merge conflicts: apply stash

Author: Tobin Ford

pvdeg/degradation.py

@@ -863,70 +863,33 @@ def _gJtoMJ(gJ):
     return MJ
 
 
-# new version of degradation
 def degradation(
-    spectra_df: pd.DataFrame,
-    conditions_df: pd.DataFrame = None,
-    temp_module: pd.Series = None,
-    rh_module: pd.Series = None,
+    spectra: pd.Series,
+    rh_module: pd.Series,
+    temp_module: pd.Series,
+    wavelengths: Union[int, np.ndarray[float]],
     Ea: float = 40.0,
     n: float = 1.0,
     p: float = 0.5,
     C2: float = 0.07,
     C: float = 1.0,
-)-> float:
+) -> float:
     """
     Compute degredation as double integral of Arrhenius (Activation
     Energy, RH, Temperature) and spectral (wavelength, irradiance)
     functions over wavelength and time.
 
-    .. math::
-
-        D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt
-
     Parameters
     ----------
-    spectra_df : pd.DataFrame
-        front or rear irradiance data in dataframe format
-
-        - `data`: Spectral irradiance values for each wavelength [W/m^2 nm].
-        - `index`: pd.DateTimeIndex
-        - `columns`: Wavelengths as floats (e.g., 280, 300, etc.).
-
-        Example::
-
-            timestamp                 280     300     320     340     360     380     400
-            2021-03-09 10:00:00    0.6892  0.4022  0.6726  0.0268  0.3398  0.9432  0.7411
-            2021-03-09 11:00:00    0.1558  0.5464  0.6896  0.7828  0.5050  0.9336  0.4652
-            2021-03-09 12:00:00    0.2278  0.9057  0.2639  0.0572  0.9906  0.9370  0.1800
-            2021-03-09 13:00:00    0.3742  0.0358  0.4052  0.9578  0.1044  0.8917  0.4876
-
-    conditions_df : pd.DataFrame, optional
-        Environmental conditions including temperature and relative humidity.
-
-        - `index`: pd.DateTimeIndex
-        - `columns`:  (required)
-            - "temperature" [°C or K]
-            - "relative_humidity" [%]
-
-        Example::
-
-            timestamp                 temperature  relative_humidity
-            2021-03-09 10:00:00         298.0               45.0
-            2021-03-09 11:00:00         303.0               50.0
-            2021-03-09 12:00:00         310.0               55.0
-            2021-03-09 13:00:00         315.0               60.0
-
-    temp_module : pd.Series, optional
-        Module temperatures [°C]. Required if `conditions_df` is not provided. Time indexed same as spectra_df
-
-    rh_module : pd.Series, optional
-        Relative humidity values [%]. Required if `conditions_df` is not provided. Time indexed same as spectra_df
-
-        Example::
-
-            30 = 30%
-
+    spectra : pd.Series type=Float
+        front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm]
+    rh_module : pd.Series type=Float
+        module RH, time indexed [%]
+    temp_module : pd.Series type=Float
+        module temperature, time indexed [C]
+    wavelengths : int-array
+        integer array (or list) of wavelengths tested w/ uniform delta
+        in nanometers [nm]
     Ea : float
         Arrhenius activation energy. The default is 40. [kJ/mol]
     n : float
@@ -945,183 +908,58 @@ def degradation(
     -------
     degradation : float
         Total degredation factor over time and wavelength.
+
     """
+    # --- TO DO ---
+    # unpack input-dataframe
+    # spectra = df['spectra']
+    # temp_module = df['temp_module']
+    # rh_module = df['rh_module']
 
+    # Constants
+    R = 0.0083145  # Gas Constant in [kJ/mol*K]
 
-    if conditions_df is not None and (temp_module is not None or rh_module is not None):
-        raise ValueError("Provide either conditions_df or temp_module and rh_module")
+    wav_bin = list(np.diff(wavelengths))
+    wav_bin.append(wav_bin[-1])  # Adding a bin for the last wavelength
 
-    if conditions_df is not None:
-        rh = conditions_df["relative_humidity"].values
-        temps = conditions_df["temperature"].values
-    else:
-        rh = rh_module.values
-        temps = temp_module.values
-
-    wavelengths = spectra_df.columns.values.astype(float)
-    irr = spectra_df.values  # irradiance as array
-
-    # call numba compiled function
-    return deg(
-        wavelengths=wavelengths, 
-        irr=irr,
-        rh=rh, 
-        temps=temps, 
-        Ea=Ea, 
-        C2=C2, 
-        p=p, 
-        n=n, 
-        C=C
-    )
+    # Integral over Wavelength
+    try:
+        irr = pd.DataFrame(spectra.tolist(), index=spectra.index)
+        irr.columns = wavelengths
+    except:
+        # TODO: Fix this except it works on some cases, veto it by cases
+        print("Removing brackets from spectral irradiance data")
+        # irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float)
+        irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float)
+        irr.columns = wavelengths
 
-# @njit 
-def deg(
-    wavelengths: np.ndarray, 
-    irr: np.ndarray, 
-    rh: np.ndarray, 
-    temps: np.ndarray, 
-    Ea: float, 
-    C2: float, 
-    p: float, 
-    n: float, 
-    C: float
-) -> float:
+    sensitivitywavelengths = np.exp(-C2 * wavelengths)
+    irr = irr * sensitivitywavelengths
+    irr *= np.array(wav_bin)
+    irr = irr**p
+    data = pd.DataFrame(index=spectra.index)
+    data["G_integral"] = irr.sum(axis=1)
 
-    R = 0.0083145  # Gas Constant in [kJ/mol*K]
+    EApR = -Ea / R
+    C4 = np.exp(EApR / temp_module)
 
-    wav_bin = np.diff(wavelengths)
-    wav_bin = np.append(wav_bin, wav_bin[-1])  # Extend last bin
-    
-    # inner integral
-    # wavelength d lambda
-    irr_weighted = irr * np.exp(-C2 * wavelengths) # weight irradiances
-    irr_weighted *= wav_bin                       
-    irr_pow = irr_weighted ** p
-    wavelength_integral = np.sum(irr_pow, axis=1) # sum over wavelengths
+    RHn = rh_module**n
+    data["Arr_integrand"] = C4 * RHn
 
-    # outer integral
-    # arrhenius integral dt
-    time_integrand = (rh ** n) * np.exp(-Ea / (R * temps))
+    data["dD"] = data["G_integral"] * data["Arr_integrand"]
 
-    dD = wavelength_integral * time_integrand
-    degradation = C * np.sum(dD)
+    degradation = C * data["dD"].sum(axis=0)
 
     return degradation
 
 
-# @deprecated("old double integral degradation function will be replaced 'pvdegradation' in an updated version of pvdeg")
-# def degradation(
-#     spectra: pd.Series,
-#     rh_module: pd.Series,
-#     temp_module: pd.Series,
-#     wavelengths: Union[int, np.ndarray[float]],
-#     Ea: float = 40.0,
-#     n: float = 1.0,
-#     p: float = 0.5,
-#     C2: float = 0.07,
-#     C: float = 1.0,
-# ) -> float:
-#     """
-#     Compute degredation as double integral of Arrhenius (Activation
-#     Energy, RH, Temperature) and spectral (wavelength, irradiance)
-#     functions over wavelength and time.
-
-#     .. math::
-
-#         D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt
-
-#     Parameters
-#     ----------
-#     spectra : pd.Series type=Float
-#         front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm]
-#     rh_module : pd.Series type=Float
-#         module RH, time indexed [%]
-#     temp_module : pd.Series type=Float
-#         module temperature, time indexed [C]
-#     wavelengths : int-array
-#         integer array (or list) of wavelengths tested w/ uniform delta
-#         in nanometers [nm]
-#     Ea : float
-#         Arrhenius activation energy. The default is 40. [kJ/mol]
-#     n : float
-#         Fit paramter for RH sensitivity. The default is 1.
-#     p : float
-#         Fit parameter for irradiance sensitivity. Typically
-#         0.6 +- 0.22
-#     C2 : float
-#         Fit parameter for sensitivity to wavelength exponential.
-#         Typically 0.07
-#     C : float
-#         Fit parameter for the Degradation equaiton
-#         Typically 1.0
-
-#     Returns
-#     -------
-#     degradation : float
-#         Total degredation factor over time and wavelength.
-#     """
-#     # --- TO DO ---
-#     # unpack input-dataframe
-#     # spectra = df['spectra']
-#     # temp_module = df['temp_module']
-#     # rh_module = df['rh_module']
-
-#     # Constants
-#     R = 0.0083145  # Gas Constant in [kJ/mol*K]
-
-#     wav_bin = list(np.diff(wavelengths))
-#     wav_bin.append(wav_bin[-1])  # Adding a bin for the last wavelength
-
-#     # Integral over Wavelength
-#     try:
-#         irr = pd.DataFrame(spectra.tolist(), index=spectra.index)
-#         irr.columns = wavelengths
-#     except:
-#         # TODO: Fix this except it works on some cases, veto it by cases
-#         print("Removing brackets from spectral irradiance data")
-#         # irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float)
-#         irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float)
-#         irr.columns = wavelengths
-
-
-#     # double integral calculation
-#     sensitivitywavelengths = np.exp(-C2 * wavelengths)
-#     irr = irr * sensitivitywavelengths
-#     irr *= np.array(wav_bin)
-#     irr = irr**p
-#     data = pd.DataFrame(index=spectra.index)
-#     data["G_integral"] = irr.sum(axis=1)
-
-#     EApR = -Ea / R
-#     C4 = np.exp(EApR / temp_module)
-
-#     RHn = rh_module**n
-
-#     data["Arr_integrand"] = C4 * RHn
-
-#     print("arr integral", data["Arr_integrand"])  
-#     print("wavelength integral", data["G_integral"] )
-
-#     data["dD"] = data["G_integral"] * data["Arr_integrand"]
-
-#     print(f"delta degradation ", data["dD"])
-
-#     degradation = C * data["dD"].sum(axis=0)
-
-#     return degradation
-
-
 # change it to take pd.DataFrame? instead of np.ndarray
 @njit
 def vecArrhenius(
     poa_global: np.ndarray, module_temp: np.ndarray, ea: float, x: float, lnr0: float
 ) -> float:
     """
-    Calculate arrhenius degradation using vectorized operations. To eliminate the irradiance term set the irradiance sensitivity to 0.
-    
-    .. math::
-
-        R_D = R_0 \\cdot I^X \\cdot e^{\\frac{-E_a}{kT}}
+    Calculates degradation using :math:`R_D = R_0 * I^X * e^{\\frac{-Ea}{kT}}`
 
     Parameters
     ----------