On 9/19/2011 2:23 AM, Christoph Gohlke wrote: > > > On 9/18/2011 2:30 PM, Eric Firing wrote: >> On 09/18/2011 09:30 AM, Christoph Gohlke wrote: >>> Hello, >>> >>> matplotlib uses int(x*255) or np.array(x*255, np.uint8) to quantize >>> normalized floating point numbers x in the range [0.0 to 1.0] to >>> integers in the range [0 to 255]. This way only 1.0 is mapped to 255, >>> not for example 0.999. Is this really intended or would not the largest >>> floating point number below 256.0 be a better scale factor than 255? The >>> exact factor depends on the floating point precision (~255.999992 for >>> np.float32, ~255.93 for np.float16). >>> >>> Christoph >> >> Christoph, >> >> It's a reasonable question; but do you have use cases in mind where it >> actually makes a difference? >> >> The simple scaling with truncation is used in many places, both in the >> python and the c++ code. >> >> Eric >> > > Hi Eric, > > visually it will be hardly noticeable in most cases. However, I'd expect > the histogram of normalized intensity data to be the same as the > histogram of a linear grayscale image of that data (neglecting gamma > correction, image scaling/interpolation for now). Consider this code for > example: > > import numpy as np > a = np.random.rand(1024*1024) > a[0], a[-1] = 0.0, 1.0 > h0 = np.histogram(a, bins=256, range=(0, 1))[0] > h1 = np.bincount(np.uint8(a * 255)) > h2 = np.bincount(np.uint8(a * 255.9999999999999)) > print (h0 - h1) > print (h0 - h2) > > Christoph >
To make this work with any float type one could use: np.uint8(a * np.nextafter(a.dtype.type(256), a.dtype.type(0))) Christoph ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2dcopy1 _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
