implement Axis.chunks & LArray.chunks #505

Axis.split(chunks=10, length=None, step=None, before=None, after=None, indices=None)
LArray.split(chunks=10, length=None, step=None, before=None, after=None, indices=None, axis=-1)
>>> age = Axis("0..99", "age")
>>> age.split(5)
(age.i[0:20], age.i[20:40], age.i[40:60], age.i[60:80], age.i[80:100])
>>> age.split(length=20)
(age.i[0:20], age.i[20:40], age.i[40:60], age.i[60:80], age.i[80:100])
>>> age.split(length=10, step=20)
(age.i[0:10], age.i[20:30], age.i[40:50], age.i[60:70], age.i[80:90])
>>> age.split(before=50)
(age.i[0:50], age.i[50:100])
>>> age.split(before=[10, 15, 20, 40])
(age.i[0:10], age.i[10:15], age.i[15:20], age.i[20:40], age.i[40:100])
>>> age.split(indices=50)
(age.i[0:50], age.i[50:100])
>>> age.split(indices=[10, 15, 20, 40])
(age.i[0:10], age.i[10:15], age.i[15:20], age.i[20:40], age.i[40:100])

>>> arr = ndrange(age) * 0.25
>>> arr.split(10, axis='age')
[age    0     1    2     3    4     5    6     7    8     9
     0.0  0.25  0.5  0.75  1.0  1.25  1.5  1.75  2.0  2.25,
age   10    11   12    13   14    15   16    17   18    19
     2.5  2.75  3.0  3.25  3.5  3.75  4.0  4.25  4.5  4.75,
age   20    21   22    23   24    25   26    27   28    29
     5.0  5.25  5.5  5.75  6.0  6.25  6.5  6.75  7.0  7.25,
age   30    31   32    33   34    35   36    37   38    39
     7.5  7.75  8.0  8.25  8.5  8.75  9.0  9.25  9.5  9.75,
age    40     41    42     43    44     45    46     47    48     49
     10.0  10.25  10.5  10.75  11.0  11.25  11.5  11.75  12.0  12.25,
age    50     51    52     53    54     55    56     57    58     59
     12.5  12.75  13.0  13.25  13.5  13.75  14.0  14.25  14.5  14.75,
age    60     61    62     63    64     65    66     67    68     69
     15.0  15.25  15.5  15.75  16.0  16.25  16.5  16.75  17.0  17.25,
age    70     71    72     73    74     75    76     77    78     79
     17.5  17.75  18.0  18.25  18.5  18.75  19.0  19.25  19.5  19.75,
age    80     81    82     83    84     85    86     87    88     89
     20.0  20.25  20.5  20.75  21.0  21.25  21.5  21.75  22.0  22.25,
age    90     91    92     93    94     95    96     97    98     99
     22.5  22.75  23.0  23.25  23.5  23.75  24.0  24.25  24.5  24.75]
>>> arr1d.split(10)
idem