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I have a numpy array with xy co-ordinates for points. I have plotted each of these points and want a line connecting each point to every other point (a complete graph). The array is a 2x50 structure so I have transposed it and used a view to let me iterate through the rows. However, I am getting an 'index out of bounds' error with the following:

     plt.plot(*zip(*v.T)) #to plot all the points
     viewVX = (v[0]).T
     viewVY = (v[1]).T
     for i in range(0, 49):
        xPoints = viewVX[i], viewVX[i+1]
        print("xPoints is", xPoints)
        yPoints = viewVY[i+2], viewVY[i+3]
        print("yPoints is", yPoints)
        xy = xPoints, yPoints
        plt.plot(*zip(*xy), ls ='-')

I was hoping that the indexing would 'wrap-around' so that for the ypoints, it'd start with y0, y1 etc. Is there an easier way to accomplish what I'm trying to achieve?

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  • 1
    I'm a little lost. First, plt.plot(*zip(*v.T)) seems to do the same thing as plt.plot(v[0], v[1]). Second, your question makes it sound like you want a line between every pair of points (maybe a complete graph?) but that's not what your code does. Could you be a little more clear about what you're trying to do. Commented Jan 1, 2012 at 19:27
  • Yes Bago, I'm trying to draw a complete graph and getting my code to do that is proving a problem for me. Thanks for the simpler plt.plot(v[0], v[1]) syntax. I'm new to numpy and matplotlab. I'll edit my question to make explicit the complete graph. Commented Jan 1, 2012 at 19:37
  • possible duplicate of How do you create line segments between two points? Commented Jan 3, 2012 at 10:21

4 Answers 4

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import matplotlib.pyplot as plt
import numpy as np
import itertools

v=np.random.random((2,50))
plt.plot(
    *zip(*itertools.chain.from_iterable(itertools.combinations(v.T,2))),
    marker='o', markerfacecolor='red')
plt.show()

The advantage of doing it this way is that there are fewer calls to plt.plot. This should be significantly faster than methods that make O(N**2) calls to plt.plot.

Note also that you do not need to plot the points separately. Instead, you can use the marker='o' parameter.

Explanation: I think the easiest way to understand this code is to see how it operates on a simple v:

In [4]: import numpy as np
In [5]: import itertools
In [7]: v=np.arange(8).reshape(2,4)
In [8]: v
Out[8]: 
array([[0, 1, 2, 3],
       [4, 5, 6, 7]])

itertools.combinations(...,2) generates all possible pairs of points:

In [10]: list(itertools.combinations(v.T,2))
Out[10]: 
[(array([0, 4]), array([1, 5])),
 (array([0, 4]), array([2, 6])),
 (array([0, 4]), array([3, 7])),
 (array([1, 5]), array([2, 6])),
 (array([1, 5]), array([3, 7])),
 (array([2, 6]), array([3, 7]))]

Now we use itertools.chain.from_iterable to convert this list of pairs of points into a (flattened) list of points:

In [11]: list(itertools.chain.from_iterable(itertools.combinations(v.T,2)))
Out[11]: 
[array([0, 4]),
 array([1, 5]),
 array([0, 4]),
 array([2, 6]),
 array([0, 4]),
 array([3, 7]),
 array([1, 5]),
 array([2, 6]),
 array([1, 5]),
 array([3, 7]),
 array([2, 6]),
 array([3, 7])]

If we plot these points one after another, connected by lines, we get our complete graph. The only problem is that plt.plot(x,y) expects x to be a sequence of x-values, and y to be a sequence of y-values.

We can use zip to convert the list of points into a list of x-values and y-values:

In [12]: zip(*itertools.chain.from_iterable(itertools.combinations(v.T,2)))
Out[12]: [(0, 1, 0, 2, 0, 3, 1, 2, 1, 3, 2, 3), (4, 5, 4, 6, 4, 7, 5, 6, 5, 7, 6, 7)]

The use of the splat operator (*) in zip and plt.plot is explained here.

Thus we've managed to massage the data into the right form to be fed to plt.plot.

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1 Comment

that is fantastic - thanks! I haven't used itertools before so some of the syntax in the plt.plot call is unfamiliar to me. Is this similar to nditer?
2

With a 2 by 50 array,

 for i in range(0, 49):
    xPoints = viewVX[i], viewVX[i+1]
    print("xPoints is", xPoints)
    yPoints = viewVY[i+2], viewVY[i+3]

would get out of bounds for i = 47 and i = 48 since you use i+2 and i+3 as indices into viewVY.

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4 Comments

Is there a way of iterating through array elements from different starting points so the iteration wraps back round to the starting element?
Modular indexing, (i + 2(3)) % 50 would wrap it back to 0 when it reaches 50.
thanks that solved my indexing problem. But I just need to sort out which points to send for a complete graph.
Happy to help. I'm afraid I can't help you with the plotting, though,not my domain.
2

This is what I came up with, but I hope someone comes up with something better.

def plot_complete(v):
     for x1, y1 in v.T:
          for x2, y2, in v.T:
             plt.plot([x1, x2], [y1, y2], 'b')
     plt.plot(v[0], v[1], 'sr')

The 'b' makes the lines blue, and 'sr' marks the points with red squares.

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1 Comment

Bago, thanks - this is basically what I got it down to too. I prefer your cleaner syntax. I am starting to get used to the idea of labelling columns with just the 'for x1, y1 in v.T' syntax.
1

Have figured it out. Basically used simplified syntax provided by @Bago for plotting and considered @Daniel's indexing tip. Just have to iterate through each xy set of points and construct a new set of xx' yy' set of points to use to send to plt.plot():

        viewVX = (v[0]).T #this is if your matrix is 2x100 ie row [0] is x and row[1] is y
        viewVY = (v[1]).T
        for i in range(0, v.shape[1]): #v.shape[1] gives the number of columns
           for j in range(0, v.shape[1]):
              xPoints = viewVX[j], viewVX[i]
              yPoints = viewVY[j], viewVY[i]
              xy = [xPoints, yPoints]         #tuple/array of xx, yy point
              #print("xy points are", xy)
              plt.plot(xy[0],xy[1], ls ='-')
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