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

import numpy as num 

import logging 

 

from pyrocko import gf, util 

from pyrocko.guts import String, Float, Dict, StringChoice, Int 

 

from grond.meta import Forbidden, expand_template, Parameter, \ 

has_get_plot_classes 

 

from ..base import Problem, ProblemConfig 

 

guts_prefix = 'grond' 

logger = logging.getLogger('grond.problems.double_sf.problem') 

km = 1e3 

as_km = dict(scale_factor=km, scale_unit='km') 

 

 

class DoubleSFProblemConfig(ProblemConfig): 

 

ranges = Dict.T(String.T(), gf.Range.T()) 

distance_min = Float.T(default=0.0) 

nthreads = Int.T(default=1) 

force_directions = StringChoice.T( 

choices=('off', 'unidirectional', 'counterdirectional'), 

default='off') 

 

def get_problem(self, event, target_groups, targets): 

if event.depth is None: 

event.depth = 0. 

 

base_source = gf.DoubleSFSource.from_pyrocko_event(event) 

 

base_source.stf1 = gf.HalfSinusoidSTF(duration=event.duration or 0.0) 

base_source.stf2 = gf.HalfSinusoidSTF(duration=event.duration or 0.0) 

 

subs = dict( 

event_name=event.name, 

event_time=util.time_to_str(event.time)) 

 

problem = DoubleSFProblem( 

name=expand_template(self.name_template, subs), 

base_source=base_source, 

target_groups=target_groups, 

targets=targets, 

ranges=self.ranges, 

distance_min=self.distance_min, 

norm_exponent=self.norm_exponent, 

nthreads=self.nthreads, 

force_directions=self.force_directions) 

 

return problem 

 

 

@has_get_plot_classes 

class DoubleSFProblem(Problem): 

 

problem_parameters = [ 

Parameter('time', 's', label='Time'), 

Parameter('north_shift', 'm', label='Northing', **as_km), 

Parameter('east_shift', 'm', label='Easting', **as_km), 

Parameter('depth', 'm', label='Depth', **as_km), 

Parameter('force', 'N', label='$||F||$'), 

Parameter('rfn1', '', label='$rF_{n1}$'), 

Parameter('rfe1', '', label='$rF_{e1}$'), 

Parameter('rfd1', '', label='$rF_{d1}$'), 

Parameter('rfn2', '', label='$rF_{n2}$'), 

Parameter('rfe2', '', label='$rF_{e2}$'), 

Parameter('rfd2', '', label='$rF_{d2}$'), 

Parameter('delta_time', 's', label='$\\Delta$ Time'), 

Parameter('delta_depth', 'm', label='$\\Delta$ Depth'), 

Parameter('azimuth', 'deg', label='Azimuth'), 

Parameter('distance', 'm', label='Distance'), 

Parameter('mix', label='Mix'), 

Parameter('duration1', 's', label='Duration 1'), 

Parameter('duration2', 's', label='Duration 2')] 

 

dependants = [] 

 

distance_min = Float.T(default=0.0) 

force_directions = String.T() 

 

def get_source(self, x): 

d = self.get_parameter_dict(x) 

 

p = {} 

for k in self.base_source.keys(): 

if k in d: 

p[k] = float( 

self.ranges[k].make_relative(self.base_source[k], d[k])) 

 

stf1 = gf.HalfSinusoidSTF(duration=float(d.duration1)) 

stf2 = gf.HalfSinusoidSTF(duration=float(d.duration2)) 

 

source = self.base_source.clone(stf1=stf1, stf2=stf2, **p) 

return source 

 

def make_dependant(self, xs, pname): 

pass 

 

def pack(self, source): 

arr = self.get_parameter_array(source) 

for ip, p in enumerate(self.parameters): 

if p.name == 'time': 

arr[ip] -= self.base_source.time 

if p.name == 'duration1': 

arr[ip] = source.stf1.duration if source.stf1 else 0.0 

if p.name == 'duration2': 

arr[ip] = source.stf2.duration if source.stf2 else 0.0 

return arr 

 

def random_uniform(self, xbounds, rstate, fixed_magnitude=None): 

 

x = num.zeros(self.nparameters) 

for i in range(self.nparameters): 

x[i] = rstate.uniform(xbounds[i, 0], xbounds[i, 1]) 

 

return x.tolist() 

 

def preconstrain(self, x): 

source = self.get_source(x) 

if any(self.distance_min > source.distance_to(t) 

for t in self.targets): 

raise Forbidden() 

 

if self.force_directions == 'unidirectional': 

idx_rfn2 = self.get_parameter_index('rfn2') 

idx_rfe2 = self.get_parameter_index('rfe2') 

idx_rfd2 = self.get_parameter_index('rfd2') 

 

x[idx_rfn2] = source.rfn1 

x[idx_rfe2] = source.rfe1 

x[idx_rfd2] = source.rfd1 

 

elif self.force_directions == 'counterdirectional': 

idx_rfn2 = self.get_parameter_index('rfn2') 

idx_rfe2 = self.get_parameter_index('rfe2') 

idx_rfd2 = self.get_parameter_index('rfd2') 

 

x[idx_rfn2] = -source.rfn1 

x[idx_rfe2] = -source.rfe1 

x[idx_rfd2] = -source.rfd1 

 

return num.array(x, dtype=num.float) 

 

@classmethod 

def get_plot_classes(cls): 

from . import plot 

from ..singleforce import plot as sfplot 

plots = super(DoubleSFProblem, cls).get_plot_classes() 

plots.extend([sfplot.SFLocationPlot, plot.SFForcePlot]) 

return plots 

 

 

__all__ = ''' 

DoubleSFProblem 

DoubleSFProblemConfig 

'''.split()