This should be easy.
here's my array (rather, a method of generating representative test arrays):
>>> ri = numpy.random.randint
>>> ri2 = lambda x: ''.join(ri(0,9,x).astype('S'))
>>> a = array([float(ri2(x)+ '.' + ri2(y)) for x,y in ri(1,10,(10,2))])
>>> a
array([ 7.99914000e+01, 2.08000000e+01, 3.94000000e+02,
4.66100000e+03, 5.00000000e+00, 1.72575100e+03,
3.91500000e+02, 1.90610000e+04, 1.16247000e+04,
3.53920000e+02])
I want a list of strings where '\n'.join(list_o_strings) would print:
79.9914
20.8
394.0
4661.0
5.0
1725.751
391.5
19061.0
11624.7
353.92
I want to space pad to the left and the right (but no more than necessary).
I want a zero after the decimal if that is all that is after the decimal.
I do not want scientific notation.
..and I do not want to lose any significant digits. (in 353.98000000000002 the 2 is not significant)
Yeah, it's nice to want..
python 2.5's %g, %fx.x
, ect are either befuddling me, or can't do it.
have not tried import decimal
yet. Can't see that numpy does it either (although, the array.__str__
and array.__repr__
are decimal aligned (but sometimes return scientific).
Oh, and speed counts. I'm dealing with big arrays here.
My current solution approaches are:
- to str(a) and parse off numpy's brackets
- to str(e) each element in the array and split('.') then pad and reconstruct
- to a.astype('S'+str(i)) where i is the max(len(str(a))), then pad
It seems like there should be some off-the-shelf solution out there... (but not required)
top suggestion fails with when dtype is float64:
>>> a
array([ 5.50056103e+02, 6.77383566e+03, 6.01001513e+05,
3.55425142e+08, 7.07254875e+05, 8.83174744e+02,
8.22320510e+01, 4.25076609e+08, 6.28662635e+07,
1.56503068e+02])
>>> ut0 = re.compile(r'(\d)0+$')
>>> thelist = [ut0.sub(r'\1', "%12f" % x) for x in a]
>>> print '\n'.join(thelist)
550.056103
6773.835663
601001.513
355425141.8471
707254.875038
883.174744
82.232051
425076608.7676
62866263.55
156.503068