Module qudi_hira_analysis.data_handler
Expand source code
from __future__ import annotations
import datetime
import logging
from pathlib import Path
from typing import TYPE_CHECKING, Callable
from qudi_hira_analysis.analysis_logic import AnalysisLogic
from qudi_hira_analysis.io_handler import IOHandler
from qudi_hira_analysis.measurement_dataclass import (
LaserPulses,
MeasurementDataclass,
PulsedMeasurement,
PulsedMeasurementDataclass,
RawTimetrace,
)
if TYPE_CHECKING:
import numpy as np
import pandas as pd
import pySPM
logging.basicConfig(format='%(name)s :: %(levelname)s :: %(message)s',
level=logging.INFO)
class DataLoader(IOHandler):
"""
Interface to map measurement data loading methods in IOHandler to the automated data
methods in DataHandler. Also provides a direct passthrough of the IOHandler methods.
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
# Create callables used in measurement dataclasses
self.default_qudi_loader: (
Callable[[Path], pd.DataFrame], Callable[[Path], dict]) = (
self.read_into_dataframe,
self.read_qudi_parameters
)
self.confocal_qudi_loader: (
Callable[[Path], np.ndarray], Callable[[Path], dict]) = (
self.read_confocal_into_dataframe,
self.read_qudi_parameters
)
self.pixelscanner_qudi_loader: (
Callable[[Path], (pySPM.SPM_image, pySPM.SPM_image)],
Callable[[Path], dict]) = (
self.read_pixelscanner_data,
self.read_qudi_parameters
)
self.trace_qudi_loader: (
Callable[[Path], np.ndarray], Callable[[Path], dict]) = (
self.read_into_ndarray_transposed,
self.read_qudi_parameters
)
self.nanonis_loader: (
Callable[[Path], pd.DataFrame], Callable[[Path], dict]) = (
self.read_nanonis_data,
self.read_nanonis_parameters
)
self.nanonis_spm_loader: (Callable[[Path], pySPM.SXM], None) = (
self.read_nanonis_spm_data,
None
)
self.bruker_spm_loader: (Callable[[Path], pySPM.Bruker], None) = (
self.read_bruker_spm_data,
None
)
self.temperature_loader: (Callable[[Path], pd.DataFrame], None) = (
self.read_lakeshore_data,
None
)
self.pys_loader: (Callable[[Path], dict], None) = (
self.read_pys,
None
)
self.pressure_loader: (Callable[[Path], pd.DataFrame], None) = (
self.read_pfeiffer_data,
None
)
class DataHandler(DataLoader, AnalysisLogic):
"""
Handles automated data searching and extraction into dataclasses.
Args:
data_folder: Path to the data folder.
figure_folder: Path to the figure folder.
measurement_folder: Path to the measurement folder.
Examples:
Create an instance of the DataHandler class:
>>> dh = DataHandler(
>>> data_folder=Path('C:\\'', 'Data'),
>>> figure_folder=Path('C:\\'', 'QudiHiraAnalysis'),
>>> measurement_folder=Path('20230101_Bakeout'),
>>> )
"""
def __init__(
self,
data_folder: Path,
figure_folder: Path,
measurement_folder: Path = Path(),
copy_measurement_folder_structure: bool = True,
):
self.log = logging.getLogger(__name__)
self.data_folder_path = self.__get_data_folder_path(data_folder,
measurement_folder)
if copy_measurement_folder_structure:
self.figure_folder_path = self.__get_figure_folder_path(figure_folder,
measurement_folder)
else:
self.figure_folder_path = self.__get_figure_folder_path(figure_folder,
Path())
super().__init__(base_read_path=self.data_folder_path,
base_write_path=self.figure_folder_path)
self.timestamp_format_str = "%Y%m%d-%H%M-%S"
def __get_data_folder_path(self, data_folder: Path, folder_name: Path) -> Path:
""" Check if folder exists, if not, create and return absolute folder paths. """
path = data_folder / folder_name
if not path.exists():
raise OSError("Data folder path does not exist.")
self.log.info(f"Data folder path is {path}")
return path
def __get_figure_folder_path(self, figure_folder: Path, folder_name: Path) -> Path:
""" Check if folder exists, if not, create and return absolute folder paths. """
path = figure_folder / folder_name
if not path.exists():
path.mkdir()
self.log.info(f"Creating new output folder path {path}")
else:
self.log.info(f"Figure folder path is {path}")
return path
def __tree(self, dir_path: Path, prefix: str = ''):
"""
A recursive generator, given a directory Path object
will yield a visual tree structure line by line
with each line prefixed by the same characters
"""
# prefix components:
space = ' '
branch = '│ '
# pointers:
tee = '├── '
last = '└── '
contents = list(dir_path.iterdir())
# contents each get pointers that are ├── with a final └── :
pointers = [tee] * (len(contents) - 1) + [last]
for pointer, path in zip(pointers, contents):
yield prefix + pointer + path.name
if path.is_dir(): # extend the prefix and recurse:
extension = branch if pointer == tee else space
# i.e. space because last, └── , above so no more |
yield from self.__tree(path, prefix=prefix + extension)
def __print_or_return_tree(self, folder: Path, print_tree: bool) -> str | None:
""" Print or return a tree of the data and figure folders. """
if print_tree:
for line in self.__tree(folder):
print(line)
else:
tree = ""
for line in self.__tree(folder):
tree += line + "\n"
return tree
def data_folder_tree(self, print_tree: bool = True) -> str | None:
"""
Print or return a string tree of the data folder.
Args:
print_tree: Print the tree or return it as a string (default: True).
Returns:
str: The tree as a string if `print_tree is False.
"""
return self.__print_or_return_tree(self.data_folder_path, print_tree=print_tree)
def figure_folder_tree(self, print_tree: bool = True) -> str | None:
"""
Print or return a string tree of the figure folder.
Args:
print_tree: Print the tree or return it as a string (default: True).
Returns:
str: The tree as a string if `print_tree is False.
"""
return self.__print_or_return_tree(self.figure_folder_path,
print_tree=print_tree)
def _get_measurement_filepaths(
self,
measurement: str,
extension: str,
exclude_str: str | None = None
) -> list[Path]:
"""
List all measurement files for a single measurement type, regardless of date
within a similar set (i.e. top level folder).
"""
filepaths: list[Path] = []
for path in self.data_folder_path.rglob("*"):
if path.is_file() and measurement.lower() in str(
path).lower():
if exclude_str is None or exclude_str not in str(path):
if extension:
if path.suffix == extension:
filepaths.append(path)
else:
filepaths.append(path)
return filepaths
def __load_qudi_measurements_into_dataclass(
self,
measurement_str: str,
pulsed: bool,
extension: str
) -> dict[str: MeasurementDataclass]:
if pulsed:
filtered_filepaths = []
timestamps = set()
# Get set of unique timestamps containing pulsed_measurement_str
for filepath in self._get_measurement_filepaths(measurement=measurement_str,
extension=extension,
exclude_str="image_1.dat"):
timestamps.add(filepath.name[:16])
filtered_filepaths.append(filepath)
pulsed_measurement_data: dict[str: MeasurementDataclass] = {}
for idx, ts in enumerate(timestamps):
pm, lp, rt = None, None, None
for filepath in filtered_filepaths:
filename = filepath.name
if filename.startswith(ts):
if str(filename).endswith("laser_pulses.dat"):
lp = LaserPulses(filepath=filepath,
loaders=self.trace_qudi_loader)
elif str(filename).endswith("pulsed_measurement.dat"):
pm = PulsedMeasurement(filepath=filepath,
loaders=self.default_qudi_loader)
elif str(filename).endswith("raw_timetrace.dat"):
rt = RawTimetrace(filepath=filepath,
loaders=self.trace_qudi_loader)
if lp and pm and rt:
break
if not (lp and pm and rt):
raise OSError(
f"'{filtered_filepaths[idx]}' is a invalid pulsed measurement.")
pulsed_measurement_data[ts] = (
MeasurementDataclass(
timestamp=datetime.datetime.strptime(
ts,
self.timestamp_format_str
),
pulsed=PulsedMeasurementDataclass(
measurement=pm,
laser_pulses=lp,
timetrace=rt
)
)
)
return pulsed_measurement_data
else:
if measurement_str.lower() == "confocal":
loaders = self.confocal_qudi_loader
exclude_str = "xy_data.dat"
elif measurement_str.lower() == "pixelscanner":
loaders = self.pixelscanner_qudi_loader
exclude_str = None
else:
loaders = self.default_qudi_loader
exclude_str = None
measurement_data: dict[str: MeasurementDataclass] = {}
for filepath in self._get_measurement_filepaths(measurement_str, extension,
exclude_str):
ts = filepath.name[:16]
measurement_data[ts] = (
MeasurementDataclass(
filepath=filepath,
timestamp=datetime.datetime.strptime(
ts,
self.timestamp_format_str
),
_loaders=loaders
)
)
return measurement_data
def __load_standard_measurements_into_dataclass(
self,
measurement_str: str,
extension: str
) -> dict[str: MeasurementDataclass]:
measurement_list: dict[str: MeasurementDataclass] = {}
# Try and infer measurement type
if measurement_str.lower() == "temperature-monitoring":
loaders = self.temperature_loader
extension = ".xls"
exclude_str = None
elif measurement_str.lower() == "pressure-monitoring":
loaders = self.pressure_loader
extension = ".txt"
exclude_str = None
elif measurement_str == "frq-sweep":
loaders = self.nanonis_loader
exclude_str = None
elif extension == ".sxm":
loaders = self.nanonis_spm_loader
exclude_str = None
elif extension == ".pys":
loaders = self.pys_loader
exclude_str = None
elif extension == ".001":
loaders = self.bruker_spm_loader
exclude_str = None
else:
loaders = self.default_qudi_loader
exclude_str = None
for filepath in self._get_measurement_filepaths(measurement_str, extension,
exclude_str):
timestamp = datetime.datetime.fromtimestamp(filepath.stat().st_mtime)
self.log.warning(
"Extracting timestamp from file modified time, may not be accurate.")
ts = datetime.datetime.strftime(timestamp, self.timestamp_format_str)
measurement_list[ts] = (
MeasurementDataclass(
filepath=filepath,
timestamp=timestamp,
_loaders=loaders
)
)
return measurement_list
def load_measurements(
self,
measurement_str: str,
qudi: bool = True,
pulsed: bool = False,
extension: str = ".dat"
) -> dict[str: MeasurementDataclass]:
"""
Lazy-load all measurements of a given type into a dictionary of dataclasses.
Args:
measurement_str: The name of the measurement type to load e.g. t1, t2,
confocal etc.
Recursively searches through the path defined by
data_folder and measurement_folder.
Case-insensitive (i.e. "odmr" == "ODMR" == "Odmr").
qudi: Whether the measurement is a qudi measurement (default: True).
pulsed: Whether the measurement is a pulsed measurement (default: False).
extension: The file extension of the measurement files (default: .dat).
Returns:
dict: A dictionary where keys are the measurement timestamps and values are
dataclasses containing the measurement data.
Examples:
`dh` is an instance of the `DataHandler` class.
Load all ODMR measurements:
>>> dh.load_measurements(measurement_str="ODMR", pulsed=True)
Load all confocal data:
>>> dh.load_measurements(measurement_str="Confocal")
Load all temperature monitoring data:
>>> dh.load_measurements(measurement_str="Temperature")
Load all pressure monitoring data:
>>> dh.load_measurements(measurement_str="Pressure")
"""
measurement_str = measurement_str.lower()
if qudi:
return self.__load_qudi_measurements_into_dataclass(
measurement_str, pulsed=pulsed, extension=".dat"
)
else:
return self.__load_standard_measurements_into_dataclass(
measurement_str, extension=extension
)Classes
class DataHandler (data_folder: Path, figure_folder: Path, measurement_folder: Path = PosixPath('.'), copy_measurement_folder_structure: bool = True)-
Handles automated data searching and extraction into dataclasses.
Args
data_folder- Path to the data folder.
figure_folder- Path to the figure folder.
measurement_folder- Path to the measurement folder.
Examples
Create an instance of the DataHandler class:
>>> dh = DataHandler( >>> data_folder=Path('C:\'', 'Data'), >>> figure_folder=Path('C:\'', 'QudiHiraAnalysis'), >>> measurement_folder=Path('20230101_Bakeout'), >>> )Expand source code
class DataHandler(DataLoader, AnalysisLogic): """ Handles automated data searching and extraction into dataclasses. Args: data_folder: Path to the data folder. figure_folder: Path to the figure folder. measurement_folder: Path to the measurement folder. Examples: Create an instance of the DataHandler class: >>> dh = DataHandler( >>> data_folder=Path('C:\\'', 'Data'), >>> figure_folder=Path('C:\\'', 'QudiHiraAnalysis'), >>> measurement_folder=Path('20230101_Bakeout'), >>> ) """ def __init__( self, data_folder: Path, figure_folder: Path, measurement_folder: Path = Path(), copy_measurement_folder_structure: bool = True, ): self.log = logging.getLogger(__name__) self.data_folder_path = self.__get_data_folder_path(data_folder, measurement_folder) if copy_measurement_folder_structure: self.figure_folder_path = self.__get_figure_folder_path(figure_folder, measurement_folder) else: self.figure_folder_path = self.__get_figure_folder_path(figure_folder, Path()) super().__init__(base_read_path=self.data_folder_path, base_write_path=self.figure_folder_path) self.timestamp_format_str = "%Y%m%d-%H%M-%S" def __get_data_folder_path(self, data_folder: Path, folder_name: Path) -> Path: """ Check if folder exists, if not, create and return absolute folder paths. """ path = data_folder / folder_name if not path.exists(): raise OSError("Data folder path does not exist.") self.log.info(f"Data folder path is {path}") return path def __get_figure_folder_path(self, figure_folder: Path, folder_name: Path) -> Path: """ Check if folder exists, if not, create and return absolute folder paths. """ path = figure_folder / folder_name if not path.exists(): path.mkdir() self.log.info(f"Creating new output folder path {path}") else: self.log.info(f"Figure folder path is {path}") return path def __tree(self, dir_path: Path, prefix: str = ''): """ A recursive generator, given a directory Path object will yield a visual tree structure line by line with each line prefixed by the same characters """ # prefix components: space = ' ' branch = '│ ' # pointers: tee = '├── ' last = '└── ' contents = list(dir_path.iterdir()) # contents each get pointers that are ├── with a final └── : pointers = [tee] * (len(contents) - 1) + [last] for pointer, path in zip(pointers, contents): yield prefix + pointer + path.name if path.is_dir(): # extend the prefix and recurse: extension = branch if pointer == tee else space # i.e. space because last, └── , above so no more | yield from self.__tree(path, prefix=prefix + extension) def __print_or_return_tree(self, folder: Path, print_tree: bool) -> str | None: """ Print or return a tree of the data and figure folders. """ if print_tree: for line in self.__tree(folder): print(line) else: tree = "" for line in self.__tree(folder): tree += line + "\n" return tree def data_folder_tree(self, print_tree: bool = True) -> str | None: """ Print or return a string tree of the data folder. Args: print_tree: Print the tree or return it as a string (default: True). Returns: str: The tree as a string if `print_tree is False. """ return self.__print_or_return_tree(self.data_folder_path, print_tree=print_tree) def figure_folder_tree(self, print_tree: bool = True) -> str | None: """ Print or return a string tree of the figure folder. Args: print_tree: Print the tree or return it as a string (default: True). Returns: str: The tree as a string if `print_tree is False. """ return self.__print_or_return_tree(self.figure_folder_path, print_tree=print_tree) def _get_measurement_filepaths( self, measurement: str, extension: str, exclude_str: str | None = None ) -> list[Path]: """ List all measurement files for a single measurement type, regardless of date within a similar set (i.e. top level folder). """ filepaths: list[Path] = [] for path in self.data_folder_path.rglob("*"): if path.is_file() and measurement.lower() in str( path).lower(): if exclude_str is None or exclude_str not in str(path): if extension: if path.suffix == extension: filepaths.append(path) else: filepaths.append(path) return filepaths def __load_qudi_measurements_into_dataclass( self, measurement_str: str, pulsed: bool, extension: str ) -> dict[str: MeasurementDataclass]: if pulsed: filtered_filepaths = [] timestamps = set() # Get set of unique timestamps containing pulsed_measurement_str for filepath in self._get_measurement_filepaths(measurement=measurement_str, extension=extension, exclude_str="image_1.dat"): timestamps.add(filepath.name[:16]) filtered_filepaths.append(filepath) pulsed_measurement_data: dict[str: MeasurementDataclass] = {} for idx, ts in enumerate(timestamps): pm, lp, rt = None, None, None for filepath in filtered_filepaths: filename = filepath.name if filename.startswith(ts): if str(filename).endswith("laser_pulses.dat"): lp = LaserPulses(filepath=filepath, loaders=self.trace_qudi_loader) elif str(filename).endswith("pulsed_measurement.dat"): pm = PulsedMeasurement(filepath=filepath, loaders=self.default_qudi_loader) elif str(filename).endswith("raw_timetrace.dat"): rt = RawTimetrace(filepath=filepath, loaders=self.trace_qudi_loader) if lp and pm and rt: break if not (lp and pm and rt): raise OSError( f"'{filtered_filepaths[idx]}' is a invalid pulsed measurement.") pulsed_measurement_data[ts] = ( MeasurementDataclass( timestamp=datetime.datetime.strptime( ts, self.timestamp_format_str ), pulsed=PulsedMeasurementDataclass( measurement=pm, laser_pulses=lp, timetrace=rt ) ) ) return pulsed_measurement_data else: if measurement_str.lower() == "confocal": loaders = self.confocal_qudi_loader exclude_str = "xy_data.dat" elif measurement_str.lower() == "pixelscanner": loaders = self.pixelscanner_qudi_loader exclude_str = None else: loaders = self.default_qudi_loader exclude_str = None measurement_data: dict[str: MeasurementDataclass] = {} for filepath in self._get_measurement_filepaths(measurement_str, extension, exclude_str): ts = filepath.name[:16] measurement_data[ts] = ( MeasurementDataclass( filepath=filepath, timestamp=datetime.datetime.strptime( ts, self.timestamp_format_str ), _loaders=loaders ) ) return measurement_data def __load_standard_measurements_into_dataclass( self, measurement_str: str, extension: str ) -> dict[str: MeasurementDataclass]: measurement_list: dict[str: MeasurementDataclass] = {} # Try and infer measurement type if measurement_str.lower() == "temperature-monitoring": loaders = self.temperature_loader extension = ".xls" exclude_str = None elif measurement_str.lower() == "pressure-monitoring": loaders = self.pressure_loader extension = ".txt" exclude_str = None elif measurement_str == "frq-sweep": loaders = self.nanonis_loader exclude_str = None elif extension == ".sxm": loaders = self.nanonis_spm_loader exclude_str = None elif extension == ".pys": loaders = self.pys_loader exclude_str = None elif extension == ".001": loaders = self.bruker_spm_loader exclude_str = None else: loaders = self.default_qudi_loader exclude_str = None for filepath in self._get_measurement_filepaths(measurement_str, extension, exclude_str): timestamp = datetime.datetime.fromtimestamp(filepath.stat().st_mtime) self.log.warning( "Extracting timestamp from file modified time, may not be accurate.") ts = datetime.datetime.strftime(timestamp, self.timestamp_format_str) measurement_list[ts] = ( MeasurementDataclass( filepath=filepath, timestamp=timestamp, _loaders=loaders ) ) return measurement_list def load_measurements( self, measurement_str: str, qudi: bool = True, pulsed: bool = False, extension: str = ".dat" ) -> dict[str: MeasurementDataclass]: """ Lazy-load all measurements of a given type into a dictionary of dataclasses. Args: measurement_str: The name of the measurement type to load e.g. t1, t2, confocal etc. Recursively searches through the path defined by data_folder and measurement_folder. Case-insensitive (i.e. "odmr" == "ODMR" == "Odmr"). qudi: Whether the measurement is a qudi measurement (default: True). pulsed: Whether the measurement is a pulsed measurement (default: False). extension: The file extension of the measurement files (default: .dat). Returns: dict: A dictionary where keys are the measurement timestamps and values are dataclasses containing the measurement data. Examples: `dh` is an instance of the `DataHandler` class. Load all ODMR measurements: >>> dh.load_measurements(measurement_str="ODMR", pulsed=True) Load all confocal data: >>> dh.load_measurements(measurement_str="Confocal") Load all temperature monitoring data: >>> dh.load_measurements(measurement_str="Temperature") Load all pressure monitoring data: >>> dh.load_measurements(measurement_str="Pressure") """ measurement_str = measurement_str.lower() if qudi: return self.__load_qudi_measurements_into_dataclass( measurement_str, pulsed=pulsed, extension=".dat" ) else: return self.__load_standard_measurements_into_dataclass( measurement_str, extension=extension )Ancestors
- DataLoader
- IOHandler
- AnalysisLogic
- qudi_hira_analysis._qudi_fit_logic.FitLogic
Methods
def data_folder_tree(self, print_tree: bool = True) ‑> str | None-
Print or return a string tree of the data folder.
Args
print_tree- Print the tree or return it as a string (default: True).
Returns
str- The tree as a string if `print_tree is False.
Expand source code
def data_folder_tree(self, print_tree: bool = True) -> str | None: """ Print or return a string tree of the data folder. Args: print_tree: Print the tree or return it as a string (default: True). Returns: str: The tree as a string if `print_tree is False. """ return self.__print_or_return_tree(self.data_folder_path, print_tree=print_tree) def figure_folder_tree(self, print_tree: bool = True) ‑> str | None-
Print or return a string tree of the figure folder.
Args
print_tree- Print the tree or return it as a string (default: True).
Returns
str- The tree as a string if `print_tree is False.
Expand source code
def figure_folder_tree(self, print_tree: bool = True) -> str | None: """ Print or return a string tree of the figure folder. Args: print_tree: Print the tree or return it as a string (default: True). Returns: str: The tree as a string if `print_tree is False. """ return self.__print_or_return_tree(self.figure_folder_path, print_tree=print_tree) def load_measurements(self, measurement_str: str, qudi: bool = True, pulsed: bool = False, extension: str = '.dat') ‑> dict[slice(-
Lazy-load all measurements of a given type into a dictionary of dataclasses.
Args
measurement_str- The name of the measurement type to load e.g. t1, t2, confocal etc. Recursively searches through the path defined by data_folder and measurement_folder. Case-insensitive (i.e. "odmr" == "ODMR" == "Odmr").
qudi- Whether the measurement is a qudi measurement (default: True).
pulsed- Whether the measurement is a pulsed measurement (default: False).
extension- The file extension of the measurement files (default: .dat).
Returns
dict- A dictionary where keys are the measurement timestamps and values are dataclasses containing the measurement data.
Examples
dhis an instance of theDataHandlerclass.Load all ODMR measurements:
>>> dh.load_measurements(measurement_str="ODMR", pulsed=True)Load all confocal data:
>>> dh.load_measurements(measurement_str="Confocal")Load all temperature monitoring data:
>>> dh.load_measurements(measurement_str="Temperature")Load all pressure monitoring data:
>>> dh.load_measurements(measurement_str="Pressure")Expand source code
def load_measurements( self, measurement_str: str, qudi: bool = True, pulsed: bool = False, extension: str = ".dat" ) -> dict[str: MeasurementDataclass]: """ Lazy-load all measurements of a given type into a dictionary of dataclasses. Args: measurement_str: The name of the measurement type to load e.g. t1, t2, confocal etc. Recursively searches through the path defined by data_folder and measurement_folder. Case-insensitive (i.e. "odmr" == "ODMR" == "Odmr"). qudi: Whether the measurement is a qudi measurement (default: True). pulsed: Whether the measurement is a pulsed measurement (default: False). extension: The file extension of the measurement files (default: .dat). Returns: dict: A dictionary where keys are the measurement timestamps and values are dataclasses containing the measurement data. Examples: `dh` is an instance of the `DataHandler` class. Load all ODMR measurements: >>> dh.load_measurements(measurement_str="ODMR", pulsed=True) Load all confocal data: >>> dh.load_measurements(measurement_str="Confocal") Load all temperature monitoring data: >>> dh.load_measurements(measurement_str="Temperature") Load all pressure monitoring data: >>> dh.load_measurements(measurement_str="Pressure") """ measurement_str = measurement_str.lower() if qudi: return self.__load_qudi_measurements_into_dataclass( measurement_str, pulsed=pulsed, extension=".dat" ) else: return self.__load_standard_measurements_into_dataclass( measurement_str, extension=extension )
Inherited members
DataLoader:read_bruker_spm_dataread_confocal_into_dataframeread_csvread_excelread_into_dataframeread_into_ndarrayread_into_ndarray_transposedread_lakeshore_dataread_nanonis_dataread_nanonis_parametersread_nanonis_spm_dataread_oceanoptics_dataread_pfeiffer_dataread_pixelscanner_dataread_pklread_pysread_qudi_parameterssave_dfsave_figuressave_pklsave_pys
AnalysisLogic:
class DataLoader (**kwargs)-
Interface to map measurement data loading methods in IOHandler to the automated data methods in DataHandler. Also provides a direct passthrough of the IOHandler methods.
Expand source code
class DataLoader(IOHandler): """ Interface to map measurement data loading methods in IOHandler to the automated data methods in DataHandler. Also provides a direct passthrough of the IOHandler methods. """ def __init__(self, **kwargs): super().__init__(**kwargs) # Create callables used in measurement dataclasses self.default_qudi_loader: ( Callable[[Path], pd.DataFrame], Callable[[Path], dict]) = ( self.read_into_dataframe, self.read_qudi_parameters ) self.confocal_qudi_loader: ( Callable[[Path], np.ndarray], Callable[[Path], dict]) = ( self.read_confocal_into_dataframe, self.read_qudi_parameters ) self.pixelscanner_qudi_loader: ( Callable[[Path], (pySPM.SPM_image, pySPM.SPM_image)], Callable[[Path], dict]) = ( self.read_pixelscanner_data, self.read_qudi_parameters ) self.trace_qudi_loader: ( Callable[[Path], np.ndarray], Callable[[Path], dict]) = ( self.read_into_ndarray_transposed, self.read_qudi_parameters ) self.nanonis_loader: ( Callable[[Path], pd.DataFrame], Callable[[Path], dict]) = ( self.read_nanonis_data, self.read_nanonis_parameters ) self.nanonis_spm_loader: (Callable[[Path], pySPM.SXM], None) = ( self.read_nanonis_spm_data, None ) self.bruker_spm_loader: (Callable[[Path], pySPM.Bruker], None) = ( self.read_bruker_spm_data, None ) self.temperature_loader: (Callable[[Path], pd.DataFrame], None) = ( self.read_lakeshore_data, None ) self.pys_loader: (Callable[[Path], dict], None) = ( self.read_pys, None ) self.pressure_loader: (Callable[[Path], pd.DataFrame], None) = ( self.read_pfeiffer_data, None )Ancestors
Subclasses
Inherited members
IOHandler:read_bruker_spm_dataread_confocal_into_dataframeread_csvread_excelread_into_dataframeread_into_ndarrayread_into_ndarray_transposedread_lakeshore_dataread_nanonis_dataread_nanonis_parametersread_nanonis_spm_dataread_oceanoptics_dataread_pfeiffer_dataread_pixelscanner_dataread_pklread_pysread_qudi_parameterssave_dfsave_figuressave_pklsave_pys