"""
=========================
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.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 during the internal ``date2num`` conversion, 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]')
# simulate the plot being made using the old epoch
xold = np.array([mdates.num2date(mdates.date2num(d)) for d in x])
y = np.arange(0, len(x))

# resetting the Epoch so plots are comparable
_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(xold, y)
ax.set_title('Epoch: ' + mdates.get_epoch())
ax.xaxis.set_tick_params(rotation=40)
plt.show()

#############################################################################
# For dates plotted using the more recent epoch, the plot is smooth:

fig, ax = plt.subplots(constrained_layout=True)
ax.plot(x, y)
ax.set_title('Epoch: ' + mdates.get_epoch())
ax.xaxis.set_tick_params(rotation=40)
plt.show()

_reset_epoch_for_tutorial()  # Don't do this.  Just for this tutorial.

#############################################################################
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.dates.num2date`
#    - `matplotlib.dates.date2num`
#    - `matplotlib.dates.set_epoch`
