Numpy Zeros Memory Error
Contents |
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 more about hiring developers or posting ads with us Stack Overflow Questions
Numpy Asarray Memory Error
Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a python numpy memory error community of 6.2 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Numpy memory error creating huge matrix up memoryerror python vote 2 down vote favorite 3 I am using numpy and trying to create a huge matrix. While doing this, I receive a memory error Because the matrix is not important, I will just show the way how to easily reproduce the error. a
Numpy Very Large Arrays
= 10000000000 data = np.array([float('nan')] * a) not surprisingly, this throws me MemoryError There are two things I would like to tell: I really need to create and to use a big matrix I think I have enough RAM to handle this matrix (I have 24 Gb or RAM) Is there an easy way to handle big matrices in numpy? Just to be on the safe side, I previously read these posts (which sounds similar): Python Numpy Very Large Matrices Python/Numpy MemoryError Processing a very very big data
Python Huge Matrix
set in python - memory error P.S. apparently I have some problems with multiplication and division of numbers, which made me think that I have enough memory. So I think it is time for me to go to sleep, review math and may be to buy some memory. May be during this time some genius might come up with idea how to actually create this matrix using only 24 Gb of Ram. Why I need this big matrix I am not going to do any manipulations with this matrix. All I need to do with it is to save it into pytables. python memory numpy share|improve this question edited Sep 30 '13 at 1:18 asked Sep 30 '13 at 0:53 Salvador Dali 50.3k40232310 2 How do you expect to fit 10 billion floats in 24 GB? If a float were 2.4 bytes, and 100% of your RAM were devoted to holding this array - sure ;-) –Tim Peters Sep 30 '13 at 0:56 What do you need to do with this matrix? That might give an insight to a workaround. –Rohit Sep 30 '13 at 1:14 cant you save it piece by piece? n work on partitions of your data? –usethedeathstar Sep 30 '13 at 7:20 Also, The way you create it first creates a python list of that size. Now the float is always the same object, but the list itself will have the same size as the resulting array (pointer is 8 bytes and double is 8 bytes). So use np.empty plus np.fill to create
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 python memory error increase memory Learn more about Stack Overflow the company Business Learn more about hiring developers or
Numpy Sparse Matrix
posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow numpy memmap Community Stack Overflow is a community of 6.2 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up MemoryError when creating a very large numpy array up http://stackoverflow.com/questions/19085012/numpy-memory-error-creating-huge-matrix vote 4 down vote favorite I'm trying to create a very large numpy array of zeros and then copy values from another array into the large array of zeros. I am using Pycharm and I keep getting: MemoryError even when I try and only create the array. Here is how I've tried to create the array of zeros: import numpy as np last_array = np.zeros((211148,211148)) I've tried http://stackoverflow.com/questions/37213750/memoryerror-when-creating-a-very-large-numpy-array increasing the memory heap in Pycharm from 750m to 1024m as per this question: http://superuser.com/questions/919204/how-can-i-increase-the-memory-heap-in-pycharm, but that doesn't seem to help. Let me know if you'd like any further clarification. Thanks! python arrays numpy share|improve this question asked May 13 at 15:20 Andrew Earl 716 10 You have created an array that is over 100GB in size, assuming the size of int is 4 bytes –smac89 May 13 at 15:22 Oh lord, I had no idea. That is terrifying. It is a very sparse array though. Is there any way to create an empty array with values in certain positions, such as: last_array[211148][9] but everywhere else would be empty? –Andrew Earl May 13 at 15:28 This may be helpful: stackoverflow.com/questions/1857780/… –Keozon May 13 at 15:35 3 Or the scipy.sparse module... –schwobaseggl May 13 at 15:37 It depends on what you are trying to do, but in this case it will be really impossible to create an array that big unless you have the memory for it. In graph problems, we sacrifice speed by making use of an adjacency list. –smac89 May 13 at 15:37 | show 1 more comment 1 Answer 1 a
Sign in Pricing Blog Support Search GitHub This repository Watch 247 Star 3,463 Fork 1,755 numpy/numpy Code Issues 1,170 Pull requests https://github.com/numpy/numpy/issues/7819 152 Projects 0 Wiki Pulse Graphs New issue numpy.zeros((0, 2**31-1)) raises MemoryError #7819 Closed cgohlke opened this Issue Jul 10, 2016 · 11 comments Projects None yet http://codereview.stackexchange.com/questions/41316/python-numpy-optimize-module-to-handle-big-file Labels 11 - Bug component: numpy.core Milestone No milestone Assignees No one assigned 4 participants cgohlke commented Jul 10, 2016 Using numpy-1.11.1 with the patch for issue memory error #7813 on 64-bit Python, creating an array of size=0 several times raises MemoryError on a Windows 10 system with 32 GB RAM: Python 2.7.12 (v2.7.12:d33e0cf91556, Jun 27 2016, 15:24:40) [MSC v.1500 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy >>> a = numpy.zeros((0, 2**31-1)) >>> a.size 0 >>> numpy zeros memory a = numpy.zeros((0, 2**31-1)) >>> a = numpy.zeros((0, 2**31-1)) Traceback (most recent call last): File "
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 more about hiring developers or posting ads with us Code Review Questions Tags Users Badges Unanswered Ask Question _ Code Review Stack Exchange is a question and answer site for peer programmer code reviews. Join them; 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 Python, numpy, optimize module to handle big file up vote 7 down vote favorite 2 With the help of some people here and there, I wrote the module below which works very well if the file targets.csv is not too big. As soon as this file exceeds 100 MB, a MemoryError is returned. The problem is that I used numpy to make the computations faster (and they became really fast compared to the previous versions of this module), and I think numpy requires to load the entire file into memory. However, there should be a way to handle the MemoryError that happens there: targets = np.array([(float(X), float(Y), float(Z)) for X, Y, Z in csv.reader(open('targets.csv'))]) Any ideas? Let me know if you need more details (files, etc.) import csv import numpy as np import scipy.spatial import cv2 import random """loading files""" points = np.array([(int(R), int(G), int(B), float(X), float(Y), float(Z)) for R, G, B, X, Y, Z in csv.reader(open('colorlist.csv'))]) # load X,Y,Z coordinates of 'points' in a np.array print "colorlist loaded" targets = np.array([(float(X), float(Y), float(Z)) for X, Y, Z in csv.reader(open('targets.csv'))]) # load the XYZ target values in a np.array print "targets loaded" img = cv2.imread("MAP.tif", -1) height, width = img.shape total = height * width # load dimensions of tif image print "MAP loaded" ppm = file("walladrien.ppm", 'w') ppm.write("P3" + "\n" + str(height) + " " + str(width) +"\n" + "255" + "\n") # write PPM file header """doing geometry""" tri = scipy.spatial.Delaunay(points[:,[3,4,5]], furthest_site=False) # True makes an almost BW picture # Delaun