[model]
name = single_template

#; This model precalculates the SNR time series at a fixed rate.
#; If you need a higher time resolution, this may be increased
sample_rate = 32768
low-frequency-cutoff = 30.0

[data]
instruments = H1 L1 V1
analysis-start-time = 1187008482
analysis-end-time = 1187008892
psd-estimation = median
psd-segment-length = 16
psd-segment-stride = 8
psd-inverse-length = 16
pad-data = 8
channel-name = H1:LOSC-STRAIN L1:LOSC-STRAIN V1:LOSC-STRAIN
frame-files = H1:H-H1_LOSC_CLN_4_V1-1187007040-2048.gwf L1:L-L1_LOSC_CLN_4_V1-1187007040-2048.gwf V1:V-V1_LOSC_CLN_4_V1-1187007040-2048.gwf
strain-high-pass = 15
sample-rate = 2048

[sampler]
name = dynesty
sample = rwalk
bound = multi
dlogz = 0.1
nlive = 200
checkpoint_time_interval = 100
maxcall = 10000

[variable_params]
; waveform parameters that will vary in MCMC
tc =
distance =
inclination =

[static_params]
; waveform parameters that will not change in MCMC
approximant = TaylorF2
f_lower = 30
mass1 = 1.3757
mass2 = 1.3757

#; we'll choose not to sample over these, but you could
polarization = 0
ra = 3.44615914
dec = -0.40808407

#; You could also set additional parameters if your waveform model supports / requires it.
; spin1z = 0

[prior-tc]
; coalescence time prior
name = uniform
min-tc = 1187008882.4
max-tc = 1187008882.5

[prior-distance]
#; following gives a uniform in volume
name = uniform_radius
min-distance = 10
max-distance = 60

[prior-inclination]
name = sin_angle