burstH2MM documentation#
burstH2MM is designed to make analyzing single molecule burst experiments with H2MM easy. burstH2MM is built to work with FRETBursts, on which it depends for burst search and selection. burstH2MM serves to organize and process the results of H2MM optimizations and access the results of Viterbi analysis, which assigns each photon a state, and further processing segments the data into dwells.
Installation#
To install burstH2MM simply type
pip install burstH2MM
into your terminal window. Python 3.8 or greater is required.
Please Cite#
H2MM was originally introduced by Pirchi and Tsukanov et. al. 2016 and this implementation is built on the extension introduced in Harris et. al. 2022. If you use this library in a publication, please make sure to cite both these papers.
Contents#
Contents:
- Tutorial
- Divisor Approach
- How To Guides
- Discussion
- Documentation
- BurstSort
BurstDataH2MM_listH2MM_resultcalc_dwell_nanomean()calc_nanohist()find_ideal()make_divisors()trans_stats()- Plotting
BIC_plot()BICp_plot()ICL_plot()axline_E()axline_S()axline_divs()axline_irf_thresh()axline_nano_mean()burst_ES_scatter()covar_E_ll_scatter()covar_S_ll_scatter()covar_param_ll_scatter()covar_trans_ll_scatter()dwell_ES_scatter()dwell_E_hist()dwell_E_tau_scatter()dwell_S_hist()dwell_dur_hist()dwell_param_hist()dwell_param_transition()dwell_param_transition_kde_plot()dwell_params_scatter()dwell_tau_hist()dwell_trans_dur_hist()ll_E_scatter()ll_S_scatter()ll_param_scatter()ll_trans_scatter()path_BIC_plot()plot_burst_index()plot_burst_path()plot_burstjoin()raw_nanotime_hist()scatter_ES()state_nanotime_hist()trans_arrow_ES()- Selections
begin_dwell()burst_begin_dwell()burst_dwell()burst_end_dwell()dwell_size()dwell_trans()dwell_trans_from()edge_dwell()end_dwell()mid_dwell()not_mid_dwell()- Uncertainties
Bootstrap_ErrorE_space()Loglik_ErrorModelSetS_space()covar_E()covar_S()covar_trans()err_E_search()err_S_search()err_param_search()err_trans_search()trans_space_ll()- Simulations
Sim_Resultsimulate()
- Examples of Full Data Analysis
Indices and tables#
Thank you for using H2MM