Welcome to Nifty4Gemini’s documentation!¶

Nifty4Gemini is a full-featured Gemini data reduction framework for Gemini instruments and here we provide the documentation for its associated NIFS pipeline.

Package Documentation¶

Introduction¶

Nifty4Gemini, for now, uses Python 2.7. Please keep this in mind.

Running from the Command Line¶

Nifty4Gemini is started with the runNifty command by specifying a pipeline or step with arguments and options.

The syntax used to start Nifty is:

runNifty <Pipeline or Step Name> <arguments>

To get help or list the available options, type the runNifty command without any arguments.

runNifty

Running from Python¶

Python Programmers: even though Nifty’s API has not been defined yet, you can still run Nifty Pipelines, Steps, Routines and Tasks from a Python interpeter by importing them.

For example, to run a final cube merge from the Python interpreter:

# Import relevant modules; you can find those at top of nifsMerge.py
from pyraf import iraf, iraffunctions
# Import relevant local script
import nifty.pipeline.steps.nifsMerge

# Set up iraf
iraf.gemini()
iraf.gemtools()
iraf.gnirs()
iraf.nifs()

# Define routine parameters
scienceDirectoryList = []
cubeType = "uncorrected"
mergeType = "sum"
use_pq_offsets = True
im3dtran = True
over = False

# Start the cube merging
nifty.pipeline.steps.nifsMerge.mergeCubes(scienceDirectoryList, cubeType, mergeType, use_pq_offsets, im3dtran, over="")

You might be able to figure out what imports you need by checking the tops of the relevant scripts.

Examples of Running from the Command Line¶

Starting a Data Reduction from the Beginning

Supply the -i flag to start the NIFS pipeline, populating a configuration file interactively:

runNifty nifsPipeline -i

Supply a config.cfg file to start the NIFS pipeline from a pre-built configuration file:

runNifty nifsPipeline config.cfg

Supply the -f flat to do a fully automatic data reduction, downloading raw data from the Gemini Public Archive (Eg: GN-2013A-Q-62):

runNifty nifsPipeline -f GN-2013A-Q-62

Supply the -f flag to do a fully automatic data reduction, using raw data from a local directory (Eg: /Users/ncomeau/data/TUTORIAL):

runNifty nifsPipeline -f /Users/ncomeau/data/TUTORIAL

Starting a Data Reduction from a Specified Point

You can run each step, one at a time, from the command line like so. You need a config.cfg file in your current working directory to run individual steps. Each step requires the general config section and its unique config section to be populated.

You can also run an individual step by turning them on or off in nifsPipeline config and running the nifsPipeline.

nifsSort: To only copy and sort NIFS raw data use a config.cfg file like this:

# Nifty configuration file.
#
# Each section lists parameters required by a pipeline step.

manualMode = False
over = False
extractionXC = 15.0
extractionYC = 33.0
extractionRadius = 2.5
scienceOneDExtraction = True
scienceDirectoryList = []
telluricDirectoryList = []
calibrationDirectoryList = []

[nifsPipelineConfig]
sort = True
calibrationReduction = False
telluricReduction = False
scienceReduction = False
telluricCorrection = False
fluxCalibration = False
merge = False
telluricCorrectionMethod = 'gnirs'
fluxCalibrationMethod = 'gnirs'
mergeMethod = ''

[sortConfig]
rawPath = '/Users/nat/data/TUTORIAL'
program = ''
proprietaryCookie = ''
skyThreshold = 2.0
sortTellurics = True
telluricTimeThreshold = 5400

[calibrationReductionConfig]
baselineCalibrationStart = 1
baselineCalibrationStop = 4

[telluricReductionConfig]
telStart = 1
telStop = 5
telluricSkySubtraction = True

[telluricCorrectionConfig]
telluricCorrectionStart = 1
telluricCorrectionStop = 9
hLineMethod = 'vega'
hLineInter = False
continuumInter = False
telluricInter = False
tempInter = False
standardStarSpecTemperature = ''
standardStarMagnitude = ''
standardStarRA = ''
standardStarDec = ''
standardStarBand = ''

[fluxCalbrationConfig]
fluxCalibrationStart = 1
fluxCalibrationStop = 6

[mergeConfig]
mergeStart = 1
mergeStop = 3
mergeType = 'median'
use_pq_offsets = True
im3dtran = True

# Good luck with your Science!