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https://github.com/scottprahl/laserbeamsize

python module for ISO 11146 analysis of laser beam images
https://github.com/scottprahl/laserbeamsize

iso11146 jupyter-notebook laser python

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python module for ISO 11146 analysis of laser beam images

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laserbeamsize

=============



by Scott Prahl



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Simple and fast calculation of beam sizes from a single monochrome image based

on the ISO 11146 method of variances.  Some effort has been made to make the 

algorithm less sensitive to background offset and noise.



This module also supports M² calculations based on a series of images

collected at various distances from the focused beam. 



Extensive documentation can be found at 



Installation

------------



Use ``pip``::

    

    pip install --user laserbeamsize



or ``conda``::



    conda install -c conda-forge laserbeamsize



or use immediately by clicking the Google Colaboratory button below



.. image:: https://colab.research.google.com/assets/colab-badge.svg

  :target: https://colab.research.google.com/github/scottprahl/laserbeamsize/blob/main

  :alt: Colab



Determining the beam size in an image

-------------------------------------



Finding the center and dimensions of a good beam image::



    import imageio.v3 as iio

    import laserbeamsize as lbs

    

    file = "https://github.com/scottprahl/laserbeamsize/raw/main/docs/t-hene.pgm"

    image = iio.imread(file)

    

    x, y, dx, dy, phi = lbs.beam_size(image)

    print("The center of the beam ellipse is at (%.0f, %.0f)" % (x, y))

    print("The ellipse diameter (closest to horizontal) is %.0f pixels" % dx)

    print("The ellipse diameter (closest to   vertical) is %.0f pixels" % dy)

    print("The ellipse is rotated %.0f° ccw from the horizontal" % (phi * 180/3.1416))



to produce::



    The center of the beam ellipse is at (651, 492)

    The ellipse diameter (closest to horizontal) is 369 pixels

    The ellipse diameter (closest to   vertical) is 347 pixels

    The ellipse is rotated -12° ccw from the horizontal



A visual report can be done with one function call::



    lbs.plot_image_analysis(beam)

    plt.show()



produces something like



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/hene-report.png

   :alt: HeNe report



or::



    lbs.plot_image_analysis(beam, r"Original Image $\lambda$=4µm beam", pixel_size = 12, units='µm')

    plt.show()



produces something like



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/astigmatic-report.png

   :alt: astigmatic report



Non-gaussian beams work too::



    # 12-bit pixel image stored as high-order bits in 16-bit integers

    tem02 = imageio.imread("TEM02_100mm.pgm") >> 4

    lbs.plot_image_analysis(tem02, title = r"TEM$_{02}$ at z=100mm", pixel_size=3.75)

    plt.show()



produces



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/tem02.png

   :alt: TEM02



Determining M² 

--------------



Determining M² for a laser beam is also straightforward.  Just collect beam diameters from

five beam locations within one Rayleigh distance of the focus and from five locations more

than two Rayleigh distances::



    lambda1=308e-9 # meters

    z1_all=np.array([-200,-180,-160,-140,-120,-100,-80,-60,-40,-20,0,20,40,60,80,99,120,140,160,180,200])*1e-3

    d1_all=2*np.array([416,384,366,311,279,245,216,176,151,120,101,93,102,120,147,177,217,256,291,316,348])*1e-6

    lbs.M2_radius_plot(z1_all, d1_all, lambda1, strict=True)

    plt.show()



produces



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/m2fit.png

   :alt: fit for M2



Here is an analysis of a set of images that do not meet the ISO 11146

requirements for determining M² (because the image locations are not taken

in right locations relative to the focus).  These beam images are from a HeNe

laser with slightly misaligned mirrors to primarily lase in a TEM₀₁ transverse mode.

The laser resonator had a fixed rotation of 38.7° from the plane of

the optical table.::



    lambda0 = 632.8e-9 # meters

    z10 = np.array([247,251,259,266,281,292])*1e-3 # meters

    filenames = ["sb_%.0fmm_10.pgm" % (number*1e3) for number in z10]



    # the 12-bit pixel images are stored in high-order bits in 16-bit values

    tem10 = [imageio.imread(name)>>4 for name in filenames]



    # remove top to eliminate artifact 

    for i in range(len(z10)):

        tem10[i] = tem10[i][200:,:]



    # find beam rotated by 38.7° in all images

    fixed_rotation = np.radians(38.7)

    options = {'pixel_size': 3.75, 'units': "µm", 'crop': [1400,1400], 'z':z10, 'phi':fixed_rotation}

    dy, dx= lbs.beam_size_montage(tem10, **options)  # dy and dx in microns

    plt.show()



produces



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/sbmontage.png

   :alt: montage of laser images



Here is one way to plot the fit using the above diameters::



    lbs.M2_diameter_plot(z10, dx*1e-6, lambda0, dy=dy*1e-6)

    plt.show()



In the graph on the below right, the dashed line shows the expected divergence

of a pure gaussian beam.  Since real beams should diverge faster than this (not slower)

there is some problem with the measurements (too few!).  On the other hand, the M² value 

the semi-major axis 2.6±0.7 is consistent with the expected value of 3 for the TEM₁₀ mode.



.. image:: https://raw.githubusercontent.com/scottprahl/laserbeamsize/main/docs/sbfit.png

   :alt: fit



License

-------



``laserbeamsize`` is licensed under the terms of the MIT license.