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__init__(self,
K,
model,
inits,
tf,
thetanames,
phinames,
wl=None,
nw=1,
verbose=False,
burnin=1000,
constraints=[])
Initialize the model fitter. |
source code
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_plot_MAP(self,
data,
pmap)
Generates a plot of a full run of the model parameterized with the maximum a posteriori
estimates of the parameters. |
source code
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AIC_from_RSS(self)
Calculates the Akaike information criterion from the residual sum of squares
of the best fitting run. |
source code
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optimize(self,
data,
p0,
optimizer='scipy',
tol=0.0001,
verbose=0,
plot=0)
Finds best parameters using an optimization approach |
source code
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_rms_error(self,
s1,
s2)
Calculates a the error between a model-
generated time series and a observed time series.
It uses a normalized RMS deviation. |
source code
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set_priors(self,
tdists,
tpars,
tlims,
pdists,
ppars,
plims)
Set the prior distributions for Phi and Theta |
source code
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prior_sample(self)
Generates a set of sample from the starting theta prior distributions
for reporting purposes. |
source code
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_init_priors(self,
prior=None)
Initialize priors either from distributions or previous posteriors |
source code
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do_inference(self,
prior,
data,
predlen,
method,
likvar) |
source code
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run(self,
data,
method,
likvar,
pool=False,
adjinits=True,
ew=0,
dbname='results',
monitor=False,
initheta=[])
Fit the model against data |
source code
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_format_db_tables(self,
dbname,
w,
data,
pt,
series,
predseries,
AIC,
BIC,
DIC)
Formats results for writing to database |
source code
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_monitor_setup(self)
Sets up realtime plotting for inference |
source code
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plot_results(self,
names=[],
dbname="results",
savefigs=0)
Plot the final results of the inference |
source code
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_read_results(self,
nam)
read results from disk |
source code
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Inherited from object :
__delattr__ ,
__format__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__sizeof__ ,
__str__ ,
__subclasshook__
|