"""
A helper class to load data from Woollam ASCII Files.
It supports loading of standard psi/delta values.
"""
import logging
import re
from typing import TextIO, Union
import pandas as pd
from pint import DimensionalityError, UndefinedUnitError
from ..units import ureg
from ..utils import calc_rho, detect_encoding
logger = logging.getLogger(__name__)
is_float_regex = re.compile(r"[+-]?(\d+([.]\d*)?([eE][+-]?\d+)?|[.]\d+([eE][+-]?\d+)?)")
[docs]
def is_float(line: Union[float, int, str]) -> bool:
"""Checks whether the given line is a float
Args:
line (str): The line presumably containing a float
Returns:
bool: True if it is a float, False otherwise
"""
if isinstance(line, (float, int)):
return True
if isinstance(line, str):
return bool(is_float_regex.search(line))
return False
def _is_wvase_tabular(line: str) -> bool:
"""
Checks whether the provided line is in wvase tabular layout.
Args:
line (str): The line to check
Returns:
bool: True if the line is in wvase tabular layout.
"""
return bool(re.search(r"^(-?\d*\.\d*\s+){5}\d*\.\d*$", line))
def _is_complete_ease_tabular(line: str) -> bool:
"""
Checks whether the provided line is in complete ease tabular layout.
Args:
line (str): The line to check
Returns:
bool: True if the line is in complete ease tabular layout.
"""
return bool(re.search(r"^[a-zA-Z]+\s+(\d+\.\d+\s+){5}\d+\.\d+$", line))
def _is_tan_cos_format(line: str) -> bool:
"""
Checks whether the line denotes a wvase tan/cos format.
Args:
line (str): The line to check
Returns:
bool: True if the line is of the format {unit} TRIG.
"""
return bool(re.search(r"^[a-zA-Z]+\s+TRIG", line))
[docs]
def scale_to_nm(unit: str, dataframe: pd.DataFrame) -> pd.DataFrame:
"""
Scales the wavelength axis of the given dataframe from the
provided unit to nm.
Args:
unit (str): The unit string. Should be pint compatible.
dataframe (pd.DataFrame): The dataframe which axis should be scaled.
Returns:
pd.DataFrame: The dataframe with scaled wavelength axis.
"""
try:
scaling = ureg(unit).to("nm").magnitude
dataframe.index = dataframe.index.set_levels(
dataframe.index.levels[1].astype(float) * scaling, level=1
)
return dataframe
except UndefinedUnitError:
logger.warning(
"Unrecognized unit %s. "
"The wavelength axis may not be scaled appropriately.",
unit,
)
return dataframe
except DimensionalityError:
logger.warning(
"Unit %s is not a valid wavelength unit. "
"The wavelength axis may not be scaled appropriately.",
unit,
)
return dataframe
def _read_wvase_dataframe(file_object: TextIO) -> pd.DataFrame:
"""
Reads a wvase formated table from a TextIO file object.
The pointer of the file object should point to the first line
of the data table.
Args:
file_object (TextIO): The file object containing the wvase table.
Returns:
pd.DataFrame:
Dataframe containing the psi/delta values.
Ready to be further processed by pyElli.
"""
dframe = pd.read_csv(
file_object,
sep="\t",
header=None,
names=["Wavelength", "Angle of Incidence", "Ψ", "Δ", "Ψ_err", "Δ_err"],
)
dframe = (
dframe[dframe.apply(lambda x: is_float(x.iloc[0]), axis=1)]
.set_index(["Wavelength", "Angle of Incidence"])
.swaplevel(0, 1)
)
return dframe
def _read_complete_ease_dataframe(file_object: TextIO) -> pd.DataFrame:
"""
Reads a complete ease formated table from a TextIO file object.
The pointer of the file object should point to the first line
of the data table.
Args:
file_object (TextIO): The file object containing the complete ease table.
Returns:
pd.DataFrame:
Dataframe containing the psi/delta values.
Ready to be further processed by pyElli.
"""
dframe = pd.read_csv(file_object, sep="\t", header=None, index_col=(2, 1))
dframe = dframe[dframe[0] == "E"]
dframe = dframe.iloc[:, 1:]
dframe.index.names = ("Angle of Incidence", "Wavelength")
dframe.columns = ["Ψ", "Δ", "Ψ_err", "Δ_err"]
return dframe
[docs]
def read_woollam_psi_delta(fname: str) -> pd.DataFrame:
r"""Read a psi/delta woollam ascii file.
Args:
fname (str): Filename of the measurement ascii file.
Returns:
pd.DataFrame: DataFrame containing the psi/delta data in
the format to be further processes inside pyElli.
"""
encoding = detect_encoding(fname)
with open(fname, encoding=encoding) as fobj:
line_number = fobj.tell()
metadata = []
file_format = ""
line = fobj.readline()
while line:
if _is_wvase_tabular(line):
file_format = "wvase"
break
if _is_complete_ease_tabular(line):
file_format = "complete_ease"
break
if _is_tan_cos_format(line):
raise NotImplementedError(
"The wvase Tan(Psi)/Cos(Delta) format is not supported. "
"Please try using wvase's psi/delta format."
)
metadata.append(line)
line_number = fobj.tell()
line = fobj.readline()
fobj.seek(line_number)
if not line:
raise ValueError(f"Invalid file format for {fname}")
reader_map = {
"wvase": _read_wvase_dataframe,
"complete_ease": _read_complete_ease_dataframe,
}
if file_format not in reader_map:
raise ValueError(f"Invalid file format {file_format} for file {fname}")
data = reader_map.get(file_format)(fobj)
data = scale_to_nm(metadata[-1], data)
return data.iloc[:, :-2]
[docs]
def read_woollam_rho(fname: str) -> pd.DataFrame:
r"""Read a psi/delta woollam ascii file and converts it to rho values.
Args:
fname (str): Filename of the measurement ascii file.
Returns:
pd.DataFrame: DataFrame containing the rho data in
the format to be further processes inside pyElli.
"""
psi_delta = read_woollam_psi_delta(fname)
return calc_rho(psi_delta)