def get_response_content(fs):
# deserialize the xml data to create a DirectProteinMixture
try:
mixture_model = DirectProtein.deserialize_mixture_model(fs.model)
except ValueError as e:
raise HandlingError(e)
expected_rate = mixture_model.get_expected_rate()
codon_distribution = mixture_model.get_codon_stationary_distribution()
aa_distribution = mixture_model.get_aa_stationary_distribution()
nt_distribution = mixture_model.get_nt_stationary_distribution()
ordered_codons = list(sorted(Codon.g_non_stop_codons))
# show the summary
out = StringIO()
print >> out, 'expected codon substitution rate:'
print >> out, expected_rate
print >> out, ''
print >> out, 'nucleotide distribution:'
for nt, proportion in zip(Codon.g_nt_letters, nt_distribution):
print >> out, '%s : %s' % (nt, proportion)
print >> out, ''
print >> out, 'amino acid distribution:'
for aa, proportion in zip(Codon.g_aa_letters, aa_distribution):
print >> out, '%s : %s' % (aa, proportion)
print >> out, ''
print >> out, 'codon distribution:'
for codon, proportion in zip(ordered_codons, codon_distribution):
print >> out, '%s : %s' % (codon, proportion)
return out.getvalue()
def get_response_content(fs):
# deserialize the xml data to create a DirectProteinMixture
try:
mixture_model = DirectProtein.deserialize_mixture_model(fs.model)
except ValueError as e:
raise HandlingError(e)
expected_rate = mixture_model.get_expected_rate()
codon_distribution = mixture_model.get_codon_stationary_distribution()
aa_distribution = mixture_model.get_aa_stationary_distribution()
nt_distribution = mixture_model.get_nt_stationary_distribution()
ordered_codons = list(sorted(Codon.g_non_stop_codons))
# show the summary
out = StringIO()
print >> out, 'expected codon substitution rate:'
print >> out, expected_rate
print >> out, ''
print >> out, 'nucleotide distribution:'
for nt, proportion in zip(Codon.g_nt_letters, nt_distribution):
print >> out, '%s : %s' % (nt, proportion)
print >> out, ''
print >> out, 'amino acid distribution:'
for aa, proportion in zip(Codon.g_aa_letters, aa_distribution):
print >> out, '%s : %s' % (aa, proportion)
print >> out, ''
print >> out, 'codon distribution:'
for codon, proportion in zip(ordered_codons, codon_distribution):
print >> out, '%s : %s' % (codon, proportion)
return out.getvalue()
def get_response_content(fs):
# get the newick string
try:
tree = Newick.parse(fs.tree, Newick.NewickTree)
tree.assert_valid()
except Newick.NewickSyntaxError as e:
raise HandlingError(e)
# get the normalized Direct RNA mixture model
mixture_model = DirectProtein.deserialize_mixture_model(fs.model)
mixture_model.normalize()
# simulate the alignment
try:
alignment = PhyLikelihood.simulate_alignment(tree,
mixture_model, fs.ncols)
except PhyLikelihood.SimulationError as e:
raise HandlingError(e)
# get the alignment
arr = []
for node in tree.gen_tips():
arr.append(alignment.get_fasta_sequence(node.name))
# return the alignment string
return '\n'.join(arr) + '\n'
def get_response_content(fs):
# deserialize the xml data to create a DirectProteinMixture
try:
mixture_model = DirectProtein.deserialize_mixture_model(fs.model)
except ValueError as e:
raise HandlingError(e)
# Normalize the mixture model to have an expected rate of one
# substitution per unit of branch length.
mixture_model.normalize()
# begin writing the html file
out = StringIO()
# write the html header
print >> out, '<html>'
print >> out, '<head>'
print >> out, '<style type="text/css">td{font-size:x-small;}</style>'
print >> out, '</head>'
print >> out, '<body>'
# write the symmetric components of the rate matrices
for category_i, matrix_object in enumerate(mixture_model.rate_matrices):
codon_v = matrix_object.get_stationary_distribution()
matrix = matrix_object.dictionary_rate_matrix
symmetric_matrix = {}
for ca, pa in zip(codons, codon_v):
for cb, pb in zip(codons, codon_v):
value = matrix[(ca, cb)] / (math.sqrt(pb) / math.sqrt(pa))
symmetric_matrix[(ca, cb)] = value
print >> out, 'the symmetric component of the rate matrix'
print >> out, 'for category %d:' % (category_i + 1)
print >> out, '<table>'
print >> out, RateMatrix.codon_rate_matrix_to_html_string(
symmetric_matrix)
print >> out, '</table>'
print >> out, '<br/><br/>'
# write the html footer
print >> out, '</body>'
print >> out, '</html>'
# return the response
return out.getvalue()
def get_response_content(fs):
# deserialize the xml data to create a DirectProteinMixture
try:
mixture_model = DirectProtein.deserialize_mixture_model(fs.model)
except ValueError as e:
raise HandlingError(e)
# Normalize the mixture model to have an expected rate of one
# substitution per unit of branch length.
mixture_model.normalize()
# begin writing the html file
out = StringIO()
# write the html header
print >> out, '<html>'
print >> out, '<head>'
print >> out, '<style type="text/css">td{font-size:x-small;}</style>'
print >> out, '</head>'
print >> out, '<body>'
# write the symmetric components of the rate matrices
for category_i, matrix_object in enumerate(mixture_model.rate_matrices):
codon_v = matrix_object.get_stationary_distribution()
matrix = matrix_object.dictionary_rate_matrix
symmetric_matrix = {}
for ca, pa in zip(codons, codon_v):
for cb, pb in zip(codons, codon_v):
value = matrix[(ca, cb)] / (math.sqrt(pb) / math.sqrt(pa))
symmetric_matrix[(ca, cb)] = value
print >> out, 'the symmetric component of the rate matrix'
print >> out, 'for category %d:' % (category_i + 1)
print >> out, '<table>'
print >> out, RateMatrix.codon_rate_matrix_to_html_string(
symmetric_matrix)
print >> out, '</table>'
print >> out, '<br/><br/>'
# write the html footer
print >> out, '</body>'
print >> out, '</html>'
# return the response
return out.getvalue()
