- 25 Feb, 2019 8 commits
- 23 Feb, 2019 3 commits
- 22 Feb, 2019 1 commit
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Philippe Nguyen authored
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- 20 Feb, 2019 2 commits
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Leo Pound Singer authored
IMHO, this is more about presentation than logic, so it belongs in Jinja.
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Leo Pound Singer authored
Reformatted JSON data files using the json module from the Python standard library: >>> import glob >>> import json >>> for filename in glob.glob('**/*.json', recursive=True): ... with open(filename, 'r') as f: ... data = json.load(f) ... with open(filename, 'w') as f: ... json.dump(data, f, indent=4) ...
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- 19 Feb, 2019 1 commit
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Leo Pound Singer authored
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- 13 Feb, 2019 13 commits
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Min-A Cho authored
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Min-A Cho authored
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Min-A Cho authored
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Soichiro Morisaki authored
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Leo Pound Singer authored
This change makes it so that PyCharm enables Jinja2 syntax highlighting.
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Leo Pound Singer authored
I get really confused by Jinja's whitespace treatment and when to use `{%- -%}`. Perhaps adopting some uniform Jinja style guidelines could help. The closest thing to a Jinja "best practices" document that I could find is this style guide from the Chromium project: https://www.chromium.org/developers/jinja Take a look. I think it makes the templates more readable.
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Leo Pound Singer authored
The macros definitions distract from the body of the circular.
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Leo Pound Singer authored
* Cache the LALInference FITS file. Why not? It speeds up the test. * Move imports to module level. * Use the builtin function `open()` instead of `io.open()`.
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Leo Pound Singer authored
Reword the p_astro statement to improve terseness, use an apporpriate number of digits, and keep it near the closely related em_bright paragraph. Note that I added a macro to render very high probabilities as ">99%" and very low probabilities as "<1%", which is now used in both the p_astro and the em_bright paragraphs. The text was: The categorical astrophysical probabilities for the candidate event as computed by the P_astro pipeline are: BNS probability: 0.8593197490253501 BBH probability: 0.0 NSBH probability: 0.0 Terrestrial probability: 0.1406802509746499 The text is now: The classification of the signal, in order of descending confidence, is BNS (78%), terrestrial (22%), BBH (<1%), or NSBH (<1%).
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Min-A Cho authored
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Min-A Cho authored
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Leo Pound Singer authored
The original text was, `Additionally, the pipeline found there is (some level of evidence for or against) matter outside the final compact object.` This was problematic for two reasons. First, `the pipeline` (meaning the em_bright pipeline) was never introduced, so it gave the mistaken impression that the inference came from the detection pipeline. Second, without explaining that the inference relied only on the mass and spin parameters, it may have mislead the reader to think that our signal contained evidence for tidal or other matter effects. The text now reads, `Assuming this neutron star equation of state and the masses and spins inferred from the signal, there is (some level of evidence for or against) matter outside the final compact object.`
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Leo Pound Singer authored
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- 12 Feb, 2019 3 commits
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Min-A Cho authored
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Min-A Cho authored
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Brandon Piotrzkowski authored
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- 08 Feb, 2019 1 commit
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Jean-Gregoire Ducoin authored
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- 04 Jan, 2019 1 commit
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Duncan Macleod authored
including a copy of the GPL license in all distributions is a requirement of GPL usage.
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- 28 Nov, 2018 5 commits
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Leo Pound Singer authored
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Leo Pound Singer authored
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Leo Pound Singer authored
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Leo Pound Singer authored
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Leo Pound Singer authored
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- 02 Aug, 2018 2 commits
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Leo Pound Singer authored
This reverts commit ab64c62d.
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Leo Pound Singer authored
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