"""This module gives access to the vast library of optical constant data, made freely available by the SOPRA-SA
optoelectronics company founded in 1948. For further detail on the data and SOPRA-SA see the legacy website:
http://www.sspectra.com/sopra.html"""
import numpy as np
import os, sys
import re
from natsort import natsorted
from configparser import ConfigParser
from solcore.science_tracker import science_reference
from solcore import config, SOLCORE_ROOT
SOPRA_PATH = os.path.abspath(config['Others']['sopra'].replace('SOLCORE_ROOT', SOLCORE_ROOT))
compounds_path = os.path.join(SOPRA_PATH, "compounds.txt")
compounds_info = ConfigParser()
compounds_info.read(compounds_path)
# Defining the SOPRA_DB class variable
[docs]class sopra_database:
"""Import the SOPRA_DB module from the solcore.material_system package and get started by selecting a material from
the extensive list that SOPRA-SA compiled;
>>> GaAs = sopra_database('GaAs')
Once imported a number of useful methods can be called to return n, k and alpha data for the desired material.
"""
science_reference("All optical constant data made avaialble by SOPRA-SA",
"http://www.sspectra.com/sopra.html")
def __init__(self, Material):
# Define filepath to the SOPRA database for file import...
self.__SOPRA_PATH = SOPRA_PATH
# Load in SOPRA_DB.csv database file
DB = np.genfromtxt(os.path.join(self.__SOPRA_PATH, "SOPRA_DB_Updated.csv"), delimiter=",", dtype=str)
self.__fname = None
for fname, symbol, range, info in DB:
if re.fullmatch(Material.upper(), fname) is not None:
self.__fname = fname
self.path = os.path.join(self.__SOPRA_PATH, self.__fname + ".MAT")
# self.info contains all detail loaded from SOPRA_DB,csv file...
self.info = {"Material": symbol,
"Wavelength (nm)": range,
"File Info": info,
"File Path": self.path}
# If the material name is incorrect then the material attribute is not written to
if self.__fname is None:
print("SOPRA_DB :: ERROR :: Material not found in SOPRA_DB... Check materials list...")
print("Similar Matches ::")
for fname, symbol, range, info in DB:
if re.match(Material.upper(), fname) is not None:
print(fname)
# If the exception is caught, exit the program as nothing else useful can be done...
# sys.exit()
raise SOPRAError("Material not found in SOPRA database: {}".format(Material))
[docs] @staticmethod
def material_list():
""" SOPRA_DB.material_list() :: Loads a list (.pdf file) of all available SOPRA materials. """
print("Opening List of Available Materials in the SOPRA database")
# Need different treatment depending on computer OS.
if sys.platform == 'darwin':
# Find spaces in the filename and add a \ before (for unix based systems)
directory = SOPRA_PATH.split(" ")
new_path = directory[0]
for i in range(1, len(directory), 1):
new_path = new_path + "\ " + directory[i]
os.system("open " + os.path.join(new_path, "List_Of_Files_Updated_PDF.pdf"))
elif sys.platform == 'linux':
# Find spaces in the filename and add a \ before (for unix based systems)
directory = SOPRA_PATH.split(" ")
new_path = directory[0]
for i in range(1, len(directory), 1):
new_path = new_path + "\ " + directory[i]
os.system("xdg-open " + os.path.join(new_path, "List_Of_Files_Updated_PDF.pdf"))
elif sys.platform == 'win32':
# Find spaces in the filename and add a \ before (for unix based systems)
os.system("start " + os.path.join(SOPRA_PATH, "List_Of_Files_Updated_PDF.pdf"))
[docs] def load_n(self, Lambda=None):
""" SOPRA_DB.load_n(Lambda) :: Load refractive index (n) data of the requested material.
Optional argument Lambda allows user to specify a custom wavelength range. data will be interpolated into
this range before output.
Returns: Tuple of (Wavelength, n)"""
try:
os.stat(self.path)
except FileNotFoundError:
print('load_n :: WARNING :: There is no individual data file for, ' + self.material + ".")
print('This material may be part of a set of varying composition, check the materials list...')
sys.exit()
# Load in data from file...
Wav, n = np.genfromtxt(self.path, delimiter="*", skip_header=3, skip_footer=3, usecols=(2, 3), unpack=True)
if Lambda is not None:
# Interpolate in range specified by Lambda...
n_interp = np.interp(Lambda, Wav, n)
return (Lambda, n_interp)
else:
return (Wav, n)
[docs] def load_k(self, Lambda=None):
""" SOPRA_DB.load_k(Lambda) :: Load refractive index (n) data of the requested material.
Optional argument Lambda allows user to specify a custom wavelength range. data will be interpolated into
this range before output.
Returns: Tuple of (Wavelength, k) """
try:
os.stat(self.path)
except FileNotFoundError:
print('load_k :: WARNING :: There is no individual data file for, ' + self.material + ".")
print('This material may be part of a set of varying composition, check the materials list...')
sys.exit()
# Load in data from file...
Wav, k = np.genfromtxt(self.path, delimiter="*", skip_header=3, skip_footer=3, usecols=(2, 4), unpack=True)
if Lambda is not None:
# Interpolate in range specified by Lambda...
k_interp = np.interp(Lambda, Wav, k)
return (Lambda, k_interp)
else:
return (Wav, k)
[docs] def load_alpha(self, Lambda=None):
""" SOPRA_DB.load_alpha(Lambda) :: Load refractive index (n) data of the requested material.
Optional argument Lambda allows user to specify a custom wavelength range. data will be interpolated into
this range before output.
Returns: Tuple of (Wavelength, alpha) """
Wav, k = self.load_k(Lambda=Lambda)
return (Wav, ((4 * np.pi) / (Wav * 1E-9)) * k)
[docs] def load_temperature(self, Lambda, T=300):
""" SOPRA_DB.load_temperature(T, Lambda) :: Loads n and k data for a set of materials with temperature dependent
data sets
Optional argument T defaults to 300K
Required argument Lambda specifies a wavelength range and the data is interpolated to fit. This is a
required argument here as not all data sets in a group are the same length (will be fixed in a
subsequent update).
Returns: Tuple of (Wavelength, n, k) """
T_degC = T - 273.15 # Convert from Kelvin to degC (units given in the data)...
# Navigate to the correct folder that contains temperature dependent data...
path = os.path.join(self.__SOPRA_PATH, self.__fname + "_T")
try:
os.stat(path)
except FileNotFoundError:
print("load_temperature :: WARNING :: Material folder does not exists... Check materials list...")
# If material folder is not found exit program as nothing more useful can be done...
sys.exit()
# if folder exists, read in files from folder...
Folder = natsorted(os.listdir(path))
DATA = []
TEMP = []
for files in Folder:
# .DS_Store is a metadata file used in Mac OS X to store various file/ folder info. Ignoring...
if ".DS_Store" not in files:
# extract temperature from filename...
Num = re.findall("[-+]?\d+[\.]?\d*", files)
Num.append("0")
TEMP.append(float(Num[0]))
Wav, n, k = np.genfromtxt(os.path.join(path, files), delimiter="*",
skip_header=3, skip_footer=3, usecols=(2, 3, 4), unpack=True)
if Lambda is not None:
# Interpolate if the Lambda argument is specified, if not pass loaded Wav, n and k...
n_interp = np.interp(Lambda, Wav, n)
k_interp = np.interp(Lambda, Wav, k)
DATA.append((Lambda, n_interp, k_interp, float(Num[0])))
else:
DATA.append((Wav, n, k, float(Num[0])))
# Check and see if the entered temperature is within the range of data...
if T_degC <= min(TEMP):
print("load_temperature :: WARNING :: Desired Temperature < than the minimum (%6.1f K)" % (
min(TEMP) + 273.15))
print("Returned interpolated data will be that at Tmin = %6.1f K" % (min(TEMP) + 273.15))
elif T_degC >= max(TEMP):
print("load_temperature :: WARNING :: Desired Temperature > than the maximum (%6.1f K)" % (
max(TEMP) + 273.15))
print("Returned interpolated data will be that at Tmax = %6.1f K" % (max(TEMP) + 273.15))
# use linear interpolation to interpolate the data at the desired temperature...
n_interp_data = []
k_interp_data = []
# In range of all wavelenghs...
for i in range(0, len(DATA[0][0])):
T_list = []
k_at_T = []
n_at_T = []
# At each wavelenth, build a list of n and k at each T...
for X, n, k, temp in DATA:
T_list.append(temp)
k_at_T.append(k[i])
n_at_T.append(n[i])
# Interpolate the point corresponding to T and build the new data array...
n_interp_data.append(np.interp(T - 273.19, T_list, n_at_T))
k_interp_data.append(np.interp(T - 273.19, T_list, k_at_T))
# Return the Wavelength vector and the new n and k data...
return (DATA[0][0], n_interp_data, k_interp_data)
[docs] def load_composition(self, Lambda, **kwargs):
""" SOPRA_DB.load_temperature(T, Lambda) :: Loads n and k data for a set of materials with varying composition.
Required argument Lambda specifies a wavelength range and the data is interpolated to fit. This is a
required argument here as not all data sets in a group are the same length (will be fixed in a
subsequent update).
Keyword argument :: Specify the factional material and fraction of the desired alloy.
Returns: Tuple of (Wavelength, n, k) """
# Use of keyword args allows the user to specify the required material fraction for neatness...
for material in kwargs:
mat_fraction = material
frac = kwargs[material]
# Navigate to the correct folder that contains temperature dependent data...
path = os.path.join(self.__SOPRA_PATH, self.__fname + "_" + mat_fraction.upper())
try:
os.stat(path)
except FileNotFoundError:
print("load_composition :: WARNING :: Material folder does not exists... Check materials list or check" +
" that composition material is correct...")
# If material folder is not found exit program as nothing more useful can be done...
sys.exit()
# if folder exists, read in files from folder...
Folder = natsorted(os.listdir(path))
DATA = []
COMP = []
for files in Folder:
# .DS_Store is a metadata file used in Mac OS X to store various file/ folder info. Ignoring...
if ".DS_Store" not in files:
# extract temperature from filename...
Num = re.findall("[-+]?\d+[\.]?\d*", files)
Num.append("0")
COMP.append(float(Num[0]))
Wav, n, k = np.genfromtxt(os.path.join(path, files), delimiter="*",
skip_header=3, skip_footer=3, usecols=(2, 3, 4), unpack=True)
if Lambda is not None:
# Interpolate if the Lambda argument is specified, if not pass loaded Wav, n and k...
n_interp = np.interp(Lambda, Wav, n)
k_interp = np.interp(Lambda, Wav, k)
DATA.append((Lambda, n_interp, k_interp, float(Num[0])))
else:
DATA.append((Wav, n, k, float(Num[0])))
# Check and see if the entered temperature is within the range of data...
if frac <= min(COMP):
print("load_composition :: WARNING :: Desired composition < than the minimum (%6.1f %%)" % min(COMP))
print("Returned interpolated data will be that at %6.1f %%" % min(COMP))
elif frac >= max(COMP):
print("load_composition :: WARNING :: Desired composition > than the maximum (%6.1f %%)" % max(COMP))
print("Returned interpolated data will be that at %6.1f %%" % max(COMP))
# use linear interpolation to interpolate the data at the desired temperature...
n_interp_data = []
k_interp_data = []
# In range of all wavelenghs...
for i in range(0, len(DATA[0][0])):
x_list = []
k_at_C = []
n_at_C = []
# At each wavelenth, build a list of n and k at each T...
for X, n, k, x in DATA:
x_list.append(x)
k_at_C.append(k[i])
n_at_C.append(n[i])
# Interpolate the point corresponding to T and build the new data array...
n_interp_data.append(np.interp(frac, x_list, n_at_C))
k_interp_data.append(np.interp(frac, x_list, k_at_C))
# Return the Wavelength vector and the new n and k data...
return (DATA[0][0], n_interp_data, k_interp_data)
[docs]class SOPRAError(Exception):
def __init__(self, message):
self.message = message
