Time base / Realtime display Issues

[Falizar]

I am running a layout with no hardware and the simulation is taking 5X longer than it should.  But when I graph the output it shows the correct output!  Is there a trick to setting up the time base?

[CJ_Butler__DASYLab_Pro]

No trick that I can think of. Without looking at the worksheet, I can't provide any advice. Can you post the worksheet that is going slow? 

Things to look at -- sample rate/block size ratio -- if the block size is larger than the sample rate, then it will take at least the time that it takes to fill the block for the data to be displayed. 

[Falizar]

The setup I think is irrelevant.  I have Timebase Setup @ 1 kHz with a block length of 10 and Measurement Setup @ 1kHz with a block length of 1 and this seems to work.  When I alter the Time base setup, particularly the block length, it completely changes the way the program behaves real time, meaning it takes a long time for a 2 second acqusition to happen.

[CJ_Butler__DASYLab_Pro · Accepted solution]

Setup is completely relevant.

Sample rate 1000 and block size 1 is going to bog down the software to the point where it gets behind. Because there is no hardware, you're not getting a driver error... but you would. In this case, it's just working really really hard. The timestamp is based on how the data generator module time stamps it.

1000 and 10 is almost as bad.

I would really want to see the worksheet... there are modules, such as the Average module, which may need to adjust the block size down.

[Falizar]

I see what you mean. 

I was worried I could not get 1mS resolution without the low block sizes, but I see I am mistaken when looking at the data file afterwards!  Changing the block sizes to 100 did wonders! 

[CJ_Butler__DASYLab_Pro]

We recommend a sample rate block size ratio of 10:1 or less. The default is 2:1, rounded to a power of 2.

Blocks are just a way for DASYLab to manage data -- it maintains the sample rate and timestamp, but it's more efficient to handle bigger chunks of data than each sample individually.