def test_transpose_trait_table_fields(self):
"""transpose_table_fields should correctly transpose table fields"""
# The purpose is to make it easy to transpose tab-delimited tables
# before analysis starts (and to have an internal method where needed
# Get header
test_header = "genomes\t123456\t123457\t123458\t123459\n"
test_data_fields =[\
["gene1",0,3,5,0],\
["gene2",1,2,1,0],\
["gene3",0,0,0,1]]
exp_header = "genomes\tgene1\tgene2\tgene3\n"
exp_data_fields =[\
['123456',0,1,0],\
['123457',3,2,0],\
['123458',5,1,0],\
['123459',0,0,1]]
new_header,new_data_fields = transpose_trait_table_fields(test_data_fields,\
header=test_header,id_row_idx=0)
self.assertEqual(new_header, exp_header)
self.assertEqual(new_data_fields, exp_data_fields)
pass
def test_transpose_trait_table_fields(self):
"""transpose_table_fields should correctly transpose table fields"""
# The purpose is to make it easy to transpose tab-delimited tables
# before analysis starts (and to have an internal method where needed
# Get header
test_header = "genomes\t123456\t123457\t123458\t123459\n"
test_data_fields =[\
["gene1",0,3,5,0],\
["gene2",1,2,1,0],\
["gene3",0,0,0,1]]
exp_header = "genomes\tgene1\tgene2\tgene3\n"
exp_data_fields =[\
['123456',0,1,0],\
['123457',3,2,0],\
['123458',5,1,0],\
['123459',0,0,1]]
new_header,new_data_fields = transpose_trait_table_fields(test_data_fields,\
header=test_header,id_row_idx=0)
self.assertEqual(new_header,exp_header)
self.assertEqual(new_data_fields,exp_data_fields)
pass
def main():
"""Generate test trees given parameters"""
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
if opts.verbose:
print "Loading trait table..."
input_trait_table = open(opts.input_trait_table,"U")
if opts.verbose:
print "Loading tree..."
#PicrustNode seems to run into very slow/memory intentsive perfromance...
#tree = DndParser(open(opts.input_tree),constructor=PicrustNode)
tree = DndParser(open(opts.input_tree))
if opts.verbose:
print "Parsing trait table..."
#Find which taxa are to be used in tests
#(by default trait table taxa)
trait_table_header,trait_table_fields = \
parse_trait_table(input_trait_table)
if opts.verbose:
print "Ensuring tree and trait table labels are formatted consistently..."
label_conversion_fns = set_label_conversion_fns(verbose=opts.verbose)
fix_tree_labels(tree,label_conversion_fns)
trait_table_fields = convert_trait_table_entries(trait_table_fields,\
value_conversion_fns = [],\
label_conversion_fns = label_conversion_fns)
trait_table_fields = [t for t in trait_table_fields]
print "Number of trait table fields with single quotes:",\
len([t for t in trait_table_fields if "'" in t[0]])
if opts.verbose:
print "Making output directory..."
make_output_dir(opts.output_dir)
if opts.limit_to_tips:
included_tips = opts.limit_to_tips.split(",")
if opts.verbose:
print "Limiting test datasets to %i tips: %s" %(len(included_tips),included_tips)
else:
included_tips = False
method_fns =\
{"exclude_tips_by_distance":\
make_distance_based_exclusion_fn,\
"randomize_tip_labels_by_distance":\
make_distance_based_tip_label_randomizer
}
test_fn_factory = method_fns[opts.method]
if opts.verbose:
print "Setting tree modification method to:", opts.method
print "(%s)" % test_fn_factory.__doc__
modify_tree = True
if opts.suppress_tree_modification:
if opts.verbose:
print "Suppressing modification of tree when making test datasets"
modify_tree = False
if opts.verbose:
print "Starting generation of test datsets"
test_datasets = \
yield_genome_test_data_by_distance(tree,trait_table_fields,\
test_fn_factory,min_dist = opts.min_dist,\
max_dist=opts.max_dist,increment=opts.dist_increment,\
modify_tree=modify_tree,limit_to_tips= included_tips,verbose = opts.verbose)
if opts.verbose:
print "Writing files for test datasets"
for curr_dist,test_tree,tip_to_predict,\
expected_traits,test_trait_table_fields in test_datasets:
if included_tips is not False:
if tip_to_predict not in included_tips:
if opts.verbose:
print "Skipping tip %s: limiting to tip(s): %s" %(tip_to_predict,included_tips)
continue
#Make a safe version of tip to predict
# So odd characters like | don't mess up OS
safe_tip_to_predict = "'%s'"%tip_to_predict
#Write tree
base_name = "--".join(map(str,["test_tree",opts.method,curr_dist]))
curr_filepath = write_tree(opts.output_dir,base_name,test_tree,safe_tip_to_predict)
if opts.verbose:
print "Wrote test tree to: %s" % curr_filepath
#Write expected trait table
base_name = "--".join(map(str,["exp_traits",opts.method,curr_dist,safe_tip_to_predict]))
exp_trait_table_lines = [trait_table_header]
exp_trait_table_lines.append("\t".join(expected_traits)+"\n")
#print "Expected_trait_table_lines:",exp_trait_table_lines
filename=os.path.join(opts.output_dir,base_name)
if opts.verbose:
print "Writing expected trait table to:", filename
f=open(filename,"w")
f.write("".join(exp_trait_table_lines))
f.close()
#Output a transposed, BIOM format expectation table for comparison with predict_traits output
#NOTE: this is a clumsy way of getting the translated trait table
# but more elegant, direct methods (directly feeding data to biom's table_factory)
# weren't working for me readily. In the future, we should streamline this process
# Leaving as is for now since this code is mostly for developers so speed/elegence
# are probably not essential here.
#Let the hackishness begin
#Reload the tab-delimited trait table
header, fields = parse_trait_table(open(filename,"U"))
fields = [f for f in fields] #converts generator to list
#Transpose table for .BIOM format so that Observation ids are KOs
transposed_header, transposed_trait_table_lines =\
transpose_trait_table_fields(fields,header,\
id_row_idx=0, input_header_delimiter="\t",output_delimiter="\t")
#Eliminate newline in header
trans_trait_table_lines = [transposed_header.strip()]
trans_trait_table_lines.extend(["\t".join(r) for r in transposed_trait_table_lines])
trans_trait_table = '\n'.join(trans_trait_table_lines)
#Write BIOM format expected trait table
base_name = "--".join(map(str,["exp_biom_traits",opts.method,curr_dist,safe_tip_to_predict]))
expected_biom_table = parse_table_to_biom(trans_trait_table.split('\n'),\
table_format = "tab-delimited")
#print "Expected_trait_table_lines:",exp_trait_table_lines
filename=os.path.join(opts.output_dir,base_name)
if opts.verbose:
print "Writing BIOM-format expected trait table to:", filename
f=open(filename,"w")
f.write(format_biom_table(expected_biom_table))
f.close()
#Write test trait table
test_trait_table_fields = test_trait_table_fields
if expected_traits in test_trait_table_fields:
test_trait_table_fields.remove(expected_traits)
test_trait_table_lines = [trait_table_header]
test_trait_table_lines.extend(["\t".join(r)+"\n" for r in test_trait_table_fields])
#print "Test_trait_table_lines:",test_trait_table_lines
base_name = "--".join(map(str,["test_trait_table",opts.method,curr_dist,safe_tip_to_predict]))
filename=os.path.join(opts.output_dir,base_name)
if opts.verbose:
print "Writing test trait table to:", filename
f=open(filename,"w")
f.write("".join(test_trait_table_lines))
f.close()
if opts.verbose:
print "Done generating test datasets"
def main():
"""Generate test trees given parameters"""
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
if opts.verbose:
print "Loading trait table..."
input_trait_table = open(opts.input_trait_table, "U")
if opts.verbose:
print "Loading tree..."
#PicrustNode seems to run into very slow/memory intentsive perfromance...
#tree = DndParser(open(opts.input_tree),constructor=PicrustNode)
tree = DndParser(open(opts.input_tree))
if opts.verbose:
print "Parsing trait table..."
#Find which taxa are to be used in tests
#(by default trait table taxa)
trait_table_header,trait_table_fields = \
parse_trait_table(input_trait_table)
if opts.verbose:
print "Ensuring tree and trait table labels are formatted consistently..."
label_conversion_fns = set_label_conversion_fns(verbose=opts.verbose)
fix_tree_labels(tree, label_conversion_fns)
trait_table_fields = convert_trait_table_entries(trait_table_fields,\
value_conversion_fns = [],\
label_conversion_fns = label_conversion_fns)
trait_table_fields = [t for t in trait_table_fields]
print "Number of trait table fields with single quotes:",\
len([t for t in trait_table_fields if "'" in t[0]])
if opts.verbose:
print "Making output directory..."
make_output_dir(opts.output_dir)
if opts.limit_to_tips:
included_tips = opts.limit_to_tips.split(",")
if opts.verbose:
print "Limiting test datasets to %i tips: %s" % (
len(included_tips), included_tips)
else:
included_tips = False
method_fns =\
{"exclude_tips_by_distance":\
make_distance_based_exclusion_fn,\
"randomize_tip_labels_by_distance":\
make_distance_based_tip_label_randomizer
}
test_fn_factory = method_fns[opts.method]
if opts.verbose:
print "Setting tree modification method to:", opts.method
print "(%s)" % test_fn_factory.__doc__
modify_tree = True
if opts.suppress_tree_modification:
if opts.verbose:
print "Suppressing modification of tree when making test datasets"
modify_tree = False
if opts.verbose:
print "Starting generation of test datsets"
test_datasets = \
yield_genome_test_data_by_distance(tree,trait_table_fields,\
test_fn_factory,min_dist = opts.min_dist,\
max_dist=opts.max_dist,increment=opts.dist_increment,\
modify_tree=modify_tree,limit_to_tips= included_tips,verbose = opts.verbose)
if opts.verbose:
print "Writing files for test datasets"
for curr_dist,test_tree,tip_to_predict,\
expected_traits,test_trait_table_fields in test_datasets:
if included_tips is not False:
if tip_to_predict not in included_tips:
if opts.verbose:
print "Skipping tip %s: limiting to tip(s): %s" % (
tip_to_predict, included_tips)
continue
#Make a safe version of tip to predict
# So odd characters like | don't mess up OS
safe_tip_to_predict = "'%s'" % tip_to_predict
#Write tree
base_name = "--".join(map(str, ["test_tree", opts.method, curr_dist]))
curr_filepath = write_tree(opts.output_dir, base_name, test_tree,
safe_tip_to_predict)
if opts.verbose:
print "Wrote test tree to: %s" % curr_filepath
#Write expected trait table
base_name = "--".join(
map(str,
["exp_traits", opts.method, curr_dist, safe_tip_to_predict]))
exp_trait_table_lines = [trait_table_header]
exp_trait_table_lines.append("\t".join(expected_traits) + "\n")
#print "Expected_trait_table_lines:",exp_trait_table_lines
filename = os.path.join(opts.output_dir, base_name)
if opts.verbose:
print "Writing expected trait table to:", filename
f = open(filename, "w")
f.write("".join(exp_trait_table_lines))
f.close()
#Output a transposed, BIOM format expectation table for comparison with predict_traits output
#NOTE: this is a clumsy way of getting the translated trait table
# but more elegant, direct methods (directly feeding data to biom's table_factory)
# weren't working for me readily. In the future, we should streamline this process
# Leaving as is for now since this code is mostly for developers so speed/elegence
# are probably not essential here.
#Let the hackishness begin
#Reload the tab-delimited trait table
header, fields = parse_trait_table(open(filename, "U"))
fields = [f for f in fields] #converts generator to list
#Transpose table for .BIOM format so that Observation ids are KOs
transposed_header, transposed_trait_table_lines =\
transpose_trait_table_fields(fields,header,\
id_row_idx=0, input_header_delimiter="\t",output_delimiter="\t")
#Eliminate newline in header
trans_trait_table_lines = [transposed_header.strip()]
trans_trait_table_lines.extend(
["\t".join(r) for r in transposed_trait_table_lines])
trans_trait_table = '\n'.join(trans_trait_table_lines)
#Write BIOM format expected trait table
base_name = "--".join(
map(str, [
"exp_biom_traits", opts.method, curr_dist, safe_tip_to_predict
]))
expected_biom_table = parse_table_to_biom(trans_trait_table.split('\n'),\
table_format = "tab-delimited")
#print "Expected_trait_table_lines:",exp_trait_table_lines
filename = os.path.join(opts.output_dir, base_name)
if opts.verbose:
print "Writing BIOM-format expected trait table to:", filename
f = open(filename, "w")
f.write(format_biom_table(expected_biom_table))
f.close()
#Write test trait table
test_trait_table_fields = test_trait_table_fields
if expected_traits in test_trait_table_fields:
test_trait_table_fields.remove(expected_traits)
test_trait_table_lines = [trait_table_header]
test_trait_table_lines.extend(
["\t".join(r) + "\n" for r in test_trait_table_fields])
#print "Test_trait_table_lines:",test_trait_table_lines
base_name = "--".join(
map(str, [
"test_trait_table", opts.method, curr_dist, safe_tip_to_predict
]))
filename = os.path.join(opts.output_dir, base_name)
if opts.verbose:
print "Writing test trait table to:", filename
f = open(filename, "w")
f.write("".join(test_trait_table_lines))
f.close()
if opts.verbose:
print "Done generating test datasets"
