• Short answer: It's because >>> f64_info.max - f64_info.min inf
• Long answer: linspace(a,b,n) tries to calculate the step by (b-a)/n and fails at (b-a). You need to either – split your range into two parts and then glue them back: np.r_[np.linspace(f64_info.min, 0, 5), np.linspace(0, f64_info.max, 5)[1:]] – or select a range that fits into float64: np.linspace(f64_info.min/2, f64_info.max/2, 10) – or select np.float128 as a dtype for linspace (linux/macos only): np.linspace(np.float128(f64_info.min), np.float128(f64_info.max), 10) Best regards, Lev On Wed, Dec 29, 2021 at 8:01 PM Sebastian Gurovich <seb...@gmail.com> wrote: > Could it be you need to get a handle on the "epsilon machine"? > > On Wed, 29 Dec 2021, 9:21 am , <alejandro.giacome...@gmail.com> wrote: > >> I am getting an interesting result, and I'm wondering if anyone would >> care to give me some intuition of why. >> >> The example is simple enough, I want to get a range of values that are >> representable by a type: >> >> ```python >> f64_info = np.finfo(np.float64) >> valid_range = np.linspace( >> start=f64_info.min, stop=f64_info.max, num=10 >> ) >> valid_range => array([ nan, inf, inf, >> inf, >> inf, inf, inf, inf, >> inf, 1.79769313e+308]) >> ``` >> >> The minimum value is representable by the type, I can see it: >> >> ```python >> f64_info.min => -1.7976931348623157e+308 >> ``` >> >> I thought that maybe the valid range cannot start with the minimun value, >> so I've tried a few alternatives: >> >> ```python >> >> valid_range = np.linspace( >> start=f64_info.min + f64_info.eps, stop=f64_info.max, num=10 >> ) >> valid_range => array([ nan, inf, inf, >> inf, >> inf, inf, inf, inf, >> inf, 1.79769313e+308]) >> >> >> valid_range = np.linspace( >> start=f64_info.min + f64_info.tiny, stop=f64_info.max, num=10 >> ) >> valid_range => array([ nan, inf, inf, >> inf, >> inf, inf, inf, inf, >> inf, 1.79769313e+308]) >> ``` >> >> I thought maybe the range is too wide, but I can do this: >> >> ```python >> valid_range = np.linspace( >> start=0, stop=f64_info.max, num=10 >> ) >> valid_range => array([0.00000000e+000, 1.99743682e+307, 3.99487363e+307, >> 5.99231045e+307, >> 7.98974727e+307, 9.98718408e+307, 1.19846209e+308, >> 1.39820577e+308, >> 1.59794945e+308, 1.79769313e+308]) >> >> ... >> >> valid_range = np.linspace( >> start=f64_info.tiny, stop=f64_info.max, num=10 >> ) >> valid_range => array([2.22507386e-308, 1.99743682e+307, 3.99487363e+307, >> 5.99231045e+307, >> 7.98974727e+307, 9.98718408e+307, 1.19846209e+308, >> 1.39820577e+308, >> 1.59794945e+308, 1.79769313e+308]) >> >> ... >> >> f32_info = np.finfo(np.float32) >> valid_range = np.linspace( >> start=f32_info.tiny, stop=f32_info.max, num=10, dtype=np.float32, >> ) >> valid_range => array([1.1754944e-38, 3.7809150e+37, 7.5618299e+37, >> 1.1342745e+38, >> 1.5123660e+38, 1.8904575e+38, 2.2685490e+38, >> 2.6466405e+38, >> 3.0247320e+38, 3.4028235e+38], dtype=float32) >> >> ``` >> >> I know that linear space is arbitrary, and perhaps not that useful. In >> fact this is valid: >> >> ```python >> valid_range = np.logspace( >> start=f64_info.minexp, stop=f64_info.maxexp, num=10, base=2, >> endpoint=False >> ) >> valid_range => array([2.22507386e-308, 8.67124674e-247, 3.37923704e-185, >> 1.31690901e-123, >> 5.13207368e-062, 2.00000000e+000, 7.79412037e+061, >> 3.03741562e+123, >> 1.18369915e+185, 4.61294681e+246]) >> ``` >> >> But I'm still confused on why linear space is invalid >> >> Thanks! >> _______________________________________________ >> NumPy-Discussion mailing list -- numpy-discussion@python.org >> To unsubscribe send an email to numpy-discussion-le...@python.org >> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ >> Member address: seb...@gmail.com >> > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: lev.maxi...@gmail.com >
_______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
