def tree_from_splits(self,
split_distribution,
min_freq=0.5,
include_edge_lengths=True):
"""Returns a consensus tree from splits in `split_distribution`.
If include_edge_length_var is True, then the sample variance of the
edge length will also be calculated and will be stored as
a length_var attribute.
"""
taxon_set = split_distribution.taxon_set
taxa_mask = taxon_set.all_taxa_bitmask()
if self.weighted_splits:
split_freqs = split_distribution.weighted_split_frequencies
else:
split_freqs = split_distribution.split_frequencies
is_rooted = split_distribution.is_rooted
#include_edge_lengths = self.support_as_labels and include_edge_lengths
if self.support_as_edge_lengths and include_edge_lengths:
raise Exception("Cannot map support as edge lengths if edge lengths are to be set on consensus tree")
to_try_to_add = []
_almost_one = lambda x: abs(x - 1.0) <= 0.0000001
for s, freq in split_freqs.iteritems():
if (min_freq is None) or (freq > min_freq) or (_almost_one(min_freq) and _almost_one(freq)):
to_try_to_add.append((freq, s))
to_try_to_add.sort(reverse=True)
splits_for_tree = [i[1] for i in to_try_to_add]
con_tree = treesplit.tree_from_splits(splits=splits_for_tree,
taxon_set=taxon_set,
is_rooted=is_rooted)
treesplit.encode_splits(con_tree)
if include_edge_lengths:
split_edge_lengths = {}
for split, edges in split_distribution.split_edge_lengths.items():
if len(edges) > 0:
mean, var = mean_and_sample_variance(edges)
elen = mean
else:
elen = None
split_edge_lengths[split] = elen
else:
split_edge_lengths = None
for node in con_tree.postorder_node_iter():
split = node.edge.split_bitmask
if split in split_freqs:
self.map_split_support_to_node(node=node, split_support=split_freqs[split])
if include_edge_lengths and split in split_distribution.split_edge_lengths:
edges = split_distribution.split_edge_lengths[split]
if len(edges) > 0:
mean, var = mean_and_sample_variance(edges)
elen = mean
else:
elen = None
node.edge.length = elen
return con_tree
def summarize_edge_lengths_on_tree(self,
tree,
split_distribution,
summarization_func=None):
"""
Sets the lengths of edges on `tree` (a `Tree` object) to the mean
lengths of the corresponding edges on the input trees (in
`split_distribution`, a `SplitDistribution` object) being
summarized.
`summarization_func` should take an iterable of floats, and return a float. If `None`, it
defaults to calculating the mean (`lambda x: float(sum(x))/len(x)`).
"""
if summarization_func is None:
summarization_func = lambda x: float(sum(x)) / len(x)
if not hasattr(tree, "split_edges"):
tree.update_splits()
for split, edge in tree.split_edges.items():
if (split in split_distribution.split_edge_lengths
and split_distribution.split_edge_lengths[split]):
lengths = split_distribution.split_edge_lengths[split]
#if len(lengths) != split_distribution.total_trees_counted:
# # not all input trees had edge lengths (at least, for this split)
# pass
edge.length = summarization_func(lengths)
elif (split in split_distribution.split_edge_lengths
and not split_distribution.split_edge_lengths[split]):
# no input trees had any edge lengths for this split
edge.length = None
else:
# split on target tree that was not found in any of the input
# trees
edge.length = 0.0
return tree
## here we add the support values and/or edge lengths for the terminal taxa ##
for node in leaves:
if not is_rooted:
split = con_tree.split_edges.normalize_key(
node.edge.split_bitmask)
else:
split = node.edge.split_bitmask
self.map_split_support_to_node(node, 1.0)
if include_edge_lengths:
elen = split_distribution.split_edge_lengths.get(split, [0.0])
if len(elen) > 0:
mean, var = mean_and_sample_variance(elen)
node.edge.length = mean
if include_edge_length_var:
node.edge.length_var = var
else:
node.edge.length = None
if include_edge_length_var:
node.edge.length_var = None
#if include_edge_lengths:
#self.map_edge_lengths_to_tree(tree=con_tree,
# split_distribution=split_distribution,
# summarization_func=summarization_func,
# include_edge_length_var=False)
return con_tree
def summarize_edge_lengths_on_tree(self,
tree,
split_distribution,
summarization_func=None):
"""
Sets the lengths of edges on `tree` (a `Tree` object) to the mean
lengths of the corresponding edges on the input trees (in
`split_distribution`, a `SplitDistribution` object) being
summarized.
`summarization_func` should take an iterable of floats, and return a float. If `None`, it
defaults to calculating the mean (`lambda x: float(sum(x))/len(x)`).
"""
if summarization_func is None:
summarization_func = lambda x: float(sum(x))/len(x)
if not hasattr(tree, "split_edges"):
tree.update_splits()
for split, edge in tree.split_edges.items():
if (split in split_distribution.split_edge_lengths
and split_distribution.split_edge_lengths[split]):
lengths = split_distribution.split_edge_lengths[split]
#if len(lengths) != split_distribution.total_trees_counted:
# # not all input trees had edge lengths (at least, for this split)
# pass
edge.length = summarization_func(lengths)
elif (split in split_distribution.split_edge_lengths
and not split_distribution.split_edge_lengths[split]):
# no input trees had any edge lengths for this split
edge.length = None
else:
# split on target tree that was not found in any of the input
# trees
edge.length = 0.0
return tree
## here we add the support values and/or edge lengths for the terminal taxa ##
for node in leaves:
if not is_rooted:
split = con_tree.split_edges.normalize_key(node.edge.split_bitmask)
else:
split = node.edge.split_bitmask
self.map_split_support_to_node(node, 1.0)
if include_edge_lengths:
elen = split_distribution.split_edge_lengths.get(split, [0.0])
if len(elen) > 0:
mean, var = mean_and_sample_variance(elen)
node.edge.length = mean
if include_edge_length_var:
node.edge.length_var = var
else:
node.edge.length = None
if include_edge_length_var:
node.edge.length_var = None
#if include_edge_lengths:
#self.map_edge_lengths_to_tree(tree=con_tree,
# split_distribution=split_distribution,
# summarization_func=summarization_func,
# include_edge_length_var=False)
return con_tree
def summarize(mcmc, field):
results = mcmc.trace(field)[:]
results = zip(*results)
means = []
for r in results:
m, v = stats.mean_and_sample_variance(r)
means.append(m)
means.append(1.0 - sum(means))
print
print "---"
print means
def main_cli():
description = "%s %s %s" % (_program_name, _program_version, _program_subtitle)
usage = "%prog [options] TREES-FILE [TREES-FILE [TREES-FILE [...]]"
parser = OptionParser(usage=usage, add_help_option=True, version=_program_version, description=description)
sum_tree_optgroup = OptionGroup(parser, "Source Treatment Options")
parser.add_option_group(sum_tree_optgroup)
sum_tree_optgroup.add_option(
"-b",
"--burnin",
action="store",
dest="burnin",
type="int",
default=0,
help="number of trees to skip from the beginning of *each tree file* when counting support [default=%default]",
)
source_tree_optgroup = OptionGroup(parser, "Source Tree Options")
parser.add_option_group(source_tree_optgroup)
source_tree_optgroup.add_option(
"--rooted", action="store_true", dest="rooted_trees", default=None, help="treat trees as rooted"
)
source_tree_optgroup.add_option(
"--unrooted", action="store_false", dest="rooted_trees", default=None, help="treat trees as unrooted"
)
source_tree_optgroup.add_option(
"--ultrametric",
action="store_true",
dest="ultrametric_trees",
default=False,
help="assume trees are ultrametric (implies '--rooted' ; will result in node ages being summarized; will result in error if trees are not ultrametric)",
)
source_tree_optgroup.add_option(
"--weighted-trees",
action="store_true",
dest="weighted_trees",
default=False,
help="use weights of trees as indicated by '[&W m/n]' comment to weight contribution of splits found on each tree to overall split frequencies",
)
source_tree_optgroup.add_option(
"--from-newick-stream",
action="store_true",
dest="from_newick_stream",
default=False,
help="support trees will be streamed in newick format",
)
source_tree_optgroup.add_option(
"--from-nexus-stream",
action="store_true",
dest="from_nexus_stream",
default=False,
help="support trees will be streamed in NEXUS format",
)
target_tree_optgroup = OptionGroup(parser, "Target Tree Options")
parser.add_option_group(target_tree_optgroup)
target_tree_optgroup.add_option(
"-t",
"--target",
dest="target_tree_filepath",
default=None,
help="path to optional target, model or best topology tree file (Newick or NEXUS format) "
+ "to which support will be mapped; "
+ "if not given, then a majority-rule clade consensus tree will be constructed based on the "
+ "all the trees given in the support tree files (except for those discarded as burn-ins), "
+ "and this will be used as the target tree",
)
target_tree_optgroup.add_option(
"-f",
"--min-clade-freq",
dest="min_clade_freq",
type="float",
default=0.50,
metavar="#.##",
help="minimum frequency or probability for a clade or a split to be "
+ "included in the consensus tree, if used [default=%default]",
)
support_summarization_optgroup = OptionGroup(parser, "Support Summarization Options")
parser.add_option_group(support_summarization_optgroup)
support_summarization_optgroup.add_option(
"-l",
"--support-as-labels",
action="store_const",
dest="support_annotation_target",
default=1,
const=1,
help="in addition to node metadata, indicate branch support as internal node labels [default]",
)
support_summarization_optgroup.add_option(
"-v",
"--support-as-lengths",
action="store_const",
dest="support_annotation_target",
default=1,
const=2,
help="in addition to node metadata, indicate branch support as branch lengths",
)
support_summarization_optgroup.add_option(
"-x",
"--no-support",
action="store_const",
dest="support_annotation_target",
default=1,
const=0,
help="""\
do not indicate support with internal node labels or edge lengths
(support will still be indicated as node metadata unless
'--no-summary-metadata' is specified)""",
)
support_summarization_optgroup.add_option(
"-p",
"--percentages",
action="store_true",
dest="support_as_percentages",
default=False,
help="indicate branch support as percentages (otherwise, will report as proportions by default)",
)
support_summarization_optgroup.add_option(
"-d",
"--decimals",
dest="support_label_decimals",
type="int",
metavar="#",
default=2,
help="number of decimal places in indication of support values [default=%default]",
)
edge_summarization_optgroup = OptionGroup(parser, "Edge Length Summarization Options")
parser.add_option_group(edge_summarization_optgroup)
edge_summarization_choices = ["mean-length", "median-length", "mean-age", "median-age", "keep", "unweighted"]
edge_summarization_optgroup.add_option(
"-e",
"--edges",
type="choice",
dest="edge_summarization",
metavar="<%s>" % ("|".join(edge_summarization_choices)),
choices=edge_summarization_choices,
default=None,
help="""\
set edge lengths of target tree(s) to mean/median lengths/ages of
corresponding splits or edges of input trees (note that using 'mean-age' or
'median-age' require rooted ultrametric input trees, and will behave as
if '--ultrametric' and '--with-node-ages' are specified");
default is to 'keep' if target trees are specified
(i.e., target trees will have their branch lengths preserved by default),
'median-age' if no target trees are specified but the '--ultrametric' directive is given
(a consensus tree should be constructed to summarize support and input trees are ultrametric),
and 'mean-length' if no target trees are specified and the '--ultrametric' directive is *not* given
(a consensus tree should be constructed to summarize support and input trees are *not* assumed to be ultrametric),
""",
)
edge_summarization_optgroup.add_option(
"--collapse-negative-edges",
action="store_true",
dest="collapse_negative_edges",
default=False,
help="(if setting edge lengths) force parent node ages to be at least as old as its oldest child when summarizing node ages",
)
other_summarization_optgroup = OptionGroup(parser, "Other Summarization Options")
parser.add_option_group(other_summarization_optgroup)
# other_summarization_optgroup.add_option("--with-node-ages",
# action="store_true",
# dest="calc_node_ages",
# default=None,
# help="summarize node ages as well as edge lengths (implies '--rooted' and '--ultrametric'; automatically enabled if '--ultrametric' is specified; will result in error if trees are not ultrametric)")
other_summarization_optgroup.add_option(
"--trprobs",
"--calc-tree-probabilities",
dest="trprobs_filepath",
default=None,
metavar="FILEPATH",
help="if specified, a file listing tree (topologies) and the "
+ "frequencies of their occurrences will be saved to FILEPATH",
)
other_summarization_optgroup.add_option(
"--extract-edges",
dest="split_edges_filepath",
default=None,
metavar="FILEPATH",
help="if specified, a tab-delimited file of splits and their edge "
+ "lengths across input trees will be saved to FILEPATH",
)
other_summarization_optgroup.add_option(
"--no-node-ages",
action="store_false",
dest="calc_node_ages",
default=None,
help="do not calculate/summarize node ages, even if '--ultrametric' is specified",
)
other_summarization_optgroup.add_option(
"--no-summary-metadata",
action="store_true",
dest="suppress_summary_metadata",
default=False,
help="do not annotate nodes with ranges, 5%/95 quartiles, 95% HPD's etc. of edge lengths and node ages",
)
other_summarization_optgroup.add_option(
"--ultrametricity-precision", default=0.0000001, type="float", help="precision when checking ultrametricity"
)
output_filepath_optgroup = OptionGroup(parser, "Output File Options")
parser.add_option_group(output_filepath_optgroup)
output_filepath_optgroup.add_option(
"-o",
"--output",
dest="output_filepath",
default=None,
help="path to output file (if not given, will print to standard output)",
)
output_filepath_optgroup.add_option(
"--no-taxa-block",
action="store_false",
dest="include_taxa_block",
default=True,
help="do not include a taxa block in the output treefile (otherwise will create taxa block by default)",
)
output_filepath_optgroup.add_option(
"--no-meta-comments",
action="store_false",
dest="include_meta_comments",
default=True,
help="do not include initial file comment annotating details of scoring operation",
)
output_filepath_optgroup.add_option(
"-c",
"--additional-comments",
action="store",
dest="additional_comments",
default=None,
help="additional comments to be added to the summary file",
)
output_filepath_optgroup.add_option(
"--to-newick",
action="store_true",
dest="to_newick_format",
default=False,
help="save results in NEWICK (PHYLIP) format (default is to save in NEXUS format)",
)
output_filepath_optgroup.add_option(
"--to-phylip", action="store_true", dest="to_newick_format", default=False, help="same as --newick"
)
output_filepath_optgroup.add_option(
"-r",
"--replace",
action="store_true",
dest="replace",
default=False,
help="replace/overwrite output file without asking if it already exists ",
)
run_optgroup = OptionGroup(parser, "Program Run Options")
parser.add_option_group(run_optgroup)
if _MP:
run_optgroup.add_option(
"-m",
"--multiprocessing",
action="store",
dest="multiprocess",
metavar="NUM-PROCESSES",
default=None,
help="run in parallel mode with up to a maximum of NUM-PROCESSES processes "
+ "(specify '*' to run in as many processes as there are cores on the "
+ "local machine)",
)
run_optgroup.add_option(
"-g",
"--log-frequency",
type="int",
metavar="LOG-FREQUENCY",
dest="log_frequency",
default=500,
help="tree processing progress logging frequency (default=%default; set to 0 to suppress)",
)
run_optgroup.add_option(
"-q",
"--quiet",
action="store_true",
dest="quiet",
default=False,
help="suppress ALL logging, progress and feedback messages",
)
run_optgroup.add_option(
"--ignore-missing-support",
action="store_true",
dest="ignore_missing_support",
default=False,
help="ignore missing support tree files (at least one must exist!)",
)
run_optgroup.add_option(
"--ignore-missing-target",
action="store_true",
dest="ignore_missing_target",
default=False,
help="ignore missing target tree file (will construct majority rule consensus tree if missing)",
)
(opts, args) = parser.parse_args()
if opts.quiet:
messaging_level = ConsoleMessenger.ERROR_MESSAGING_LEVEL
else:
messaging_level = ConsoleMessenger.INFO_MESSAGING_LEVEL
messenger = ConsoleMessenger(name="SumTrees", messaging_level=messaging_level)
# splash
if not opts.quiet:
show_splash(
prog_name=_program_name,
prog_subtitle=_program_subtitle,
prog_version=_program_version,
prog_author=_program_author,
prog_copyright=_program_copyright,
dest=sys.stderr,
extended=False,
)
###################################################
# Support file idiot checking
support_filepaths = []
if len(args) > 0:
for fpath in args:
fpath = os.path.expanduser(os.path.expandvars(fpath))
if not os.path.exists(fpath):
if opts.ignore_missing_support:
messenger.send_warning("Support file not found: '%s'" % fpath)
else:
messenger.send_error(
"Terminating due to missing support files. "
+ "Use the '--ignore-missing-support' option to continue even "
+ "if some files are missing."
)
sys.exit(1)
else:
support_filepaths.append(fpath)
if len(support_filepaths) == 0:
messenger.send_error(
"No valid sources of input trees specified. "
+ "Please provide the path to at least one (valid and existing) file "
+ "containing tree samples to summarize."
)
sys.exit(1)
else:
if not opts.from_newick_stream and not opts.from_nexus_stream:
messenger.send_info(
"No sources of input trees specified. "
+ "Please provide the path to at least one (valid and existing) file "
+ "containing tree samples to summarize. See '--help' for other options."
)
sys.exit(1)
###################################################
# Lots of other idiot-checking ...
# target tree
if opts.target_tree_filepath is not None:
target_tree_filepath = os.path.expanduser(os.path.expandvars(opts.target_tree_filepath))
if not os.path.exists(target_tree_filepath):
if opts.ignore_missing_target:
if not opts.quiet:
messenger.send_warning(
"Target tree file not found: '%s': using majority-rule consensus tree instead."
% target_tree_filepath
)
target_tree_filepath = None
else:
messenger.send_error("Target tree file not found: '%s'" % target_tree_filepath)
sys.exit(1)
else:
target_tree_filepath = None
### TODO: these will be command-line options in the future
### here we just set it
assert not hasattr(opts, "outgroup")
opts.outgroup = None
assert not hasattr(opts, "root_target")
opts.root_target = None
### TODO: idiot-check edge length summarization
# edge lengths
if opts.edge_summarization:
opts.edge_summarization = opts.edge_summarization.lower()
if opts.edge_summarization not in edge_summarization_choices:
messenger.send_error(
"'%s' is not a valid edge summarization choice; must be one of: %s"
% (opts.edge_summarization, edge_summarization_choices)
)
sys.exit(1)
if opts.edge_summarization == "mean-age" or opts.edge_summarization == "median-age":
opts.ultrametric_trees = True
opts.rooted_trees = True
if opts.calc_node_ages is None:
opts.calc_node_ages = True
else:
if opts.ultrametric_trees:
opts.rooted_trees = True
if opts.calc_node_ages is None:
opts.calc_node_ages = True
else:
if opts.calc_node_ages is True:
opts.ultrametric_trees = True
opts.rooted_trees = True
else:
opts.calc_node_ages = False
# output
if opts.output_filepath is None:
output_dest = sys.stdout
else:
output_fpath = os.path.expanduser(os.path.expandvars(opts.output_filepath))
if confirm_overwrite(filepath=output_fpath, replace_without_asking=opts.replace):
output_dest = open(output_fpath, "w")
else:
sys.exit(1)
if opts.trprobs_filepath:
trprobs_filepath = os.path.expanduser(os.path.expandvars(opts.trprobs_filepath))
if confirm_overwrite(filepath=trprobs_filepath, replace_without_asking=opts.replace):
trprobs_dest = open(trprobs_filepath, "w")
else:
sys.exit(1)
opts.calc_tree_probs = True
else:
trprobs_dest = None
opts.calc_tree_probs = False
if opts.split_edges_filepath:
split_edges_filepath = os.path.expanduser(os.path.expandvars(opts.split_edges_filepath))
if confirm_overwrite(filepath=split_edges_filepath, replace_without_asking=opts.replace):
split_edges_dest = open(split_edges_filepath, "w")
else:
sys.exit(1)
else:
split_edges_dest = None
if opts.from_newick_stream:
schema = "newick"
elif opts.from_nexus_stream:
schema = "nexus"
else:
schema = "nexus/newick"
###################################################
# Main work begins here: Count the splits
start_time = datetime.datetime.now()
master_split_distribution = None
if (support_filepaths is not None and len(support_filepaths) > 1) and _MP and opts.multiprocess:
if opts.multiprocess is not None:
if opts.multiprocess == "*":
num_processes = multiprocessing.cpu_count()
elif opts.multiprocess == "@":
num_processes = len(support_filepaths)
else:
try:
num_processes = int(opts.multiprocess)
except ValueError:
messenger.send_error(
"'%s' is not a valid number of processes (must be a positive integer)." % opts.multiprocess
)
sys.exit(1)
if num_processes <= 0:
messenger.send_error(
"Maximum number of processes set to %d: cannot run SumTrees with less than 1 process"
% num_processes
)
sys.exit(1)
if num_processes == 1:
messenger.send_warning(
"Running in parallel processing mode but limited to only 1 process: probably more efficient to run in serial mode!"
)
master_split_distribution, master_topology_counter = process_sources_parallel(
num_processes=num_processes,
support_filepaths=support_filepaths,
schema=schema,
is_rooted=opts.rooted_trees,
ignore_node_ages=not opts.calc_node_ages,
ultrametricity_precision=opts.ultrametricity_precision,
calc_tree_probs=opts.calc_tree_probs,
weighted_trees=opts.weighted_trees,
tree_offset=opts.burnin,
log_frequency=opts.log_frequency,
messenger=messenger,
)
else:
if _MP and opts.multiprocess is not None and len(support_filepaths) == 1:
messenger.send_warning(
"Parallel processing mode requested but only one source specified: defaulting to serial mode."
)
if opts.from_newick_stream or opts.from_nexus_stream:
support_filepaths = None
master_split_distribution, master_topology_counter = process_sources_serial(
support_filepaths=support_filepaths,
schema=schema,
is_rooted=opts.rooted_trees,
ignore_node_ages=not opts.calc_node_ages,
ultrametricity_precision=opts.ultrametricity_precision,
calc_tree_probs=opts.calc_tree_probs,
weighted_trees=opts.weighted_trees,
tree_offset=opts.burnin,
log_frequency=opts.log_frequency,
messenger=messenger,
)
###################################################
# Compose post-counting report
# if not splits counted or the taxon set was not populated for any reason,
# we just produce an empty block so we don't crash as we report nothing of interest
if master_split_distribution.taxon_set is None:
assert master_split_distribution.total_trees_counted == 0
master_split_distribution.taxon_set = dendropy.TaxonSet()
# taxon set to handle target trees
master_taxon_set = master_split_distribution.taxon_set
report = []
report.append(
"%d trees considered in total for split support assessment." % (master_split_distribution.total_trees_counted)
)
if opts.rooted_trees is None:
report.append("Tree rooting as given by tree statement (defaults to unrooted).")
elif opts.rooted_trees:
report.append("Trees treated as rooted.")
else:
report.append("Trees treated as unrooted.")
if opts.ultrametric_trees:
report.append("Trees are expected to be ultrametric.")
if opts.weighted_trees:
report.append("Trees treated as weighted (default weight = 1.0).")
else:
report.append("Trees treated as unweighted.")
n_taxa = len(master_taxon_set)
report.append("%d unique taxa across all trees." % n_taxa)
num_splits, num_unique_splits, num_nt_splits, num_nt_unique_splits = master_split_distribution.splits_considered()
report.append("%d unique splits out of %d total splits counted." % (num_unique_splits, num_splits))
report.append(
"%d unique non-trivial splits out of %d total non-trivial splits counted."
% (num_nt_unique_splits, num_nt_splits)
)
comments = []
comments.extend(report)
messenger.send_info("Split counting completed:")
messenger.send_info_lines(report, prefix=" - ")
###################################################
# Target tree and mapping
if not opts.support_as_percentages and opts.support_label_decimals < 2:
messenger.send_warning(
"Reporting support by proportions require that support will be reported to at least 2 decimal places"
)
opts.support_label_decimals = 2
tsum = treesum.TreeSummarizer()
tsum.add_node_metadata = not opts.suppress_summary_metadata
if opts.support_annotation_target == 1:
tsum.support_as_labels = True
tsum.support_as_edge_lengths = False
support_show = "indicated by node labels"
if tsum.add_node_metadata:
support_show += " and node metadata"
elif opts.support_annotation_target == 2:
tsum.support_as_labels = False
tsum.support_as_edge_lengths = True
support_show = "indicated by branch lengths"
if tsum.add_node_metadata:
support_show += " and node metadata"
elif opts.support_annotation_target == 0:
tsum.support_as_labels = False
tsum.support_as_edge_lengths = False
if tsum.add_node_metadata:
support_show = "indicated by node metadata (only)"
else:
support_show = "not indicated"
else:
raise Exception("Unexpected value for support annotation target: %s" % opts.support_annotation_target)
tsum.support_as_percentages = opts.support_as_percentages
tsum.support_label_decimals = opts.support_label_decimals
tsum.weighted_splits = opts.weighted_trees
if opts.support_as_percentages:
support_units = "Percentage"
else:
support_units = "Proportion (frequency or probability)"
support_summarization = "%s of support for each split %s" % (support_units, support_show)
tt_trees = []
support_comment_pattern = re.compile(r"support\s*=\s*[0-9.eE-]+,?", re.I)
if target_tree_filepath is not None:
messenger.send_info("Mapping support to target tree ...")
# if adding node metadata, we extract it from the target tree first
for tree in tree_source_iter(
stream=open(target_tree_filepath, "r"),
schema="nexus/newick",
taxon_set=master_taxon_set,
as_rooted=opts.rooted_trees,
extract_comment_metadata=tsum.add_node_metadata,
):
if opts.root_target:
if opts.outgroup:
pass
else:
tree.root_at_midpoint(splits=True)
if opts.rooted_trees and not tree.is_rooted:
messenger.send_error(
"Support trees are treated as rooted, but target tree is unrooted. Root target tree(s) and re-run, or run using the '--root-target' flag."
)
sys.exit(1)
# strip out existing support statement
# if tsum.add_node_metadata:
# for nd in tree.postorder_node_iter():
# for nd_comment_idx, comment in enumerate(nd.comments):
# nd.comments[nd_comment_idx] = support_comment_pattern.sub("", nd.comments[nd_comment_idx])
stree = tsum.map_split_support_to_tree(tree, master_split_distribution)
tt_trees.append(stree)
messenger.send_info("Parsed '%s': %d tree(s) in file" % (target_tree_filepath, len(tt_trees)))
comments.append("Split support mapped to trees in:")
comments.append(" - '%s' (%d trees)" % (os.path.abspath(target_tree_filepath), len(tt_trees)))
if opts.root_target:
if opts.outgroup:
comments.append("Target tree(s) rooted using outgroup: %s." % opts.outgroup)
else:
comments.append("Target tree(s) rooted at midpoint.")
comments.append(support_summarization + ".")
else:
messenger.send_info("Constructing clade consensus tree ...")
if opts.min_clade_freq > 1.0:
messenger.send_warning("Maximum frequency threshold for clade inclusion is 1.0: reset to 1.0.")
min_freq = 1.0
else:
min_freq = opts.min_clade_freq
stree = tsum.tree_from_splits(master_split_distribution, min_freq=min_freq, include_edge_lengths=False)
# include_edge_lengths=not opts.no_branch_lengths)
if opts.root_target:
stree.reroot_at_midpoint(update_splits=True)
report = []
report.append("Consensus tree (%f clade frequency threshold) constructed from splits." % min_freq)
tt_trees.append(stree)
if opts.root_target:
if opts.outgroup:
report.append("Consensus tree rooted using outgroup: %s." % opts.outgroup)
else:
report.append("Consensus tree rooted at midpoint.")
report.append(support_summarization + ".")
messenger.send_info_lines(report)
comments.extend(report)
if not opts.suppress_summary_metadata:
messenger.send_info("Summarizing node ages and lengths ...")
for stree in tt_trees:
tsum.annotate_nodes_and_edges(tree=stree, split_distribution=master_split_distribution)
if opts.edge_summarization is None:
if target_tree_filepath is not None:
opts.edge_summarization = "keep"
else:
if opts.ultrametric_trees:
opts.edge_summarization = "median-age"
else:
opts.edge_summarization = "mean-length"
if opts.edge_summarization is not None and opts.edge_summarization == "unweighted":
for stree in tt_trees:
for edge in stree.postorder_edge_iter():
edge.length = None
elif opts.edge_summarization is not None and opts.edge_summarization != "keep":
if opts.edge_summarization.startswith("mean"):
summary_func_desc = "mean"
summarization_func = lambda x: statistics.mean_and_sample_variance(x)[0]
else:
summary_func_desc = "median"
summarization_func = statistics.median
if opts.edge_summarization.endswith("age"):
messenger.send_info("Mapping node ages ...")
comments.append(
"Setting node ages of output tree(s) to %s ages of corresponding nodes of input trees."
% summary_func_desc
)
if opts.collapse_negative_edges:
comments.append("Parent node ages coerced to be at least as old as oldest daughter node age.")
collapse_negative_edges = True
allow_negative_edges = False
else:
comments.append("Parent node ages not adjusted: negative edge lengths allowed.")
collapse_negative_edges = False
allow_negative_edges = True
for stree in tt_trees:
tsum.summarize_node_ages_on_tree(
tree=stree,
split_distribution=master_split_distribution,
set_edge_lengths=True,
collapse_negative_edges=collapse_negative_edges,
allow_negative_edges=allow_negative_edges,
summarization_func=summarization_func,
)
elif opts.edge_summarization.endswith("length"):
messenger.send_info("Mapping edge lengths ...")
comments.append(
"Setting edge lengths of output tree(s) to %s length of corresponding edges of input trees."
% summary_func_desc
)
for stree in tt_trees:
tsum.summarize_edge_lengths_on_tree(
tree=stree, split_distribution=master_split_distribution, summarization_func=summarization_func
)
else:
comments.append("Not setting edge lengths on output tree(s).")
end_time = datetime.datetime.now()
###################################################
# RESULTS
messenger.send_info("Writing results ...")
final_run_report = []
final_run_report.append("Began at: %s." % (start_time.isoformat(" ")))
final_run_report.append("Ended at: %s." % (end_time.isoformat(" ")))
hours, mins, secs = str(end_time - start_time).split(":")
run_time = "Run time: %s hour(s), %s minute(s), %s second(s)." % (hours, mins, secs)
final_run_report.append(run_time)
output_dataset = dendropy.DataSet(dendropy.TreeList(tt_trees, taxon_set=master_taxon_set))
if opts.to_newick_format:
output_dataset.write(
output_dest,
"newick",
suppress_rooting=False,
suppress_edge_lengths=False,
unquoted_underscores=False,
preserve_spaces=False,
store_tree_weights=False,
suppress_annotations=False,
annotations_as_nhx=False,
suppress_item_comments=False,
suppress_leaf_taxon_labels=False,
suppress_leaf_node_labels=True,
suppress_internal_taxon_labels=False,
suppress_internal_node_labels=False,
node_label_element_separator=" ",
node_label_compose_func=None,
)
else:
if opts.include_taxa_block:
simple = False
else:
simple = True
if opts.include_meta_comments:
comment = []
try:
username = getpass.getuser()
except:
username = "******"
comment.append("%s %s by %s." % (_program_name, _program_version, _program_author))
comment.append("Using DendroPy Version %s by Jeet Sukumaran and Mark T. Holder." % dendropy.__version__)
python_version = sys.version.replace("\n", "").replace("[", "(").replace("]", ")")
comment.append("Running under Python %s on %s." % (python_version, sys.platform))
comment.append("Executed on %s by %s@%s." % (platform.node(), username, socket.gethostname()))
if support_filepaths is not None and len(support_filepaths) > 0:
comment.append("Basis of split support:")
for support_file in support_filepaths:
comment.append(" - '%s'" % os.path.abspath(support_file))
else:
comment.append("Basis of split support: trees read from standard input.")
comment.extend(final_run_report)
comment.extend(comments)
if opts.additional_comments:
comment.append("\n")
comment.append(opts.additional_comments)
output_dataset.write(
output_dest,
"nexus",
simple=simple,
file_comments=comment,
suppress_rooting=False,
suppress_edge_lengths=opts.edge_summarization == "unweighted",
unquoted_underscores=False,
preserve_spaces=False,
store_tree_weights=False,
suppress_annotations=False,
annotations_as_nhx=False,
suppress_item_comments=False,
suppress_leaf_taxon_labels=False,
suppress_leaf_node_labels=True,
suppress_internal_taxon_labels=False,
suppress_internal_node_labels=False,
node_label_element_separator=" ",
node_label_compose_func=None,
)
if trprobs_dest:
messenger.send_info("Writing tree probabilities ...")
tree_list = dendropy.TreeList(taxon_set=master_split_distribution.taxon_set)
tree_freqs = master_topology_counter.calc_tree_freqs(tree_list.taxon_set)
cumulative_prob = 0.0
for idx, (tree, (count, prop)) in enumerate(tree_freqs.items()):
tree_list.append(tree)
cumulative_prob += prop
tree.probability = prop
tree.count = count
tree.cumulative_probability = cumulative_prob
tree.annotations.add_bound_attribute("count")
tree.annotations.add_bound_attribute("probability")
tree.annotations.add_bound_attribute("cumulative_probability")
tree.label = "Tree%d" % (idx + 1)
tree_list.write_to_stream(
trprobs_dest,
"nexus",
simple=simple,
suppress_rooting=True,
suppress_edge_lengths=True,
suppress_internal_labels=True,
unquoted_underscores=False,
preserve_spaces=False,
store_tree_weights=False,
suppress_annotations=False,
annotations_as_nhx=False,
suppress_item_comments=True,
suppress_leaf_taxon_labels=False,
suppress_leaf_node_labels=True,
suppress_internal_taxon_labels=False,
suppress_internal_node_labels=False,
node_label_element_separator=" ",
node_label_compose_func=None,
)
if split_edges_dest:
messenger.send_info("Writing split edge lengths ...")
for split in master_split_distribution.splits:
row = []
row.append(master_split_distribution.taxon_set.split_as_newick_string(split))
for edge_length in master_split_distribution.split_edge_lengths[split]:
row.append("%s" % edge_length)
split_edges_dest.write("%s\n" % ("\t".join(row)))
if not opts.output_filepath:
pass
else:
messenger.send_info("Results written to: '%s'." % (output_fpath))
###################################################
# WRAP UP
messenger.send_info("Summarization completed.")
messenger.send_info_lines(final_run_report)
messenger.silent = True
def tree_from_splits(self,
split_distribution,
min_freq=0.5,
include_edge_lengths=True):
"""Returns a consensus tree from splits in `split_distribution`.
If include_edge_length_var is True, then the sample variance of the
edge length will also be calculated and will be stored as
a length_var attribute.
"""
taxon_set = split_distribution.taxon_set
taxa_mask = taxon_set.all_taxa_bitmask()
if self.weighted_splits:
split_freqs = split_distribution.weighted_split_frequencies
else:
split_freqs = split_distribution.split_frequencies
is_rooted = split_distribution.is_rooted
#include_edge_lengths = self.support_as_labels and include_edge_lengths
if self.support_as_edge_lengths and include_edge_lengths:
raise Exception(
"Cannot map support as edge lengths if edge lengths are to be set on consensus tree"
)
to_try_to_add = []
_almost_one = lambda x: abs(x - 1.0) <= 0.0000001
for s, freq in split_freqs.iteritems():
if (min_freq is None) or (freq > min_freq) or (
_almost_one(min_freq) and _almost_one(freq)):
to_try_to_add.append((freq, s))
to_try_to_add.sort(reverse=True)
splits_for_tree = [i[1] for i in to_try_to_add]
con_tree = treesplit.tree_from_splits(splits=splits_for_tree,
taxon_set=taxon_set,
is_rooted=is_rooted)
treesplit.encode_splits(con_tree)
if include_edge_lengths:
split_edge_lengths = {}
for split, edges in split_distribution.split_edge_lengths.items():
if len(edges) > 0:
mean, var = mean_and_sample_variance(edges)
elen = mean
else:
elen = None
split_edge_lengths[split] = elen
else:
split_edge_lengths = None
for node in con_tree.postorder_node_iter():
split = node.edge.split_bitmask
if split in split_freqs:
self.map_split_support_to_node(
node=node, split_support=split_freqs[split])
if include_edge_lengths and split in split_distribution.split_edge_lengths:
edges = split_distribution.split_edge_lengths[split]
if len(edges) > 0:
mean, var = mean_and_sample_variance(edges)
elen = mean
else:
elen = None
node.edge.length = elen
return con_tree
