Suitcase
Suitcase contains tools for exporting data from NSLS-II. It aims to support two important use cases:
- Export all data and metadata to an HDF5 file. In principle this file can be organized any way the user desires. For now, the file reflects the NSLS-II Document specification, but we are not promoting this as a standard exchange format. There are plans to support (possibly lossy) conversion to Data Exchange and Nexus formats.
- Export all data and metadata in a portable "Data Broker" that uses can run on their own computers with minimal dependencies. (Specifically, the full- fledged Data Broker runs a mongo database. The portable broker runs on sqlite, which is built in to Python and thus requires much less setup.)
Number 2 is planned but not yet implemented.
Conda Recipes
Install the most recent tagged build: conda install suitcase -c lightsource2-tag
Install the most recent tagged build: conda install suitcase -c lightsource2-dev
Find the tagged recipe here and the dev recipe here
Export headers and data into a hdf file
from databroker import db
from suitcase import hdf
# find the header(s) that you want to export
hdrs = db(start_time='2016-03-03', stop_time='2016-03-05')
fname = '/path/to/output/data'
hdf.export(hdrs, fname)Inserting data in the spec format into the databroker
This functionality is provided so that data that has been collected with spec can be inserted into the databroker stack which allows the analysis tools that are being written at NSLS-II to be used with this sort of "legacy" data. This also has the advantage that "legacy" data can be analyzed along side data that was collected with bluesky. Note that there are a number of checks to make sure that you do not add data more than one time.
from suitcase import spec
specfile = spec.Specfile('/path/to/specfile')
# Insert the whole specfile into the databroker
spec.insert_into_broker(specfile)
# Insert a single scan into the databroker
scan_id = 1
specscan = specfile[scan_id]
spec.insert_into_broker(specscan)