plot_heatmap_v1¶
The module plots a 2-dimensional output as a heatmap.
Positional arguments
plot– define list of observables to be plotted
Options
-l, --log– use a log scale (not to use with ‘sym-log’ option)
--sym-log– use a log scale and define linear interval around zero (not to use with ‘l’/’log’ option)
-f, --filter– define list of filters to filter the matrix
choices: triu, tril, diag, corr, llt
--plot-kwargs– all additional plotting options go here. They are applied for all plots
Filters
triu– returns upper triangular of the matrix, lower is set to zero
tril– returns lower triangular of the matrix, upper is set to zero
diag– returns only diagonal of the matrix, all other values are set to zero
corr– returns the correlation matrix
llt– returns matrix multiplied by its transposed
Example
Plot a lower triangular matrix L — the Cholesky decomposition of the covariance matrix:
./gna \ -- gaussianpeak --name peak_MC --nbins 50 \ -- gaussianpeak --name peak_f --nbins 50 \ -- ns --name peak_MC --print \ --set E0 values=2 fixed \ --set Width values=0.5 fixed \ --set Mu values=2000 fixed \ --set BackgroundRate values=1000 fixed \ -- ns --name peak_f --print \ --set E0 values=2.5 relsigma=0.2 \ --set Width values=0.3 relsigma=0.2 \ --set Mu values=1500 relsigma=0.25 \ --set BackgroundRate values=1100 relsigma=0.25 \ -- pargroup minpars peak_f -vv -m free \ -- pargroup covpars peak_f -vv -m constrained \ -- dataset-v1 peak --theory-data peak_f.spectrum peak_MC.spectrum -vv \ -- analysis-v1 peak --datasets peak -p covpars -v \ -- env-print analysis \ -- plot-heatmap-v1 analysis.peak.0.L -f tril \ -- mpl-v1 --xlabel columns --ylabel rows -t 'Cholesky decomposition, L' -s
Here the filter ‘tril’ provided via -f ensures that only the lower triangular is plotted since it is not guaranteed that the upper matrix is reset to zero.
For more details on decorations and saving see mpl-v1.
See also: mpl_v1, plot_spectrum_v1.