GE Decode

Synchronize in decoder with a buffer reference, decoder GEDecode will attempt to process new data added to the buffer.

decoder = GEDecode(device.BUFFER)
decoder.process(True)

There are a set of methods for clear correctly the stored buffer and recollected data.

device.clear_buffer()  # clear input buffer.
decoder.clear_buffer()  # clear decoded data, breaks the synchrony.
decoder.clear_data()  # clear recollected data.

class pycollect.decode.FormatSubrecord(date_, header)

Bases: object

Parse raw data into Pandas DataFrames.

__init__(date_, header)

Parameters:

• date (Datetime object) – Datetime of the current set.
• header (PhysiologicalData object) – Header with raw data.

check_module(label, replace=None)

Check the status module from determinate group.

Parameters:

• label (str) – Group for check their respective module.
• replace (dict) – Some groups are indexed for multiples modules, in that case, the indexes must be removed.

Returns:

• bool – Module exist.
• bool – Module is active.

format(active, filters=None)

Process a subrecord (their raw header), aply shifts and get references.

Parameters:

• active (array) – List of groups to parse.
• filters (array, optional) – A sub list of desired subrecords.

Returns:

DataFrame with single row that contains all measures with label as headers.

Return type:

DataFrame

get_short(key)

From index in header, convert data to integer, validates and return it.

Parameters:key (Header index) – Location if header of target value. Returns:Int if valus is a signed 16 bits, None if the value is over range and bytearray in other cases. Return type:int, None, bytearray

module_status()

Return the list of present and active modules.

Based in the status bits is possible determine the state of the respective module.

Returns:

• list – List of groups with modules availables.
• list – List of groups with modules availables and actives.
• list – List of measures availables and actives.

class pycollect.decode.GEDecode(buffer, filter_subrecords=None, filter_waveforms=None)

Bases: object

Decode raw data into Pandas DataFrames.

There are two main objects:

• DATA_SUBRECORD: Pandas DataFrame with the subrecords data.

• DATA_WAVE: Dictionary with waveform name as key with the

  Pandas DataFrame with the waveform data.

__continuous_processing__(delay=0.25)

Continuous processing.

Parameters:delay (integer in seconds) – Delay in seconds between each attempted processing.

__create_framelist__(byte)

Search for a complete and validated header.

Parameters:byte (byte) – Byte readed from serial raw data.

__create_recordlist__()

Complete the raw header with the correct/full size.

Returns:Full sized DatexHeaderResponse. Return type:list

__init__(buffer, filter_subrecords=None, filter_waveforms=None)

Parameters:

• buffer (array reference) – Reference with raw data, the processer will attempt to decoded new data added to this object.
• filter_subrecords (array, optional) – Sublist with desired subrecords, if empty then will process all available measures.
• filter_waveforms (array, optional) – List of desired waveforms, if emty then will process all requested waveforms.

__processing__()

Process the input buffer one byte at a time.

Process the input buffer until a header is completed.

clear_buffer()

Clear the processed buffer.

This action brake the synchrony with GEDevice.

clear_data()

Clear the processed data.

process(flag=True, delay=1)

Enable or disable the continuous data processing.

Parameters:

• flag (bool, True) – Enable or disable the continuous data processing.
• delay (integer in seconds) – Delay in seconds between each process attempt.

read_shorts(buffer)

Convert an array if bytes from signed 16 bits to integer.

Parameters:buffer (array) – Array with raw bytes, It will be processed in pairs (for complete 16 bits).

read_subrecords(record_list)

Update the DataFrame of subrecords with new decoded data.

Parameters:record_list (array) – Raw DatexHeaderResponse.

read_waveforms(record_list, ignore_missging=False)

Update the dictionary of waveforms with new decoded data.

Parameters:record_list (array) – List of raw headers.

save_as_csv(filename)

Save the decoded data into a set of CSV files.

Parameters:filename (str) – Absolute or realtive path for CSV file. Returns:A list with filenames generated. Return type:list

save_as_edf(filename, edf_header=None, annotations=None)

Save the decoded data into a set of EDF+ files.

Parameters:

• filename (str) – Absolute or realtive path for EDF+ file.
• edf_header (dict) – Declare the EDF+ patient header.

Returns:

A list with filenames genrated.

Return type:

list

save_as_raw(filename)

Save the decoded data into a RAW file.

Parameters:filename (str) – Absolute or realtive path for RAW file. Returns:A list with filenames generated. Return type:list

set_edf_header(**header)

Set the EDF+ patient header.

Parameters:

• admincode (str) – Sets the admincode.
• birthdate (date object from datetime) – Sets the birthdate.
• equipment (str) – Describes the measurement equpipment.
• gender (int) – Sets the gender, 1 is male, 0 is female.
• patientcode (str) – Sets the patient code.
• patientname (str) – Sets the patient name.
• patient_additional (str) – Sets the additional patient info.
• recording_additional (str) – Sets the additional recordinginfo.
• startdate (datetime object) – Sets the recording start Time.
• technician (str) – Sets the technicians name.