This removes the warning from bedtools, 'WARNING: Genome (-g) files are ignored when BAM input is provided.'
Test of `bedtools genomecov -ibam records.bam > output.tsv` creates the same file as `bedtools genomecov -ibam records.bam -g lengths.tsv > output.tsv`

Binning now uses embeddings from canonical rank or from the specific rank name within the canononical rank depending on the rank partition size

…-data-mode

…ecified type

🎨 Add string instance check in kmers.embed(...) for pca_dimensions and attempt to convert to int if str given.

🐛 Add if statement to check whether user specified an output filepath to update logger message in parse(...)

…into large-data-mode

…utput table

🎨 Add script to extract log information from recursive_dbscan
🎨 Add autometa-binning-loginfo entrypoint for extracting binning log information

🐛 Fix checkpoint file writing logic where spaces were prepended to comment (#) lines
🐛 Fix merge logic when updating a checkpoint
🐛🎨 Add gzip functionality for writing of binning checkpoints file

…zipped checkpoint files

🎨 Clean logger emit message after retrieval of checkpoint info

…ckpoint_info(...)

🐛 Add newline characters for each commented param in binning checkpoints

…heckpoints

🎨 add checkpoint shape to binning checkpoints info

🎨 Update entrypoints so large data mode is separate from autometa-binning
🎨 Rename loginfo.py to large_data_mode_loginfo.py to match extracting log info for large_data_mode.py
🎨 Update loginfo entrypoint to corresopnd to large_data_mode
🎨 black formatting on summary.py and unclustered_recruitment.py
🎨 Refactor common binning functions to binning utilities.py

…data-mode

…nfo script

…for docs build

…for docs build

📝🎨 Update logger emitted messages when querying LCA

…arge-data-mode

…sta while binned seqs are written to <cluster>.fna

🎨🐍 refactor add_metrics(...) with speed-up code from KwanLab#181
📝 update autometa_clr(...) docstring

…mecov

…set comprehension

🎨 Refactor sseqids search in prot.accession2taxid.gz and dead_prot.accession2taxid.gz
🎨📝 Add docstrings and rename variables in large data mode module files
📝🔥 remove commented mathjax path in conf.py for docs

🔥🐛 Remove overwrite of input dict with empty dict
🔥 Remove unused variable in majority_vote.py args
🎨🍏 Update param arg for local lca nf module

🎨 Move search_prot_accessions(...) method to NCBI class
🎨 Add checks for prot.accession2taxid.FULL.gz in NCBI class

LCA blast2lca method now tries to retrieve taxids from sseqid_to_taxid_output iff it is already written
. This allows to skip the expensive step of parsing prot.accession2taxid databases and the blast table

🎨🐛 Account for bug where output filepath corresponds to a non-existent directory. Now creates all output directories in outpath that do not exist.

🎨 default is -1, which uses (n_cpus + 1 + core_dist_n_jobs)

…tered metagenome and is trying to retrieve gc_content and other assembly stats.

…scan

…into large-data-mode

🔥📝 Remove unused variables in docstring

🎨🐛 Drop metric columns when adding new metrics to avoid addition of suffixes
🔥🎨 Remove dropcols variable to isolate cluster metrics columns to add_metrics(...) and apply_binning_metrics_filter(...)
🔥🎨 Only drop cluster column in run_hdbscan(...)

🎨 rename 'rank' variable to more specific 'canonical_rank' variable.
🎨 Add logic to retrieve previous canonical rank kmer embedding if the current canonical rank embedding is not possible.

This first checks if the variable has been provided a value prior to filepath and filesize checking

…-binning entrypoints

Both clustering algorithms may be passed a parameter to allow them to use more cores for parallelization.

e.g. HDBSCAN(..., core_dist_n_jobs) and DBSCAN(..., n_jobs)

This parameter has been propagated through to these functions rather than the previously hardcoded -1 due to errors being raised from the joblib.externals library
while using HDBSCAN. The errors arising from n_jobs=-1 are infrequent, but frequent enough to merit providing the user more control

Some example exceptions that were raised:

- `[11/17/2021 10:53:42 PM ERROR] concurrent.futures: exception calling callback for <Future at 0x7fd2083a9c10 state=finished raised BrokenProcessPool>`
- `joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.`

🐛 Add input type conversion for --cpus arg in binning entrypoints

…ternals using joblib.

🔥🐛 This is a somewhat known error as similar messages have been discussed [here](scikit-learn/scikit-learn#21685)
and on the [hdbscan GH pull-#495](scikit-learn-contrib/hdbscan#495).

The error messages is emitted from joblib.externals.loky.process_executor._RemoteTraceback and emits a ValueError:

'ValueError: buffer source array is read-only.'

So far this has not been encountered with scikit-learn version 0.24

…data-mode

…arge-data-mode

…=Union[str,pd.DataFrame])

…into large-data-mode