 We had this plus complication. Just run it now. This is a simulated EEG. This is a simulated EEG. I'm trying to do fuzzy logic analysis. It will be away from the detector meant to have this scroller. So the idea is that you have this baseline EEG. Yeah, the temperature looks legit. Go about 0.3 plus minus 0.3 and then you will have a big EMG artifact every now and then. And we should have the fuzzy logic being able ideally to detect it. So I'll say what's the probability of EMG in the signal is based on these parameters. So we're designing a Flask application. So the Flask application, we have some, we already did a couple of sessions on it together. And we already have some code. We have a HTML file, a JavaScript file, a Python file, that is the Flask application, and a CSS file as well. Okay, the couple of issues. There are couple of issues with the code. Can we make sure the scroller actually works? Because currently, the whole waveform is shown. Well, this one did something. It made the window of the chart smaller, but it's still displaying the whole data. So I'm not able to actually scroll through it. Okay, this works better. Now, we also would like, can we double check that we actually generating the EMG artifact, the chewing artifacts? And because later we want to have them in the data while scrolling through. So essentially, we'll need this, we'll need to generate a longer data set with the EMG bits embedded into it. So we can scroll through. And later for the fuzzy logic algorithm to mark to give a percent likelihood for EMG in the signal. Okay, I tried this code. It seems, is it all EMG now? And there seem to be no baseline EEG in the data. We need to correct this. Also, can we make sure the window of the chart remains the same size and fits into the window on the front panel? Okay, this is better now, but the EEG looked better before. It looked more realistic before the last update of the code. The EMG, a periodic EMG in the code in the data looks great. So we have begin at zero at false settings for the ticks, which is scales, a few scales. Why can zero false? And we have these ticks. All right, we need a coma. And no, that didn't come on. It's not about the ticks, it's about, about, and now it's even worse. I don't see any of the data on the chart. Is it about the ticks or the auto scaling of the whole window? Okay, we need to redo this chart. The chart, there's a lot of problems with it. Can you, can you regenerate that bit of the code? Yep, understood. Let's rebuild the chart configuration with a focus on ensuring proper visibility and auto scaling of the data, particularly on the Y axis. I'll provide a revised version of your chart setup in JavaScript that should help address these issues. Key adjustments. Canvas width. The canvas width is set dynamically based on the data length. This is crucial for the horizontal scroll bar to work correctly. Chart type, type, line is appropriate for EEG data visualization. Y axis auto scaling, the Y axis is configured to automatically adjust its range based on the data. The begin at zero is set to false to allow the chart to scale based on the data values. Autoskip, max ticks limit, and autoskip padding are set to ensure that the axis labels are readable and not overcrowded. X axis configuration, adjust the X axis settings as per your data's time scale. Responsive and aspect ratio, set to false to disable automatic resizing. This setup should provide a more reliable and clear visualization of your EEG data. If the data is still not displaying correctly, it may be necessary to check the format and range of the data being passed to a chart. Please test this configuration and let me know how it goes. If there are still issues, we can explore further adjustments. Yeah, we definitely need to explore more adjustments. It still doesn't work well. There are also issues with the axis not being visible. The data being outside the visible range on the Y axis and also the EEG signal label text is moving with the scroller, whereas I'm expecting it to be stationary in one place. Yep. Yep. To address the issues you're facing with the EEG chart, let's refine the chart configuration further. The main objectives will be ensuring that both the X and Y axes are correctly scaled and visible, keeping the EEG signal label stationary while allowing the data to scroll, properly fitting the data within the visible range of the chart. Here's a more detailed approach. Y axis autoscaling, we need to ensure the Y axis scales correctly to fit the data. If the data goes outside the visible range, it suggests the autoscaling isn't functioning as expected. We can try a different scaling strategy. X axis configuration, if the X axis is invisible, it may be due to the canvas size or the chart configuration. To keep the label stationary, you can use a separate element in your HTML for the label, positioned outside the scrolling container of the chart. Data check, ensure the data passed to the chart is in the correct format and range. Canvas size, verify that the canvas size matches the amount of data you're plotting. Browser rendering, sometimes issues can arise due to how different browsers render content. It might be worth testing in different browsers. Test this setup and let's see if it resolves the issues. If problems persist, we may need to delve deeper into specific aspects of your implementation or consider alternative charting solutions. It's always easy to blame the browser rendering. I do not want the label outside the chart. As it is, it's okay. I just expected not to move, always be in the same position within the chart. We make sure the waveform, the data is centered within the chart is centered on the Y axis. Yep. To keep the EEG signal label stationary within the chart and ensure the waveform data is centered on the Y axis, we need to adjust the chart configuration. The goal is to modify the chart's Y axis scaling and the placement of the label. Let's tackle these issues. To center the waveform, we need to adjust the Y axis range so that it dynamically fits the range of your data. We'll calculate the maximum and minimum values of your data and set the Y axis limits accordingly. To keep the label stationary, we can use a plugin in chart. JS though allows us to draw custom text on the canvas. This way, the label remains in a fixed position within the chart area. Here's how you can implement these changes. The Y axis is dynamically scaled based on the data's range. Custom annotation, static label, is added using chart. JS is annotation plugin. You might need to include this plugin if it's not already part of your chart, JS bundle. The label remains stationary within the chart. This configuration should center your waveform data on the Y axis and keep the EEG signal label fixed within the chart. Please test this setup. And if there are any further adjustments or issues, let me know. And no, I do not see the label anymore. And also the data is not centered. I expect the signal, the waveform, the data waveform to be centered around zero and also zero to be the center of the chart in terms of the Y axis. Can we update the CSS code as well? The waveform is still not centered and the label is not in a fixed position. In a different browser. Yes, pretty annoying. It's different in terms of the scroller, but it displays the same. The waveform is still below the visible area of the chart. The waveform is still below the visible area of the chart. Nothing works. We need to adjust anything else as well for this to work. It's the current CSS that I have. Can we keep using the color palette for the project everywhere? Not use any other colors. Also, I'm still having the same problem where the signal is not centered in the middle of the chart. When I remove the EEG chart container code from the CSS, it is working okay. So that's probably going to be redone. Okay, it's working better now, but the chart is too high and it doesn't fit the current window. How do we fix that? Okay, adding this bit seem to have made the trick and it's not working much better. Fantastic. I'm glad to hear that adjusting the maximum height for the chart did the trick and that it's now working better for you. It's a bit odd that it has this sinusoid. It regards the EEG data. It's a bit odd that it has a sinusoid as a baseline EEG. It doesn't look realistic. Here are a few suggestions to improve the realism of the generated EEG data. Baseline oscillations. Ensure the baseline EEG oscillations reflect realistic brainwave frequencies, like alpha waves around 8 to 12 hertz, beta waves around 12 to 30 hertz, etc. The amplitude and frequency should be within realistic ranges. Noise and artifacts. Really EEG data often contains noise and artifacts that are not perfectly periodic or uniform. Consider introducing random noise and varying the artifact patterns to more closely mimic real-world signals. Signal complexity. Really EEG signals are not just a single frequency sine wave. There are mix of several oscillations from different brain regions. You could layer multiple sine waves of different frequencies and amplitudes to simulate this complexity. Use recorded data. If possible, consider using segments of real EEG data as your baseline. This data can sometimes be obtained from open source datasets if you do not have access to actual EEG recordings. Here is an example modification to the data generation code that introduces more randomness to the signal. In this example, the generated EEG signal is a mixture of alpha and beta waves, with some Gaussian noise added to simulate a more realistic EEG signal. Remember, the key to realism in synthetic data is complexity and variability. Try tweaking the parameters and layers of your signal until it visually resembles the complexity of a real EEG waveform.