How to copy unmanaged array (python list/tuple or numpy array) into managed C# array? I guess using Marshal.Copy, but can anyone point to example?
Thanks, Denis On Thu, Oct 30, 2014 at 12:19 PM, Nikhil Garg <nikhilgarg....@gmail.com> wrote: > Thanks Brad and Jeff for the detailed info. For now, fromiter is serving > me well and has reduced my processing time considerably, so I am just going > to stick with it. > > > On 29 October 2014 11:04, Jeffrey Bush <j...@coderforlife.com> wrote: > >> I finally have a chance to chime in, and Bradley is exactly right. >> Marshall.Copy copies the raw data, and apparently your file library does >> not store that data in a nice, contiguous, manner. While it is highly >> likely that copying all the data to an array in C# will be faster than the >> fromiter in Python, I am unsure if copying all the data to an array in C# >> then copying all the data again to a numpy array will be faster than >> fromiter (cause you have to copy it twice). The exception is if the file >> library has a function like ToArray that is optimized to copy the data to a >> linear chunk of data. So, what type is "Data"? >> >> Another factor is how long the chunk of data you are copying is. You say >> the last axis is only 400 elements long. Check out my code and you will see >> that at 400 elements long, fromiter is actually the fastest (at least when >> I tried). An example run: >> >> Copy using for loop in 0.000884 sec >> Copy using fromiter in 0.000144 sec # fastest >> Copy using fromstring in 0.001460 sec # fairly slow, 10.3x slower than >> fromiter >> Copy using Marshal.Copy in 0.001680 sec # slowest, 11.7x slower than >> fromiter >> >> I start to do better with Marshal.Copy then fromiter around 5000 elements >> copied. This is because the overhead of the mass copies is high but adding >> each element doesn't take much time. fromstring has a lower overhead but >> slightly longer per-element time (fromstring is better than Marshal.Copy >> until ~200,000 elements). >> >> So you might be doing as good as you can possibly do. If I knew more >> about your file format library I might be able to provide more insight. >> >> Jeff >> >> On Tue, Oct 28, 2014 at 2:45 PM, Bradley Friedman <b...@fie.us> wrote: >> >>> Well it makes sense to me that doing it via an iterator, and element at >>> a time, would be slow. There’s a lot of call overhead associated with each >>> iteration step. Whether it’s done in .net, or in python, or a call from >>> one to the other, it will be slow. It’s still a call where you’d be better >>> off copying whole buffers. >>> >>> Ideally you’d pull the data into as simple and raw a data structure as >>> you can on the dotnet side, in a buffered manner. Then you’d execute a >>> movement of the data across, a reasonably sized chunk of buffer at a time. >>> This will reduce call overhead and also allow read-ahead caching to do its >>> thing on the file-access side of things. >>> >>> Your suggestion of loading into a .net array and then moving that array >>> over, makes sense. But I think it comes down to what you can do with the >>> third party file-format library. If its not going to provide you with the >>> data as some kind of buffer with a cohesive and known format in memory, >>> you’re not really going to be able to move it over without iterating over >>> it and reformatting it at some point. >>> >>> Specifically, I’d point to Jeffery’s original caveat: >>> >>> "but does involve a number of assumptions (for example that the data in >>> the two arrays are laid out in the same way)." >>> >>> The question is: is there a way to get the data off of disk and in >>> memory from dotnet library, where its layout in memory is known, and >>> something you want exactly as it is, but in python? If so, you should be >>> able to use the methods from the afore linked thread. If not, you’re >>> probably stuck iterating somewhere to reformat it, no matter what. Which >>> is probably why you got garbage back. I’m guessing the object returned >>> from the dotnet file-format-library isn’t laid out right, as suggested in >>> the afore referenced caveat. >>> >>> >>> > On Oct 28, 2014, at 9:55 AM, Nikhil <nikhilgarg....@gmail.com> wrote: >>> > >>> > Hello, >>> > Yeah, I read data from a file say at each node and each time step, but >>> when i try to use Marshal approach i get gibberish but when i use simple >>> iter i get correct values. i have been trying the approach used in example >>> in the previous post and that example makes sense but it doesnt make sense >>> when i use it in my case. I am right now assigning it to a variable, i am >>> now thinking of exploring the possibility of saving data to a dot net array >>> maybe using System.Array and saving data to it but not sure if that even >>> make sense. >>> > >>> > Sent from my iPhone >>> >>> _________________________________________________ >>> Python.NET mailing list - PythonDotNet@python.org >>> https://mail.python.org/mailman/listinfo/pythondotnet >>> >> >> >> _________________________________________________ >> Python.NET mailing list - PythonDotNet@python.org >> https://mail.python.org/mailman/listinfo/pythondotnet >> > > > > -- > Regards > > Nikhil > > ------------------------------------------------------------------- > Big whirls have little whirls, > Which feed on their velocity, > And little whirls have lesser whirls, > And so on to viscosity > (Richardson, 1922) > > _________________________________________________ > Python.NET mailing list - PythonDotNet@python.org > https://mail.python.org/mailman/listinfo/pythondotnet >
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