Every repository with this icon (
Every repository with this icon (
| name | age | message | |
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COPYING | Sat Mar 01 15:36:54 -0800 2008 | |
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README.markdown | Sun Apr 20 21:27:51 -0700 2008 | |
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constants.py | Sat Mar 08 17:06:06 -0800 2008 | |
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julian.py | Fri May 23 05:49:49 -0700 2008 | |
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poly.py | Sat Mar 08 17:06:06 -0800 2008 | |
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pysolar.org/ | Mon Mar 10 21:31:47 -0700 2008 | |
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pysolar_v_usno.csv | Sun Jan 11 17:39:44 -0800 2009 | |
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query_usno.py | Sun Jan 11 17:34:39 -0800 2009 | |
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radiation.py | Sun Mar 16 13:14:10 -0700 2008 | |
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shade.py | Sat Mar 01 15:36:54 -0800 2008 | |
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shade_test.py | Sat Mar 01 15:36:54 -0800 2008 | |
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simulate.py | Sun Mar 16 13:14:10 -0700 2008 | |
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solar.py | Sun Jan 11 17:34:39 -0800 2009 | |
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testsolar.py | Sun Jan 11 17:34:39 -0800 2009 | |
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usno_data_6259.txt | Sat Jul 19 18:41:04 -0700 2008 | |
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usno_data_short_test.txt | Sat Jul 19 18:41:04 -0700 2008 |
Pysolar performs calculations useful for the development of photovoltaic systems. Rough steps for use, until either forever or I have time to write more documentation:
- Install python.
- Get to a prompt that looks like: >>>
import solar
import datetime
d = datetime.datetime.utcnow()
lat = 42.0
long = -71.0
solar.GetAltitude(lat, long, d)
solar.GetAzimuth(lat, long, d)
For better examples of usage, check http://pysolar.sourceforge.net/#examples
At this point, Pysolar has basic functionality, but it is relatively untested. I did validate it against the data in a paper by Reda and Andreas; it agrees to 4 significant figures, but that's just one data point.
If you use Pysolar, please let me know how accurate it is. It's difficult to measure sun location with great precision, but I'd love to hear reports of "Yeah, it worked to within a degree over the course of an afternoon in Spain."
Brandon Stafford first_name @ pingswept org







