Analytics suite for qubit SPM using FPGA timetaggers
pip install qudi-hira-analysispip install --upgrade qudi-hira-analysisIf you are publishing scientific results that use this code, as good scientific practice you should cite this work.
- Automated data import and handling
- Works natively with data from Qudi and Qudi-Hira
- Fast and robust curve fitting for NV-ODMR 2D maps, Autocorrelation, Rabi, Ramsey, T1, T2 and more...
- Supports all file formats used in NV magnetometry, AFM, MFM and NV-SPM
- Uses a Dataclass-centered design for easy access to data and metadata
from pathlib import Path
import seaborn as sns
from qudi_hira_analysis import DataHandler
dh = DataHandler(
data_folder=Path("C:/Data"), # Path to data folder
figure_folder=Path("C:/QudiHiraAnalysis"), # Path to figure folder
measurement_folder=Path("20230101_NV1") # Measurement folder name (optional)
)
# Lazy-load all pulsed measurements with "odmr" in the path into a Dataclass
odmr_measurements = dh.load_measurements("odmr", pulsed=True)
# Fit ODMR data with a double Lorentzian
odmr = odmr_measurements["20230101-0420-00"]
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")
sns.lineplot(x=x_fit, y=y_fit, ax=ax, label="Fit")
# Calculate the ODMR splitting
ax.axvline(result.best_values["l0_center"], ls="--", color="C1")
ax.axvline(result.best_values["l1_center"], ls="--", color="C1")
splitting = result.best_values["l1_center"] - result.best_values["l0_center"]
ax.set_title(f"ODMR splitting = {splitting / 1e6:.1f} MHz")
# Generate fit report
print(result.fit_report())
# Save figure
dh.save_figures(filepath=Path("odmr_fit"), fig=ax.get_figure())
The full documentation is available here.
flowchart TD
IOHandler <-- Handle IO operations --> DataLoader;
DataLoader <-- Map IO callables --> DataHandler;
Qudi[Qudi FitLogic] --> AnalysisLogic;
AnalysisLogic -- Inject fit functions --> DataHandler;
DataHandler -- Fit data --> Plot;
DataHandler -- Structure data --> MeasurementDataclass;
MeasurementDataclass -- Plot data --> Plot[JupyterLab Notebook];
Plot -- Save plotted data --> DataHandler;
style MeasurementDataclass fill: #bbf, stroke: #f66, stroke-width: 2px, color: #fff, stroke-dasharray: 5 5
flowchart LR
subgraph Standard Data
MeasurementDataclass --o filepath1[filepath: Path];
MeasurementDataclass --o data1[data: DataFrame];
MeasurementDataclass --o params1[params: dict];
MeasurementDataclass --o timestamp1[timestamp: datetime.datetime];
MeasurementDataclass --o methods1[get_param_from_filename: Callable];
MeasurementDataclass --o methods2[set_datetime_index: Callable];
end
subgraph Pulsed Data
MeasurementDataclass -- pulsed --> PulsedMeasurementDataclass;
PulsedMeasurementDataclass -- measurement --> PulsedMeasurement;
PulsedMeasurement --o filepath2[filepath: Path];
PulsedMeasurement --o data2[data: DataFrame];
PulsedMeasurement --o params2[params: dict];
PulsedMeasurementDataclass -- laser_pulses --> LaserPulses;
LaserPulses --o filepath3[filepath: Path];
LaserPulses --o data3[data: DataFrame];
LaserPulses --o params3[params: dict];
PulsedMeasurementDataclass -- timetrace --> RawTimetrace;
RawTimetrace --o filepath4[filepath: Path];
RawTimetrace --o data4[data: DataFrame];
RawTimetrace --o params4[params: dict];
end
This license of this project is located in the top level folder under LICENSE. Some specific files contain their
individual licenses in the file header docstring.
git clone https://github.com/dineshpinto/qudi-hira-analysis.git
cd qudi-hira-analysis
poetry install
poetry run python -m ipykernel install --user --name=qudi-hira-analysis
poetry run jupyter labThe Makefile located in notebooks/ is configured to generate a variety of outputs:
-
make pdf: Converts all notebooks to PDF (requires LaTeX backend) -
make html: Converts all notebooks to HTML -
make py: Converts all notebooks to Python (can be useful for VCS) -
make all: Sequentially runs all the notebooks in folder
To use the make command on Windows you can install Chocolatey, then
install make with choco install make
