I've been plotting timeseries data using the matplotlib.dates module and have
come across an issue when using it in conjunction with the subplot command.
For figures with greater than one subplot in a particular column, the time (or
x) axis ticks and their labels are only printed on the final subplot that is
plotted, and are missing on all other subplots in that column (see example code
below). The only exception is when the time axis is identical for each plot in
the column (you can test this by editing my example code at ###) - then all
time axis ticks and their labels are displayed correctly.
Is this a bug in the subplot source code, or am I missing something?
from pylab import *
from matplotlib.dates import YEARLY, DateFormatter, rrulewrapper, RRuleLocator,
drange
import datetime
# tick every 5th easter #
rule = rrulewrapper(YEARLY, byeaster=1, interval=5)
loc = RRuleLocator(rule)
formatter = DateFormatter('%m/%d/%y')
# data for subplot 1 #
date1 = datetime.date( 1952, 1, 1 )
date2 = datetime.date( 2004, 4, 12 )
delta = datetime.timedelta(days=100)
dates = drange(date1, date2, delta)
s = rand(len(dates)) # make up some random y values
# plot subplot 1 #
ax1 = subplot(211)
plot_date(dates, s)
ax1.xaxis.set_major_locator(loc)
ax1.xaxis.set_major_formatter(formatter)
labels = ax1.get_xticklabels()
setp(labels, rotation=30, fontsize=10)
# data for subplot 2 #
date1 = datetime.date( 2052, 1, 1 ) ###( 1952, 1, 1 )
date2 = datetime.date( 2104, 4, 12 ) ###( 2004, 4, 12 )
dates = drange(date1, date2, delta)
s = rand(len(dates)) # make up some random y values
# plot subplot 2 #
ax2 = subplot(212)
plot_date(dates, s)
ax2.xaxis.set_major_locator(loc)
ax2.xaxis.set_major_formatter(formatter)
labels = ax2.get_xticklabels()
setp(labels, rotation=30, fontsize=10)
show()------------------------------------------------------------------------------
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