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From: Tony Yu <ts...@gm...> - 2012-05-23 16:28:33
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On Wed, May 23, 2012 at 9:04 AM, Sergi Pons Freixes <spo...@gm...>wrote: > On Wed, May 23, 2012 at 11:00 AM, Guillaume Gay > <gui...@mi...> wrote: > > Hello > > > > > > What is the size of a single image file? If they are very big, it is > > better to do everything from processing to ploting at once for each file. > > As stated below, each image is single-channel, of 4600x3840 pixels. As > you can see on the code, there is not much processing, just loading > the images and plotting them. What it's slow is not the execution of > the code, is the interactive zooming and panning once the plots "are > in the screen". > > >> It's 15 images, single-channel, of 4600x3840 pixels each. > > This is a lot of data. 8bit or 16bit ? > > They are floating point values (for example, from 0 to 45.xxx). If I > understood correctly, setting the vmin and vmax, matplotlib should > normalize the values to an appropriate number of bits. > > I'm not sure what you mean by "normalize the values to an appropriate number of bits", but I don't think setting `vmin` or `vmax` will change the data type of the image. So if you have 64-bit floating point images (100+ Mb per image), then that's what you're going to be moving/scaling when you pan and zoom. -Tony |