initial upload

cookbook/dem_brasil/dem_brasil.bat

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+
+
+:: First, insert the density information into
+:: the DEM file using the Python script.
+python dem_density.py dem.xyz > dem-dens.txt
+
+:: Next, use the modified DEM with tessmodgen
+:: to create a tesseroid model
+tessmodgen -s0.166667/0.166667 -z0 -v < dem-dens.txt ^
+> dem-tess.txt
+
+:: Calculate the GGT on a regular grid at 250km
+:: use the -l option to log the processes to files
+:: (usefull to diagnose when things go wrong)
+:: The output is dumped to dem-ggt.txt
+tessgrd -r-60/-45/-30/-15 -b50/50 -z250e03 | ^
+tessgxx dem-tess.txt -lgxx.log | ^
+tessgxy dem-tess.txt -lgxy.log | ^
+tessgxz dem-tess.txt -lgxz.log | ^
+tessgyy dem-tess.txt -lgyy.log | ^
+tessgyz dem-tess.txt -lgyz.log | ^
+tessgzz dem-tess.txt -lgzz.log -v > dem-ggt.txt

cookbook/dem_brasil/dem_brasil.sh

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+#!/bin/bash
+
+# First, insert the density information into
+# the DEM file using the Python script.
+python dem_density.py dem.xyz > dem-dens.txt
+
+# Next, use the modified DEM with tessmodgen
+# to create a tesseroid model
+tessmodgen -s0.166667/0.166667 -z0 -v < dem-dens.txt \
+> dem-tess.txt
+
+# Calculate the GGT on a regular grid at 250km
+# use the -l option to log the processes to files
+# (usefull to diagnose when things go wrong)
+# The output is dumped to dem-ggt.txt
+tessgrd -r-60/-45/-30/-15 -b50/50 -z250e03 | \
+tessgxx dem-tess.txt -lgxx.log | \
+tessgxy dem-tess.txt -lgxy.log | \
+tessgxz dem-tess.txt -lgxz.log | \
+tessgyy dem-tess.txt -lgyy.log | \
+tessgyz dem-tess.txt -lgyz.log | \
+tessgzz dem-tess.txt -lgzz.log -v > dem-ggt.txt

cookbook/dem_brasil/dem_density.py

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+"""
+Assign density values for the DEM points.
+"""
+import sys
+import numpy
+
+lons, lats, heights = numpy.loadtxt(sys.argv[1], unpack=True)
+
+for i in xrange(len(heights)):
+    if heights[i] >=0:
+        print "%lf %lf %lf %lf" % (lons[i], lats[i], heights[i], 2670.0)
+    else:
+        print "%lf %lf %lf %lf" % (lons[i], lats[i], heights[i], 1670.0)

cookbook/dem_brasil/plot.py

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+# Make some nice plots of the DEM, the densities used and the calculated GGT
+import numpy
+from matplotlib import pyplot as plt
+from mpl_toolkits.basemap import Basemap
+
+# Plot the DEM and density maps
+################################################################################
+lons, lats, heights, dens = numpy.loadtxt('dem-dens.txt', unpack=True)
+nlons = 151  # Number of points in the longitude direction
+nlats = len(lats)/nlons
+
+# Convert the lists to 2D grids
+glons = numpy.reshape(lons, (nlats, nlons))
+glats = numpy.reshape(lats, (nlats, nlons))
+gheights = numpy.reshape(heights, (nlats, nlons))
+gdens = numpy.reshape(dens, (nlats, nlons))
+
+# Set up a Mercator projection
+bm = Basemap(projection='merc',
+             llcrnrlon=lons[0], llcrnrlat=lats[-1],
+             urcrnrlon=lons[-1], urcrnrlat=lats[0],
+             lon_0=lons[nlons//2], lat_0=lats[len(lats)//2],
+             resolution='l',
+             area_thresh=10000)
+glons, glats = bm(glons, glats)
+
+# Plot the DEM first
+print "Plotting DEM"
+plt.figure()
+bm.drawmeridians(numpy.arange(lons[0]+5., lons[-1], 5.),
+                 labels=[0,0,0,1], fontsize=12, linewidth=0.5)
+bm.drawparallels(numpy.arange(lats[-1]+5., lats[0], 5.),
+                 labels=[1,0,0,0], fontsize=12, linewidth=0.5)
+bm.drawcoastlines(linewidth=1)
+bm.drawmapboundary()
+bm.drawcountries(linewidth=0.8)
+# Do the pseudocolor plot
+cf = bm.pcolor(glons, glats, gheights, cmap=plt.cm.gist_earth, \
+               vmin=-1000, vmax=1000)
+cb = plt.colorbar()
+cb.set_label("Height [m]")
+# Plot the calculation area used later
+w = -60
+e = -45
+s = -30
+n = -15
+areax, areay = bm([w, w, e, e, w], \
+                  [n, s, s, n, n])
+bm.plot(areax, areay, '-r', label="Computation grid", linewidth=1.8)
+plt.legend(shadow=True, loc='lower right', prop={'size':10})
+# Save a png figure
+plt.savefig('dem.png')
+
+# Now plot the densities
+print "Plotting density model"
+plt.figure()
+bm.drawmeridians(numpy.arange(lons[0]+5., lons[-1], 5.),
+                 labels=[0,0,0,1], fontsize=12, linewidth=0.5)
+bm.drawparallels(numpy.arange(lats[-1]+5., lats[0], 5.),
+                 labels=[1,0,0,0], fontsize=12, linewidth=0.5)
+bm.drawcoastlines(linewidth=1)
+bm.drawmapboundary()
+bm.drawcountries(linewidth=0.8)
+# Do the pseudocolor plot
+cf = bm.pcolor(glons, glats, gdens, cmap=plt.cm.jet)
+cb = plt.colorbar()
+cb.set_label(r"Density [$g.cm^{-3}$]")
+# Save a png figure
+plt.savefig('dem-dens.png')
+
+# Plot the GGT
+################################################################################
+print "Plotting GGT"
+data = numpy.loadtxt('dem-ggt.txt')
+lons, lats, heights, gxx, gxy, gxz, gyy, gyz, gzz = data.T
+nlons = 50  # Number of points in the longitude direction
+nlats = len(lats)/nlons
+
+# Convert the lists to 2D grids
+glons = numpy.reshape(lons, (nlats, nlons))
+glats = numpy.reshape(lats, (nlats, nlons))
+
+# Set up a Mercator projection
+bm = Basemap(projection='merc', \
+             llcrnrlon=lons[0], llcrnrlat=lats[0], \
+             urcrnrlon=lons[-1], urcrnrlat=lats[-1], \
+             lon_0=lons[nlons//2], lat_0=lats[len(lats)//2],
+             resolution='l', area_thresh=10000)
+glons, glats = bm(glons, glats)
+
+# Plot each component
+fig = plt.figure(figsize=(14,9))
+plt.subplots_adjust(wspace=0.35)
+titles = [r"$g_{xx}$", r"$g_{xy}$", r"$g_{xz}$", r"$g_{yy}$", r"$g_{yz}$",
+          r"$g_{zz}$"]
+fields = [gxx, gxy, gxz, gyy, gyz, gzz]
+for i, args in enumerate(zip(fields, titles)):
+    field, title = args
+    ax = plt.subplot(2, 3, i + 1, aspect='equal')
+    plt.title(title, fontsize=18)
+    # Make it a 2D grid
+    gfield = numpy.reshape(field, (nlats, nlons))
+    # Plot the coastlines and etc
+    mer = bm.drawmeridians(numpy.arange(lons[0]+3, lons[-1]-3, 3),
+                           labels=[0,0,0,1], fontsize=9, linewidth=0.5)
+    bm.drawparallels(numpy.arange(lats[0]+3, lats[-1]-3, 3),
+                     labels=[1,0,0,0], fontsize=9, linewidth=0.5)
+    bm.drawcoastlines(linewidth=1)
+    bm.drawmapboundary()
+    bm.drawcountries(linewidth=1)
+    bm.drawstates(linewidth=0.2)
+    # Make a pseudocolor plot
+    cf = bm.pcolor(glons, glats, gfield, cmap=plt.cm.jet)
+    cb = plt.colorbar(orientation='vertical', format='%.2f', shrink=0.8)
+    cb.set_label(r"$E\"otv\"os$")
+# Save a png figure
+plt.savefig('dem-ggt.png')