On Wed, Oct 20, 2021 at 8:29 AM Robert Kern wrote:
>
> On Tue, Oct 19, 2021 at 8:22 PM wrote:
>>
>> Do I have to use it this way?
>
>
> Nothing is forcing you to, but everyone else will write it as `dtype=bool`,
> not `dtype=(bool)`. `dtype=(bool)` is perfectly syntactically-valid Python.
> It'
Do I have to use it this way?
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> You could use `dis.dis` to compare the two expressions and see that they
> compile to the same bytecode.
Do you mean the following:
In [1]: import numpy as np
In [2]: from dis import dis
In [7]: dis('bool')
1 0 LOAD_NAME0 (bool)
2 RETURN_VALUE
In [8]:
See the following testing in IPython shell:
In [6]: import numpy as np
In [7]: a = np.array([1], dtype=(bool))
In [8]: b = np.array([1], dtype=bool)
In [9]: a
Out[9]: array([ True])
In [10]: b
Out[10]: array([ True])
It seems that dtype=(bool) and dtype=bool are both correct usages. If so, wh
I've written the following python code snippet in pycharm:
```python
import numpy as np
from numpy import pi, sin
a = np.array([1], dtype=bool)
if np.in|vert(a) == ~a:
print('ok')
```
When putting the point/cursor in the above code snippet at the position denoted
by `|`, I would like to see infor
On Mon, Oct 4, 2021 at 11:54 PM Stephen Waterbury
wrote:
>
> On 10/4/21 10:07 AM, Hongyi Zhao wrote:
>
> On Mon, Oct 4, 2021 at 9:33 PM Robert Kern wrote:
>
> On Mon, Oct 4, 2021 at 5:17 AM Hongyi Zhao wrote:
>
> That’s just the way Python’s syntax works. Operators are
On Mon, Oct 4, 2021 at 9:33 PM Robert Kern wrote:
>
> On Mon, Oct 4, 2021 at 5:17 AM Hongyi Zhao wrote:
>>
>>
>> > That’s just the way Python’s syntax works. Operators are not names that
>> > can be resolved to objects that can be compared with the `is
On Mon, Oct 4, 2021 at 4:41 PM Robert Kern wrote:
>
> On Mon, Oct 4, 2021 at 1:09 AM wrote:
>>
>> Thank you for pointing this out. This is the code block which includes the
>> first appearance of the keyword `logical_not`.
>>
>> BTW, why can't the ~ operator be tested equal to 'np.invert', as sh
Thank you for pointing this out. This is the code block which includes the
first appearance of the keyword `logical_not`.
BTW, why can't the ~ operator be tested equal to 'np.invert', as shown below:
```
In [1]: import numpy as np
In [3]: np.invert is np.bitwise_not
Out[3]: True
In [4]: np.inv
> (the bool implementation uses the `logical_not` loop).
Do you the following code snippet:
https://github.com/numpy/numpy/blob/3c1e9b4717b2eb33a2bf2d495006bc300f5b8765/numpy/core/src/umath/loops.c.src#L1627-L1633
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I noticed the following documentation on `numpy.invert`: [1]
numpy.invert
[...]
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of the
integers in the input arrays. This ufunc implements the C/Python operator ~
On Mon, Oct 12, 2020 at 10:41 PM Andrea Gavana wrote:
>
> Hi,
>
> On Mon, 12 Oct 2020 at 16.22, Hongyi Zhao wrote:
>>
>> On Mon, Oct 12, 2020 at 9:33 PM Andrea Gavana
>> wrote:
>> >
>> > Hi,
>> >
>> > On Mon, 12 Oct 2020 at 14:3
On Mon, Oct 12, 2020 at 9:33 PM Andrea Gavana wrote:
>
> Hi,
>
> On Mon, 12 Oct 2020 at 14:38, Hongyi Zhao wrote:
>>
>> On Sun, Oct 11, 2020 at 3:42 PM Evgeni Burovski
>> wrote:
>> >
>> > On Sun, Oct 11, 2020 at 9:55 AM Evgeni Burovski
>> &g
appropriate. What's your point of view on this
testing results?
Regards,
HY
>
>
>
> > Second:
> >
> > Move the loop into cython.
> >
> >
> >
> >
> > вс, 11 окт. 2020 г., 9:32 Hongyi Zhao :
> >>
> >> On Sun, Oc
nations on the reasons why
doing so can improve performance?
>
> Second:
>
> Move the loop into cython.
>
>
>
>
> вс, 11 окт. 2020 г., 9:32 Hongyi Zhao :
>>
>> On Sun, Oct 11, 2020 at 2:02 PM Andrea Gavana
>> wrote:
>> >
>> >
>>
; > (Or avoid the overhead of trapz by just implementing the trapezoid formula
> > manually)
>
>
> Roughly like this:
> https://gist.github.com/ev-br/0250e4eee461670cf489515ee427eb99
I try to run this notebook, but find that all of the
function/variable/method can't be found a
also learned that the numpy array is
optimized and has the performance close to C/C++.
>
>
>
> > Second:
> >
> > Move the loop into cython.
> >
> >
> >
> >
> > вс, 11 окт. 2020 г., 9:32 Hongyi Zhao :
> >>
> >> On Sun, Oct 1
t;
> Second:
>
> Move the loop into cython.
Will this be more efficient than the schema like parallelization based
on python modules, say, joblib?
>
>
>
>
> вс, 11 окт. 2020 г., 9:32 Hongyi Zhao :
>>
>> On Sun, Oct 11, 2020 at 2:02 PM Andrea Gavana
On Sun, Oct 11, 2020 at 2:02 PM Andrea Gavana wrote:
>
>
>
> On Sun, 11 Oct 2020 at 07.52, Hongyi Zhao wrote:
>>
>> On Sun, Oct 11, 2020 at 1:33 PM Andrea Gavana
>> wrote:
>> >
>> >
>> >
>> > On Sun, 11 Oct 2020 at 07.14, Andr
On Sun, Oct 11, 2020 at 1:33 PM Andrea Gavana wrote:
>
>
>
> On Sun, 11 Oct 2020 at 07.14, Andrea Gavana wrote:
>>
>> Hi,
>>
>> On Sun, 11 Oct 2020 at 00.27, Hongyi Zhao wrote:
>>>
>>> On Sun, Oct 11, 2020 at 1:48 AM Robert Kern wrote:
mu.py
[-10.999 -10.999 -10.999 ... 20. 20. 20. ] [4.973e-84
4.973e-84 4.973e-84 ... 4.973e-84 4.973e-84 4.973e-84]
real0m41.056s
user0m43.970s
sys0m3.813s
But are there any ways to further improve/increase efficiency?
Regards,
HY
>
> On Sat, Oct 10, 2020, 8:23 A
es/numpy/lib/function_base.py",
line 2192, in _vectorize_call
outputs = ufunc(*inputs)
File "mu.py", line 8, in fermi
return 1./(exp((E-mu)/kT)+1)
KeyboardInterrupt
Any helps and hints for this problem will be highly appreciated?
Regards,
--
Hongyi Zhao
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