Get Started
conda
apt
pip
feCSEP
Example Experiments
Defining an Experiment
Deploying an Experiment
Help & Reference
run()
plot()
reproduce()
Experiment
Experiment.set_models()
Experiment.get_model()
Experiment.stage_models()
Experiment.set_tests()
Experiment.catalog
Experiment.set_test_cat()
Experiment.set_tasks()
Experiment.run()
Experiment.read_results()
Experiment.plot_results()
Experiment.plot_catalog()
Experiment.plot_forecasts()
Experiment.generate_report()
Experiment.to_yml()
Experiment.from_yml()
Model
Model.get_source()
Model.stage()
Model.init_db()
Model.rm_db()
Model.get_forecast()
Model.create_forecast()
Model.forecast_from_func()
Model.forecast_from_file()
Model.from_dict()
Evaluation
Evaluation.type
Evaluation.get_catalog()
Evaluation.prepare_args()
Evaluation.compute()
Evaluation.write_result()
Evaluation.from_dict()
query_gcmt()
from_zenodo()
from_git()
sequential_likelihood()
sequential_information_gain()
vector_poisson_t_w_test()
brier_score()
negative_binomial_number_test()
binomial_joint_log_likelihood_ndarray()
binomial_spatial_test()
binomial_conditional_likelihood_test()
binary_paired_t_test()
log_likelihood_point_process()
paired_ttest_point_process()
parse_csep_func()
parse_timedelta_string()
timewindows_ti()
timewindows_td()
Task
Task.run()
Task.check_exist()
timewindow2str()
plot_sequential_likelihood()
magnitude_vs_time()
ForecastParsers.dat()
ForecastParsers.xml()
ForecastParsers.quadtree()
ForecastParsers.csv()
ForecastParsers.hdf5()
HDF5Serializer.grid2hdf5()
serialize()
Log-likelihood for point process