Am 11.04.18 um 08:38 schrieb Priya Singh:
I have two 2D arrays one R and another T (which is also a 2D array).
Do you know how can I fit T with R in order to find central
coordinate x0,y0 for T relative to R???
So the main question is do you know in python how can I fit two 2D arrays to
find
x0
> * mxDateTime Portierung auf Python 3.6
+1 !!
Karsten Hilbert
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On Tue, 10 Apr 2018 23:36:27 -0700, cuddlycaveman wrote:
[snip a number of carefully chosen, non-random numbers shown in binary]
> Don’t know if that helps
Helps what?
With no context, we don't know who you are replying to, what they asked,
or why you think this is helpful.
According to my a
Good morning.
I need some suggestion from you if you have encountered this problem ever.
I have two 2D arrays one R and another T (which is also a 2D array).
Do you know how can I fit T with R in order to find central
coordinate x0,y0 for T relative to R???
So the main question is do you know in
Hi! I want users’ devices to be able to monitor the maximum amount of POIs at
once (geo-fences/beacons) and I need to prepare an algorithm solution for
monitoring the POIs. How should it be implemented in Python?
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Thomas Jollans wrote:
>
> Welcome to python-list/comp.lang.python!
>
> This isn't originally a Google group. Google just mirrors the old USENET
> group, which is awash with spam.
>
> There is also a mailing list version of this group (posts are mirrored
> both ways) at https://mail.python.org/m
I am sorry, but I thought Levenberg marquardt was used quite bit in Image
registration. Computing/refining homographies between two related views for
instance.
On Wed, Apr 11, 2018 at 12:49 PM, Christian Gollwitzer
wrote:
> Am 11.04.18 um 08:38 schrieb Priya Singh:
>
>> I have two 2D arrays one
I have a dataframe:
import pandas as pd
import numpy as np
df = pd.DataFrame( { 'A' : ['a', 'b', '', None, np.nan],
'B' : [None, np.nan, 'a', 'b', '']})
A B
0 a None
1 b NaN
2 a
3 None b
4 NaN
I would like to create column C in
On Wed, Apr 11, 2018, at 14:48, zljubi...@gmail.com wrote:
> I have a dataframe:
> [...]
This seems to work:
df1 = pd.DataFrame( { 'A' : ['a', 'b', '', None, np.nan],
'B' : [None, np.nan, 'a',
'b', '']})
df1['C'] = df1[['A', 'B']].apply(lambda x
On Wednesday, April 11, 2018 at 2:49:01 PM UTC-4, zlju...@gmail.com wrote:
> I have a dataframe:
>
> import pandas as pd
> import numpy as np
>
> df = pd.DataFrame( { 'A' : ['a', 'b', '', None, np.nan],
> 'B' : [None, np.nan, 'a', 'b', '']})
>
> A B
> 0 a Non
On 2018-03-25 22:52:59 +, Steven D'Aprano wrote:
> On Sun, 25 Mar 2018 23:29:07 +0200, Peter J. Holzer wrote:
> >> >> By the way, multiple CPU machines are different from CPUs with
> >> >> multiple cores:
> >> >>
> >> >> http://smallbusiness.chron.com/multiple-cpu-vs-multicore-33195.html
> >> >
On 2018-03-25, Steven D'Aprano wrote:
> Not really. With multiple CPUs, you have the option of running two
> distinct OSes in isolation, not merely virtual machines but actual
> distinct machines in the same box.
Not on any of the multi-CPU motherboards I ever worked with. The CPUs
shared SDR
On Apr 11, 2018 20:52, zljubi...@gmail.com wrote:
>
> I have a dataframe:
>
> import pandas as pd
> import numpy as np
>
> df = pd.DataFrame( { 'A' : ['a', 'b', '', None, np.nan],
> 'B' : [None, np.nan, 'a', 'b', '']})
>
> A B
> 0 a None
> 1 b NaN
> 2
Rafal Sikora wrote:
Hi! I want users’ devices to be able to monitor the maximum amount of POIs at
once (geo-fences/beacons) and I need to prepare an algorithm solution for
> monitoring the POIs. How should it be implemented in Python?
What? You'll have to describe the problem in more details
On 10/04/18 21:06, C W Rose via Python-list wrote:
Thomas Jollans wrote:
Welcome to python-list/comp.lang.python!
This isn't originally a Google group. Google just mirrors the old USENET
group, which is awash with spam.
There is also a mailing list version of this group (posts are mirrored
b
> I fetch comp.lang.python from eternal.september with leafnode, and after
> 30 years of Usenet I recently had to install a news filter to remove the
> garbage. After the initial flurry the filter doesn't need much updating,
> but here's why it's necessary:
...
> for totals of 2168 fetched and 438
I’m replying to your post on January 28th
Nice carefully chosen non random numbers Steven D'Aprano.
Was just doing what you asked, but you don’t remember 😂😂😂
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This C function returns a buffer which I declared it as a ctypes.c_char_p. The
buffer has size 0x1 bytes long and the valid data may vary from a few bytes
to the whole size.
In every call I know how much the valid data size is, but I suppose I can't use
slice to get it because there may be
On Thu, Apr 12, 2018 at 2:16 PM, wrote:
> This C function returns a buffer which I declared it as a ctypes.c_char_p.
> The buffer has size 0x1 bytes long and the valid data may vary from a few
> bytes to the whole size.
>
> In every call I know how much the valid data size is, but I suppose
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