Thank you Joseph
El vie, 18 dic 2020 a las 16:56, Joseph Fox-Rabinovitz (<
jfoxrabinov...@gmail.com>) escribió:
> There is: np.floor_divide.
>
> On Fri, Dec 18, 2020, 14:38 Martín Chalela
> wrote:
>
>> Right! I just thought there would/should be a "digitize" function that
>> did this.
>>
>> El v
There is: np.floor_divide.
On Fri, Dec 18, 2020, 14:38 Martín Chalela wrote:
> Right! I just thought there would/should be a "digitize" function that did
> this.
>
> El vie, 18 dic 2020 a las 14:16, Joseph Fox-Rabinovitz (<
> jfoxrabinov...@gmail.com>) escribió:
>
>> Bin index is just value floo
Right! I just thought there would/should be a "digitize" function that did
this.
El vie, 18 dic 2020 a las 14:16, Joseph Fox-Rabinovitz (<
jfoxrabinov...@gmail.com>) escribió:
> Bin index is just value floor divided by the bin size.
>
> On Fri, Dec 18, 2020, 09:59 Martín Chalela
> wrote:
>
>> Hi
Bin index is just value floor divided by the bin size.
On Fri, Dec 18, 2020, 09:59 Martín Chalela wrote:
> Hi all! I was wondering if there is a way around to using np.digitize when
> dealing with equidistant bins. For example:
> bins = np.linspace(0, 1, 20)
>
> The main problem I encountered is
Hi all! I was wondering if there is a way around to using np.digitize when
dealing with equidistant bins. For example:
bins = np.linspace(0, 1, 20)
The main problem I encountered is that digitize calls np.searchsorted. This
is the correct way, I think, for generic bins, i.e. bins that have
differe
