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Produces MAT file from WFDB format
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‎wfdb/__init__.py

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from wfdb.io.record import (Record, MultiRecord, rdheader, rdrecord, rdsamp,
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wrsamp, dl_database, edf2mit, wav2mit, sampfreq, signame)
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wrsamp, dl_database, edf2mit, wav2mit, wfdb2mat, sampfreq, signame)
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from wfdb.io.annotation import (Annotation, rdann, wrann, show_ann_labels,
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show_ann_classes, ann2rr)
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from wfdb.io.download import get_dbs, get_record_list, dl_files, set_db_index_url

‎wfdb/io/__init__.py

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@@ -1,5 +1,5 @@
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from wfdb.io.record import (Record, MultiRecord, rdheader, rdrecord, rdsamp, wrsamp,
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dl_database, edf2mit, wav2mit, sampfreq, signame, SIGNAL_CLASSES)
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dl_database, edf2mit, wav2mit, wfdb2mat, sampfreq, signame, SIGNAL_CLASSES)
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from wfdb.io._signal import est_res, wr_dat_file
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from wfdb.io.annotation import (Annotation, rdann, wrann, show_ann_labels,
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show_ann_classes, ann2rr)

‎wfdb/io/record.py

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@@ -1706,6 +1706,278 @@ def wav2mit(record_name, pn_dir=None, delete_file=True, record_only=False):
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pass
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def wfdb2mat(record_name, pn_dir=None, sampfrom=0, sampto=None, channels=None):
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"""
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This program converts the signals of any PhysioNet record (or one in any
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compatible format) into a .mat file that can be read directly using any version
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of Matlab, and a short text file containing information about the signals
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(names, gains, baselines, units, sampling frequency, and start time/date if
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known). If the input record name is REC, the output files are RECm.mat and
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RECm.hea. The output files can also be read by any WFDB application as record
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RECm.
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This program does not convert annotation files; for that task, 'rdann' is
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recommended.
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The output .mat file contains a single matrix named `val` containing raw
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(unshifted, unscaled) samples from the selected record. Using various options,
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you can select any time interval within a record, or any subset of the signals,
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which can be rearranged as desired within the rows of the matrix. Since .mat
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files are written in column-major order (i.e., all of column n precedes all of
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column n+1), each vector of samples is written as a column rather than as a
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row, so that the column number in the .mat file equals the sample number in the
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input record (minus however many samples were skipped at the beginning of the
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record, as specified using the `start_time` option). If this seems odd, transpose
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your matrix after reading it!
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This program writes version 5 MAT-file format output files, as documented in
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http://www.mathworks.com/access/helpdesk/help/pdf_doc/matlab/matfile_format.pdf
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The samples are written as 32-bit signed integers (mattype=20 below) in
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little-endian format if the record contains any format 24 or format 32 signals,
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as 8-bit unsigned integers (mattype=50) if the record contains only format 80
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signals, or as 16-bit signed integers in little-endian format (mattype=30)
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otherwise.
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The maximum size of the output variable is 2^31 bytes. `wfdb2mat` from versions
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10.5.24 and earlier of the original WFDB software package writes version 4 MAT-
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files which have the additional constraint of 100,000,000 elements per variable.
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The output files (recordm.mat + recordm.hea) are still WFDB-compatible, given
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the .hea file constructed by this program.
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Parameters
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----------
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record_name : str
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The name of the input WFDB record to be read. Can also work with both
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EDF and WAV files.
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pn_dir : str, optional
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Option used to stream data from Physionet. The Physionet
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database directory from which to find the required record files.
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eg. For record '100' in 'http://physionet.org/content/mitdb'
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pn_dir='mitdb'.
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sampfrom : int, optional
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The starting sample number to read for all channels.
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sampto : int, 'end', optional
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The sample number at which to stop reading for all channels.
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Reads the entire duration by default.
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channels : list, optional
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List of integer indices specifying the channels to be read.
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Reads all channels by default.
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Returns
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-------
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N/A
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Notes
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-----
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The entire file is composed of:
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Bytes 0 - 127: descriptive text
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Bytes 128 - 131: master tag (data type = matrix)
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Bytes 132 - 135: master tag (data size)
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Bytes 136 - 151: array flags (4 byte tag with data type, 4 byte
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tag with subelement size, 8 bytes of content)
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Bytes 152 - 167: array dimension (4 byte tag with data type, 4
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byte tag with subelement size, 8 bytes of content)
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Bytes 168 - 183: array name (4 byte tag with data type, 4 byte
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tag with subelement size, 8 bytes of content)
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Bytes 184 - ...: array content (4 byte tag with data type, 4 byte
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tag with subelement size, ... bytes of content)
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Examples
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--------
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>>> wfdb.wfdb2mat('100', pn_dir='pwave')
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The output file name is 100m.mat and 100m.hea
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"""
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record = rdrecord(record_name, pn_dir=pn_dir, sampfrom=sampfrom, sampto=sampto)
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record_name_out = record_name.split(os.sep)[-1].replace('-','_') + 'm'
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# Some variables describing the format of the .mat file
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field_version = 256 # 0x0100 or 256
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endian_indicator = b'IM' # little endian
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master_type = 14 # matrix
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sub1_type = 6 # UINT32
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sub2_type = 5 # INT32
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sub3_type = 1 # INT8
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sub1_class = 6 # double precision array
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# Determine if we can write 8-bit unsigned samples, or if 16 or 32 bits
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# are needed per sample
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bytes_per_element = 1
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for i in range(record.n_sig):
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if (record.adc_res[i] > 0):
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if (record.adc_res[i] > 16):
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bytes_per_element = 4
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elif (record.adc_res[i] > 8) and (bytes_per_element < 2):
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bytes_per_element = 2
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else:
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# adc_res not specified.. try to guess from format
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if (record.fmt[i] == '24') or (record.fmt[i] == '32'):
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bytes_per_element = 4
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elif (record.fmt[i] != '80') and (bytes_per_element < 2):
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bytes_per_element = 2
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if (bytes_per_element == 1):
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sub4_type = 2 # MAT8
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out_type = '<u1' # np.uint8
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wfdb_type = '80' # Offset binary form (80)
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offset = 128 # Offset between sample values and the raw
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# byte/word values as interpreted by Matlab/Octave
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elif (bytes_per_element == 2):
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sub4_type = 3 # MAT16
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out_type = '<i2' # np.int16
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wfdb_type = '16' # Align with byte boundary (16)
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offset = 0 # Offset between sample values and the raw
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# byte/word values as interpreted by Matlab/Octave
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else:
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sub4_type = 5 # MAT32
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out_type = '<i4' # np.int32
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wfdb_type = '32' # Align with byte boundary (32)
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offset = 0 # Offset between sample values and the raw
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# byte/word values as interpreted by Matlab/Octave
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# Ensure the signal size does not exceed the 2^31 byte limit
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max_length = int((2**31) / bytes_per_element / record.n_sig)
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if sampto is None:
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sampto = record.p_signal.shape[0]
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desired_length = sampto - sampfrom
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# Snip record
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if desired_length > max_length:
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raise Exception("Can't write .mat file: data size exceeds 2GB limit")
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# Bytes of actual data
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bytes_of_data = bytes_per_element * record.n_sig * desired_length
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# This is the remaining number of bytes that don't fit into integer
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# multiple of 8: i.e. if 18 bytes, bytes_remain = 2, from 17 to 18
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bytes_remain = bytes_of_data % 8
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# master_bytes = (8 + 8) + (8 + 8) + (8 + 8) + (8 + bytes_of_data) + padding
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# Must be integer multiple 8
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if bytes_remain == 0:
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master_bytes = bytes_of_data + 56
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else:
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master_bytes = bytes_of_data + 64 - (bytes_remain)
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# Start writing the file
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output_file = record_name_out + '.mat'
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with open(output_file, 'wb') as f:
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# Descriptive text (124 bytes)
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f.write(struct.pack('<124s', b'MATLAB 5.0'))
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# Version (2 bytes)
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f.write(struct.pack('<H', field_version))
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# Endian indicator (2 bytes)
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f.write(struct.pack('<2s', endian_indicator))
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# Master tag data type (4 bytes)
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f.write(struct.pack('<I', master_type))
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# Master tag number of bytes (4 bytes)
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# Number of bytes of data element
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# = (8 + 8) + (8 + 8) + (8 + 8) + (8 + bytes_of_data)
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# = 56 + bytes_of_data
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f.write(struct.pack('<I', master_bytes))
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# Matrix data has 4 subelements (5 if imaginary):
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# Array flags, dimensions array, array name, real part
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# Each subelement has its own subtag, and subdata
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# Subelement 1: Array flags
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# Subtag 1: data type (4 bytes)
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f.write(struct.pack('<I', sub1_type))
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# Subtag 1: number of bytes (4 bytes)
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f.write(struct.pack('<I', 8))
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# Value class indication the MATLAB data type (8 bytes)
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f.write(struct.pack('<Q', sub1_class))
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# Subelement 2: Rows and columns
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# Subtag 2: data type (4 bytes)
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f.write(struct.pack('<I', sub2_type))
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# Subtag 2: number of bytes (4 bytes)
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f.write(struct.pack('<I', 8))
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# Number of signals (4 bytes)
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f.write(struct.pack('<I', record.n_sig))
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# Number of rows (4 bytes)
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f.write(struct.pack('<I', desired_length))
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# Subelement 3: Array name
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# Subtag 3: data type (4 bytes)
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f.write(struct.pack('<I', sub3_type))
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# Subtag 3: number of bytes (4 bytes)
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f.write(struct.pack('<I', 3))
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# Subtag 3: name of the array (8 bytes)
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f.write(struct.pack('<8s', b'val'))
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# Subelement 4: Signal data
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# Subtag 4: data type (4 bytes)
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f.write(struct.pack('<I', sub4_type))
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# Subtag 4: number of bytes (4 bytes)
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f.write(struct.pack('<I', bytes_of_data))
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# Total size of everything before actual data:
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# 128 byte header
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# + 8 byte master tag
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# + 56 byte subelements (48 byte default + 8 byte name)
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# = 192
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# Copy the selected data into the .mat file
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out_data = record.p_signal * record.adc_gain + record.baseline - record.adc_zero
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# Cast the data to the correct type base on the bytes_per_element
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out_data = np.around(out_data).astype(out_type)
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# out_data should be [r1c1, r1c2, r2c1, r2c2, etc.]
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out_data = out_data.flatten()
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out_fmt = '<%sh' % len(out_data)
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f.write(struct.pack(out_fmt, *out_data))
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# Display some useful information
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if record.base_time is None:
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if record.base_date is None:
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datetime_string = '[None]'
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else:
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datetime_string = '[{}]'.format(record.base_date.strftime('%d/%m/%Y'))
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else:
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if record.base_date is None:
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datetime_string = '[{}]'.format(record.base_time.strftime('%H:%M:%S.%f'))
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else:
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datetime_string = '[{} {}]'.format(record.base_time.strftime('%H:%M:%S.%f'),
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record.base_date.strftime('%d/%m/%Y'))
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print('Source: record {}\t\tStart: {}'.format(record_name, datetime_string))
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print('val has {} rows (signals) and {} columns (samples/signal)'.format(record.n_sig,
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desired_length))
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duration_string = str(datetime.timedelta(seconds=desired_length/record.fs))
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print('Duration: {}'.format(duration_string))
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print('Sampling frequency: {} Hz\tSampling interval: {} sec'.format(record.fs,
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1/record.fs))
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print('{:<7}{:<20}{:<17}{:<10}{:<10}'.format('Row','Signal','Gain','Base','Units'))
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record.sig_name = [s.replace(' ','_') for s in record.sig_name]
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for i in range(record.n_sig):
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print('{:<7}{:<20}{:<17}{:<10}{:<10}'.format(i,
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record.sig_name[i],
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record.adc_gain[i],
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record.baseline[i]-record.adc_zero[i]+offset,
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record.units[i]))
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# Modify the record file to reflect the new data
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num_channels = record.n_sig if (channels is None) else len(channels)
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record.record_name = record_name_out
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record.n_sig = num_channels
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record.samps_per_frame = num_channels * [1]
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record.file_name = num_channels * [output_file]
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record.fmt = num_channels * [wfdb_type]
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record.byte_offset = num_channels * [192]
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record.baseline = [b - record.adc_zero[i] for i,b in enumerate(record.baseline)]
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record.adc_zero = num_channels * [0]
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record.init_value = out_data[:record.n_sig].tolist()
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# Write the header file RECm.hea
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record.wrheader()
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# Append the following lines to create a signature
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with open(record_name_out+'.hea','a') as f:
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f.write('#Creator: wfdb2mat\n')
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f.write('#Source: record {}\n'.format(record_name))
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#------------------------- Reading Records --------------------------- #
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