.AutoDateFormatter
has a .scale
dictionary that maps tick scales (the interval in days between one major tick) to format strings; this dictionary defaults to :
self.scaled = {
DAYS_PER_YEAR: rcParams['date.autoformat.year'],
DAYS_PER_MONTH: rcParams['date.autoformat.month'],
1: rcParams['date.autoformat.day'],
1 / HOURS_PER_DAY: rcParams['date.autoformat.hour'],
1 / MINUTES_PER_DAY: rcParams['date.autoformat.minute'],
1 / SEC_PER_DAY: rcParams['date.autoformat.second'],
1 / MUSECONDS_PER_DAY: rcParams['date.autoformat.microsecond'],
}
The formatter uses the format string corresponding to the lowest key in the dictionary that is greater or equal to the current scale. Dictionary entries can be customized:
locator = AutoDateLocator() formatter = AutoDateFormatter(locator) formatter.scaled[1/(24*60)] = '%M:%S' # only show min and sec
Custom callables can also be used instead of format strings. The following example shows how to use a custom format function to strip trailing zeros from decimal seconds and adds the date to the first ticklabel:
def my_format_function(x, pos=None):
x = matplotlib.dates.num2date(x)
if pos == 0:
fmt = '%D %H:%M:%S.%f'
else:
fmt = '%H:%M:%S.%f'
label = x.strftime(fmt)
label = label.rstrip("0")
label = label.rstrip(".")
return label
formatter.scaled[1/(24*60)] = my_format_function
A .Formatter
which attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator
.
The following pages refer to to this document either explicitly or contain code examples using this.
matplotlib.dates.AutoDateFormatter
matplotlib.axes._axes.Axes.plot_date
matplotlib.pyplot.plot_date
matplotlib.dates.AutoDateLocator.__init__
matplotlib.dates
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