def _draw_basefeatures(self):
gmt = self._gmt
cres = self._coastline_resolution
rivers = self._rivers
minarea = self._minarea
color_wet = self.color_wet
color_dry = self.color_dry
if self.show_rivers and rivers:
rivers = ["-Ir/0.25p,%s" % gmtpy.color(self.color_wet)]
else:
rivers = []
fill = {}
if not self._have_topo_land:
fill["G"] = color_dry
if not self._have_topo_ocean:
fill["S"] = color_wet
gmt.pscoast(
D=cres,
W="thinnest,%s" % gmtpy.color(darken(gmtpy.color_tup(color_dry))),
A=minarea,
*(rivers + self._jxyr),
**fill
)
def _draw_basefeatures(self):
gmt = self._gmt
cres = self._coastline_resolution
rivers = self._rivers
minarea = self._minarea
color_wet = self.color_wet
color_dry = self.color_dry
if self.show_rivers and rivers:
rivers = ['-Ir/0.25p,%s' % gmtpy.color(self.color_wet)]
else:
rivers = []
fill = {}
if not self._have_topo_land:
fill['G'] = color_dry
if not self._have_topo_ocean:
fill['S'] = color_wet
gmt.pscoast(D=cres,
W='thinnest,%s' %
gmtpy.color(darken(gmtpy.color_tup(color_dry))),
A=minarea,
*(rivers + self._jxyr),
**fill)
def test_simple(self):
x = num.linspace(0., 2 * math.pi)
y = num.sin(x)
y2 = num.cos(x)
for version in gmtpy.all_installed_gmt_versions():
for ymode in ['off', 'symmetric', 'min-max', 'min-0', '0-max']:
plot = gmtpy.Simple(gmtversion=version, ymode=ymode)
plot.plot((x, y), '-W1p,%s' % gmtpy.color('skyblue2'))
plot.plot(
(x, y2),
'-W1p,%s' % gmtpy.color(gmtpy.color_tup('scarletred2')))
plot.text((3., 0.5, 'hello'), size=20.)
fname = 'gmtpy_test_simple_%s.png' % ymode
fpath = self.fpath(fname)
plot.save(fpath)
self.compare_with_ref(fname, 0.01, show=False)
# Load events from catalog file (generated using catalog.GlobalCMT()
# download from www.globalcmt.org)
# If no moment tensor is provided in the catalogue, the event is plotted
# as a red circle. Symbol size relative to magnitude.
events = model.load_events('deadsea_events_1976-2017.txt')
beachball_symbol = 'd'
factor_symbl_size = 5.0
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c' + str(mag * factor_symbl_size) + 'p'
m.gmt.psxy(in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
def main(args=None):
if args is None:
args = sys.argv[1:]
parser = OptionParser(
usage=usage,
description=description)
parser.add_option(
'--width',
dest='width',
type='float',
default=20.0,
metavar='FLOAT',
help='set width of output image [cm] (%default)')
parser.add_option(
'--height',
dest='height',
type='float',
default=15.0,
metavar='FLOAT',
help='set height of output image [cm] (%default)')
parser.add_option(
'--topo-resolution-min',
dest='topo_resolution_min',
type='float',
default=40.0,
metavar='FLOAT',
help='minimum resolution of topography [dpi] (%default)')
parser.add_option(
'--topo-resolution-max',
dest='topo_resolution_max',
type='float',
default=200.0,
metavar='FLOAT',
help='maximum resolution of topography [dpi] (%default)')
parser.add_option(
'--no-grid',
dest='show_grid',
default=True,
action='store_false',
help='don\'t show grid lines')
parser.add_option(
'--no-topo',
dest='show_topo',
default=True,
action='store_false',
help='don\'t show topography')
parser.add_option(
'--no-cities',
dest='show_cities',
default=True,
action='store_false',
help='don\'t show cities')
parser.add_option(
'--no-illuminate',
dest='illuminate',
default=True,
action='store_false',
help='deactivate artificial illumination of topography')
parser.add_option(
'--illuminate-factor-land',
dest='illuminate_factor_land',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of land (0.5)')
parser.add_option(
'--illuminate-factor-ocean',
dest='illuminate_factor_ocean',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of ocean (0.25)')
parser.add_option(
'--theme',
choices=['topo', 'soft'],
default='topo',
help='select color theme, available: topo, soft (topo)"')
parser.add_option(
'--download-etopo1',
dest='download_etopo1',
action='store_true',
help='download full ETOPO1 topography dataset')
parser.add_option(
'--download-srtmgl3',
dest='download_srtmgl3',
action='store_true',
help='download full SRTMGL3 topography dataset')
parser.add_option(
'--make-decimated-topo',
dest='make_decimated',
action='store_true',
help='pre-make all decimated topography datasets')
parser.add_option(
'--stations',
dest='stations_fn',
metavar='FILENAME',
help='load station coordinates from FILENAME')
parser.add_option(
'--events',
dest='events_fn',
metavar='FILENAME',
help='load event coordinates from FILENAME')
parser.add_option(
'--debug',
dest='debug',
action='store_true',
default=False,
help='print debugging information to stderr')
(options, args) = parser.parse_args(args)
if options.debug:
util.setup_logging(program_name, 'debug')
else:
util.setup_logging(program_name, 'info')
if options.download_etopo1:
import pyrocko.datasets.topo.etopo1
pyrocko.datasets.topo.etopo1.download()
if options.download_srtmgl3:
import pyrocko.datasets.topo.srtmgl3
pyrocko.datasets.topo.srtmgl3.download()
if options.make_decimated:
import pyrocko.datasets.topo
pyrocko.datasets.topo.make_all_missing_decimated()
if (options.download_etopo1 or options.download_srtmgl3 or
options.make_decimated) and len(args) == 0:
sys.exit(0)
if options.theme == 'soft':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.2,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.15,
'color_wet': (216, 242, 254),
'color_dry': (238, 236, 230),
'topo_cpt_wet': 'light_sea_uniform',
'topo_cpt_dry': 'light_land_uniform'}
elif options.theme == 'topo':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.5,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.25}
events = []
if options.events_fn:
events = model.load_events(options.events_fn)
stations = []
if options.stations_fn:
stations = model.load_stations(options.stations_fn)
if not (len(args) == 4 or (
len(args) == 1 and (events or stations))):
parser.print_help()
sys.exit(1)
if len(args) == 4:
try:
lat = float(args[0])
lon = float(args[1])
radius = float(args[2])*km
except Exception:
parser.print_help()
sys.exit(1)
else:
lats, lons = latlon_arrays(stations+events)
lat, lon = map(float, od.geographic_midpoint(lats, lons))
radius = float(
num.max(od.distance_accurate50m_numpy(lat, lon, lats, lons)))
radius *= 1.1
m = automap.Map(
width=options.width,
height=options.height,
lat=lat,
lon=lon,
radius=radius,
topo_resolution_max=options.topo_resolution_max,
topo_resolution_min=options.topo_resolution_min,
show_topo=options.show_topo,
show_grid=options.show_grid,
illuminate=options.illuminate,
**color_kwargs)
logger.debug('map configuration:\n%s' % str(m))
if options.show_cities:
m.draw_cities()
if stations:
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
m.gmt.psxy(
in_columns=(lons, lats),
S='t8p',
G='black',
*m.jxyr)
for s in stations:
m.add_label(s.lat, s.lon, '%s' % '.'.join(
x for x in s.nsl() if x))
if events:
beachball_symbol = 'mt'
beachball_size = 20.0
for ev in events:
if ev.moment_tensor is None:
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S='c12p',
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (
beachball_symbol[0], beachball_size / gmtpy.cm))
else:
kwargs = dict(
S='%s%g' % (
beachball_symbol[0], beachball_size*2 / gmtpy.cm))
m.gmt.psmeca(
in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
m.save(args[-1])
def bandpass(t):
t.bandpass(4, 0.1, 5.)
def lowpass_highpass(t):
t.lowpass(4, 5.)
t.highpass(4, 0.1)
def bandpass_fft(t):
t.bandpass_fft(0.1, 5.)
tab = []
for n in range(1, 22):
a = timeit(lambda: bandpass(mktrace(2**n)))
b = timeit(lambda: lowpass_highpass(mktrace(2**n)))
c = timeit(lambda: bandpass_fft(mktrace(2**n)))
print(2**n, a, b, c)
tab.append((2**n, a, b, c))
a = num.array(tab).T
p = gmtpy.Simple()
for i in range(1, 4):
p.plot((a[0], a[i]), '-W1p,%s' % gmtpy.color(i))
p.save('speed_filtering.pdf')
def main(args=None):
if args is None:
args = sys.argv[1:]
parser = OptionParser(
usage=usage,
description=description)
parser.add_option(
'--width',
dest='width',
type='float',
default=20.0,
metavar='FLOAT',
help='set width of output image [cm] (%default)')
parser.add_option(
'--height',
dest='height',
type='float',
default=15.0,
metavar='FLOAT',
help='set height of output image [cm] (%default)')
parser.add_option(
'--topo-resolution-min',
dest='topo_resolution_min',
type='float',
default=40.0,
metavar='FLOAT',
help='minimum resolution of topography [dpi] (%default)')
parser.add_option(
'--topo-resolution-max',
dest='topo_resolution_max',
type='float',
default=200.0,
metavar='FLOAT',
help='maximum resolution of topography [dpi] (%default)')
parser.add_option(
'--no-grid',
dest='show_grid',
default=True,
action='store_false',
help='don\'t show grid lines')
parser.add_option(
'--no-topo',
dest='show_topo',
default=True,
action='store_false',
help='don\'t show topography')
parser.add_option(
'--no-cities',
dest='show_cities',
default=True,
action='store_false',
help='don\'t show cities')
parser.add_option(
'--no-illuminate',
dest='illuminate',
default=True,
action='store_false',
help='deactivate artificial illumination of topography')
parser.add_option(
'--illuminate-factor-land',
dest='illuminate_factor_land',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of land (0.5)')
parser.add_option(
'--illuminate-factor-ocean',
dest='illuminate_factor_ocean',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of ocean (0.25)')
parser.add_option(
'--theme',
choices=['topo', 'soft'],
default='topo',
help='select color theme, available: topo, soft (topo)"')
parser.add_option(
'--download-etopo1',
dest='download_etopo1',
action='store_true',
help='download full ETOPO1 topography dataset')
parser.add_option(
'--download-srtmgl3',
dest='download_srtmgl3',
action='store_true',
help='download full SRTMGL3 topography dataset')
parser.add_option(
'--make-decimated-topo',
dest='make_decimated',
action='store_true',
help='pre-make all decimated topography datasets')
parser.add_option(
'--stations',
dest='stations_fn',
metavar='FILENAME',
help='load station coordinates from FILENAME')
parser.add_option(
'--events',
dest='events_fn',
metavar='FILENAME',
help='load event coordinates from FILENAME')
parser.add_option(
'--debug',
dest='debug',
action='store_true',
default=False,
help='print debugging information to stderr')
(options, args) = parser.parse_args(args)
if options.debug:
util.setup_logging(program_name, 'debug')
else:
util.setup_logging(program_name, 'info')
if options.download_etopo1:
import pyrocko.datasets.topo.etopo1
pyrocko.datasets.topo.etopo1.download()
if options.download_srtmgl3:
import pyrocko.datasets.topo.srtmgl3
pyrocko.datasets.topo.srtmgl3.download()
if options.make_decimated:
import pyrocko.datasets.topo
pyrocko.datasets.topo.make_all_missing_decimated()
if (options.download_etopo1 or options.download_srtmgl3 or
options.make_decimated) and len(args) == 0:
sys.exit(0)
if options.theme == 'soft':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.2,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.15,
'color_wet': (216, 242, 254),
'color_dry': (238, 236, 230),
'topo_cpt_wet': 'light_sea_uniform',
'topo_cpt_dry': 'light_land_uniform'}
elif options.theme == 'topo':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.5,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.25}
events = []
if options.events_fn:
events = model.load_events(options.events_fn)
stations = []
if options.stations_fn:
stations = model.load_stations(options.stations_fn)
if not (len(args) == 4 or (
len(args) == 1 and (events or stations))):
parser.print_help()
sys.exit(1)
if len(args) == 4:
try:
lat = float(args[0])
lon = float(args[1])
radius = float(args[2])*km
except Exception:
parser.print_help()
sys.exit(1)
else:
lats, lons = latlon_arrays(stations+events)
lat, lon = map(float, od.geographic_midpoint(lats, lons))
radius = float(
num.max(od.distance_accurate50m_numpy(lat, lon, lats, lons)))
radius *= 1.1
m = automap.Map(
width=options.width,
height=options.height,
lat=lat,
lon=lon,
radius=radius,
topo_resolution_max=options.topo_resolution_max,
topo_resolution_min=options.topo_resolution_min,
show_topo=options.show_topo,
show_grid=options.show_grid,
illuminate=options.illuminate,
**color_kwargs)
logger.debug('map configuration:\n%s' % str(m))
if options.show_cities:
m.draw_cities()
if stations:
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
m.gmt.psxy(
in_columns=(lons, lats),
S='t8p',
G='black',
*m.jxyr)
for s in stations:
m.add_label(s.lat, s.lon, '%s' % '.'.join(
x for x in s.nsl() if x))
if events:
beachball_symbol = 'mt'
beachball_size = 20.0
for ev in events:
if ev.moment_tensor is None:
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S='c12p',
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (
beachball_symbol[0], beachball_size / gmtpy.cm))
else:
kwargs = dict(
S='%s%g' % (
beachball_symbol[0], beachball_size*2 / gmtpy.cm))
m.gmt.psmeca(
in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
m.save(args[-1])
def plot_map(stations, center, events=None, savename=None):
from pyrocko.plot.automap import Map
from pyrocko.example import get_example_data
from pyrocko import model, gmtpy
from pyrocko import moment_tensor as pmt
gmtpy.check_have_gmt()
# Generate the basic map
m = Map(lat=center[0],
lon=center[1],
radius=150000.,
width=30.,
height=30.,
show_grid=False,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
# Draw some larger cities covered by the map area
m.draw_cities()
# Generate with latitute, longitude and labels of the stations
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
labels = ['.'.join(s.nsl()) for s in stations]
# Stations as black triangles.
m.gmt.psxy(in_columns=(lons, lats), S='t20p', G='black', *m.jxyr)
# Station labels
for i in range(len(stations)):
m.add_label(lats[i], lons[i], labels[i])
beachball_symbol = 'd'
factor_symbl_size = 5.0
if events is not None:
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c' + str(mag * factor_symbl_size) + 'p'
m.gmt.psxy(in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
else:
kwargs = dict(S='%s%g' % (beachball_symbol[0],
(beachball_size) * 2 / gmtpy.cm))
m.gmt.psmeca(in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
if savename is None:
if events is None:
m.save('pics/stations_ridgecrest.png')
else:
m.save('pics/mechanisms_scedc_ridgecrest.png')
else:
m.save(savename)
# Load events from catalog file (generated using catalog.GlobalCMT() to download from www.globalcmt.org)
# If no moment tensor is provided in the catalogue, the event is plotted as a red circle.
# Symbol size relative to magnitude.
events = model.load_events('deadsea_events_1976-2017.txt')
beachball_symbol = 'd'
factor_symbl_size = 5.0
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c'+str(mag*factor_symbl_size)+'p'
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag*factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)#
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (beachball_symbol[0], (beachball_size) / gmtpy.cm))
def bandpass(t):
t.bandpass(4, 0.1, 5.)
def lowpass_highpass(t):
t.lowpass(4, 5.)
t.highpass(4, 0.1)
def bandpass_fft(t):
t.bandpass_fft(0.1, 5.)
tab = []
for n in range(1, 22):
a = timeit(lambda: bandpass(mktrace(2**n)))
b = timeit(lambda: lowpass_highpass(mktrace(2**n)))
c = timeit(lambda: bandpass_fft(mktrace(2**n)))
print(2**n, a, b, c)
tab.append((2**n, a, b, c))
a = num.array(tab).T
p = gmtpy.Simple()
for i in range(1, 4):
p.plot((a[0], a[i]), '-W1p,%s' % gmtpy.color(i))
p.save('speed_filtering.pdf')
