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‎examples/ticks_and_spines/date_precision_and_epochs.py‎

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"""
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=========================
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Date Precision and Epochs
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=========================
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Matplotlib can handle `.datetime` objects and `numpy.datetime64` objects using
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a unit converter that recognizes these dates and converts them to floating
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point numbers. By deafult this conversion returns a float that is days
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since "0000-01-01T00:00:00". This has resolution implications for modern
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dates: "2000-01-01" in this time frame is 730120, and a 64-bit floating point
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number has a resolution of 2^{-52}, or approximately 14 microseconds.
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"""
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import datetime
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import dateutil
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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#############################################################################
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# Datetime
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# --------
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#
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# Python `.datetime` objects have microsecond reesolution, so by default
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# matplotlib dates cannot round-trip full-resolution datetime objects:
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date1 = datetime.datetime(2000, 1, 1, 0, 10, 0, 12,
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tzinfo=dateutil.tz.gettz('UTC'))
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mdate1 = mdates.date2num(date1)
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print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1)
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date2 = mdates.num2date(mdate1)
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print('After Roundtrip: ', date2)
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#############################################################################
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# Note this is only a round-off error, and there is no problem for
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# dates closer to the epoch:
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date1 = datetime.datetime(10, 1, 1, 0, 10, 0, 12,
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tzinfo=dateutil.tz.gettz('UTC'))
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mdate1 = mdates.date2num(date1)
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print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1)
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date2 = mdates.num2date(mdate1)
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print('After Roundtrip: ', date2)
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#############################################################################
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# If a user wants to use modern dates at micro-second precision, they
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# can change the epoch.
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mdates.set_epoch('1990-01-01')
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date1 = datetime.datetime(2000, 1, 1, 0, 10, 0, 12,
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tzinfo=dateutil.tz.gettz('UTC'))
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mdate1 = mdates.date2num(date1)
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print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1)
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date2 = mdates.num2date(mdate1)
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print('After Roundtrip: ', date2)
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#############################################################################
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# datetime64
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# ----------
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#
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# `numpy.datetime64` objects have micro-second precision for a much larger
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# timespace than `.datetime` objects. However, currently Matplotlib time is
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# only converted back to datetime objects, which have microsecond resolution,
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# and years that only span 0000 to 9999.
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mdates.set_epoch('1990-01-01')
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date1 = np.datetime64('2000-01-01T00:10:00.000012')
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mdate1 = mdates.date2num(date1)
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print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1)
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date2 = mdates.num2date(mdate1)
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print('After Roundtrip: ', date2)
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#############################################################################
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# Plotting
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# --------
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#
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# This all of course has an effect on plotting. With the default epoch
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# the times are rounded, leading to jumps in the data:
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mdates.set_epoch('0000-01-01')
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x = np.arange('2000-01-01T00:00:00.0', '2000-01-01T00:00:00.000100',
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dtype='datetime64[us]')
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y = np.arange(0, len(x))
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fig, ax = plt.subplots(constrained_layout=True)
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ax.plot(x, y)
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plt.setp(ax.xaxis.get_majorticklabels(), rotation=40)
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plt.show()
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#############################################################################
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# For a more recent epoch, the plot is smooth:
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mdates.set_epoch('1999-01-01')
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fig, ax = plt.subplots(constrained_layout=True)
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ax.plot(x, y)
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plt.setp(ax.xaxis.get_majorticklabels(), rotation=40)
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plt.show()
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#############################################################################
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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matplotlib.dates.num2date
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matplotlib.dates.date2num
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matplotlib.dates.set_epoch

‎lib/matplotlib/dates.py‎

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Matplotlib date format
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----------------------
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Matplotlib represents dates using floating point numbers specifying the number
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of days since 0001-01-01 UTC, plus 1. For example, 0001-01-01, 06:00 is 1.25,
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not 0.25. Values < 1, i.e. dates before 0001-01-01 UTC, are not supported.
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of days since a defaul epoch of 0001-01-01 UTC, plus 1. For example,
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0001-01-01, 06:00 is 1.25, not 0.25. (The epoch can be changed via
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`.dates.set_epoch` to other dates; see
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:doc:`/gallery/misc/date_accuracy_and_epochs` for a discussion.)
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There are a number of helper functions to convert between :mod:`datetime`
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objects and Matplotlib dates:
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date2num
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num2date
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num2timedelta
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epoch2num
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num2epoch
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drange
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set_epoch
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.. note::
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@@ -155,7 +156,7 @@
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import matplotlib.ticker as ticker
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__all__ = ('datestr2num', 'date2num', 'num2date', 'num2timedelta', 'drange',
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'epoch2num', 'num2epoch', 'mx2num', 'DateFormatter',
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'epoch2num', 'num2epoch', 'mx2num', 'set_epoch', 'DateFormatter',
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'ConciseDateFormatter', 'IndexDateFormatter', 'AutoDateFormatter',
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'DateLocator', 'RRuleLocator', 'AutoDateLocator', 'YearLocator',
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'MonthLocator', 'WeekdayLocator',
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MO, TU, WE, TH, FR, SA, SU)
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WEEKDAYS = (MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY, SUNDAY)
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# default epoch: passed to np.datetime64...
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_epoch = '0001-01-01T00:00:00'
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def set_epoch(epoch):
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"""
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Set the epoch (origin for dates) for datetime calculations. The
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default epoch is '0000-01-01T00:00:00', but this means "modern"
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dates only have an accuracy of approximately 8 microseconds in the
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matplotlib floating point representation. Smaller floats means more
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precision, so an epoch within 50 days of the dates being considered
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can reach 1 nanosecond resolution.
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See :doc:`/gallery/misc/date_accuracy_and_epochs` for a discussion.
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Parameters
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----------
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epoch : str
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valid UTC date parsable by `.datetime64` (do not include timezone).
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"""
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global _epoch
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_epoch = epoch
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def get_epoch():
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"""
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Get the epoch currently used by `.dates`.
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Returns
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-------
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epoch: str
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"""
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return _epoch
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def _to_ordinalf(dt):
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"""
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Convert :mod:`datetime` or :mod:`date` to the Gregorian date as UTC float
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# seconds. That should get out to +/-2e11 years.
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dseconds = d.astype('datetime64[s]')
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extra = (d - dseconds).astype('timedelta64[ns]')
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t0 = np.datetime64(_epoch)
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t0 = np.datetime64(_epoch, 's')
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dt = (dseconds - t0).astype(np.float64)
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dt += extra.astype(np.float64) / 1.0e9
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dt = dt / SEC_PER_DAY + 1.0
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timezone *tz*, or if *tz* is ``None``, in the timezone specified in
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:rc:`timezone`.
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"""
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if tz is None:
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tz = _get_rc_timezone()
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dt = (np.datetime64(_epoch) +
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dt = (np.datetime64(_epoch) +
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np.timedelta64(int((x - 1.0) * MUSECONDS_PER_DAY), 'us'))
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if dt < np.datetime64('0001-01-01') or dt > np.datetime64('10000-01-01'):
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raise ValueError(f'Matplotlib date {dt} cannot be converted to a '
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'datetime.')
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dt = dt.tolist()
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# datetime64 is always UTC:
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dt = dt.tolist().replace(tzinfo=dateutil.tz.gettz('UTC'))
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dt = dt.replace(tzinfo=dateutil.tz.gettz('UTC'))
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# but maybe we are working in a different timezone so move.
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dt = dt.astimezone(tz)
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if x > 30 * 365:
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# if x is big, round off to nearest twenty microseconds.
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self.tz = tz
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def __call__(self, x, pos=0):
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if x == 0:
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raise ValueError('DateFormatter found a value of x=0, which is '
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'an illegal date; this usually occurs because '
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'you have not informed the axis that it is '
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'plotting dates, e.g., with ax.xaxis_date()')
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return num2date(x, self.tz).strftime(self.fmt)
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def set_tzinfo(self, tz):
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locator = RRuleLocator(rrule, self.tz)
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else:
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locator = MicrosecondLocator(interval, tz=self.tz)
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if dmin.year > 20 and interval < 1000:
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if date2num(dmin) > 30 * 365 and interval < 1000:
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cbook._warn_external(
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'Plotting microsecond time intervals is not well '
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'supported; please see the MicrosecondLocator '
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'documentation for details.')
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'Plotting microsecond time intervals for dates far from '
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f'the epoch (time origin: {_epoch}) is not well-'
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'supported. See matplotlib.dates.set_epoch to change the '
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'epoch.')
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locator.set_axis(self.axis)
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.. note::
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Due to the floating point representation of time in days since
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0001-01-01 UTC (plus 1), plotting data with microsecond time
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resolution does not work well with current dates.
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By default, Matplotlib uses a floating point representation of time in
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days since 0001-01-01 UTC (plus 1), so plotting data with
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microsecond time resolution does not work well with modern dates.
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If you want microsecond resolution time plots, it is strongly
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recommended to use floating point seconds, not datetime-like
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time representation.
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If you really must use datetime.datetime() or similar and still
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need microsecond precision, your only chance is to use very
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early years; using year 0001 is recommended.
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need microsecond precision, change the time origin via
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`.dates.set_epoch` to something closer to the dates being plotted.
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16881719
"""
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def __init__(self, interval=1, tz=None):
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return self._interval
17451776

17461777

1778+
@cbook.deprecated("3.2")
17471779
def epoch2num(e):
17481780
"""
17491781
Convert an epoch or sequence of epochs to the new date format,
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17521784
return EPOCH_OFFSET + np.asarray(e) / SEC_PER_DAY
17531785

17541786

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@cbook.deprecated("3.2")
17551788
def num2epoch(d):
17561789
"""
17571790
Convert days since 0001 to epoch. *d* can be a number or sequence.

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