Test Cases Plotting

horizontal_slice.py

This command discretizes a region, given a cvm, depth, and datatype, plots a map of the results. A key to using this command are the valid types of "data" -d put on the command line without quotes: vs,vp,rho,poisson (vp/vs)

Example of poisson ratio calculation

-bash-4.2$ ./plot_horizontal_slice.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.05 -e 0.0 -d poisson -a s -c cs173 -o cs173_poisson_0m_map.png
Using parameters:

datafile  =  None
lat1  =  30.5
data_type  =  poisson
lat2  =  42.5
color  =  s
outfile  =  cs173_poisson_0m_map.png
spacing  =  0.05
cvm_selected  =  cs173
depth  =  0.0
lon1  =  -126.0
lon2  =  -112.5

Retrieving data. Please wait...

Example of plot_horizontal_slice.py

The following are a low resolution, and a higher resolution version of the same plot. Vs for most of California based on the cs173 cvm.

-bash-4.2$ ./plot_horizontal_slice.py -b 30.5,-126.0 -u 42.5,-112.5 -s 1.0 -e 0 -d vs -a s -c cs173 -o cs173_map.png
Using parameters:

datafile  =  None
lat1  =  30.5
data_type  =  vs
lat2  =  42.5
color  =  s
outfile  =  cs173_map.png
spacing  =  1.0
cvm_selected  =  cs173
depth  =  0
lon1  =  -126.0
lon2  =  -112.5

Retrieving data. Please wait...
/home/scec-00/maechlin/anaconda2/lib/python2.7/site-packages/mpl_toolkits/basemap/__init__.py:3296: MatplotlibDeprecationWarning: The ishold function was deprecated in version 2.0.
  b = ax.ishold()
/home/scec-00/maechlin/anaconda2/lib/python2.7/site-packages/mpl_toolkits/basemap/__init__.py:3305: MatplotlibDeprecationWarning: axes.hold is deprecated.
    See the API Changes document (http://matplotlib.org/api/api_changes.html)
    for more details.
  ax.hold(b)



-bash-4.2$ ./plot_horizontal_slice.py -b 30.5,-126.0 -u 42.5,-112.5 -s 0.05 -e 100.0 -d vs -a s -c cs173 -o cs173_vs_100m_map.png
Using parameters:

datafile  =  None
lat1  =  30.5
data_type  =  vs
lat2  =  42.5
color  =  s
outfile  =  cs173_vs_100m_map.png
spacing  =  0.05
cvm_selected  =  cs173
depth  =  100.0
lon1  =  -126.0
lon2  =  -112.5

Retrieving data. Please wait..

Show effect of smooth versus discrete color scale in plot_cross_section.py

Call plot_cross_section with color parameter set to smooth and discrete:

Smooth Call

-bash-4.2$ ./plot_cross_section.py -b 34.0,-118.0 -u 35.0,-117.0 -h 100 -v 10 -d vs -c cvms -a s -s 0 -e 500
Using parameters:

lat1 = 34.0
data_type = vs
lat2 = 35.0
cvm_selected = cvms
ending_depth = 500
horizontal_spacing = 100
color = s
lon1 = -118.0
vertical_spacing = 10
lon2 = -117.0
starting_depth = 0

Retrieving data. Please wait...

Resulting Image: Cross Section Smooth Color

Discrete Colorscale Plotting Call

-bash-4.2$ ./plot_cross_section.py -b 34.0,-118.0 -u 35.0,-117.0 -h 100 -v 10 -d vs -c cvms -a d -s 0 -e 500
Using parameters:

lat1 = 34.0
data_type = vs
lat2 = 35.0
cvm_selected = cvms
ending_depth = 500
horizontal_spacing = 100
color = d
lon1 = -118.0
vertical_spacing = 10
lon2 = -117.0
starting_depth = 0

Retrieving data. Please wait...

Resulting Image: Cross Section Discrete Color

Show effect of smooth versus discrete color scale in plot_horizontal.py

Show effect of smooth versus discrete color scale in plot_vs30_map.py