Could it be you need to get a handle on the "epsilon machine"?

On Wed, 29 Dec 2021, 9:21 am , <alejandro.giacometti@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!
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