Merge pull request #70 from wholmgren/variablenames

Update variable names

Author: bmu

.travis.yml

@@ -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

docs/sphinx/source/whatsnew/v0.2.0.txt

@@ -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
 ~~~~~~~~~~~~
@@ -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
 ~~~~~~~~~

docs/tutorials/pvsystem.ipynb

@@ -22,8 +22,8 @@ def pres2alt(pressure):
 
     Parameters
     ----------
-    Pressure : scalar or Series
-        Atomspheric pressure (Pascals)
+    pressure : scalar or Series
+        Atmospheric pressure (Pascals)
 
     Returns
     -------
@@ -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
@@ -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
@@ -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
 
@@ -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
@@ -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.
 
@@ -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

pvlib/atmosphere.py

@@ -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.
     
@@ -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
     ----------
@@ -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)
 
@@ -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
@@ -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 *
+                     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"
@@ -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
@@ -232,7 +233,7 @@ def haurwitz(ApparentZenith):
 
     Parameters
     ----------
-    ApparentZenith : DataFrame
+    apparent_zenith : Series
         The apparent (refraction corrected) sun zenith angle
         in degrees.
 
@@ -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
 
@@ -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