Questions tagged [numpy-memmap]

An advanced numpy.memmap() utility to avoid RAM-size limit and reduce final RAM-footprint ( at a reasonable cost of O/S-cached fileIO mediated via a small-size in-RAM proxy-view window into whole array-data ) Creates and handles a memory-map to an array stored in a binary file on disk.

Creates and handles a memory-map to an array stored in a binary file on disk.

Memory-mapped files are used for arranging access to large non-in-RAM arrays via small proxy-segments of an O/S-cached area of otherwise unmanageably large data files.

Leaving most of the data on disk, without reading the entire file into RAM memory and working with data via smart, moving, O/S-cached window-view into the non-in-RAM big file, enables to escape from both O/S RAM-limits and from adverse side-effects of python's memory management painfull reluctance to release once allocated memory-blocks anytime before the python program termination.

numpy's memmap's are array-like objects.

This differs from Python's mmap module, which uses file-like objects.

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Numpy load part of *.npz file in mmap_mode

I know there already exists a similar question, which has not been answered. I have a very large numpy array saved in a npz file. I don't want it to be loaded completely (my RAM can't handle it entirely), but just want to load a part of it. This is…
wetrust
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Is there a maximum number of processes a numpy memmap can handle at a time?

I saw here that for multi-processing, that numpy memmaps should be used https://joblib.readthedocs.io/en/latest/parallel.html#working-with-numerical-data-in-shared-memory-memmapping As this problem can often occur in scientific computing with numpy…
SantoshGupta7
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how to put numpy array entirely on RAM using numpy memmap?

I would like to use a memmap allocated numpy array that can be processed in parallel using joblib i.e. shared memory between different processes. But I also want the big array to be stored entirely on RAM to avoid the write/read to disk that memmap…
danny
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How can I visualize a large file read in numpy memmap format?

I am trying to read czi format images, But because they need a lot of memmory I tried reading them in memmap file. Here is the code I used> import czifile as czi fileName = "Zimt3.czi" # read file to binary file = czi.CziFile(fileName) imageArr =…
Maryam S
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How does numpy.memmap work on HDF5 with multiple datasets?

I'm trying to memory-map individual datasets in an HDF5 file: import h5py import numpy as np import numpy.random as rdm n = int(1E+8) rdm.seed(70) dset01 = rdm.rand(n) dset02 = rdm.normal(0, 1, size=n).astype(np.float32) with h5py.File('foo.h5',…
Indominus
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Assigning values to list slices of large dense square matrices (Python)

I'm dealing with large dense square matrices of size NxN ~(100k x 100k) that are too large to fit into memory. After doing some research, I've found that most people handle large matrices by either using numpy's memap or the pytables package.…
matohak
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How to create shared memory objects with joblib on linux?

I am working through the joblib shared memory tutorial. It seems that numpy.memmap dumps data to disk, which is unfortunate. However, using ramfs it should be theoretically possible to share memory between joblib processes on a linux box. Is there…
Him
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Shuffling large memory-mapped numpy array

I have an array of dimension (20000000, 247) of size around 30 GB in a .npy file. I have 32 GB available memory. I need to shuffle the data along rows. I have opened the file in mmap_mode. However, if I try anything other than in-place modification,…
Sayandip Dutta
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Is there a way to load a numpy unicode array into a memmap?

I am trying to create an array of dtype='U' and saving that using numpy.save(), however, when trying to load the saved file into a numpy.memmap I get an error related to the size not being a multiple of 'U3' I am working with python 3.5.2. I have…
Kour
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Is it possible to create a numpy.memmap of array of arrays?

I have a (4,) arrays that I want to save to the disk (The sizes I am working with can not fit into memory so I need to dynamically load what I need). However, I want to have that in a single numpy.memmap. Not sure if it is possible but any…
Kour
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In python, how does GC handle mmap?

I am writing a multiprocessing system in python. One of the child processes is in charge of reading frames from a camera stream using cv2 and pass that frame along to another child process for some manipulation and previewing. The problem is that in…
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Getting the index of the next element in a very large memmap which satisfies a condition

I have a memmap to a very large (10-100 GB) file containing current and voltage data. From a given starting index, I want to find the index of the next point for which the voltage satisfies a given condition. In the case of a relatively small list…
KBriggs
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Using Numpy Memmap to Read In Certain Rows or Columns

I just wanted to ask if it was possible to store a numpy array as a .npy file and then use memmap to look through it at certain rows/columns?
ajl123
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Delete numpy 2D memmap array if sum equals 0

I am using a numpy memmap object that acts as a 2D array: In [8]: data_2d.shape Out[8]: (16777216, 50) What is the best way to delete a row in which the sum of that row is zero?
SabCo
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NumPy memmap performance issues

I have a large (75000 x 5 x 6000) 3D array stored as a NumPy memory map. If I simply iterate over the first dimension like so: import numpy as np import time a = np.memmap(r"S:\bin\Preprocessed\mtb.dat", dtype='float32', mode='r', shape=(75000, 5,…
triphook
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