NAStools

A python module for working with file formats commonly encountered in the field of observational/airborne atmospheric sciences. The project is still in its infancy but (limited) functionality is currently present in the module.

What is Nastools?

Nastools provides a python package for dealing with common NASA file formats commonly encountered in the atmospheric science and instrumentation community.

Two common file formats are:

• ICARTT File Format
• NASA Ames File Format

NASA Ames format is now supported!

Note that only FFI = 1001 type-files are supported at this point.

Quick Start Guide

The following should get you up and running quickly.

Issues/bugs/feature requests/etc can be reported here.

Installation

Nastools are available from the cheeseshop:

pip install NAStools

Using Nastools

Here are a few examples of how you can use nastools to help with your interactive analysis work.

Header Information

import nastools

# Generate a Naspy object
h = nastools.Naspy(~/Desktop/sampleFile.nas)

# Get variable names
h.get_column_names()

# Get instrument info
print h.header.INSTRUMENT_INFO

# Get start time of file
startUtc = h.time.start_time()
print startUtc.isoformat()

# Get end time of file
endUtc = h.time.end_time()
print endUtc.isoformat()

# Total length of file
totalTime = endUtc - startUtc
print "**TOTAL FILE LENGTH**"
print "%s seconds" % totalTime.total_seconds()

# See all the header keys
print D.header.__dict__.keys()

# See all the header info in a (relatively) nice format
for key, val in h.header.__dict__.iteritems():
    print '%s: %s\n' % (key, val)

Generating a Naspy object is enough to start doing analysis.

Generate a Numpy Array

import nastools
h = nastools.Naspy(~/Desktop/sampleFile.nas)

# Make a numpy array
arr = h.make_numpy()

# Make a masked array with missing values masked
arr = h.make_numpy(masked=True)

Generate a DataFrame

import nastools
h = nastools.Naspy(~/Desktop/sampleFile.nas)

# Make a pandas.DataFrame
df = h.make_DataFrame()

# Make a pandas.DataFrame with integer index (not datetime)
df = h.make_DataFrame(datetime_asindex=False)
# rename 'DATETIME' field to 'DT'
df = df.rename(columns={'DATETIME':'DT'})

VERSION HISTORY

• 0.1.0: Initial release.
• 0.1.1: Support for NASA Ames files added; custom variable names can be passed to both pandas.DataFrame and numpy.array objects.
• 0.1.2: Added timezone localization to DataFrames; fixed bug preventing Datetime construction in DataFrames; fixed potential bug when automatically determining filetype.
• 0.2.0: Adds option to use any column as datetime field (@maahn, #4); removes unused yamler.py source file (fixes #3); ownership info updated.
• 0.2.1: Fixes incorrect spelling throughout (ICARRT -> ICARTT, fixes #7).