I'm trying to visualize graph in NetworkX. I need to colorize the graph like this: center node needs to be colored dark. Then, all nodes that are further away will need to be colored lighter, but when i run the code i get this error :
error: Cannot convert argument type < class 'numpy.ndarray' > to rgba array on the line :
nx.draw_networkx_nodes(G,pos,nodelist=p.keys(),node_size=90,
node_color=p.values(),cmap=plt.cm.Reds_r)
I think the problem is in:
node_color=p.values()
The code is:
import numpy
import pandas
import networkx as nx
import unicodecsv as csv
import community
import matplotlib.pyplot as plt
# Generate the Graph
G=nx.davis_southern_women_graph()
# Create a Spring Layout
pos=nx.spring_layout(G)
# Find the center Node
dmin=1
ncenter=0
for n in pos:
x,y=pos[n]
d=(x-0.5)**2+(y-0.5)**2
if d<dmin:
ncenter=n
dmin=d
""" returns a dictionary of nodes and their distance to the node
supplied as an argument. We will then use these distances
to determine colors"""
p=nx.single_source_shortest_path_length(G,ncenter)
plt.figure(figsize=(8,8))
nx.draw_networkx_edges(G,pos,nodelist=[ncenter],alpha=0.4)
nx.draw_networkx_nodes(G,pos,nodelist=p.keys(),node_size=90,
node_color=p.values(),cmap=plt.cm.Reds_r)
plt.show()
Full Traceback
Traceback (most recent call last):
File "<ipython-input-4-da1414ba5e14>", line 1, in <module>
runfile('C:/Users/Desktop/Marvel/finding_key_players.py', wdir='C:/Users/Desktop/Marvel')
File "C:\Users\Anaconda33\lib\site- packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "C:\Users\Anaconda33\lib\site packages\spyderlib\widgets\externalshell\sitecustomize.py", line 85, in execfile
exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)
File "C:/Users/Desktop/Marvel/finding_key_players.py", line 70, in
<module>
cmap=plt.cm.Reds_r)
File "C:\Users\Anaconda33\lib\site-packages\networkx\drawing\nx_pylab.py", line 399, in draw_networkx_nodes
label=label)
File "C:\Users\Anaconda33\lib\site-packages\matplotlib\axes\_axes.py", line 3606, in scatter
colors = mcolors.colorConverter.to_rgba_array(c, alpha)
File "C:\Users\Anaconda33\lib\site-packages\matplotlib\colors.py", line 391, in to_rgba_array
if alpha > 1 or alpha < 0:
ValueError: Cannot convert argument type <class 'numpy.ndarray'> to rgba array
The error is in the function for drawing nodes.
p.keys()values must be put in a list for nodelist, and node_color, otherwise it's not working.
So the correct line is:
nx.draw_networkx_nodes(G,pos,nodelist=list(p.keys()),node_size=80,node_color=list(p.values()), cmap=plt.cm.Reds_r)
plt.axis('off')
plt.show()
Related
I have a graph having
957267 Number of nodes ;
1860761 Number of edges and
Average degree is 3.8877
G=nx.from_edgelist(edge)
print(nx.info(G))
nx.draw_spring(G)
plt.draw()
plt.show()
till print function, every thing work, but after that when I draw graph, I got the error
All the values in edge list are integers.
I am getting memory error. Though I have 8 GB ram, and SSD hard disk Is there a way to deal with it or alternative of NetworkX
Traceback (most recent call last):
File "", line 1, in
nx.draw_spring(G)
File "C:\ProgramData\Anaconda3\lib\site-packages\networkx\drawing\nx_pylab.py", line 965, in draw_spring
draw(G, spring_layout(G), **kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\networkx\drawing\layout.py", line 333, in fruchterman_reingold_layout
pos = _fruchterman_reingold(A, k, pos_arr, fixed, iterations, dim)
File "C:\ProgramData\Anaconda3\lib\site-packages\networkx\drawing\layout.py", line 388, in _fruchterman_reingold
distance = np.linalg.norm(delta, axis=-1)
File "C:\ProgramData\Anaconda3\lib\site-packages\numpy\linalg\linalg.py", line 2198, in norm
return sqrt(add.reduce(s, axis=axis, keepdims=keepdims))
MemoryError
I am trying to add start points to a streamline plot. I found an example code using start points here; at this link a different issue is discussed but the start_points argument works. From here I grabbed the streamline example code (images_contours_and_fields example code: streamplot_demo_features.py). I don't understand why I can define start points in one code and not the other. I get the following error when I try to define start points in the example code (streamplot_demo_features.py):
Traceback (most recent call last):
File "<ipython-input-79-981cad64cff6>", line 1, in <module>
runfile('C:/Users/Admin/.spyder/StreamlineExample.py', wdir='C:/Users/Admin/.spyder')
File "C:\ProgramData\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 866, in runfile
execfile(filename, namespace)
File "C:\ProgramData\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 87, in execfile
exec(compile(scripttext, filename, 'exec'), glob, loc)
File "C:/Users/Admin/.spyder/StreamlineExample.py", line 28, in <module>
ax1.streamplot(X, Y, U, V,start_points=start_points)
File "C:\ProgramData\Anaconda2\lib\site-packages\matplotlib\__init__.py", line 1891, in inner
return func(ax, *args, **kwargs)
File "C:\ProgramData\Anaconda2\lib\site-packages\matplotlib\axes\_axes.py", line 4620, in streamplot
zorder=zorder)
File "C:\ProgramData\Anaconda2\lib\site-packages\matplotlib\streamplot.py", line 144, in streamplot
sp2[:, 0] += np.abs(x[0])
ValueError: non-broadcastable output operand with shape (1,) doesn't match the broadcast shape (100,)
I've notice there isn't much on the web in way of using start_points, so any additional information would be helpful.
The main difference between the example that successfully uses start_points and the example from the matplotlib page is that the first uses 1D arrays as x and y grid, whereas the official example uses 2D arrays.
Since the documentation explicitely states
x, y : 1d arrays, an evenly spaced grid.
we might stick to 1D arrays. It's unclear why the example contradicts the docsting, but we can simply ignore that.
Now, using 1D arrays as grid, start_points works as expected in that it takes a 2-column array (first column x-coords, second y-coords).
A complete example:
import numpy as np
import matplotlib.pyplot as plt
x,y = np.linspace(-3,3,100),np.linspace(-3,3,100)
X,Y = np.meshgrid(x,y)
U = -1 - X**2 + Y
V = 1 + X - Y**2
speed = np.sqrt(U*U + V*V)
start = [[0,0], [1,2]]
fig0, ax0 = plt.subplots()
strm = ax0.streamplot(x,y, U, V, color=(.75,.90,.93))
strmS = ax0.streamplot(x,y, U, V, start_points=start, color="crimson", linewidth=2)
plt.show()
I'm trying to write a short script that takes a .csv file with some distance data, and outputs the psd file for it. the code is here:
import math
import matplotlib.pyplot as plt
name = raw_input('File:')
data = open(name + '.csv', 'r')
distances = []
for row in data:
distances.append(row.replace("\n",""))
for i in range(len(distances)):
distances[i] = float(distances[i])
Pxx, freqs = plt.psd(distances, NFFT=16,Fs=2,detrend='detrend_mean',window='window_none',noverlap=128,sides='onesided',scale_by_freq=True)
plot(Pxx,freqs)
plt.savefig(name + 'psd.png', bbox_inches = 'tight')
As you can see, it's pretty simple. the csv file just features one column of numbers, so distances is a vector.
The error I'm getting is as follows:
Traceback (most recent call last):
File "C:psdplot.py", line 15, in <module>
Pxx, freqs = plt.psd(distances, NFFT=16,Fs=2,detrend='detrend_mean',window='window_none',noverlap=128,sides='onesided',scale_by_freq=True)
File "C:\Python27\lib\site-packages\matplotlib\pyplot.py", line 3029, in psd
sides=sides, scale_by_freq=scale_by_freq, **kwargs)
File "C:\Python27\lib\site-packages\matplotlib\axes.py", line 8696, in psd
sides, scale_by_freq)
File "C:\Python27\lib\site-packages\matplotlib\mlab.py", line 389, in psd
scale_by_freq)
File "C:\Python27\lib\site-packages\matplotlib\mlab.py", line 423, in csd
noverlap, pad_to, sides, scale_by_freq)
File "C:\Python27\lib\site-packages\matplotlib\mlab.py", line 251, in _spectral_helper
assert(len(window) == NFFT)
AssertionError
Could someone direct me on how to fix this? I'm sure it's rather obvious, but I haven't been able to find anything on fixing it in this particular context.
Thanks in advance!
I am interpolating data from satellite imagery. My initial data is not on a regular grid. The data e.g. ch1 refers to positions given by longitude and latitude. When I try nearest neighbour interpolation the result I get is good.
from scipy import interpolate
lats = np.arange(latitude.max(), latitude.min(),-.1)
lons = np.arange(longitude.min(),longitude.max(),.1)
all_lon,all_lat = np.meshgrid(lons,lats)
ch1_all = interpolate.griddata((longitude.reshape(-1),latitude.reshape(-1)),ch1.reshape(-1),(all_lon,all_lat),'nearest')
However when I request bilinear interpolation I raise a Qhull error.
ch1_all = interpolate.griddata((longitude.reshape(-1),latitude.reshape(-1)),ch1.reshape(-1),(all_lon,all_lat),'linear')
The error I get is:
Traceback (most recent call last):
File "<interactive input>", line 1, in <module>
File "C:\Python27\lib\site-packages\scipy\interpolate\ndgriddata.py", line 206, in griddata
rescale=rescale)
File "interpnd.pyx", line 239, in scipy.interpolate.interpnd.LinearNDInterpolator.__init__ (scipy\interpolate\interpnd.c:4549)
File "qhull.pyx", line 1736, in scipy.spatial.qhull.Delaunay.__init__ (scipy\spatial\qhull.c:13719)
File "qhull.pyx", line 328, in scipy.spatial.qhull._Qhull.__init__ (scipy\spatial\qhull.c:3602)
QhullError: Qhull error
I have read the post at griddata runtime error -- Python / SciPy (Interpolation) but in my case, it interpolates data with one method but not with the other.
What am I doing wrong?
In the image below I have plotted the final point positions (red) and overlaid the initial positions (blue)
I am trying to follow a tutorial on youtube, now in the tutorial they plot some standard text files using matplotlib.pyplot, I can achieve this easy enough, however I am now trying to perform the same thing using some csvs I have of real data.
The code I am using is import matplotlib.pyplot as plt
import csv
#import numpy as np
with open(r"Example RFI regression axis\Delta RFI.csv") as x, open(r"Example RFI regression axis\strikerate.csv") as y:
readx = csv.reader(x)
ready = csv.reader(y)
plt.plot(readx,ready)
plt.title ('Test graph')
plt.xlabel('x axis')
plt.ylabel('y axis')
plt.show()
The traceback I receive is long
Traceback (most recent call last):
File "C:\V4 code snippets\matplotlib_test.py", line 11, in <module>
plt.plot(readx,ready)
File "C:\Python27\lib\site-packages\matplotlib\pyplot.py", line 2832, in plot
ret = ax.plot(*args, **kwargs)
File "C:\Python27\lib\site-packages\matplotlib\axes.py", line 3997, in plot
self.add_line(line)
File "C:\Python27\lib\site-packages\matplotlib\axes.py", line 1507, in add_line
self._update_line_limits(line)
File "C:\Python27\lib\site-packages\matplotlib\axes.py", line 1516, in _update_line_limits
path = line.get_path()
File "C:\Python27\lib\site-packages\matplotlib\lines.py", line 677, in get_path
self.recache()
File "C:\Python27\lib\site-packages\matplotlib\lines.py", line 401, in recache
x = np.asarray(xconv, np.float_)
File "C:\Python27\lib\site-packages\numpy\core\numeric.py", line 320, in asarray
return array(a, dtype, copy=False, order=order)
TypeError: float() argument must be a string or a number
Please advise what I need to do, I realise this is probably very easy to most seasoned coders. Kind regards SMNALLY
csv.reader() returns strings (technically, .next()method of reader object returns lists of strings). Without converting them to float or int, you won't be able to plt.plot() them.
To save the trouble of converting, I suggest using genfromtxt() from numpy. (http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html)
For example, there are two files:
data1.csv:
data1
2
3
4
3
6
6
4
and data2.csv:
data2
92
73
64
53
16
26
74
Both of them have one line of header. We can do:
import numpy as np
data1=np.genfromtxt('data1.csv', skip_header=1) #suppose it is in the current working directory
data2=np.genfromtxt('data2.csv', skip_header=1)
plt.plot(data1, data2,'o-')
and the result: