datetime to astropy Time: examples

.gitignore

@@ -209,3 +209,5 @@ docs/generated
 docs/api/
 # This is incase you run the figure tests
 figure_test_images*
+
+tags

docs/code_ref/time.rst

@@ -2,7 +2,7 @@ SunPy time
 ==========
 
 The time submodule contains helpers for converting strings to Python
-`datetime.datetime` objects and handling common operations on these objects. As
+`astropy.time.Time` objects and handling common operations on these objects. As
 well as this a `~sunpy.time.TimeRange` object is provided for representing a
 period of time and performing operations on that range.
 

docs/dev_guide/documentation.rst

@@ -224,7 +224,7 @@ Example (:class:`sunpy.map.Map`) ::
     ----------
     header : dict
         A dictionary representation of the image header
-    date : datetime
+    date : `astropy.time.Time`
         Image observation time
     det : str
         Detector name

docs/guide/acquiring_data/hek.rst

@@ -336,7 +336,7 @@ HEK results and create the corresponding VSO query attributes.
 
     >>> vso_query = hek2vso.translate_results_to_query(result[10:11])  # doctest: +REMOTE_DATA
     >>> vso_query[0]  # doctest: +REMOTE_DATA
-    [<Time(datetime.datetime(2011, 8, 9, 7, 22, 44), datetime.datetime(2011, 8, 9, 7, 28, 56), None)>, <Source('SDO')>, <Instrument('AIA')>, <Wavelength(193.0, 193.0, 'Angstrom')>]
+    [<Time(<Time object: scale='utc' format='isot' value=2011-08-09T07:22:44.000>, <Time object: scale='utc' format='isot' value=2011-08-09T07:28:56.000>, None)>, <Source('SDO')>, <Instrument('AIA')>, <Wavelength(193.0, 193.0, 'Angstrom')>]
 
 This function allows users finer-grained control of VSO queries
 generated from HEK results.

docs/guide/time.rst

@@ -16,29 +16,27 @@ SunPy builds upon its functionality.
 
 Solar data is associated with a number of different time formats. SunPy provides a simple
 parsing function which can deal with most every format that a user may encounter. Called
-`sunpy.time.parse_time()`, this function takes a string as input and returns a datetime object.
+`sunpy.time.parse_time()`, this function takes a string as input and returns a `~astropy.time.Time` object.
 Here are few examples of formats which `sunpy.time.parse_time()` accepts::
 
     >>> from sunpy.time import parse_time
     >>> parse_time('2007-05-04T21:08:12')
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
+    <Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>
     >>> parse_time('2007/05/04T21:08:12')
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
+    <Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>
     >>> parse_time('20070504T210812')
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
+    <Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>
     >>> parse_time('2007-May-04 21:08:12')
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
+    <Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>
     >>> parse_time('20070504_210812')
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
+    <Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>
 
-Each of the above returns the same datetime object ``datetime.datetime(2007,
-5, 4, 21, 8, 12)``. One of the most standard time formats used in solar
-physics is the number of seconds since 1979 January 01. The parse_time
+Each of the above returns the same `~astropy.time.Time` object ``<Time object: scale='utc' format='isot' value=2007-05-04T21:08:12.000>``. One of the most standard time formats used in solar
+physics is the number of seconds since 1979 January 01 called ``utime``. The parse_time
 function also accepts this as input, e.g.::
 
-    >>> parse_time(894316092.00000000)
-    datetime.datetime(2007, 5, 4, 21, 8, 12)
-
+    >>> parse_time(894316092.00000000, format='utime')
+    <Time object: scale='utc' format='utime' value=894316092.0>
 
 All SunPy functions which require
 time as an input sanitize the input using parse_time.
@@ -60,13 +58,19 @@ You can also pass the start and end times as a tuple: ::
 
 This object makes use of parse_time() so it can accept a wide variety of time formats.
 A time range object can also be created by providing a start time and a duration.
-The duration must be provided as a `datetime.timedelta` object or
-time-equivalent `astropy.units.Quantity`
+The duration must be provided as a `~astropy.time.TimeDelta` or
+time-equivalent `astropy.units.Quantity` or `datetime.timedelta` object
 example: ::
 
     >>> import astropy.units as u
     >>> time_range = TimeRange('2010/03/04 00:10', 400 * u.second)
 
+or: ::
+
+    >>> import astropy.units as u
+    >>> from astropy.time import TimeDelta
+    >>> time_range = TimeRange('2010/03/04 00:10', TimeDelta(400 * u.second))
+
 or: ::
 
     >>> from datetime import timedelta
@@ -77,7 +81,7 @@ get the time at the center of your interval or the length of your interval in mi
 or days or seconds: ::
 
     >>> time_range.center
-    datetime.datetime(2010, 3, 4, 0, 13, 20)
+    <Time object: scale='utc' format='isot' value=2010-03-04T00:13:20.000>
     >>> time_range.minutes
     <Quantity 6.66666667 min>
     >>> time_range.days

docs/guide/tour.rst

@@ -264,9 +264,9 @@ and times. Here is a short example: ::
 
     # parsing a standard time strings
     >>> sunpy.time.parse_time('2004/02/05 12:00')
-    datetime.datetime(2004, 2, 5, 12, 0)
+    <Time object: scale='utc' format='isot' value=2004-02-05T12:00:00.000>
 
-    # This returns a datetime object. All SunPy functions which require
+    # This returns a astropy.time.Time object. All SunPy functions which require
     # time as an input sanitize the input using parse_time.
     >>> sunpy.time.day_of_year('2004-Jul-05 12:00:02')
     187.50002314814816
@@ -278,7 +278,7 @@ and times. Here is a short example: ::
     # TimeRange objects are useful for representing ranges of time
     >>> time_range = sunpy.time.TimeRange('2010/03/04 00:10', '2010/03/04 00:20')
     >>> time_range.center
-    datetime.datetime(2010, 3, 4, 0, 15)
+    <Time object: scale='utc' format='isot' value=2010-03-04T00:15:00.000>
 
 For more information about working with time in SunPy checkout the :doc:`time guide <time>`.
 

examples/plotting/finegrained_plot.py

@@ -27,7 +27,7 @@
 top_right = SkyCoord(800*u.arcsec, 700*u.arcsec, frame=aiamap.coordinate_frame)
 aiamap_sub = aiamap.submap(bottom_left, top_right)
 
-title_obsdate = '{:%Y-%b-%d %H:%M:%S}'.format(aiamap_sub.date)
+title_obsdate = aiamap_sub.date.strftime('%Y-%b-%d %H:%M:%S')
 
 ###############################################################################
 # The SunPy map peek method shows a helioprojective  grid by default.

examples/plotting/overplot_hek_polygon.py

@@ -11,13 +11,13 @@
 
 from __future__ import print_function, division
 
-from datetime import timedelta
 import numpy as np
 
 import matplotlib.pyplot as plt
 
 import astropy.units as u
 from astropy.coordinates import SkyCoord
+from astropy.time import TimeDelta
 
 import sunpy.map
 import sunpy.data.sample
@@ -40,8 +40,8 @@
 ##############################################################################
 # Look for coronal holes detected using the SPoCA feature recognition method:
 
-start_time = aia_map.date - timedelta(hours=2)
-end_time = aia_map.date + timedelta(hours=2)
+start_time = aia_map.date - TimeDelta(2*u.hour)
+end_time = aia_map.date + TimeDelta(2*u.hour)
 responses = hek_client.search(hek.attrs.Time(start_time, end_time),
                               hek.attrs.CH, hek.attrs.FRM.Name == 'SPoCA')
 

examples/plotting/simple_differential_rotation.py

@@ -18,13 +18,12 @@
 
 from __future__ import print_function, division
 
-from datetime import timedelta
-
 import numpy as np
 import matplotlib.pyplot as plt
 
 import astropy.units as u
 from astropy.coordinates import SkyCoord
+from astropy.time import TimeDelta
 
 import sunpy.map
 import sunpy.data.sample
@@ -61,7 +60,7 @@
 ##############################################################################
 # Let's define how many days in the future we want to rotate to
 
-dt = timedelta(days=4)
+dt = TimeDelta(4*u.day)
 future_date = aia_map.date + dt
 
 ##############################################################################
@@ -70,7 +69,7 @@
 fig = plt.figure()
 ax = plt.subplot(projection=aia_map)
 aia_map.plot()
-ax.set_title('The effect of {0} days of differential rotation'.format(dt.days))
+ax.set_title('The effect of {0} days of differential rotation'.format(dt.to(u.day).value))
 aia_map.draw_grid()
 
 for this_hpc_x, this_hpc_y in zip(hpc_x, hpc_y):

examples/plotting/skip_magnetogram_active_regions.py

@@ -10,13 +10,12 @@
 # Start by importing the necessary modules.
 from __future__ import print_function, division
 
-import datetime
-
 import numpy as np
 import matplotlib.pyplot as plt
 
 from astropy import units as u
 from astropy.coordinates import SkyCoord
+from astropy.time import TimeDelta
 
 import sunpy.map
 import sunpy.coordinates
@@ -33,7 +32,7 @@
 # We will select the entire day as our timerange.
 
 start_time = day
-end_time = day + datetime.timedelta(hours=23, minutes=59, seconds=59)
+end_time = day + TimeDelta(23*u.hour + 59*u.minute + 59*u.second)
 
 ##############################################################################
 # Send the search query.

examples/time_series/goes_hek_m25.py

@@ -38,9 +38,9 @@
 # Finally lets plot everything together
 
 goes.peek()
-plt.axvline(parse_time(flares_hek[0].get('event_peaktime')))
-plt.axvspan(parse_time(flares_hek[0].get('event_starttime')),
-            parse_time(flares_hek[0].get('event_endtime')),
+plt.axvline(parse_time(flares_hek[0].get('event_peaktime')).plot_date)
+plt.axvspan(parse_time(flares_hek[0].get('event_starttime')).plot_date,
+            parse_time(flares_hek[0].get('event_endtime')).plot_date,
             alpha=0.2, label=flares_hek[0].get('fl_goescls'))
 plt.legend(loc=2)
 plt.show()

examples/time_series/skip_timeseries_example.py

@@ -99,7 +99,7 @@
 # You can access a specific value within the TimeSeries data DataFrame using
 # all the normal Pandas methods.
 # For example, the row with the index of 2015-01-01 00:02:00.008000:
-ts_lyra.data.loc[parse_time('2011-06-07 00:02:00.010')]
+ts_lyra.data.loc[parse_time('2011-06-07 00:02:00.010').datetime]
 # Pandas will actually parse a string to a datetime automatically if it can:
 ts_lyra.data.loc['2011-06-07 00:02:00.010']
 # Pandas includes methods to find the indexes of the max/min values in a dataframe:

sunpy/instr/tests/test_fermi.py

@@ -2,8 +2,11 @@
 from numpy.testing import assert_almost_equal
 from sunpy.instr import fermi
 from sunpy.time import parse_time
+from sunpy.time.astropy_time import _is_time_equal
 from sunpy.extern import six
 
+import astropy.units as u
+
 
 @pytest.mark.remote_data
 def test_download_weekly_pointing_file():
@@ -50,3 +53,8 @@ def test_detector_angles():
     assert_almost_equal(det2['n7'].value, 127.35783, decimal=1)
     assert_almost_equal(det2['n8'].value, 122.98894, decimal=1)
     assert_almost_equal(det2['n9'].value, 126.95987, decimal=1)
+
+
+def test_met_to_utc():
+    time = fermi.met_to_utc(500000000)
+    assert (time - parse_time('2016-11-05T00:53:16.000')) < 1e-7 * u.s

sunpy/net/jsoc/attrs.py

@@ -8,7 +8,7 @@
 from sunpy.net.vso.attrs import Wavelength
 
 
-__all__ = ['Series', 'Time', 'Protocol', 'Notify', 'Segment', 'Keys', 'PrimeKey']
+__all__ = ['Series', 'Protocol', 'Notify', 'Segment', 'Keys', 'PrimeKey']
 
 from sunpy.net.vso.attrs import Time
 

sunpy/tests/figure_hashes_py36.json

@@ -19,11 +19,11 @@
     "sunpy.map.tests.test_plotting.test_plot_masked_aia171_superpixel_nowcsaxes": "a34f0342097bd3967aefdaaea335ff084df2fbe6466330312abc8398538f7b1a",
     "sunpy.map.tests.test_plotting.test_rectangle_aia171": "3c2e977ccf7d07ca1b56e216ea06fc634259fa425526f643eaaab685d79a0afe",
     "sunpy.timeseries.tests.test_timeseriesbase.test_eve_peek": "c483d82bacee7217e4d18f6a8433457fcc698746fae71065208223c2d5e5eb6a",
-    "sunpy.timeseries.tests.test_timeseriesbase.test_fermi_gbm_peek": "213ea4e7e86de1951c357fa3e149c4c76f95ac7fe5e1ba035d78cbd5122b7947",
+    "sunpy.timeseries.tests.test_timeseriesbase.test_fermi_gbm_peek": "56da147444455d1466e0073656aff59b901c670b931e94dd878613e7b2bb55fb",
     "sunpy.timeseries.tests.test_timeseriesbase.test_generic_ts_peek": "ca11e496d4dcb157841a76513543694af61a7562181f61250619c1bfa9e5b70c",
     "sunpy.timeseries.tests.test_timeseriesbase.test_lyra_peek": "7cc6b761b6f015e5c2470f561de2ef029592dbd77ed97203a2f9895c6b140bc4",
     "sunpy.timeseries.tests.test_timeseriesbase.test_noaa_ind_peek": "10f1fc9e29f41f07ba63b119170e2ba649fa6440b0e23ffd32baee59b5df9aed",
     "sunpy.timeseries.tests.test_timeseriesbase.test_noaa_pre_peek": "09c2fb9890be936cdd414309c456e624c39183f594c663d4956fa9c20cf7a289",
     "sunpy.timeseries.tests.test_timeseriesbase.test_norh_peek": "1e03ed25af3b6534a50c849e3b37c7307f8903009966744440d77cfc231c3855",
     "sunpy.timeseries.tests.test_timeseriesbase.test_rhessi_peek": "0efa07c81fcf5ef99f9b09be131dac2bf2ae5509e4c123b72930f09562ed4b7c"
-}
+}

sunpy/timeseries/tests/test_timeseriesbase.py

@@ -109,11 +109,11 @@ def noaa_pre_test_ts():
 def generic_ts():
     # Generate the data and the corrisponding dates
     base = parse_time("2016/10/01T05:00:00")
-    dates = [base - TimeDelta(x*u.minute) for x in range(0, 24 * 60)]
+    dates = parse_time([base - TimeDelta(x*u.minute) for x in range(0, 24 * 60)])
     intensity = np.sin(np.arange(0, 12 * np.pi, ((12 * np.pi) / (24 * 60))))
 
     # Create the data DataFrame, header MetaDict and units OrderedDict
-    data = DataFrame(intensity, index=dates, columns=['intensity'])
+    data = DataFrame(intensity, index=dates.isot.astype('datetime64'), columns=['intensity'])
     units = OrderedDict([('intensity', u.W / u.m**2)])
     meta = MetaDict({'key': 'value'})