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How to use chunkify method in tempest

Best Python code snippet using tempest_python

chunkify.smk

Source:chunkify.smk

1# =================================================================================================2#     Chunkify and Unchunkify3# =================================================================================================4# We want the sample names of the output files to fit the naming given by the user.5# In case our input for the samples is a table with two columns, the sample names (first column)6# can be different from the file names. However, the gappa chunkify command uses file names as7# sample names. For now, it is easiest to just symlink to the files to get a list of properly8# named files. In the future, we might add an option to rename samples in gappa chunkify,9# to make this step a bit less convoluted...10rule chunkify_sample_prep:11    input:12        fasta=get_sample_fasta13    output:14        "{outdir}/chunkify/samples/{sample}.fasta"15    shell:16        "ln -s {input.fasta} {output}"17# No need to execute this on the cluster computed nodes.18localrules: chunkify_sample_prep19# The rule to chunkify input fasta samples (query sequences) into chunks of equal size without20# duplicate sequences.21# We need a snakemake checkpoint here, because we cannot predict the number of chunks being produced.22checkpoint chunkify:23    input:24        # Request renamed samples, using the rule above, to get chunkify to use proper sample names.25        expand( "{outdir}/chunkify/samples/{sample}.fasta", outdir=outdir, sample=sample_names )26    output:27        abundances      = expand(   "{outdir}/chunkify/abundances/abundances_{sample}.json",28                                    outdir=outdir,29                                    sample=sample_names30                                )31    params:32        chunks_dir      = directory("{outdir}/chunkify/chunks"),33        abundances_dir  = directory("{outdir}/chunkify/abundances"),34        hashfunction    = config["params"]["chunkify"]["hash-function"],35        minabun         = config["params"]["chunkify"]["min-abundance"],36        chunksize       = config["params"]["chunkify"]["chunk-size"]37    # log:38    #     "{outdir}/logs/chunkify.log"39    conda:40        "../envs/gappa.yaml"41    shell:42        "mkdir -p {params.chunks_dir} ;"43        " mkdir -p {params.abundances_dir} ;"44        " gappa prepare chunkify"45        " --fasta-path {input}"46        " --chunks-out-dir {params.chunks_dir}"47        " --abundances-out-dir {params.abundances_dir}"48        " --hash-function {params.hashfunction}"49        " --min-abundance {params.minabun}"50        " --chunk-size {params.chunksize}"51        " > {log} 2>&1"52# Following the documentation tutorial here:53# https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#data-dependent-conditional-execution54def aggregate_chunkify_chunks(wildcards):55    # Wildcards are ignored here, as the chunkify process is for the whole dataset,56    # so we do not have any wildcards to take into account;57    # but still have to use them in the argument list,58    # because otherwise snakemake complains.59    chunks     = checkpoints.chunkify.get().output["chunks"]60    # abundances = checkpoints.chunkify.get().output[1]61    return expand(62        "chunkify/placed/{chunk}.jplace",63        chunk = glob_wildcards( os.path.join(chunks, "{chunk}.fasta")).chunk64    )65rule unchunkify:66    input:67        aggregate_chunkify_chunks,68        expand("{outdir}/chunkify/abundances/abundances_{sample}.json", outdir=outdir, sample=sample_names)69    output:70        protected( expand( "{outdir}/placed/{sample}.jplace", outdir=outdir, sample=sample_names ))71    params:72        hash_function = config["params"]["chunkify"]["hash-function"]73    # log:74    #     "{outdir}/logs/unchunkify.log"75    conda:76        "../envs/gappa.yaml"77    shell:78        "gappa prepare unchunkify"79        " --abundances-path {outdir}/chunkify/abundances"80        " --chunk-file-expression {outdir}/chunkify/placed/chunk_@.jplace"81        " --hash-function {params.hash_function}"82        " --out-dir {outdir}/placed"...

chunkify.py

Source:chunkify.py

1def chunkify(lst, s):2    n=[lst[(i-1)*s:i*s] for i in range(1,len(lst)+1)]3    return [i for i in n if i]4print(chunkify([2, 3, 4, 5], 2), [[2, 3], [4, 5]])5print(chunkify([2, 3, 4, 5, 6], 2), [[2, 3], [4, 5], [6]])6print(chunkify([2, 3, 4, 5, 6, 7], 3), [[2, 3, 4], [5, 6, 7]])7print(chunkify([2, 3, 4, 5, 6, 7], 1), [[2], [3], [4], [5], [6], [7]] )8print(chunkify([2, 3, 4, 5, 6, 7], 7), [[2, 3, 4, 5, 6, 7]] )9print(chunkify([2, 3, 4, 5], 3), [[2, 3, 4], [5]])10print(chunkify([2, 3, 4, 5, 6, 7, 8], 3), [[2, 3, 4], [5, 6, 7], [8]])...

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