From aebc82d7646f39a8600dc4b572b056c64ee6e6f9 Mon Sep 17 00:00:00 2001 From: LaraFuhrmann <55209716+LaraFuhrmann@users.noreply.github.com> Date: Tue, 3 Dec 2024 16:23:00 +0100 Subject: [PATCH] Run e2e-tests in separate dir + reuse_files + record_history (#41) * b2w and inference: rerun windows that failed + check if window was processed already before adding process to process list * reference to manuscript * restarting failed process doesn't work, exit again * fix: check if files already exist * add minimum number of iterations * pass unique_modus argument * Revert "Merge pull request #38 from cbg-ethz/enable-unique-modus" This reverts commit ffd4fd13575b9412fda3d689e5b3b588dc1587ef, reversing changes made to 279cc634a5d7856b9b280aef5b29a7b647d97407. * rebase to master * reference to manuscript * restarting failed process doesn't work, exit again * add minimum number of iterations * pass unique_modus argument * Revert "Merge pull request #38 from cbg-ethz/enable-unique-modus" This reverts commit ffd4fd13575b9412fda3d689e5b3b588dc1587ef, reversing changes made to 279cc634a5d7856b9b280aef5b29a7b647d97407. * update readme * no poerty lock flie * add param record_history * add command line params: reuse_files + record_history * pass record_history + implement reuse_files * implemnt reuse_files * typo * add param record_history * fix syntax * [fix[ unexpected keyword argument 'metavar' * fix ctime * add pathlib package * fix the pathlib import * fix: too many argmuments to unpack * fix params to unpack * [e2e tests] run the e2e tests in seperate directories * partially addresses #40 * enable unique_modus --- Dockerfile | 4 +- poetry.lock | 743 ------------------ tests/data_1/shotgun_test.sh | 2 +- tests/test_shotgun_e2e.py | 17 +- viloca/b2w.py | 10 +- viloca/cli.py | 7 + .../learn_error_params/cavi.py | 81 +- .../learn_error_params/run_dpm_mfa.py | 16 +- .../use_quality_scores/cavi.py | 66 +- .../use_quality_scores/run_dpm_mfa.py | 28 +- viloca/shotgun.py | 119 +-- 11 files changed, 198 insertions(+), 895 deletions(-) delete mode 100644 poetry.lock diff --git a/Dockerfile b/Dockerfile index ada3b21..9c1c09c 100644 --- a/Dockerfile +++ b/Dockerfile @@ -11,7 +11,7 @@ RUN apt-get update -y && \ RUN pip install "poetry==$POETRY_VERSION" -COPY pyproject.toml poetry.lock /usr/app/ +COPY pyproject.toml /usr/app/ # https://stackoverflow.com/questions/53835198/integrating-python-poetry-with-docker RUN cd /usr/app && poetry install --no-interaction --no-ansi --no-root @@ -19,4 +19,4 @@ RUN cd /usr/app && poetry install --no-interaction --no-ansi --no-root # GitHub Actions chimes in here and sets docker's WORKDIR=${GITHUB_WORKSPACE} # https://docs.github.com/en/actions/creating-actions/dockerfile-support-for-github-actions#workdir # poetry install --only-root would be more elegant but does not work in Github Actions -CMD poetry install --no-interaction --no-ansi && cd ./tests && poetry run pytest \ No newline at end of file +CMD poetry install --no-interaction --no-ansi && cd ./tests && poetry run pytest diff --git a/poetry.lock b/poetry.lock deleted file mode 100644 index 5aa4b8b..0000000 --- a/poetry.lock +++ /dev/null @@ -1,743 +0,0 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. - 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"./shotgun_test.sh", shell=True, check=True, cwd=cwd + "../shotgun_test.sh", shell=True, check=True, cwd=cwd_test_e2e ) assert original.returncode == 0 assert os.path.isfile(os.path.join(cwd, f_path)) == False assert filecmp.cmp( "./data_1/test.csv", - "./data_1/work/snv/SNVs_0.010000_final.csv", + "./data_1/test_e2e_shorah/work/snv/SNVs_0.010000_final.csv", shallow=False ) def test_e2e_shorah_with_extended_window_mode(): + cwd_test_e2e_extended_window_mode = "./data_1/test_e2e_extended_window_modee" + # Check if the directory exists, if not, create it + if not os.path.exists(cwd_test_e2e_extended_window_mode): + os.makedirs(cwd_test_e2e_extended_window_mode) p = subprocess.run( - "./shotgun_test.sh --extended_window_mode", shell=True, check=True, cwd=cwd + "../shotgun_test.sh --extended_window_mode", shell=True, check=True, cwd=cwd_test_e2e_extended_window_mode ) assert p.returncode == 0 - assert os.path.isfile(os.path.join(cwd, f_path)) == True + assert os.path.isfile(os.path.join(cwd_test_e2e_extended_window_mode, f_path)) == True diff --git a/viloca/b2w.py b/viloca/b2w.py index 3536710..6024bbc 100644 --- a/viloca/b2w.py +++ b/viloca/b2w.py @@ -7,6 +7,7 @@ from multiprocessing import Process, cpu_count import os import hashlib +from pathlib import Path def _write_to_file(lines, file_name): with open(file_name, "w") as f: @@ -340,7 +341,7 @@ def parallel_run_one_window( indel_map, max_ins_at_pos, extended_window_mode, - exclude_non_var_pos_threshold + exclude_non_var_pos_threshold, ): """ build one window. @@ -510,7 +511,8 @@ def build_windows(alignment_file: str, tiling_strategy: TilingStrategy, exact_conformance_fix_0_1_basing_in_reads: Optional[bool] = False, extended_window_mode: Optional[bool] = False, exclude_non_var_pos_threshold: Optional[float] = -1, - maxthreads: Optional[int] = 1) -> None: + maxthreads: Optional[int] = 1, + reuse_files = False) -> None: """Summarizes reads aligned to reference into windows. Three products are created: #. Multiple FASTA files (one for each window position) @@ -580,7 +582,7 @@ def build_windows(alignment_file: str, tiling_strategy: TilingStrategy, all_processes = [] for idx, (window_start, window_length, control_window_length) in enumerate(tiling): counter = counter_list[idx] - if not os.path.isfile(f"coverage_{idx}.txt"): + if not (reuse_files and os.path.isfile(f"coverage_{idx}.txt")): p = Process( target=parallel_run_one_window, args=( @@ -605,6 +607,8 @@ def build_windows(alignment_file: str, tiling_strategy: TilingStrategy, ) ) all_processes.append(p) + else: + logging.info(f'[file already exits] Use window files generated on {time.ctime(Path(f"coverage_{idx}.txt").stat().st_mtime)}') for p in all_processes: p.start() diff --git a/viloca/cli.py b/viloca/cli.py index 024a62a..8cad5cd 100644 --- a/viloca/cli.py +++ b/viloca/cli.py @@ -200,6 +200,13 @@ def main(): parser_shotgun.add_argument('--exclude_non_var_pos_threshold', metavar='FLOAT', type=float, dest="exclude_non_var_pos_threshold", default=-1, help="Runs exclude non-variable positions mode. Set percentage threshold for exclusion.") + + parser_shotgun.add_argument('--reuse_files', action='store_true', dest="reuse_files", + default=-1, help="Enabling this option allows the command line tool to reuse files that were generated in previous runs. When set to true, the tool will check for existing output files and reuse them instead of regenerating the data. This can help improve performance by avoiding redundant file generation processes.") + + parser_shotgun.add_argument('--record_history', action='store_true', dest="record_history", + default=-1, help="When enabled, this option saves the history of the parameter values learned during the inference process.") + parser_shotgun.add_argument("--min_windows_coverage", metavar='INT', type=int, required=False, default=2, dest="min_windows_coverage", help="Number of windows that need to cover a mutation to have it called.") diff --git a/viloca/local_haplotype_inference/learn_error_params/cavi.py b/viloca/local_haplotype_inference/learn_error_params/cavi.py index a88036a..d0aec73 100644 --- a/viloca/local_haplotype_inference/learn_error_params/cavi.py +++ b/viloca/local_haplotype_inference/learn_error_params/cavi.py @@ -34,6 +34,7 @@ def multistart_cavi( reads_weights, n_starts, output_dir, + record_history ): pool = mp.Pool(mp.cpu_count()) @@ -51,6 +52,7 @@ def multistart_cavi( reads_weights, start, output_dir, + record_history ), callback=collect_result, ) @@ -72,6 +74,7 @@ def run_cavi( reads_weights, start_id, output_dir, + record_history ): """ @@ -85,16 +88,7 @@ def run_cavi( "alphabet": alphabet, } # N= #reads, K= #components - history_alpha = [] - history_mean_log_pi = [] - history_theta_c = [] - history_theta_d = [] - history_mean_log_theta = [] - history_gamma_a = [] - history_gamma_b = [] - history_mean_log_gamma = [] - history_mean_haplo = [] - history_mean_cluster = [] + history_elbo = [] state_init_dict = initialization.draw_init_state( @@ -130,8 +124,8 @@ def run_cavi( converged = False elbo = 0 state_curr_dict = state_init_dict - k = 0 - while converged is False: + min_number_iterations = 10 + while (converged is False) or (iter < min_number_iterations): if iter <= 1: digamma_alpha_sum = digamma(state_curr_dict["alpha"].sum(axis=0)) @@ -160,7 +154,7 @@ def run_cavi( state_init_dict, state_curr_dict, ) - + if iter % 2 == 0: history_elbo.append(elbo) history_mean_log_pi.append(state_curr_dict["mean_log_pi"]) @@ -184,11 +178,11 @@ def run_cavi( break elif np.abs(elbo - history_elbo[-2]) < 1e-03: converged = True - k += 1 + iter += 1 message = "ELBO converged." exitflag = 0 else: - k = 0 + iter = 0 # if k%10==0: # every 10th parameter set is saved to history state_curr_dict.update({"elbo": elbo}) @@ -198,28 +192,41 @@ def run_cavi( state_curr_dict.update({"elbo": elbo}) - dict_result.update( - { - "exit_message": message, - "exitflag": exitflag, - "n_iterations": iter, - "converged": converged, - "elbo": elbo, - "history_mean_log_theta": history_mean_log_theta, - "history_elbo": history_elbo, - "history_alpha": history_alpha, - "history_mean_log_pi": history_mean_log_pi, - "history_theta_c": history_theta_c, - "history_alpha": history_alpha, - "history_theta_d": history_theta_d, - "history_mean_log_theta": history_mean_log_theta, - "history_gamma_a": history_gamma_a, - "history_gamma_b": history_gamma_b, - "history_mean_log_gamma": history_mean_log_gamma, - "history_mean_haplo": history_mean_haplo, - "history_mean_cluster": history_mean_cluster, - } - ) + if record_history: + dict_result.update( + { + "exit_message": message, + "exitflag": exitflag, + "n_iterations": iter, + "converged": converged, + "elbo": elbo, + "history_mean_log_theta": history_mean_log_theta, + "history_elbo": history_elbo, + "history_alpha": history_alpha, + "history_mean_log_pi": history_mean_log_pi, + "history_theta_c": history_theta_c, + "history_alpha": history_alpha, + "history_theta_d": history_theta_d, + "history_mean_log_theta": history_mean_log_theta, + "history_gamma_a": history_gamma_a, + "history_gamma_b": history_gamma_b, + "history_mean_log_gamma": history_mean_log_gamma, + "history_mean_haplo": history_mean_haplo, + "history_mean_cluster": history_mean_cluster, + } + ) + else: + dict_result.update( + { + "exit_message": message, + "exitflag": exitflag, + "n_iterations": iter, + "converged": converged, + "elbo": elbo, + "history_elbo": history_elbo, + } + ) + # dict_result.update(state_curr_dict) summary = analyze_results.summarize_results( diff --git a/viloca/local_haplotype_inference/learn_error_params/run_dpm_mfa.py b/viloca/local_haplotype_inference/learn_error_params/run_dpm_mfa.py index eabb610..aff6f3e 100644 --- a/viloca/local_haplotype_inference/learn_error_params/run_dpm_mfa.py +++ b/viloca/local_haplotype_inference/learn_error_params/run_dpm_mfa.py @@ -29,7 +29,7 @@ def gzip_file(f_name): return f_out.name -def main(freads_in, fref_in, output_dir, n_starts, K, alpha0, alphabet="ACGT-", unique_modus=False): +def main(freads_in, fref_in, output_dir, n_starts, K, alpha0, alphabet="ACGT-", unique_modus=True, record_history=False): window_id = freads_in.split("/")[-1][:-4] # freads_in is absolute path @@ -39,7 +39,7 @@ def main(freads_in, fref_in, output_dir, n_starts, K, alpha0, alphabet="ACGT-", # Read in reads reference_seq, ref_id = preparation.load_reference_seq(fref_in) reference_binary = preparation.reference2binary(reference_seq, alphabet) - reads_list = preparation.load_fasta2reads_list(freads_in, alphabet, False) + reads_list = preparation.load_fasta2reads_list(freads_in, alphabet, unique_modus) reads_seq_binary, reads_weights = preparation.reads_list_to_array(reads_list) if n_starts >1: @@ -88,12 +88,12 @@ def main(freads_in, fref_in, output_dir, n_starts, K, alpha0, alphabet="ACGT-", logging.info("CAVI termination " + str(sort_results[0][2]["exit_message"])) - with open(output_name + "all_results.pkl", "wb") as f2: - pickle.dump(sort_results, f2) - - logging.info( - "Results dicts of all runs written to " + output_name + "all_results.pkl" - ) + if record_history: + with open(output_name + "all_results.pkl", "wb") as f2: + pickle.dump(sort_results, f2) + logging.info( + "Results dicts of all runs written to " + output_name + "all_results.pkl" + ) state_curr_dict = result_list[max_idx][1] logging.info("Maximal ELBO " + str(max_elbo) + "in run " + str(max_idx)) diff --git a/viloca/local_haplotype_inference/use_quality_scores/cavi.py b/viloca/local_haplotype_inference/use_quality_scores/cavi.py index 3ff3c58..e78330d 100644 --- a/viloca/local_haplotype_inference/use_quality_scores/cavi.py +++ b/viloca/local_haplotype_inference/use_quality_scores/cavi.py @@ -33,7 +33,8 @@ def multistart_cavi( reads_log_error_proba, n_starts, output_dir, - convergence_threshold + convergence_threshold, + record_history ): pool = mp.Pool(mp.cpu_count()) @@ -51,7 +52,8 @@ def multistart_cavi( reads_log_error_proba, start, output_dir, - convergence_threshold + convergence_threshold, + record_history ), callback=collect_result, ) @@ -74,6 +76,7 @@ def run_cavi( start_id, output_dir, convergence_threshold, + record_history, ): """ Runs cavi (coordinate ascent variational inference). @@ -86,12 +89,6 @@ def run_cavi( "alphabet": alphabet, } - history_alpha = [] - history_mean_log_pi = [] - history_mean_log_gamma = [] - history_mean_cluster = [] - history_elbo = [] - state_init_dict = initialization.draw_init_state( n_cluster, alpha0, alphabet, reads_list, reference_binary ) @@ -104,10 +101,11 @@ def run_cavi( } ) - history_alpha = [state_init_dict["alpha"]] - history_mean_log_pi = [state_init_dict["mean_log_pi"]] - history_mean_log_gamma = [state_init_dict["mean_log_gamma"]] - history_mean_cluster = [state_init_dict["mean_cluster"]] + if record_history: + history_alpha = [state_init_dict["alpha"]] + history_mean_log_pi = [state_init_dict["mean_log_pi"]] + history_mean_log_gamma = [state_init_dict["mean_log_gamma"]] + history_mean_cluster = [state_init_dict["mean_cluster"]] history_elbo = [] # Iteratively update mean values @@ -115,7 +113,8 @@ def run_cavi( converged = False elbo = 0 state_curr_dict = state_init_dict - while converged is False: + min_number_iterations = 10 + while (converged is False) or (iter < min_number_iterations): if iter <= 1: digamma_alpha_sum = digamma(state_curr_dict["alpha"].sum(axis=0)) @@ -141,11 +140,13 @@ def run_cavi( state_curr_dict, ) - if iter % 2 == 0: + if (iter % 2 == 0) and record_history: history_elbo.append(elbo) history_mean_log_pi.append(state_curr_dict["mean_log_pi"]) history_mean_log_gamma.append(state_curr_dict["mean_log_gamma"]) history_mean_cluster.append(state_curr_dict["mean_cluster"]) + else: + history_elbo.append(elbo) if iter > 1: if np.isnan(elbo): @@ -167,19 +168,30 @@ def run_cavi( state_curr_dict.update({"elbo": elbo}) - dict_result.update( - { - "exit_message": exit_message, - "n_iterations": iter, - "converged": converged, - "elbo": elbo, - "history_elbo": history_elbo, - "history_alpha": history_alpha, - "history_mean_log_pi": history_mean_log_pi, - "history_mean_log_gamma": history_mean_log_gamma, - "history_mean_cluster": history_mean_cluster, - } - ) + if record_history: + dict_result.update( + { + "exit_message": exit_message, + "n_iterations": iter, + "converged": converged, + "elbo": elbo, + "history_elbo": history_elbo, + "history_alpha": history_alpha, + "history_mean_log_pi": history_mean_log_pi, + "history_mean_log_gamma": history_mean_log_gamma, + "history_mean_cluster": history_mean_cluster, + } + ) + else: + dict_result.update( + { + "exit_message": exit_message, + "n_iterations": iter, + "converged": converged, + "elbo": elbo, + "history_elbo": history_elbo, + } + ) dict_result.update(state_curr_dict) result = (state_curr_dict, dict_result) diff --git a/viloca/local_haplotype_inference/use_quality_scores/run_dpm_mfa.py b/viloca/local_haplotype_inference/use_quality_scores/run_dpm_mfa.py index 58ff5b4..e2678bf 100644 --- a/viloca/local_haplotype_inference/use_quality_scores/run_dpm_mfa.py +++ b/viloca/local_haplotype_inference/use_quality_scores/run_dpm_mfa.py @@ -33,8 +33,9 @@ def main( K, alpha0, alphabet="ACGT-", - unique_modus=False, + unique_modus=True, convergence_threshold=1e-03, + record_history=False, ): window_id = freads_in.split("/")[-1][:-4] # freads_in is absolute path @@ -46,7 +47,7 @@ def main( reference_binary, ref_id = preparation.load_reference_seq(fref_in, alphabet) reads_list, qualities = preparation.load_fasta_and_qualities( - freads_in, fname_qualities, alphabet, False + freads_in, fname_qualities, alphabet, unique_modus ) reads_seq_binary, reads_weights = preparation.reads_list_to_array(reads_list) reads_log_error_proba = preparation.compute_reads_log_error_proba( @@ -65,7 +66,8 @@ def main( reads_log_error_proba, n_starts, output_name, - convergence_threshold + convergence_threshold, + record_history ) else: @@ -82,6 +84,7 @@ def main( 0, output_name, convergence_threshold, + record_history ) ] @@ -105,20 +108,13 @@ def main( exit_meassage = sorted_results[0][1]["exit_message"] logging.info("CAVI termination " + str(exit_meassage)) - # with open(output_name + "all_results.json", "w") as f: - # json.dump(sorted_results[0][1], f, cls=NumpyEncoder) + if record_history: + with open(output_name + "all_results.pkl", "wb") as f2: + pickle.dump(sorted_results, f2) - with open(output_name + "all_results.pkl", "wb") as f2: - pickle.dump(sorted_results, f2) - - # TODO: Would be nicer to use json dump. - # import json - # with open(output_name + "all_results.pkl", "wb") as fp: - # json.dump(sorted_results, fp) - - logging.info( - "Results dicts of all runs written to " + output_name + "all_results.pkl" - ) + logging.info( + "Results dicts of all runs written to " + output_name + "all_results.pkl" + ) state_curr_dict = result_list[best_run_idx][0] diff --git a/viloca/shotgun.py b/viloca/shotgun.py index 1495a71..b3e0e8f 100644 --- a/viloca/shotgun.py +++ b/viloca/shotgun.py @@ -138,7 +138,7 @@ def run_dpm(run_setting): """run the dirichlet process clustering """ - filein, j, a, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold = run_setting + filein, j, a, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold, record_history = run_setting ref_in = filein.split('.reads.')[0] + str('.ref.fas') fname_qualities = filein.split('.reads.')[0] + str('.qualities.npy') @@ -187,7 +187,8 @@ def run_dpm(run_setting): alpha0=float(a), alphabet = 'ACGT-', unique_modus = unique_modus, - convergence_threshold = inference_convergence_threshold + convergence_threshold = inference_convergence_threshold, + record_history = record_history ) elif inference_type == 'learn_error_params': @@ -198,8 +199,9 @@ def run_dpm(run_setting): K=int(n_max_haplotypes), alpha0=float(a), alphabet = 'ACGT-', - unique_modus = unique_modus + unique_modus = unique_modus, #convergence_threshold = inference_convergence_threshold, + record_history = record_history ) logging.debug('Finished sampler') @@ -296,7 +298,7 @@ def base_break(baselist): return rc -def win_to_run(alpha_w, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold): +def win_to_run(alpha_w, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold, record_history, reuse_files): """Return windows to run on diri_sampler.""" rn_list = [] @@ -307,10 +309,13 @@ def win_to_run(alpha_w, seed, inference_type, n_max_haplotypes, n_mfa_starts, un for f1 in file1: winFile, chr1, beg, end, cov = f1.rstrip().split('\t') - output_name = winFile.split("/")[-1][:-4] + "-" + "cor.fas" - if not os.path.isfile(output_name): - j = min(300_000, int(cov) * 15) - rn_list.append((winFile, j, alpha_w, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold)) + j = min(300_000, int(cov) * 15) + output_name = winFile.split(".fas")[0] + "-" + "cor.fas" + if not (reuse_files and os.path.isfile(output_name)): + rn_list.append((winFile, j, alpha_w, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold, record_history)) + else: + logging.info(f'[file already exits] Use {output_name} generated on {time.ctime(Path(output_name).stat().st_mtime)}') + del end del(beg, chr1) @@ -405,6 +410,8 @@ def main(args): extended_window_mode = args.extended_window_mode exclude_non_var_pos_threshold = args.exclude_non_var_pos_threshold win_min_ext = args.win_min_ext + reuse_files = args.reuse_files + record_history = args.record_history logging.info(' '.join(sys.argv)) @@ -432,53 +439,57 @@ def main(args): # run b2w logging.info('starting b2w') - try: - if ignore_indels == True: - raise NotImplementedError('This argument was deprecated.') - b2w_logging((in_bam, in_fasta, win_length, incr, win_min_ext, - max_coverage, cov_thrd, region, ignore_indels)) + if not (reuse_files and os.path.isfile(f"coverage.txt")): + try: + if ignore_indels == True: + raise NotImplementedError('This argument was deprecated.') + b2w_logging((in_bam, in_fasta, win_length, incr, win_min_ext, + max_coverage, cov_thrd, region, ignore_indels)) + + if path_insert_file == None and region == "": # special case if no region defined + samfile = pysam.AlignmentFile( + in_bam, + "r", # auto-detect bam/cram (rc) + reference_filename=in_fasta, + threads=1 + ) + if samfile.nreferences != 1: + raise NotImplementedError("There are multiple references in this alignment file.") + strategy = tiling.EquispacedTilingStrategy( + f"{samfile.references[0]}:1-{samfile.lengths[0]}", + win_length, + incr, + False, + True + ) + elif path_insert_file == None: + strategy = tiling.EquispacedTilingStrategy(region, win_length, incr, True) + else: + strategy = tiling.PrimerTilingStrategy(path_insert_file) + if region != "": + logging.warn(f"region is set to {region} but is not used with this tiling strategy") + + logging.info(f"Using tiling strategy: {type(strategy).__name__}") - if path_insert_file == None and region == "": # special case if no region defined - samfile = pysam.AlignmentFile( + b2w.build_windows( in_bam, - "r", # auto-detect bam/cram (rc) - reference_filename=in_fasta, - threads=1 + strategy, + win_min_ext, + max_coverage, + cov_thrd, + in_fasta, + extended_window_mode=extended_window_mode, + exclude_non_var_pos_threshold=exclude_non_var_pos_threshold, + maxthreads=maxthreads, + reuse_files=reuse_files ) - if samfile.nreferences != 1: - raise NotImplementedError("There are multiple references in this alignment file.") - strategy = tiling.EquispacedTilingStrategy( - f"{samfile.references[0]}:1-{samfile.lengths[0]}", - win_length, - incr, - False, - True - ) - elif path_insert_file == None: - strategy = tiling.EquispacedTilingStrategy(region, win_length, incr, True) - else: - strategy = tiling.PrimerTilingStrategy(path_insert_file) - if region != "": - logging.warn(f"region is set to {region} but is not used with this tiling strategy") - - logging.info(f"Using tiling strategy: {type(strategy).__name__}") - - b2w.build_windows( - in_bam, - strategy, - win_min_ext, - max_coverage, - cov_thrd, - in_fasta, - extended_window_mode=extended_window_mode, - exclude_non_var_pos_threshold=exclude_non_var_pos_threshold, - maxthreads=maxthreads - ) - logging.info('finished b2w') - - except Exception as e: - logging.debug(e) - sys.exit('b2w run not successful') + logging.info('finished b2w') + + except Exception as e: + logging.debug(e) + sys.exit('b2w run not successful') + else: + logging.info(f'[file already exits] Use coverage.txt generated on {time.ctime(Path("coverage.txt").stat().st_mtime)}') aligned_reads = parse_aligned_reads('reads.fas') if len(aligned_reads) == 0: @@ -502,7 +513,7 @@ def main(args): # Now the windows and the error correction # ############################################ - runlist = win_to_run(alpha, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold) + runlist = win_to_run(alpha, seed, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold, record_history, reuse_files) logging.info('will run on %d windows', len(runlist)) # run diri_sampler on all available processors but one max_proc = max(cpu_count() - 1, 1) @@ -533,7 +544,7 @@ def main(args): # parse corrected reads proposed = {} for i in runlist: - winFile, j, a, s, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold = i + winFile, j, a, s, inference_type, n_max_haplotypes, n_mfa_starts, unique_modus, inference_convergence_threshold, record_history = i del a # in future alpha might be different on each window del s # greedy re match to handle situation where '.' or '-' appears in the