wfdb

These core components are accessible by importing the wfdb package directly, as well as from their respective subpackages.

WFDB Records

wfdb.rdrecord(record_name, sampfrom=0, sampto='end', channels='all', physical=True, pb_dir=None, m2s=True, smooth_frames=True, ignore_skew=False, return_res=64, force_channels=True)

Read a WFDB record and return the signal and record descriptors as attributes in a Record or MultiRecord object.

record_name : str
The name of the WFDB record to be read (without any file extensions). If the argument contains any path delimiter characters, the argument will be interpreted as PATH/baserecord and the data files will be searched for in the local path.
sampfrom : int, optional
The starting sample number to read for all channels.
sampto : int, or ‘end’, optional
The sample number at which to stop reading for all channels. Leave as ‘end’ to read the entire duration.
channels : list, or ‘all’, optional
List of integer indices specifying the channels to be read. Leave as ‘all’ to read all channels.
physical : bool, optional
Specifies whether to return signals in physical units in the p_signal field (True), or digital units in the d_signal field (False).
pb_dir : str, optional
Option used to stream data from Physiobank. The Physiobank database directory from which to find the required record files. eg. For record ‘100’ in ‘http://physionet.org/physiobank/database/mitdb’ pb_dir=’mitdb’.
m2s : bool, optional
Used when reading multi-segment records. Specifies whether to directly return a wfdb MultiRecord object (False), or to convert it into and return a wfdb Record object (True).
smooth_frames : bool, optional
Used when reading records with signals having multiple samples per frame. Specifies whether to smooth the samples in signals with more than one sample per frame and return an (MxN) uniform numpy array as the d_signal or p_signal field (True), or to return a list of 1d numpy arrays containing every expanded sample as the e_d_signal or e_p_signal field (False).
ignore_skew : bool, optional
Used when reading records with at least one skewed signal. Specifies whether to apply the skew to align the signals in the output variable (False), or to ignore the skew field and load in all values contained in the dat files unaligned (True).
return_res : int, optional
The numpy array dtype of the returned signals. Options are: 64, 32, 16, and 8, where the value represents the numpy int or float dtype. Note that the value cannot be 8 when physical is True since there is no float8 format.
force_channels : bool, optional
Used when reading multi-segment variable layout records. Whether to update the layout specification record, and the converted Record object if m2s is True, to match the input channels argument, or to omit channels in which no read segment contains the signals.
record : Record or MultiRecord
The wfdb Record or MultiRecord object representing the contents of the record read.

If a signal range or channel selection is specified when calling this function, the resulting attributes of the returned object will be set to reflect the section of the record that is actually read, rather than necessarily the entire record. For example, if channels=[0, 1, 2] is specified when reading a 12 channel record, the ‘n_sig’ attribute will be 3, not 12.

The rdsamp function exists as a simple alternative to rdrecord for the common purpose of extracting the physical signals and a few important descriptor fields.

>>> record = wfdb.rdrecord('sample-data/test01_00s', sampfrom=800,
                           channels=[1,3])
wfdb.rdsamp(record_name, sampfrom=0, sampto='end', channels='all', pb_dir=None)

Read a WFDB record, and return the physical signals and a few important descriptor fields.

record_name : str
The name of the WFDB record to be read (without any file extensions). If the argument contains any path delimiter characters, the argument will be interpreted as PATH/baserecord and the data files will be searched for in the local path.
sampfrom : int, optional
The starting sample number to read for all channels.
sampto : int, or ‘end’, optional
The sample number at which to stop reading for all channels. Leave as ‘end’ to read the entire duration.
channels : list, or ‘all’, optional
List of integer indices specifying the channels to be read. Leave as ‘all’ to read all channels.
pb_dir : str, optional
Option used to stream data from Physiobank. The Physiobank database directory from which to find the required record files. eg. For record ‘100’ in ‘http://physionet.org/physiobank/database/mitdb’ pb_dir=’mitdb’.
signals : numpy array
A 2d numpy array storing the physical signals from the record.
fields : dict

A dictionary containing several key attributes of the read record:

  • fs: The sampling frequency of the record
  • units: The units for each channel
  • sig_name: The signal name for each channel
  • comments: Any comments written in the header

If a signal range or channel selection is specified when calling this function, the resulting attributes of the returned object will be set to reflect the section of the record that is actually read, rather than necessarily the entire record. For example, if channels=[0, 1, 2] is specified when reading a 12 channel record, the ‘n_sig’ attribute will be 3, not 12.

The rdrecord function is the base function upon which this one is built. It returns all attributes present, along with the signals, as attributes in a Record object. The function, along with the returned data type, has more options than rdsamp for users who wish to more directly manipulate WFDB content.

>>> signals, fields = wfdb.rdsamp('sample-data/test01_00s',
                                  sampfrom=800,
                                  channel =[1,3])
wfdb.wrsamp(record_name, fs, units, sig_name, p_signal=None, d_signal=None, fmt=None, adc_gain=None, baseline=None, comments=None, base_time=None, base_date=None, write_dir='')

Write a single segment WFDB record, creating a WFDB header file and any associated dat files.

record_name : str
The string name of the WFDB record to be written (without any file extensions).
fs : int, or float
The sampling frequency of the record.
units : list
A list of strings giving the units of each signal channel.
sig_name :
A list of strings giving the signal name of each signal channel.
p_signal : numpy array, optional
An (MxN) 2d numpy array, where M is the signal length. Gives the physical signal values intended to be written. Either p_signal or d_signal must be set, but not both. If p_signal is set, this method will use it to perform analogue-digital conversion, writing the resultant digital values to the dat file(s). If fmt is set, gain and baseline must be set or unset together. If fmt is unset, gain and baseline must both be unset.
d_signal : numpy array, optional
An (MxN) 2d numpy array, where M is the signal length. Gives the digital signal values intended to be directly written to the dat file(s). The dtype must be an integer type. Either p_signal or d_signal must be set, but not both. In addition, if d_signal is set, fmt, gain and baseline must also all be set.
fmt : list, optional
A list of strings giving the WFDB format of each file used to store each channel. Accepted formats are: ‘80’,‘212”,‘16’,‘24’, and ‘32’. There are other WFDB formats as specified by: https://www.physionet.org/physiotools/wag/signal-5.htm but this library will not write (though it will read) those file types.
adc_gain : list, optional
A list of numbers specifying the ADC gain.
baseline : list, optional
A list of integers specifying the digital baseline.
comments : list, optional
A list of string comments to be written to the header file.
base_time : str, optional
A string of the record’s start time in 24h ‘HH:MM:SS(.ms)’ format.
base_date : str, optional
A string of the record’s start date in ‘DD/MM/YYYY’ format.
write_dir : str, optional
The directory in which to write the files.

This is a gateway function, written as a simple method to write WFDB record files using the most common parameters. Therefore not all WFDB fields can be set via this function.

For more control over attributes, create a Record object, manually set its attributes, and call its wrsamp instance method. If you choose this more advanced method, see also the set_defaults, set_d_features, and set_p_features instance methods to help populate attributes.

>>> # Read part of a record from Physiobank
>>> signals, fields = wfdb.rdsamp('a103l', sampfrom=50000, channels=[0,1],
                               pb_dir='challenge/2015/training')
>>> # Write a local WFDB record (manually inserting fields)
>>> wfdb.wrsamp('ecgrecord', fs = 250, units=['mV', 'mV'],
                sig_name=['I', 'II'], p_signal=signals, fmt=['16', '16'])
class wfdb.Record(p_signal=None, d_signal=None, e_p_signal=None, e_d_signal=None, record_name=None, n_sig=None, fs=None, counter_freq=None, base_counter=None, sig_len=None, base_time=None, base_date=None, file_name=None, fmt=None, samps_per_frame=None, skew=None, byte_offset=None, adc_gain=None, baseline=None, units=None, adc_res=None, adc_zero=None, init_value=None, checksum=None, block_size=None, sig_name=None, comments=None)

The class representing single segment WFDB records.

Record objects can be created using the initializer, by reading a WFDB header with rdheader, or a WFDB record (header and associated dat files) with rdrecord.

The attributes of the Record object give information about the record as specified by: https://www.physionet.org/physiotools/wag/header-5.htm

In addition, the d_signal and p_signal attributes store the digital and physical signals of WFDB records with at least one channel.

>>> record = wfdb.Record(record_name='r1', fs=250, n_sig=2, sig_len=1000,
                     file_name=['r1.dat','r1.dat'])
adc(expanded=False, inplace=False)

Performs analogue to digital conversion of the physical signal stored in p_signal if expanded is False, or e_p_signal if expanded is True.

The p_signal/e_p_signal, fmt, gain, and baseline fields must all be valid.

If inplace is True, the adc will be performed inplace on the variable, the d_signal/e_d_signal attribute will be set, and the p_signal/e_p_signal field will be set to None.

expanded : bool, optional
Whether to transform the e_p_signal attribute (True) or the p_signal attribute (False).
inplace : bool, optional
Whether to automatically set the object’s corresponding digital signal attribute and set the physical signal attribute to None (True), or to return the converted signal as a separate variable without changing the original physical signal attribute (False).
d_signal : numpy array, optional
The digital conversion of the signal. Either a 2d numpy array or a list of 1d numpy arrays.
>>> import wfdb
>>> record = wfdb.rdsamp('sample-data/100')
>>> d_signal = record.adc()
>>> record.adc(inplace=True)
>>> record.dac(inplace=True)
dac(expanded=False, return_res=64, inplace=False)

Performs the digital to analogue conversion of the signal stored in d_signal if expanded is False, or e_d_signal if expanded is True.

The d_signal/e_d_signal, fmt, gain, and baseline fields must all be valid.

If inplace is True, the dac will be performed inplace on the variable, the p_signal/e_p_signal attribute will be set, and the d_signal/e_d_signal field will be set to None.

expanded : bool, optional
Whether to transform the e_d_signal attribute (True) or the d_signal attribute (False).
inplace : bool, optional
Whether to automatically set the object’s corresponding physical signal attribute and set the digital signal attribute to None (True), or to return the converted signal as a separate variable without changing the original digital signal attribute (False).
p_signal : numpy array, optional
The physical conversion of the signal. Either a 2d numpy array or a list of 1d numpy arrays.
>>> import wfdb
>>> record = wfdb.rdsamp('sample-data/100', physical=False)
>>> p_signal = record.dac()
>>> record.dac(inplace=True)
>>> record.adc(inplace=True)
wrsamp(expanded=False, write_dir='')

Write a wfdb header file and any associated dat files from this object.

expanded : bool, optional
Whether to write the expanded signal (e_d_signal) instead of the uniform signal (d_signal).
write_dir : str, optional
The directory in which to write the files.
class wfdb.MultiRecord(segments=None, layout=None, record_name=None, n_sig=None, fs=None, counter_freq=None, base_counter=None, sig_len=None, base_time=None, base_date=None, seg_name=None, seg_len=None, comments=None, sig_name=None, sig_segments=None)

The class representing multi-segment WFDB records.

MultiRecord objects can be created using the initializer, or by reading a multi-segment WFDB record using ‘rdrecord’ with the m2s (multi to single) input parameter set to False.

The attributes of the MultiRecord object give information about the entire record as specified by: https://www.physionet.org/physiotools/wag/header-5.htm

In addition, the segments parameter is a list of Record objects representing each individual segment, or None representing empty segments, of the entire multi-segment record.

Notably, this class has no attribute representing the signals as a whole. The ‘multi_to_single’ instance method can be called on MultiRecord objects to return a single segment representation of the record as a Record object. The resulting Record object will have its ‘p_signal’ field set.

>>> record_m = wfdb.MultiRecord(record_name='rm', fs=50, n_sig=8,
                                sig_len=9999, seg_name=['rm_1', '~', rm_2'],
                                seg_len=[800, 200, 900])
>>> # Get a MultiRecord object
>>> record_s = wfdb.rdsamp('s00001-2896-10-10-00-31', m2s=False)
>>> # Turn it into a
>>> record_s = record_s.multi_to_single()

record_s initially stores a MultiRecord object, and is then converted into a Record object.

multi_to_single(physical, return_res=64)

Create a Record object from the MultiRecord object. All signal segments will be combined into the new object’s p_signal or d_signal field. For digital format, the signals must have the same storage format, baseline, and adc_gain in all segments.

physical : bool
Whether to convert the physical or digital signal.
return_res : int, optional
The return resolution of the p_signal field. Options are: 64, 32, and 16.
record : wfdb Record
The single segment record created.

WFDB Anotations

wfdb.rdann(record_name, extension, sampfrom=0, sampto=None, shift_samps=False, pb_dir=None, return_label_elements=['symbol'], summarize_labels=False)

Read a WFDB annotation file record_name.extension and return an Annotation object.

record_name : str
The record name of the WFDB annotation file. ie. for file ‘100.atr’, record_name=‘100’.
extension : str
The annotatator extension of the annotation file. ie. for file ‘100.atr’, extension=’atr’.
sampfrom : int, optional
The minimum sample number for annotations to be returned.
sampto : int, optional
The maximum sample number for annotations to be returned.
shift_samps : bool, optional
Specifies whether to return the sample indices relative to sampfrom (True), or sample 0 (False).
pb_dir : str, optional
Option used to stream data from Physiobank. The Physiobank database directory from which to find the required annotation file. eg. For record ‘100’ in ‘http://physionet.org/physiobank/database/mitdb’: pb_dir=’mitdb’.
return_label_elements : list, optional
The label elements that are to be returned from reading the annotation file. A list with at least one of the following options: ‘symbol’, ‘label_store’, ‘description’.
summarize_labels : bool, optional
If True, assign a summary table of the set of annotation labels contained in the file to the ‘contained_labels’ attribute of the returned object. This table will contain the columns: [‘label_store’, ‘symbol’, ‘description’, ‘n_occurences’]
annotation : Annotation
The Annotation object. Call help(wfdb.Annotation) for the attribute descriptions.

For every annotation sample, the annotation file explictly stores the ‘sample’ and ‘symbol’ fields, but not necessarily the others. When reading annotation files using this function, fields which are not stored in the file will either take their default values of 0 or None, or will be carried over from their previous values if any.

>>> ann = wfdb.rdann('sample-data/100', 'atr', sampto=300000)
wfdb.wrann(record_name, extension, sample, symbol=None, subtype=None, chan=None, num=None, aux_note=None, label_store=None, fs=None, custom_labels=None, write_dir='')

Write a WFDB annotation file.

Specify at least the following:

  • The record name of the WFDB record (record_name)
  • The annotation file extension (extension)
  • The annotation locations in samples relative to the beginning of the record (sample)
  • Either the numerical values used to store the labels (label_store), or more commonly, the display symbols of each label (symbol).
record_name : str
The string name of the WFDB record to be written (without any file extensions).
extension : str
The string annotation file extension.
sample : numpy array
A numpy array containing the annotation locations in samples relative to the beginning of the record.
symbol : list, or numpy array, optional
The symbols used to display the annotation labels. List or numpy array. If this field is present, label_store must not be present.
subtype : numpy array, optional
A numpy array containing the marked class/category of each annotation.
chan : numpy array, optional
A numpy array containing the signal channel associated with each annotation.
num : numpy array, optional
A numpy array containing the labelled annotation number for each annotation.
aux_note : list, optional
A list containing the auxiliary information string (or None for annotations without notes) for each annotation.
label_store : numpy array, optional
A numpy array containing the integer values used to store the annotation labels. If this field is present, symbol must not be present.
fs : int, or float, optional
The numerical sampling frequency of the record to be written to the file.
custom_labels : pandas dataframe, optional

The map of custom defined annotation labels used for this annotation, in addition to the standard WFDB annotation labels. Custom labels are defined by two or three fields:

  • The integer values used to store custom annotation labels in the file (optional)
  • Their short display symbols
  • Their long descriptions.

This input argument may come in four formats:

  1. A pandas.DataFrame object with columns: [‘label_store’, ‘symbol’, ‘description’]
  2. A pandas.DataFrame object with columns: [‘symbol’, ‘description’] If this option is chosen, label_store values are automatically chosen.
  3. A list or tuple of tuple triplets, with triplet elements representing: (label_store, symbol, description).
  4. A list or tuple of tuple pairs, with pair elements representing: (symbol, description). If this option is chosen, label_store values are automatically chosen.

If the label_store field is given for this function, and custom_labels is defined, custom_labels must contain label_store in its mapping. ie. it must come in format 1 or 3 above.

write_dir : str, optional
The directory in which to write the annotation file

This is a gateway function, written as a simple way to write WFDB annotation files without needing to explicity create an Annotation object. You may also create an Annotation object, manually set its attributes, and call its wrann instance method.

Each annotation stored in a WFDB annotation file contains a sample field and a label field. All other fields may or may not be present.

>>> # Read an annotation as an Annotation object
>>> annotation = wfdb.rdann('b001', 'atr', pb_dir='cebsdb')
>>> # Write a copy of the annotation file
>>> wfdb.wrann('b001', 'cpy', annotation.sample, annotation.symbol)
wfdb.show_ann_labels()

Display the standard wfdb annotation label mapping.

>>> show_ann_labels()
wfdb.show_ann_classes()

Display the standard wfdb annotation classes

>>> show_ann_classes()
class wfdb.Annotation(record_name, extension, sample, symbol=None, subtype=None, chan=None, num=None, aux_note=None, fs=None, label_store=None, description=None, custom_labels=None, contained_labels=None)

The class representing WFDB annotations.

Annotation objects can be created using the initializer, or by reading a WFDB annotation file with rdann.

The attributes of the Annotation object give information about the annotation as specified by: https://www.physionet.org/physiotools/wag/annot-5.htm

Call show_ann_labels() to see the list of standard annotation codes. Any text used to label annotations that are not one of these codes should go in the ‘aux_note’ field rather than the ‘sym’ field.

>>> ann1 = wfdb.Annotation(record_name='rec1', extension='atr',
                           sample=[10,20,400], symbol=['N','N','['],
                           aux_note=[None, None, 'Serious Vfib'])
wrann(write_fs=False, write_dir='')

Write a WFDB annotation file from this object.

write_fs : bool, optional
Whether to write the fs attribute to the file.

Downloading

wfdb.get_dbs()

Get a list of all the Physiobank databases available.

>>> dbs = get_dbs()
wfdb.get_record_list(db_dir, records='all')

Get a list of records belonging to a database.

db_dir : str
The database directory, usually the same as the database slug. The location to look for a RECORDS file.
records : list, optional
A Option used when this function acts as a helper function. Leave as default ‘all’ to get all records.
>>> wfdb.get_record_list('mitdb')
wfdb.dl_database(db_dir, dl_dir, records='all', annotators='all', keep_subdirs=True, overwrite=False)

Download WFDB record (and optionally annotation) files from a Physiobank database. The database must contain a ‘RECORDS’ file in its base directory which lists its WFDB records.

db_dir : str
The Physiobank database directory to download. eg. For database: ‘http://physionet.org/physiobank/database/mitdb’, db_dir=’mitdb’.
dl_dir : str
The full local directory path in which to download the files.
records : list, or ‘all’, optional
A list of strings specifying the WFDB records to download. Leave as ‘all’ to download all records listed in the database’s RECORDS file. eg. records=[‘test01_00s’, test02_45s] for database: https://physionet.org/physiobank/database/macecgdb/
annotators : list, ‘all’, or None, optional
A list of strings specifying the WFDB annotation file types to download along with the record files. Is either None to skip downloading any annotations, ‘all’ to download all annotation types as specified by the ANNOTATORS file, or a list of strings which each specify an annotation extension. eg. annotators = [‘anI’] for database: https://physionet.org/physiobank/database/prcp/
keep_subdirs : bool, optional
Whether to keep the relative subdirectories of downloaded files as they are organized in Physiobank (True), or to download all files into the same base directory (False).
overwrite : bool, optional
If True, all files will be redownloaded regardless. If False, existing files with the same name and relative subdirectory will be checked. If the local file is the same size as the online file, the download is skipped. If the local file is larger, it will be deleted and the file will be redownloaded. If the local file is smaller, the file will be assumed to be partially downloaded and the remaining bytes will be downloaded and appended.
>>> wfdb.dl_database('ahadb', os.getcwd())
wfdb.dl_files(db, dl_dir, files, keep_subdirs=True, overwrite=False)

Download specified files from a Physiobank database.

db : str
The Physiobank database directory to download. eg. For database: ‘http://physionet.org/physiobank/database/mitdb’, db=’mitdb’.
dl_dir : str
The full local directory path in which to download the files.
files : list
A list of strings specifying the file names to download relative to the database base directory.
keep_subdirs : bool, optional
Whether to keep the relative subdirectories of downloaded files as they are organized in Physiobank (True), or to download all files into the same base directory (False).
overwrite : bool, optional
If True, all files will be redownloaded regardless. If False, existing files with the same name and relative subdirectory will be checked. If the local file is the same size as the online file, the download is skipped. If the local file is larger, it will be deleted and the file will be redownloaded. If the local file is smaller, the file will be assumed to be partially downloaded and the remaining bytes will be downloaded and appended.
>>> wfdb.dl_files('ahadb', os.getcwd(),
                  ['STAFF-Studies-bibliography-2016.pdf', 'data/001a.hea',
                  'data/001a.dat'])

Plotting

wfdb.plot_items(signal=None, ann_samp=None, ann_sym=None, fs=None, time_units='samples', sig_name=None, sig_units=None, ylabel=None, title=None, sig_style=[''], ann_style=['r*'], ecg_grids=[], figsize=None, return_fig=False)

Subplot individual channels of signals and/or annotations.

signal : 1d or 2d numpy array, optional
The uniformly sampled signal to be plotted. If signal.ndim is 1, it is assumed to be a one channel signal. If it is 2, axes 0 and 1, must represent time and channel number respectively.
ann_samp: list, optional

A list of annotation locations to plot, with each list item corresponding to a different channel. List items may be:

  • 1d numpy array, with values representing sample indices. Empty arrays are skipped.
  • list, with values representing sample indices. Empty lists are skipped.
  • None. For channels in which nothing is to be plotted.

If signal is defined, the annotation locations will be overlaid on the signals, with the list index corresponding to the signal channel. The length of annotation does not have to match the number of channels of signal.

ann_sym: list, optional
A list of annotation symbols to plot, with each list item corresponding to a different channel. List items should be lists of strings. The symbols are plotted over the corresponding ann_samp index locations.
fs : int or float, optional
The sampling frequency of the signals and/or annotations. Used to calculate time intervals if time_units is not ‘samples’. Also required for plotting ecg grids.
time_units : str, optional
The x axis unit. Allowed options are: ‘samples’, ‘seconds’, ‘minutes’, and ‘hours’.
sig_name : list, optional
A list of strings specifying the signal names. Used with sig_units to form y labels, if ylabel is not set.
sig_units : list, optional
A list of strings specifying the units of each signal channel. Used with sig_name to form y labels, if ylabel is not set. This parameter is required for plotting ecg grids.
ylabel : list, optional
A list of strings specifying the final y labels. If this option is present, sig_name and sig_units will not be used for labels.
title : str, optional
The title of the graph.
sig_style : list, optional
A list of strings, specifying the style of the matplotlib plot for each signal channel. The list length should match the number of signal channels. If the list has a length of 1, the style will be used for all channels.
ann_style : list, optional
A list of strings, specifying the style of the matplotlib plot for each annotation channel. If the list has a length of 1, the style will be used for all channels.
ecg_grids : list, optional
A list of integers specifying channels in which to plot ecg grids. May also be set to ‘all’ for all channels. Major grids at 0.5mV, and minor grids at 0.125mV. All channels to be plotted with grids must have sig_units equal to ‘uV’, ‘mV’, or ‘V’.
figsize : tuple, optional
Tuple pair specifying the width, and height of the figure. It is the ‘figsize’ argument passed into matplotlib.pyplot’s figure function.
return_fig : bool, optional
Whether the figure is to be returned as an output argument.
figure : matplotlib figure, optional
The matplotlib figure generated. Only returned if the ‘return_fig’ parameter is set to True.
>>> record = wfdb.rdrecord('sample-data/100', sampto=3000)
>>> ann = wfdb.rdann('sample-data/100', 'atr', sampto=3000)
>>> wfdb.plot_items(signal=record.p_signal,
                    annotation=[ann.sample, ann.sample],
                    title='MIT-BIH Record 100', time_units='seconds',
                    figsize=(10,4), ecg_grids='all')
wfdb.plot_wfdb(record=None, annotation=None, plot_sym=False, time_units='samples', title=None, sig_style=[''], ann_style=['r*'], ecg_grids=[], figsize=None, return_fig=False)

Subplot individual channels of a wfdb record and/or annotation.

This function implements the base functionality of the plot_items function, while allowing direct input of wfdb objects.

If the record object is input, the function will extract from it:
  • signal values, from the p_signal (priority) or d_signal attribute
  • sampling frequency, from the fs attribute
  • signal names, from the sig_name attribute
  • signal units, from the units attribute
If the annotation object is input, the function will extract from it:
  • sample locations, from the sample attribute
  • symbols, from the symbol attribute
  • the annotation channels, from the chan attribute
  • the sampling frequency, from the fs attribute if present, and if fs was not already extracted from the record argument.
record : wfdb Record, optional
The Record object to be plotted
annotation : wfdb Annotation, optional
The Annotation object to be plotted
plot_sym : bool, optional
Whether to plot the annotation symbols on the graph.
time_units : str, optional
The x axis unit. Allowed options are: ‘samples’, ‘seconds’, ‘minutes’, and ‘hours’.
title : str, optional
The title of the graph.
sig_style : list, optional
A list of strings, specifying the style of the matplotlib plot for each signal channel. The list length should match the number of signal channels. If the list has a length of 1, the style will be used for all channels.
ann_style : list, optional
A list of strings, specifying the style of the matplotlib plot for each annotation channel. The list length should match the number of annotation channels. If the list has a length of 1, the style will be used for all channels.
ecg_grids : list, optional
A list of integers specifying channels in which to plot ecg grids. May also be set to ‘all’ for all channels. Major grids at 0.5mV, and minor grids at 0.125mV. All channels to be plotted with grids must have sig_units equal to ‘uV’, ‘mV’, or ‘V’.
figsize : tuple, optional
Tuple pair specifying the width, and height of the figure. It is the ‘figsize’ argument passed into matplotlib.pyplot’s figure function.
return_fig : bool, optional
Whether the figure is to be returned as an output argument.
figure : matplotlib figure, optional
The matplotlib figure generated. Only returned if the ‘return_fig’ option is set to True.
>>> record = wfdb.rdrecord('sample-data/100', sampto=3000)
>>> annotation = wfdb.rdann('sample-data/100', 'atr', sampto=3000)
>>> wfdb.plot_wfdb(record=record, annotation=annotation, plot_sym=True
                   time_units='seconds', title='MIT-BIH Record 100',
                   figsize=(10,4), ecg_grids='all')
wfdb.plot_all_records(directory='')

Plot all wfdb records in a directory (by finding header files), one at a time, until the ‘enter’ key is pressed.

directory : str, optional
The directory in which to search for WFDB records. Defaults to current working directory.