csv2mit_with_dir_out.py
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Created: Tue, Jun 18, 19:58

csv2mit_with_dir_out.py
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	import datetime
	import multiprocessing
	import posixpath
	import re

	import numpy as np
	import os
	import pandas as pd
	import requests
	import math
	import functools
	import struct
	import pdb

	from wfdb.io import _header
	from wfdb.io import _signal
	from wfdb.io import download
	from wfdb.io import annotation
	import wfdb

	def csv2mit_with_dir_out(file_name, fs, units, fmt=None, adc_gain=None, baseline=None,
	samps_per_frame=None, counter_freq=None, base_counter=None,
	base_time=None, base_date=None, comments=None, sig_name=None,
	dat_file_name=None, skew=None, byte_offset=None, adc_res=None,
	adc_zero=None, init_value=None, checksum=None, block_size=None,
	record_only=False, header=True, delimiter=',', verbose=False, write_dir = ''):
	"""
	Read a WFDB header file and return either a `Record` object with the
	record descriptors as attributes or write a record and header file.

	Parameters
	----------
	file_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/BASE_RECORD.
	Both relative and absolute paths are accepted. If the `pn_dir`
	parameter is set, this parameter should contain just the base
	record name, and the files fill be searched for remotely.
	Otherwise, the data files will be searched for in the local path.
	fs : float
	This number can be expressed in any format legal for a Python input of
	floating point numbers (thus '360', '360.', '360.0', and '3.6e2' are
	all legal and equivalent). The sampling frequency must be greater than 0;
	if it is missing, a value of 250 is assumed.
	units : list, str
	This will be applied as the passed list unless a single str is passed
	instead - in which case the str will be assigned for all channels.
	This field can be present only if the ADC gain is also present. It
	follows the baseline field if that field is present, or the gain field
	if the baseline field is absent. The units field is a list of character
	strings that specifies the type of physical unit. If the units field is
	absent, the physical unit may be assumed to be 1 mV.
	fmt : list, str, optional
	This will be applied as the passed list unless a single str is passed
	instead - in which case the str will be assigned for all
	channels. 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.
	Each field is an integer that specifies the storage format of the signal.
	All signals in a given group are stored in the same format. The most
	common format is format `16` (sixteen-bit amplitudes). The parameters
	`samps_per_frame`, `skew`, and `byte_offset` are optional fields, and
	if present, are bound to the format field. In other words, they may be
	considered as format modifiers, since they further describe the encoding
	of samples within the signal file.
	adc_gain : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	This field is a list of numbers that specifies the difference in
	sample values that would be observed if a step of one physical unit
	occurred in the original analog signal. For ECGs, the gain is usually
	roughly equal to the R-wave amplitude in a lead that is roughly parallel
	to the mean cardiac electrical axis. If the gain is zero or missing, this
	indicates that the signal amplitude is uncalibrated; in such cases, a
	value of 200 ADC units per physical unit may be assumed.
	baseline : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels. This
	field can be present only if the ADC gain is also present. It is not
	separated by whitespace from the ADC gain field; rather, it is
	surrounded by parentheses, which delimit it. The baseline is an integer
	that specifies the sample value corresponding to 0 physical units. If
	absent, the baseline is taken to be equal to the ADC zero. Note that
	the baseline need not be a value within the ADC range; for example,
	if the ADC input range corresponds to 200-300 degrees Kelvin, the
	baseline is the (extended precision) value that would map to 0 degrees
	Kelvin.
	samps_per_frame : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	Normally, all signals in a given record are sampled at the (base)
	sampling frequency as specified by `fs`; in this case, the number of
	samples per frame is 1 for all signals, and this field is conventionally
	omitted. If the signal was sampled at some integer multiple, n, of the
	base sampling frequency, however, each frame contains n samples of the
	signal, and the value specified in this field is also n. (Note that
	non-integer multiples of the base sampling frequency are not supported).
	counter_freq : float, optional
	This field (a floating-point number, in the same format as `fs`) can be
	present only if `fs` is also present. Typically, the counter frequency
	may be derived from an analog tape counter, or from page numbers in a
	chart recording. If the counter frequency is absent or not positive,
	it is assumed to be equal to `fs`.
	base_counter : float, optional
	This field can be present only if the counter frequency is also present.
	The base counter value is a floating-point number that specifies the counter
	value corresponding to sample 0. If absent, the base counter value is
	taken to be 0.
	base_time : str, optional
	This field can be present only if the number of samples is also present.
	It gives the time of day that corresponds to the beginning of the
	record, in 'HH:MM:SS' format (using a 24-hour clock; thus '13:05:00', or
	'13:5:0', represent 1:05 pm). If this field is absent, the time-conversion
	functions assume a value of '0:0:0', corresponding to midnight.
	base_date : str, optional
	This field can be present only if the base time is also present. It contains
	the date that corresponds to the beginning of the record, in 'DD/MM/YYYY'
	format (e.g., '25/4/1989' is '25 April 1989').
	comments : list, optional
	A list of string comments to be written to the header file. Each string
	entry represents a new line to be appended to the bottom of the header
	file ('.hea').
	sig_name : list, optional
	A list of strings giving the signal name of each signal channel. This
	will be used for plotting the signal both in this package and
	LightWave. Note, this value will be used in preference to the CSV
	header, if applicable, to define custom signal names.
	dat_file_name : str, optional
	The name of the file in which samples of the signal are kept. Although the
	record name is usually part of the signal file name, this convention is
	not a requirement. Note that several signals can share the same file
	(i.e., they can belong to the same signal group); all entries for signals
	that share a given file must be consecutive, however. Note, the default
	behavior is to save the files in the current working directory, not the
	directory of the file being read.
	skew : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	Ideally, within a given record, samples of different signals with the
	same sample number are simultaneous (within one sampling interval).
	If this is not the case (as, for example, when a multitrack analog
	tape recording is digitized and the azimuth of the playback head does
	not match that of the recording head), the skew between signals can
	sometimes be determined (for example, by locating recorded waveform
	features with known time relationships, such as calibration signals).
	If this has been done, the skew field may be inserted into the header
	file to indicate the (positive) number of samples of the signal that
	are considered to precede sample 0. These samples, if any, are included
	in the checksum. (Note the checksum need not be changed if the skew field
	is inserted or modified).
	byte_offset : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	Normally, signal files include only sample data. If a signal file
	includes a preamble, however, this field specifies the offset in bytes
	from the beginning of the signal file to sample 0 (i.e., the length
	of the preamble). Data within the preamble is not included in the signal
	checksum. Note that the byte offset must be the same for all signals
	within a given group (use the skew field to correct for intersignal
	skew). This feature is provided only to simplify the task of reading
	signal files not generated using the WFDB library; the WFDB library
	does not support any means of writing such files, and byte offsets must
	be inserted into header files manually.
	adc_res: list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	This field can be present only if the ADC gain is also present. It
	specifies the resolution of the analog-to-digital converter used to
	digitize the signal. Typical ADCs have resolutions between 8 and 16
	bits. If this field is missing or zero, the default value is 12 bits
	for amplitude-format signals, or 10 bits for difference-format signals
	(unless a lower value is specified by the format field).
	adc_zero: list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	This field can be present only if the ADC resolution is also present.
	It is an integer that represents the amplitude (sample value) that
	would be observed if the analog signal present at the ADC inputs had
	a level that fell exactly in the middle of the input range of the ADC.
	For a bipolar ADC, this value is usually zero, but a unipolar (offset
	binary) ADC usually produces a non-zero value in the middle of its
	range. Together with the ADC resolution, the contents of this field
	can be used to determine the range of possible sample values. If this
	field is missing, a value of 0 is assumed.
	init_value : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	This field can be present only if the ADC zero is also present. It
	specifies the value of sample 0 in the signal, but is used only if the
	signal is stored in difference format. If this field is missing, a
	value equal to the ADC zero is assumed.
	checksum : list, optional
	This field can be present only if the initial value is also present. It
	is a 16-bit signed checksum of all samples in the signal. (Thus the
	checksum is independent of the storage format.) If the entire record
	is read without skipping samples, and the header’s record line specifies
	the correct number of samples per signal, this field is compared against
	a computed checksum to verify that the signal file has not been corrupted.
	A value of zero may be used as a field placeholder if the number of
	samples is unspecified.
	block_size : list, int, optional
	This will be applied as the passed list unless a single int is passed
	instead - in which case the int will be assigned for all channels.
	This field can be present only if the checksum is present. This field
	is an integer and is usually 0. If the signal is stored in a file
	that must be read in blocks of a specific size, however, this field
	specifies the block size in bytes. (On UNIX systems, this is the case
	only for character special files, corresponding to certain tape and
	raw disk files. If necessary, the block size may be given as a negative
	number to indicate that the associated file lacks I/O driver support for
	some operations.) All signals belonging to the same signal group have
	the same block size.
	record_only : bool, optional
	Whether to only return the record information (True) or not (False).
	If false, this function will generate both a .dat and .hea file.
	header : bool, optional
	Whether to assume the CSV has a first line header (True) or not (False)
	which defines the signal names. If false, this function will generate
	either the signal names provided by `sig_name` or set `[ch_1, ch_2, ...]`
	as the default.
	delimiter : str, optional
	What to use as the delimiter for the file to separate data. The default
	if a comma (','). Other common delimiters are tabs ('\t'), spaces (' '),
	pipes ('\|'), and colons (':').
	verbose : bool, optional
	Whether to print all the information read about the file (True) or
	not (False).
	write_dir : str, optional
	the target directory to write the data to

	Returns
	-------
	record : Record or MultiRecord, optional
	The WFDB Record or MultiRecord object representing the contents
	of the CSV file read.

	Notes
	-----
	CSVs should be in the following format:

	sig_1_name,sig_2_name,...
	sig_1_val_1,sig_2_val_1,...
	sig_1_val_2,sig_2_val_2,...
	...,...,...

	Or this format if `header=False` is defined:

	sig_1_val_1,sig_2_val_1,...
	sig_1_val_2,sig_2_val_2,...
	...,...,...

	The signal will be saved defaultly as a `p_signal` so both floats and
	ints are acceptable.

	Examples
	--------
	Create the header ('.hea') and record ('.dat') files, specifies both
	units to be 'mV'
	>>> wfdb.csv2mit('sample-data/100.csv', fs=360, units='mV')

	Create the header ('.hea') and record ('.dat') files, change units for
	each signal
	>>> wfdb.csv2mit('sample-data/100.csv', fs=360, units=['mV','kV'])

	Return just the record, note the use of lists to specify which values should
	be applied to each signal
	>>> csv_record = wfdb.csv2mit('sample-data/100.csv', fs=360, units=['mV','mV'],
	fmt=['80',212'], adc_gain=[100,200],
	baseline=[1024,512], record_only=True)

	Return just the record, note the use of single strings and ints to specify
	when fields can be applied to all signals
	>>> csv_record = wfdb.csv2mit('sample-data/100.csv', fs=360, units='mV',
	fmt=['80','212'], adc_gain=200, baseline=1024,
	record_only=True)

	"""
	# NOTE: No need to write input checks here since the Record class should
	# handle them (except verifying the CSV input format which is for Pandas)
	if header:
	df_CSV = pd.read_csv(file_name, delimiter=delimiter)
	else:
	df_CSV = pd.read_csv(file_name, delimiter=delimiter, header=None)
	if verbose:
	print('Successfully read CSV')
	# Extract the entire signal from the dataframe
	p_signal = df_CSV.values
	# The dataframe should be in (`sig_len`, `n_sig`) dimensions
	sig_len = p_signal.shape[0]
	if verbose:
	print('Signal length: {}'.format(sig_len))
	n_sig = p_signal.shape[1]
	if verbose:
	print('Number of signals: {}'.format(n_sig))
	# Check if signal names are valid and set defaults
	if not sig_name:
	if header:
	sig_name = df_CSV.columns.to_list()
	if any(map(str.isdigit, sig_name)):
	print("WARNING: One or more of your signal names are numbers, this "\
	"is not recommended:\n- Does your CSV have a header line "\
	"which defines the signal names?\n- If not, please set the "\
	"parameter 'header' to False.\nSignal names: {}".format(sig_name))
	else:
	sig_name = ['ch_'+str(i) for i in range(n_sig)]
	if verbose:
	print('Signal names: {}'.format(sig_name))

	# Set the output header file name to be the same, remove path
	if write_dir == '':
	write_dir = os.path.join(*file_name.split(os.sep)[:-1])
	if os.sep in file_name:
	file_name = file_name.split(os.sep)[-1]
	record_name = file_name.replace('.csv','')
	if verbose:
	print('Output header: {}.hea'.format(record_name))

	# Replace the CSV file tag with DAT
	dat_file_name = file_name.replace('.csv','.dat')
	dat_file_name = [dat_file_name] * n_sig
	if verbose:
	print('Output record: {}'.format(dat_file_name[0]))

	# Convert `units` from string to list if necessary
	units = [units]*n_sig if type(units) is str else units

	# Set the default `fmt` if none exists
	if not fmt:
	fmt = ['16'] * n_sig
	fmt = [fmt]*n_sig if type(fmt) is str else fmt
	if verbose:
	print('Signal format: {}'.format(fmt))

	# Set the default `adc_gain` if none exists
	if not adc_gain:
	adc_gain = [200] * n_sig
	adc_gain = [adc_gain]*n_sig if type(adc_gain) is int else adc_gain
	if verbose:
	print('Signal ADC gain: {}'.format(adc_gain))

	# Set the default `baseline` if none exists
	if not baseline:
	if adc_zero:
	baseline = [adc_zero] * n_sig
	else:
	baseline = [0] * n_sig
	baseline = [baseline]*n_sig if type(baseline) is int else baseline
	if verbose:
	print('Signal baseline: {}'.format(baseline))

	# Convert `samps_per_frame` from int to list if necessary
	samps_per_frame = [samps_per_frame]*n_sig if type(samps_per_frame) is int else samps_per_frame

	# Convert `skew` from int to list if necessary
	skew = [skew]*n_sig if type(skew) is int else skew

	# Convert `byte_offset` from int to list if necessary
	byte_offset = [byte_offset]*n_sig if type(byte_offset) is int else byte_offset

	# Set the default `adc_res` if none exists
	if not adc_res:
	adc_res = [12] * n_sig
	adc_res = [adc_res]*n_sig if type(adc_res) is int else adc_res
	if verbose:
	print('Signal ADC resolution: {}'.format(adc_res))

	# Set the default `adc_zero` if none exists
	if not adc_zero:
	adc_zero = [0] * n_sig
	adc_zero = [adc_zero]*n_sig if type(adc_zero) is int else adc_zero
	if verbose:
	print('Signal ADC zero: {}'.format(adc_zero))

	# Set the default `init_value`
	# NOTE: Initial value (and subsequently the digital signal) won't be correct
	# unless the correct `baseline` and `adc_gain` are provided... this is just
	# the best approximation
	if not init_value:
	init_value = p_signal[0,:]
	init_value = baseline + (np.array(adc_gain) * init_value)
	init_value = [int(i) for i in init_value.tolist()]
	if verbose:
	print('Signal initial value: {}'.format(init_value))

	# Set the default `checksum`
	if not checksum:
	checksum = [int(np.sum(v) % 65536) for v in np.transpose(p_signal)]
	if verbose:
	print('Signal checksum: {}'.format(checksum))

	# Set the default `block_size`
	if not block_size:
	block_size = [0] * n_sig
	block_size = [block_size]*n_sig if type(block_size) is int else block_size
	if verbose:
	print('Signal block size: {}'.format(block_size))

	# Change the dates and times into `datetime` objects
	if base_time:
	base_time = _header.wfdb_strptime(base_time)
	if base_date:
	base_date = datetime.datetime.strptime(base_date, '%d/%m/%Y').date()

	# Convert array to floating point
	p_signal = p_signal.astype('float64')

	# Either return the record or generate the record and header files
	# if requested
	if record_only:
	# Create the record from the input and generated values
	record = wfdb.Record(
	record_name = record_name,
	n_sig = n_sig,
	fs = fs,
	samps_per_frame = samps_per_frame,
	counter_freq = counter_freq,
	base_counter = base_counter,
	sig_len = sig_len,
	base_time = base_time,
	base_date = base_date,
	comments = comments,
	sig_name = sig_name,
	p_signal = p_signal,
	d_signal = None,
	e_p_signal = None,
	e_d_signal = None,
	file_name = dat_file_name,
	fmt = fmt,
	skew = skew,
	byte_offset = byte_offset,
	adc_gain = adc_gain,
	baseline = baseline,
	units = units,
	adc_res = adc_res,
	adc_zero = adc_zero,
	init_value = init_value,
	checksum = checksum,
	block_size = block_size
	)
	if verbose:
	print('Record generated successfully')
	return record

	else:
	# Write the information to a record and header file
	wfdb.wrsamp(
	record_name = record_name,
	fs = fs,
	units = units,
	sig_name = sig_name,
	p_signal = p_signal,
	fmt = fmt,
	adc_gain = adc_gain,
	baseline = baseline,
	comments = comments,
	base_time = base_time,
	base_date = base_date,
	write_dir = write_dir
	)
	if verbose:
	print('File generated successfully')

	if __name__ == "__main__":
	pass

csv2mit_with_dir_out.pyNo OneTemporaryActions

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csv2mit_with_dir_out.py
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csv2mit_with_dir_out.py
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