Sometimes the data have a gap between the start of the validation period and the start of the data. Attached is a stand-alone Python script that demonstrates the problem, along with the plot that the script produces.
April 20 is the start of the validation period. I want 04-20 to appear at the plot origin. This does not happen unless either the model or observed dictionary contain a key/value pair for 1998,4,20,0. I tried adding datetime(1998,4,20,0):None to one or both dictionaries, but it is ignored.
Also the minor tick marks do not look right, especially the ones just to the right of each x-axis label.
Do you have any suggestions? Thanks, AnnI am working on a Windows PC; O/S is Windows XP Professional, Version 2002, Service Pack 3. I am running matplotlib, version '0.99.0' which I obtained from the matplotlib Sourceforge site.
I have not customized matplotlibrc. I am running python version 2.6.2.Attached is output.txt, the result of running my script with a verbose-helpful
<<inline: test_plot.png>>
import pylab
from datetime import datetime
from matplotlib.dates import date2num,DayLocator,HourLocator,DateFormatter
from matplotlib.pyplot import close
def test_plot():
'''
test_plot.py
Test code: How to get x-axis labeling to start at the plot origin?
USE
test_plot()
'''
model={datetime(1998,4,20,1):19.7,datetime(1998,4,21):42.2,datetime(1998,4,22):8.4,datetime(1998,4,23):28.2,datetime(1998,4,24):21.5}
observed={datetime(1998,4,20,1):20.1,datetime(1998,4,21):40.2,datetime(1998,4,22):10.4,datetime(1998,4,23):30.2,datetime(1998,4,24):22.5}
observed_keys=observed.keys()
observed_keys.sort()
observed_values=[]
for timetag in observed_keys:
observed_values.append(observed[timetag])
model_keys=model.keys()
model_keys.sort()
model_values=[]
for timetag in model_keys:
model_values.append(model[timetag])
fig=pylab.figure(facecolor='w')
ax=fig.add_subplot(111)
ax.plot_date(date2num(observed_keys),observed_values,'-',color='black')
ax.plot_date(date2num(model_keys),model_values,'-',color='red')
days=DayLocator() #major ticks will be on each day of the month
hours=HourLocator(interval=6) #minor ticks will be every 6 hours
daysFmt=DateFormatter('%m-%d') #x-axis major tick labels for plot
# format the ticks
ax.xaxis.set_major_locator(days) # major x-axis ticks
ax.xaxis.set_major_formatter(daysFmt) #x-axis major tick labels
ax.xaxis.set_minor_locator(hours) #minor x-axis ticks
ax.fmt_xdata = DateFormatter('%m-%d')
fig.autofmt_xdate(rotation=-30, ha='left') #rotate and right align the
xaxis labels
pylab.legend(('obs','model'),labelspacing = 0.005,loc='upper right')
pylab.show()
raw_input("press return to continue")
close() #close the figure.
return 1
if __name__ == '__main__':
test_plot()
$HOME=C:\Documents and Settings\ann.newman CONFIGDIR=C:\Documents and Settings\ann.newman\.matplotlib matplotlib data path C:\Python26\lib\site-packages\matplotlib\mpl-data loaded rc file C:\Python26\lib\site-packages\matplotlib\mpl-data\matplotlibrc matplotlib version 0.99.0 verbose.level helpful interactive is False units is False platform is win32 Using fontManager instance from C:\Documents and Settings\ann.newman\.matplotlib\fontList.cache backend TkAgg version 8.5 findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=medium to Bitstream Vera Sans (C:\Python26\lib\site-packages\matplotlib\mpl-data\fonts\ttf\Vera.ttf) with score of 0.000000 findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=large to Bitstream Vera Sans (C:\Python26\lib\site-packages\matplotlib\mpl-data\fonts\ttf\Vera.ttf) with score of 0.000000 press return to continue
<<attachment: Ann_Newman.vcf>>
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