def makeCloud(tips, RF_norm_cloud, name, cloud_size, starting_trees):
# Make cluster of trees around each starting tree
# Get starting trees parsed
t1 = starting_trees[0]
t2 = starting_trees[1]
# Calculate number of NNI moves based on desired normalized RF distance.
RF_max = 2 * (tips - 2)
NNI_moves_cloud = int((RF_max * RF_norm_cloud) / 2)
if NNI_moves_cloud == 0:
NNI_moves_cloud = 1
# Make a cloud for each starting tree
c_size = int(cloud_size) - 1
print("Making clouds...")
# Make clouds
cluster1 = readTree.NNI_mult_trees(in_tree=t1,
num_out_trees=c_size,
num_nni_moves=NNI_moves_cloud,
out='list')
cluster2 = readTree.NNI_mult_trees(in_tree=t2,
num_out_trees=c_size,
num_nni_moves=NNI_moves_cloud,
out='list')
tree_list = [cluster1, cluster2]
# Make a nexus file with starting trees and cloud trees
readTree.list_to_out(tree_list, '%s_cloud.tree' % name)
############################################################
# Make cluster of trees around each starting tree
############################################################
# Calculate number of NNI moves based on desired normalized RF distance.
NNI_moves_cloud = int((RF_max * RF_norm_cloud) / 2)
if NNI_moves_cloud == 0:
NNI_moves_cloud = 1
# Make a cloud for each starting tree
c_size = int(cloud_size) - 1
print("Making clouds...")
# Make clouds
cluster1 = readTree.NNI_mult_trees(in_tree=t1,
num_out_trees=c_size,
num_nni_moves=NNI_moves_cloud,
out='list')
cluster2 = readTree.NNI_mult_trees(in_tree=t2,
num_out_trees=c_size,
num_nni_moves=NNI_moves_cloud,
out='list')
# Make a nexus file with starting trees and cloud trees
readTree.list_to_out(cluster1, cluster2, '%s_cloud.tree' % name)
############################################################
# Print info to log file
############################################################
print("Calculating stats on trees...")
# Calculate emperical distance between two start trees
RF_emp = readTree.rf_unweighted(t1, t2, normalized='T')[1]
# Calculate average density of each cloud
in_tree_object = readTree.rand_tree(tips=10,brl_avg=1,brl_std=None,verbose='T') ############################## # Make moves ############################## # Print newick string in_tree_object.newick(in_tree_object.root) # Make NNI move new_tree_object = readTree.NNI(orig_tree=in_tree_object,node_choice='exponential') # Make multiple moves on a single tree new_tree_object = readTree.NNI_mult_moves(in_tree=in_tree,num_moves=1,node_choice='exponential',no_dup_start_tree='T') # Make multiple trees, each with one NNI move from starting tree. Output as nexus file. readTree.NNI_mult_trees(in_tree=in_tree,num_out_trees=10,num_nni_moves=2,out_file='outFile2.t',node_choice='random',no_dup_start_tree='T') ############################## # Look at and compare trees ############################## # Print newick string new_tree_object.newick(new_tree_object.root) # View tree in terminal along with newick string readTree.view_phylo(new_tree_object) # Check that all trees have the right number of moves from start tree readTree.compare_tree_file(in_file='outFile1.t',total_trees=11,distance_metric="uRF") # Compare RF distance between two trees.
