solarposition.py tutorial¶
This tutorial needs your help to make it better!
Table of contents:
This tutorial has been tested against the following package versions:
- pvlib 0.3.0
- Python 3.5.1
- IPython 4.1
- Pandas 0.18.0
It should work with other Python and Pandas versions. It requires pvlib > 0.3.0 and IPython > 3.0.
Authors:
- Will Holmgren (@wholmgren), University of Arizona. July 2014, July 2015, March 2016
Setup¶
In [1]:
import datetime
# scientific python add-ons
import numpy as np
import pandas as pd
# plotting stuff
# first line makes the plots appear in the notebook
%matplotlib inline
import matplotlib.pyplot as plt
# finally, we import the pvlib library
import pvlib
In [2]:
import pvlib
from pvlib.location import Location
SPA output¶
In [3]:
tus = Location(32.2, -111, 'US/Arizona', 700, 'Tucson')
print(tus)
golden = Location(39.742476, -105.1786, 'America/Denver', 1830, 'Golden')
print(golden)
golden_mst = Location(39.742476, -105.1786, 'MST', 1830, 'Golden MST')
print(golden_mst)
berlin = Location(52.5167, 13.3833, 'Europe/Berlin', 34, 'Berlin')
print(berlin)
In [4]:
times = pd.date_range(start=datetime.datetime(2014,6,23), end=datetime.datetime(2014,6,24), freq='1Min')
times_loc = times.tz_localize(tus.pytz)
In [5]:
times
Out[5]:
In [6]:
pyephemout = pvlib.solarposition.pyephem(times_loc, tus.latitude, tus.longitude)
spaout = pvlib.solarposition.spa_python(times_loc, tus.latitude, tus.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
spaout['elevation'].plot(label='spa')
plt.legend(ncol=2)
plt.title('elevation')
print('pyephem')
print(pyephemout.head())
print('spa')
print(spaout.head())
In [7]:
plt.figure()
pyephemout['elevation'].plot(label='pyephem')
spaout['elevation'].plot(label='spa')
(pyephemout['elevation'] - spaout['elevation']).plot(label='diff')
plt.legend(ncol=3)
plt.title('elevation')
plt.figure()
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
spaout['elevation'].plot(label='spa')
(pyephemout['apparent_elevation'] - spaout['elevation']).plot(label='diff')
plt.legend(ncol=3)
plt.title('elevation')
plt.figure()
pyephemout['apparent_zenith'].plot(label='pyephem apparent')
spaout['zenith'].plot(label='spa')
(pyephemout['apparent_zenith'] - spaout['zenith']).plot(label='diff')
plt.legend(ncol=3)
plt.title('zenith')
plt.figure()
pyephemout['apparent_azimuth'].plot(label='pyephem apparent')
spaout['azimuth'].plot(label='spa')
(pyephemout['apparent_azimuth'] - spaout['azimuth']).plot(label='diff')
plt.legend(ncol=3)
plt.title('azimuth')
Out[7]:
In [8]:
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(golden.tz), golden.latitude, golden.longitude)
spaout = pvlib.solarposition.spa_python(times.tz_localize(golden.tz), golden.latitude, golden.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
spaout['elevation'].plot(label='spa')
plt.legend(ncol=2)
plt.title('elevation')
print('pyephem')
print(pyephemout.head())
print('spa')
print(spaout.head())
In [9]:
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(golden.tz), golden.latitude, golden.longitude)
ephemout = pvlib.solarposition.ephemeris(times.tz_localize(golden.tz), golden.latitude, golden.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('elevation')
print('pyephem')
print(pyephemout.head())
print('ephem')
print(ephemout.head())
In [10]:
loc = berlin
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
ephemout = pvlib.solarposition.ephemeris(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
ephemout['apparent_elevation'].plot(label='ephem apparent')
plt.legend(ncol=2)
plt.title('elevation')
print('pyephem')
print(pyephemout.head())
print('ephem')
print(ephemout.head())
In [11]:
loc = berlin
times = pd.DatetimeIndex(start=datetime.date(2015,3,28), end=datetime.date(2015,3,29), freq='5min')
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
ephemout = pvlib.solarposition.ephemeris(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('elevation')
plt.figure()
pyephemout['azimuth'].plot(label='pyephem')
ephemout['azimuth'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('azimuth')
print('pyephem')
print(pyephemout.head())
print('ephem')
print(ephemout.head())
In [12]:
loc = berlin
times = pd.DatetimeIndex(start=datetime.date(2015,3,30), end=datetime.date(2015,3,31), freq='5min')
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
ephemout = pvlib.solarposition.ephemeris(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('elevation')
plt.figure()
pyephemout['azimuth'].plot(label='pyephem')
ephemout['azimuth'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('azimuth')
print('pyephem')
print(pyephemout.head())
print('ephem')
print(ephemout.head())
In [13]:
loc = berlin
times = pd.DatetimeIndex(start=datetime.date(2015,6,28), end=datetime.date(2015,6,29), freq='5min')
pyephemout = pvlib.solarposition.pyephem(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
ephemout = pvlib.solarposition.ephemeris(times.tz_localize(loc.tz), loc.latitude, loc.longitude)
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('elevation')
plt.figure()
pyephemout['azimuth'].plot(label='pyephem')
ephemout['azimuth'].plot(label='ephem')
plt.legend(ncol=2)
plt.title('azimuth')
print('pyephem')
print(pyephemout.head())
print('ephem')
print(ephemout.head())
In [14]:
pyephemout['elevation'].plot(label='pyephem')
pyephemout['apparent_elevation'].plot(label='pyephem apparent')
ephemout['elevation'].plot(label='ephem')
ephemout['apparent_elevation'].plot(label='ephem apparent')
plt.legend(ncol=2)
plt.title('elevation')
plt.xlim(pd.Timestamp('2015-06-28 02:00:00+02:00'), pd.Timestamp('2015-06-28 06:00:00+02:00'))
plt.ylim(-10,10)
Out[14]:
Speed tests¶
In [15]:
times_loc = times.tz_localize(loc.tz)
In [16]:
%%timeit
pyephemout = pvlib.solarposition.pyephem(times_loc, loc.latitude, loc.longitude)
#ephemout = pvlib.solarposition.ephemeris(times, loc)
In [17]:
%%timeit
#pyephemout = pvlib.solarposition.pyephem(times, loc)
ephemout = pvlib.solarposition.ephemeris(times_loc, loc.latitude, loc.longitude)
In [18]:
%%timeit
#pyephemout = pvlib.solarposition.pyephem(times, loc)
ephemout = pvlib.solarposition.get_solarposition(times_loc, loc.latitude, loc.longitude,
method='nrel_numpy')
This numba test will only work properly if you have installed numba.
In [19]:
%%timeit
#pyephemout = pvlib.solarposition.pyephem(times, loc)
ephemout = pvlib.solarposition.get_solarposition(times_loc, loc.latitude, loc.longitude,
method='nrel_numba')
The numba calculation takes a long time the first time that it's run because it uses LLVM to compile the Python code to machine code. After that it's about 4-10 times faster depending on your machine. You can pass a numthreads argument to this function. The optimum numthreads depends on your machine and is equal to 4 by default.
In [20]:
%%timeit
#pyephemout = pvlib.solarposition.pyephem(times, loc)
ephemout = pvlib.solarposition.get_solarposition(times_loc, loc.latitude, loc.longitude,
method='nrel_numba', numthreads=16)
In [21]:
%%timeit
ephemout = pvlib.solarposition.spa_python(times_loc, loc.latitude, loc.longitude,
how='numba', numthreads=16)
In [ ]: