General description

This repository is just a collection of useful Python code for SNOM data processing. Not all the implemented procedures are finished and tested.

NeaSpectrum class

The NeaSpectra.py implements a base class for nano-FTIR, TERS, PTE, and PsHetPoint Spectroscopy data collected by NeaSNOM/NeaSCOPE instruments. readNeaSpectrum method of the NeaSpectrum class read the measurement parameter and the measurement data channels for the measurement .txt file.

Usage

Examples\test_neaspectrummodule.py provides an example of creating a NeaSpectrum object and the measurement load data:

import NeaSpectra as neas
s = neas.NeaSpectrum()
s.readNeaSpectrum(file_name)

The parameters attribute of the NeaSpectrum object is a dictionary containing the measurement parameters. For example:

print(s.parameters["Project"])
print(s.parameters["Description"])

The data attribute is also a dictionary containing the measurement channels as key-value pairs. For example:

s.data["Wavenumber"][0,0,:]
s.data["PTE"][0,0,:]
s.data["O3P"][0,0,:]

In the case of hyperspectral measurement (linescan or areascan) the data channels are 3D numpy arrays, while in case of single spectra it is a simple numpy array with only one index.

The SaveSpectraToDAT() method of the class enables you to save the spectrum recorded to a specific data channel. For example, to save/write the O2P spectrum into a .dat file, you can call:

s.SaveSpectraToDAT("O2P")

You will get a file with two columns. The first is the wavenumber and the second is the O2P spectrum. The file will have the same name as the original file with '.dat' extension in the same location where the original file is.

NeaImage class

The NeaImager.py file implements the base class for imaging measurements (PsHet, PTE, AFM) collected with NeaSCOPE instruments. The attributes of the class contain the basic parameters from the .gwy file. As an extra, you can load the additional measurement parameters from the info text file generated when you save the measurements.

Usage

Examples\test_neaimagemodule.py provides an example how to create a NeaImage object and load the measurement. You have to create the object and call read_from_gwyfile() and define which measurement channel you want to load from the .gwy file:

import NeaImager as neaim
channelname = 'O3P raw'
m = neaim.NeaImage()
m.read_from_gwyfile(meas_file_path,channelname)

The data attribute contains the measured image as a 2d numpy array. The most basic measurement parameters related to the image are also read from the .gwy file. They are xreal,yreal - real, physical lengths of the corresponding axes, xoff,yoff - x and y offset of the middlepoint of teh corresponding axes (this is the scanner centor position basically), xres,yres - number of pixels along each axes. You can use these to plot the data with the physically correct axes. Example:

import matplotlib.pyplot as plt
# Calculate min and max of the axis (*1e6 converts to microns from meters)
xmin = (-m.xreal/2+m.xoff)*1e6
xmax = (m.xreal/2+m.xoff)*1e6
ymin = (-m.yreal/2+m.yoff)*1e6
ymax = (m.yreal/2+m.yoff)*1e6
# Plot data with the correct axis extent
plt.imshow(m.data, extent=[xmin, xmax, ymin, ymax])
plt.xlabel('Scanner Position - X / micron')
plt.ylabel('Scanner Position - Y / micron')
plt.title('Original image')
plt.show()

Other measurement parameters can be read from the info text file generated by the instrument. These are contained in the parameters attribute of the NeaImage object as a dictionary. You can access them by their corresponding keys in the dictionary. For example:

m.parameters = m.read_info_file(info_file_path)
print(s.parameters["Scan"])
print(s.parameters["TargetWavelength"])
print(s.parameters["LaserSource"])

To list the dictionary keys just call print(list(m.parameters.keys())).

Image correction methods

The NeaImager module not only defines the NeaImage class but also provides methods to correct image artifact and normalize the pixel values. These method are BackgroundPolyFit, LineLevel, NeaImage, RotatePhase, SelfReferencing, SimpleNormalize. The inputobject is a NeaImage object for all methods and their return value is a new NeaImage objact with the corresponding correction method applied.

Examples\test_imageprocess.ipynb notebook demonstrates the usage of all the available methods.