Rosetta
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Functions | |
def | find_nonmodulo_autocorrelation (x) |
def | find_autocorrelation (x) |
Variables | |
parser = helpers.define_args('torsion', 'plot') | |
type | |
float | |
default | |
arguments = parser.parse_args() | |
iterations = helpers.load_array(arguments.job, 'iterations') | |
torsions = helpers.load_arrays(arguments.job, 'torsions') | |
def | autocorrelation = find_autocorrelation(torsions[key]) |
color = pylab.cm.Dark2(numpy.median(autocorrelation)) | |
label | |
key | |
def autocorrelation.find_autocorrelation | ( | x | ) |
This homebrew autocorrelation function is specifically written to handle modulo variable like dihedral angles. Think of the cosine function as an alternative, and more appropriate, metric for overlap.
References helpers.connect_to_database(), ObjexxFCL.len(), numeric::conversions.radians(), range, and sum().
def autocorrelation.find_nonmodulo_autocorrelation | ( | x | ) |
The standard correlation function isn't meant for modulo variables, like dihedral angles. I'm sure this version is much faster, but it will choke on angles constantly jumping between 180 and -180.
References ObjexxFCL.len().
autocorrelation.arguments = parser.parse_args() |
autocorrelation.autocorrelation = find_autocorrelation(torsions[key]) |
autocorrelation.color = pylab.cm.Dark2(numpy.median(autocorrelation)) |
autocorrelation.default |
autocorrelation.float |
autocorrelation.iterations = helpers.load_array(arguments.job, 'iterations') |
autocorrelation.key |
autocorrelation.label |
autocorrelation.parser = helpers.define_args('torsion', 'plot') |
autocorrelation.torsions = helpers.load_arrays(arguments.job, 'torsions') |
autocorrelation.type |