Is there an interactive graphing library for python

Question

I\'m looking for an interactive graphing library for Python.

By \"graph\", I meant a set of nodes connected by a set of vertices (not a plot of values over x-y axis, no

Answer 1

I have the same problem. In the end, I think nodebox opengl seems to do the trick. Don't try to use the graph library at the following link

http://nodebox.net/code/index.php/Graph

with nodebox opengl. It doesn't work, that graph library is only compatible with the mac OSX nodebox. But in anycase that is ok because you don't need it.

See for example the following question:

Adding label to an edge of a graph in nodebox opnegl

It shows example code which works for me, the code can be modified so that clicking on a node not only allows you to move the node, but also allows you to modify the graph.

Just delete

label = "Placeholder"

from the code and it works.

EDIT:

I put some more detailed example code here: Nodebox open GL Graph, size function not recognized. (Ubuntu)

Answer 2

You should definitely look at the igraph library if you haven't.

It's a powerful library that can handle large graphs and different layout styles. It can also be used for directed graphs and for interactive and non-interactive visualitzations in 2D and 3D according to the list of features. There is also a tutorial.

Update: Another well-known library is NetworkX for which there are Python packages here. Note that the Mac/Windows software Nodebox, recommended by Acorn, uses NetworkX algorithms.

Answer 3

Looks like Nodebox might be what you want:

http://nodebox.net/code/index.php/Graph Mac OSX

http://www.cityinabottle.org/nodebox/ Windows (using OpenGL)

The graph object has functionality for mouse interaction as well, bundled in the graph.events object. It has the following properties:

• graph.events.hovered: None or the node over which the mouse hovers.
• graph.events.pressed: None or the node on which the mouse is pressing down.
• graph.events.dragged: None or the node being dragged.
• graph.events.clicked: None or the last node clicked.
• graph.events.popup: when True, will display a popup window over the hovered node.

---

Also came accross Gephi, looks like that might have the functionality you want as well.

http://gephi.org/ Windows, Linux and Mac OSX

Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.

Answer 4

I thought and tried all the solutions given in this question and finally end up with the following solution.

I think the best scalable solution is using interactive mode of Matplotlib together with networkx. The following code segment explain how to display an annotation of a datapoint for a mouse click. Since we are using Networkx, this solution was much more scalable than anticipated.

import networkx as nx
import matplotlib.pyplot as plt
import nx_altair as nxa
from pylab import *

class AnnoteFinder:  # thanks to http://www.scipy.org/Cookbook/Matplotlib/Interactive_Plotting
    """
    callback for matplotlib to visit a node (display an annotation) when points are clicked on.  The
    point which is closest to the click and within xtol and ytol is identified.
    """
    def __init__(self, xdata, ydata, annotes, axis=None, xtol=None, ytol=None):
        self.data = list(zip(xdata, ydata, annotes))
        if xtol is None: xtol = ((max(xdata) - min(xdata))/float(len(xdata)))/2
        if ytol is None: ytol = ((max(ydata) - min(ydata))/float(len(ydata)))/2
        self.xtol = xtol
        self.ytol = ytol
        if axis is None: axis = gca()
        self.axis= axis
        self.drawnAnnotations = {}
        self.links = []

    def __call__(self, event):
        if event.inaxes:
            clickX = event.xdata
            clickY = event.ydata
            print(dir(event),event.key)
            if self.axis is None or self.axis==event.inaxes:
                annotes = []
                smallest_x_dist = float('inf')
                smallest_y_dist = float('inf')

                for x,y,a in self.data:
                    if abs(clickX-x)<=smallest_x_dist and abs(clickY-y)<=smallest_y_dist :
                        dx, dy = x - clickX, y - clickY
                        annotes.append((dx*dx+dy*dy,x,y, a) )
                        smallest_x_dist=abs(clickX-x)
                        smallest_y_dist=abs(clickY-y)
                        print(annotes,'annotate')
                    # if  clickX-self.xtol < x < clickX+self.xtol and  clickY-self.ytol < y < clickY+self.ytol :
                    #     dx,dy=x-clickX,y-clickY
                    #     annotes.append((dx*dx+dy*dy,x,y, a) )
                print(annotes,clickX,clickY,self.xtol,self.ytol )
                if annotes:
                    annotes.sort() # to select the nearest node
                    distance, x, y, annote = annotes[0]
                    self.drawAnnote(event.inaxes, x, y, annote)

    def drawAnnote(self, axis, x, y, annote):
        if (x, y) in self.drawnAnnotations:
            markers = self.drawnAnnotations[(x, y)]
            for m in markers:
                m.set_visible(not m.get_visible())
            self.axis.figure.canvas.draw()
        else:
            t = axis.text(x, y, "%s" % (annote), )
            m = axis.scatter([x], [y], marker='d', c='r', zorder=100)
            self.drawnAnnotations[(x, y)] = (t, m)
            self.axis.figure.canvas.draw()

df = pd.DataFrame('LOAD YOUR DATA')

# Build your graph
G = nx.from_pandas_edgelist(df, 'from', 'to')
pos = nx.spring_layout(G,k=0.1, iterations=20)  # the layout gives us the nodes position x,y,annotes=[],[],[] for key in pos:
x, y, annotes = [], [], []
for key in pos:
    d = pos[key]
    annotes.append(key)
    x.append(d[0])
    y.append(d[1])

fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111)
ax.set_title('select nodes to navigate there')

nx.draw(G, pos, font_size=6,node_color='#A0CBE2', edge_color='#BB0000', width=0.1,
                  node_size=2,with_labels=True)


af = AnnoteFinder(x, y, annotes)
connect('button_press_event', af)

show()