GMT-plotting

Note

Updates for PyGMT based notebooks are carried out at irregular intervals. The GMT bash scripts are not maintained anymore.

Did you find a bug or have suggestions for improvements? Simply open a new issue or pull request.

Collection of GMT (Generic Mapping Tools) scripts and files (including digitized map content, colormaps, grid files etc.). All scripts should run with GMT versions >= 5.2.1 and < 6.0.0 . Each directory in this repository represents a single stand-alone application (individual manuals in pdf format are included as well):

Some directories include Jupyter Notebooks in which I use PyGMT, a Python interface for GMT (Tian et al., 2024) to generate the individual maps and plots (see the ▶️ symbol).

001_map_equidist_EQ: plotting global seismicity between 1960 and 2023 on equidistant map ▶️ Jupyter Notebook
002_map_equidist_EQ_GCMT: plotting focal mechanisms ("beach balls") of the global seismicity between 1964 and 2019 on equidistant map
003_map_seafloor_ages: plotting the ages of oceanic lithosphere on a global map ▶️ Jupyter Notebook
004_map_splitting_database: plotting the content of the shear-wave splitting data base on a global map
005_map_equidist_siberia: plotting an equidistant map centered on NW Siberia (and raypaths)
006_map_SKS_SKKS_areas: visualizing of SKS-SKKS pierce point areas in the D" layer ▶️ Jupyter Notebook
007_map_SKS_SKKS_pierce_points: reproducing SKS-SKKS pierce point figures of Grund & Ritter (2019), Geology
008_map_scan_tectonic: visualizing geological and tectonic content of Fennoscandia ▶️ Jupyter Notebook
009_paper_GR2020: ▶️ Jupyter Notebooks to reproduce some figures presented in our paper Grund & Ritter (2020), GJI
010_paper_RFSG2022: ▶️ Jupyter Notebook to reproduce figure 1 presented in our paper Ritter, Fröhlich, Sanz Alonso & Grund (2022) Journal of Seismology

If you make use of the content in this repository please acknowledge GMT (e.g. Wessel et al., 2013; 2019), PyGMT (Tian et al., 2024), our published papers and/or my PhD thesis in whose framework several of the scripts and notebooks were developed:

Ritter, J.R.R., Fröhlich, Y., Sanz Alonso, Y. & Grund, M. (2022), Short-scale laterally varying SK(K)S shear wave splitting at BFO, Germany – implications for the determination of anisotropic structures, Journal of Seismology, 26, 1137-1156, https://doi.org/10.1007/s10950-022-10112-w.
Grund, M. & Ritter, J.R.R. (2020), Shear-wave splitting beneath Fennoscandia - Evidence for dipping structures and laterally varying multilayer anisotropy, Geophysical Journal International, 223, 1525–1547, https://doi.org/10.1093/gji/ggaa388.
Grund, M. & Ritter, J.R.R. (2019), Widespread seismic anisotropy in Earth’s lowermost mantle beneath the Atlantic and Siberia, Geology, 47(2), 123–126, https://doi.org/10.1130/G45514.1.
Grund, M. (2019), Exploring geodynamics at different depths with shear wave splitting, Dissertation, Karlsruhe Institute of Technology (KIT), https://doi.org/10.5445/IR/1000091425.

Although I now work outside of academia as a data scientist, I provide these GMT/PyGMT examples and notebooks in the hope that they will be useful for other students, scientists or interested map creators.

Final figure outputs of a few examples are shown below. Details and further references can be found in the individual directories.

References

Tian, D., Uieda, L., Leong, W. J., Fröhlich, Y., Schlitzer, W., Grund, M., Jones, M., Toney, L., Yao, J., Magen, Y., Jing-Hui, T., Materna, K., Belem, A., Newton, T., Anant, A., Ziebarth, M., Quinn, J., & Wessel, P. (2024), PyGMT: A Python interface for the Generic Mapping Tools, v0.12.0, Zenodo, https://zenodo.org/records/11062720.
Wessel, P., Luis, J. F., Uieda, L., Scharroo, R., Wobbe, F., Smith, W. H. F. & Tian, D. (2019), The generic mapping tools version 6. Geochemistry, Geophysics, Geosystems, 20(11), 5556-5564, https://doi.org/10.1029/2019GC008515.
Wessel, P., Smith, W. H. F., Scharroo, R., Luis, J., & Wobbe, F. (2013), Generic mapping tools: improved version released. Eos, Transactions American Geophysical Union, 94(45), 409-410, https://doi.org/10.1002/2013EO450001.

009_paper_GR2020/Figure S10: Wrong colormap set up in colorwheel

In Figure S10 (009_paper_GR2020), the colormap represented by the colorwheel does not match the color-coding used for the bars of the splits. The plots in the Supplementary Material of Grund & Ritter (2020) shown up on page 28 look correct.

Suggestions to fix this issue
This Jupyter Notebook seems not completely finished. However, maybe the code snippets below can serve as an orientations, in case further work on this JN is planed.

(1) Adjust colormap used for plotting the data points

limitation: Not the same color-coding as used for the maps in the Supp Material
cell 11, line 4: reverse=True (not False)

# generate colormap for values between 0 and 360 degrees
pygmt.makecpt(
    cmap="romaO", 
    series=[0 ,360 , 1], 
    reverse=True,   # not False
    output="cmapmod.cpt",
)

(2) Adjust creation of colorwheel via Matplotlib

limitation: Problem to save the new colorwheel as (eps) file via matplotlib.pyplot.savefig. Error message FigureCanvasPS._print_figure() got an unexpected keyword argument 'figsize'

# define plotting range
theta = np.linspace(0, 2*pi, 360)  # no shift by 0.5*pi anymore
rho = ([1.22, 2])
	
# plot in polar projection, loop over the whole range 0 to 360 degrees
for ii in range(360):
	# backazimuth in seismology
	# from North (0 deg)
	ax.set_theta_offset(pi/2)
	# clockwise, i.e. to East (90 deg)
	ax.set_theta_direction(-1)
	plt.polar(
	    [theta[ii], theta[ii]], 
	    rho, 
	    color=[cmapa[0][ii], cmapa[1][ii], cmapa[2][ii]], 
	    linewidth=2,
	)

(3) Use PyGMT instead of Matplotlib to create colorwheel

limitation: Running time of the code

import pygmt

cmap_colorwheel = "romaO"
rho_min = 1.22
rho_max = 2

fig = pygmt.Figure()

pygmt.config(
    # make area outside of plot transparent
    PS_PAGE_COLOR="white@1",
    # make frame outline white
    MAP_FRAME_PEN="white",
)

fig.basemap(
    region=[0, 360, rho_min, rho_max],
    # geographic azimuth instead of standard angle
    # clockwise from North instead of counter-clockwise from East
    projection="P5c+a",
    frame="rltb",
)

pygmt.makecpt(
    cmap=cmap_colorwheel,
    cyclic=True,
    series=[0, 360, 1],
)

# takes some time
for i_ang in range(0,360,1):  # min, max], step
    rho = [rho_min, rho_max]
    fig.plot(
        x=[i_ang, i_ang],
        y=rho,
        zvalue=i_ang,
        pen="2p+z",
        cmap=True,
)

fig.show()

# fig.savefig(fname="colorwheel_N_cw_pygmt" + cmap_colorwheel + ".png")
# fig.savefig(fname="colorwheel_N_cw_pygmt" + cmap_colorwheel + ".eps")
# fig.savefig(fname="colorwheel_N_cw_pygmt" + cmap_colorwheel + ".pdf")