How to decrease resolution of xticks when showing clock
Labels on the x-axis show the time in hours of the day. Whenever I get closer to the plot, they look silly with six decimal places at 0. I'm not interested in showing microseconds at all.
See the xticks shortcuts before the increase:
After scaling:
Here's what I have today:
ax_average.xaxis_date()
fig_average.autofmt_xdate()
fig_average.tight_layout()
How can I make sure that only seconds (or even best minutes) are displayed on the labels?
Here's a slightly smaller version of the code shown above:
# Requires python-matplotlib
import numpy
from pylab import *
raw_data = [
'Apr 20 12:14:36 a b temp_0 = 21.400000',
'Apr 20 12:14:36 a b temp_1 = 17.860000',
'Apr 20 12:14:36 a b temp_3 = 50.350006',
'Apr 20 12:14:51 a b temp_0 = 21.400000',
'Apr 20 12:14:51 a b temp_1 = 17.860000',
'Apr 20 12:14:51 a b temp_3 = 50.350006',
'Apr 20 12:15:06 a b temp_0 = 21.400000',
'Apr 20 12:15:06 a b temp_1 = 17.860000',
'Apr 20 12:15:06 a b temp_3 = 50.250000',
'Apr 20 12:15:21 a b temp_0 = 21.400000',
'Apr 20 12:15:21 a b temp_1 = 17.860000',
'Apr 20 12:15:21 a b temp_3 = 50.250000']
def month_string_to_int(input):
if (input == 'Jan'):
return 1
elif (input == 'Feb'):
return 2
elif (input == 'Mar'):
return 3
elif (input == 'Apr'):
return 4
elif (input == 'May'):
return 5
elif (input == 'Jun'):
return 6
elif (input == 'Jul'):
return 7
elif (input == 'Aug'):
return 8
elif (input == 'Sep'):
return 9
elif (input == 'Oct'):
return 10
elif (input == 'Nov'):
return 11
elif (input == 'Dev'):
return 12
else:
print "Error in the month string: %s" % input
return -1
data = {}
timestamps = {}
for line in raw_data:
line = line.strip() # strip newline character
lst = line.split() # space as separator
day = datetime.date(2015, month_string_to_int(lst[0]), int(lst[1]))
time = datetime.datetime.strptime(lst[2], "%H:%M:%S").time()
timestamp = datetime.datetime.combine(day, time)
identifier = lst[5]
value = float(lst[7])
if identifier not in data:
data[identifier] = []
timestamps[identifier] = []
data[identifier].append(value)
timestamps[identifier].append(timestamp)
fig, ax = subplots()
plot(timestamps['temp_0'], data['temp_0'])
ax.xaxis_date()
fig.autofmt_xdate()
fig.tight_layout()
show()
The dictionary timestamps
looks like what I expect:
In [103]: timestamps
Out[103]:
{'temp_0': [datetime.datetime(2015, 4, 20, 12, 14, 36),
datetime.datetime(2015, 4, 20, 12, 14, 51),
datetime.datetime(2015, 4, 20, 12, 15, 6),
datetime.datetime(2015, 4, 20, 12, 15, 21)],
'temp_1': [datetime.datetime(2015, 4, 20, 12, 14, 36),
datetime.datetime(2015, 4, 20, 12, 14, 51),
datetime.datetime(2015, 4, 20, 12, 15, 6),
datetime.datetime(2015, 4, 20, 12, 15, 21)],
'temp_3': [datetime.datetime(2015, 4, 20, 12, 14, 36),
datetime.datetime(2015, 4, 20, 12, 14, 51),
datetime.datetime(2015, 4, 20, 12, 15, 6),
datetime.datetime(2015, 4, 20, 12, 15, 21)]}
The xticks labels look like this:
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I finally found this:
ax.xaxis.set_major_formatter(DateFormatter('%H:%M'))
here .
Better yet, as the above solution no longer displays the days when zoomed out:
from matplotlib.dates import AutoDateFormatter, AutoDateLocator
xtick_locator = AutoDateLocator()
xtick_formatter = AutoDateFormatter(xtick_locator)
xtick_formatter.scaled[30.] = '%d %b'
xtick_formatter.scaled[1.] = '%d %b'
xtick_formatter.scaled[1/24.] = '%d/%m %H:%M'
xtick_formatter.scaled[1/(24.*60.)] = '%d/%m %H:%M'
xtick_formatter.scaled[1/(24.*60.*60.)] = '%d/%m %H:%M:%S'
ax_av.xaxis.set_major_locator(xtick_locator)
ax_av.xaxis.set_major_formatter(xtick_formatter)
This helped a lot (although the no-argument example for AutoDateFormatter
doesn't work for me)
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