labstreaminglayer/app-sigvisualizer

PyQt5 application for real time signal visualization

SigVisualizer

SigVisualizer is a PyQt5 GUI application that visualizes electroencephalogram signals streamed from lab streaming layer (LSL) in real time.

Requirements

• Python 3.x
• PyQt5

app-sigvisualizer's Issues

Rename to all lowercase "sigvisualizer"

Python packages are commonly all lowercase. Would it be possible to rename this repository to "sigvisualizer"? If you are OK with this change, the files SigVisualizer.png, SigVisualizer.py, Ui_SigVisualizer.py, and Ui_SigVisualizer.ui should also be renamed accordingly.

Testing setup

I'd like to test the app by receiving some artificial LSL streams - do you know if there is a simple LSL outlet I could use? Ideally, this outlet would produce sinusoidal, rectangular, and sawtooth signals instead of random noise.

MNE LSL realtime client

Just a heads up that MNE now supports LSL streaming with its realtime client API: mne-tools/mne-python#6141

Is it possible to put filter in SigVisualizer?

I am trying to put the filtering or PSD calculation in the middle of SigVisualizer.
In the paintwidget.py, where is the best place to put the some code lines using scipy.signal and mne.filter?

from scipy.signal import lfilter, lfilter_zi
from mne.filter import create_filter

window = 10
n_samples = int(self.sfreq * window)
#self.sfreq=params['metadata']['srate']
#n_chans=params['metadata']['ch_count']

self.data_f = np.zeros((n_samples, self.n_chans))
self.data = np.zeros((n_samples, self.n_chans))
self.af = [1.0]
self.bf = create_filter(self.data_f.T, self.sfreq, 3, 40.,
                            method='fir')

OverflowError when HD-EEG data streamed to SigVisualizer

LSL SigVisualizer repeatedly crashes when It receive streamed EEG Inlet from 256ch EGI Amplifier. The program starts properly and visualize very short part of initial eeg signals from 256chs, than crash.

Traceback (most recent call last):

  File "/Users/User/Downloads/App-SigVisualizer-64fe663e88246c14fbd60b14eff84c228f5a85a6/paintwidget.py", line 216, in paintEvent

    -self.dataBuffer[0][ch_idx] + chan_offset)

OverflowError: argument 4 overflowed: value must be in the range -2147483648 to 2147483647

Abort trap: 6

OverflwError

As soon as i click on Update Stream, i get an error in paintwidget.py:

`
for ch_idx in range(n_chans):

     chan_offset = (ch_idx + 0.5) * self.channelHeight
         if self.lastY:
                if not math.isnan(self.lastY[ch_idx]) and not math.isnan(self.dataBuffer[0][ch_idx]):
                    painter.drawLine(x0 - self.px_per_samp,
                                     -self.lastY[ch_idx] + chan_offset,
                                     x0,
                                     -self.dataBuffer[0][ch_idx] + chan_offset)

`

in line in painter.drawLine(...)
OverflowError: argument 4 overflowed: value must be in the range -2147483648 to 2147483647

When debuging, values in dataBuffer are too large, but i cannot figure out why is that. Im not sending those kind of values on the stream.

Signal lines break

And this happens more if I add filters like below:

convert list to aray

x = np.array(self.dataBuffer).T

set up mean and scaling coef

`
if self.chunk_idx == 0 or self.mean.size == 0:
self.mean = np.mean(x, axis=1).reshape(-1, 1)
x2 = copy.deepcopy(x) - self.mean

data_range = (np.max(x2, axis=1) - np.min(x2, axis=1) + 0.0000000000001).reshape(-1, 1)
self.scaling = self.channelHeight * CHANNEL_Y_FILL / data_range
self.scaling = np.clip(self.scaling, 0.05, 1e8)

`

rescaling and minus mean

x = x - self.mean x = x * self.scaling

bandpass filter

nyq = 0.5 * 1024
low = 1 / nyq
high = 50 / nyq
order = 5
b, a = signal.butter(order, [low,high], btype='band')
x = signal.filtfilt(b, a, x, axis=1)`

turn back to list

`self.dataBuffer = list(x.T)

This is the signal after filtering:

If there is any question regarding the issue, please feel free to ask me.

Control panel on the left under construction

Currently the control panel on the left with checkboxes are not functional, yet. Ideally it should control which stream/channels are being streamed, and when checkbox is toggled, the changes should be reflected immediately.

list index out of range due to downsampling

Code here

for m in range(round(self.chunkSize/self.downSamplingFactor)):
    if m != round(self.chunkSize/self.downSamplingFactor):
        endIdx = (m+1) * self.downSamplingFactor
        buf = [chunk[n][k] for n in range(m * self.downSamplingFactor, endIdx)]
    else:
        buf = [chunk[n][k] for n in range(m * self.downSamplingFactor, len(chunk))]

When round rounds up, this goes out of range. e.g., I have a self.chunkSize of 655, self.downSamplingFactor of 16. 655 / 14 = 40.937. On the 41st iteration, m is 40 which != round(<>) so the first path is used with endIdx = 656; too big!

A simple solution would be to make endIdx = min((m+1) * self.downSamplingFactor, len(chunk)) and then the if-else block isn't needed.