def plot_erroneous_ne_to_latlon():
import gmtpy
import random
import subprocess
import time
while True:
w, h = 20, 15
gsize = random.uniform(0., 1.) * 4. * 10.**random.uniform(4., 7.)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize / 2., gsize / 2., 11),
num.linspace(-gsize / 2., gsize / 2., 11))
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize / earthradius * r2d * 2.
lon = random.uniform(-180., 180.)
lat = random.uniform(-90., 90.)
print(gsize / 1000.)
lat_grid, lon_grid = orthodrome.ne_to_latlon(lat, lon, north_grid,
east_grid)
lat_grid_alt, lon_grid_alt = \
orthodrome.ne_to_latlon_alternative_method(
lat, lon, north_grid, east_grid)
maxerrlat = num.max(num.abs(lat_grid - lat_grid_alt))
maxerrlon = num.max(num.abs(lon_grid - lon_grid_alt))
eps = 1.0e-8
if maxerrlon > eps or maxerrlat > eps:
print(lat, lon, maxerrlat, maxerrlon)
gmt = gmtpy.GMT(
config={
'PLOT_DEGREE_FORMAT': 'ddd.xxxF',
'PAPER_MEDIA': 'Custom_%ix%i' %
(w * gmtpy.cm, h * gmtpy.cm),
'GRID_PEN_PRIMARY': 'thinnest/0/50/0'
})
south = max(-85., lat - 0.5 * lat_delta)
north = min(85., lat + 0.5 * lat_delta)
lon_delta = lat_delta / math.cos(lat * d2r)
delta = lat_delta / 360. * earthradius * 2. * math.pi
scale_km = gmtpy.nice_value(delta / 10.) / 1000.
west = lon - 0.5 * lon_delta
east = lon + 0.5 * lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler['R'] = '-Rg'
layout = gmt.default_layout()
mw = 2.5 * gmtpy.cm
layout.set_fixed_margins(mw, mw, mw / gmtpy.golden_ratio,
mw / gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget['J'] = (
'-JE%g/%g/%g' % (lon, lat, min(lat_delta/2., 180.)))\
+ '/%(width)gp'
aspect = gmtpy.aspect_for_projection(*(widget.J() + scaler.R()))
widget.set_aspect(aspect)
gmt.psbasemap(B='5g5',
L=('x%gp/%gp/%g/%g/%gk' %
(widget.width() / 2., widget.height() / 7., lon,
lat, scale_km)),
*(widget.JXY() + scaler.R()))
gmt.psxy(in_columns=(lon_grid, lat_grid),
S='x10p',
W='1p/200/0/0',
*(widget.JXY() + scaler.R()))
gmt.psxy(in_columns=(lon_grid_alt, lat_grid_alt),
S='c10p',
W='1p/0/0/200',
*(widget.JXY() + scaler.R()))
gmt.save('orthodrome.pdf')
subprocess.call(['xpdf', '-remote', 'ortho', '-reload'])
time.sleep(2)
else:
print('ok', gsize, lat, lon)
def plot_erroneous_ne_to_latlon():
import sys
import gmtpy
import random
import subprocess
import time
while True:
w,h = 20,15
km = 1000.
gsize = random.uniform(0.,1.)*4.*10.**random.uniform(4.,7.)
north_grid, east_grid = num.meshgrid(num.linspace(-gsize/2.,gsize/2.,11) ,
num.linspace(-gsize/2.,gsize/2.,11) )
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize/config.earthradius*r2d*2.
lon = random.uniform(-180.,180.)
lat = random.uniform(-90.,90.)
print gsize/1000.
lat_grid, lon_grid = ne_to_latlon(lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = ne_to_latlon_alternative_method(lat, lon, north_grid, east_grid)
maxerrlat = num.max(num.abs(lat_grid-lat_grid_alt))
maxerrlon = num.max(num.abs(lon_grid-lon_grid_alt))
eps = 1.0e-8
if maxerrlon > eps or maxerrlat > eps:
print lat, lon, maxerrlat, maxerrlon
gmt = gmtpy.GMT( config={ 'PLOT_DEGREE_FORMAT':'ddd.xxxF',
'PAPER_MEDIA':'Custom_%ix%i' % (w*gmtpy.cm,h*gmtpy.cm),
'GRID_PEN_PRIMARY': 'thinnest/0/50/0' } )
south = max(-85., lat - 0.5*lat_delta)
north = min(85., lat + 0.5*lat_delta)
lon_delta = lat_delta/math.cos(lat*d2r)
delta = lat_delta/360.*config.earthradius*2.*math.pi
scale_km = gmtpy.nice_value(delta/10.)/1000.
west = lon - 0.5*lon_delta
east = lon + 0.5*lon_delta
x,y = (west, east), (south,north)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
scaler = gmtpy.ScaleGuru( data_tuples=[(x,y)], axes=(xax,yax))
scaler['R'] = '-Rg'
layout = gmt.default_layout()
mw = 2.5*gmtpy.cm
layout.set_fixed_margins(mw,mw,mw/gmtpy.golden_ratio,mw/gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget['J'] = ('-JE%g/%g/%g' % (lon, lat, min(lat_delta/2.,180.))) + '/%(width)gp'
aspect = gmtpy.aspect_for_projection( *(widget.J() + scaler.R()) )
widget.set_aspect(aspect)
if lat > 0:
axes_layout = 'WSen'
else:
axes_layout = 'WseN'
gmt.psbasemap( #B=('%(xinc)gg%(xinc)g:%(xlabel)s:/%(yinc)gg%(yinc)g:%(ylabel)s:' % scaler.get_params())+axes_layout,
B='5g5',
L=('x%gp/%gp/%g/%g/%gk' % (widget.width()/2., widget.height()/7.,lon,lat,scale_km) ),
*(widget.JXY()+scaler.R()) )
gmt.psxy( in_columns=(lon_grid,lat_grid), S='x10p', W='1p/200/0/0', *(widget.JXY()+scaler.R()) )
gmt.psxy( in_columns=(lon_grid_alt,lat_grid_alt), S='c10p', W='1p/0/0/200', *(widget.JXY()+scaler.R()) )
gmt.save('orthodrome.pdf')
subprocess.call( [ 'xpdf', '-remote', 'ortho', '-reload' ] )
time.sleep(2)
else:
print 'ok', gsize, lat, lon
gmt = gmtpy.GMT(
config={
"PLOT_DEGREE_FORMAT": "ddd.xxxF",
"PAPER_MEDIA": "Custom_%ix%i" % (w * gmtpy.cm, h * gmtpy.cm),
"GRID_PEN_PRIMARY": "thinnest/0/50/0",
}
)
south = max(-85.0, lat - 0.5 * lat_delta)
north = min(85.0, lat + 0.5 * lat_delta)
lon_delta = lat_delta / math.cos(lat * d2r)
delta = lat_delta / 360.0 * config.earthradius * 2.0 * math.pi
scale_km = gmtpy.nice_value(delta / 10.0) / 1000.0
west = lon - 0.5 * lon_delta
east = lon + 0.5 * lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode="min-max", approx_ticks=4.0)
yax = gmtpy.Ax(mode="min-max", approx_ticks=4.0)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler["R"] = "-Rg"
layout = gmt.default_layout()
mw = 2.5 * gmtpy.cm
layout.set_fixed_margins(mw, mw, mw / gmtpy.golden_ratio, mw / gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget["J"] = ("-JE%g/%g/%g" % (lon, lat, min(lat_delta / 2.0, 180.0))) + "/%(width)gp"
def location_map( filename, lat, lon, lat_delta, conf_overrides, source=None,
source_model_infos=None, receivers=None,
with_palette=False, shakemap_data=None, shakemap_range=None, shakemap_cpt=None, show_topo=True):
conf = dict(**config.location_map_config)
conf.update( conf_overrides )
w = conf.pop('width')
h = conf.pop('height')
margins = conf.pop('margins')
d2r = math.pi/180.0
if source:
slat, slon = lat, lon
lat, lon = orthodrome.ne_to_latlon(lat,lon, source['north-shift'], source['east-shift'])
south = lat - 0.5*lat_delta
north = lat + 0.5*lat_delta
if lat_delta > 20. or south < -80. or north > 80.:
resolution = 5
coastline_resolution = 'i'
rivers=[]
else:
resolution = 1
coastline_resolution = 'f'
rivers = ['-Ir',]
lon_delta = lat_delta/math.cos(lat*d2r)
delta = lat_delta/360.*config.earthradius*2.*math.pi
scale_km = gmtpy.nice_value(delta/10.)/1000.
west = lon - 0.5*lon_delta
east = lon + 0.5*lon_delta
x,y,z = (west, east), (south,north), (-6000.,4500.)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
zax = gmtpy.Ax(mode='min-max', inc=1000., label='Height', scaled_unit='km', scaled_unit_factor=0.001)
scaler = gmtpy.ScaleGuru( data_tuples=[(x,y,z)], axes=(xax,yax,zax))
curcfg = {'TICK_PEN': '1.25p',
'TICK_LENGTH': '0.2c',
'ANNOT_FONT_PRIMARY': '1',
'ANNOT_FONT_SIZE_PRIMARY': '14p',
'LABEL_FONT': '1',
'LABEL_FONT_SIZE': '14p',
'CHAR_ENCODING': 'ISOLatin1+',
'D_FORMAT': '%.1f',
'PLOT_DEGREE_FORMAT':'DF',
'PAPER_MEDIA':'Custom_%ix%i' % (w,h),
'GRID_PEN_PRIMARY': 'thinnest/0/0/0' }
#degree_format = 'dddF'
#if scaler.get_params()['xinc'] < 1. or scaler.get_params()['yinc'] < 1.:
# degree_format = 'ddd:mmF'
gmt = gmtpy.GMT( config=curcfg )
if with_palette:
layout = gmt.default_layout(with_palette=True)
layout.set_fixed_margins(*margins)
widget = layout.get_widget().get_widget(0,0)
palette_layout = gmtpy.FrameLayout()
palette_layout.set_policy( *layout.get_widget().get_widget(2,0).get_policy() )
layout.get_widget().set_widget(2,0,palette_layout)
inset = h-margins[2]-margins[3]
palette_layout.set_fixed_margins(0.,0.,inset/6., inset/6.)
palette_widget = palette_layout.get_widget()
else:
layout = gmt.default_layout()
layout.set_fixed_margins(*margins)
widget = layout.get_widget()
widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
aspect = gmtpy.aspect_for_projection( *(widget.J() + scaler.R()) )
widget.set_aspect(aspect)
if show_topo:
cptfile = draw_topo(gmt, widget.JXY(), (west,east,south,north), resolution, coastline_resolution, rivers, conf)
zscaler = scaler
if shakemap_data is not None:
cptfile, zscaler = draw_shakemap( gmt, widget, scaler, (xax,yax,zax),
shakemap_range, shakemap_cpt, *shakemap_data)
draw_coastlines(gmt, widget.JXY(), (west,east,south,north), coastline_resolution, rivers)
if source_model_infos and source:
try:
draw_rupture(gmt, widget, source_model_infos, axes=(xax,yax,zax), view='from-top', source_loc=(slat,slon), outer_scaler=scaler, with_centroids=False)
except NoOutlineFound:
gmt.psxy( in_rows=[[lon,lat]], S='c20p', W='2p,0/0/0', *(widget.JXY()+scaler.R()))
else:
if source and 'strike' in source.keys() and 'dip' in source.keys() and 'slip-rake' in source.keys():
gmt.psmeca( in_rows=[[lon, lat, 1., source['strike'], source['dip'], source['slip-rake'], 6., 0.,0., '' ]],
S='a0.3', *(widget.JXY()+scaler.R()) )
else:
gmt.psxy( in_rows=[[lon,lat]], S='c20p', W='2p,0/0/0', *(widget.JXY()+scaler.R()))
if receivers:
rlats, rlons, rnames = receivers
gmt.psxy( in_columns=(rlons, rlats), S='t12p', W='1p,black', G='red', *(widget.JXY()+scaler.R()))
nr = len(rnames)
size = [7]*nr
angle = [0]*nr
fontno = [1]*nr
justify = ['MC']*nr
gmt.pstext( in_columns=(rlons,rlats,size,angle,fontno,justify,rnames), D=(0.,-0.1), *(widget.JXY()+scaler.R()))
if lat > 0:
axes_layout = 'WSen'
else:
axes_layout = 'WseN'
gmt.psbasemap( B=('%(xinc)gg%(xinc)g:%(xlabel)s:/%(yinc)gg%(yinc)g:%(ylabel)s:' % scaler.get_params())+axes_layout,
L=('x%gp/%gp/%g/%g/%gk' % (widget.width()/2., widget.height()/7.,lon,lat,scale_km) ),
*(widget.JXY()+scaler.R()) )
if with_palette and (show_topo or shakemap_data is not None):
gmtpy.nice_palette(gmt, palette_widget, zscaler, cptfile, innerticks=False, zlabeloffset=1.5*gmtpy.cm)
gmt.save(filename)
gmt = gmtpy.GMT(
config={
'PLOT_DEGREE_FORMAT': 'ddd.xxxF',
'PAPER_MEDIA': 'Custom_%ix%i' %
(w * gmtpy.cm, h * gmtpy.cm),
'GRID_PEN_PRIMARY': 'thinnest/0/50/0'
})
south = max(-85., lat - 0.5 * lat_delta)
north = min(85., lat + 0.5 * lat_delta)
lon_delta = lat_delta / math.cos(lat * d2r)
delta = lat_delta / 360. * config.earthradius * 2. * math.pi
scale_km = gmtpy.nice_value(delta / 10.) / 1000.
west = lon - 0.5 * lon_delta
east = lon + 0.5 * lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
yax = gmtpy.Ax(mode='min-max', approx_ticks=4.)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler['R'] = '-Rg'
layout = gmt.default_layout()
mw = 2.5 * gmtpy.cm
layout.set_fixed_margins(mw, mw, mw / gmtpy.golden_ratio,
mw / gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
def plot_erroneous_ne_to_latlon():
import sys
import gmtpy
import random
import subprocess
import time
while True:
w, h = 20, 15
km = 1000.0
gsize = random.uniform(0.0, 1.0) * 4.0 * 10.0 ** random.uniform(4.0, 7.0)
north_grid, east_grid = num.meshgrid(
num.linspace(-gsize / 2.0, gsize / 2.0, 11), num.linspace(-gsize / 2.0, gsize / 2.0, 11)
)
north_grid = north_grid.flatten()
east_grid = east_grid.flatten()
lat_delta = gsize / config.earthradius * r2d * 2.0
lon = random.uniform(-180.0, 180.0)
lat = random.uniform(-90.0, 90.0)
print gsize / 1000.0
lat_grid, lon_grid = ne_to_latlon(lat, lon, north_grid, east_grid)
lat_grid_alt, lon_grid_alt = ne_to_latlon_alternative_method(lat, lon, north_grid, east_grid)
maxerrlat = num.max(num.abs(lat_grid - lat_grid_alt))
maxerrlon = num.max(num.abs(lon_grid - lon_grid_alt))
eps = 1.0e-8
if maxerrlon > eps or maxerrlat > eps:
print lat, lon, maxerrlat, maxerrlon
gmt = gmtpy.GMT(
config={
"PLOT_DEGREE_FORMAT": "ddd.xxxF",
"PAPER_MEDIA": "Custom_%ix%i" % (w * gmtpy.cm, h * gmtpy.cm),
"GRID_PEN_PRIMARY": "thinnest/0/50/0",
}
)
south = max(-85.0, lat - 0.5 * lat_delta)
north = min(85.0, lat + 0.5 * lat_delta)
lon_delta = lat_delta / math.cos(lat * d2r)
delta = lat_delta / 360.0 * config.earthradius * 2.0 * math.pi
scale_km = gmtpy.nice_value(delta / 10.0) / 1000.0
west = lon - 0.5 * lon_delta
east = lon + 0.5 * lon_delta
x, y = (west, east), (south, north)
xax = gmtpy.Ax(mode="min-max", approx_ticks=4.0)
yax = gmtpy.Ax(mode="min-max", approx_ticks=4.0)
scaler = gmtpy.ScaleGuru(data_tuples=[(x, y)], axes=(xax, yax))
scaler["R"] = "-Rg"
layout = gmt.default_layout()
mw = 2.5 * gmtpy.cm
layout.set_fixed_margins(mw, mw, mw / gmtpy.golden_ratio, mw / gmtpy.golden_ratio)
widget = layout.get_widget()
# widget['J'] = ('-JT%g/%g' % (lon, lat)) + '/%(width)gp'
widget["J"] = ("-JE%g/%g/%g" % (lon, lat, min(lat_delta / 2.0, 180.0))) + "/%(width)gp"
aspect = gmtpy.aspect_for_projection(*(widget.J() + scaler.R()))
widget.set_aspect(aspect)
if lat > 0:
axes_layout = "WSen"
else:
axes_layout = "WseN"
gmt.psbasemap( # B=('%(xinc)gg%(xinc)g:%(xlabel)s:/%(yinc)gg%(yinc)g:%(ylabel)s:' % scaler.get_params())+axes_layout,
B="5g5",
L=("x%gp/%gp/%g/%g/%gk" % (widget.width() / 2.0, widget.height() / 7.0, lon, lat, scale_km)),
*(widget.JXY() + scaler.R())
)
gmt.psxy(in_columns=(lon_grid, lat_grid), S="x10p", W="1p/200/0/0", *(widget.JXY() + scaler.R()))
gmt.psxy(in_columns=(lon_grid_alt, lat_grid_alt), S="c10p", W="1p/0/0/200", *(widget.JXY() + scaler.R()))
gmt.save("orthodrome.pdf")
subprocess.call(["xpdf", "-remote", "ortho", "-reload"])
time.sleep(2)
else:
print "ok", gsize, lat, lon
