sBlot is a Python library for visualising the results of a sBayes analysis. It provides static plots (weights, preferences per component, pie charts, maps and LOO model comparison) as well as an interactive browser-based explorer for inspecting posterior samples.
For detailed instructions on configuration and individual plot types, see the documentation.
Install the latest release from PyPI:
pip install sblot
To include the interactive explorer:
pip install sblot[interactive]
To include LOO model comparison plots:
pip install sblot[loo]
To install all optional dependencies:
pip install sblot[all]
To install the development version directly from GitHub:
pip install git+https://github.com/derpetermann/sBlot.git
Generate all plots specified in config_plot.yaml:
sblot -c config_plot.yaml
To use a custom style configuration:
sblot -c config_plot.yaml -s config_style.yaml
To initialise a new experiment directory with example configuration files:
sblot --init my_experiment/
from sblot.config.config_io import load_config, read_data, read_results
from sblot.plots.weights import plot_weights_grid
from sblot.plots.preferences import plot_preferences_grid
from sblot.plots.pies import plot_pies
from sblot.plots.map import plot_maps
from sblot.plots.loo import plot_loo
config = load_config("config_plot.yaml", "config_style.yaml")
data = read_data(config)
all_models = list(read_results(config))
for model in all_models:
plot_weights(model.results, config)
plot_preferences(model.results, config)
plot_pies(model.results, data, config)
plot_maps(model.results, data, config)
plot_loo(all_models, config)
In the command line:
sblot-interactive --conf family -d data/features.csv
Then open the interactive map in your browser at the address shown in the command line.
sBlot is released under the GNU General Public License v3.