PySpectrometer2

The second incarnation of the Spectrometer project!

This is a more advanced, but more flexible version of the original program. It changes the spectrometer from educational 'toy' to serious instrument, which can easily compete with commercial units costing thousands of dollars!

This program, hardware design, and associated information is Open Source (see Licence), but if you have gotten value from these kinds of projects and think they are worth something, please consider donating: https://paypal.me/leslaboratory?locale.x=en_GB This project is a follow on from: https://github.com/leswright1977/PySpectrometer

This readme is accompanied by youtube videos, showing how to build and use the spectrometer! Visit my Youtube Channel at: https://www.youtube.com/leslaboratory

There is a video on this project here: https://youtu.be/SCp9T8NKfnM

Rationale for the new build

Recent changes in the OS (Bullseye) broke the old version e.g broken video, broken dependencies and so on. PySpectrometer v3.0 was hacked and fixed as of 3.1), however I have been thinking about a rewrite of this software for a while, so here it is!

Accuracy has been significantly improved by implementing multi-wavelength calibration and a Polynomial regression data fit to compute wavelengths as precisely as possible across the measured range.

Tk has been dropped as the GUI to allow easier maintainability, extendability and flexibility. The new interface is coded entirely in OpenCV, and whilst things like trackbars and buttons are now dropped in favour of keybindings, this frees up screen real estate, and allows the support of resizing without fuss, and fullscreen mode is now supported!

In Fullscreen mode on Raspberry Pi systems, the interface is designed to fit 800 x 480 screens, which seem to be a common resolution for RPi LCD's, paving the way for the creation of a stand alone benchtop instrument.

Whats new:

• Higher resolution (800px wide graph).

• 3 row pixel averaging of sensor data.

• Fullscreen option for the Spectrometer graph.

• 3rd order polynomial fit of calibration data for accurate measurement.

• Improved graph labelling.

• Labelled measurement cursors.

• Optional waterfall display for recording spectra changes over time.

• Key Bindings for all operations.

• Analogue Gain control for the Picam

The functionality of the previous version has been retained, including peak hold, peak detect, Savitsky Golay filter, and the ability to save graphs as png and data as CSV.

A very cool addition to this project is a Waterfall display! This allows the recording of change in in wavelength over time. For my purposes this is especially useful for Dye Lasers, however this may be of use to those observing the spectra of light sources that may change in intensity or wavelength.

Example waterfall display of a fluorescent lamp:

Waterfall display of a Dye laser being tuned (Coumarin-1). The jagged tuning curve is because this laser was hand-tuned!

Below the tuning curve of Rhodamine 6G

Hardware

The hardware is simple and widely available and so should be easily to duplicate without critical alignment or difficult construction. The hard work was developing the software.

Resolution/accuracy seems to be down to the nanometre with a well built and calibrated setup, which is excellent for the price of the hardware, especially when you consider the price of commercial components such as the Hamamatsu C12880MA breakout boards which run north of 300 bucks, and has a resolution of 15nm. Of course, this build is physically much larger, but not enormous!

Standard Spectroscope

For the standard build, I used a pocket spectroscope(link below) coupled into a picamera by means of a zoom lens. The job is simple: Mount the zoom lens on the picam, and mount the spectroscope in front, and focus the camera on the spectrum, until it is sharp and clear. Use either daylight (which has pronounced Fraunhoffer lines) or a fluorescent lamp, which has pronounced emission lines. The following command will help you: libcamera-hello -t 0

The hardware consists of:

• A commercial Diffraction grating Spectroscope https://www.patonhawksley.com/product-page/benchtop-spectroscope

• A Raspberry Pi Camera (with an M12 Thread) https://thepihut.com/products/raspberry-pi-camera-adjustable-focus-5mp

• A CCTV Lens with Zoom (M12 Thread) (Search eBay for F1.6 zoom lens)

Everything is assembled on an aluminium base (note the Camera is not cooled, the heatsink was a conveniently sized piece of aluminium.)

Miniture Spectroscope

The build is as simple as the standard version, however, uses a miniature pocket spectrometer.

• A commercial Diffraction grating Pocket Spectroscope: https://www.patonhawksley.com/product-page/pocket-spectroscope

• A Raspberry Pi Camera (with an M12 Thread): https://thepihut.com/products/raspberry-pi-camera-adjustable-focus-5mp

• M12x0.5 F2.0 Fixed 12mm Focal length Lens: (search eBay)

Stand alone unit

Above, a compact unit built with a Hyperpixel 4 inch screen, running on fullscreen mode (800 x 480)

https://shop.pimoroni.com/products/hyperpixel-4?variant=12569539706963

Custom units

There is nothing to stop you building a spectrometer head with a couple of razor blades, a diffraction grating, a couple of lenses and a Picam! The software should work just the same as shown in this readme!

User Guide

Key Bindings:

Graph Display Controls

• t/g = Analogue Gain up/down (not available on USB version, see below for alternative camera controls)
• o/l = savpoly up/down
• i/k = peak width up/down
• u/j = Label threshold up/down
• h = hold peaks

Calibration and General Software

• m = measure (Toggles measure function. In this mode a crosshairs is displayed on the Spectrogram that allows the measurement of wavelength)
• p = record pixels (Toggles pixel function (Part of the calibration procedure) allows the selection of multiple pixel positions on the graph)
• x = clear points (Clear selected pixel points above)
• c = calibrate (Enter the calibration routine, requires console input)
• s = save data (Saves Spectrograph as png and CSV data. Saves waterfall as png.
• q = quit (Quit Program)

Starting the program

First, clone this repo!

In /src you will find:

• PySpectrometer2-Picam2-v1.0.py (PySpectrometer for Raspberry Pi)
• PySpectrometer2-USB-v1.0.py (USB version of this program (This is for USB Cameras See end of Readme)).
• specFunctions.py (A library of functions including: Wavelength to RGB, SavGol filter from Scipy, Peak detect from peakutils, readcal and writecal.

Dependencies

Run: sudo apt-get install python3-opencv

Also note, this build is designed for Raspberry Pi OS Bullseye, and will only work with the new libcamera based python library (picamera2) It will not work with older versions of Raspbery Pi OS. You will however be able to use PySpectrometer2-USB-v1.0.py with an external USB camera with other Operating Systems.

To run the program, first make it executable by running: chmod +x PySpectrometer2-Picam2-v1.0.py

Run by typing: ./PySpectrometer2-Picam2-v1.0.py

Note to also display the waterfall display, run with the option: ./PySpectrometer2-Picam2-v1.0.py --waterfall

To run in fullscreen mode (perform calibration in standard mode first), run with the option: ./PySpectrometer2-Picam2-v1.0.py --fullscreen

When first started, the spectrometer is in an uncalibrated state! You must therefore perform the calibration procedure, but at this stage you should be able to focus and align your camera with your spectroscope using the preview window. Is is expected that red light is on the right, and blue-violet on the left. An excellent choice for this is daylight, as well defined Fraunhoffer lines are indicative of good camera focus.

Calibration

This version of the PySpectrometer performs Polynomial curve fitting of the user provided calibration wavelengths. This procedure if done with care with result in a precision instrument!

When light from a diffraction grating falls upon a flat sensor the dispersion of light is not linear, and so calibration with just two data points (as in the old version of this software) will result in inaccurate readings. This nonlinearity is likely compounded by additional nonlinearities introduced by the camera lenses. To address the nonlinearity, the user must provide the pixel positions of at least 3 known wavelengths (4 to 6 is highly recommended for high accuracy!). This information is then used by the program to compute the wavelengths of every single pixel position of the sensor.

Where 3 wavelengths are used for calibration, the software will perform a 2nd order polynomial fit (Reasonably accurate)

Where 4 or more wavelengths are used, the software will perform a 3rd order polynomial fit (Very accurate)

Assuming your physical spectrometer setup is rigid and robust (not held together with gravity, tape or hot glue!), calibration will only need to be done once (Data is saved to a file called: caldata.txt), and therafter when any change is made to the physical setup.

Direct your Spectrometer at a light source with many discrete emission lines. A target illuminated by Lasers would be an excellent (though very expensive!) choice! An inexpensive alternative is a Fluorescent tube.

You should be able to identify several peaks in your graph, now you need to match them up with known good data. For serious work I would recommend an academic resource such as: https://physics.nist.gov/PhysRefData/Handbook/Tables/mercurytable2.htm how