[source]#: The physical range as a tuple of (physical_min, physical_max).

property prefiltering[source]#: Signal prefiltering, e.g., "HP:0.1Hz LP:75Hz".

property reserved[source]#: Reserved signal header field, always "".

property samples_per_data_record[source]#

Number of samples in each data record.

For newly instantiated BdfSignal objects, this is only set once Bdf.write() is called.

property sampling_frequency[source]#: The sampling frequency in Hz.

property transducer_type[source]#: Transducer type, e.g., "AgAgCl electrode".

update_data(data, *, keep_physical_range=False, sampling_frequency=None)[source]#

Overwrite physical signal values with an array of equal length.

Parameters:

datanpt.NDArray[np.float64]: The new physical data.
keep_physical_rangebool, default: False: If True, the physical_range is not modified to accomodate the new data.
sampling_frequencyfloat | None, default: None: If not None, the sampling_frequency is updated to the new value. The new data must match the expected length for the new sampling frequency.