x, y = cst.data.mapdata('coastlines', 'high', extent, 10.0)
x, y = proj(x, y)
ax.plot(x - 360.0, y, 'k-', lw=0.5)
# source
mts = 'scsn-mts-14383980.py'
mts = cst.util.load(mts)
x = mts.longitude
y = mts.latitude
x, y = proj(x, y)
if 0:
ax.plot(x, y, 'k*', ms=12, mew=1.0, mec='k', mfc='none')
else:
m = mts.double_couple_clvd
m = m['mzz'], m['mxx'], m['myy'], m['mxz'], -m['myz'], -m['mxy']
b = beachball.Beach(m, xy=(x, y), width=8000, linewidth=0.5, facecolor='k')
ax.add_collection(b)
# stations
sta = np.loadtxt('station-list.txt', 'S8, f, f, f')
x, y = proj(sta['f2'], sta['f1'])
ax.plot(x, y, 'k^', markersize=5)
for s, y, x, z in sta:
x, y = proj(x, y)
ax.text(x, y - 1800, s.split('.')[-1], ha='center', va='top')
# finish up
axis = bounds[0] + bounds[1]
#ax.set_aspect( aspect )
ax.set_xticks([])
ax.set_yticks([])
def maps(station_list, origin, strike, dip, rake, plot_file):
"""
Plotting a map with epicenter and possible stations according to distance
and a map with with the beachball
"""
# sets figure's dimensions
_fig_x = 10
_fig_y = 10
fig = plt.figure(figsize=(_fig_x, _fig_y))
# calculating map space
_max = max(_station.distance_by_origin for _station in station_list)
_max = int(round(_max * 1000 * 2))
_size = _max + int(round(_max / 7.0))
_diff = kilometer2degrees(round(_size / (2 * 2.0 * 1000)))
parallels = [
round(origin.latitude, 2),
round((origin.latitude - _diff), 2),
round((origin.latitude + _diff), 2)
]
meridians = [
round(origin.longitude, 2),
round((origin.longitude - _diff), 2),
round((origin.longitude + _diff), 2)
]
m = Basemap(projection='laea',
lat_0=origin.latitude,
lon_0=origin.longitude,
lat_ts=origin.latitude,
resolution='i',
area_thresh=0.1,
width=_size,
height=_size)
m.drawparallels(parallels, labels=[1, 0, 0, 0], color='grey', fontsize=10)
m.drawmeridians(meridians, labels=[0, 0, 0, 1], color='grey', fontsize=10)
m.drawrivers(color='aqua')
m.drawcoastlines(color='0.2')
m.drawcountries(color='0.4')
m.drawmapboundary(fill_color='aqua')
m.fillcontinents(color='coral', lake_color='aqua')
x, y = m(origin.longitude, origin.latitude)
# epicenter
m.scatter(x,
y,
1,
color="#FFFF00",
marker="*",
zorder=3,
linewidths=2,
edgecolor="k")
# beachball
ax = plt.gca()
b = beach.Beach([strike, dip, rake],
xy=(x, y),
width=35000,
linewidth=1,
facecolor='r')
b.set_zorder(10)
ax.add_collection(b)
# stations
for station in station_list:
x, y = m(station.longitude, station.latitude)
m.scatter(x,
y,
150,
color="#33CC00",
marker="^",
zorder=3,
linewidths=1,
edgecolor="k")
plt.text(x + 1800,
y + 3000,
station.code,
family="monospace",
fontsize=12)
fig.savefig(plot_file)
def correlation(depth_x, correlation_y, dc, beachballs, plot_file):
"""
Illustrates an example for plotting beachballs and data points on line
with specific color based on values with a labelled colorbar.
"""
# sets figure's dimensions
_fig_x = 30
_fig_y = 20
# creates figure
fig, ax = plt.subplots(figsize=(_fig_x, _fig_y))
# plots (depth_x, correlation_y) points on line
ax.plot(depth_x, correlation_y, '--', linewidth=2, color='k')
# creates a grid on the (main) plot
ax.grid()
# sets labels
plt.xlabel('Depth (km)')
plt.ylabel('Correlation')
# sets font size
plt.rcParams.update({'font.size': 28})
# sets fixed y-axis range
plt.ylim((0, 1))
# sets margins on the plot
plt.margins(0.1)
# sets color canvas for coloring beachball
cm = plt.cm.jet
# creates a colorbar at the right of main plot:
divider = make_axes_locatable(ax)
# makes room for colorbar
cax = divider.append_axes("right", size="2%", pad=1)
# set values to colorbar
norm = colors.Normalize(vmin=0, vmax=100)
# creates colorbar on specific axes, norm, canvas color and orientation
cb1 = colorbar.ColorbarBase(cax,
norm=norm,
cmap=cm,
orientation='vertical')
# sets colorbar label
cb1.set_label('DC%')
# plotting beachballs on specific x-axis and y-axis
# with a color based on the data_dc values (normalized to 0-1)
for i in xrange(len(depth_x)):
# sets color value
color = cm(dc[i] / 100.0)
# draws beachball
b = beach.Beach([beachballs[i][0], beachballs[i][1], beachballs[i][2]],
xy=(depth_x[i], correlation_y[i]),
width=80,
linewidth=1,
facecolor=color)
# holds the aspect but fixes positioning:
b.set_transform(transforms.IdentityTransform())
# brings the all patches to the origin (0, 0).
for p in b._paths:
p.vertices -= [depth_x[i], correlation_y[i]]
# uses the offset property of the collection to position the patches
b.set_offsets((depth_x[i], correlation_y[i]))
b._transOffset = ax.transData
# adds beachball to plot
ax.add_collection(b)
# saves plot to file
plt.savefig(plot_file, dpi=fig.dpi)
def contour(time_list, depth_list, dc_list, corr_list, beachball_list,
plot_file):
"""
Plotting contour
"""
# sets figure's dimensions
_fig_x = 60
_fig_y = 40
# creates figure
fig, ax = plt.subplots(figsize=(_fig_x, _fig_y))
# creates a grid on the (main) plot
ax.grid()
# sets labels
plt.xlabel('Time (sec)')
plt.ylabel('Centroid Depth (km)')
# sets font size
plt.rcParams.update({'font.size': 28})
# sets margins on the plot
plt.margins(0.05)
tri.Triangulation(time_list, depth_list)
levels = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.8, 1.0]
cont = plt.tricontour(time_list,
depth_list,
corr_list,
len(levels),
levels=levels,
linewidths=0.5,
colors='k')
plt.tricontourf(time_list,
depth_list,
corr_list,
len(levels),
levels=levels,
cmap=plt.cm.cool)
plt.clabel(cont)
cm = plt.cm.copper_r #gia dc
# plotting beachballs on specific x-axis and y-axis
# with a color based on the data_dc values (normalized to 0-1)
_max_corr = max(corr_list)
_index = corr_list.index(_max_corr)
for i in xrange(len(beachball_list)):
if i == _index:
# sets best beachball's color value to red
_color = 'red'
_width = 45 # bigger beachball for best match
else:
# sets beachball's color value
_color = cm(dc_list[i] / 100.0)
_width = 35
# draws beachball
b = beach.Beach(
[beachball_list[i][0], beachball_list[i][1], beachball_list[i][2]],
xy=(time_list[i], depth_list[i]),
width=_width,
linewidth=1,
facecolor=_color)
# holds the aspect but fixes positioning:
b.set_transform(transforms.IdentityTransform())
# brings the all patches to the origin (0, 0).
for p in b._paths:
p.vertices -= [time_list[i], depth_list[i]]
# uses the offset property of the collection to position the patches
b.set_offsets((time_list[i], depth_list[i]))
b._transOffset = ax.transData
# adds beachball to plot
ax.add_collection(b)
# creates a colorbar at the right of main plot
divider = make_axes_locatable(ax)
# makes room for colorbar
cax = divider.append_axes("right", size="1%", pad=0.5)
# set values to colorbar
norm = colors.Normalize(vmin=0.0, vmax=1.0)
# creates colorbar on specific axes, norm, canvas color and orientation
colorbar.ColorbarBase(cax,
cmap=plt.cm.cool,
norm=norm,
orientation='vertical',
label='Correlation')
cax = divider.append_axes("right", size="1%", pad=1.5)
# set values to colorbar
norm = colors.Normalize(vmin=0, vmax=100)
# creates colorbar on specific axes, norm, canvas color and orientation
colorbar.ColorbarBase(cax,
cmap=plt.cm.copper_r,
norm=norm,
orientation='vertical',
label='DC%')
# save plot to file
plt.savefig(plot_file, dpi=fig.dpi)
cax = divider.append_axes("right", size="2%", pad=1)
# set values to colorbar
norm = colors.Normalize(vmin=0, vmax=100)
# creates colorbar on specific axes, norm, canvas color and orientation
cb1 = colorbar.ColorbarBase(cax, norm=norm, cmap=cm, orientation='vertical')
# sets colorbar label
cb1.set_label('DC%')
# plotting beachballs on specific x-axis and y-axis with a color based on the data_dc values (normalized to 0-1)
for i in xrange(len(data_x)):
# sets color value
color = cm(data_dc[i] / 100.0)
# draws beachball
b = beach.Beach(
[data_beachballs[i][0], data_beachballs[i][1], data_beachballs[i][2]],
xy=(data_x[i], data_y[i]),
width=150,
linewidth=1,
facecolor=color)
# holds the aspect but fixes positioning:
b.set_transform(transforms.IdentityTransform())
# brings the all patches to the origin (0, 0).
for p in b._paths:
p.vertices -= [data_x[i], data_y[i]]
# uses the offset property of the collection to position the patches
b.set_offsets((data_x[i], data_y[i]))
b._transOffset = ax.transData
# adds beachball to plot
ax.add_collection(b)