def main(fin, fout, fout_weights):
"""
@param fin: open file for reading interleaved phylip alignment
@param fout: open file for writing interleaved phylip alignment
@param fout_weights: open file for writing codon column multiplicities
"""
# init the list of unique columns
unique_col_list = []
col_to_count = defaultdict(int)
# read the taxon names and the columns
taxon_names = None
for col in phylip.read_interleaved_codon_alignment(fin):
if taxon_names is None:
taxon_names = col
else:
if col not in col_to_count:
unique_col_list.append(col)
col_to_count[col] += 1
# get some output formatting info
ntaxa = len(taxon_names)
name_lengths = [len(name) for name in taxon_names]
ljust_spacing = max(name_lengths + [9])
# write the interleaved phylip header
nunique_codon_cols = len(unique_col_list)
print >> fout, ' %d %d' % (ntaxa, 3 * nunique_codon_cols)
# write the output files
ncols_per_paragraph = 15
offset = 0
while True:
# transpose the column list back into a paragraph
cols = unique_col_list[offset : offset+ncols_per_paragraph]
if not cols:
break
paragraph = zip(*cols)
# write the weights corresponding to these columns
if fout_weights is not None:
weights = [col_to_count[col] for col in cols]
print >> fout_weights, '\n'.join(str(w) for w in weights)
# write the paragraph
for i in range(ntaxa):
row = paragraph[i]
if offset:
print >> fout, ''.ljust(ljust_spacing),
else:
print >> fout, taxon_names[i].ljust(ljust_spacing),
print >> fout, ' '.join(row)
print >> fout
# move the the next paragraph worth of columns
offset += ncols_per_paragraph
def main(fin, fin_gcode, fin_taxa, fout):
"""
@param fin: interleaved phylip codon alignment file open for reading
@param fin_gcode: open file for reading the genetic code
@param fin_taxa: optional open file for defining taxon subset and order
@param fout: open file for writing the integer ndarray as text
"""
# read the description of the genetic code
arr = list(csv.reader(fin_gcode, delimiter='\t'))
indices, aminos, codons = zip(*arr)
if [int(x) for x in indices] != range(len(indices)):
raise ValueError
# read the interleaved phylip alignment
taxon_names = None
cols = []
for col in phylip.read_interleaved_codon_alignment(fin):
if taxon_names is None:
taxon_names = col
else:
cols.append(col)
# define the ndarray of integers
M_full = design.get_pattern_array(codons, cols)
if fin_taxa is None:
M = M_full
else:
# read the ordered taxon subset
arr = list(csv.reader(fin_taxa, delimiter='\t'))
indices, requested_taxa = zip(*arr)
if [int(x) for x in indices] != range(len(indices)):
raise ValueError
# init the pattern ndarray with unknown codon states
M = np.empty((len(cols), len(requested_taxa)), dtype=int)
M.fill(-1)
# construct the inverse map of the default taxon ordering
name_to_phlip_index = dict((x, i) for i, x in enumerate(taxon_names))
# Redefine the columns according to the user ordering and subsetting.
# In this code we are pretending to be a database software.
for i, name in enumerate(requested_taxa):
phylip_index = name_to_phlip_index.get(name, None)
if phylip_index is not None:
M[:, i] = M_full[:, phylip_index]
# write the ndarray of integers
np.savetxt(fout, M, fmt='%d', delimiter='\t')