UCVM Visualization

Overview

The UCVM Visualization software is a set of Python scripts for producing 2D plots from one or more community velocity models or a 3D mesh. The following plots are supported:

• Map views for a lon-lat box
• Cross-section views between to lon-lat endpoints
• Difference plots for both maps and cross-sections
• Histogram plots of differences

The following mesh types are supported:

• AWP 3, 5, and 8 value
• SORD
• RWG (CyberShake format)

Requirements

• UCVM with one or more velocity models installed
• Python 2.6.2+, with the modules: numpy, matplotlib, basemap

Configuration

Edit the paths in ./src/Params.py so that the scripts can find your UCVM installation:

# UCVM Config
UCVM_DIR = '/home/scec-00/patrices/opt/aftershock/ucvm-12.2.0/bin'
UCVM_CONF = '/home/scec-00/patrices/opt/aftershock/ucvm-12.2.0/conf/ucvm.conf'
UCVM_SCRIPT = 'run_ucvm.sh'
#UCVM_MAP = 'yong'
UCVM_MAP = 'ucvm'

# GRD Config
GRD_DIR = '/home/scec-00/patrices/opt/aftershock/ucvm-12.2.0/bin'
GRD_NED_DIR = '/home/scec-00/patrices/opt/ned'
GRD_BATH_DIR = '/home/scec-00/patrices/opt/bath'
GRD_HR_VS30_DIR = '/home/scec-00/patrices/opt/vs30/wills_gridfloat'
GRD_LR_VS30_DIR = '/home/scec-00/patrices/opt/vs30/wald_gridfloat'
GRD_SCRIPT = 'run_grd.sh'

The lines to change at a minimum are UCVM_DIR and UCVM_CONF. UCVM_SCRIPT should reference the standard run_ucvm.sh script included in UCVM. UCVM_MAP allows you to specify an alternate Vs30/elevation map.

The GRD configuration is necessary only if you want to plot Vs30 or elevation data from ArcGIS GridFloat formatted grid files. The meaning of each config line is:

• GRD_NED_DIR specifies the directory containing that National Elevation Dataset grid files (GridFloat format).
• GRD_MATH_DIR specifies the directory containing bathymetry information (GridFloat format).
• GRD_HR_VS30_DIR specifies the directory containing the high-rez (preferred) Vs30 data
• GRD_LR_VS30_DIR contains the low-rez data

Using the Software

The UCVM Visualization package splits the plotting process into three steps:

1. Extract data slice from a CVM or mesh
2. (Optional) Difference one or more previously extracted datasets to produce a new dataset
3. Visualize the slice

Data Extraction

The data extraction step pulls a slice of information from a CVM or mesh and saves it in a text file. This text file is space-delimited with a commented metadata section as a header. The format is Matlab friendly.

• CrossSectionCVM.py: Extracts cross-section from one or more CVMs
• CrossSectionMesh.py: Extracts cross-section from a 3D mesh
• MapCVM.py: Extracts map view at specified depth from one or more CVMs
• MapDEM.py: Extracts map view of DEM from NED data
• MapMesh.py: Extracts map view at specified depth from a mesh
• MapVs30.py: Extracts map view of Vs30 from a UCVM 2D map
• ProfileCVM.py: Extracts velocity profile at specific lon-lat point
• Vs30MapCVM.py: Computes Vs30 map from one or more CVMs (note that this is not the same as MapVs30.py)
• ZMapCVM.py: Compute Z map for desired Vs threshold

Differencing

• DiffData.py: Perform operation between two datasets with the same datatype and format (typically difference).

Plotting

The following scripts accept a previously extracted data set and plot it with Python matplotlib. It is important to use the correct plotting script for the dataset that you want to visualize. For example, a Map view extracted from a CVM with MapCVM.py must be plotted with PlotMapCVM.py. The naming is consistent so that any dataset produced with <extractor>.py can be plotted with Plot<extractor>.py.

• PlotCrossSectionCVM.py
• PlotCrossSectionDiff.py: Plot a cross-section difference data set generated by DiffData.py.
• PlotCrossSectionMesh.py
• PlotHistDiff.py: Plot histogram of a difference data set, filtered to include only data points that fall within a bounding box (lat_0,lon_0,xsize_m,ysize_m,rot_angle).
• PlotMapCVM.py
• PlotMapDEM.py
• PlotMapDiff.py: Plot a map difference data set generated by DiffData.py.
• PlotMapMesh.py
• PlotMapVs30.py
• PlotProfileCVM.py
• PlotVs30MapCVM.py
• PlotZMapCVM.py

Various customizations are allowed:

• Choice of value from the dataset to plot (generally vp, vs, or rho)
• Color scale type (ie: Spectral), minimum/maximum values, and discrete intervals versus continuous
• Map view scripts support optional polygon overlays
• Cross-section scripts support optional region context bounding box

Helper Utilities

• BatchPlot.py: Creates a set of standard cross-sections and map views for a SoCal model

Download

• SVN: https://source.usc.edu/svn/viz-cvm