Hi experts!
Im working with conductivity of sticks film - systems.
In my
algorithm (N sticks) I have the intersection graph matrix M (M is a NxN
matrix, M_ij=1 if sticks 'i' and 'j' do intersect, and M_ij=0 if sticks
'i' and 'j' do not).
Also I have 2 lists with the end-points of each stic
Hi experts!
I have a numpy array M. I generate a graph using NetworkX and then I want to
draw this graph:
import networkx as nx
import matplotlib.pyplot as plt
G=nx.graph(M)
nx.draw(G)
plt.draw()
Doing this, no picture appears. In addition, if I do `plt.show()` no picture
a
Hi experts!!
I am studying the intersection between line
segments (sticks). I have an Numpy array (M) corresponding to the
intersection graph of the system (the element Mij = 1 if the sticks' i
'and' 'j' intersect, and Mij = 0 if not intersect).
I want to
determine the number of elements that
Hi experts!
I wanna use less RAM memory in my Monte Carlo simulations. In my algorithm I
use numpy arrays and xrange() function.
I hear that I can reduce RAM used in my lagorithm if I do the next:
1) replace xrange() for range().
2) replace numpya arrays for python lists
3) use reset() funct
Hi experts!
I wanna use networkx.has_path(). This is applies, necesary, to a networkx
graph. I have a adjacency matrix of a undirected graph (M, wich is a numpy
matrix (array of N x N elements)).
How can I do for use M in networkx.has_path()?
If I must transform M into a networkx graph: ho
Thanks so much!!
Best regards,
José Luis
De: Daπid
Para: Discussion of Numerical Python
Enviado: jueves, 5 de septiembre de 2013 12:56
Asunto: Re: [Numpy-discussion] Stick intersection path algorithm
On 5 September 2013 17:03, Josè Luis Mietta wrote
algorithm
On 5 September 2013 17:03, Josè Luis Mietta wrote:
The array ([ 0, 39, 7, 3, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1]) means that in the sistem (graph) are : 4 cluster of size 1, one
cluster of size 3, one cluster of size 7 and one cluste of size 39?
No, it means
?
Thans a lot!
José Luis
De: Daπid
Para: Discussion of Numerical Python
Enviado: jueves, 5 de septiembre de 2013 11:06
Asunto: Re: [Numpy-discussion] Stick intersection path algorithm
On 5 September 2013 13:14, Josè Luis Mietta wrote:
2. Using network
e: [Numpy-discussion] Stick intersection path algorithm
On Wed, Sep 4, 2013 at 3:17 PM, Josè Luis Mietta
wrote:
>
> Hi experts!
>
> If I do:
>
> G = Graph(M)
>
> That is: to use the associated intersection graph, where the vertices are the
> sticks and there is an edge
ers.
Thanks a lot!!
De: Robert Kern
Para: Discussion of Numerical Python
Enviado: lunes, 2 de septiembre de 2013 10:40
Asunto: Re: [Numpy-discussion] Stick intersection path algorithm
On Sun, Sep 1, 2013 at 11:55 PM, Josè Luis Mietta
wrote:
>
> Hi e
-discussion] Stick intersection path algorithm
On Sun, Sep 1, 2013 at 3:55 PM, Josè Luis Mietta
wrote:
Given two arbitrary sticks, i need a simple and effective algorithm that
determinate if that two sticks are conected by a 'intersected-sticks' path.
>
>
>
do you mean a test
Hi experts!
I wanna study the intersection between line segments (sticks).
I wrote a algorithm that generate a matrix, M, with N rows and N columns. The
M-element Mij is 1 if stick number 'i' intersect stick number 'j' (obviously M
is symmetric).
Given two arbitrary sticks, i need a simple and
probably add an interval check to ensure that the x and y intervals for the
segments of interest overlap before doing the full check, but how much that
would help would depend on the implementations.
~Brett
On Fri, Aug 23, 2013 at 5:09 PM, Josè Luis Mietta
wrote:
I wrote an algorithm
Hi experts!
I wrote an algorithm for study stick percolation (i.e.: networks between line
segments that intersect between them). In my algorithm N sticks (line segments)
are created inside a rectanglar box of sides 'b' and 'h' and then, one by one,
the algorithm explores the intersection between
Hi experts!
I have a core i3 3GB RAM Toshiba laptop. Im a newby Ubuntu 13.04, python and
sage user. I note that RAM memory becomes full while running script (starts in
50% of RAM ocupation and becomes to 100% (full)). This generate that operating
system become slower... In the code few numpy a
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