But up to now, I don't find any example about it(Google or NI forum, maybe it's primary). The people of NI forum advice that I should put AO0 and AO1 into one FPGA/IO node and use SCTL. And in "FPGA 2-Test DO and AO.vi", it has same problem. Such as, t1, t2, t3, t4, with disired output A1, A2, A3, A4.
![labview python labview python](https://i.ytimg.com/vi/dDzyNCUv-SM/maxresdefault.jpg)
In "FPGA 1-Test DO and AO.vi", I find that the loop timer helps me to realize accurate time interval, however, it ignore the first time interval. I can't explain that it can realize time interval below 134us, even I acturally realize a delay of 10us, but the input is not acturally 10us, so it's not accurate.Ģ. And to complete once of while loop, it needs 134us. But in "FPGA 0-Test DO.vi", it can't not realize specific time interval by several us's error(maybe large). To realize the specific time interval, I can use Wait and Loop timer. I search in Google, NI forum, and decide to use for loop and loop timer in FPGA.ġ. I want to realize that, for example, with time sequence t1, t2, t3, t4, DO outputs T, F, T, F, AO1 outputs A1, A2, A3, A4, AO2 outputs B1, B2, B3, B4, and the delay of AO1 and AO2 should as small as possible(AO1 and AO2 may comes from difference modules). I attach my test project for explanation. I'm a beginner in labview, and now test cRIO about two weeks.
LABVIEW PYTHON FOR FREE
Sources are available now on our GitHub for free :
LABVIEW PYTHON FULL
HAIBAL will propose more than 100 different layers, 22 initialisators, 15 activation type, 7 optimizors, 17 looses.Īs we like AI Facebook and Google products, we will of course make HAIBAL natively full compatible with PyTorch and Keras.
![labview python labview python](https://lavag.org/uploads/monthly_11_2013/post-46289-0-00127800-1384474802_thumb.png)
It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy from the famous scikit-learn Python library.Ĭoming soon, our team is working on the « HAIBAL Project », deep learning library written in native LabVIEW, full compatible CUDA and NI FPGA.īut why deprive ourselves of the power of ALL the FPGA boards ? No reason, that's why we are working on our own compilator to make HAIBAL full compatible with all Xilinx and Intel Altera FPGA boards. LabVIEW developer can now use our library for free as simple and efficient tools for predictive data analysis, accessible to everybody, and reusable in various contexts. TDF team is proud to propose for free download the scikit-learn library adapted for LabVIEW in open source.