ENH: Initial implementation of calculation of astronomical Julian Date. #4041
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can you hook up travis (see contributing in main pandas dir) |
| def test_compare_1700(self): | ||
| r1 = 2342145.5 | ||
| r2 = Timestamp('1700-06-23').to_julian_date() | ||
| assert(r1 == r2), "{0} is not equal to {1}".format(r1, r2) |
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could you change this to: self.assertEqual(r1, r2)? or, even better:
self.assertEqual(r2, 2342145.5)
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As an aside, you could probably combine most of your tests into 2 tests (check out some of the other test cases in tseries/tests and core/tests to get an example) - just nice to follow the format of the rest of the test suite. |
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@timcera how's this coming along? would be a nice addition.... |
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This issue (#4065) is why I haven't worked on this. What is the use to me to implement a calendar that starts in 4714 BC (proleptic gregorian), if pandas can't represent the date? I tried to wade through the pandas code to help out with #4065, but quickly got in way over my head. Back to this PR, it seems that the only issues are that I need to hook up travis, and possibly change the tests? Is there anything else? It is possible that I could do these things soonish. My main concern though that I haven't got any feedback on is whether this is the right way to implement this functionality. Should it be a part of the Timestamp and Datetimeindex OR should it be a seperate utility function? Is there a pandas way? What is the big picture in how this should be implemented? Should pandas even care about calendars other than gregorian? Would other calendars make sense? Should the julian date be a completely separate object with a 'to_gregorian()' function? Should I just keep this functionality in my code? Should it be represented as a tuple (integer day, float fraction of day) which would allow representation of smaller intervals. I don't have any tests for small intervals though I include nanosecond in the calculations - don't know whether it actually does anything. Kindest regards, |
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| class TestDateTimeIndex(unittest.TestCase): | ||
| def test_1700(self): | ||
| r1 = [2345897.5, 2345898.5, 2345899.5, 2345900.5, 2345901.5] |
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pls add an self.assert_(isinstance(r2,np.ndarray) just to confirm that it returns that type
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need to remove the merge branches you can just |
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I have the rebase correct now, but trying to push to my repository with: Returns the following error: To git@github.com:timcera/pandas.git Any suggestions? |
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use git push --force origin to_juilian |
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Still interested. Rebased to the latest. I think it looks right, but if there are any issues, would be glad to work at getting things in order. Kindest regards, |
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converting a DatetimeIndex returns a float array yes? pls add a release note under new features for 0.14 and a mention in v0.14.0.txt ideally always would like to see your tests in tseries/test_timeseries.py |
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Looking at this should probably include a Float64Index.to_gregorian(). Might actually be more useful than the 'Datetime.Index.to_julian()'. Might need to be clear in the name though - perhaps Float64.Index.julian_date_to_gregorian()? |
* Added 'to_julian_date()' to Timestamp * Added 'to_julian_date()' to DatetimeIndex * Added tests for both methods.
Float64Index.
TST: Moved to_julian_date tests from
pandas/tseries/tests/test_julian_date.py into
pandas/tseries/tests/test_timeseries.py
DOC: Added mention of to_julian_date functionality
to doc/source/release.rst and v0.14.0.txt
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Travis was failing, but because of a testing bug fixed in a2c99fd I rebased to the latest upstream and pushed that changes up again. Kindest regards, |
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Forgot to add a docstring to Timestamp.to_julian() I can squash these commits. I don't know what the preferred view is. |
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I think it makes sense to add to period / period index as well (esp since periods CAN represent dates that are out if bounds for time stamps ) but this will require a common mixin class for period index / DatetimeIndex (which I need to add anyhow) so this looks ready to merge? |
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I think it is ready. |
| periods=5, | ||
| freq='D').to_julian_date() | ||
| self.assert_(isinstance(r2, Float64Index)) | ||
| np.testing.assert_array_equal(r1, r2) |
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change these test comparisons to use tm.assert_index_equal(r1,r2)
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merged via 10ad9dd thanks! |
Toying with the idea of using pandas for my astronomy and tidal analysis packages and I need the astronomical Julian Date. So here is an implementation and tests. I think I put these in the right place. Really wanted to have the same function for the Timestamp and DatetimeIndex so that both would benefit from improvements, but couldn't figure out how to make that work.
Kindest regards,
Tim