""" ========================= Date Precision and Epochs ========================= Matplotlib can handle `.datetime` objects and `numpy.datetime64` objects using a unit converter that recognizes these dates and converts them to floating point numbers. Before Matplotlib 3.3, the default for this conversion returns a float that was days since "0000-12-31T00:00:00". As of Matplotlib 3.3, the default is days from "1970-01-01T00:00:00". This allows more resolution for modern dates. "2020-01-01" with the old epoch converted to 730120, and a 64-bit floating point number has a resolution of 2^{-52}, or approximately 14 microseconds, so microsecond precision was lost. With the new default epoch "2020-01-01" is 10957.0, so the achievable resolution is 0.21 microseconds. """ import datetime import numpy as np import matplotlib import matplotlib.pyplot as plt import matplotlib.dates as mdates def _reset_epoch_for_tutorial(): """ Users (and downstream libraries) should not use the private method of resetting the epoch. """ mdates._reset_epoch_test_example() ############################################################################# # Datetime # -------- # # Python `.datetime` objects have microsecond resolution, so with the # old default matplotlib dates could not round-trip full-resolution datetime # objects. old_epoch = '0000-12-31T00:00:00' new_epoch = '1970-01-01T00:00:00' _reset_epoch_for_tutorial() # Don't do this. Just for this tutorial. mdates.set_epoch(old_epoch) # old epoch (pre MPL 3.3) date1 = datetime.datetime(2000, 1, 1, 0, 10, 0, 12, tzinfo=datetime.timezone.utc) mdate1 = mdates.date2num(date1) print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1) date2 = mdates.num2date(mdate1) print('After Roundtrip: ', date2) ############################################################################# # Note this is only a round-off error, and there is no problem for # dates closer to the old epoch: date1 = datetime.datetime(10, 1, 1, 0, 10, 0, 12, tzinfo=datetime.timezone.utc) mdate1 = mdates.date2num(date1) print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1) date2 = mdates.num2date(mdate1) print('After Roundtrip: ', date2) ############################################################################# # If a user wants to use modern dates at microsecond precision, they # can change the epoch using `~.set_epoch`. However, the epoch has to be # set before any date operations to prevent confusion between different # epochs. Trying to change the epoch later will raise a `RuntimeError`. try: mdates.set_epoch(new_epoch) # this is the new MPL 3.3 default. except RuntimeError as e: print('RuntimeError:', str(e)) ############################################################################# # For this tutorial, we reset the sentinel using a private method, but users # should just set the epoch once, if at all. _reset_epoch_for_tutorial() # Just being done for this tutorial. mdates.set_epoch(new_epoch) date1 = datetime.datetime(2020, 1, 1, 0, 10, 0, 12, tzinfo=datetime.timezone.utc) mdate1 = mdates.date2num(date1) print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1) date2 = mdates.num2date(mdate1) print('After Roundtrip: ', date2) ############################################################################# # datetime64 # ---------- # # `numpy.datetime64` objects have microsecond precision for a much larger # timespace than `.datetime` objects. However, currently Matplotlib time is # only converted back to datetime objects, which have microsecond resolution, # and years that only span 0000 to 9999. _reset_epoch_for_tutorial() # Don't do this. Just for this tutorial. mdates.set_epoch(new_epoch) date1 = np.datetime64('2000-01-01T00:10:00.000012') mdate1 = mdates.date2num(date1) print('Before Roundtrip: ', date1, 'Matplotlib date:', mdate1) date2 = mdates.num2date(mdate1) print('After Roundtrip: ', date2) ############################################################################# # Plotting # -------- # # This all of course has an effect on plotting. With the old default epoch # the times were rounded, leading to jumps in the data: _reset_epoch_for_tutorial() # Don't do this. Just for this tutorial. mdates.set_epoch(old_epoch) x = np.arange('2000-01-01T00:00:00.0', '2000-01-01T00:00:00.000100', dtype='datetime64[us]') y = np.arange(0, len(x)) fig, ax = plt.subplots(constrained_layout=True) ax.plot(x, y) ax.set_title('Epoch: ' + mdates.get_epoch()) plt.setp(ax.xaxis.get_majorticklabels(), rotation=40) plt.show() ############################################################################# # For a more recent epoch, the plot is smooth: _reset_epoch_for_tutorial() # Don't do this. Just for this tutorial. mdates.set_epoch(new_epoch) fig, ax = plt.subplots(constrained_layout=True) ax.plot(x, y) ax.set_title('Epoch: ' + mdates.get_epoch()) plt.setp(ax.xaxis.get_majorticklabels(), rotation=40) plt.show() _reset_epoch_for_tutorial() # Don't do this. Just for this tutorial. ############################################################################# # ------------ # # References # """""""""" # # The use of the following functions, methods and classes is shown # in this example: matplotlib.dates.num2date matplotlib.dates.date2num matplotlib.dates.set_epoch