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 > On 28 Oct 2014, at 12:50 am, Bradley Friedman <b...@fie.us> wrote: > > You indicate that you are reading from a file. The thread you reference was > about copying data in memory. I’d think matters of buffering and read-ahead > caches would be far more relevant than anything else. Am I missing something? > >> On Oct 26, 2014, at 5:18 AM, Nikhil Garg <nikhilgarg....@gmail.com> wrote: >> >> >> Hi, >> >> I have looked at the following thread to copy a c# array to numpy list using >> python dot net. >> >> https://mail.python.org/pipermail/pythondotnet/2014-May/001525.html >> >> When I try the methods mentioned in the complete thread I manage to get the >> array from simple iteration method or >> np.fromiter, but I have not been able to make GCHandle or Marshal.Copy work >> for my case. >> >> To explain about my issue, I use a computer code written in c# which >> produces output in a custom build format. I am able to access the data from >> the file system using python dot net, but it seems that it take almost half >> an hour to get the data from the file. >> >> For example my file has an array of size 5018x73x400, if i use fromiter, i >> provide the last bit of array to copy to python due to the way file stores >> output. >> >> for j in xrange(num_nodes-1): >> for i in xrange(nsteps): >> temp = file_in.ReadItemTimeStep(j+1,i).Data >> temp_1 = np.fromiter(temp, float) >> dest[j, i] = temp_1 >> >> Other way of doing same task would be to use a for loop but tht would be >> really slow. >> >> for k in xrange(num_nodes-1): >> for k in xrange(nsteps): >> for i in xrange(nvals): >> temp[k,j,i] = file_in.ReadItemTimeStep(k+1, j).Data[i] >> >> I am trying to find a faster way to extract the data from the file. I was >> wondering if there is a possibility to use something like GChandle or >> Marshal.Copy. I have also attached same output from Marshal.Copy >> >> Marshal.Copy(temp, 0, >> IntPtr.__overloads__[int](temp2.__array_interface__['data'][0]), len(temp)) >> >> >> 0.00000000e+000, 0.00000000e+000, 0.00000000e+000, >> 0.00000000e+000, 3.13551399e-242, 4.20993645e-161, >> 8.71245319e-119, 8.38370432e-089, 2.60762781e-075, >> 1.92616374e-072, 2.89006184e-072, 3.06007265e-082, >> 3.81879776e-315, 0.00000000e+000, 0.00000000e+000, >> 0.00000000e+000, 1.03959661e-297, 7.22038448e-196, >> 3.05237954e-130, 2.58469346e-093, 2.29495911e-070, >> 3.74354820e-062, 1.74288060e-061, 2.13172553e-067, >> 2.74305386e-077, 0.00000000e+000, 0.00000000e+000, >> 0.00000000e+000, 0.00000000e+000, 1.02484756e-240, >> 1.70193770e-154, 1.30625320e-108, 1.16793762e-075, >> 2.96889340e-061, 7.84687103e-058, 1.16879604e-057, >> 5.56256478e-068, 4.06437857e-315, 0.00000000e+000, >> 0.00000000e+000, 0.00000000e+000, 1.11705239e-296, >> 1.46978156e-194, 1.98034372e-128, 3.79615170e-091, >> 5.88936509e-068, 1.85305929e-059, 2.16186001e-058, >> >> Whereas the actual values stored in the array are >> 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, >> 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, >> 0.00000000e+00, 0.00000000e+00, 5.66641200e-37, >> 1.24961600e-30, 5.34846800e-25, 1.72519600e-20, >> 1.49402200e-17, 3.27685300e-15, 4.10687500e-13, >> 1.87978200e-11, 2.01397900e-10, 8.83561100e-10, >> 2.14397600e-09, 2.02600300e-09, 2.47599800e-09, >> 2.15987100e-09, 4.82694100e-10, 1.18759300e-10, >> 3.32024100e-11, 0.00000000e+00, 0.00000000e+00, >> 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, >> 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, >> 1.45288600e-37, 7.37245900e-31, 7.59282500e-25, >> 5.85463400e-20, 1.20634700e-16, 3.06414300e-14, >> 5.16041300e-12, 2.87562800e-10, 3.62841500e-09, >> 1.63540600e-08, 4.06988300e-08, 3.97764200e-08, >> 4.88768500e-08, 4.07385000e-08, 8.78868600e-09, >> >> I would appreciate any help i can get regarding this matter. >> >> Nikhil >> _________________________________________________ >> 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
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