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Commit 8e68e4a6 authored by Gregory Ashton's avatar Gregory Ashton

Improve the documentation for get_optimal_setup_functions

Closes # 72
parent d8571a7d
......@@ -18,17 +18,28 @@ def get_optimal_setup(
):
""" Using an optimisation step, calculate the optimal setup ladder
The details of the methods are described in Sec Va of arXiv:1802.05450.
Here we provide implementation details. All equation numbers refer to
arXiv:1802.05450.
Parameters
----------
NstarMax : float
The ratio of the size at the old coherence time to the new coherence
time for each step, see Eq. (31). Larger values allow a more rapid
"zoom" of the search space at the cost of convergence. Smaller values
are more conservative at the cost of additional computing time. The
exact choice should be optimized for the problem in hand, but values
of 100-1000 are typically okay.
Nsegs0 : int
The number of segments for the initial step of the ladder
minStartTime, maxStartTime : int
GPS times of the start and end time of the search
tref, minStartTime, maxStartTime : int
GPS times of the reference, start, and end time.
prior : dict
Prior dictionary, each item must either be a fixed scalar value, or
a uniform prior.
detector_names : list of str
detector_names : list or str
Names of the detectors to use
Returns
-------
......@@ -66,7 +77,29 @@ def get_optimal_setup(
def _get_nsegs_ip1(
nsegs_i, NstarMax, tref, minStartTime, maxStartTime, prior, detector_names
):
""" Calculate Nsegs_{i+1} given Nsegs_{i} """
""" Calculate Nsegs_{i+1} given Nsegs_{i}
Perform the optimization step to calculate nsegs and i+1 given the setup
and i. The "Powell" minimiization method from scipy is used. Below, we give
help for parameters unique to _get_nsegs_ip1, for help with other
parameters see get_optimal_setup
Parameters
----------
nsegs_i: int
The number of segments at step i
Returns
-------
nsegs_ip1: int
The number of segments at i + 1
Raises
------
ValueError: Optimisation unsuccesful
A value error is raised if the optimization step fails
"""
log10NstarMax = np.log10(NstarMax)
log10Nstari = np.log10(
......
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