Add bin method

[mirca]

I was sure I had open a PR for this...

[mirca]

exactly

On Tue, Jan 2, 2018 at 10:55 PM, Geert Barentsen notifications@github.com wrote:

@barentsen commented on this pull request.

In pyke/lightcurve.py https://github.com/KeplerGO/pyke/pull/161#discussion_r159367988:

@@ -118,6 +118,15 @@ def fold(self, period, phase=0.): sorted_args = np.argsort(fold_time) return LightCurve(fold_time[sorted_args], self.flux[sorted_args])

• def bin(self, binsize):
• flux_err = None
• if self.flux_err is not None:
• flux_err = np.nanmean(self.self.flux_err[:-q or None].reshape(-1, N), axis=-1)

To do correct uncertainty propagation, should this be the square root of the sum of squares?

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/KeplerGO/pyke/pull/161#pullrequestreview-86303971, or mute the thread https://github.com/notifications/unsubscribe-auth/AMeKOwK6EFq8TphS1ZS6lN-nnQhFJEMEks5tGyRzgaJpZM4RRY8V .

-- github: @mirca http://www.github.com/mirca twitter: @mircaze http://www.twitter.com/mircaze webpage: mirca.github.io

[codecov[bot]]

Codecov Report

Merging #161 into master will decrease coverage by 0.47%. The diff coverage is 92.85%.

@@            Coverage Diff             @@
##           master     #161      +/-   ##
==========================================
- Coverage   33.23%   32.75%   -0.48%     
==========================================
  Files          65       65              
  Lines       10362    10269      -93     
==========================================
- Hits         3444     3364      -80     
+ Misses       6918     6905      -13

Impacted Files	Coverage Δ
pyke/tests/test_lightcurve.py	100% <100%> (ø)	:arrow_up:
pyke/lightcurve.py	77.17% <89.47%> (-0.52%)	:arrow_down:
pyke/targetpixelfile.py	73.68% <0%> (-2.13%)	:arrow_down:
pyke/utils.py	78.2% <0%> (-1.02%)	:arrow_down:
pyke/prf.py	89.83% <0%> (+2.85%)	:arrow_up:

---

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update 424af6c...b7ab3de. Read the comment docs.

[barentsen]

:+1: This looks great!

[barentsen]

@mirca came up with the idea to use np.array_like and @barentsen promptly stole the idea and implemented it!

[mirca]

I stole the idea from @gully