How to use the pyedflib.FILETYPE_EDFPLUS function in pyEDFlib

if self.doRealTimeStreaming:
            self.path_and_file_name_event = self.path_and_file_name_event
            print "Will export Events CSV to:", self.path_and_file_name_event + '.csv'
            # Open in append mode
            self.fevent = open(self.path_and_file_name_event + '.csv', 'a', buffering=100000)
            if self.exportEDFAnnotations:
                print "Will export Events from EDF to CSV in:", self.path_and_file_name_event + '.edf' + '.csv'
                self.feventEDF = open(self.path_and_file_name_event + '.edf' + '.csv', 'a', buffering=100000)
                self.feventEDF.write('onset' + self.delim + 'annotation' + '\n')
            # if self.isActivated:
            #     self.fevent.write('#Streaming restarted at ' + self.time_stamp + '\n')
            # self.fevent.write('#Streaming started at ' + self.time_stamp + '\n')
            if self.writeEDF:

                EDF_format_extention = ".edf"
                EDF_format_filetype = pyedflib.FILETYPE_EDFPLUS
                temp_filterStringFileIndicator = "_prefiltered"
                temp_filterStringHeader = 'HP ' + str(self.prefilterEDF_hp) + ' Hz'
                if self.prefilterEDF_hp is None:
                    EDF_format_extention = ".bdf"
                    EDF_format_filetype = pyedflib.FILETYPE_BDFPLUS
                    temp_filterStringFileIndicator = "_unfiltered"
                    temp_filterStringHeader = 'none'

                self.edfWriter = pyedflib.EdfWriter(self.path_and_file_name + "_missing_samples_corrected" + temp_filterStringFileIndicator + EDF_format_extention, self.nChannels+3, file_type=EDF_format_filetype)

                """
                 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 */
                """
                if self.writeEDFAnnotations:
                    self.edfWriter.set_number_of_annotation_signals(self.edfAnnotationChannels) #7*60 = 420 annotations per minute on average

def write_edf(fname, raw):
    """Export raw to EDF/BDF file (requires pyEDFlib)."""
    import pyedflib

    ext = "".join(Path(fname).suffixes)
    if ext == ".edf":
        filetype = pyedflib.FILETYPE_EDFPLUS
        dmin, dmax = -32768, 32767
    elif ext == ".bdf":
        filetype = pyedflib.FILETYPE_BDFPLUS
        dmin, dmax = -8388608, 8388607
    data = raw.get_data() * 1e6  # convert to microvolts
    fs = raw.info["sfreq"]
    nchan = raw.info["nchan"]
    ch_names = raw.info["ch_names"]
    if raw.info["meas_date"] is not None:
        meas_date = raw.info["meas_date"]
    else:
        meas_date = None
    prefilter = (f"{raw.info['highpass']}Hz - "
                 f"{raw.info['lowpass']}")
    pmin, pmax = data.min(axis=1), data.max(axis=1)
    f = pyedflib.EdfWriter(fname, nchan, filetype)

#    5    pulse 3           100 uV    1 Hz    217 Hz
#    6    noise             100 uV    - Hz    200 Hz
#    7    sine 1 Hz         100 uV    1 Hz    200 Hz
#    8    sine 8 Hz         100 uV    8 Hz    200 Hz
#    9    sine 8.1777 Hz    100 uV    8.25 Hz 200 Hz
#    10    sine 8.5 Hz       100 uV    8.5Hz   200 Hz
#    11    sine 15 Hz        100 uV   15 Hz    200 Hz
#    12    sine 17 Hz        100 uV   17 Hz    200 Hz
#    13    sine 50 Hz        100 uV   50 Hz    200 Hz


if __name__ == '__main__':
    test_data_file = os.path.join('.', 'test_generator2.edf')
    file_duration = 600
    f = pyedflib.EdfWriter(test_data_file, 13,
                           file_type=pyedflib.FILETYPE_EDFPLUS)
    channel_info = []
    data_list = []

    ch_dict = {'label': 'squarewave', 'dimension': 'uV', 'sample_rate': 200, 'physical_max': 100, 'physical_min': -100, 'digital_max': 32767, 'digital_min': -32768, 'transducer': '', 'prefilter':''}
    channel_info.append(ch_dict)
    time = np.linspace(0, file_duration, file_duration*200)
    xtemp = np.sin(2*np.pi*0.1*time)
    x1 = xtemp.copy()
    x1[np.where(xtemp > 0)[0]] = 100
    x1[np.where(xtemp < 0)[0]] = -100
    data_list.append(x1)

    ch_dict = {'label': 'ramp', 'dimension': 'uV', 'sample_rate': 200, 'physical_max': 100, 'physical_min': -100, 'digital_max': 32767, 'digital_min': -32768, 'transducer': '', 'prefilter':''}
    channel_info.append(ch_dict)
    time = np.linspace(0, file_duration, file_duration*200)
    x2 = signal.sawtooth(2 * np.pi * 1 * time)