05-12-2019 10:48 PM
Hello, sorry for the question that may be a silly one for experts. Actually i am reading a text file consisting of several columns and more than 200 thousand rows. I have to plot this data as XY plot. But when i plot the data, the system becomes very slow and i to wait for further actions when i analyse the plot. Is there any way to overcome this issue?
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05-13-2019 12:24 AM
There really aren't enough pixels on your xy graph to reasonably show all that data, meaning your approach is bad. I would use an intensity graph and map the data into the pixels at a reasonable resolution and fixed number of grid points.
How does the data look like? What kind of interpolation are you using? What is the datatype of the xy graph? Can you give a simplified example and data?
05-13-2019 04:03 AM
Thank you for your reply. i would like to post my VI and the sample text file.
05-13-2019 04:24 AM - edited 05-13-2019 04:25 AM
Hi Hussam,
Like this:
Now LabVIEW is still "usable" even when displaying your data…
05-13-2019 11:28 AM
Sorry, I just had a change to look at your VI right now and I am truly horrified.
Can we take a step back and try to figure out what you are actually trying to show and what's interesting in that dataset. Decimation as suggested by others is a lossy operation so I am not sure it is appropriate, but it is also definitely not appropriate to push way more data that ever can be seen into an xy graph.
So I recommend a little more thinking for the entire thing. See how far you get. Most data seems quite constant over time and is mostly noise.
05-13-2019 10:54 PM
Hi, thank you for your kind response. I have skipped first rows and last rows but still have the issue when i plotting the all the data, the program becomes slow. can you share this sample VI?
05-13-2019 11:28 PM
Hi, thank you for your detailed reply,
05-15-2019 10:05 AM
Can you define what "becomes stable" means? What is the "instability" and how do you recognize it? How many points are typically involved in the "instability"? You have so much data that a few outliers won't really hurt any mean/SD, and if they do, you can just ignore them based on some criteria.
If you are just looking in a drift of a rolling mean, you can massively reduce the data to be plotted. You probably could even detect it automatically, without any need to plot anything. It's just data analysis. So what is the plot for?
05-16-2019 12:13 AM
The data varies with time, specially in column 7 which is temperature data. At certain time the temperature becomes constant. Till that point or time i have to ignore the first data.
Next i have to find the mean and standard deviation of usable data and then have to find the allan variance plot too.
Allan varian plot program is not yet available. I have to make too.