def plot_global_map(self):
"""
Plot global map of event and stations
"""
# ax = plt.subplot(211)
plt.title(self.cmtsource.eventname)
m = Basemap(projection='cyl', lon_0=0.0, lat_0=0.0,
resolution='c')
m.drawcoastlines()
m.fillcontinents()
m.drawparallels(np.arange(-90., 120., 30.))
m.drawmeridians(np.arange(0., 420., 60.))
m.drawmapboundary()
x, y = m(self.sta_lon, self.sta_lat)
m.scatter(x, y, 30, color="r", marker="^", edgecolor="k",
linewidth='0.3', zorder=3)
cmt_lat = self.cmtsource.latitude
cmt_lon = self.cmtsource.longitude
focmecs = self.moment_tensor
ax = plt.gca()
bb = Beach(focmecs, xy=(cmt_lon, cmt_lat), width=20, linewidth=1,
alpha=1.0)
bb.set_zorder(10)
ax.add_collection(bb)
def source_reciever_plot(st, **kwargs):
"""
Plot source and reciever on map
"""
save = kwargs.get('save', False)
topo = kwargs.get('topo', False)
mt = kwargs.get('moment_tensor', False)
w = kwargs.get('width', (900000, 900000))
title = kwargs.get('title', True)
proj = kwargs.get('proj', 'aeqd')
m = mapplot(proj,
lat_0=st[0].stats.sac['evla'],
lon_0=st[0].stats.sac['evlo'])
m.drawparallels(np.arange(-80., 81., 20.), labels=[True])
m.drawmeridians(np.arange(-180., 181., 20.))
source_coord = add_source(st, m)
coord_list = stat_coord(st)
add_station(coord_list, m)
for ii in range(0, len(coord_list[0]), 2):
m.drawgreatcircle(source_coord[1],
source_coord[0],
coord_list[1][ii],
coord_list[0][ii],
c='k',
lw=0.3,
alpha=0.3)
title = os.getcwd().split('/')
ax = plt.gca()
x, y = m(st[0].stats.sac['evlo'], st[0].stats.sac['evla'])
if mt == False:
try:
b = beachball(st[0], xy=(x, y), plot='map')
b.set_zorder(2)
ax.add_collection(b)
except KeyError:
print('No focal mechanism found')
else:
b = Beach(mt, width=w, xy=(x, y))
b.set_zorder(2)
ax.add_collection(b)
if title == True:
ax.set_title('{} \n Depth (km): {} '.format(
title[5], round(st[0].stats.sac['evdp'], 3)))
if topo != False:
myplot.basemap.drawtopography(m, alpha=0.5, cmap=matplotlib.cm.gray)
if save != False:
plt.savefig(save + '/map.pdf', format='pdf')
if save == False:
plt.show()
def source_reciever_plot(st, **kwargs):
"""
Plot source and reciever on map
"""
save = kwargs.get('save',False)
topo = kwargs.get('topo',False)
mt = kwargs.get('moment_tensor',False)
w = kwargs.get('width',(900000,900000))
title = kwargs.get('title',True)
proj = kwargs.get('proj','eck4')
m = mapplot(proj,lat_0=st[0].stats.sac['evla'],lon_0=st[0].stats.sac['evlo'])
m.drawparallels(np.arange(-80.,81.,20.),labels=[True])
m.drawmeridians(np.arange(-180.,181.,20.))
source_coord = add_source(st,m)
coord_list = stat_coord(st)
add_station(coord_list,m)
for ii in range(0,len(coord_list[0]),2):
m.drawgreatcircle(source_coord[1],source_coord[0],
coord_list[1][ii],coord_list[0][ii],c='k',lw=0.3,alpha=0.3)
title = os.getcwd().split('/')
ax = plt.gca()
x,y = m(st[0].stats.sac['evlo'],st[0].stats.sac['evla'])
if mt == False:
try:
b = beachball(st[0],xy=(x,y),plot='map')
b.set_zorder(2)
ax.add_collection(b)
except KeyError:
print('No focal mechanism found')
else:
b = Beach(mt,width=w,xy=(x,y))
b.set_zorder(2)
ax.add_collection(b)
if title == True:
ax.set_title('{} \n Depth (km): {} '.format(
title[5],round(st[0].stats.sac['evdp'],3)))
if topo != False:
myplot.basemap.drawtopography(m,alpha=0.5,cmap=matplotlib.cm.gray)
if save != False:
plt.savefig(save+'/map.pdf',format='pdf')
if save == False:
plt.show()
def plot_events(events, map_object):
"""
"""
for event in events:
org = event.preferred_origin() or event.origins[0]
fm = event.preferred_focal_mechanism() or event.focal_mechanisms[0]
mt = fm.moment_tensor.tensor
# Add beachball plot.
x, y = map_object(org.longitude, org.latitude)
focmec = [mt.m_rr, mt.m_tt, mt.m_pp, mt.m_rt, mt.m_rp, mt.m_tp]
# Attempt to calculate the best beachball size.
width = max((map_object.xmax - map_object.xmin,
map_object.ymax - map_object.ymin)) * 0.020
b = Beach(focmec, xy=(x, y), width=width, linewidth=1, facecolor="red")
b.set_zorder(200000000)
plt.gca().add_collection(b)
def plot_events(events, map_object):
"""
"""
for event in events:
org = event.preferred_origin() or event.origins[0]
fm = event.preferred_focal_mechanism() or event.focal_mechanisms[0]
mt = fm.moment_tensor.tensor
# Add beachball plot.
x, y = map_object(org.longitude, org.latitude)
focmec = [mt.m_rr, mt.m_tt, mt.m_pp, mt.m_rt, mt.m_rp, mt.m_tp]
# Attempt to calculate the best beachball size.
width = max((map_object.xmax - map_object.xmin,
map_object.ymax - map_object.ymin)) * 0.020
b = Beach(focmec, xy=(x, y), width=width, linewidth=1, facecolor="red")
b.set_zorder(200000000)
plt.gca().add_collection(b)
def plot_mt(mapobj,
axisobj,
figobj,
earthquakes,
mt,
event_id,
location=None,
M_above=3.0,
show_above_M=True,
llat='-90',
ulat='90',
llon='-170',
ulon='190',
figsize=(12, 8),
radius=25,
dist_bt=600,
mt_width=2,
angle_step=20,
show_eq=True,
par_range=(-90., 120., 30.),
mer_range=(0, 360, 60),
pretty=False,
legend_loc=4,
title='',
resolution='l'):
'''
Function to plot moment tensors on the map
Input:
mapobj - already existing Basemap object onwhich to plot the quakes
earthquakes - list of earthquake information
mt - list of focal/moment_tensor information
event_id - event ID corresponding to the earthquakes
location - predefined region, choose from 'US' or 'CA',
default is 'None' which will plot the whole world
M_above - Only show the events with magnitude larger than this number
default is 5.0, use with show_above_M
show_above_M - Flag to turn on the M_above option, default is True,
llat - bottom left corner latitude, default is -90
ulat - upper right corner latitude, default is 90
llon - bottom left corner longitude, default is -170
ulon - upper right corner longitude, default is 190
figsize - figure size, default is (12,8)
radius - used in checking collisions (MT), put the MT on a circle with this
radius, default is 25
dist_bt - used in checking collisions (MT), if two events within dist_bt km,
then we say it is a collision, default is 600
angle_step - used in checking collisions (MT), this is to decide the angle
step on the circle, default is 20 degree
mt_width - size of the MT on the map. Different scale of the map may need
different size, play with it.
show_eq - flag to show the seismicity as well, default is True
par_range - range of latitudes you want to label on the map, start lat, end lat
and step size, default is (-90., 120., 30.),
mer_range - range of longitudes you want to label on the map, start lon, end lon
and step size, default is (0, 360, 60),
pretty - draw a pretty map, default is False to make faster plot
legend_loc - location of the legend, default is 4
title - title of the plot
resolution - resolution of the map, Possible values are
* ``"c"`` (crude)
* ``"l"`` (low)
* ``"i"`` (intermediate)
* ``"h"`` (high)
* ``"f"`` (full)
Defaults to ``"l"``
'''
quakedots = None
if location == 'US':
llon = -125
llat = 20
ulon = -70
ulat = 60
M_above = 4.0
radius = 5
dist_bt = 200
par_range = (20, 60, 15)
mer_range = (-120, -60, 15)
mt_width = 0.8
drawCountries = True
elif location == 'CAL':
llat = '30'
ulat = '45'
llon = '-130'
ulon = '-110'
M_above = 3.0
radius = 1.5
dist_bt = 50
mt_width = 0.3
drawStates = True
else:
location = None
times = [event[6] for event in earthquakes]
if show_above_M:
mags = [row[3] for row in mt]
index = np.array(mags) >= M_above
mt_select = np.array(mt)[index]
evid = np.array(event_id)[index]
#times_select = np.array(times)[index]
else:
evid = [row for row in event_id]
times_select = times
mt_select = mt
lats = [row[0] for row in mt_select]
lons = [row[1] for row in mt_select]
depths = [row[2] for row in mt_select]
mags = [row[3] for row in mt_select]
focmecs = [row[4:] for row in mt_select]
lats_m, lons_m, indicator = check_collision(lats, lons, radius, dist_bt,
angle_step)
#sys.exit(1)
count = 0
colors = []
min_color = 1 #min(times_select) 1
max_color = 10 #max(times_select) 10
colormap = plt.get_cmap()
for i in range(min_color, max_color):
colors.append(i)
scal_map = ScalarMappable(norm=cc.Normalize(min_color, max_color),
cmap=colormap)
scal_map.set_array(np.linspace(0, 1, 1))
colors_plot = [scal_map.to_rgba(c) for c in colors]
ys = np.array(lats_m)
xs = np.array(lons_m)
url = [
'http://earthquake.usgs.gov/earthquakes/eventpage/' + tmp + '#summary'
for tmp in evid
]
stnm = np.array(evid)
#fig, ax1 = plt.subplots(1,1, figsize = figsize)
#map_ax = fig.add_axes([0.03, 0.13, 0.94, 0.82])
# if show_eq:
# cm_ax = fig.add_axes([0.98, 0.39, 0.04, 0.3])
# plt.sca(ax1)
# cb = mpl.colorbar.ColorbarBase(ax=cm_ax, cmap=colormap, orientation='vertical')
# cb.set_ticks([0, 0.25, 0.5, 0.75, 1.0])
# color_range = max_color - min_color
# cb.set_ticklabels([_i.strftime('%Y-%b-%d, %H:%M:%S %p')
# for _i in [min_color, min_color + color_range * 0.25,
# min_color + color_range * 0.50,
# min_color + color_range * 0.75, max_color]])
#m = Basemap(projection='cyl', lon_0=142.36929, lat_0=38.3215, llcrnrlon=llon,llcrnrlat=llat,urcrnrlon=ulon,urcrnrlat=ulat,resolution=resolution)
#mapobj.drawmapboundary()
#mapobj.drawcountries()
#mapobj.drawparallels(np.arange(par_range[0], par_range[1], par_range[2]), labels=[1,0,0,0], linewidth=0)
#mapobj.drawmeridians(np.arange(mer_range[0],mer_range[1], mer_range[2]), labels=[0,0,0,1], linewidth=0)
# Plot the earthquake epicenters as points
x, y = mapobj(lons, lats)
min_size = 1
max_size = 8
min_mag = min(mags)
max_mag = max(mags)
if show_eq:
if len(lats) > 1:
frac = [(_i - min_mag) / (max_mag - min_mag) for _i in mags]
magnitude_size = [(_i * (max_size - min_size))**2 for _i in frac]
magnitude_size = [(_i * min_size / 2)**2 for _i in mags]
else:
magnitude_size = 15.0**2
colors_plot = "red"
quakedots = mapobj.scatter(x,
y,
marker='o',
s=magnitude_size,
c=colors_plot,
zorder=10)
print 'Max magnitude ' + str(np.max(mags)), 'Min magnitude ' + str(
np.min(mags))
#plot the moment tensor beachballs if available
x, y = mapobj(lons_m, lats_m)
mtlineobjs = []
mtobjs = []
for i in range(len(focmecs)):
index = np.where(focmecs[i] == 0)[0]
#note here, if the mrr is zero, then you will have an error
#so, change this to a very small number
if focmecs[i][0] == 0:
focmecs[i][0] = 0.001
width = mags[i] * mt_width
if depths[i] <= 50:
color = '#FFA500'
#label_
elif depths[i] > 50 and depths[i] <= 100:
color = '#FFFF00'
elif depths[i] > 100 and depths[i] <= 150:
color = '#00FF00'
elif depths[i] > 150 and depths[i] <= 200:
color = 'b'
else:
color = 'r'
if indicator[i] == 1:
lineobj = mapobj.plot([lons[i], lons_m[i]], [lats[i], lats_m[i]],
'k')
#mtlineobjs.append(lineobj)
#m.plot([10,20],[0,0])
else:
lineobj = None
try:
b = Beach(focmecs[i],
xy=(x[i], y[i]),
width=width,
linewidth=1,
facecolor=color,
alpha=1)
count += 1
#line = axisobj.plot(x[i],y[i], 'o', picker=5, markersize=30, alpha =0)
#mtlineobjs.append(line)
except:
pass
#ensure that the MTs are always plotted on top of the earthquakes associated with them
b.set_zorder(100)
axisobj.add_collection(b)
mtobjs.append(b)
mtlineobjs.append(lineobj)
d = 2
circ1 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="#FFA500")
circ2 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="#FFFF00")
circ3 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="#00FF00")
circ4 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="b")
circ5 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="r")
M4 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.4,
markersize=4 * d,
markerfacecolor="k")
M5 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.4,
markersize=5 * d,
markerfacecolor="k")
M6 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.4,
markersize=6 * d,
markerfacecolor="k")
M7 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.4,
markersize=7 * d,
markerfacecolor="k")
if location == 'World':
title = str(
count
) + ' events with focal mechanism - color codes depth, size the magnitude'
elif location == 'US':
title = 'US events with focal mechanism - color codes depth, size the magnitude'
elif location == 'CAL':
title = 'California events with focal mechanism - color codes depth, size the magnitude'
elif location is None:
pass
#handles, labels = axisobj.get_legend_handles_labels()
#axisobj.legend(handles,labels,(circ1, circ2, circ3, circ4, circ5), ("depth $\leq$ 50 km", "50 km $<$ depth $\leq$ 100 km",
# "100 km $<$ depth $\leq$ 150 km", "150 km $<$ depth $\leq$ 200 km","200 km $<$ depth"), numpoints=1, loc=legend_loc)
#plt.title(title)
#plt.gca().add_artist(legend1)
#if location == 'World':
# axisobj.legend(han,dles,labels(M4,M5,M6,M7), ("M 4.0", "M 5.0", "M 6.0", "M 7.0"), numpoints=1, loc=legend_loc)
if not quakedots:
quakedots = False
return mtlineobjs, mtobjs, quakedots, xs, ys, url
def plot_hist_mt(psmeca_dict,
figsize=(16, 24),
mt_size=10,
pretty=False,
resolution='l'):
if psmeca_dict['psmeca'] != []:
psmeca = psmeca_dict['psmeca']
#get the latitudes, longitudes, and the 6 independent component
lats = psmeca[:, 1]
lons = psmeca[:, 0]
focmecs = psmeca[:, 3:9]
depths = psmeca[:, 2]
(llat, ulat, llon, ulon) = psmeca_dict['range']
evla = psmeca_dict['evloc'][0]
evlo = psmeca_dict['evloc'][1]
plt.figure(figsize=figsize)
m = Basemap(projection='cyl',
lon_0=142.36929,
lat_0=38.3215,
llcrnrlon=llon,
llcrnrlat=llat,
urcrnrlon=ulon,
urcrnrlat=ulat,
resolution=resolution)
m.drawcoastlines()
m.drawmapboundary()
if pretty:
m.etopo()
else:
m.fillcontinents()
llat = float(llat)
ulat = float(ulat)
llon = float(llon)
ulon = float(ulon)
m.drawparallels(np.arange(llat, ulat, (ulat - llat) / 4.0),
labels=[1, 0, 0, 0])
m.drawmeridians(np.arange(llon, ulon, (ulon - llon) / 4.0),
labels=[0, 0, 0, 1])
ax = plt.gca()
x, y = m(lons, lats)
for i in range(len(focmecs)):
'''
if x[i] < 0:
x[i] = 360 + x[i]
'''
if depths[i] <= 50:
color = '#FFA500'
#label_
elif depths[i] > 50 and depths[i] <= 100:
color = 'g'
elif depths[i] > 100 and depths[i] <= 200:
color = 'b'
else:
color = 'r'
index = np.where(focmecs[i] == 0)[0]
#note here, if the mrr is zero, then you will have an error
#so, change this to a very small number
if focmecs[i][0] == 0:
focmecs[i][0] = 0.001
try:
b = Beach(focmecs[i],
xy=(x[i], y[i]),
width=mt_size,
linewidth=1,
facecolor=color)
except:
pass
b.set_zorder(10)
ax.add_collection(b)
x_0, y_0 = m(evlo, evla)
m.plot(x_0, y_0, 'r*', markersize=25)
circ1 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="#FFA500")
circ2 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="g")
circ3 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="b")
circ4 = Line2D([0], [0],
linestyle="none",
marker="o",
alpha=0.6,
markersize=10,
markerfacecolor="r")
plt.legend((circ1, circ2, circ3, circ4),
("depth $\leq$ 50 km", "50 km $<$ depth $\leq$ 100 km",
"100 km $<$ depth $\leq$ 200 km", "200 km $<$ depth"),
numpoints=1,
loc=3)
plt.show()
else:
print 'No historical MT found!'
# Make gradient plot.
#ps = m.pcolor(x, y, srtm3)
# Make contour plot.
cs = m.contour(x, y, srtm3, 40, colors=".4", lw=0.5, alpha=0.3)
m.drawcountries(color="red", linewidth=1)
# Draw a lon/lat grid (20 lines for an interval of one degree).
m.drawparallels(np.linspace(47, 48, 21), labels=[1,1,0,0], fmt="%.2f",
dashes=[2,2])
m.drawmeridians(np.linspace(12, 13, 21), labels=[0,0,1,1], fmt="%.2f",
dashes=[2,2])
# Calculate map projection for the coordinates.
x, y = m(stations_long, stations_lat)
m.scatter(x, y, 200, color="r", marker="v", edgecolor="k", zorder=3)
for i in range(len(stations_id)):
plt.text(x[i], y[i], " " + stations_id[i], color='k', va="top",
family="monospace", weight="bold")
# Calculate map projectoins for the beachballs.
x, y = m(events_long, events_lat)
# Plot the beachballs.
ax = plt.gca()
for i in range(len(events_focmec)):
b = Beach(events_focmec[i], xy=(x[i], y[i]), width=1000, linewidth=1)
b.set_zorder(10)
ax.add_collection(b)
# Save the figure.
plt.savefig("basemap_beachball_example.pdf")
def plot_mt(earthquakes, mt, event_id, location = None, M_above = 5.0, show_above_M = True,
llat = '-90', ulat = '90', llon = '-170', ulon = '190', figsize = (12,8),
radius = 25, dist_bt = 600, mt_width = 2, angle_step = 20, show_eq = True,
par_range = (-90., 120., 30.), mer_range = (0, 360, 60),
pretty = False, legend_loc = 4, title = '', resolution = 'l'):
'''
Function to plot moment tensors on the map
Input:
earthquakes - list of earthquake information
mt - list of focal/moment_tensor information
event_id - event ID corresponding to the earthquakes
location - predefined region, choose from 'US' or 'CA',
default is 'None' which will plot the whole world
M_above - Only show the events with magnitude larger than this number
default is 5.0, use with show_above_M
show_above_M - Flag to turn on the M_above option, default is True,
llat - bottom left corner latitude, default is -90
ulat - upper right corner latitude, default is 90
llon - bottom left corner longitude, default is -170
ulon - upper right corner longitude, default is 190
figsize - figure size, default is (12,8)
radius - used in checking collisions (MT), put the MT on a circle with this
radius, default is 25
dist_bt - used in checking collisions (MT), if two events within dist_bt km,
then we say it is a collision, default is 600
angle_step - used in checking collisions (MT), this is to decide the angle
step on the circle, default is 20 degree
mt_width - size of the MT on the map. Different scale of the map may need
different size, play with it.
show_eq - flag to show the seismicity as well, default is True
par_range - range of latitudes you want to label on the map, start lat, end lat
and step size, default is (-90., 120., 30.),
mer_range - range of longitudes you want to label on the map, start lon, end lon
and step size, default is (0, 360, 60),
pretty - draw a pretty map, default is False to make faster plot
legend_loc - location of the legend, default is 4
title - title of the plot
resolution - resolution of the map, Possible values are
* ``"c"`` (crude)
* ``"l"`` (low)
* ``"i"`` (intermediate)
* ``"h"`` (high)
* ``"f"`` (full)
Defaults to ``"l"``
'''
if location == 'US':
llon=-125
llat=20
ulon=-70
ulat=60
M_above = 4.0
radius = 5
dist_bt = 200
par_range = (20, 60, 15)
mer_range = (-120, -60, 15)
mt_width = 0.8
drawCountries = True
elif location == 'CAL':
llat = '30'
ulat = '45'
llon = '-130'
ulon = '-110'
M_above = 3.0
radius = 1.5
dist_bt = 50
mt_width = 0.3
drawStates = True
else:
location = None
print earthquakes,mt,event_id
times = [event[6] for event in earthquakes]
if show_above_M:
mags = [row[3] for row in mt]
index = np.array(mags) >= M_above
mt_select = np.array(mt)[index]
evid = np.array(event_id)[index]
times_select = np.array(times)[index]
else:
evid = [row[0] for row in event_id]
times_select = times
mt_select = mt
lats = [row[0] for row in mt_select]
lons = [row[1] for row in mt_select]
depths = [row[2] for row in mt_select]
mags = [row[3] for row in mt_select]
focmecs = [row[4:] for row in mt_select]
lats_m, lons_m, indicator = check_collision(lats, lons, radius, dist_bt, angle_step)
count = 0
colors=[]
min_color = min(times_select)
max_color = max(times_select)
colormap = plt.get_cmap()
for i in times_select:
colors.append(i)
scal_map = ScalarMappable(norm=cc.Normalize(min_color, max_color),cmap=colormap)
scal_map.set_array(np.linspace(0, 1, 1))
colors_plot = [scal_map.to_rgba(c) for c in colors]
ys = np.array(lats_m)
xs = np.array(lons_m)
url = ['http://earthquake.usgs.gov/earthquakes/eventpage/' + tmp + '#summary' for tmp in evid]
stnm = np.array(evid)
fig, ax1 = plt.subplots(1,1, figsize = figsize)
#map_ax = fig.add_axes([0.03, 0.13, 0.94, 0.82])
if show_eq:
cm_ax = fig.add_axes([0.98, 0.39, 0.04, 0.3])
plt.sca(ax1)
cb = mpl.colorbar.ColorbarBase(ax=cm_ax, cmap=colormap, orientation='vertical')
cb.set_ticks([0, 0.25, 0.5, 0.75, 1.0])
color_range = max_color - min_color
cb.set_ticklabels([_i.strftime('%Y-%b-%d, %H:%M:%S %p')
for _i in [min_color, min_color + color_range * 0.25,
min_color + color_range * 0.50,
min_color + color_range * 0.75, max_color]])
m = Basemap(projection='cyl', lon_0=142.36929, lat_0=38.3215,
llcrnrlon=llon,llcrnrlat=llat,urcrnrlon=ulon,urcrnrlat=ulat,resolution=resolution)
m.drawcoastlines()
m.drawmapboundary()
m.drawcountries()
m.drawparallels(np.arange(par_range[0], par_range[1], par_range[2]), labels=[1,0,0,0], linewidth=0)
m.drawmeridians(np.arange(mer_range[0],mer_range[1], mer_range[2]), labels=[0,0,0,1], linewidth=0)
if pretty:
m.etopo()
else:
m.fillcontinents()
x, y = m(lons_m, lats_m)
for i in range(len(focmecs)):
index = np.where(focmecs[i] == 0)[0]
#note here, if the mrr is zero, then you will have an error
#so, change this to a very small number
if focmecs[i][0] == 0:
focmecs[i][0] = 0.001
width = mags[i] * mt_width
if depths[i] <= 50:
color = '#FFA500'
#label_
elif depths[i] > 50 and depths [i] <= 100:
color = '#FFFF00'
elif depths[i] > 100 and depths [i] <= 150:
color = '#00FF00'
elif depths[i] > 150 and depths [i] <= 200:
color = 'b'
else:
color = 'r'
if indicator[i] == 1:
m.plot([lons[i],lons_m[i]],[lats[i], lats_m[i]], 'k')
#m.plot([10,20],[0,0])
try:
b = Beach(focmecs[i], xy=(x[i], y[i]),width=width, linewidth=1, facecolor= color, alpha=1)
count += 1
line, = ax1.plot(x[i],y[i], 'o', picker=5, markersize=30, alpha =0)
except:
pass
b.set_zorder(3)
ax1.add_collection(b)
d=5
circ1 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="#FFA500")
circ2 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="#FFFF00")
circ3 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="#00FF00")
circ4 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="b")
circ5 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="r")
M4 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.4, markersize= 4*d, markerfacecolor="k")
M5 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.4, markersize= 5*d, markerfacecolor="k")
M6 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.4, markersize= 6*d, markerfacecolor="k")
M7 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.4, markersize= 7*d, markerfacecolor="k")
if location == 'World':
title = str(count) + ' events with focal mechanism - color codes depth, size the magnitude'
elif location == 'US':
title = 'US events with focal mechanism - color codes depth, size the magnitude'
elif location == 'CAL':
title = 'California events with focal mechanism - color codes depth, size the magnitude'
elif location is None:
pass
legend1 = plt.legend((circ1, circ2, circ3, circ4, circ5), ("depth $\leq$ 50 km", "50 km $<$ depth $\leq$ 100 km",
"100 km $<$ depth $\leq$ 150 km", "150 km $<$ depth $\leq$ 200 km","200 km $<$ depth"), numpoints=1, loc=legend_loc)
plt.title(title)
plt.gca().add_artist(legend1)
if location == 'World':
plt.legend((M4,M5,M6,M7), ("M 4.0", "M 5.0", "M 6.0", "M 7.0"), numpoints=1, loc=legend_loc)
x, y = m(lons, lats)
min_size = 6
max_size = 30
min_mag = min(mags)
max_mag = max(mags)
if show_eq:
if len(lats) > 1:
frac = [(_i - min_mag) / (max_mag - min_mag) for _i in mags]
magnitude_size = [(_i * (max_size - min_size)) ** 2 for _i in frac]
magnitude_size = [(_i * min_size/2)**2 for _i in mags]
else:
magnitude_size = 15.0 ** 2
colors_plot = "red"
m.scatter(x, y, marker='o', s=magnitude_size, c=colors_plot,
zorder=10)
plt.show()
print 'Max magnitude ' + str(np.max(mags)), 'Min magnitude ' + str(np.min(mags))
def plot_hist_mt(psmeca_dict, figsize = (16,24), mt_size = 10, pretty = False, resolution='l'):
if psmeca_dict['psmeca'] != []:
psmeca = psmeca_dict['psmeca']
#get the latitudes, longitudes, and the 6 independent component
lats = psmeca[:,1]
lons = psmeca[:,0]
focmecs = psmeca[:,3:9]
depths = psmeca[:,2]
(llat, ulat, llon, ulon) = psmeca_dict['range']
evla = psmeca_dict['evloc'][0]
evlo = psmeca_dict['evloc'][1]
plt.figure(figsize=figsize)
m = Basemap(projection='cyl', lon_0=142.36929, lat_0=38.3215,
llcrnrlon=llon,llcrnrlat=llat,urcrnrlon=ulon,urcrnrlat=ulat,resolution=resolution)
m.drawcoastlines()
m.drawmapboundary()
if pretty:
m.etopo()
else:
m.fillcontinents()
llat = float(llat)
ulat = float(ulat)
llon = float(llon)
ulon = float(ulon)
m.drawparallels(np.arange(llat, ulat, (ulat - llat) / 4.0), labels=[1,0,0,0])
m.drawmeridians(np.arange(llon, ulon, (ulon - llon) / 4.0), labels=[0,0,0,1])
ax = plt.gca()
x, y = m(lons, lats)
for i in range(len(focmecs)):
'''
if x[i] < 0:
x[i] = 360 + x[i]
'''
if depths[i] <= 50:
color = '#FFA500'
#label_
elif depths[i] > 50 and depths [i] <= 100:
color = 'g'
elif depths[i] > 100 and depths [i] <= 200:
color = 'b'
else:
color = 'r'
index = np.where(focmecs[i] == 0)[0]
#note here, if the mrr is zero, then you will have an error
#so, change this to a very small number
if focmecs[i][0] == 0:
focmecs[i][0] = 0.001
try:
b = Beach(focmecs[i], xy=(x[i], y[i]),width=mt_size, linewidth=1, facecolor=color)
except:
pass
b.set_zorder(10)
ax.add_collection(b)
x_0, y_0 = m(evlo, evla)
m.plot(x_0, y_0, 'r*', markersize=25)
circ1 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="#FFA500")
circ2 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="g")
circ3 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="b")
circ4 = Line2D([0], [0], linestyle="none", marker="o", alpha=0.6, markersize=10, markerfacecolor="r")
plt.legend((circ1, circ2, circ3, circ4), ("depth $\leq$ 50 km", "50 km $<$ depth $\leq$ 100 km",
"100 km $<$ depth $\leq$ 200 km", "200 km $<$ depth"), numpoints=1, loc=3)
plt.show()
else:
print 'No historical MT found!'
def createMap(
ll=None,
ur=None,
figsize=None,
margin=None,
ax=None,
dict_basemap=None,
countries=True,
lw=1,
coastlines=True,
mapboundary=True,
grid=False,
grid_labels=True,
watercolor="#ADD8E6",
fillcontinents="coral",
use_lsmask=False,
stations=None,
cities=None,
trench=None,
earthquake=None,
slip=None,
elevation=None,
elevation_args=(7000, 500, True),
elevation_offset=None,
shaded=True,
shaded_args=(315, 45, 0.2),
colormap=None,
title=None,
show=True,
save=None,
station_markersize=4,
elev_oceans=True,
grid_lw=None,
spines_lw=None,
dpi=None,
station_labelsize="small",
loffset=None,
):
if figsize:
fig = plt.figure(figsize=figsize)
if margin:
ax = fig.add_axes(margin)
else:
fig = None
if dict_basemap is None:
dict_basemap = dict(
llcrnrlon=-180,
llcrnrlat=-60,
urcrnrlon=180,
urcrnrlat=60,
lat_0=0,
lon_0=0,
projection="hammer",
resolution="l",
)
elif ll is not None:
print dict_basemap
up_dict = dict(llcrnrlon=ll[1], llcrnrlat=ll[0], urcrnrlon=ur[1], urcrnrlat=ur[0])
dict_basemap.update(up_dict)
m = Basemap(ax=ax, **dict_basemap)
if fillcontinents and use_lsmask:
m.drawlsmask(land_color=fillcontinents, ocean_color="white")
elif fillcontinents:
m.fillcontinents(color=fillcontinents, lake_color=watercolor, zorder=0)
if countries:
m.drawcountries(linewidth=lw)
if coastlines:
m.drawcoastlines(linewidth=lw)
if mapboundary:
m.drawmapboundary(fill_color=watercolor, zorder=-10)
print 1
if grid or grid_labels:
if not grid_lw:
grid_lw = lw
if grid is True:
grid = 1.0
# JGR
if grid and grid_labels:
m.drawparallels(
np.arange(-90.0, 90.0, grid),
labels=[True, True, False, False],
linewidth=grid_lw,
xoffset=loffset,
yoffset=loffset,
size="small",
)
m.drawmeridians(
np.arange(0.0, 390.0, grid),
labels=[False, False, True, True],
linewidth=grid_lw,
xoffset=loffset,
yoffset=loffset,
size="small",
)
elif grid:
m.drawparallels(np.arange(-90.0, 90.0, grid), labels=[False, False, False, False], linewidth=grid_lw)
m.drawmeridians(np.arange(0.0, 390.0, grid), labels=[False, False, False, False], linewidth=grid_lw)
if stations:
stations.plot(m, mfc="b", ms=station_markersize, zorder=10, lsize=station_labelsize)
if slip:
if len(slip) == 4:
x, y, z, levels = slip
colors_slip = None
else:
x, y, z, levels, colors_slip = slip
x, y = zip(*[m(lon, lat) for lon, lat in zip(x, y)])
if len(np.shape(z)) == 2:
grid_x = x
grid_y = y
else:
grid_x = np.arange(
min(x), max(x) - 0.15 * (max(x) - min(x)), 100
) # VERY dirty hack to cut of parts of the slip model
grid_y = np.arange(min(y), max(y), 100)
# grid_x, grid_y = np.mgrid[min(x):max(x):100j, min(y):max(y):100j]
z = scipy.interpolate.griddata((x, y), z, (grid_x[None, :], grid_y[:, None]), method="cubic")
plt.gca().contour(grid_x, grid_y, z, levels, colors=colors_slip, lw=lw)
if earthquake == "Tocopilla":
x, y = m(-70.06, -22.34)
x2, y2 = m(-69.5, -24.2) # x2, y2 = m(-70.4, -21.5)
m.plot((x, x2), (y, y2), "k-", lw=lw) # line
m.plot((x), (y), "r*", ms=2 * station_markersize, zorder=10) # epicenter
b = Beach([358, 26, 109], xy=(x2, y2), width=50000, linewidth=lw)
b.set_zorder(10)
plt.gca().add_collection(b)
plt.annotate(
"14 Nov. 2007\n M 7.7",
(x2, y2),
xytext=(15, 0), # 22
textcoords="offset points",
va="center",
size=station_labelsize,
)
elif earthquake == "Tocopilla_beachball":
# x, y = m(-70.06, -22.34)
x2, y2 = m(-69.5, -24.2) # x2, y2 = m(-70.4, -21.5)
b = Beach([358, 26, 109], xy=(x2, y2), width=50000, linewidth=lw)
b.set_zorder(10)
plt.gca().add_collection(b)
plt.annotate("14 Nov. 2007\n M 7.6", (x2, y2), xytext=(22, 0), textcoords="offset points", va="center")
elif earthquake == "Tocopilla_position":
x, y = m(-70.06, -22.34)
m.plot((x), (y), "r*", ms=15, zorder=10) # epicenter
elif earthquake:
xs, ys = zip(*[m(lon, lat) for lon, lat in zip(*earthquake[:2])])
m.plot(xs, ys, "r*", ms=15, zorder=10) # epicenters
if len(earthquake) == 3:
for i in range(len(xs)):
x, y, mag = xs[i], ys[i], earthquake[2][i]
plt.annotate("M%.1f" % mag, xy=(x, y), xytext=(-5, -15), textcoords="offset points", va="center")
elif len(earthquake) > 3:
for i in range(len(xs)):
x, y, mag, date = xs[i], ys[i], earthquake[2][i], earthquake[3][i]
plt.annotate(
"M%.1f\n%s" % (mag, date.date), xy=(x, y), xytext=(10, 0), textcoords="offset points", va="center"
)
print 2
if elevation:
vmax, resol, bar = elevation_args
geo = gdal.Open(elevation)
topoin = geo.ReadAsArray()
if elevation_offset:
topoin[topoin > 0] += elevation_offset
coords = geo.GetGeoTransform()
nlons = topoin.shape[1]
nlats = topoin.shape[0]
delon = coords[1]
delat = coords[5]
lons = coords[0] + delon * np.arange(nlons)
lats = coords[3] + delat * np.arange(nlats)[::-1] # reverse lats
# create masked array, reversing data in latitude direction
# (so that data is oriented in increasing latitude,
# as transform_scalar requires).
topoin = np.ma.masked_less(topoin[::-1, :], -11000)
# topoin = gaussian_filter(topoin, 1)
# topoin = array[::-1, :]
# transform DEM data to a 250m native projection grid
# if True:
# x, y = m(*np.meshgrid(lons, lats))
# m.contourf(x, y, topoin, 100, cm=colormap)
# if save:
# plt.savefig(save)
# return
if resol:
if resol < 25:
nx = resol * len(lons)
ny = resol * len(lats)
else:
nx = int((m.xmax - m.xmin) / resol) + 1
ny = int((m.ymax - m.ymin) / resol) + 1
else:
nx = len(lons)
ny = len(lats)
topodat = m.transform_scalar(topoin, lons, lats, nx, ny, masked=True)
if elevation == "CleanTopo2_nchile.tif":
# -10,701m(0) to 8,248m(18948)
topodat = topodat - 10701
if isinstance(colormap, basestring) and os.path.isfile(colormap) and colormap.endswith(".gpf"):
colormap = createColormapFromGPF(colormap)
if shaded:
azdeg, altdeg, fraction = shaded_args
ls = colors.LightSource(azdeg=azdeg, altdeg=altdeg)
# convert data to rgb array including shading from light source.
if elev_oceans:
rgb = colormap(0.5 * topodat / vmax + 0.5)
else:
rgb = colormap(topodat / vmax)
rgb1 = ls.shade_rgb(rgb, elevation=topodat, fraction=fraction)
rgb[:, :, 0:3] = rgb1
m.imshow(rgb, zorder=1)
else:
if elev_oceans:
m.imshow(topodat, interpolation="bilinear", cmap=colormap, zorder=1, vmin=-vmax, vmax=vmax)
else:
m.imshow(topodat, interpolation="bilinear", cmap=colormap, zorder=1, vmin=0, vmax=vmax)
if bar:
ax = plt.gca()
fig = plt.gcf()
# cb_ax = fig.add_axes([0.8, 0.3, 0.02, 0.4])
cb_ax = fig.add_axes([0.82, 0.3, 0.02, 0.4])
cb = colorbar.ColorbarBase(cb_ax, cmap=colormap, norm=colors.Normalize(vmin=-vmax, vmax=vmax))
# cb.set_label('elevation and bathymetry')
ticks = (np.arange(20) - 10) * 1000
ticks = ticks[np.abs(ticks) <= vmax]
cb.set_ticks(ticks)
tls = ["%dm" % i if i % 2000 == 0 else "" for i in ticks]
cb.set_ticklabels(tls)
plt.axes(ax) # make the original axes current again
if cities == "ipoc":
cities = "Antofagasta Tocopilla Iquique Calama Pisagua Arica".split()
lons = [-70.4, -70.2, -70.1525, -68.933333, -70.216667, -70.333333]
lats = [-23.65, -22.096389, -20.213889, -22.466667, -19.6, -18.483333]
x, y = m(lons[: len(cities)], lats[: len(cities)])
m.plot(x, y, "o", ms=station_markersize, mfc="w", mec="k", zorder=10)
for i in range(len(cities)):
if "Anto" in cities[i]:
plt.annotate(
cities[i], (x[i], y[i]), xytext=(5, 0), textcoords="offset points", va="top", size=station_labelsize
)
else:
plt.annotate(
cities[i],
(x[i], y[i]),
xytext=(-5, 0),
textcoords="offset points",
ha="right",
size=station_labelsize,
)
elif cities == "Tocopilla":
lons = [-70.2]
lats = [-22.096389]
x, y = m(lons, lats)
m.plot(x, y, "o", ms=station_markersize, mfc="w", mec="k", zorder=10)
plt.annotate("Tocopilla", (x[0], y[0]), xytext=(5, 0), textcoords="offset points", size=station_labelsize)
if trench == "ipoc":
coords = np.transpose(np.loadtxt("/home/richter/Data/map/" "nchile_trench.txt"))
import matplotlib as mpl # hack JGR
mpl.rcParams.update({"lines.linewidth": 1})
plotTrench(m, coords[0, :], coords[1, :], facecolors="k", edgecolors="k")
if spines_lw:
for l in plt.gca().spines.values():
l.set_linewidth(spines_lw)
if title:
plt.title(title, y=1.05)
if save:
plt.savefig(save, dpi=dpi)
if show:
plt.show()
return m
def createMap(ll=None,
ur=None,
figsize=None,
margin=None,
ax=None,
dict_basemap=None,
countries=True,
lw=1,
coastlines=True,
mapboundary=True,
grid=False,
grid_labels=True,
watercolor='#ADD8E6',
fillcontinents='coral',
use_lsmask=False,
stations=None,
cities=None,
trench=None,
earthquake=None,
slip=None,
elevation=None,
elevation_args=(7000, 500, True),
elevation_offset=None,
shaded=True,
shaded_args=(315, 45, 0.2),
colormap=None,
title=None,
show=True,
save=None,
station_markersize=4,
elev_oceans=True,
grid_lw=None,
spines_lw=None,
dpi=None,
station_labelsize='small',
loffset=None):
if figsize:
fig = plt.figure(figsize=figsize)
if margin:
ax = fig.add_axes(margin)
else:
fig = None
if dict_basemap is None:
dict_basemap = dict(llcrnrlon=-180,
llcrnrlat=-60,
urcrnrlon=180,
urcrnrlat=60,
lat_0=0,
lon_0=0,
projection='hammer',
resolution='l')
elif ll is not None:
print dict_basemap
up_dict = dict(llcrnrlon=ll[1],
llcrnrlat=ll[0],
urcrnrlon=ur[1],
urcrnrlat=ur[0])
dict_basemap.update(up_dict)
m = Basemap(ax=ax, **dict_basemap)
if fillcontinents and use_lsmask:
m.drawlsmask(land_color=fillcontinents, ocean_color='white')
elif fillcontinents:
m.fillcontinents(color=fillcontinents, lake_color=watercolor, zorder=0)
if countries:
m.drawcountries(linewidth=lw)
if coastlines:
m.drawcoastlines(linewidth=lw)
if mapboundary:
m.drawmapboundary(fill_color=watercolor, zorder=-10)
print 1
if grid or grid_labels:
if not grid_lw:
grid_lw = lw
if grid is True:
grid = 1.
#JGR
if grid and grid_labels:
m.drawparallels(np.arange(-90., 90., grid),
labels=[True, True, False, False],
linewidth=grid_lw,
xoffset=loffset,
yoffset=loffset,
size='small')
m.drawmeridians(np.arange(0., 390., grid),
labels=[False, False, True, True],
linewidth=grid_lw,
xoffset=loffset,
yoffset=loffset,
size='small')
elif grid:
m.drawparallels(np.arange(-90., 90., grid),
labels=[False, False, False, False],
linewidth=grid_lw)
m.drawmeridians(np.arange(0., 390., grid),
labels=[False, False, False, False],
linewidth=grid_lw)
if stations:
stations.plot(m,
mfc='b',
ms=station_markersize,
zorder=10,
lsize=station_labelsize)
if slip:
if len(slip) == 4:
x, y, z, levels = slip
colors_slip = None
else:
x, y, z, levels, colors_slip = slip
x, y = zip(*[m(lon, lat) for lon, lat in zip(x, y)])
if len(np.shape(z)) == 2:
grid_x = x
grid_y = y
else:
grid_x = np.arange(
min(x),
max(x) - 0.15 * (max(x) - min(x)),
100) #VERY dirty hack to cut of parts of the slip model
grid_y = np.arange(min(y), max(y), 100)
#grid_x, grid_y = np.mgrid[min(x):max(x):100j, min(y):max(y):100j]
z = scipy.interpolate.griddata((x, y),
z,
(grid_x[None, :], grid_y[:, None]),
method='cubic')
plt.gca().contour(grid_x, grid_y, z, levels, colors=colors_slip, lw=lw)
if earthquake == 'Tocopilla':
x, y = m(-70.06, -22.34)
x2, y2 = m(-69.5, -24.2) #x2, y2 = m(-70.4, -21.5)
m.plot((x, x2), (y, y2), 'k-', lw=lw) #line
m.plot((x), (y), 'r*', ms=2 * station_markersize,
zorder=10) #epicenter
b = Beach([358, 26, 109], xy=(x2, y2), width=50000, linewidth=lw)
b.set_zorder(10)
plt.gca().add_collection(b)
plt.annotate(
'14 Nov. 2007\n M 7.7',
(x2, y2),
xytext=(15, 0), # 22
textcoords='offset points',
va='center',
size=station_labelsize)
elif earthquake == 'Tocopilla_beachball':
#x, y = m(-70.06, -22.34)
x2, y2 = m(-69.5, -24.2) #x2, y2 = m(-70.4, -21.5)
b = Beach([358, 26, 109], xy=(x2, y2), width=50000, linewidth=lw)
b.set_zorder(10)
plt.gca().add_collection(b)
plt.annotate('14 Nov. 2007\n M 7.6', (x2, y2),
xytext=(22, 0),
textcoords='offset points',
va='center')
elif earthquake == 'Tocopilla_position':
x, y = m(-70.06, -22.34)
m.plot((x), (y), 'r*', ms=15, zorder=10) #epicenter
elif earthquake:
xs, ys = zip(*[m(lon, lat) for lon, lat in zip(*earthquake[:2])])
m.plot(xs, ys, 'r*', ms=15, zorder=10) #epicenters
if len(earthquake) == 3:
for i in range(len(xs)):
x, y, mag = xs[i], ys[i], earthquake[2][i]
plt.annotate('M%.1f' % mag,
xy=(x, y),
xytext=(-5, -15),
textcoords='offset points',
va='center')
elif len(earthquake) > 3:
for i in range(len(xs)):
x, y, mag, date = xs[i], ys[i], earthquake[2][i], earthquake[
3][i]
plt.annotate('M%.1f\n%s' % (mag, date.date),
xy=(x, y),
xytext=(10, 0),
textcoords='offset points',
va='center')
print 2
if elevation:
vmax, resol, bar = elevation_args
geo = gdal.Open(elevation)
topoin = geo.ReadAsArray()
if elevation_offset:
topoin[topoin > 0] += elevation_offset
coords = geo.GetGeoTransform()
nlons = topoin.shape[1]
nlats = topoin.shape[0]
delon = coords[1]
delat = coords[5]
lons = coords[0] + delon * np.arange(nlons)
lats = coords[3] + delat * np.arange(nlats)[::-1] # reverse lats
# create masked array, reversing data in latitude direction
# (so that data is oriented in increasing latitude,
# as transform_scalar requires).
topoin = np.ma.masked_less(topoin[::-1, :], -11000)
#topoin = gaussian_filter(topoin, 1)
#topoin = array[::-1, :]
# transform DEM data to a 250m native projection grid
# if True:
# x, y = m(*np.meshgrid(lons, lats))
# m.contourf(x, y, topoin, 100, cm=colormap)
# if save:
# plt.savefig(save)
# return
if resol:
if resol < 25:
nx = resol * len(lons)
ny = resol * len(lats)
else:
nx = int((m.xmax - m.xmin) / resol) + 1
ny = int((m.ymax - m.ymin) / resol) + 1
else:
nx = len(lons)
ny = len(lats)
topodat = m.transform_scalar(topoin, lons, lats, nx, ny, masked=True)
if elevation == 'CleanTopo2_nchile.tif':
# -10,701m(0) to 8,248m(18948)
topodat = topodat - 10701
if (isinstance(colormap, basestring) and os.path.isfile(colormap)
and colormap.endswith('.gpf')):
colormap = createColormapFromGPF(colormap)
if shaded:
azdeg, altdeg, fraction = shaded_args
ls = colors.LightSource(azdeg=azdeg, altdeg=altdeg)
# convert data to rgb array including shading from light source.
if elev_oceans:
rgb = colormap(0.5 * topodat / vmax + 0.5)
else:
rgb = colormap(topodat / vmax)
rgb1 = ls.shade_rgb(rgb, elevation=topodat, fraction=fraction)
rgb[:, :, 0:3] = rgb1
m.imshow(rgb, zorder=1)
else:
if elev_oceans:
m.imshow(topodat,
interpolation='bilinear',
cmap=colormap,
zorder=1,
vmin=-vmax,
vmax=vmax)
else:
m.imshow(topodat,
interpolation='bilinear',
cmap=colormap,
zorder=1,
vmin=0,
vmax=vmax)
if bar:
ax = plt.gca()
fig = plt.gcf()
#cb_ax = fig.add_axes([0.8, 0.3, 0.02, 0.4])
cb_ax = fig.add_axes([0.82, 0.3, 0.02, 0.4])
cb = colorbar.ColorbarBase(cb_ax,
cmap=colormap,
norm=colors.Normalize(vmin=-vmax,
vmax=vmax))
#cb.set_label('elevation and bathymetry')
ticks = (np.arange(20) - 10) * 1000
ticks = ticks[np.abs(ticks) <= vmax]
cb.set_ticks(ticks)
tls = ['%dm' % i if i % 2000 == 0 else '' for i in ticks]
cb.set_ticklabels(tls)
plt.axes(ax) # make the original axes current again
if cities == 'ipoc':
cities = 'Antofagasta Tocopilla Iquique Calama Pisagua Arica'.split()
lons = [-70.4, -70.2, -70.1525, -68.933333, -70.216667, -70.333333]
lats = [-23.65, -22.096389, -20.213889, -22.466667, -19.6, -18.483333]
x, y = m(lons[:len(cities)], lats[:len(cities)])
m.plot(x, y, 'o', ms=station_markersize, mfc='w', mec='k', zorder=10)
for i in range(len(cities)):
if 'Anto' in cities[i]:
plt.annotate(cities[i], (x[i], y[i]),
xytext=(5, 0),
textcoords='offset points',
va='top',
size=station_labelsize)
else:
plt.annotate(cities[i], (x[i], y[i]),
xytext=(-5, 0),
textcoords='offset points',
ha='right',
size=station_labelsize)
elif cities == 'Tocopilla':
lons = [-70.2]
lats = [-22.096389]
x, y = m(lons, lats)
m.plot(x, y, 'o', ms=station_markersize, mfc='w', mec='k', zorder=10)
plt.annotate('Tocopilla', (x[0], y[0]),
xytext=(5, 0),
textcoords='offset points',
size=station_labelsize)
if trench == 'ipoc':
coords = np.transpose(
np.loadtxt('/home/richter/Data/map/'
'nchile_trench.txt'))
import matplotlib as mpl # hack JGR
mpl.rcParams.update({'lines.linewidth': 1})
plotTrench(m,
coords[0, :],
coords[1, :],
facecolors='k',
edgecolors='k')
if spines_lw:
for l in plt.gca().spines.values():
l.set_linewidth(spines_lw)
if title:
plt.title(title, y=1.05)
if save:
plt.savefig(save, dpi=dpi)
if show:
plt.show()
return m
from obspy.imaging.beachball import Beach
focmec, lat, lon = [], [], []
datos = open('datos.txt')
counter = 0
for line in datos:
if counter > 0:
focmec.append([float(line.split('\t')[7]),float(line.split('\t')[9]),float(line.split('\t')[9])])
lat.append(float(line.split('\t')[1]))
lon.append(float(line.split('\t')[2]))
counter+= 1
map = Basemap(llcrnrlon=-83.5,llcrnrlat=-4.5,urcrnrlon=-76,urcrnrlat=6, projection='cyl', resolution=None)
#map.drawcoastlines()
x, y = map(lon, lat)
#map.scatter(x, y, 200, color="r", marker="v", edgecolor="k", zorder=3)
ax = plt.gca()
for i in range(len(focmec)):
b = Beach(focmec[i], xy=(x[i], y[i]), width=0.35, linewidth=1)
b.set_zorder(1)
ax.add_collection(b)
map.arcgisimage(service='NatGeo_World_Map', xpixels = 1500, verbose= True)
plt.show()
