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Update plots #76

Merged
merged 17 commits into from
May 25, 2021
Merged

Update plots #76

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a7d1e46
update magnetization series with rows
jmarshrossney May 17, 2021
f1ef447
split correlator and error into two figures
jmarshrossney May 17, 2021
738cad1
plot with multiple estimates of correlation length
jmarshrossney May 17, 2021
dad6a8a
bootstrap the cosh fit
jmarshrossney May 20, 2021
1eaac3e
standardise table row/col names
jmarshrossney May 20, 2021
8f582c6
update report.md to include new plots
jmarshrossney May 20, 2021
9c4ce28
minor adjustment to autocorrelation plot
jmarshrossney May 20, 2021
30ba442
add docstrings to plot actions, remove plots due to be superseded
jmarshrossney May 20, 2021
c530e0b
raw strings to get rid of pytest warnings
jmarshrossney May 20, 2021
7504922
minor change to counting number of successful cosh fits
jmarshrossney May 20, 2021
7bb45a8
remove default cosh_fit_window in plot.py
jmarshrossney May 20, 2021
c0a1df8
option to plot cosh fit overlay, add docstrings
jmarshrossney May 20, 2021
691a282
minor typos in docstring
jmarshrossney May 20, 2021
a185078
update plot docstrings
jmarshrossney May 24, 2021
64ea16e
update table docstrings, minor alterations to plot docstrings
jmarshrossney May 24, 2021
35536e4
indicate that bootstrap dim is assumed to be last
jmarshrossney May 24, 2021
0980f87
docstrings need to be raw strings
jmarshrossney May 24, 2021
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15 changes: 7 additions & 8 deletions anvil/observables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,14 +38,13 @@ def fit_zero_momentum_correlator(
pass

n_boot = zero_momentum_correlator.shape[-1]
failures = n_boot - len(optimised_parameters)
if failures > 0:
log.warning(
f"Failed to fit cosh to correlation function for {failures}/{n_boot} members of the bootstrap ensemble."
)
if failures >= n_boot - 1:
log.warning("Too many failures: no fit parameters will be returned.")
return None
n_fits = len(optimised_parameters)
log.info(
f"Cosh fit succeeded for {n_fits}/{n_boot} members of the bootstrap ensemble."
)
if n_fits < 2:
log.warning("Too few successful fits: no fit parameters will be returned.")
return None
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xi, A, c = np.array(optimised_parameters).transpose()
return xi, A, c
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