PyEDFlib -EDF/BDF Toolbox in Python

PyEDFlib is a free Open Source wavelet toolbox for reading / writing EDF/EDF+/BDF files.

import pyedflib
import numpy as np

file_name = pyedflib.data.get_generator_filename()
f = pyedflib.EdfReader(file_name)
n = f.signals_in_file
signal_labels = f.getSignalLabels()
sigbufs = np.zeros((n, f.getNSamples()[0]))
for i in np.arange(n):
        sigbufs[i, :] = f.readSignal(i)

Description

PyEDFlib is a Python library to read/write EDF/EDF+/BDF files based on EDFlib.

EDF stands for European Data Format, a data format for EEG data, first published in 1992. In 2003, an improved version of the file protocol named EDF+ has been published.

The definition of the EDF/EDF+ format can be found under edfplus.info.

The EDF/EDF+ format saves all data with 16 Bit. A version of the format which saves all data with 24 Bit, called BDF, was introduced by the company BioSemi.

The PyEDFlib Python toolbox is a fork of the python-edf toolbox from Christopher Lee-Messer. and uses the EDFlib from Teunis van Beelen.

Requirements

PyEDFlib requires:

Download

The most recent development version can be found on GitHub at https://github.com/holgern/pyedflib.

The latest release, including source and binary package for Windows, is available for download from the Python Package Index or on the Releases Page.

License

This code is licensed under the same BSD-style license that Teunis released edflib under and with the same disclaimer.

Contents

API Reference

EDF/BDF file writer edfwriter

class pyedflib.EdfWriter(file_name, n_channels, file_type=1)[source]

Bases: object

Methods

blockWritePhysicalSamples(self, data) Writes physical samples (uV, mA, Ohm) must be filled with samples from all signals where each signal has n samples which is the samplefrequency of the signal.
close(self) Closes the file.
setAdmincode(self, admincode) Sets the admincode.
setBirthdate(self, birthdate) Sets the birthdate.
setDatarecordDuration(self, duration) Sets the datarecord duration.
setDigitalMaximum(self, edfsignal, …) Sets the maximum digital value of signal edfsignal.
setDigitalMinimum(self, edfsignal, …) Sets the minimum digital value of signal edfsignal.
setEquipment(self, equipment) Sets the name of the param equipment used during the aquisition.
setGender(self, gender) Sets the gender.
setHeader(self, fileHeader) Sets the file header
setLabel(self, edfsignal, label) Sets the label (name) of signal edfsignal (“FP1”, “SaO2”, etc.).
setPatientAdditional(self, patient_additional) Sets the additional patientinfo to patient_additional.
setPatientCode(self, patient_code) Sets the patientcode to patient_code.
setPatientName(self, patient_name) Sets the patientname to patient_name.
setPhysicalDimension(self, edfsignal, …) Sets the physical dimension of signal edfsignal (“uV”, “BPM”, “mA”, “Degr.”, etc.)
setPhysicalMaximum(self, edfsignal, …) Sets the physical_maximum of signal edfsignal.
setPhysicalMinimum(self, edfsignal, …) Sets the physical_minimum of signal edfsignal.
setPrefilter(self, edfsignal, prefilter) Sets the prefilter of signal edfsignal (“HP:0.1Hz”, “LP:75Hz N:50Hz”, etc.)
setRecordingAdditional(self, …) Sets the additional recordinginfo
setSamplefrequency(self, edfsignal, …) Sets the samplefrequency of signal edfsignal.
setSignalHeader(self, edfsignal, channel_info) Sets the parameter for signal edfsignal.
setSignalHeaders(self, signalHeaders) Sets the parameter for all signals
setStartdatetime(self, recording_start_time) Sets the recording start Time
setTechnician(self, technician) Sets the technicians name to technician.
setTransducer(self, edfsignal, transducer) Sets the transducer of signal edfsignal
set_number_of_annotation_signals(self, …) Sets the number of annotation signals.
update_header(self) Updates header to edffile struct
writeAnnotation(self, onset_in_seconds, …) Writes an annotation/event to the file
writePhysicalSamples(self, data) Writes n physical samples (uV, mA, Ohm) belonging to one signal where n is the samplefrequency of the signal.
writeSamples(self, data_list[, digital]) Writes physical samples (uV, mA, Ohm) from data belonging to all signals The physical samples will be converted to digital samples using the values of physical maximum, physical minimum, digital maximum and digital minimum.
blockWriteDigitalSamples  
blockWriteDigitalShortSamples  
writeDigitalSamples  
writeDigitalShortSamples  
blockWriteDigitalSamples(self, data)[source]
blockWriteDigitalShortSamples(self, data)[source]
blockWritePhysicalSamples(self, data)[source]

Writes physical samples (uV, mA, Ohm) must be filled with samples from all signals where each signal has n samples which is the samplefrequency of the signal.

data_vec belonging to one signal. The size must be the samplefrequency of the signal.

Notes

buf must be filled with samples from all signals, starting with signal 0, 1, 2, etc. one block equals one second The physical samples will be converted to digital samples using the values of physical maximum, physical minimum, digital maximum and digital minimum The number of samples written is equal to the sum of the samplefrequencies of all signals Size of buf should be equal to or bigger than sizeof(double) multiplied by the sum of the samplefrequencies of all signals Returns 0 on success, otherwise -1

All parameters must be already written into the bdf/edf-file.

close(self)[source]

Closes the file.

setAdmincode(self, admincode)[source]

Sets the admincode.

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

Parameters:
admincode : str

admincode which is written into the header
setBirthdate(self, birthdate)[source]

Sets the birthdate.

Parameters:
birthdate: date object from datetime

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

Examples

>>> import pyedflib
>>> from datetime import datetime, date
>>> f = pyedflib.EdfWriter('test.bdf', 1, file_type=pyedflib.FILETYPE_BDFPLUS)
>>> f.setBirthdate(date(1951, 8, 2))
>>> f.close()
setDatarecordDuration(self, duration)[source]

Sets the datarecord duration. The default value is 100000 which is 1 second. ATTENTION: the argument “duration” is expressed in units of 10 microSeconds! So, if you want to set the datarecord duration to 0.1 second, you must give the argument “duration” a value of “10000”. This function is optional, normally you don’t need to change the default value. The datarecord duration must be in the range 0.001 to 60 seconds. Returns 0 on success, otherwise -1.

Parameters:
duration : integer

Sets the datarecord duration in units of 10 microSeconds

Notes

This function is NOT REQUIRED but can be called after opening a file in writemode and before the first sample write action. This function can be used when you want to use a samplerate which is not an integer. For example, if you want to use a samplerate of 0.5 Hz, set the samplefrequency to 5 Hz and the datarecord duration to 10 seconds. Do not use this function, except when absolutely necessary!

setDigitalMaximum(self, edfsignal, digital_maximum)[source]

Sets the maximum digital value of signal edfsignal. Usually, the value 32767 is used for EDF+ and 8388607 for BDF+.

Parameters:
edfsignal : int

signal number

digital_maximum : int

Sets the maximum digital value

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setDigitalMinimum(self, edfsignal, digital_minimum)[source]

Sets the minimum digital value of signal edfsignal. Usually, the value -32768 is used for EDF+ and -8388608 for BDF+. Usually this will be (-(digital_maximum + 1)).

Parameters:
edfsignal : int

signal number

digital_minimum : int

Sets the minimum digital value

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setEquipment(self, equipment)[source]

Sets the name of the param equipment used during the aquisition. This function is optional and can be called only after opening a file in writemode and before the first sample write action.

Parameters:
equipment : str

Describes the measurement equpipment
setGender(self, gender)[source]

Sets the gender. This function is optional and can be called only after opening a file in writemode and before the first sample write action.

Parameters:
gender : int

1 is male, 0 is female
setHeader(self, fileHeader)[source]

Sets the file header

setLabel(self, edfsignal, label)[source]

Sets the label (name) of signal edfsignal (“FP1”, “SaO2”, etc.).

Parameters:
edfsignal : int

signal number on which the label should be changed

label : str

signal label

Notes

This function is recommended for every signal and can be called only after opening a file in writemode and before the first sample write action.

setPatientAdditional(self, patient_additional)[source]

Sets the additional patientinfo to patient_additional.

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setPatientCode(self, patient_code)[source]

Sets the patientcode to patient_code.

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setPatientName(self, patient_name)[source]

Sets the patientname to patient_name.

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setPhysicalDimension(self, edfsignal, physical_dimension)[source]

Sets the physical dimension of signal edfsignal (“uV”, “BPM”, “mA”, “Degr.”, etc.)

Parameters:
  • edfsignal – int
  • physical_dimension – str

Notes

This function is recommended for every signal and can be called only after opening a file in writemode and before the first sample write action.

setPhysicalMaximum(self, edfsignal, physical_maximum)[source]

Sets the physical_maximum of signal edfsignal.

Parameters:
edfsignal: int

signal number

physical_maximum: float

Sets the physical maximum

Notes

This function is required for every signal and can be called only after opening a file in writemode and before the first sample write action.

setPhysicalMinimum(self, edfsignal, physical_minimum)[source]

Sets the physical_minimum of signal edfsignal.

Parameters:
edfsignal: int

signal number

physical_minimum: float

Sets the physical minimum

Notes

This function is required for every signal and can be called only after opening a file in writemode and before the first sample write action.

setPrefilter(self, edfsignal, prefilter)[source]

Sets the prefilter of signal edfsignal (“HP:0.1Hz”, “LP:75Hz N:50Hz”, etc.)

Parameters:
  • edfsignal – int
  • prefilter – str

Notes

This function is optional for every signal and can be called only after opening a file in writemode and before the first sample write action.

setRecordingAdditional(self, recording_additional)[source]

Sets the additional recordinginfo

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setSamplefrequency(self, edfsignal, samplefrequency)[source]

Sets the samplefrequency of signal edfsignal.

Notes

This function is required for every signal and can be called only after opening a file in writemode and before the first sample write action.

setSignalHeader(self, edfsignal, channel_info)[source]

Sets the parameter for signal edfsignal.

channel_info should be a dict with these values:

‘label’ : channel label (string, <= 16 characters, must be unique) ‘dimension’ : physical dimension (e.g., mV) (string, <= 8 characters) ‘sample_rate’ : sample frequency in hertz (int). Deprecated: use ‘sample_frequency’ instead. ‘sample_frequency’ : number of samples per record (int) ‘physical_max’ : maximum physical value (float) ‘physical_min’ : minimum physical value (float) ‘digital_max’ : maximum digital value (int, -2**15 <= x < 2**15) ‘digital_min’ : minimum digital value (int, -2**15 <= x < 2**15)
setSignalHeaders(self, signalHeaders)[source]

Sets the parameter for all signals

Parameters:
signalHeaders : array_like
containing dict with
‘label’ : str

channel label (string, <= 16 characters, must be unique)

‘dimension’ : str

physical dimension (e.g., mV) (string, <= 8 characters)

‘sample_rate’ :

sample frequency in hertz (int). Deprecated: use ‘sample_frequency’ instead.

‘sample_frequency’ : int

number of samples per record

‘physical_max’ : float

maximum physical value

‘physical_min’ : float

minimum physical value

‘digital_max’ : int

maximum digital value (-2**15 <= x < 2**15)

‘digital_min’ : int

minimum digital value (-2**15 <= x < 2**15)
setStartdatetime(self, recording_start_time)[source]

Sets the recording start Time

Parameters:
recording_start_time: datetime object

Sets the recording start Time
setTechnician(self, technician)[source]

Sets the technicians name to technician.

Notes

This function is optional and can be called only after opening a file in writemode and before the first sample write action.

setTransducer(self, edfsignal, transducer)[source]

Sets the transducer of signal edfsignal

Parameters:
  • edfsignal – int
  • transducer – str

Notes

This function is optional for every signal and can be called only after opening a file in writemode and before the first sample write action.

set_number_of_annotation_signals(self, number_of_annotations)[source]

Sets the number of annotation signals. The default value is 1 This function is optional and can be called only after opening a file in writemode and before the first sample write action Normally you don’t need to change the default value. Only when the number of annotations you want to write is more than the number of seconds of the duration of the recording, you can use this function to increase the storage space for annotations Minimum is 1, maximum is 64

Parameters:
number_of_annotations : integer

Sets the number of annotation signals
update_header(self)[source]

Updates header to edffile struct

writeAnnotation(self, onset_in_seconds, duration_in_seconds, description, str_format='utf-8')[source]

Writes an annotation/event to the file

writeDigitalSamples(self, data)[source]
writeDigitalShortSamples(self, data)[source]
writePhysicalSamples(self, data)[source]

Writes n physical samples (uV, mA, Ohm) belonging to one signal where n is the samplefrequency of the signal.

data_vec belonging to one signal. The size must be the samplefrequency of the signal.

Notes

Writes n physical samples (uV, mA, Ohm) from data_vec belonging to one signal where n is the samplefrequency of the signal. The physical samples will be converted to digital samples using the values of physical maximum, physical minimum, digital maximum and digital minimum. The number of samples written is equal to the samplefrequency of the signal. Call this function for every signal in the file. The order is important! When there are 4 signals in the file, the order of calling this function must be: signal 0, signal 1, signal 2, signal 3, signal 0, signal 1, signal 2, etc.

All parameters must be already written into the bdf/edf-file.

writeSamples(self, data_list, digital=False)[source]

Writes physical samples (uV, mA, Ohm) from data belonging to all signals The physical samples will be converted to digital samples using the values of physical maximum, physical minimum, digital maximum and digital minimum. if the samplefrequency of all signals are equal, then the data could be saved into a matrix with the size (N,signals) If the samplefrequency is different, then sample_freq is a vector containing all the different samplefrequencys. The data is saved as list. Each list entry contains a vector with the data of one signal.

If digital is True, digital signals (as directly from the ADC) will be expected. (e.g. int16 from 0 to 2048)

All parameters must be already written into the bdf/edf-file.

This section describes functions used to perform reading of a EDF/BDF file.

EDF/BDF file reader edfreader

class pyedflib.EdfReader[source]

Bases: pyedflib._extensions._pyedflib.CyEdfReader

This provides a simple interface to read EDF, EDF+, BDF and BDF+ files.

Attributes:
admincode
annotations_in_file
birthdate
datarecord_duration

datarecord duration in seconds (as a double)

datarecords_in_file

number of data records

equipment
file_duration

file duration in seconds

filetype
gender
handle

edflib internal int handle

patient

patient name?

patient_additional
patientcode
patientname
recording_additional
signals_in_file
startdate_day
startdate_month
startdate_year
starttime_hour
starttime_minute
starttime_second
starttime_subsecond
technician

Methods

close(self) Closes the file handler
file_info_long(self) Returns information about the opened EDF/BDF file
getAdmincode(self) Returns the Admincode.
getBirthdate(self[, string]) Returns the birthdate as string object
getDigitalMaximum(self[, chn]) Returns the maximum digital value of signal edfsignal.
getDigitalMinimum(self[, chn]) Returns the minimum digital value of signal edfsignal.
getEquipment(self) Returns the used Equipment.
getFileDuration(self) Returns the duration of the file in seconds.
getGender(self) Returns the Gender of the patient.
getHeader(self) Returns the file header as dict
getLabel(self, chn) Returns the label (name) of signal chn (“FP1”, “SaO2”, etc.).
getPatientAdditional(self) Returns the additional patientinfo.
getPatientCode(self) Returns the patientcode
getPatientName(self) Returns the patientname
getPhysicalDimension(self, chn) Returns the physical dimension of signal edfsignal (“uV”, “BPM”, “mA”, “Degr.”, etc.)
getPhysicalMaximum(self[, chn]) Returns the maximum physical value of signal edfsignal.
getPhysicalMinimum(self[, chn]) Returns the minimum physical value of signal edfsignal.
getPrefilter(self, chn) Returns the prefilter of signal chn (“HP:0.1Hz”, “LP:75Hz N:50Hz”, etc.)
getRecordingAdditional(self) Returns the additional recordinginfo
getSampleFrequencies(self) Returns samplefrequencies of all signals.
getSampleFrequency(self, chn) Returns the samplefrequency of signal edfsignal.
getSignalHeader(self, chn) Returns the header of one signal as dicts
getSignalHeaders(self) Returns the header of all signals as array of dicts
getSignalLabels(self) Returns all labels (name) (“FP1”, “SaO2”, etc.).
getStartdatetime(self) Returns the date and starttime as datetime object
getTechnician(self) Returns the technicians name
getTransducer(self, chn) Returns the transducer of signal chn (“AgAgCl cup electrodes”, etc.).
make_buffer() utilty function to make a buffer that can hold a single datarecord.
open(file_name, annotations_mode, …)
readAnnotations(self) Annotations from a edf-file
readSignal(self, chn[, start, n, digital]) Returns the physical data of signal chn.
read_digital_signal() read_digital_signal(self, signalnum, start, n, np.ndarray[np.int32_t, ndim=1] sigbuf read @n number of samples from signal number @signum starting at @start into numpy int32 array @sigbuf sigbuf must be at least n long
readsignal() read @n number of samples from signal number @signum starting at @start into numpy float64 array @sigbuf sigbuf must be at least n long
check_open_ok  
digital_max  
digital_min  
file_info  
getNSamples  
load_datarecord  
physical_dimension  
physical_max  
physical_min  
prefilter  
read_annotation  
samplefrequency  
samples_in_datarecord  
samples_in_file  
signal_label  
transducer  
close(self)[source]

Closes the file handler

file_info(self)[source]
file_info_long(self)[source]

Returns information about the opened EDF/BDF file

getAdmincode(self)[source]

Returns the Admincode.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getAdmincode()==''
True
>>> f.close()
getBirthdate(self, string=True)[source]

Returns the birthdate as string object

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getBirthdate()=='30 jun 1969'
True
>>> f.close()
getDigitalMaximum(self, chn=None)[source]

Returns the maximum digital value of signal edfsignal.

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getDigitalMaximum(0)
32767
>>> f.close()
getDigitalMinimum(self, chn=None)[source]

Returns the minimum digital value of signal edfsignal.

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getDigitalMinimum(0)
-32768
>>> f.close()
getEquipment(self)[source]

Returns the used Equipment.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getEquipment()=='test generator'
True
>>> f.close()
getFileDuration(self)[source]

Returns the duration of the file in seconds.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getFileDuration()==600
True
>>> f.close()
getGender(self)[source]

Returns the Gender of the patient.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getGender()==''
True
>>> f.close()
getHeader(self)[source]

Returns the file header as dict

Parameters:
None
getLabel(self, chn)[source]

Returns the label (name) of signal chn (“FP1”, “SaO2”, etc.).

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getLabel(0)=='squarewave'
True
>>> f.close()
getNSamples(self)[source]
getPatientAdditional(self)[source]

Returns the additional patientinfo.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPatientAdditional()==''
True
>>> f.close()
getPatientCode(self)[source]

Returns the patientcode

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPatientCode()==''
True
>>> f.close()
getPatientName(self)[source]

Returns the patientname

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPatientName()=='X'
True
>>> f.close()
getPhysicalDimension(self, chn)[source]

Returns the physical dimension of signal edfsignal (“uV”, “BPM”, “mA”, “Degr.”, etc.)

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPhysicalDimension(0)=='uV'
True
>>> f.close()
getPhysicalMaximum(self, chn=None)[source]

Returns the maximum physical value of signal edfsignal.

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPhysicalMaximum(0)==1000.0
True
>>> f.close()
getPhysicalMinimum(self, chn=None)[source]

Returns the minimum physical value of signal edfsignal.

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPhysicalMinimum(0)==-1000.0
True
>>> f.close()
getPrefilter(self, chn)[source]

Returns the prefilter of signal chn (“HP:0.1Hz”, “LP:75Hz N:50Hz”, etc.)

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getPrefilter(0)==''
True
>>> f.close()
getRecordingAdditional(self)[source]

Returns the additional recordinginfo

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getRecordingAdditional()==''
True
>>> f.close()
getSampleFrequencies(self)[source]

Returns samplefrequencies of all signals.

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> all(f.getSampleFrequencies()==200.0)
True
>>> f.close()
getSampleFrequency(self, chn)[source]

Returns the samplefrequency of signal edfsignal.

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getSampleFrequency(0)==200.0
True
>>> f.close()
getSignalHeader(self, chn)[source]

Returns the header of one signal as dicts

Parameters:
None
getSignalHeaders(self)[source]

Returns the header of all signals as array of dicts

Parameters:
None
getSignalLabels(self)[source]

Returns all labels (name) (“FP1”, “SaO2”, etc.).

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getSignalLabels()==['squarewave', 'ramp', 'pulse', 'noise', 'sine 1 Hz', 'sine 8 Hz', 'sine 8.1777 Hz', 'sine 8.5 Hz', 'sine 15 Hz', 'sine 17 Hz', 'sine 50 Hz']
True
>>> f.close()
getStartdatetime(self)[source]

Returns the date and starttime as datetime object

Parameters:
None

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getStartdatetime()
datetime.datetime(2011, 4, 4, 12, 57, 2)
>>> f.close()
getTechnician(self)[source]

Returns the technicians name

Parameters:
None
.. code-block:: python
>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getTechnician()==''
True
>>> f.close()
getTransducer(self, chn)[source]

Returns the transducer of signal chn (“AgAgCl cup electrodes”, etc.).

Parameters:
chn : int

channel number

Examples

>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> f.getTransducer(0)==''
True
>>> f.close()
readAnnotations(self)[source]

Annotations from a edf-file

Parameters:
None
readSignal(self, chn, start=0, n=None, digital=False)[source]

Returns the physical data of signal chn. When start and n is set, a subset is returned

Parameters:
chn : int

channel number

start : int

start pointer (default is 0)

n : int

length of data to read (default is None, by which the complete data of the channel are returned)

digital: bool

will return the signal in original digital values instead of physical values

Examples
——–
>>> import pyedflib
>>> f = pyedflib.data.test_generator()
>>> x = f.readSignal(0,0,1000)
>>> int(x.shape[0])
1000
>>> x2 = f.readSignal(0)
>>> int(x2.shape[0])
120000
>>> f.close()

EDF/BDF highlevel functions

pyedflib.highlevel.change_polarity(edf_file, channels, new_file=None, verify=True, verbose=False)[source]

Change polarity of certain channels

Parameters:
edf_file : str

from which file to change polarity.

channels : list of int

the indices of the channels.

new_file : str, optional

where to save the edf with inverted channels. The default is None.

verify : bool, optional

whether to verify the two edfs for similarity. The default is True.

verbose : str, optional

print progress or not. The default is True.
Returns:
bool

True if success.
pyedflib.highlevel.rename_channels(edf_file, mapping, new_file=None, verbose=False)[source]

A convenience function to rename channels in an EDF file.

Parameters:
edf_file : str

an string pointing to an edf file.

mapping : dict

a dictionary with channel mappings as key:value. eg: {‘M1-O2’:’A1-O2’}

new_file : str, optional

the new filename. If None will be edf_file + ‘_renamed’ The default is None.

verbose : bool, optional

print progress or not. The default is False.
Returns:
bool

True if successful, False if failed.
pyedflib.highlevel.anonymize_edf(edf_file, new_file=None, to_remove=['patientname', 'birthdate'], new_values=['xxx', ''], verify=False, verbose=False)[source]

Anonymize an EDF file by replacing values of header fields.

This function can be used to overwrite all header information that is patient specific, for example birthdate and patientname. All header fields can be overwritten this way (i.e., all header.keys() given _, _, header = read_edf(edf_file, digital=True)).

Parameters:
edf_file : str

Filename of an EDF/BDF.

new_file : str | None

The filename of the anonymized file. If None, the input filename appended with ‘_anonymized’ is used. Defaults to None.

to_remove : list of str

List of attributes to overwrite in the edf_file. Defaults to [‘patientname’, ‘birthdate’].

new_values : list of str

List of values used for overwriting the attributes specified in to_remove. Each item in to_remove must have a corresponding item in new_values. Defaults to [‘xxx’, ‘’].

verify : bool

Compare edf_file and new_file for equality (i.e., double check that values are same). Defaults to False

verbose : bool, optional

print progress or not. The default is False.
Returns:
bool

True if successful, or if verify is False. Raises an error otherwise.
pyedflib.highlevel.drop_channels(edf_source, edf_target=None, to_keep=None, to_drop=None, verbose=False)[source]

Remove channels from an edf file. Save the file. For safety reasons, no source files can be overwritten.

Parameters:
edf_source : str

The source edf file from which to drop channels.

edf_target : str, optional

Where to save the file.If None, will be edf_source+’dropped.edf’. The default is None.

to_keep : list, optional

A list of channel names or indices that will be kept. Strings will always be interpreted as channel names. ‘to_keep’ will overwrite any droppings proposed by to_drop. The default is None.

to_drop : list, optional

A list of channel names/indices that should be dropped. Strings will be interpreted as channel names. The default is None.

verbose : bool, optional

print progress or not. The default is False.
Returns:
edf_target : str

the target filename with the dropped channels.
pyedflib.highlevel.compare_edf(edf_file1, edf_file2, verbose=False)[source]

Loads two edf files and checks whether the values contained in them are the same. Does not check the header or annotations data.

Mainly to verify that other options (eg anonymization) produce the same EDF file.

Parameters:
edf_file1 : str

edf file 1 to compare.

edf_file2 : str

edf file 2 to compare.

verbose : bool, optional

print progress or not. The default is False.
Returns:
bool

True if signals are equal, else raises error.
pyedflib.highlevel.read_edf_header(edf_file, read_annotations=True)[source]

Reads the header and signal headers of an EDF file and it’s annotations

Parameters:
edf_file : str

EDF/BDF file to read.
Returns:
summary : dict

header of the edf file as dictionary.
pyedflib.highlevel.write_edf_quick(edf_file, signals, sfreq, digital=False)[source]

wrapper for write_pyedf without creating headers. Use this if you don’t care about headers or channel names and just want to dump some signals with the same sampling freq. to an edf

Parameters:
edf_file : str

where to store the data/edf.

signals : np.ndarray

The signals you want to store as numpy array.

sfreq : int

the sampling frequency of the signals.

digital : bool, optional

if the data is present digitally (int) or as mV/uV.The default is False.
Returns:
bool

True if successful, else False or raise Error.
pyedflib.highlevel.write_edf(edf_file, signals, signal_headers, header=None, digital=False, file_type=-1, block_size=1)[source]

Write signals to an edf_file. Header can be generated on the fly with generic values. EDF+/BDF+ is selected based on the filename extension, but can be overwritten by setting file_type to pyedflib.FILETYPE_XXX

Parameters:
edf_file : np.ndarray or list

where to save the EDF file

signals : list

The signals as a list of arrays or a ndarray.

signal_headers : list of dict

a list with one signal header(dict) for each signal. See pyedflib.EdfWriter.setSignalHeader..

header : dict

a main header (dict) for the EDF file, see pyedflib.EdfWriter.setHeader for details. If no header present, will create an empty header

digital : bool, optional

whether the signals are in digital format (ADC). The default is False.

file_type: int, optional

choose file_type for saving. EDF = 0, EDF+ = 1, BDF = 2, BDF+ = 3, automatic from extension = -1

block_size : int

set the block size for writing. Should be divisor of signal length in seconds. Higher values mean faster writing speed, but if it is not a divisor of the signal duration, it will append zeros. Can be any value between 1=><=60, -1 will auto-infer the fastest value.
Returns:
bool

True if successful, False if failed.
pyedflib.highlevel.read_edf(edf_file, ch_nrs=None, ch_names=None, digital=False, verbose=False)[source]

Convenience function for reading EDF+/BDF data with pyedflib.

Will load the edf and return the signals, the headers of the signals and the header of the EDF. If all signals have the same sample frequency will return a numpy array, else a list with the individual signals

Parameters:
edf_file : str

link to an edf file.

ch_nrs : list of int, optional

The indices of the channels to read. The default is None.

ch_names : list of str, optional

The names of channels to read. The default is None.

digital : bool, optional

will return the signals as digital values (ADC). The default is False.

verbose : bool, optional

Print progress bar while loading or not. The default is False.
Returns:
signals : np.ndarray or list

the signals of the chosen channels contained in the EDF.

signal_headers : list

one signal header for each channel in the EDF.

header : dict

the main header of the EDF file containing meta information.
pyedflib.highlevel.make_signal_headers(list_of_labels, dimension='uV', sample_rate=256, sample_frequency=None, physical_min=-200.0, physical_max=200.0, digital_min=-32768, digital_max=32767, transducer='', prefiler='')[source]

A function that creates signal headers for a given list of channel labels. This can only be used if each channel has the same sampling frequency

Parameters:
list_of_labels : list of str

A list with labels for each channel.

dimension : str, optional

dimension, eg mV. The default is ‘uV’.

sample_rate : int, optional

sampling frequency. The default is 256. Deprecated: use ‘sample_frequency’ instead.

sample_frequency : int, optional

sampling frequency. The default is 256.

physical_min : float, optional

minimum value in dimension. The default is -200.

physical_max : float, optional

maximum value in dimension. The default is 200.

digital_min : int, optional

digital minimum of the ADC. The default is -32768.

digital_max : int, optional

digital maximum of the ADC. The default is 32767.

transducer : str, optional

electrode type that was used. The default is ‘’.

prefiler : str, optional

filtering and sampling method. The default is ‘’.
Returns:
signal_headers : list of dict

returns n signal headers as a list to save several signal headers.
pyedflib.highlevel.make_signal_header(label, dimension='uV', sample_rate=256, sample_frequency=None, physical_min=-200, physical_max=200, digital_min=-32768, digital_max=32767, transducer='', prefiler='')[source]

A convenience function that creates a signal header for a given signal. This can be used to create a list of signal headers that is used by pyedflib to create an edf. With this, different sampling frequencies can be indicated.

Parameters:
label : str

the name of the channel.

dimension : str, optional

dimension, eg mV. The default is ‘uV’.

sample_rate : int, optional

sampling frequency. The default is 256. Deprecated: use ‘sample_frequency’ instead.

sample_frequency : int, optional

sampling frequency. The default is 256.

physical_min : float, optional

minimum value in dimension. The default is -200.

physical_max : float, optional

maximum value in dimension. The default is 200.

digital_min : int, optional

digital minimum of the ADC. The default is -32768.

digital_max : int, optional

digital maximum of the ADC. The default is 32767.

transducer : str, optional

electrode type that was used. The default is ‘’.

prefiler : str, optional

filtering and sampling method. The default is ‘’.
Returns:
signal_header : dict

a signal header that can be used to save a channel to an EDF.
pyedflib.highlevel.make_header(technician='', recording_additional='', patientname='', patient_additional='', patientcode='', equipment='', admincode='', gender='', startdate=None, birthdate='')[source]

A convenience function to create an EDF header (a dictionary) that can be used by pyedflib to update the main header of the EDF

Parameters:
technician : str, optional

name of the technician. The default is ‘’.

recording_additional : str, optional

comments etc. The default is ‘’.

patientname : str, optional

the name of the patient. The default is ‘’.

patient_additional : TYPE, optional

more info about the patient. The default is ‘’.

patientcode : str, optional

alphanumeric code. The default is ‘’.

equipment : str, optional

which system was used. The default is ‘’.

admincode : str, optional

code of the admin. The default is ‘’.

gender : str, optional

gender of patient. The default is ‘’.

startdate : datetime.datetime, optional

startdate of recording. The default is None.

birthdate : str/datetime.datetime, optional

date of birth of the patient. The default is ‘’.
Returns:
header : dict

a dictionary with the values given filled in.
pyedflib.highlevel.phys2dig(signal, dmin, dmax, pmin, pmax)[source]

converts physical values to digital values

Parameters:
signal : np.ndarray or int

A numpy array with int values (digital values) or an int.

dmin : int

digital minimum value of the edf file (eg -2048).

dmax : int

digital maximum value of the edf file (eg 2048).

pmin : float

physical maximum value of the edf file (eg -200.0).

pmax : float

physical maximum value of the edf file (eg 200.0).
Returns:
digital : np.ndarray or int

converted digital values
pyedflib.highlevel.dig2phys(signal, dmin, dmax, pmin, pmax)[source]

converts digital edf values to physical values

Parameters:
signal : np.ndarray or int

A numpy array with int values (digital values) or an int.

dmin : int

digital minimum value of the edf file (eg -2048).

dmax : int

digital maximum value of the edf file (eg 2048).

pmin : float

physical maximum value of the edf file (eg -200.0).

pmax : float

physical maximum value of the edf file (eg 200.0).
Returns:
physical : np.ndarray or float

converted physical values

Development notes

This section contains information on building and installing PyEDFlib from source code as well as instructions for preparing the build environment on Windows and Linux.

Preparing Windows build environment

To start developing pyedflib code on Windows you will have to install a C compiler and prepare the build environment.

Installing Microsoft Visual C++ Compiler for Python 2.7

Downloading Microsoft Visual C++ Compiler for Python 2.7 from https://www.microsoft.com/en-us/download/details.aspx?id=44266.

After installing the Compiler and before compiling the extension you have to configure some environment variables.

For build execute the util/setenv_win.bat script in the cmd window:

rem Configure the environment for builds.
rem Convince setup.py to use the SDK tools.
set MSSdk=1
set DISTUTILS_USE_SDK=1
Next steps

After completing these steps continue with Installing build dependencies.

Preparing Linux build environment

There is a good chance that you already have a working build environment. Just skip steps that you don’t need to execute.

Installing basic build tools

Note that the example below uses aptitude package manager, which is specific to Debian and Ubuntu Linux distributions. Use your favourite package manager to install these packages on your OS.

aptitude install build-essential gcc python-dev git-core
Next steps

After completing these steps continue with Installing build dependencies.

Installing build dependencies

Setting up Python virtual environment

A good practice is to create a separate Python virtual environment for each project. If you don’t have virtualenv yet, install and activate it using:

curl -O https://raw.github.com/pypa/virtualenv/master/virtualenv.py
python virtualenv.py <name_of_the_venv>
. <name_of_the_venv>/bin/activate
Installing Cython

Use pip (http://pypi.python.org/pypi/pip) to install Cython:

pip install Cython>=0.16
Installing numpy

Use pip to install numpy:

pip install numpy

Numpy can also be obtained via scientific python distributions such as:

Note

You can find binaries for 64-bit Windows on http://www.lfd.uci.edu/~gohlke/pythonlibs/.

Installing Sphinx

Sphinx is a documentation tool that converts reStructuredText files into nicely looking html documentation. Install it with:

pip install Sphinx

numpydoc is used to format the API docmentation appropriately. Install it via:

pip install numpydoc

Building and installing PyEDFlib

Installing from source code

Go to https://github.com/holgern/pyedflib GitHub project page, fork and clone the repository or use the upstream repository to get the source code:

git clone https://github.com/holgern/pyedflib.git pyedflib

Activate your Python virtual environment, go to the cloned source directory and type the following commands to build and install the package:

python setup.py build
python setup.py install

To verify the installation run the following command:

python setup.py test

To build docs:

cd doc
make html
Installing from source code in Windows

Go to https://github.com/holgern/pyedflib GitHub project page, fork and clone the repository or use the upstream repository to get the source code:

git clone https://github.com/holgern/pyedflib.git pyedflib

Install Microsoft Visual C++ Compiler for Python 2.7 from https://www.microsoft.com/en-us/download/details.aspx?id=44266

Activate your Python virtual environment, go to the cloned source directory and type the following commands to build and install the package:

    util\setenv_win.bat
python setup.py build_ext --inplace
python setup.py install --user

To verify the installation run the following command:

python runtests.py

To build docs:

cd doc
make html
Installing a development version

You can also install directly from the source repository:

pip install -e git+https://github.com/holgern/pyedflib.git#egg=pyedflib

or:

pip install pyedflib==dev
Installing a regular release from PyPi

A regular release can be installed with pip or easy_install:

pip install pyedflib

Testing

We are currently using AppVeyor and CircleCI for continuous integration.

If you are submitting a patch or pull request please make sure it does not break the build.

Running tests locally

Tests are implemented with nose, so use one of:

$ nosetests pyedflib

>>> pyedflib.test()  # doctest: +SKIP

Note doctests require Matplotlib in addition to the usual dependencies.

Guidelines for new releases for pyedflib

vX.X.X refers to the release number

Tag the release and trigger bulding of wheels in appvoyer

Change ISRELEASED in setup.py to True and commit.

Appveyor will now build wheels for windows.

Tag the relase with

`git tag -s vX.X.X`

and push the tag to master.

Clean up source

Remove untraced files with git clean

First check which files will be deleted:

`git clean -xfdn`

Then run without -n:

`git clean -xfd`

Create the source distribution files with:

`python setup.py sdist --formats=gztar,zip`

Upload the release and windows wheels to pypi

Download all wheels from Appveyor and put them into the dist directory

Register all files with

`twine register dist\filename_which_should_uploaded.whl`

and upload with

`twine upload  dist\filename_which_should_uploaded.whl`

Prepare for continued development

Increment the version number in setup.py and change ISRELEASED to False.

Something not working?

If these instructions are not clear or you need help setting up your development environment, go ahead and open a ticket on GitHub.

Resources

Code

The GitHub repository is now the main code repository.

If you are using the Mercurial repository at Bitbucket, please switch to Git/GitHub and follow for development updates.

Questions and bug reports

Use GitHub Issues to post questions and open tickets.

PyEDFlib

Release Notes

PyEDFlib 0.1.6 Release Notes
  • Faster writing of BDF/EDF files
  • bug fixes
Authors
  • Holger Nahrstaedt
Issues closed for v0.1.6
  • #5: edf writer code executing really slow
PyEDFlib 0.1.7 Release Notes
  • Fix Crash on 64 Bit
  • Fix strings on python 3
  • Fix edf handle
  • Fix getSignalHeaders
Authors
  • Matthias Klumpp +
  • Holger Nahrstaedt
  • Jukka Zitting +

A total of 3 people contributed to this release. People with a “+” by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

Issues closed for v0.1.7
  • #7: Handling of wrong paths
  • #8: Wrong and misleading docstring for setDatarecordDuration
  • #9: How to close an already opened file?
  • #10: Incorrect results from calling read_digital_signal when opening more than one file
Pull requests for v0.1.7
  • #12: Fix getSignalHeaders
  • #13: Don’t crash when writing files on 64bit machines
PyEDFlib 0.1.8 Release Notes
  • Fix proper reading of EDF/BDF files
  • Fix writing of EDF/BDF files
Authors
  • Holger Nahrstaedt
Issues closed for v0.1.8
  • #11: IOError: malloc error
  • #14:CHB-MIT (Physionet) error - regular EDF not supported anymore
PyEDFlib 0.1.9 Release Notes
  • Fix proper reading of EDF/BDF files
  • Bug fixes
  • Improved error messages
Authors
  • Zaccharie Ramzi +
  • Holger Nahrstaedt
Issues closed for v0.1.9
  • #16:Double rounding when writing to file leads to accumulating errors
  • #17:Error with chb17b_69 in CHB-MIT (Physionet) Database
Pull requests for v0.1.9
  • #15: Essentially corrected a typo in readme
PyEDFlib 0.1.10 Release Notes
  • Add function for access subset of data
  • Improved error messages
Authors
  • Holger Nahrstaedt
Issues closed for v0.1.10
  • #19 : IOError: the file is not EDF(+) or BDF(+) compliant (Label)
  • #20 : access subset of data
PyEDFlib 0.1.11 Release Notes
  • Bug fixes
Authors
  • Holger Nahrstaedt
  • Steffen Heimes +

A total of 2 people contributed to this release. People with a “+” by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

Issues closed for v0.1.11
  • #21 : Cannot open file containing accented character on Windows
Pull requests for v0.1.11
  • #23: Fixed Typo edfreader and improve edfwriter
PyEDFlib 0.1.12 Release Notes
  • small bug fixes
Authors
  • Holger Nahrstaedt
Issues closed for v0.1.12
  • #24 : Issues reading EDF’s
  • #25 : file_info_long() method is broken.
PyEDFlib 0.1.15 Release Notes
  • Fix Documentation (Add class functions)
  • Add build for python 3.7
  • add close() on EdfReader
Authors
  • Holger Nahrstaedt
  • skjerns
Issues closed for v0.1.15
  • Fix issue #48 - DOC
  • Fix issue #60 - No Windows binaries for python 3.7 on PyPI
  • Fix issue #62 - Install via pip fails on Windows (no file stdio.h)
  • Fix issue #42 - Problem with setGender
  • Fix issue #43 - Writer as context manager
Pull requests for v0.1.15
  • PR #49 - Added option to get digital samples
PyEDFlib 0.1.16 Release Notes
  • Add high-level functions
Authors
  • Holger Nahrstaedt
  • skjerns
Issues closed for v0.1.16
  • Fix issue #64 - request to provide a sample script to de-identify edf
Pull requests for v0.1.16
  • PR #69 - Fix docstring of method setDigitalMaximum
  • PR #66 - Add support for PEP 517 & 518
  • PR #65 - Added high-level functions
PyEDFlib 0.1.17 Release Notes
  • Fix readme
  • Fix docs
  • Add python 3.8 to CI
Authors
  • Holger Nahrstaedt
PyEDFlib 0.1.19 Release Notes
Authors
  • Holger Nahrstaedt
  • skjerns
  • LucaCerina
Issues closed for v0.1.19
  • Fix issue #87 - Gender and patient name can’t be properly anonymized
Pull requests for v0.1.19
  • PR #85 - Add subsecond precision
  • PR #89 - Assert that physical_min is different from physical_max
  • PR #90 - Add support for gender removal
PyEDFlib 0.1.19 Release Notes
Authors
  • Holger Nahrstaedt
  • skjerns
  • LucaCerina
Issues closed for v0.1.19
  • Fix issue #87 - Gender and patient name can’t be properly anonymized
Pull requests for v0.1.19
  • PR #85 - Add subsecond precision
  • PR #89 - Assert that physical_min is different from physical_max
  • PR #90 - Add support for gender removal
PyEDFlib 0.1.20 Release Notes
Authors
  • Holger Nahrstaedt
  • skjerns
Issues closed for v0.1.20
  • Fix issue #91 - Fix date given as string (backwards compatible)
Pull requests for v0.1.20
  • PR #93 - Automatically set blocksize // speed up writing
PyEDFlib 0.1.21 Release Notes
  • Include unit tests into python package
  • Add manylinux builds
  • Fix unit test für ARM
Authors
  • Holger Nahrstaedt
  • skjerns
Issues closed for v0.1.21
  • Fix issue #99 - The pyedflib File Package does not support Chinese path
  • Fix issue #105 - Take hours/days to write signals into edf file using highlevel.write_edf?
  • Fix issue #109 - highlevel.read_edf fails with ValueError
Pull requests for v0.1.21
  • PR #100 - adding unicode read/write tests + workaround windows unicode files
  • PR #103 - Verbose options default to False
  • PR #106 - add warnings for header length
  • PR #107 - Prevent fortran layout
  • PR #109 - Round sample rates up to 3 decimals not to int
  • PR #116 - fixed wrong variable use in rename_channel function
PyEDFlib 0.1.23 Release Notes
  • Use cibuildwheel for wheel building
Authors
  • Holger Nahrstaedt
  • skjerns
  • LucaCerina
  • wmvanvliet
  • cfranklin11
  • BlakeJC94
Issues closed for v0.1.23
  • #145 Typo in write_edf documentation
  • #142 set_physical_minimum return value is missing
  • #133 Trigger UTF8-filename warning only if it’s really the case
  • #132 Add warning if header is too long or contains unrecognized header fields
Pull requests for v0.1.23
  • #124 updated edfWriter:setSignalHeaders to update default dicts instead of overwriting
  • #126 Fix annotation bytestring
  • #127 Cleanup travis buildscript
  • #125 non-empty data check in edfwriter to prevent unknown OS error
  • #121 Fix sample frequencies for record duration != 1
  • #134 add warnings if dmin/dmax/pmin/pmax is out of bounds
  • #135 split up Errors in FileNotFoundError and OSError
  • #136 suppress warnings in tests
  • #114 Be less strict about prefilter fields
  • #137 improved speedup write with F-contiguous arrays

Indices and tables