forked from pyrocko/contrib-snufflings
/
time_line.py
260 lines (219 loc) · 8.78 KB
/
time_line.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
from pyrocko.gui.snuffling import Snuffling, Param, Choice, Switch
from pyrocko.gui.util import EventMarker
from pyrocko import orthodrome
from pyrocko import moment_tensor
from pyrocko.orthodrome import distance_accurate50m as distance
from pyrocko import util, model
import matplotlib.dates as mdates
from matplotlib import cm
import numpy as num
from datetime import datetime
km = 1000.
cmap = cm.RdYlBu
cmaps = {'Red-Yellow-Blue': 'RdYlBu',
'Viridis': 'viridis',
'Magma': 'magma'}
save_cmaps = {}
for k, v in cmaps.items():
try:
x = getattr(cm, v)
save_cmaps[k] = x
except AttributeError:
continue
class TimeLine(Snuffling):
'''
<html>
<body>
<h1>Temporal Evolution of Seismicity</h1>
The considered region can be limited by defining one central coordinate
and a maximum epicentral distance.
</body>
</html>
'''
def setup(self):
'''Customization of the snuffling.'''
self.set_name('Time Line')
self.add_parameter(
Param('Latitude:', 'lat', 90, -90., 90., high_is_none=True))
self.add_parameter(
Param('Longitude:', 'lon', 180., -180, 180., high_is_none=True))
self.add_parameter(
Param('Maximum Distance [km]:', 'maxd', 20000., 0., 20000.,
high_is_none=True))
self.add_parameter(
Choice('Color by', 'color_by', 'time',
['time', 'longitude', 'latitude', 'magnitude', 'depth', 'kind']))
self.add_parameter(Choice('Colormap', 'cmap_selector',
'Red-Yellow-Blue', list(save_cmaps.keys())))
self.add_parameter(Choice('Coordinate system', 'coord_system',
'Lat/Lon', ['Lat/Lon', 'cartesian']))
self.add_parameter(Switch('Show stations', 'show_stations', False))
self.add_trigger('Save Figure', self.save_as)
self.set_live_update(False)
self.fig = None
self.cli_mode = False
def call(self):
'''Main work routine of the snuffling.'''
self.cleanup()
cmap = save_cmaps[self.cmap_selector]
viewer = self.get_viewer()
tmin, tmax = self.get_selected_time_range(fallback=True)
event_markers = filter(lambda x: x.tmin >= tmin and x.tmax <= tmax,
viewer.markers)
event_markers = filter(
lambda x: isinstance(x, EventMarker), event_markers)
if self.maxd:
event_markers = filter(
lambda x: distance(self, x._event) <= self.maxd*km,
event_markers)
if event_markers == []:
self.fail('No events in selected area found')
event_markers = list(event_markers)
stations = self.get_stations() if self.show_stations else None
self.make_time_line(event_markers, stations, cmap=cmap)
def make_time_line(self, markers, stations=None, cmap=cmap):
events = [m.get_event() for m in markers]
kinds = num.array([m.kind for m in markers])
if self.cli_mode:
self.fig = plt.figure()
else:
fframe = self.figure_frame()
self.fig = fframe.gcf()
ax = self.fig.add_subplot(311)
ax_cum = ax.twinx()
ax1 = self.fig.add_subplot(323)
ax2 = self.fig.add_subplot(325, sharex=ax1)
ax3 = self.fig.add_subplot(324, sharey=ax1)
num_events = len(events)
data = num.zeros((num_events, 6))
column_to_index = dict(zip(['magnitude', 'latitude', 'longitude', 'depth', 'time', 'kind'],
range(6)))
c2i = column_to_index
for i, e in enumerate(events):
if e.magnitude:
mag = e.magnitude
else:
mag = 0.
data[i, :] = mag, e.lat, e.lon, e.depth, e.time, kinds[i]
s_coords = num.array([])
s_labels = []
if stations is not None:
s_coords = num.array([(s.lon, s.lat, s.elevation-s.depth) for s in stations])
s_labels = ['.'.join(s.nsl()) for s in stations]
isorted = num.argsort(data[:, c2i['time']])
data = data[isorted]
def _D(key):
return data[:, c2i[key]]
tmin = _D('time').min()
tmax = _D('time').max()
lon_max = _D('longitude').max()
lon_min = _D('longitude').min()
lat_max = _D('latitude').max()
lat_min = _D('latitude').min()
depths_min = _D('depth').min()
depths_max = _D('depth').max()
mags_min = _D('magnitude').min()
mags_max = _D('magnitude').max()
moments = moment_tensor.magnitude_to_moment(_D('magnitude'))
dates = list(map(datetime.fromtimestamp, _D('time')))
fds = mdates.date2num(dates)
tday = 3600*24
tweek = tday*7
if tmax-tmin < 1*tday:
hfmt = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
elif tmax-tmin < tweek*52:
hfmt = mdates.DateFormatter('%Y-%m-%d')
else:
hfmt = mdates.DateFormatter('%Y/%m')
color_values = _D(self.color_by)
color_args = dict(c=color_values, vmin=color_values.min(),
vmax=color_values.max(), cmap=cmap)
ax.scatter(fds, _D('magnitude'), s=20, **color_args)
ax.xaxis.set_major_formatter(hfmt)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.set_ylim((mags_min, mags_max*1.10))
ax.set_xlim(map(datetime.fromtimestamp, (tmin, tmax)))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_ylabel('Magnitude')
init_pos = ax.get_position()
ax_cum.plot(fds, num.cumsum(moments), 'grey')
ax_cum.xaxis.set_major_formatter(hfmt)
ax_cum.spines['top'].set_color('none')
ax_cum.spines['right'].set_color('grey')
ax_cum.set_ylabel('Cumulative seismic moment')
lats_min = num.array([lat_min for x in range(num_events)])
lons_min = num.array([lon_min for x in range(num_events)])
if self.coord_system == 'cartesian':
lats, lons = orthodrome.latlon_to_ne_numpy(
lats_min, lons_min, _D('latitude'), _D('longitude'))
_x = num.empty((len(s_coords), 3))
for i, (slon, slat, sele) in enumerate(s_coords):
n, e = orthodrome.latlon_to_ne(lat_min, lon_min, slat, slon)
_x[i, :] = (e, n, sele)
s_coords = _x
else:
lats = _D('latitude')
lons = _D('longitude')
s_coords = s_coords.T
ax1.scatter(lons, lats, s=20, **color_args)
ax1.set_aspect('equal')
ax1.grid(True, which='both')
ax1.set_ylabel('Northing [m]')
ax1.get_yaxis().tick_left()
if len(s_coords):
ax1.scatter(s_coords[0], s_coords[1], marker='v', s=40, color='black')
for c, sl in zip(s_coords.T, s_labels):
ax1.text(c[0], c[1], sl, color='black')
# bottom left plot
ax2.scatter(lons, _D('depth'), s=20, **color_args)
ax2.grid(True)
ax2.set_xlabel('Easting [m]')
ax2.set_ylabel('Depth [m]')
ax2.get_yaxis().tick_left()
ax2.get_xaxis().tick_bottom()
ax2.invert_yaxis()
ax2.text(1.1, 0, 'Origin at:\nlat=%1.3f, lon=%1.3f' %
(lat_min, lon_min), transform=ax2.transAxes)
# top right plot
ax3.scatter(_D('depth'), lats, s=20, **color_args)
ax3.set_xlim((depths_min, depths_max))
ax3.grid(True)
ax3.set_xlabel('Depth [m]')
ax3.get_xaxis().tick_bottom()
ax3.get_yaxis().tick_right()
self.fig.subplots_adjust(
bottom=0.05, right=0.95, left=0.075, top=0.95, wspace=0.02, hspace=0.02)
init_pos.y0 += 0.05
ax.set_position(init_pos)
ax_cum.set_position(init_pos)
if self.cli_mode:
plt.show()
else:
self.fig.canvas.draw()
def save_as(self):
if self.fig:
fn = self.output_filename()
self.fig.savefig(fn,
pad_inches=0.05,
bbox_inches='tight')
def configure_cli_parser(self, parser):
parser.add_option(
'--events',
dest='events_filename',
default=None,
metavar='FILENAME',
help='Read events from FILENAME')
def __snufflings__():
'''Returns a list of snufflings to be exported by this module.'''
return [TimeLine()]
if __name__ == '__main__':
import matplotlib.pyplot as plt
util.setup_logging('time_line.py', 'info')
s = TimeLine()
options, args, parser = s.setup_cli()
s.cli_mode = True
if options.events_filename:
s.make_time_line(
list(model.Event.load_catalog(options.events_filename)))