Browsing the available version of tensorflow for the dates before January
2021 (date when Python 2.7 stopped being supported) I can't find a
tensorflow version for Python 2.7 that works under Windows.
The reference site I use is https://pypi.org/project/tensorflow/
Anybody can point out a
What are the parameters to account for in this type of algorithm? are there
some checks to perform the arm moves ? for example angle moves or cartesian
moves based on some distance thresholds? Any idea about the
pseudo-algorithm is welcome.
Thanks.
Le dim. 23 juin 2024 à 10:33, Alan Gauld via
Hello to all of this magnificent community!
I have this problem I had already spent a few days on and still can't
figure out a proper solution.
So, given the x,y,z coordinates of a target object and the offset x,y,z of
arms of a robot, what is a good algorithm to perform to grab the object
My code is just an attempt at the task, it is not exact as what relates to
the coordinates (e.g., doesn't account for the size of the object. I would
like to have a idea on the general approach to such problems (even a pseudo
code would do)
"Get the hands rapidly enough in the vicinity and then
I am trying to install numpy library on Python 2.7.15 in PyCharm but the
error message I get is:
ERROR: Could not find a version that satisfies the requirement numpy (from
> versions: none)
> ERROR: No matching distribution found for numpy
>
ch tuple I should use to refer to the underlying list value as you
suggest?
Anything else is good in my code ?
Thanks
Le dim. 31 mars 2024 à 01:44, MRAB via Python-list
a écrit :
> On 2024-03-31 00:09, marc nicole via Python-list wrote:
> > I am creating a memoization example with a fu
I am creating a memoization example with a function that adds up / averages
the elements of an array and compares it with the cached ones to retrieve
them in case they are already stored.
In addition, I want to store only if the result of the function differs
considerably (passes a threshold e.g.
So I am trying to build a binary tree hierarchy given numerical elements
serving for its leaves (last level of the tree to build). From the leaves I
want to randomly create a name for the higher level of the hierarchy and
assign it to the children elements. For example: if the elements inputted
_original.iloc[
> > dataset_index_values[idx_cell][1],
> > dataset_index_values[idx_cell][0]
> > ]
> > all_datasets.append(dataframe_cpy)
> > all_datasets_final.append(all_datasets)
> > return all_datasets_final
&g
4 7:37 AM, marc nicole via Python-list wrote:
> > Hello,
> >
> > I have an initial dataframe with a random list of target cells (each cell
> > being identified with a couple (x,y)).
> > I want to yield four different dataframes each containing the value of
> one
>
Hello,
I have an initial dataframe with a random list of target cells (each cell
being identified with a couple (x,y)).
I want to yield four different dataframes each containing the value of one
of the contour (surrounding) cells of each specified target cell.
the surrounding cells to consider
Hi all,
I have a csv OLAP dataset that I want to extract the domain hierarchies
from each of its dimensions.
Anybody could recommend a Python tool that could manage this properly?
Thanks
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Hello to All,
I want to create a cube from csv data file and to perform and aggregation
on it, the code is below:
from sqlalchemy import create_enginefrom cubes.tutorial.sql import
create_table_from_csvfrom cubes import Workspace, Cell, browser
import dataif __name__ == '__main__':
engine =
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