def eval_decmodel(s):
d = eval(s)
v = d["lagrange_version"]
if v != VERSION:
print >> sys.stderr, "***Version mismatch: %s (expecting %s)***" \
% (v, VERSION)
print >> sys.stderr, "Things may not work as expected"
for x in ("area_labels", "taxon_range_data", "newick_trees"):
assert x in d, "required for analysis, but missing: %s" % x
labels = d["area_labels"]
nareas = len(labels)
data = d["taxon_range_data"]
maxareas = d.get("max_range_size") or len(labels)
dists = d["ranges"]
excluded = d["excluded_ranges"]
dm = d["area_dispersal"]
periods = d["dispersal_durations"]
model = DECModel(nareas, labels, periods=periods, dists=dists)
model.Dmask[:] = dm
trees = d["newick_trees"]
newicktree = trees[0]["newick"]
nodelabels = trees[0]["included"]
root_age = trees[0]["root_age"] or None
tree = Tree(newicktree, periods=periods, root_age=root_age)
tree.set_default_model(model)
tree.set_tip_conditionals(data)
base_rates = d["base_rates"]
if base_rates == "__estimate__":
pass
else:
base_rates = (d["base_rates"]["dispersal"], d["base_rates"]["extinction"])
return model, tree, data, nodelabels, base_rates
