Working with Files

DASCore contains two data structures which are useful for working with directories of fiber data.

FileSpool

The file spool is used to retrieve data from a directory of dascore-readable files. It has the same interface as other spools and is created with the dascore.spool function.

For example:

import dascore
from dascore import examples as ex

# Get a directory with several files
diverse_spool = dascore.get_example_spool('diverse_das')
path = ex.spool_to_directory(diverse_spool)

# Create a spool for interacting with the files in the directory.
spool = (
  dascore.spool(path)
  .select(network='das2')  # sub-select das2 network
  .select(time=(None, '2022-01-01'))  # unselect anything after 2022
  .chunk(time=2, overlap=0.5)  # change the chunking of the patches
)

# Iterate each patch and do something with it
for patch in spool:
  ...

Directory Indexer

The ‘DirectoryIndexer’ is used to track the contents of a directory which contains fiber data. It creates a small, hidden HDF index file at the top of the directory which can be efficiently queried for directory contents (it is used internally by the DirectorySpool).

import dascore
from dascore.io.indexer import DirectoryIndexer
from dascore import examples as ex

# Get a directory with several files
diverse_spool = dascore.get_example_spool('diverse_das')
path = ex.spool_to_directory(diverse_spool)

# Create an indexer and update the index. This will include any new files
# with timestamps newer than the last update, or create a new HDF index file
# if one does not yet exist.
indexer = DirectoryIndexer(path).update()

# get the contents of the directory's files
df = indexer.get_contents()

# This dataframe can be used to ascertain data availability, detect gaps, etc.

	path	time_min	file_format	station	file_version	time_step	time_max	tag	dims
0	DAS____wayout__random__1989_05_04T00_00_00_000...	1989-05-04	DASDAE	wayout	1	0 days 00:00:00.004000	1989-05-04 00:00:07.996	random	distance,time
1	DAS____big_gaps__random__2020_01_03T00_00_00_0...	2020-01-03	DASDAE	big_gaps	1	0 days 00:00:00.004000	2020-01-03 00:00:07.996	random	distance,time
2	DAS______random__2020_01_03T00_00_00_000000000...	2020-01-03	DASDAE		1	0 days 00:00:00.004000	2020-01-03 00:00:07.996	random	distance,time
3	DAS____smallg__random__2020_01_03T00_00_00_000...	2020-01-03	DASDAE	smallg	1	0 days 00:00:00.004000	2020-01-03 00:00:07.996	random	distance,time
4	DAS____overlaps__random__2020_01_03T00_00_00_0...	2020-01-03	DASDAE	overlaps	1	0 days 00:00:00.004000	2020-01-03 00:00:07.996	random	distance,time