PWSpy¶
PWSpy is a Python library for working with Partial Wave Spectroscopic Microscopy data. It provides a concise and simple interface for loading and analyzing experimental data. Support for modern as well as legacy file formats of PWS data is provided.
With PWSpy, it is trivial to skip to skip the basics and get to the heart of extracting meaningful results from your experimental data. Basic operations such as normalization, hardware compensation, and calibration are handled with the call of a single method. Additionally, the library provides a means for conveniently loading and storing auxiliary data such as ROIs, notes, and analysis outputs.
Utility functionality for generating visualizations, automatic colocalization, calculation of thin-film reflectance based on fresnel equations, parsing metadata from the graph-based acquisition engine, and more are provided in the utility subpackage.
Usage¶
Almost any usage of PWSpy will start with loading of experimental data. The simplest way to do this is
with the pwspy.dataTypes.Acquisition class. An instance of Acquisition provides properties (pws, dynamics,
fluorescence) which provide references to colocalized measurements which may be part of a single acquisition.
import pwspy.dataTypes as pwsdt
acq = pwsdt.Acquisition(pathToData)
pwsMetadata = acq.pws
if acq.dynamics is not None:
dynamicsMetadata = acq.dynamics
if acq.fluorescence is not None:
listOfFluorMetadata = acq.fluorescence
An acquisition also provides access to information that applies to all measurements such as ROIs and automated imaging metadata.
roiInfos: List[Tuple[str, int, Roi.FileFormat]] = acq.getRois()
for roiInfo in roiInfos:
roiFile = acq.loadRoi(*roiInfo)
Each sub-measurement metadata object of an Acquisition provides access to information specific to that measurement such as analysis results and raw data.
from pwspy.analysis.pws import PWSAnalysisResults
from pwspy.analysis.dynamics import DynAnalysisResults
listOfAnalysisNames = acq.pws.getAnalyses()
analysisName = listOfAnalysisNames[0]
pAnalysisResults: PWSAnalysisResults = acq.pws.loadAnalysis(analysisName)
dAnalysisResults: DynAnalysisResults = acq.dynamics.loadAnalysis(analysisName)
roi: pwsdt.Roi = acq.loadRoi(roiName, roiNumber).getRoi()
print(f"Average nuclear Sigma is: {pAnalysisResults.rms[roi.mask].mean()}")
print(f"Average nuclear Sigma_t^2 is: {dAnalysisResults.rms_t_squared[roi.mask].mean()}")
There is much more functionality in this library, please see the examples and API documentation.
API¶
Contains all code used for the analysis of data acquired with the PWS system. |
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Custom datatypes that are commonly used in the analysis of PWS related data. |
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Useful subpackages ranging many different topics |
Examples¶
- Examples
- Running basic PWS analysis on a single image.
- Performing FFT to visualize the estimated depth of cell features
- Compile analysis results to a table of average values within each ROI
- Basic loading of ROI’s to extract data from specific regions
- Using a hand-drawn ROI to generate a reference pseudo-measurement
- Blurring data laterally to smooth a reference image.
- Measuring Sigma using only a limited range of the OPD signal.
- Generating new position lists to enable colocalized measurements on multiple systems.