EphysDataAnalysis/paq2py.py at master · AMShelton/EphysDataAnalysis · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
"""
paq2py
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
"""

import numpy as np
import seaborn as sns

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, figsize=(15,7.5), frameon=False)
        for idx, ax in enumerate(axes):
            sns.despine(bottom=True,left=True)
            # ax.set_ylabel([])
            # ax.set_xlabel([])
            # ax.set_xticklabels([])
            # ax.set_yticklabels([])
            ax.plot(data[idx],'k',lw=0.5)
            ax.set_xlim([0, num_datapoints-1])
            ax.set_ylim([data[idx].min()-1, data[idx].max()+1])
            ax.set_ylabel(units[idx])
            ax.set_title(chan_names[idx],fontsize=20)
        plt.tight_layout()
        plt.show()

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