def MagePointFromBaseFreqs(freqs, get_label=None, get_color=None, \
get_radius=None):
"""Returns a MagePoint from an object with counts for the bases.
get_label should be a function that calculates a label from the freqs.
If get_label is not supplied, checks freqs.Label, freqs.Species, freqs.Id,
freqs.Accession, and freqs.Name in that order. If get_label fails or none
of the attributes is found, no label is written.
get_color should be a function that calculates a color from the freqs.
Default is no color (i.e. the point has the color for the series), which
will also happen if get_color fails.
get_radius is similar to get_color.
"""
label = None
if get_label:
try:
label = get_label(freqs)
except:
pass #label will be assigned None below
else:
for attr in ['Label', 'Species', 'Id', 'Accession', 'Name']:
if hasattr(freqs, attr):
label = getattr(freqs, attr)
#keep going if the label is empty
if label is not None and label != '':
break
if not label and label != 0:
label = None
if get_color:
try:
color = get_color(freqs)
except:
color=None
else:
if hasattr(freqs, 'Color'):
color = freqs.Color
else:
color = None
if get_radius:
try:
radius = get_radius(freqs)
except:
radius=None
else:
if hasattr(freqs, 'Radius'):
try:
radius = float(freqs.Radius)
except:
radius = None
else:
radius = None
relevant = Freqs({'A':freqs.get('A',0), 'C':freqs.get('C',0),
'G':freqs.get('G',0), 'U':freqs.get('U',0) or freqs.get('T',0)})
relevant.normalize()
return MagePoint((relevant['A'],relevant['C'],relevant['G']), Label=label,\
Color=color, Radius=radius)
def __init__(self, data=None, Info=None, **kwargs):
"""Intializes BaseUsage with data, either sequence or dict of freqs.
Ignores additional kwargs (e.g. to support copy).
Makes the _handler for delegator accessible with the name Info.
"""
if Info is None:
if hasattr(data, 'Info'):
Info = data.Info
else:
Info = InfoClass()
Delegator.__init__(self, Info)
Freqs.__init__(self, data or [], **kwargs)
def codons(self, genetic_code=SGC, codon_usage=_equal_codons):
"""Predicts most likely set of codon frequencies.
Optionally uses genetic_code (to figure out which codons belong
with each amino acid), and codon_usage (to get most likely codons for
each amino acid). Defaults are the standard genetic code and unbiased
codon frequencies.
"""
result = {}
normalized = Freqs(self)
normalized.normalize()
for aa, aa_freq in normalized.items():
curr_codons = genetic_code[aa]
if not curr_codons:
continue #code might be missing some amino acids?
curr_codon_freqs = Numbers([codon_usage[c] for c in curr_codons])
curr_codon_freqs.normalize()
for codon, c_freq in zip(curr_codons, curr_codon_freqs):
result[codon] = c_freq * aa_freq
return CodonUsage(result, self.info, genetic_code)
