def get_form():
"""
@return: the body of a form
"""
form_objects = [
Form.Integer('ntaxa',
'number of taxa for distance matrix sampling',
20,
low=4,
high=20),
Form.Integer('seqlen',
'sequence length for distance matrix sampling',
200,
low=100,
high=10000),
Form.Integer('nsamples', 'number of samples', 10, low=1, high=1000),
Form.RadioGroup('tree_sampling', 'branch length distribution', [
Form.RadioItem('pachter_length', str(BranchLenSampler.Pachter()),
True),
Form.RadioItem('exponential_length',
str(BranchLenSampler.Exponential())),
Form.RadioItem('uniform_length_a', str(
BranchLenSampler.UniformA())),
Form.RadioItem('uniform_length_b', str(
BranchLenSampler.UniformB()))
])
]
return form_objects
def get_form():
"""
@return: the body of a form
"""
form_objects = [
Form.Integer('length', 'sequence length', 1000, low=10, high=20000),
Form.Integer('ntaxa', 'number of taxa', 20, low=4, high=20),
Form.RadioGroup('tree_sampling', 'branch length distribution', [
Form.RadioItem('pachter_length', str(BranchLenSampler.Pachter()),
True),
Form.RadioItem('exponential_length',
str(BranchLenSampler.Exponential())),
Form.RadioItem('uniform_length_a', str(
BranchLenSampler.UniformA())),
Form.RadioItem('uniform_length_b', str(
BranchLenSampler.UniformB()))
]),
Form.RadioGroup('first_method', 'first estimation method', [
Form.RadioItem('first_nj', 'neighbor joining', True),
Form.RadioItem('first_modnj', 'modified neighbor joining'),
Form.RadioItem('first_specnj', 'spectral reconstruction')
]),
Form.RadioGroup('second_method', 'second estimation method', [
Form.RadioItem('second_nj', 'neighbor joining'),
Form.RadioItem('second_modnj', 'modified neighbor joining'),
Form.RadioItem('second_specnj', 'spectral', True)
])
]
return form_objects
def get_response_content(fs):
nseconds = 2
ntaxa = fs.ntaxa
# define the branch length sampler
if fs.pachter_length:
branch_length_sampler = BranchLenSampler.Pachter()
elif fs.exponential_length:
branch_length_sampler = BranchLenSampler.Exponential()
elif fs.uniform_length_a:
branch_length_sampler = BranchLenSampler.UniformA()
elif fs.uniform_length_b:
branch_length_sampler = BranchLenSampler.UniformB()
return process(ntaxa, nseconds, branch_length_sampler) + '\n'
def main(options):
assert 0 <= options.nseconds
assert 4 <= options.ntaxa <= 20
assert 10 <= options.length <= 10000
branch_length_sampler = BranchLenSampler.Pachter()
print process(options.ntaxa, options.length, options.nseconds,
branch_length_sampler, True, True, True, True)
def get_response_content(fs):
nseconds = 2
length = fs.length
ntaxa = fs.ntaxa
# define the branch length sampler
if fs.pachter_length:
branch_length_sampler = BranchLenSampler.Pachter()
elif fs.exponential_length:
branch_length_sampler = BranchLenSampler.Exponential()
elif fs.uniform_length_a:
branch_length_sampler = BranchLenSampler.UniformA()
elif fs.uniform_length_b:
branch_length_sampler = BranchLenSampler.UniformB()
response_text = process(ntaxa, length, nseconds, branch_length_sampler,
fs.nj, fs.modified_nj, fs.all_spectral,
fs.one_spectral)
return response_text + '\n'
def get_response_content(fs):
nseconds = 2
length = fs.length
ntaxa = fs.ntaxa
# define the branch length sampler
if fs.pachter_length:
branch_length_sampler = BranchLenSampler.Pachter()
elif fs.exponential_length:
branch_length_sampler = BranchLenSampler.Exponential()
elif fs.uniform_length_a:
branch_length_sampler = BranchLenSampler.UniformA()
elif fs.uniform_length_b:
branch_length_sampler = BranchLenSampler.UniformB()
# define the first builder
if fs.first_nj:
splitter = BuildTreeTopology.split_nj
updater = BuildTreeTopology.update_nj
first_builder = Builder(splitter, updater, 'nj')
elif fs.first_modnj:
splitter = BuildTreeTopology.split_nj
updater = BuildTreeTopology.update_using_laplacian
first_builder = Builder(splitter, updater, 'modnj')
elif fs.first_specnj:
splitter = BuildTreeTopology.split_using_eigenvector_with_nj_fallback
updater = BuildTreeTopology.update_using_laplacian
first_builder = Builder(splitter, updater, 'specnj')
# define the second builder
if fs.second_nj:
splitter = BuildTreeTopology.split_nj
updater = BuildTreeTopology.update_nj
second_builder = Builder(splitter, updater, 'nj')
elif fs.second_modnj:
splitter = BuildTreeTopology.split_nj
updater = BuildTreeTopology.update_using_laplacian
second_builder = Builder(splitter, updater, 'modnj')
elif fs.second_specnj:
splitter = BuildTreeTopology.split_using_eigenvector_with_nj_fallback
updater = BuildTreeTopology.update_using_laplacian
second_builder = Builder(splitter, updater, 'specnj')
builders = [first_builder, second_builder]
response_text = process(ntaxa, length, nseconds, builders,
branch_length_sampler)
return response_text
def main(options):
#FIXME use argparse and a nonnegative type instead of the assertion
assert 0 <= options.nseconds
sampling_function = BranchLenSampler.ShortAscii(
options.allow_integers, options.allow_reciprocals)
tree_search = SixLeafSearch()
tree_search.informative_children = options.informative_children
tree_search.force_difference = options.force_difference
tree_search.informative_full_split = options.informative_full_split
tree_search.invalid_dendrogram = options.invalid_dendrogram
print do_tree_search(tree_search, options.nseconds, sampling_function)
def get_response_content(fs):
# allow only two seconds for web access
nseconds = 2
# read the options
ntaxa = fs.ntaxa
seqlen = fs.seqlen
nsamples = fs.nsamples
# define the branch length sampler
if fs.pachter_length:
branch_length_sampler = BranchLenSampler.Pachter()
elif fs.exponential_length:
branch_length_sampler = BranchLenSampler.Exponential()
elif fs.uniform_length_a:
branch_length_sampler = BranchLenSampler.UniformA()
elif fs.uniform_length_b:
branch_length_sampler = BranchLenSampler.UniformB()
# return the response
response_text = process(ntaxa, nseconds, seqlen, nsamples,
branch_length_sampler, False)
return response_text + '\n'
def get_form():
"""
@return: the body of a form
"""
form_objects = [
Form.Integer('ntaxa',
'number of taxa for distance matrix sampling',
20,
low=4,
high=20),
Form.Integer('nlengths',
'number of sequence lengths to consider (must be odd)',
9,
low=3,
high=99),
Form.Integer('nsamples',
'number of samples per sequence length',
5,
low=1,
high=99),
Form.RadioGroup('tree_sampling', 'branch length distribution', [
Form.RadioItem('pachter_length', str(BranchLenSampler.Pachter()),
True),
Form.RadioItem('exponential_length',
str(BranchLenSampler.Exponential())),
Form.RadioItem('uniform_length_a', str(
BranchLenSampler.UniformA())),
Form.RadioItem('uniform_length_b', str(
BranchLenSampler.UniformB()))
]),
Form.RadioGroup(
'distance_options', 'recursive matrix construction method', [
Form.RadioItem(
'pruning_like',
'go through the Laplacian, like Felsenstein pruning',
True),
Form.RadioItem(
'nj_like', 'directly use distances, like neighbor joining')
])
]
return form_objects
def main():
ntaxa = 20
length = 200
nseconds = 5 * 60
print ntaxa, 'taxa per tree'
print length, 'nucleotides per sequence'
print
branch_length_samplers = (BranchLenSampler.Pachter(),
BranchLenSampler.UniformB())
for i, branch_length_sampler in enumerate(branch_length_samplers):
print 'group', i + 1
print branch_length_sampler
print
builders = [
Builder(BuildTreeTopology.split_nj, BuildTreeTopology.update_nj,
'nj'),
Builder(BuildTreeTopology.split_using_eigenvector_with_nj_fallback,
BuildTreeTopology.update_using_laplacian, 'specnj')
]
print process(ntaxa, length, nseconds, builders, branch_length_sampler)
print
def get_response_content(fs):
nseconds = 2
sampling_function = BranchLenSampler.ShortAscii(
fs.allow_integers, fs.allow_reciprocals)
if fs.six_leaves:
tree_search = SixLeafSearch()
elif fs.seven_leaves:
tree_search = SevenLeafSearch()
tree_search.informative_children = fs.informative_children
tree_search.force_difference = fs.force_difference
tree_search.informative_full_split = fs.informative_full_split
tree_search.invalid_dendrogram = fs.invalid_dendrogram
return do_tree_search(tree_search, nseconds, sampling_function) + '\n'
def get_form():
"""
@return: the body of a form
"""
form_objects = [
Form.Integer('length',
'sequence length for distance matrix sampling',
1000,
low=10,
high=20000),
Form.Integer('ntaxa',
'number of taxa for distance matrix sampling',
20,
low=4,
high=20),
Form.RadioGroup('tree_sampling', 'branch length distribution', [
Form.RadioItem('pachter_length', str(BranchLenSampler.Pachter()),
True),
Form.RadioItem('exponential_length',
str(BranchLenSampler.Exponential())),
Form.RadioItem('uniform_length_a', str(
BranchLenSampler.UniformA())),
Form.RadioItem('uniform_length_b', str(
BranchLenSampler.UniformB()))
]),
Form.CheckGroup('method_options', 'compare these methods', [
Form.CheckItem('nj', 'neighbor joining', True),
Form.CheckItem('modified_nj',
'neighbor joining with laplacian updates', True),
Form.CheckItem('all_spectral',
'spectral with laplacian updates and nj fallback',
True),
Form.CheckItem(
'one_spectral',
'an initial spectral split followed by neighbor joining', True)
])
]
return form_objects
def main(options):
# validate the options
assert 0 <= options.nseconds
assert 4 <= options.ntaxa <= 30
assert 1 <= options.seqlen
assert 1 <= options.nsamples
branch_length_sampler = BranchLenSampler.UniformB()
#branch_length_sampler = BranchLenSampler.Pachter()
use_pbar = True
try:
print process(options.ntaxa, options.nseconds, options.seqlen,
options.nsamples, branch_length_sampler, use_pbar)
except HandlingError as e:
print 'error:', e
def get_response_content(fs):
# allow only two seconds for web access
nseconds = 2
# read the options
ntaxa = fs.ntaxa
nlengths = fs.nlengths
nsamples = fs.nsamples
nj_like = fs.nj_like
# do extra validation
if nlengths % 2 == 0:
raise HandlingError('the number of sequence lengths must be odd')
# define the branch length sampler
if fs.pachter_length:
branch_length_sampler = BranchLenSampler.Pachter()
elif fs.exponential_length:
branch_length_sampler = BranchLenSampler.Exponential()
elif fs.uniform_length_a:
branch_length_sampler = BranchLenSampler.UniformA()
elif fs.uniform_length_b:
branch_length_sampler = BranchLenSampler.UniformB()
# get the response
response_text = process(ntaxa, nseconds, nlengths, nsamples, nj_like,
branch_length_sampler, False)
return response_text + '\n'
def __init__(self):
self.components = [
BranchLenSampler.Pachter(),
BranchLenSampler.Exponential(),
BranchLenSampler.UniformA(),
BranchLenSampler.UniformB()]