def showTreeInGrid(gid,biome,grid_level=14,taxonomic_level='sp'):
"""
Performs a selection, spatial filter and returns an image.
grid_level is the grid layer.
taxonomic_level is the taxonomic level to be shown. Options are:
sp, gns, fam, ord, cls, phy, king
"""
mesh = initMesh(grid_level)
try:
cell = mesh.objects.get(id=id)
except:
logger.error("Selected id does not exist in selected grid")
return None
gb=GriddedTaxonomy(biome,cell,generate_tree_now=True)
forest = gb.taxonomies[0].forest
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 360
forest[taxonomic_level].show(tree_style=ts)
return 'Parece que se tiene que ver algo'
def ete_tree(aln):
"""Tree showing alleles"""
from ete2 import Tree, PhyloTree, TreeStyle, NodeStyle
t = Tree('temp.dnd')
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180
ts.arc_span = 180
cutoff = 0.25
def func(node):
if node.name == 'NoName': #or not node.name in metric:
return False
#if metric[node.name]<=cutoff:
# return True
matches = filter(func, t.traverse())
print(len(matches), "nodes have distance <=%s" % cutoff)
nst1 = NodeStyle()
nst1["bgcolor"] = "Yellow"
for n in matches:
n.set_style(nst1)
nst2 = NodeStyle()
nst2["bgcolor"] = "LightGreen"
#hlanodes = [t.get_leaves_by_name(name=r)[0] for r in refalleles]
#for n in hlanodes:
# n.set_style(nst2)
t.show(tree_style=ts)
return
def build_vis(): ts = TreeStyle() ts.mode = "c" ts.arc_start = 0 # 0 degrees = 3 o'clock ts.arc_span = 360 ts.layout_fn = my_layout # Use custom layout return ts
def ETETree(seqs, ref, metric):
"""Tree showing bola alleles covered by tepitope"""
from ete2 import Tree,PhyloTree,TreeStyle,NodeStyle
aln = Genome.clustalAlignment(seqs=seqs)
t = Tree('temp.dnd')
#t.set_outgroup(t&ref)
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180
ts.arc_span = 180
cutoff=0.25
def func(node):
if node.name=='NoName' or not node.name in metric:
return False
if metric[node.name]<=cutoff:
return True
matches = filter(func, t.traverse())
print len(matches), "nodes have distance <=%s" %cutoff
nst1 = NodeStyle()
nst1["bgcolor"] = "Yellow"
for n in matches:
n.set_style(nst1)
nst2 = NodeStyle()
nst2["bgcolor"] = "LightGreen"
hlanodes = [t.get_leaves_by_name(name=r)[0] for r in refalleles]
for n in hlanodes:
n.set_style(nst2)
t.show(tree_style=ts)
return
def showTreeInGrid(gid, biome, grid_level=14, taxonomic_level='sp'):
"""
Performs a selection, spatial filter and returns an image.
grid_level is the grid layer.
taxonomic_level is the taxonomic level to be shown. Options are:
sp, gns, fam, ord, cls, phy, king
"""
mesh = initMesh(grid_level)
try:
cell = mesh.objects.get(id=id)
except:
logger.error("Selected id does not exist in selected grid")
return None
gb = GriddedTaxonomy(biome, cell, generate_tree_now=True)
forest = gb.taxonomies[0].forest
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 360
forest[taxonomic_level].show(tree_style=ts)
return 'Parece que se tiene que ver algo'
def setUp(self):
tree = Tree()
root = tree.get_tree_root()
root.dist = 0
root.name = "root"
node = root.add_child(name="Left")
node.add_child(name="Alpha")
node.add_child(name="Beta")
node = root.add_child(name="Right")
node.add_child(name="Gamma")
node.add_child(name="Delta")
for desc in tree.iter_descendants():
desc.dist = 0
ts = TreeStyle()
ts.show_leaf_name = True
ts.show_branch_length = False
ts.mode = "c"
ts.arc_start = 0
ts.arc_span = 360
self.circular_style = ts
self.exampleTree = tree
self.alignment = MultipleSeqAlignment([
SeqRecord(Seq("AAG", generic_dna), id="Alpha"),
SeqRecord(Seq("AGA", generic_dna), id="Beta"),
SeqRecord(Seq("AAA", generic_dna), id="Gamma"),
SeqRecord(Seq("GGA", generic_dna), id="Delta"),
])
def ETETree(seqs, ref, metric):
"""Tree showing bola alleles covered by tepitope"""
from ete2 import Tree, PhyloTree, TreeStyle, NodeStyle
aln = Genome.clustalAlignment(seqs=seqs)
t = Tree('temp.dnd')
#t.set_outgroup(t&ref)
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180
ts.arc_span = 180
cutoff = 0.25
def func(node):
if node.name == 'NoName' or not node.name in metric:
return False
if metric[node.name] <= cutoff:
return True
matches = filter(func, t.traverse())
print len(matches), "nodes have distance <=%s" % cutoff
nst1 = NodeStyle()
nst1["bgcolor"] = "Yellow"
for n in matches:
n.set_style(nst1)
nst2 = NodeStyle()
nst2["bgcolor"] = "LightGreen"
hlanodes = [t.get_leaves_by_name(name=r)[0] for r in refalleles]
for n in hlanodes:
n.set_style(nst2)
t.show(tree_style=ts)
return
def showTreeInGrid(request):
"""
.. showTreeInGrid:
Performs a selection, spatial filter and returns an image.
Parameters in GET variable
===========================
grid_level : int
The grid layer.
taxonomic_level : string
The taxonomic level to be shown.
Options are: sp, gns, fam, ord, cls, phy, king
Returns
=======
HTTP RESPONSE
with an image showing the tree.
See figure:
.. image::
"""
from ete2.treeview import drawer
from PyQt4 import QtCore
import ipdb
response = HttpResponse()
get = request.GET
try:
gid = int(get['gid'])
grid_level = int(get['g_l'])
taxonomic_level = get['tax_lvl']
except:
response.content='Bad request. Check GET variable definitions'
response.status_code = 500
return response
biome = Occurrence.objects.all()
mesh = initMesh(grid_level)
try:
cell = mesh.objects.get(id=gid)
except:
logger.error("Selected id does not exist in selected grid")
return None
import os.path
head_path = settings.PATH_IMAGES
filename = "%s-%s-%s.png" %(grid_level,gid,taxonomic_level)
file_ = head_path+filename
logger.info('Writing in: %s'%file_)
if not os.path.isfile(file_):
logger.info("The image doens't exist")
gb=GriddedTaxonomy(biome,cell,generate_tree_now=True)
forest = gb.taxonomies[0].forest
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 360
try:
#ipdb.set_trace()
forest[taxonomic_level].render(file_, w=100, units="mm",tree_style=ts)
#drawer.exit_gui(1, 1)
#logger.info(QtCore.QThreadPool)
del(forest[taxonomic_level])
except:
logger.error('Something went wrong with the image rendering')
#del(forest)
#ipdb.set_trace()
template = get_template('base.html')
html = template.render(Context({'gid':gid,'taxonomic_level':taxonomic_level,'grid_level':grid_level,'image_path':filename}))
response.content=(html)
#response.content=str(forest[taxonomic_level])
response.status_code = 200
return response
def showAllLevelsInTreeInGrid(request):
"""
Performs a selection, spatial filter and returns an image.
grid_level is the grid layer.
taxonomic_level is the taxonomic level to be shown. Options are:
sp, gns, fam, ord, cls, phy, king
"""
import ipdb
response = HttpResponse()
get = request.GET
try:
gid = int(get['gid'])
grid_level = int(get['g_l'])
names = int(get['names'])
if names > 0:
only_id = False
else:
only_id = True
#taxonomic_level = get['tax_lvl']
except:
response.content='Bad request. Check GET variable definitions'
response.status_code = 500
return response
biome = Occurrence.objects.all()
mesh = initMesh(grid_level)
try:
cell = mesh.objects.get(id=gid)
except:
logger.error("Selected id does not exist in selected grid")
return None
import os.path
tax_levels = ['sp','gns','fam','cls','ord','phy','kng']
tax_keys = {'sp':'1.Species','gns':'2. Genera','fam':'3. Families','ord':'4. Orders','cls':'5. Classes','phy':'6. Phyla','kng':'7. Kingdoms'}
rich_keys = { 'oc':'occurrences','sp' :'species','gns':'genera','fam':'families','cls':'classes','ord':'orders','phy':'phyla','kng':'kingdoms'}
img_paths = {}
#THIS IS VERY VERY WRONG AND I WOULD SUGGEST A REFACTORING like the use of a binary written copy in disk about the object in question (cached)
gb=GriddedTaxonomy(biome,cell,generate_tree_now=True,use_id_as_name=only_id)
taxonomy = gb.taxonomies[0]
#ipdb.set_trace()
mat_complex = taxonomy.calculateIntrinsicComplexity()
for taxonomic_level in tax_levels:
head_path = settings.PATH_IMAGES
filename = "%s-%s-%s.png" %(grid_level,gid,taxonomic_level)
file_ = head_path+filename
logger.info('Writing in: %s'%file_)
if not os.path.isfile(file_):
logger.info("The image doens't exist")
try:
if gb not in locals():
#gb=GriddedTaxonomy(biome,cell,generate_tree_now=True)
logger.info("Gridded taxonomy doesn't found")
except:
gb=GriddedTaxonomy(biome,cell,generate_tree_now=True,use_id_as_name=only_id)
forest = taxonomy.forest
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 360
ts.show_scale = False
try:
#ipdb.set_trace()
forest[taxonomic_level].render(file_,h=500, w=500, units="px",tree_style=ts)
#drawer.exit_gui(1, 1)
#logger.info(QtCore.QThreadPool)
#del(forest[taxonomic_level])
except:
logger.error('Something went wrong with the image rendering')
img_paths[taxonomic_level] = {'name': tax_keys[taxonomic_level],'path':filename,'richness':taxonomy.richness[rich_keys[taxonomic_level]]}
else:
img_paths[taxonomic_level] = {'name': tax_keys[taxonomic_level],'path':filename,'richness':taxonomy.richness[rich_keys[taxonomic_level]]}
#del(forest)
#
#dic_richness = gb.taxonomies[0].richness
det_complex = gb.taxonomies[0].vectorIntrinsic
template = get_template('base.html')
submatrices = map(lambda i : mat_complex[0:i,0:i],range(1,len(mat_complex)))
#ipdb.set_trace()
import numpy as np
tras = map(lambda mat : np.linalg.eigvals(mat),submatrices)
#ipdb.set_trace()
try:
eigenv = np.linalg.eigvals(mat_complex).tolist()
svd = np.linalg.svd(mat_complex)
except:
eigenv =[]
svd = [[],[],[]]
#ipdb.set_trace()
html = template.render(Context({'gid':gid,'taxonomic_level':taxonomic_level,'grid_level':grid_level,'image_path':sorted(img_paths.itervalues()),'complexity':mat_complex.tolist(),'vect_comp':det_complex,'eigenv':eigenv,'left_eig_vect':svd[0].tolist(),'svd':svd[1].tolist(),'right_eig_vect':svd[2].tolist()}))
response.content=(html)
#response.content=str(forest[taxonomic_level])
response.status_code = 200
return response
#faces.add_face_to_node(f, node, 0, position="branch-right")
f.border.width = 0
node.img_style["size"] = 10
node.img_style["shape"] = "square"
node.img_style["bgcolor"] = random_color()
node.img_style["hz_line_width"] = 0
node.img_style["vt_line_width"] = 0
#if node.is_leaf():
# f = faces.CircleFace(50, "red")
# faces.add_face_to_node(f, node, 0, position="aligned")
ts = TreeStyle()
ts.mode = "c"
ts.arc_span = 360
ts.layout_fn = layout
ts.show_leaf_name = False
ts.show_border = True
ts.draw_guiding_lines = False
ts.show_scale = True
#ts.scale = 60
t = Tree()
t.dist = 0
t.size = 0, 0
for x in xrange(100):
n = t.add_child()
n = n.add_child()
n = n.add_child()
n2 = n.add_child()
if __name__ == "__main__":
full_tree = Tree('swisstree_speciestree.nhx')
for leaf in full_tree:
fields = leaf.name.split("__")
name = fields[1].replace('_', ' ')
code = "%s" %fields[0].strip()
leaf.orig_name = leaf.name
leaf.name = code
# basic tree styling
ts = TreeStyle()
ts.show_leaf_name = False
ts.layout_fn = layout
ts.arc_span = 340
ts.show_scale = False
# Make a pruned version of the tree
pruned_tree = full_tree.copy()
valid_codes = set(['CANAL', 'CHLAA', 'KORCO', 'IXOSC', 'ORNAN', 'BACTN',
'RHOBA', 'GLOVI', 'PSEAE', 'METJA', 'DICTD', 'METAC', 'MYCTX', 'PHANO',
'HALSA', 'TRIVA', 'XENTR', 'MONBE', 'ASPFU', 'BACSU', 'GIAIC', 'CIOIN',
'ECOLI', 'SCHPO', 'RAT', 'USTMA', 'HUMAN', 'MONDO', 'SCHMA', 'DANRE',
'MOUSE', 'THEKO', 'STRCO', 'CAEEL', 'THEMA', 'BOVIN', 'GEOSL', 'NEUCR',
'CANFA', 'BRADU', 'MACMU', 'ARATH', 'PHYPA', 'SYNY3', 'NEMVE', 'DROME',
'PLAF7', 'CHICK', 'BRAFL', 'YARLI', 'LEIMA', 'PANTR', 'FUSNN', 'TAKRU',
'LEPIN', 'DEIRA', 'SCLS1', 'DICDI', 'YEAST', 'CRYNJ', 'SULSO', 'THAPS',
'THEYD', 'AQUAE', 'ANOGA', 'CHLTR'])
target_codes = (set(full_tree.get_leaf_names()) & valid_codes)
pruned_tree.prune(target_codes)
#!/usr/bin/python # drawunrootedcircular.py # Use ete2 to render an unrooted tree from an input Newick formatted tree file. # Render the tree as circular. # sys.argv[1] -- filename for tree file # sys.argv[2] -- filename for output .png file import sys from ete2 import Tree, TreeStyle if( len(sys.argv) != 3 ): print "Usage: python drawunrootedcircular.py <Newick_file> <Tree_png>" exit(-1) t = Tree(sys.argv[1]) c = TreeStyle() c.mode = "c" c.scale = 50 c.arc_start = -90 c.arc_span = 360 t.render(sys.argv[2], w=720, units="px", tree_style=c)
#from models import Count,Sum,Avg
from django.contrib.gis.db.models import Extent, Union, Collect,Count,Min
from gbif.models import Specie,Genus,Family,Order,Class,Phylum,Kingdom
from mesh.models import NestedMesh
from django.contrib.gis.db.models.query import GeoQuerySet
logger = logging.getLogger('biospatial.gbif.general_test')
import biospatial.settings as settings
# Create your tests here.
from ete2 import Tree, TreeStyle
t = Tree()
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 360
from gbif.taxonomy import Taxonomy,embedTaxonomyInGrid,embedTaxonomyInNestedGrid,NestedTaxonomy
def createShapefile(taxonomy_list,name='default_name',store='out_maps'):
"""
This function creates a shapefile for a given list of Taxonomies.
Do note that the list of taxonomies is a mapping to the cells in a mesh.
"""
#Method for generating the shapefile object
from osgeo import ogr
#from shapely.geometry import Polygon
# Now convert it to a shapefile with OGR
#f = faces.AttrFace("name", fsize=random.randint(20,20))
faces.add_face_to_node(f, node, 0, position="aligned")
f.border.width = 0
#f = faces.CircleFace(20, "red")
#f = faces.AttrFace("name", fsize=20)
f = faces.TextFace("NAME", fsize=10)
#faces.add_face_to_node(f, node, 0, position="branch-right")
f.border.width = 0
#node.img_style["bgcolor"] = random_color()
#Tree().show()
ts = TreeStyle()
ts.mode = "c"
ts.layout_fn = layout
ts.show_leaf_name = False
ts.arc_span = 340
ts.arc_start = -70
#ts.allow_face_overlap = True
#ts.show_branch_length = True
ts.draw_guiding_lines = False
ts.optimal_scale_level = "mid"
ts.extra_branch_line_color = "red"
ts.root_opening_factor = 0.50
ts.show_border = True
ts.scale = None
t = Tree()
t.populate(200, random_branches=True, branch_range=(0, 0))
t.dist = 0.0
dists = [n.dist for n in t.traverse() if n.dist != 0]
#print max(dists), min(dists)
t.write(outfile="test.nw")
for e in old_edges:
to = e[1]
dist = e[2]["weight"]
if dist < r:
RadiusGraph.add_edge(n, to, weight=dist )
nodes = RadiusGraph.nodes()
total_radius = sum(map(lambda x: RadiusGraph.node[x]["weight"], nodes))
average_radius = total_radius/float(len(nodes))
partgraph = partition(RadiusGraph)
print json.dumps(partgraph)
source = str(partgraph)+";"
t = Tree(source)
ts = TreeStyle()
ts.show_leaf_name = True
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 180
t.show(tree_style=ts)
#pos = nx.spring_layout(partgraph,weight="weight")
#nx.draw(partgraph,pos)
#nx.draw(RadiusGraph,pos)
#end = time.time()
#print end-start
#plt.show()
