Thanks for your help, I simplified what I was doing and so changed the data,
which is my fault. Here is some data of similar size to the data I am
plotting:
data1 = np.array([22000, 25000, 27000, 32000, 25000])
data2 = np.array([14000000, 22000000, 3500000, 3000000, 2700000])
When I try to run this with the above code I get a very strange graph and
these errors:
> In [16]: run t.py
> Warning: overflow encountered in long_scalars
> Warning: overflow encountered in long_scalars
> Warning: overflow encountered in long_scalars
> Warning: overflow encountered in long_scalars
> Warning: invalid value encountered in sqrt
>
So then tried the same method using the annotation as suggested (code below)
which worked perfectly.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.ticker import FuncFormatter
labels=('91','92','93','94','95')
data1 = np.array([22000, 25000, 27000, 32000, 25000])
data2 = np.array([14000000, 22000000, 3500000, 3000000, 2700000])
fig = plt.figure()
ax = fig.add_subplot(111)
# the next line is only use to set the proper lims,
p = ax.plot(data1, data2, 'bo', linestyle='-', markersize=3, alpha=0)
for x,y,dx,dy in zip(data1[:-1], data2[:-1], data1[1:], data2[1:]):
ax.annotate('', xy=(dx,dy), xycoords='data',
xytext=(x,y), textcoords='data',
arrowprops=dict(arrowstyle="->"))
ax.set_xlim(21000,33000)
for i, label in enumerate(labels):
x_loc = data1[i]
y_loc = data2[i]
txt = ax.annotate(label, xy=(x_loc, y_loc), size=8,
xytext=(-10, 10), textcoords='offset points',
arrowprops=None)
plt.show()
Just in case someone else has a similar problem.
Thanks
Catherine
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