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python-versions = ">=3.10,<3.13" -content-hash = "a1a1173f44fd5e063467f613cea96cd92dd232f51c34082d440ff784716400a3" +content-hash = "375193dd1ccff1c2a23feec605bd308cbab3b18aaf32597580626f734955cf15" diff --git a/pyproject.toml b/pyproject.toml index d6b2df2..b8e2b12 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,13 +14,13 @@ packages = [{ include = "qudi_hira_analysis" }] [tool.poetry.dependencies] python = ">=3.10,<3.13" lmfit = "^1.1.0" -matplotlib = "^3.6.2" +matplotlib = "^3.8.2" numpy = "^1.26.0" pandas = "^2.0.0" xlrd = "^2.0.1" openpyxl = "^3.0.10" tqdm = "^4.64.1" -pyspm = "^0.5.0" +pyspm = "^0.6.0" [tool.poetry.group.dev] optional = true @@ -28,7 +28,7 @@ optional = true [tool.poetry.group.dev.dependencies] jupyterlab = "^3.6.2" notebook = "^6.5.4" -ruff = "^0.1.0" +ruff = "^0.3.0" ruff-lsp = "^0.0.39" seaborn = "^0.13.0" @@ -49,12 +49,21 @@ requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" [tool.ruff] +target-version = "py310" + +[tool.ruff.lint] extend-select = [ + "E", # pycodestyle-error + "W", # pycodestyle-warning + "F", # pyflakes + "N", # pep8-naming "B", # flake8-bugbear + "I", # isort + "ASYNC", # flake8-async + "BLE", # flake8-blind-except + "A", # flake8-builtins "C4", # flake8-comprehensions "ERA", # flake8-eradicate/eradicate - "I", # isort - "N", # pep8-naming "PIE", # flake8-pie "PGH", # pygrep "RUF", # ruff checks @@ -63,3 +72,6 @@ extend-select = [ "TID", # flake8-tidy-imports "UP", # pyupgrade ] + +[tool.ruff.format] +docstring-code-format = true \ No newline at end of file diff --git a/qudi_hira_analysis/__init__.py b/qudi_hira_analysis/__init__.py index cfd1466..750d98a 100644 --- a/qudi_hira_analysis/__init__.py +++ b/qudi_hira_analysis/__init__.py @@ -16,13 +16,13 @@ from qudi_hira_analysis import DataHandler dh = DataHandler( - data_folder=Path("C:/Data"), # Path to the data folder - figure_folder=Path("C:/QudiHiraAnalysis"), # Path to the figure folder - measurement_folder=Path("20230101_NV1") # Name of the measurement folder - ) - # Output: - # qudi_hira_analysis.data_handler :: INFO :: Data folder path is C:/Data/20230101_NV1 - # qudi_hira_analysis.data_handler :: INFO :: Figure folder path is C:/QudiHiraAnalysis/20230101_NV1 + data_folder=Path("C:/Data"), # Path to the data folder + figure_folder=Path("C:/QudiHiraAnalysis"), # Path to the figure folder + measurement_folder=Path("20230101_NV1"), # Name of the measurement folder +) +# Output: +# qudi_hira_analysis.data_handler :: INFO :: Data folder path is C:/Data/20230101_NV1 +# qudi_hira_analysis.data_handler :: INFO :: Figure folder path is C:/QudiHiraAnalysis/20230101_NV1 ``` ### Loading data @@ -90,12 +90,17 @@ ```python -x_fit, y_fit, result = dh.fit(x="Controlled variable(Hz)", y="Signal", - fit_function=dh.fit_function.lorentziandouble, - data=odmr.data) +x_fit, y_fit, result = dh.fit( + x="Controlled variable(Hz)", + y="Signal", + fit_function=dh.fit_function.lorentziandouble, + data=odmr.data, +) # Plot the data and the fit -ax = sns.scatterplot(x="Controlled variable(Hz)", y="Signal", data=odmr.data, label="Data") +ax = sns.scatterplot( + x="Controlled variable(Hz)", y="Signal", data=odmr.data, label="Data" +) sns.lineplot(x=x_fit, y=y_fit, ax=ax, label="Fit") ``` @@ -143,8 +148,9 @@ ```python # Save the figure to the figure folder specified earlier -dh.save_figures(filepath=Path("odmr"), fig=ax.get_figure(), - only_pdf=True, bbox_inches="tight") +dh.save_figures( + filepath=Path("odmr"), fig=ax.get_figure(), only_pdf=True, bbox_inches="tight" +) # The figure is saved to C:/QudiHiraAnalysis/20230101_NV1/odmr.pdf ``` @@ -167,11 +173,13 @@ image = np.zeros((pixels, pixels)) for idx, odmr in enumerate(odmr_measurements.values()): - row, col = odmr.xy_position - if len(odmr.fit_model.params) > 6: - # Calculate double Lorentzian splitting - image[row, col] = np.abs(odmr.fit_model.best_values["l1_center"] - - odmr.fit_model.best_values["l0_center"]) + row, col = odmr.xy_position + if len(odmr.fit_model.params) > 6: + # Calculate double Lorentzian splitting + image[row, col] = np.abs( + odmr.fit_model.best_values["l1_center"] + - odmr.fit_model.best_values["l0_center"] + ) map = sns.heatmap(image, cbar_kws={"label": "Delta E (MHz)"}) @@ -249,9 +257,12 @@ # Plot the data sns.lineplot(data=autocorrelation.data, x="Time (ns)", y="g2(t) norm", ax=ax) # Fit the data using the antibunching function - fit_x, fit_y, result = dh.fit(x="Time (ns)", y="g2(t) norm", - data=autocorrelation.data, - fit_function=dh.fit_function.antibunching) + fit_x, fit_y, result = dh.fit( + x="Time (ns)", + y="g2(t) norm", + data=autocorrelation.data, + fit_function=dh.fit_function.antibunching, + ) # Plot the fit sns.lineplot(x=fit_x, y=fit_y, ax=ax, color="C1") @@ -269,9 +280,12 @@ for odmr in odmr_measurements.values(): sns.scatterplot(data=odmr.data, x="Controlled variable(Hz)", y="Signal", ax=ax) - fit_x, fit_y, result = dh.fit(x="Controlled variable(Hz)", y="Signal", - data=odmr.data, - fit_function=dh.fit_function.lorentziandouble) + fit_x, fit_y, result = dh.fit( + x="Controlled variable(Hz)", + y="Signal", + data=odmr.data, + fit_function=dh.fit_function.lorentziandouble, + ) sns.lineplot(x=fit_x, y=fit_y, ax=ax, color="C1") dh.save_figures(filepath="odmr_variation", fig=fig) @@ -287,9 +301,12 @@ for rabi in rabi_measurements.values(): sns.scatterplot(data=rabi.data, x="Controlled variable(s)", y="Signal", ax=ax) - fit_x, fit_y, result = dh.fit(x="Controlled variable(s)", y="Signal", - data=rabi.data, - fit_function=dh.fit_function.sineexponentialdecay) + fit_x, fit_y, result = dh.fit( + x="Controlled variable(s)", + y="Signal", + data=rabi.data, + fit_function=dh.fit_function.sineexponentialdecay, + ) sns.lineplot(x=fit_x, y=fit_y, ax=ax, color="C1") dh.save_figures(filepath="rabi_variation", fig=fig) diff --git a/qudi_hira_analysis/_fitmethods/gaussianlikemethods.py b/qudi_hira_analysis/_fitmethods/gaussianlikemethods.py index 18cb5c6..a6754a5 100644 --- a/qudi_hira_analysis/_fitmethods/gaussianlikemethods.py +++ b/qudi_hira_analysis/_fitmethods/gaussianlikemethods.py @@ -908,7 +908,7 @@ def estimate_twoDgaussian(self, x_axis, y_axis, data, params): for var in parameters: # FIXME: Why don't you check earlier? # FIXME: Check for 1D array, 2D - if not isinstance(var, (frozenset, list, set, tuple, np.ndarray)): + if not isinstance(var, frozenset | list | set | tuple | np.ndarray): self.log.error("Given parameter is not an array.") amplitude = 0.0 center_x = 0.0 @@ -989,7 +989,7 @@ def estimate_twoDgaussian_MLE(self, x_axis, y_axis, data, params): for var in parameters: # FIXME: Why don't you check earlier? # FIXME: Check for 1D array, 2D - if not isinstance(var, (frozenset, list, set, tuple, np.ndarray)): + if not isinstance(var, frozenset | list | set | tuple | np.ndarray): self.log.error("Given parameter is not an array.") amplitude = 0.0 center_x = 0.0 diff --git a/qudi_hira_analysis/_fitmethods/generalmethods.py b/qudi_hira_analysis/_fitmethods/generalmethods.py index ec330ab..f91cf92 100644 --- a/qudi_hira_analysis/_fitmethods/generalmethods.py +++ b/qudi_hira_analysis/_fitmethods/generalmethods.py @@ -586,7 +586,7 @@ def _check_1D_input(self, x_axis, data, params): error = 0 parameters = [x_axis, data] for var in parameters: - if not isinstance(var, (frozenset, list, set, tuple, np.ndarray)): + if not isinstance(var, frozenset | list | set | tuple | np.ndarray): self.log.error("Given parameter is no array.") error = -1 elif len(np.shape(var)) != 1: diff --git a/qudi_hira_analysis/_qudi_fit_logic.py b/qudi_hira_analysis/_qudi_fit_logic.py index 8737363..1961f57 100644 --- a/qudi_hira_analysis/_qudi_fit_logic.py +++ b/qudi_hira_analysis/_qudi_fit_logic.py @@ -71,7 +71,7 @@ def __init__(self): f"Adding fit methods path: {self._additional_methods_import_path}" ) - if isinstance(self._additional_methods_import_path, (list, tuple, set)): + if isinstance(self._additional_methods_import_path, list | tuple | set): self.log.info( "Adding fit methods path list: {}".format( self._additional_methods_import_path diff --git a/qudi_hira_analysis/analysis_logic.py b/qudi_hira_analysis/analysis_logic.py index 717b498..557b5b8 100644 --- a/qudi_hira_analysis/analysis_logic.py +++ b/qudi_hira_analysis/analysis_logic.py @@ -154,7 +154,7 @@ def fit( dims: str = "1d" if data is None: - if isinstance(x, (pd.Series, pd.Index)): + if isinstance(x, pd.Series | pd.Index): x: np.ndarray = x.to_numpy() if isinstance(y, pd.Series): y: np.ndarray = y.to_numpy() @@ -493,7 +493,7 @@ def fit_raster_odmr( x = next(iter(odmr_measurements.values())).data["Freq(MHz)"].to_numpy() x_fit = np.linspace(start=x[0], stop=x[-1], num=int(len(x) * 2)) - for odmr, res in zip(odmr_measurements.values(), model_results): + for odmr, res in zip(odmr_measurements.values(), model_results, strict=False): if len(res.params) == 6: # Evaluate a single Lorentzian y_fit = model1.eval(x=x_fit, params=res.params) diff --git a/qudi_hira_analysis/data_handler.py b/qudi_hira_analysis/data_handler.py index cef3db1..4d7f627 100644 --- a/qudi_hira_analysis/data_handler.py +++ b/qudi_hira_analysis/data_handler.py @@ -3,7 +3,7 @@ import datetime import logging from pathlib import Path -from typing import TYPE_CHECKING, Callable +from typing import TYPE_CHECKING from qudi_hira_analysis.analysis_logic import AnalysisLogic from qudi_hira_analysis.io_handler import IOHandler @@ -16,6 +16,8 @@ ) if TYPE_CHECKING: + from collections.abc import Callable + import numpy as np import pandas as pd import pySPM @@ -159,7 +161,7 @@ def __tree(self, dir_path: Path, prefix: str = ""): 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): + for pointer, path in zip(pointers, contents, strict=False): yield prefix + pointer + path.name if path.is_dir(): # extend the prefix and recurse: extension = branch if pointer == tee else space diff --git a/qudi_hira_analysis/io_handler.py b/qudi_hira_analysis/io_handler.py index dbeeb2c..8b6a582 100644 --- a/qudi_hira_analysis/io_handler.py +++ b/qudi_hira_analysis/io_handler.py @@ -4,9 +4,9 @@ import inspect import itertools import pickle +from collections.abc import Callable from functools import wraps from pathlib import Path -from typing import Callable, Optional import matplotlib.pyplot as plt import numpy as np @@ -19,8 +19,8 @@ class IOHandler: def __init__( self, - base_read_path: Optional[Path] = None, - base_write_path: Optional[Path] = None, + base_read_path: Path | None = None, + base_write_path: Path | None = None, ): super().__init__() self.base_read_path = base_read_path @@ -130,7 +130,7 @@ def read_qudi_parameters(self, filepath: Path) -> dict: timestamp_str = "".join(line.split(":")[1:]).strip() datetime_str = datetime.datetime.strptime( timestamp_str, "%d.%m.%Y %Hh%Mmin%Ss" - ).replace(tzinfo=datetime.timezone.utc) + ).replace(tzinfo=datetime.UTC) params[label] = datetime_str except Exception as _: pass diff --git a/qudi_hira_analysis/measurement_dataclass.py b/qudi_hira_analysis/measurement_dataclass.py index 5344636..2942adc 100644 --- a/qudi_hira_analysis/measurement_dataclass.py +++ b/qudi_hira_analysis/measurement_dataclass.py @@ -3,13 +3,14 @@ import logging import re from dataclasses import dataclass, field -from typing import TYPE_CHECKING, Callable +from typing import TYPE_CHECKING import pandas as pd from PIL import Image if TYPE_CHECKING: import datetime + from collections.abc import Callable from pathlib import Path import lmfit @@ -200,19 +201,19 @@ def get_param_from_filename(self, unit: str) -> float | None: Examples: filename = "rabi_12dBm" - >>> get_param_from_filename(unit='dBm') + >>> get_param_from_filename(unit="dBm") 12.0 filename = "pixelscan_minus100nm" - >>> get_param_from_filename(unit='dBm') + >>> get_param_from_filename(unit="dBm") -100.0 filename = "rabi_2e-6mbar" - >>> get_param_from_filename(unit='mbar') + >>> get_param_from_filename(unit="mbar") 2e-6 filename = "rabi_2point3uW" - >>> get_param_from_filename(unit='uW') + >>> get_param_from_filename(unit="uW") 2.5 """ filename = self.filename diff --git a/tools/remove_empty_data_folders.py b/tools/remove_empty_data_folders.py index 1ffe856..b66ea4c 100644 --- a/tools/remove_empty_data_folders.py +++ b/tools/remove_empty_data_folders.py @@ -54,7 +54,7 @@ def dir_path(path: str) -> str: - use a set to store all extensions - if the length of the set > 2, keep folder - else delete folder - + Examples -------- python remove_empty_data_folders.py --path "C:\\Data"