Numpy Memory Error
Contents |
here for a quick overview of the site Help Center Detailed answers to any questions you might have numpy memory error zeros Meta Discuss the workings and policies of this site About Us
How To Solve Memory Error In Python
Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with python memory error increase memory us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 6.2 million programmers, memory error pandas just like you, helping each other. Join them; it only takes a minute: Sign up Python/Numpy MemoryError up vote 10 down vote favorite 7 Basically, I am getting a memory error in python when trying to perform an algebraic operation on a numpy matrix. The variable u, is a large matrix of double (in the failing
Memoryerror Python
case its a 288x288x156 matrix of doubles. I only get this error in this huge case, but I am able to do this on other large matrices, just not this big). Here is the Python error: Traceback (most recent call last): File "S:\3D_Simulation_Data\Patient SPM Segmentation\20 pc t perim erosion flattop\SwSim.py", line 121, in __init__ self.mainSimLoop() File "S:\3D_Simulation_Data\Patient SPM Segmentation\20 pc t perim erosion flattop\SwSim.py", line 309, in mainSimLoop u = solver.solve_cg(u,b,tensors,param,fdHold,resid) # Solve the left hand si de of the equation Au=b with conjugate gradient method to approximate u File "S:\3D_Simulation_Data\Patient SPM Segmentation\20 pc t perim erosion flattop\conjugate_getb.py", line 47, in solv e_cg u = u + alpha*p MemoryError u = u + alpha*p is the line of code that fails. alpha is just a double, while u and r are the large matrices described above (both of the same size). I don't know that much about memory errors especially in Python. Any insight/tips into solving this would be very appreciated! Thanks python memory numpy sci
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn python sparse more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags gc.collect python Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 6.2 million programmers, just like you,
Python Clear Memory
helping each other. Join them; it only takes a minute: Sign up Numpy memory error up vote 0 down vote favorite I'm running into a memory error issue with numpy. The following line of code seems to be http://stackoverflow.com/questions/4318615/python-numpy-memoryerror the issue: self.D_r = numpy.diag(1/numpy.sqrt(self.r)) Where self.r is a relatively small numpy array. The interesting thing is I monitored the memory usage and the process took up at most 3% of the RAM on the machine. So I'm thinking there's something that is killing the script before all the RAM is taken up because there is an expectation that the process will do so. If anybody has any ideas I would be very grateful. Edit 1: http://stackoverflow.com/questions/36162662/numpy-memory-error Here's the traceback: Traceback (most recent call last): File "/path_to_file/my_script.py", line 82, in
Badges sign up log in tour help Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have http://gis.stackexchange.com/questions/191237/memory-error-in-python-when-reclassifying-array Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us http://numpy-discussion.10968.n7.nabble.com/Huge-arrays-td25254.html Geographic Information Systems Questions Tags Users Badges Unanswered Ask Question _ Geographic Information Systems Stack Exchange is a question and answer site for cartographers, geographers and GIS professionals. Join them; memory error it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top Memory error in python when reclassifying array up vote 3 down vote favorite I have a .tif that I read into an array (call it tifArray), and I would numpy memory error like to classify the array based on set of conditions: Where 1200 <= tifArray <= 4000, outputArray = 1 Where tifArray < 1200, outputArray = 2 Where tifArrary > 4000, outputArray = 3 I've tried both creating a new array (preferred) and replacing the values in place (see below) but I regardless I get a MemoryError. I've tried on machines that have 10 and 8 GB of free RAM. I've also tried using the np.where function and just plain indexing (below). I have no clue why I'm getting a memory error, and I don't think I should be running into that problem. Some information about tifArray: tifArray.shape = (55500, 55500) tifArray.dtype = uint16 And here is one method I tried: threshold_low = 1200 threshold_high = 4000 tifArray[(tifArray >= threshold_low) & (tifArray <= threshold_high)] = 1 tifArray[(tifArray < threshold_low)] = 2 tifArray[(tifArray > threshold_high)] = 3 The error: File "./classify_segmented_fromAmplitude.py", line 90, in process_tile tifArray[(tifArray >= threshold_low) & (tifArray <= threshold_high)] = 1 MemoryError When I comment out the first condition: tifArray[(tifArray >= threshold_low) & (tif
Inappropriate ♦ ♦ Huge arrays Hi, I have a numpy newbie question. I want to store a huge amount of data in an array. This data come from a measurement setup and I want to write them to disk later since there is nearly no time for this during the measurement. To put some numbers up: I have 2*256*2000000 int16 numbers which I want to store. I tried data1 = numpy.zeros((256,2000000),dtype=int16) data2 = numpy.zeros((256,2000000),dtype=int16) This works for the first array data1. However, it returns with a memory error for array data2. I have read somewhere that there is a 2GB limit for numpy arrays on a 32 bit machine but shouldn't I still be below that? I use Windows XP Pro 32 bit with 3GB of RAM. If someone has an idea to help me I would be very glad. Thanks in advance. Daniel _______________________________________________ NumPy-Discussion mailing list [hidden email] http://mail.scipy.org/mailman/listinfo/numpy-discussion David Cournapeau Reply | Threaded Open this post in threaded view ♦ ♦ | Report Content as Inappropriate ♦ ♦ Re: Huge arrays On Wed, Sep 9, 2009 at 9:30 AM, Daniel Platz<[hidden email]> wrote: > Hi, > > I have a numpy newbie question. I want to store a huge amount of data > in an array. This data come from a measurement setup and I want to > write them to disk later since there is nearly no time for this during > the measurement. To put some numbers up: I have 2*256*2000000 int16 > numbers which I want to store. I tried > > data1 = numpy.zeros((256,2000000),dtype=int16) > data2 = numpy.zeros((256,2000000),dtype=int16) > > This works for the first array data1. However, it returns with a > memory error for array data2. I have read somewhere that there is a > 2GB limit for numpy arrays on a 32 bit machine This has nothing to do with numpy per se - that's the fundamental limitation of 32 bits architectures. Each of your array is 1024 Mb, so you won't be able to create two of them. The 2Gb limit is a theoretical upper limit, and in practice, it will always be lower, if only because python itself needs some memory. There is also the memory fragmentation problem, which means allocating one contiguous, almost 2Gb segment will be difficult. > If someone has an idea to help me I would be very glad. If you really need to deal with arrays that big, you should move on 64 bits architecture. That's exactly the problem they are solving. cheers, David _______________________________________________ NumPy-Discussion mailing list [hidden email] http://mail.scipy.org/mailman/listinfo/numpy-discussion Charles R Harris Rep