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: arch...@mail-archive.com

Reply via email to