dynast.benchmarking.simulation

Module Contents

Functions

generate_sequence(k, seed=None)

simulate_reads(sequence, p_e, p_c, pi, l=100, n=100, seed=None)

initializer(model)

estimate(df_counts, p_e, p_c, pi, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, model=None, nasc=False)

_simulate(p_e, p_c, pi, sequence=None, k=10000, l=100, n=100, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, seed=None, model=None, nasc=False)

simulate(p_e, p_c, pi, sequence=None, k=10000, l=100, n=100, n_runs=16, n_threads=8, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, model=None, nasc=False)

simulate_batch(p_e, p_c, pi, l, n, estimate_p_e, estimate_p_c, estimate_pi, n_runs, n_threads, model, nasc=False)

Helper function to run simulations in batches.

plot_estimations(X, Y, n_runs, means, truth, ax=None, box=True, tick_decimals=1, title=None, xlabel=None, ylabel=None)

Attributes

__model

_pi_model

dynast.benchmarking.simulation.generate_sequence(k, seed=None)[source]
dynast.benchmarking.simulation.simulate_reads(sequence, p_e, p_c, pi, l=100, n=100, seed=None)[source]
dynast.benchmarking.simulation.__model[source]
dynast.benchmarking.simulation._pi_model[source]
dynast.benchmarking.simulation.initializer(model)[source]
dynast.benchmarking.simulation.estimate(df_counts, p_e, p_c, pi, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, model=None, nasc=False)[source]
dynast.benchmarking.simulation._simulate(p_e, p_c, pi, sequence=None, k=10000, l=100, n=100, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, seed=None, model=None, nasc=False)[source]
dynast.benchmarking.simulation.simulate(p_e, p_c, pi, sequence=None, k=10000, l=100, n=100, n_runs=16, n_threads=8, estimate_p_e=False, estimate_p_c=False, estimate_pi=True, model=None, nasc=False)[source]
dynast.benchmarking.simulation.simulate_batch(p_e, p_c, pi, l, n, estimate_p_e, estimate_p_c, estimate_pi, n_runs, n_threads, model, nasc=False)[source]

Helper function to run simulations in batches.

dynast.benchmarking.simulation.plot_estimations(X, Y, n_runs, means, truth, ax=None, box=True, tick_decimals=1, title=None, xlabel=None, ylabel=None)[source]