er visible change we
would like some more input.
In particular:
* What are expectations of the auto binning algorithm?
* What is a reasonable maximum number of bins for a sample of size n?
With kind regards,
Pieter Eendebak
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Hi Steve,
The representation of the polynomials without including the domain is
indeed confusing. In https://github.com/numpy/numpy/pull/21760 the
representation is changed to avoid this. Would this representation work for
you, or are there better representations?
With kind regards,
Pieter
. numpy financials)
With kind regards,
Pieter Eendebak
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we can
use the old style of setting the seed)
With kind regards,
Pieter Eendebak
On Sun, Jun 19, 2022 at 5:36 PM Robert Kern wrote:
> On Sun, Jun 19, 2022 at 9:37 AM Pieter Eendebak
> wrote:
>
>> Hi everyone,
>>
>> The new numpy random interface (e.g. r=numpy.rand
(seed=42) # fails, with good error
message
rng.bit_generator.state['state']['state']=42 # has no effect, perhaps make
this dict read-only?
Is there a way to set the seed without creating a new RNG object?
With kind regards,
Pieter Eendebak
_
the
suggestions from Sebastian (free lists or scalar ufuncs) might be required,
but both involve some larger effort.
With kind regards,
Pieter Eendebak
On Wed, May 4, 2022 at 3:49 PM Sebastian Berg
wrote:
> On Tue, 2022-05-03 at 15:06 +0200, Pieter Eendebak wrote:
> > Hi everyone,
> >
>
omial([Polynomial([1.0217, 0.99 ], domain=[-1., 1.],
window=[-1., 1.])],
dtype=object, domain=[-1., 1.], window=[-1., 1.])
but I am looking for:
Polynomial([1.0217, 0.99 ], domain=[-1., 1.], window=[-1., 1.])
With kind regards,
Pieter Eendebak
__
?
With kind regards,
Pieter Eendebak
Example benchmark:
import numpy as np
from numpy import sqrt
import time
v=np.array([1.1])
t0=time.perf_counter()
x=np.float64(v)
for kk in range(1_000_000):
w1=sqrt(x)
dt1=time.perf_counter()-t0
print(dt1)
t0=time.perf_counter()
x=v
for kk in range(1_000_000
