Vision – Multipurpose HTML Template

Site Templates
Vision is a unique, fully responsive and flexible multipurpose template designed for business, corporate, agency’s, portfolio, blog, shop and many other. What’s inside? Over 70 HTML files, ready to use pages, pre-made layouts and many other features. It looks perfect on all major browsers, tablets and mobile devices. Additionally, you get the most caring support, Free Future Updates..
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DYON – Simple vCard Resume Template

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Dyon is a minimal creative online resume template. Boasting large images, video backgrounds, and a variety of animation overlays. This theme gives you a personal space to share what you are all about as a creative designer, photographer, developer, or any profession! It’s fully customizable, you can change the background easily and set any color to elements such as links, buttons, etc.
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Difference of precision/display between numpy.tolist() and list()

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Question: This is kind of a follow up to coldspeed's question. (And this is not a duplicate of is floating point math broken ? BTW) I'm converting a list of lists to a numpy array, and then trying to convert it back to a python list of lists. import numpy as np x = [[ 1.00000000e+00, 6.61560000e-13], [ 2.00000000e+00, 3.05350000e-13], [ 3.00000000e+00, 6.22240000e-13], [ 4.00000000e+00, 3.08850000e-13], [ 5.00000000e+00, 1.11170000e-10], [ 6.00000000e+00, 3.82440000e-11], [ 7.00000000e+00, 5.39160000e-11], [ 8.00000000e+00, 1.75910000e-11], [ 9.00000000e+00, 2.27330000e-10]] x=np.array(x,np.float) print([y.tolist() for y in x]) print([list(y) for y in x]) Result:[[1.0, 6.6156e-13], [2.0, 3.0535e-13], [3.0, 6.2224e-13], [4.0, 3.0885e-13], [5.0, 1.1117e-10], [6.0, 3.8244e-11], [7.0, 5.3916e-11], [8.0, 1.7591e-11], [9.0, 2.2733e-10]] [[1.0, 6.6155999999999996e-13], [2.0, 3.0535000000000001e-13], [3.0, 6.2223999999999998e-13], [4.0, 3.0884999999999999e-13], [5.0, 1.1117e-10], [6.0, 3.8243999999999997e-11], [7.0, 5.3915999999999998e-11], [8.0, 1.7591e-11], [9.0, 2.2733e-10]] Note that…
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