paq2py.py

"""
paq2py
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
"""

import numpy as np


def paq_read(file_path=None, plot=False):
    """
    Read PAQ file (from PackIO) into python
    Lloyd Russell 2015
    Parameters
    ==========
    file_path : str, optional
        full path to file to read in. if none is supplied a load file dialog
        is opened, buggy on mac osx - Tk/matplotlib. Default: None.
    plot : bool, optional
        plot the data after reading? Default: False.
    Returns
    =======
    data : ndarray
        the data as a m-by-n array where m is the number of channels and n is
        the number of datapoints
    chan_names : list of str
        the names of the channels provided in PackIO
    hw_chans : list of str
        the hardware lines corresponding to each channel
    units : list of str
        the units of measurement for each channel
    rate : int
        the acquisition sample rate, in Hz
    """

    # file load gui
    if file_path is None:
        import Tkinter
        import tkFileDialog
        root = Tkinter.Tk()
        root.withdraw()
        file_path = tkFileDialog.askopenfilename()
        root.destroy()

    # open file
    fid = open(file_path, 'rb')

    # get sample rate
    rate = int(np.fromfile(fid, dtype='>f', count=1))

    # get number of channels
    num_chans = int(np.fromfile(fid, dtype='>f', count=1))

    # get channel names
    chan_names = []
    for i in range(num_chans):
        num_chars = int(np.fromfile(fid, dtype='>f', count=1))
        chan_name = ''
        for j in range(num_chars):
            chan_name = chan_name + chr(np.fromfile(fid, dtype='>f', count=1))
        chan_names.append(chan_name)

    # get channel hardware lines
    hw_chans = []
    for i in range(num_chans):
        num_chars = int(np.fromfile(fid, dtype='>f', count=1))
        hw_chan = ''
        for j in range(num_chars):
            hw_chan = hw_chan + chr(np.fromfile(fid, dtype='>f', count=1))
        hw_chans.append(hw_chan)

    # get acquisition units
    units = []
    for i in range(num_chans):
        num_chars = int(np.fromfile(fid, dtype='>f', count=1))
        unit = ''
        for j in range(num_chars):
            unit = unit + chr(np.fromfile(fid, dtype='>f', count=1))
        units.append(unit)

    # get data
    temp_data = np.fromfile(fid, dtype='>f', count=-1)
    num_datapoints = int(len(temp_data)/num_chans)
    data = np.reshape(temp_data, [num_datapoints, num_chans]).transpose()

    # close file
    fid.close()

    # plot
    if plot:
        import matplotlib
        # matplotlib.use('QT4Agg')
        import matplotlib.pylab as plt
        f, axes = plt.subplots(num_chans, 1, sharex=True)
        for idx, ax in enumerate(axes):
            ax.plot(data[idx])
            ax.set_xlim([0, num_datapoints-1])
            ax.set_ylabel(units[idx])
            ax.set_title(chan_names[idx])
        plt.show()

    return {"data": data,
            "chan_names": chan_names,
            "hw_chans": hw_chans,
            "units": units,
            "rate": rate}

            
def paq_data(paq, chan_name, threshold_ttl=False, plot=False):
    
    '''returns the data in paq (from paq_read) from channel: chan_names
       if threshold_tll: returns sample that trigger occured on
       JR 2019
       '''

    chan_idx = paq['chan_names'].index(chan_name)
    data = paq['data'][chan_idx, :]
    if threshold_ttl:
        data = threshold_detect(data, 1)

    if plot:
        if threshold_ttl:
            plt.plot(data, np.ones(len(data)), '.')
        else:
            plt.plot(data)

    return data