[FIXED] ObsPy Plot Beachball in Time Series

Issue

I am trying to plot an ObsPy (or any python) seismic focal mechanism in time series.

import matplotlib.pyplot as plt
import datetime
import numpy as np
from obspy.imaging.beachball import Beach

# x = np.arange(0,100,4)
x = np.array([datetime.datetime(2013, 9, 28, i, 0) for i in range(24)])
y = np.random.randint(100, size=x.shape)

fig, ax = plt.subplots(figsize=(10,6))
ax.plot(x,y)

bball = Beach([70, 90, 80], xy=(x[10],y[10]), width=5, linewidth=1, alpha=0.85)

bball.set_zorder(1)
ax.add_collection(bball)
plt.show()

When using an integer/float series for x it works fine, but the time series fails here:

Traceback (most recent call last):
  File "./beachballs.py", line 15, in <module>
    bball = Beach([70, 90, 80], xy=(x[10],y[10]), width=5, linewidth=1, alpha=0.85)
  File "/usr/local/lib/python3.3/site-packages/obspy-0.9.2_787_gf176-py3.3-linux-x86_64.egg/obspy/imaging/beachball.py", line 119, in Beach
    colors, p = plotDC(np1, size=size, xy=xy, width=width)
  File "/usr/local/lib/python3.3/site-packages/obspy-0.9.2_787_gf176-py3.3-linux-x86_64.egg/obspy/imaging/beachball.py", line 645, in plotDC
    collect.append(xy2patch(Y, X, res, xy))
  File "/usr/local/lib/python3.3/site-packages/obspy-0.9.2_787_gf176-py3.3-linux-x86_64.egg/obspy/imaging/beachball.py", line 656, in xy2patch
    x = x * res[0] + xy[0]
TypeError: unsupported operand type(s) for +: 'float' and 'datetime.datetime'

The function xy2patch in the source code is trying to scale the time by a float value.

Any ideas? Hack the source? Other packages? Thanks.

Solution

Found it. Convert times to matplotlib float representation.

import matplotlib.pyplot as plt
import datetime
import numpy as np
from obspy.imaging.beachball import Beach
from matplotlib.dates import date2num

# x = np.arange(0,100,4)

x = date2num(np.array([datetime.datetime(2013, 9, 28, i, 0) for i in range(24)]))
y = np.random.randint(100, size=x.shape)

fig, ax = plt.subplots(figsize=(10,6))
ax.plot(x,y)

bball = Beach([70, 90, 80], xy=(x[10],y[10]), width=(.1,15), linewidth=1, alpha=0.85)

bball.set_zorder(1)
ax.add_collection(bball)
plt.show()

Answered By - skytaker