gaps.cli.collect.collect#

collect(_out_path, _pattern, project_points=None, datasets=None, purge_chunks=False, clobber=True)[source]#

Run collection on local worker.

Collect data generated across multiple nodes into a single HDF5 file.

Parameters:

project_points (str | list, optional) – This input should represent the project points that correspond to the full collection of points contained in the input HDF5 files to be collected. You may simply point to a ProjectPoints csv file that contains the GID’s that should be collected. You may also input the GID’s as a list, though this may not be suitable for collections with a large number of points. You may also set this to input to None to generate a list of GID’s automatically from the input files. By default, None.
datasets (list of str, optional) – List of dataset names to collect into the output file. If collection is performed into multiple files (i.e. multiple input patterns), this list can contain all relevant datasets across all files (a warning wil be thrown, but it is safe to ignore it). If None, all datasets from the input files are collected. By default, None.
purge_chunks (bool, optional) – Option to delete single-node input HDF5 files. Note that the input files will not be removed if any of the datasets they contain have not been collected, regardless of the value of this input. By default, False.
clobber (bool, optional) – Flag to purge all collection output HDF5 files prior to running the collection step if they exist on disk. This helps avoid any surprising data byproducts when re-running the collection step in a project directory. By default, True.

Returns:

str – Path to HDF5 file with the collected outputs.