Ryan,
I should clarify my color issue. Your code is smart enough to generate
however many colors are needed but I want to make sure the colors are all
unique.
Thanks again!
Mike
Mike, sorry to send this twice... I should have sent it to the list as
well...
_______________________________
Mike,
If your locations were integers or floats rather than strings, you could
just change the scatter call to the following:
ax.scatter(dates,IDs,c=
locations,marker='d')
I don't know about a legend... I don't know if that is possible with a
scatter plot (?). Because scatter plots get their colors based off of a
color map, you could generate a color bar for your data. You may need to
capture the collection object returned from the scatter plot function call,
though. Here's your code with these modifications:
# Of course, you need to change your locations list to integers rather than
strings.
fig = plt.figure()
ax = fig.add_subplot(111)
sc = ax.scatter(dates,IDs,c=locations,marker='d')
ax.xaxis_date()
fig.autofmt_xdate()
plt.colorbar(sc)
plt.grid(True)
plt.show()
If you really need a legend, then you could do a loop of plot commands for
each set of unique locations. Using some fancy Numpy masking makes the
process easier...
import numpy as np
import matplotlib.pyplot as plt
IDs = np.array([47, 33, 47, 12, 50, 50, 27, 27, 16, 27])
locations = np.array(['201', '207', '207', '205', '204', '201', '209',
'209', \
'207','207'])
dates = np.array([ 733315.83240741, 733315.83521991, 733315.83681713,
733315.83788194, 733336.54554398, 733336.54731481,
733337.99842593, 733337.99943287, 733338.00070602,
733338.00252315])
fig = plt.figure()
ax = fig.add_subplot(111)
cs = ['r', 'b', 'g', 'k', 'c']
for n, i in enumerate(np.unique(locations)):
ax.plot(dates[locations==i],IDs[locations==i],'d', c=cs[n%len(cs)],
label=i)
ax.xaxis_date()
fig.autofmt_xdate()
plt.legend(numpoints=1)
plt.grid(True)
plt.show()
Not sure if this is exactly what you wanted, but I hope it helps a little.
Ryan
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