5. Routines and wrappers

The following is a brief overview of the commands available in the SeidarT environment. More information is available in the Command reference.

5.1. Routines

5.1.1. prjbuild.py

Constructs a template and assigns default values from a PNG image. See prjbuild.

5.1.2. sourcefunction.py

Creates .dat files needed to define the source impulse. Does not need to be run if source function files are already present. See sourcefunction.

5.1.3. prjrun.py

Reads the project file assigns coefficients given that all the required fields are satisfied then runs the specified 2D forward model. You can suppress modeling and edit the stiffness and/or permittivity and conductivity coefficients. Once they are provided in the project file, they won’t be computed or overwritten from the material values. If you would like to change the material values and recompute the tensor coefficients, you need to delete the existing tensor coefficients if included in the project file. See prjrun.

5.1.4. im2anim.py

Create a animation from the model outputs. Currently, this takes some time to run which you can speed up by increasing the ‘write’ value in the project file. This only takes 2D models, and there are bugs with matplotlib that cause red/blue flashing. See im2anim.

5.1.5. arraybuild.py

Build the basis for plotting the seismograms or radargrams for the wide angle survey. You can suppress plotting which will return a .csv file. An auto-controlled gain function can be called for better visualization. The receiver locations are given by a text file with the header X,Y,Z. These locations can be given in meters relative to (0,0,0) or in indices. (0,0,0) is top left when viewing the image. See arraybuild.

5.1.6. rcxdisplay.py

Note

Originally “codisplay” in legacy code

Display the outputs of the common offset survey. This is also called to display the common midpoint survey. Similar to arrayplot.py, the gain function can be called. See rcxdisplay.

5.1.7. orientation_tensor.py

Compute the Euler angles and orientation tensor for a fabric defined by it’s trend and plunge angles. The orientation tensor isn’t required by the program but it provides useful quantitative information describing the orientation of the fabric. See orientation_tensor.

5.2. Wrappers

5.2.1. common_offset.sh

This is a wrapper that simulates a common offset survey. The receiver .xyz file is input to give the points of the survey and the source is offset from this location given the offsets for the x, y, and z directions. See common_offset.

5.2.2. common_midpoint.sh

This is similar to the common offset survey but it shifts the source and reciever away from a common midpoint. The midpoint is specified by the source location in the project file. By default the source will be to the viewer’s right of the midpoint but to flip the location of the source and reciever, set the midpoint x-value to negative. See common_midpoint.

Note

The aspect ratio for the common offset and common midpoint surveys determines the axis exaggeration. This will be updated in the future to be easier to adjust but to change this value edit the line ax.set_aspect(aspect=??) in arrayplot.py and codisplay.py then run the plotting scripts individually not the wrapper scripts.