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Merged
merged 14 commits into from
Jul 5, 2015
Merged

Update variable names #70

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ef75d8b
update whatsnew
wholmgren Jun 22, 2015
82b93f3
fix celltemp keys. make output a df. closes #54
wholmgren Jun 22, 2015
1914afd
update singlediode etc for var names. add tests
wholmgren Jun 24, 2015
bc763a5
update pvsystem tutorial
wholmgren Jun 25, 2015
e8a71bf
update snlinverter variable names
wholmgren Jun 25, 2015
1c8223a
update sapm variable names
wholmgren Jun 25, 2015
ac6d9b8
update desoto variable names
wholmgren Jun 25, 2015
531240d
update tutorial
wholmgren Jun 25, 2015
2cd68b8
update atmosphere for new variable names
wholmgren Jun 25, 2015
dc05ba0
update clearsky variable style
wholmgren Jun 25, 2015
1f968a0
update irradiance for new variable names
wholmgren Jun 25, 2015
eb5708e
emphasize the API changes in the whatsnew
wholmgren Jun 25, 2015
3889e02
note about install instructions changing significantly
wholmgren Jun 25, 2015
ddfacfe
change travis config to hack around python3 testing
wholmgren Jun 25, 2015
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3 changes: 2 additions & 1 deletion .travis.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@ before_install:

install:
- echo "install"
- conda install --yes python=$TRAVIS_PYTHON_VERSION numpy scipy pandas=$PD_VERSION nose pytz ephem
- if [[ $TRAVIS_PYTHON_VERSION == '2.7' ]]; then conda install --yes python=$TRAVIS_PYTHON_VERSION numpy scipy pandas=$PD_VERSION nose pytz ephem; fi
- if [[ $TRAVIS_PYTHON_VERSION == '3.3' || $TRAVIS_PYTHON_VERSION == '3.4' ]]; then conda install --yes python=$TRAVIS_PYTHON_VERSION numpy=1.8 scipy=0.14 pandas nose pytz ephem; conda install --yes pandas=$PD_VERSION --no-deps; fi
- test $PD_VERSION != 0.13.1 && conda install --yes "numba>=0.17" || echo "Not installing numba"
- conda install --yes coverage
- pip install coveralls
Expand Down
11 changes: 10 additions & 1 deletion docs/sphinx/source/whatsnew/v0.2.0.txt
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Expand Up @@ -3,17 +3,25 @@
v0.2.0 (??, 2015)
-----------------------

This is a major release from 0.1 and includes a small number of API changes,
This is a major release from 0.1 and includes a large number of API changes,
several new features and enhancements along with a number of bug fixes.
We recommend that all users upgrade to this version.

Due to the large number of API changes, you will probably need to update your
code.


API changes
~~~~~~~~~~~

* Change variable names to conform with new
`Variables and style rules wiki <https://github.com/pvlib/pvlib-python/wiki/Variables-and-style-rules>`_.
This impacts many function declarations and return values.
Your existing code probably will not work! (:issue:`37`, :issue:`54`).
* Move ``dirint`` and ``disc`` algorithms from ``clearsky.py``
to ``irradiance.py`` (:issue:`42`)
* Mark some ``pvsystem.py`` methods as private (:issue:`20`)
* Make output of ``pvsystem.sapm_celltemp`` a DataFrame (:issue:`54`)

Enhancements
~~~~~~~~~~~~
Expand All @@ -23,6 +31,7 @@ Enhancements
* Add optional ``projection_ratio`` keyword argument to the ``haydavies``
calculator. Speeds calculations when irradiance changes but
solar position remains the same (:issue:`58`)
* Improved installation instructions in README.

Bug fixes
~~~~~~~~~
Expand Down
11,631 changes: 2,048 additions & 9,583 deletions docs/tutorials/pvsystem.ipynb
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55 changes: 34 additions & 21 deletions pvlib/atmosphere.py
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Expand Up @@ -22,8 +22,8 @@ def pres2alt(pressure):

Parameters
----------
Pressure : scalar or Series
Atomspheric pressure (Pascals)
pressure : scalar or Series
Atmospheric pressure (Pascals)

Returns
-------
Expand Down Expand Up @@ -100,7 +100,7 @@ def alt2pres(altitude):



def absoluteairmass(AMrelative, pressure=101325.):
def absoluteairmass(airmass_relative, pressure=101325.):
'''
Determine absolute (pressure corrected) airmass from relative
airmass and pressure
Expand All @@ -117,7 +117,7 @@ def absoluteairmass(AMrelative, pressure=101325.):
Parameters
----------

AMrelative : scalar or Series
airmass_relative : scalar or Series
The airmass at sea-level.

pressure : scalar or Series
Expand All @@ -136,13 +136,12 @@ def absoluteairmass(AMrelative, pressure=101325.):

'''

AMa = AMrelative * pressure / 101325.

return AMa
airmass_absolute = airmass_relative * pressure / 101325.

return airmass_absolute


def relativeairmass(z, model='kastenyoung1989'):
def relativeairmass(zenith, model='kastenyoung1989'):
'''
Gives the relative (not pressure-corrected) airmass

Expand All @@ -155,17 +154,20 @@ def relativeairmass(z, model='kastenyoung1989'):
Parameters
----------

z : float or DataFrame
zenith : float or Series
Zenith angle of the sun in degrees.
Note that some models use the apparent (refraction corrected)
zenith angle, and some models use the true (not refraction-corrected)
zenith angle. See model descriptions to determine which type of zenith
angle is required. Apparent zenith angles must be calculated at sea level.
zenith angle, and some models use the true
(not refraction-corrected) zenith angle.
See model descriptions to determine which type of zenith
angle is required.
Apparent zenith angles must be calculated at sea level.

model : String
Available models include the following:

* 'simple' - secant(apparent zenith angle) - Note that this gives -inf at zenith=90
* 'simple' - secant(apparent zenith angle) -
Note that this gives -inf at zenith=90
* 'kasten1966' - See reference [1] - requires apparent sun zenith
* 'youngirvine1967' - See reference [2] - requires true sun zenith
* 'kastenyoung1989' - See reference [3] - requires apparent sun zenith
Expand All @@ -175,7 +177,7 @@ def relativeairmass(z, model='kastenyoung1989'):

Returns
-------
AM : float or DataFrame
airmass_relative : float or Series
Relative airmass at sea level. Will return NaN values for any
zenith angle greater than 90 degrees.

Expand Down Expand Up @@ -207,27 +209,38 @@ def relativeairmass(z, model='kastenyoung1989'):
Sandia Report, (2012).
'''

z = zenith
zenith_rad = np.radians(z)

model = model.lower()

if 'kastenyoung1989' == model:
AM = 1.0 / (np.cos(zenith_rad) + 0.50572*(((6.07995 + (90 - z)) ** - 1.6364)))
AM = ( 1.0 / (np.cos(zenith_rad) +
0.50572*(((6.07995 + (90 - z)) ** - 1.6364))) )
elif 'kasten1966' == model:
AM = 1.0 / (np.cos(zenith_rad) + 0.15*((93.885 - z) ** - 1.253))
elif 'simple' == model:
AM = 1.0 / np.cos(zenith_rad)
elif 'pickering2002' == model:
AM = 1.0 / (np.sin(np.radians(90 - z + 244.0 / (165 + 47.0 * (90 - z) ** 1.1))))
AM = ( 1.0 / (np.sin(np.radians(90 - z +
244.0 / (165 + 47.0 * (90 - z) ** 1.1)))) )
elif 'youngirvine1967' == model:
AM = (1.0 / np.cos(zenith_rad)) * (1 - 0.0012*( (1.0 / np.cos(zenith_rad)) ** 2) - 1)
AM = ( (1.0 / np.cos(zenith_rad)) *
(1 - 0.0012*( (1.0 / np.cos(zenith_rad)) ** 2) - 1) )
elif 'young1994' == model:
AM = (1.002432*((np.cos(zenith_rad)) ** 2) + 0.148386*(np.cos(zenith_rad)) + 0.0096467) / (np.cos(zenith_rad) ** 3 + 0.149864*(np.cos(zenith_rad) ** 2) + 0.0102963*(np.cos(zenith_rad)) + 0.000303978)
AM = ( (1.002432*((np.cos(zenith_rad)) ** 2) +
0.148386*(np.cos(zenith_rad)) + 0.0096467) /
(np.cos(zenith_rad) ** 3 +
0.149864*(np.cos(zenith_rad) ** 2) +
0.0102963*(np.cos(zenith_rad)) + 0.000303978) )
elif 'gueymard1993' == model:
AM = 1.0 / (np.cos(zenith_rad) + 0.00176759*(z)*((94.37515 - z) ** - 1.21563))
AM = ( 1.0 / (np.cos(zenith_rad) +
0.00176759*(z)*((94.37515 - z) ** - 1.21563)) )
else:
pvl_logger.warning("{} is not a valid model type for relative airmass. The 'kastenyoung1989' model was used.".format(model))
AM = 1.0 / (np.cos(zenith_rad) + 0.50572*(((6.07995 + (90 - z)) ** - 1.6364)))
pvl_logger.warning("{} is not a valid model type for relative airmass. The 'kastenyoung1989' model was used."
.format(model))
AM = ( 1.0 / (np.cos(zenith_rad) +
0.50572*(((6.07995 + (90 - z)) ** - 1.6364))) )

try:
AM[z > 90] = np.nan
Expand Down
49 changes: 25 additions & 24 deletions pvlib/clearsky.py
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Expand Up @@ -49,13 +49,13 @@ def ineichen(time, location, linke_turbidity=None,
Sets the solar position algorithm.
See solarposition.get_solarposition()

zenith_data : None or pandas.Series
zenith_data : None or Series
If None, ephemeris data will be calculated using ``solarposition_method``.

airmass_model : string
See pvlib.airmass.relativeairmass().

airmass_data : None or pandas.Series
airmass_data : None or Series
If None, absolute air mass data will be calculated using
``airmass_model`` and location.alitude.

Expand All @@ -65,14 +65,14 @@ def ineichen(time, location, linke_turbidity=None,

Returns
--------
DataFrame with the following columns: ``GHI, DNI, DHI``.
DataFrame with the following columns: ``ghi, dni, dhi``.

Notes
-----
If you are using this function
in a loop, it may be faster to load LinkeTurbidities.mat outside of
the loop and feed it in as a variable, rather than
having the function open the file each time it is called.
the loop and feed it in as a keyword argument, rather than
having the function open and process the file each time it is called.

References
----------
Expand All @@ -96,7 +96,7 @@ def ineichen(time, location, linke_turbidity=None,
'''
# Initial implementation of this algorithm by Matthew Reno.
# Ported to python by Rob Andrews
# Added functionality by Will Holmgren
# Added functionality by Will Holmgren (@wholmgren)

I0 = irradiance.extraradiation(time.dayofyear)

Expand Down Expand Up @@ -161,7 +161,7 @@ def ineichen(time, location, linke_turbidity=None,
# alt2pres) using Kasten and Young's 1989 formula for airmass.

if airmass_data is None:
AMabsolute = atmosphere.absoluteairmass(AMrelative=atmosphere.relativeairmass(ApparentZenith, airmass_model),
AMabsolute = atmosphere.absoluteairmass(airmass_relative=atmosphere.relativeairmass(ApparentZenith, airmass_model),
pressure=atmosphere.alt2pres(location.altitude))
else:
AMabsolute = airmass_data
Expand Down Expand Up @@ -195,7 +195,9 @@ def ineichen(time, location, linke_turbidity=None,

cos_zenith = tools.cosd(ApparentZenith)

clearsky_GHI = cg1 * I0 * cos_zenith * np.exp(-cg2*AMabsolute*(fh1 + fh2*(TL - 1))) * np.exp(0.01*AMabsolute**1.8)
clearsky_GHI = ( cg1 * I0 * cos_zenith *
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would also change clearsky_GHI to all lower case (clearsky_ghi) for consistency.
Not sure, did you intended to change only names for the kw arguments (all api related) or all internal variable names too?

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I only intended to change the API related names for now. I would like to see the internal variables get updated, but I think we can do this in smaller chunks.

np.exp(-cg2*AMabsolute*(fh1 + fh2*(TL - 1))) *
np.exp(0.01*AMabsolute**1.8) )
clearsky_GHI[clearsky_GHI < 0] = 0

# BncI == "normal beam clear sky radiation"
Expand All @@ -204,25 +206,24 @@ def ineichen(time, location, linke_turbidity=None,
logger.debug('b={}'.format(b))

# "empirical correction" SE 73, 157 & SE 73, 312.
BncI_2 = clearsky_GHI * ( 1 - (0.1 - 0.2*np.exp(-TL))/(0.1 + 0.882/fh1) ) / cos_zenith
#return BncI, BncI_2
clearsky_DNI = np.minimum(BncI, BncI_2) # Will H: use np.minimum explicitly
BncI_2 = ( clearsky_GHI *
( 1 - (0.1 - 0.2*np.exp(-TL))/(0.1 + 0.882/fh1) ) /
cos_zenith )

clearsky_DNI = np.minimum(BncI, BncI_2)

clearsky_DHI = clearsky_GHI - clearsky_DNI*cos_zenith

df_out = pd.DataFrame({'GHI':clearsky_GHI, 'DNI':clearsky_DNI,
'DHI':clearsky_DHI})
df_out = pd.DataFrame({'ghi':clearsky_GHI, 'dni':clearsky_DNI,
'dhi':clearsky_DHI})
df_out.fillna(0, inplace=True)
#df_out['BncI'] = BncI
#df_out['BncI_2'] = BncI

return df_out



def haurwitz(ApparentZenith):


def haurwitz(apparent_zenith):
'''
Determine clear sky GHI from Haurwitz model
Determine clear sky GHI from Haurwitz model.

Implements the Haurwitz clear sky model for global horizontal
irradiance (GHI) as presented in [1, 2]. A report on clear
Expand All @@ -232,7 +233,7 @@ def haurwitz(ApparentZenith):

Parameters
----------
ApparentZenith : DataFrame
apparent_zenith : Series
The apparent (refraction corrected) sun zenith angle
in degrees.

Expand All @@ -258,13 +259,13 @@ def haurwitz(ApparentZenith):
Laboratories, SAND2012-2389, 2012.
'''

cos_zenith = tools.cosd(ApparentZenith)
cos_zenith = tools.cosd(apparent_zenith)

clearsky_GHI = 1098.0 * cos_zenith * np.exp(-0.059/cos_zenith)

clearsky_GHI[clearsky_GHI < 0] = 0

df_out = pd.DataFrame({'GHI':clearsky_GHI})
df_out = pd.DataFrame({'ghi':clearsky_GHI})

return df_out

Expand All @@ -274,5 +275,5 @@ def _linearly_scale(inputmatrix, inputmin, inputmax, outputmin, outputmax):

inputrange = inputmax - inputmin
outputrange = outputmax - outputmin
OutputMatrix = (inputmatrix - inputmin) * outputrange / inputrange + outputmin
OutputMatrix = (inputmatrix-inputmin) * outputrange/inputrange + outputmin
return OutputMatrix
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