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已同步 2025-08-06 20:46:52 +08:00
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Craig Warren
@@ -115,6 +115,8 @@ Microsoft Windows
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* Download and install Build Tools for Visual Studio 2017 from the `Visual Studio downloads page <https://www.visualstudio.com/downloads/>`_ in the section Other Tools and Frameworks. Use the default installation options.
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Alternatively if you are using Windows 10 and feeling adventurous you can install the `Windows Subsystem for Linux <https://msdn.microsoft.com/en-gb/commandline/wsl/about>`_ and then follow the Linux install instructions for gprMax.
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3. Build and install gprMax
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---------------------------
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@@ -7,7 +7,7 @@ This section presents comparisons of models using different numerical modelling
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FDTD/MoM
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========
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The Finite-Difference Time-Domain (FDTD) method from gprMax is compared with the Method of Moments (MoM) from the MATLAB antenna toolbox (http://uk.mathworks.com/products/antenna/).
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The Finite-Difference Time-Domain (FDTD) method from gprMax is compared with the Method of Moments (MoM) from the `MATLAB antenna toolbox <http://uk.mathworks.com/products/antenna/>`_.
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Bowtie antenna in free space
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----------------------------
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@@ -11,16 +11,16 @@ gprMax is electromagnetic wave simulation software that is based on the Finite-D
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We considered developing a CAD-based graphical user interface (GUI) but, for now, decided against it. There were two guiding principals behind this design decision: firstly, users most often perform a series of related simulations with varying parameters to solve or optimize a particular problem; and secondly, we decided the limited resources we had were best concentrated on developing advanced modelling features for GPR within software that could easily be interfaced with other tools. Although a CAD-based GUI is useful for creating single simulations it becomes increasingly cumbersome for a series of simulations or where simulations contain heterogeneities, e.g. a model of a soil with stochastically varying electrical properties.
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**How is gprMax licensed?**
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gprMax is released under the GNU General Public License v3 or higher (http://www.gnu.org/copyleft/gpl.html). This means when distributing derived works, the source code of the work must be made available under the same license.
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gprMax is released under the `GNU General Public License v3 or higher <http://www.gnu.org/copyleft/gpl.html>`_. This means when distributing derived works, the source code of the work must be made available under the same license.
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**Do I need to learn Python to use gprMax?**
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No, but it can be beneficial to know a little Python. We have made it easier to create more complex simulations in gprMax through scripting in the input file. This is achieved by allowing blocks of Python code to be written in the input file which are executed when the file is read by gprMax.
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**Can I still do all my pre/post-processing for gprMax in MATLAB?**
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Yes, MATLAB has built-in functions to read HDF5 files (http://uk.mathworks.com/help/matlab/high-level-functions.html).
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Yes, `MATLAB has built-in functions to read HDF5 files <http://uk.mathworks.com/help/matlab/high-level-functions.html>`_.
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**Can I convert my output file to a text file, e.g. to import into Microsoft Excel**
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Yes, we recommend you download HDFView (https://support.hdfgroup.org/products/java/hdfview/) which is free viewer for HDF files. You can then export any of datasets in the output file to a text (ASCII) file that can be imported into Microsoft Excel. To do so right-click on the dataset in HDFView and choose Export Dataset -> Export Data to Text File.
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Yes, we recommend you download `HDFView <https://support.hdfgroup.org/products/java/hdfview/>`_ which is free viewer for HDF files. You can then export any of datasets in the output file to a text (ASCII) file that can be imported into Microsoft Excel. To do so right-click on the dataset in HDFView and choose Export Dataset -> Export Data to Text File.
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**But converting my input file from the old version of gprMax will be really painful**
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Hopefully not! We have provided a Python module to help you convert input files from the old version of gprMax to use syntax introduced in version 3.
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@@ -32,4 +32,4 @@ Spatial resolution should be chosen to mitigate numerical dispersion and to adeq
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gprMax builds objects in a model in the order the objects were specified in the input file, using a layered canvas approach. This means, for example, a cylinder object which comes after a box object in the input file will overwrite the properties of the box object at any locations where they overlap. This approach allows complex geometries to be created using basic object building blocks.
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**Can I run gprMax on my HPC/cluster?**
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Yes. gprMax has been parallelised using OpenMP and features a task farm based on MPI. For more information read the :ref:`section on parallelism. <openmp-mpi>`
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Yes. gprMax has been parallelised using OpenMP and features a task farm based on MPI. For more information read the :ref:`parallel performance section of the User Guide <openmp-mpi>`
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@@ -32,7 +32,7 @@ New commands
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* ``#add_dispersion_drude`` is used to add Drude dispersive properties to a ``#material``
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* ``#soil_peplinski`` is a soil mixing model that can be used with ``#fractal_box`` to generate soil(s) with more realistic dielectric and geometric properties
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* ``#cylindrical_sector`` is a new object building command
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* ``#geometry_view`` replaces ``#geometry_file`` or ``#geometry_vtk`` and is used to create views of the geometry of the model in open source Visualization ToolKit (VTK) (http://www.vtk.org) format which can be viewed in many free readers, such as Paraview (http://www.paraview.org)
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* ``#geometry_view`` replaces ``#geometry_file`` or ``#geometry_vtk`` and is used to create views of the geometry of the model in open source `Visualization Toolkit (VTK) <http://www.vtk.org>`_ format which can be viewed in many free readers, such as `Paraview <http://www.paraview.org>`_
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* ``#fractal_box`` is used to create a volume with a fractal distribution of properties
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* ``#add_surface_roughness`` is used to add a rough surface to a ``#fractal_box``
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* ``#add_surface_water`` is used to add surface water to a ``#fractal_box`` that has a rough surface
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@@ -58,7 +58,7 @@ Changed commands
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Retired commands
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----------------
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* ``#analysis`` and ``#end_analysis`` are no longer required as: sources and receivers can be specified anywhere is the input file; the output file automatically has the same name as the input file with a ``.out`` extension; the format of the output file is now HDF5 (https://www.hdfgroup.org/HDF5/); gprMax can be run with the syntax ``gprMax my_input_file -n number_of_runs``, where ``number_of_runs`` can be used to rerun the model for creating scans and/or moving geometry between runs.
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* ``#analysis`` and ``#end_analysis`` are no longer required as: sources and receivers can be specified anywhere is the input file; the output file automatically has the same name as the input file with a ``.out`` extension; the format of the output file is now `HDF5 <http://www.hdfgroup.org/HDF5/>`_; gprMax can be run with the syntax ``gprMax my_input_file -n number_of_runs``, where ``number_of_runs`` can be used to rerun the model for creating scans and/or moving geometry between runs.
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* ``#tx`` is no longer required as the polarisation and position of a source is now specified in the source command, e.g. ``#hertzian_dipole: y 0.05 0.05 0.05 myPulse``
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* ``#cylinder_new`` has become ``#cylinder``
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* ``#cylindrical_segment`` was under-used and its effect can be created by cutting a ``#cylinder`` with a ``#box``
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@@ -111,7 +111,7 @@ Fractal correlated noise [TUR1997]_ is used to describe the stochastic distribut
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Library of antenna models
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-------------------------
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gprMax now includes Python modules with pre-defined models of antennas that behave similarly to commercial antennas [WAR2011]_. Currently models of antennas similar to Geophysical Survey Systems, Inc. (GSSI) (http://www.geophysical.com) 1.5 GHz (Model 5100) antenna, and MALA Geoscience (http://www.malags.com/) 1.2 GHz antenna are included. By taking advantage of Python scripting in input files, using such complex structures in a model is straightforward without having to be built step-by-step by the user. For further details see the :ref:`Python section <python>`.
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gprMax now includes Python modules with pre-defined models of antennas that behave similarly to commercial antennas [WAR2011]_. Currently models of antennas similar to `Geophysical Survey Systems, Inc. (GSSI) <http://www.geophysical.com>`_ 1.5 GHz (Model 5100) antenna, and `MALA Geoscience <http://www.malags.com/>`_ 1.2 GHz antenna are included. By taking advantage of Python scripting in input files, using such complex structures in a model is straightforward without having to be built step-by-step by the user. For further details see the :ref:`Python section <python>`.
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Anisotropic materials
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---------------------
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@@ -136,9 +136,9 @@ With increased research into quantitative information from GPR, it has become ne
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Open source, robust, file formats
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---------------------------------
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Alongside improvements to the input file there is a new output file format – HDF5 (http://www.hdfgroup.org/HDF5/) – to manage the larger and more complex data sets that are being generated. HDF5 is a robust, portable and extensible format with a number of free readers available. For further details see the :ref:`output file section <output>`.
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Alongside improvements to the input file there is a new output file format – `HDF5 <http://www.hdfgroup.org/HDF5/>`_ – to manage the larger and more complex data sets that are being generated. HDF5 is a robust, portable and extensible format with a number of free readers available. For further details see the :ref:`output file section <output>`.
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In addition, the Visualization Toolkit (VTK) (http://www.vtk.org) is being used for improved handling and viewing of the detailed 3D FDTD geometry meshes. The VTK is an open-source system for 3D computer graphics, image processing and visualisation. It also has a number of free readers available including Paraview (http://www.paraview.org). For further details see the :ref:`geometry view command <geometryview>`.
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In addition, the `Visualization Toolkit (VTK) <http://www.vtk.org>`_ is being used for improved handling and viewing of the detailed 3D FDTD geometry meshes. The VTK is an open-source system for 3D computer graphics, image processing and visualisation. It also has a number of free readers available including `Paraview <http://www.paraview.org>`_. For further details see the :ref:`geometry view command <geometryview>`.
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@@ -156,7 +156,7 @@ where ``c1`` can be either y (yes) or n (no) which turns on or off the messages
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#num_threads:
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-----------------
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Allows you to control how many OpenMP threads (usually the number of physical CPU cores available) are used when running the model. The most computationally intensive parts of gprMax, which are the FDTD solver loops, have been parallelised using OpenMP (http://openmp.org) which supports multi-platform shared memory multiprocessing. The syntax of the command is:
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Allows you to control how many OpenMP threads (usually the number of physical CPU cores available) are used when running the model. The most computationally intensive parts of gprMax, which are the FDTD solver loops, have been parallelised using `OpenMP <http://openmp.org>`_ which supports multi-platform shared memory multiprocessing. The syntax of the command is:
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.. code-block:: none
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@@ -374,7 +374,7 @@ At the boundaries between different materials in the model there is the question
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#geometry_view:
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---------------
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Allows you output to file(s) information about the geometry of model. The file(s) use the open source Visualization ToolKit (VTK) (http://www.vtk.org) format which can be viewed in many free readers, such as Paraview (http://www.paraview.org). The command can be used to create several 3D views of the model which are useful for checking that it has been constructed as desired. The syntax of the command is:
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Allows you output to file(s) information about the geometry of model. The file(s) use the open source `Visualization ToolKit (VTK) <http://www.vtk.org>`_ format which can be viewed in many free readers, such as `Paraview <http://www.paraview.org>`_. The command can be used to create several 3D views of the model which are useful for checking that it has been constructed as desired. The syntax of the command is:
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.. code-block:: none
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@@ -845,7 +845,7 @@ Provides a simple method to allow you to move the location of all simple sources
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#snapshot:
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----------
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Allows you to obtain information about the electromagnetic fields within a volume of the model at a given time instant. The file(s) use the open source Visualization ToolKit (VTK) (http://www.vtk.org) format which can be viewed in many free readers, such as Paraview (http://www.paraview.org). The syntax of this command is:
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Allows you to obtain information about the electromagnetic fields within a volume of the model at a given time instant. The file(s) use the open source `Visualization ToolKit (VTK) <http://www.vtk.org>`_ format which can be viewed in many free readers, such as `Paraview <http://www.paraview.org>`_. The syntax of this command is:
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.. code-block:: none
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@@ -7,7 +7,7 @@ Parallel execution
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OpenMP
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======
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The most computationally intensive parts of gprMax, which are the FDTD solver loops, have been parallelised using OpenMP (http://openmp.org) which supports multi-platform shared memory multiprocessing.
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The most computationally intensive parts of gprMax, which are the FDTD solver loops, have been parallelised using `OpenMP <http://openmp.org>`_ which supports multi-platform shared memory multiprocessing.
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By default gprMax will try to determine and use the maximum number of OpenMP threads (usually the number of physical CPU cores) available on your machine. You can override this behaviour in two ways: firstly, gprMax will check to see if the ``#num_threads`` command is present in your input file; if not, gprMax will check to see if the environment variable ``OMP_NUM_THREADS`` is set. This can be useful if you are running gprMax in a High-Performance Computing (HPC) environment where you might not want to use all of the available CPU cores.
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@@ -16,12 +16,12 @@ MPI
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The Message Passing Interface (MPI) has been utilised to implement a simple task farm that can be used to distribute a series of models as independent tasks. This can be useful in many GPR simulations where a B-scan (composed of multiple A-scans) is required. Each A-scan can be task-farmed as a independent model. Within each independent model OpenMP threading will continue to be used (as described above). Overall this creates what is know as a mixed mode OpenMP/MPI job.
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By default the MPI task farm functionality is turned off. It can be switched on using the ``-mpi`` command line flag. MPI requires an installation of the ``mpi4py`` Python package, which itself depends on an underlying MPI installation, usually OpenMPI (http://www.open-mpi.org). On Microsoft Windows ``mpi4py`` requires Microsoft MPI 6 (https://www.microsoft.com/en-us/download/details.aspx?id=47259).
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By default the MPI task farm functionality is turned off. It can be switched on using the ``-mpi`` command line flag. MPI requires an installation of the ``mpi4py`` Python package, which itself depends on an underlying MPI installation, usually `OpenMPI <http://www.open-mpi.org>`_. On Microsoft Windows ``mpi4py`` requires `Microsoft MPI 6 <https://www.microsoft.com/en-us/download/details.aspx?id=47259>`_.
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HPC job scripts
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===============
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HPC environments usually require jobs to be submitted to a queue using a job script. The following are examples of job scripts for a HPC environment that uses Open Grid Scheduler/Grid Engine (http://gridscheduler.sourceforge.net/index.html), and are intended as general guidance to help you get started. Using gprMax in an HPC environment is heavily dependent on the configuration of your specific HPC/cluster, e.g. the names of parallel environments (``-pe``) and compiler modules will depend on how they were defined by your system administrator.
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HPC environments usually require jobs to be submitted to a queue using a job script. The following are examples of job scripts for a HPC environment that uses O`pen Grid Scheduler/Grid Engine <http://gridscheduler.sourceforge.net/index.html>`_, and are intended as general guidance to help you get started. Using gprMax in an HPC environment is heavily dependent on the configuration of your specific HPC/cluster, e.g. the names of parallel environments (``-pe``) and compiler modules will depend on how they were defined by your system administrator.
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OpenMP example
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@@ -75,11 +75,11 @@ A job array means that exactly the same submit script is going to be run multipl
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Eddie
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-----
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Eddie is the Edinburgh Compute and Data Facility (ECDF) - http://www.ed.ac.uk/information-services/research-support/research-computing/ecdf/high-performance-computing - run by the University of Edinburgh. The following are useful notes to get gprMax installed and running on eddie3 (the third iteration of the cluster):
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Eddie is the `Edinburgh Compute and Data Facility (ECDF) <http://www.ed.ac.uk/information-services/research-support/research-computing/ecdf/high-performance-computing>`_ run by the `University of Edinburgh <http://www.ed.ac.uk>`_. The following are useful notes to get gprMax installed and running on eddie3 (the third iteration of the cluster):
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* Git is already installed on eddie3, so you don't need to install it through Anaconda, you can proceed directly to cloning the gprMax GitHub repository with ``git clone https://github.com/gprMax/gprMax.git``
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* Anaconda is already installed as an application module on eddie3. You should follow these instructions (https://www.wiki.ed.ac.uk/display/ResearchServices/Anaconda) to ensure Anaconda environments will be created in a suitable location (not your home directory as you will rapidly run out of space). Before you proceed to create the Anaconda environment for gprMax you must make sure the OpenMPI module is loaded with ``module load openmpi``. This is neccessary so that the ``mpi4py`` Python module is correctly linked to OpenMPI. You can then create the Anaconda environment with ``conda env create -f conda_env.yml``
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* Anaconda is already installed as an application module on eddie3. You should follow `these instructions <https://www.wiki.ed.ac.uk/display/ResearchServices/Anaconda>`_ to ensure Anaconda environments will be created in a suitable location (not your home directory as you will rapidly run out of space). Before you proceed to create the Anaconda environment for gprMax you must make sure the OpenMPI module is loaded with ``module load openmpi``. This is neccessary so that the ``mpi4py`` Python module is correctly linked to OpenMPI. You can then create the Anaconda environment with ``conda env create -f conda_env.yml``
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* You should then activate the gprMax Anaconda environment, and build and install gprMax according the standard installation procedure.
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@@ -7,7 +7,7 @@ Output data
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Field(s) output
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===============
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gprMax produces an output file that has the same name as the input file but with ``.out`` appended. The output file uses the widely-supported HDF5 (https://www.hdfgroup.org/HDF5/) format which was designed to store and organize large amounts of numerical data. There are a number of free tools available to read HDF5 files. Also MATLAB has high- and low-level functions for reading and writing HDF5 files, i.e. ``h5info`` and ``h5disp`` are useful for returning information and displaying the contents of HDF5 files respectively. gprMax includes some Python modules (in the ``tools`` package) to help you view output data. These are documented in the :ref:`tools section <plotting>`.
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gprMax produces an output file that has the same name as the input file but with ``.out`` appended. The output file uses the widely-supported `HDF5 <https://www.hdfgroup.org/HDF5/>`_ format which was designed to store and organize large amounts of numerical data. There are a number of free tools available to read HDF5 files. Also MATLAB has high- and low-level functions for reading and writing HDF5 files, i.e. ``h5info`` and ``h5disp`` are useful for returning information and displaying the contents of HDF5 files respectively. gprMax includes some Python modules (in the ``tools`` package) to help you view output data. These are documented in the :ref:`tools section <plotting>`.
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File structure
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--------------
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@@ -103,7 +103,7 @@ Within each individual ``tl`` group are the following datasets:
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Snapshots
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---------
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Snapshot files use the open source Visualization ToolKit (VTK) (http://www.vtk.org) format which can be viewed in many free readers, such as Paraview (http://www.paraview.org). Paraview is an open-source, multi-platform data analysis and visualization application. It is available for Linux, Mac OS X, and Windows. The ``#snapshot:`` command produces an ImageData (.vti) snapshot file containing electric and magnetic field data and current data for each time instance requested.
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Snapshot files use the open source `Visualization ToolKit (VTK) <http://www.vtk.org>`_ format which can be viewed in many free readers, such as `Paraview <http://www.paraview.org>`_. Paraview is an open-source, multi-platform data analysis and visualization application. It is available for Linux, macOS, and Windows. The ``#snapshot:`` command produces an ImageData (.vti) snapshot file containing electric and magnetic field data and current data for each time instance requested.
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.. tip::
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You can take advantage of Python scripting to easily create a series of snapshots. For example, to create 30 snapshots starting at time 0.1ns until 3ns in intervals of 0.1ns, use the following code snippet in your input file. Replace ``xs, ys, zs, xf, yf, zf, dx, dy, dz`` accordingly.
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@@ -135,7 +135,7 @@ The following are steps to get started with viewing snapshot files in Paraview:
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Geometry output
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===============
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Geometry files use the open source Visualization ToolKit (VTK) (http://www.vtk.org) format which can be viewed in many free readers, such as Paraview (http://www.paraview.org). Paraview is an open-source, multi-platform data analysis and visualization application. It is available for Linux, Mac OS X, and Windows.
|
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Geometry files use the open source `Visualization ToolKit (VTK) <http://www.vtk.org>`_ format which can be viewed in many free readers, such as `Paraview <http://www.paraview.org>`_. Paraview is an open-source, multi-platform data analysis and visualization application. It is available for Linux, Mac OS X, and Windows.
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The ``#geometry_view:`` command produces either ImageData (.vti) for a per-cell geometry view, or PolygonalData (.vtp) for a per-cell-edge geometry view. The per-cell geometry views also show the location of the PML regions and any sources and receivers in the model. The following are steps to get started with viewing geometry files in Paraview:
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@@ -38,11 +38,3 @@ To make it easier to create commands within a block of Python code, there is a b
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#end_python:
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The ``domain`` function will print the ``#domain`` command to the input file and return a variable with the extent of the domain that can be used elsewhere in a Python code block, e.g. in this case with the ``cylinder`` function. The ``cylinder`` function is just a functional version of the ``#cylinder`` command which prints it to the input file.
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input_cmd_funcs.py
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------------------
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.. automodule:: gprMax.input_cmd_funcs
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@@ -9,7 +9,7 @@ This section provides links to screencasts and videos that explain how to instal
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Installation
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------------
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These screencasts are demonstrated on Microsoft Windows 7, but the installation and updating procedure is the same for other versions of Windows, and quite similar for Linux and Mac OS X also. Detailed written installation and updating instructions are provided in the Getting Started section.
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These screencasts are demonstrated on Microsoft Windows 7, but the installation and updating procedure is the same for other versions of Windows, and quite similar for Linux and macOS also. Detailed written installation and updating instructions are provided in the Getting Started section.
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* `How to install gprMax on Microsoft Windows <https://youtu.be/YkPWMmJILcI>`_
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* `How to update gprMax on Microsoft Windows <https://youtu.be/e0ROY792s9o>`_
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@@ -9,7 +9,7 @@ Information
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**Author/Contact**: Craig Warren (Craig.Warren@ed.ac.uk), University of Edinburgh
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**License**: Creative Commons Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0/)
|
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**License**: `Creative Commons Attribution-ShareAlike 4.0 International License <http://creativecommons.org/licenses/by-sa/4.0/>`_
|
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**Attribution/cite**: Warren, C., Giannopoulos, A. (2016). Characterisation of a Ground Penetrating Radar Antenna in Lossless Homogeneous and Lossy Heterogeneous Environments. *Signal Processing* (http://dx.doi.org/10.1016/j.sigpro.2016.04.010)
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@@ -9,16 +9,16 @@ Information
|
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**Author/Contact**: Craig Warren (Craig.Warren@ed.ac.uk), University of Edinburgh
|
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**License**: Creative Commons Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0/)
|
||||
**License**: `Creative Commons Attribution-ShareAlike 4.0 International License <http://creativecommons.org/licenses/by-sa/4.0/>`_
|
||||
|
||||
**Attribution/cite**: Warren, C., Giannopoulos, A. (2011). Creating finite-difference time-domain models of commercial ground-penetrating radar antennas using Taguchi's optimization method. *Geophysics*, 76(2), G37-G47. (http://dx.doi.org/10.1190/1.3548506)
|
||||
|
||||
The module currently features models of antennas similar to commercial GPR antennas:
|
||||
|
||||
* Geophysical Survey Systems, Inc. (GSSI) 1.5 GHz (Model 5100) antenna (http://www.geophysical.com). The dimensions of the GSSI 1.5GHz antenna model are: 170x108x45mm.
|
||||
* MALA Geoscience 1.2 GHz antenna (http://www.malags.com/). The dimensions of the MALA 1.2GHz antenna model are: 184x109x46mm.
|
||||
* `Geophysical Survey Systems, Inc. (GSSI) <http://www.geophysical.com>`_ 1.5 GHz (Model 5100) antenna. The dimensions of the GSSI 1.5GHz antenna model are: 170x108x45mm.
|
||||
* `MALA Geoscience <http://www.malags.com/>`_ 1.2 GHz antenna. The dimensions of the MALA 1.2GHz antenna model are: 184x109x46mm.
|
||||
|
||||
A description of how the models were created can be found at http://dx.doi.org/10.1190/1.3548506.
|
||||
A description of how the models were created can be found at the reference given by the aforementioned attribution/cite.
|
||||
|
||||
Module overview
|
||||
===============
|
||||
|
||||
@@ -11,11 +11,11 @@ Information
|
||||
|
||||
**Contact**: Ali E. Yılmaz (ayilmaz@mail.utexas.edu), The University of Texas at Austin
|
||||
|
||||
**License**: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
|
||||
**License**: `Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License <http://creativecommons.org/licenses/by-nc-nd/3.0/>`_
|
||||
|
||||
**Attribution/cite**: Please follow the instructions at http://web.corral.tacc.utexas.edu/AustinManEMVoxels/AustinMan/citing_the_model/index.html
|
||||
|
||||
AustinMan and AustinWoman (http://bit.ly/AustinMan) are open source electromagnetic voxel models of the human body, which are developed by the Computational Electromagnetics Group (http://www.ece.utexas.edu/research/areas/electromagnetics-acoustics) at The University of Texas at Austin (http://www.utexas.edu). The models are based on data from the National Library of Medicine’s Visible Human Project (https://www.nlm.nih.gov/research/visible/visible_human.html).
|
||||
`AustinMan and AustinWoman <http://bit.ly/AustinMan>`_ are open source electromagnetic voxel models of the human body, which are developed by the `Computational Electromagnetics Group <http://www.ece.utexas.edu/research/areas/electromagnetics-acoustics>`_ at `The University of Texas at Austin <http://www.utexas.edu>`_. The models are based on data from the `National Library of Medicine’s Visible Human Project <https://www.nlm.nih.gov/research/visible/visible_human.html>`_.
|
||||
|
||||
.. figure:: images/user_libs/AustinMan_head.png
|
||||
:width: 600 px
|
||||
@@ -46,8 +46,8 @@ Package overview
|
||||
AustinManWoman_materials_dispersive.txt
|
||||
head_only_hdf5.py
|
||||
|
||||
* ``AustinManWoman_materials.txt`` is a text file containing non-dispersive material properties at 900 MHz (http://niremf.ifac.cnr.it/tissprop/).
|
||||
* ``AustinManWoman_materials_dispersive.txt`` is a text file containing dispersive material properties using a 3-pole Debye model (http://dx.doi.org/10.1109/LMWC.2011.2180371). Note the main body tissues are described using a 3-pole Debye model, nbut ot all materials have a dispersive description.
|
||||
* ``AustinManWoman_materials.txt`` is a text file containing `non-dispersive material properties at 900 MHz <http://niremf.ifac.cnr.it/tissprop/>`_.
|
||||
* ``AustinManWoman_materials_dispersive.txt`` is a text file containing `dispersive material properties using a 3-pole Debye model <http://dx.doi.org/10.1109/LMWC.2011.2180371>`_. Note the main body tissues are described using a 3-pole Debye model, but not all materials have a dispersive description.
|
||||
* ``head_only_hdf5.py`` is a script to assist with creating a model of only the head from a full body AustinMan/Woman model.
|
||||
|
||||
How to use the models
|
||||
@@ -55,7 +55,7 @@ How to use the models
|
||||
|
||||
The AustinMan and AustinWoman models themselves are not included in the user libraries sub-package.
|
||||
|
||||
* Download a HDF5 file (.h5) of AustinMan or AustinWoman at the resolution you wish to use from http://bit.ly/AustinMan
|
||||
* `Download a HDF5 file (.h5) of AustinMan or AustinWoman <http://bit.ly/AustinMan>`_ at the resolution you wish to use
|
||||
|
||||
To insert either AustinMan or AustinWoman models into a simulation use the ``#geometry_objects_read``.
|
||||
|
||||
|
||||
@@ -9,7 +9,7 @@ Information
|
||||
|
||||
**Author/Contact**: Iraklis Giannakis (I.Giannakis@ed.ac.uk), University of Edinburgh
|
||||
|
||||
**License**: Creative Commons Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0/)
|
||||
**License**: `Creative Commons Attribution-ShareAlike 4.0 International License <http://creativecommons.org/licenses/by-sa/4.0/>`_
|
||||
|
||||
**Attribution/cite**: Giannakis, I., Giannopoulos, A., Warren, C. (2016). A Realistic FDTD Numerical Modeling Framework of Ground Penetrating Radar for Landmine Detection. *IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing*, 9(1), 37-51. (http://dx.doi.org/10.1109/JSTARS.2015.2468597)
|
||||
|
||||
@@ -22,7 +22,7 @@ The module currently features models of different anti-personnel (AP) landmines
|
||||
|
||||
The landmine models and the metal can be used with a cubic spatial resolution of either 1mm or 2mm.
|
||||
|
||||
The dielectric properties of the landmines were obtained through an iterative process of matching numerical and laboratory measurements of scattered electromagnetic fields in free space. A full description of how the models were created can be found at http://dx.doi.org/10.1109/JSTARS.2015.2468597.
|
||||
The dielectric properties of the landmines were obtained through an iterative process of matching numerical and laboratory measurements of scattered electromagnetic fields in free space. A full description of how the models were created can be found at the reference given by the aforementioned attribution/cite.
|
||||
|
||||
Package overview
|
||||
================
|
||||
|
||||
@@ -9,7 +9,7 @@ Information
|
||||
|
||||
**Author/Contact**: Craig Warren (Craig.Warren@ed.ac.uk), University of Edinburgh
|
||||
|
||||
**License**: Creative Commons Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0/)
|
||||
**License**: `Creative Commons Attribution-ShareAlike 4.0 International License <http://creativecommons.org/licenses/by-sa/4.0/>`_
|
||||
|
||||
**Attribution/cite**: Warren, C., Giannopoulos, A. (2011). Creating finite-difference time-domain models of commercial ground-penetrating radar antennas using Taguchi's optimization method. *Geophysics*, 76(2), G37-G47. (http://dx.doi.org/10.1190/1.3548506)
|
||||
|
||||
@@ -51,7 +51,7 @@ Package overview
|
||||
|
||||
* ``antenna_bowtie_opt.in`` is a example model of a bowtie antenna where values of loading resistors are optimised.
|
||||
* ``fitness_functions.py`` is a module containing fitness functions. There are some pre-built ones but users should add their own here.
|
||||
* ``OA_9_4_3_2.npy`` and ``OA_18_7_3_2.npy`` are NumPy archives containing pre-built OAs from http://neilsloane.com/oadir/
|
||||
* ``OA_9_4_3_2.npy`` and ``OA_18_7_3_2.npy`` are NumPy archives `containing pre-built OAs <http://neilsloane.com/oadir/>`_
|
||||
* ``plot_results.py`` is a module for plotting the results, such as parameter values and convergence history, from an optimisation process when it has completed.
|
||||
|
||||
Implementation
|
||||
|
||||
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