id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
46,200 | kgori/treeCl | treeCl/collection.py | Collection.permuted_copy | def permuted_copy(self, partition=None):
""" Return a copy of the collection with all alignment columns permuted
"""
def take(n, iterable):
return [next(iterable) for _ in range(n)]
if partition is None:
partition = Partition([1] * len(self))
index_tuple... | python | def permuted_copy(self, partition=None):
""" Return a copy of the collection with all alignment columns permuted
"""
def take(n, iterable):
return [next(iterable) for _ in range(n)]
if partition is None:
partition = Partition([1] * len(self))
index_tuple... | [
"def",
"permuted_copy",
"(",
"self",
",",
"partition",
"=",
"None",
")",
":",
"def",
"take",
"(",
"n",
",",
"iterable",
")",
":",
"return",
"[",
"next",
"(",
"iterable",
")",
"for",
"_",
"in",
"range",
"(",
"n",
")",
"]",
"if",
"partition",
"is",
... | Return a copy of the collection with all alignment columns permuted | [
"Return",
"a",
"copy",
"of",
"the",
"collection",
"with",
"all",
"alignment",
"columns",
"permuted"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L489-L513 |
46,201 | kgori/treeCl | treeCl/collection.py | Scorer.get_id | def get_id(self, grp):
"""
Return a hash of the tuple of indices that specify the group
"""
thehash = hex(hash(grp))
if ISPY3: # use default encoding to get bytes
thehash = thehash.encode()
return self.cache.get(grp, hashlib.sha1(thehash).hexdigest()) | python | def get_id(self, grp):
"""
Return a hash of the tuple of indices that specify the group
"""
thehash = hex(hash(grp))
if ISPY3: # use default encoding to get bytes
thehash = thehash.encode()
return self.cache.get(grp, hashlib.sha1(thehash).hexdigest()) | [
"def",
"get_id",
"(",
"self",
",",
"grp",
")",
":",
"thehash",
"=",
"hex",
"(",
"hash",
"(",
"grp",
")",
")",
"if",
"ISPY3",
":",
"# use default encoding to get bytes",
"thehash",
"=",
"thehash",
".",
"encode",
"(",
")",
"return",
"self",
".",
"cache",
... | Return a hash of the tuple of indices that specify the group | [
"Return",
"a",
"hash",
"of",
"the",
"tuple",
"of",
"indices",
"that",
"specify",
"the",
"group"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L534-L541 |
46,202 | kgori/treeCl | treeCl/collection.py | Scorer.check_work_done | def check_work_done(self, grp):
"""
Check for the existence of alignment and result files.
"""
id_ = self.get_id(grp)
concat_file = os.path.join(self.cache_dir, '{}.phy'.format(id_))
result_file = os.path.join(self.cache_dir, '{}.{}.json'.format(id_, self.task_interface.n... | python | def check_work_done(self, grp):
"""
Check for the existence of alignment and result files.
"""
id_ = self.get_id(grp)
concat_file = os.path.join(self.cache_dir, '{}.phy'.format(id_))
result_file = os.path.join(self.cache_dir, '{}.{}.json'.format(id_, self.task_interface.n... | [
"def",
"check_work_done",
"(",
"self",
",",
"grp",
")",
":",
"id_",
"=",
"self",
".",
"get_id",
"(",
"grp",
")",
"concat_file",
"=",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"cache_dir",
",",
"'{}.phy'",
".",
"format",
"(",
"id_",
")",
")"... | Check for the existence of alignment and result files. | [
"Check",
"for",
"the",
"existence",
"of",
"alignment",
"and",
"result",
"files",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L543-L550 |
46,203 | kgori/treeCl | treeCl/collection.py | Scorer.write_group | def write_group(self, grp, overwrite=False, **kwargs):
"""
Write the concatenated alignment to disk in the location specified by
self.cache_dir
"""
id_ = self.get_id(grp)
alignment_done, result_done = self.check_work_done(grp)
self.cache[grp] = id_
al_file... | python | def write_group(self, grp, overwrite=False, **kwargs):
"""
Write the concatenated alignment to disk in the location specified by
self.cache_dir
"""
id_ = self.get_id(grp)
alignment_done, result_done = self.check_work_done(grp)
self.cache[grp] = id_
al_file... | [
"def",
"write_group",
"(",
"self",
",",
"grp",
",",
"overwrite",
"=",
"False",
",",
"*",
"*",
"kwargs",
")",
":",
"id_",
"=",
"self",
".",
"get_id",
"(",
"grp",
")",
"alignment_done",
",",
"result_done",
"=",
"self",
".",
"check_work_done",
"(",
"grp",... | Write the concatenated alignment to disk in the location specified by
self.cache_dir | [
"Write",
"the",
"concatenated",
"alignment",
"to",
"disk",
"in",
"the",
"location",
"specified",
"by",
"self",
".",
"cache_dir"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L552-L568 |
46,204 | kgori/treeCl | treeCl/collection.py | Scorer.get_group_result | def get_group_result(self, grp, **kwargs):
"""
Retrieve the results for a group. Needs this to already be calculated -
errors out if result not available.
"""
id_ = self.get_id(grp)
self.cache[grp] = id_
# Check if this file is already processed
alignment... | python | def get_group_result(self, grp, **kwargs):
"""
Retrieve the results for a group. Needs this to already be calculated -
errors out if result not available.
"""
id_ = self.get_id(grp)
self.cache[grp] = id_
# Check if this file is already processed
alignment... | [
"def",
"get_group_result",
"(",
"self",
",",
"grp",
",",
"*",
"*",
"kwargs",
")",
":",
"id_",
"=",
"self",
".",
"get_id",
"(",
"grp",
")",
"self",
".",
"cache",
"[",
"grp",
"]",
"=",
"id_",
"# Check if this file is already processed",
"alignment_written",
... | Retrieve the results for a group. Needs this to already be calculated -
errors out if result not available. | [
"Retrieve",
"the",
"results",
"for",
"a",
"group",
".",
"Needs",
"this",
"to",
"already",
"be",
"calculated",
"-",
"errors",
"out",
"if",
"result",
"not",
"available",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L570-L588 |
46,205 | kgori/treeCl | treeCl/collection.py | Scorer.get_partition_score | def get_partition_score(self, p):
"""
Assumes analysis is done and written to id.json!
"""
scores = []
for grp in p.get_membership():
try:
result = self.get_group_result(grp)
scores.append(result['likelihood'])
except ValueE... | python | def get_partition_score(self, p):
"""
Assumes analysis is done and written to id.json!
"""
scores = []
for grp in p.get_membership():
try:
result = self.get_group_result(grp)
scores.append(result['likelihood'])
except ValueE... | [
"def",
"get_partition_score",
"(",
"self",
",",
"p",
")",
":",
"scores",
"=",
"[",
"]",
"for",
"grp",
"in",
"p",
".",
"get_membership",
"(",
")",
":",
"try",
":",
"result",
"=",
"self",
".",
"get_group_result",
"(",
"grp",
")",
"scores",
".",
"append... | Assumes analysis is done and written to id.json! | [
"Assumes",
"analysis",
"is",
"done",
"and",
"written",
"to",
"id",
".",
"json!"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L640-L651 |
46,206 | kgori/treeCl | treeCl/collection.py | Scorer.get_partition_trees | def get_partition_trees(self, p):
"""
Return the trees associated with a partition, p
"""
trees = []
for grp in p.get_membership():
try:
result = self.get_group_result(grp)
trees.append(result['ml_tree'])
except ValueError:
... | python | def get_partition_trees(self, p):
"""
Return the trees associated with a partition, p
"""
trees = []
for grp in p.get_membership():
try:
result = self.get_group_result(grp)
trees.append(result['ml_tree'])
except ValueError:
... | [
"def",
"get_partition_trees",
"(",
"self",
",",
"p",
")",
":",
"trees",
"=",
"[",
"]",
"for",
"grp",
"in",
"p",
".",
"get_membership",
"(",
")",
":",
"try",
":",
"result",
"=",
"self",
".",
"get_group_result",
"(",
"grp",
")",
"trees",
".",
"append",... | Return the trees associated with a partition, p | [
"Return",
"the",
"trees",
"associated",
"with",
"a",
"partition",
"p"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L653-L665 |
46,207 | kgori/treeCl | treeCl/collection.py | Optimiser.expect | def expect(self, use_proportions=True):
""" The Expectation step of the CEM algorithm """
changed = self.get_changed(self.partition, self.prev_partition)
lk_table = self.generate_lktable(self.partition, changed, use_proportions)
self.table = self.likelihood_table_to_probs(lk_table) | python | def expect(self, use_proportions=True):
""" The Expectation step of the CEM algorithm """
changed = self.get_changed(self.partition, self.prev_partition)
lk_table = self.generate_lktable(self.partition, changed, use_proportions)
self.table = self.likelihood_table_to_probs(lk_table) | [
"def",
"expect",
"(",
"self",
",",
"use_proportions",
"=",
"True",
")",
":",
"changed",
"=",
"self",
".",
"get_changed",
"(",
"self",
".",
"partition",
",",
"self",
".",
"prev_partition",
")",
"lk_table",
"=",
"self",
".",
"generate_lktable",
"(",
"self",
... | The Expectation step of the CEM algorithm | [
"The",
"Expectation",
"step",
"of",
"the",
"CEM",
"algorithm"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L791-L795 |
46,208 | kgori/treeCl | treeCl/collection.py | Optimiser.classify | def classify(self, table, weighted_choice=False, transform=None):
""" The Classification step of the CEM algorithm """
assert table.shape[1] == self.numgrp
if weighted_choice:
if transform is not None:
probs = transform_fn(table.copy(), transform) #
else:... | python | def classify(self, table, weighted_choice=False, transform=None):
""" The Classification step of the CEM algorithm """
assert table.shape[1] == self.numgrp
if weighted_choice:
if transform is not None:
probs = transform_fn(table.copy(), transform) #
else:... | [
"def",
"classify",
"(",
"self",
",",
"table",
",",
"weighted_choice",
"=",
"False",
",",
"transform",
"=",
"None",
")",
":",
"assert",
"table",
".",
"shape",
"[",
"1",
"]",
"==",
"self",
".",
"numgrp",
"if",
"weighted_choice",
":",
"if",
"transform",
"... | The Classification step of the CEM algorithm | [
"The",
"Classification",
"step",
"of",
"the",
"CEM",
"algorithm"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L797-L816 |
46,209 | kgori/treeCl | treeCl/collection.py | Optimiser.maximise | def maximise(self, **kwargs):
""" The Maximisation step of the CEM algorithm """
self.scorer.write_partition(self.partition)
self.scorer.analyse_cache_dir(**kwargs)
self.likelihood = self.scorer.get_partition_score(self.partition)
self.scorer.clean_cache()
changed = self.... | python | def maximise(self, **kwargs):
""" The Maximisation step of the CEM algorithm """
self.scorer.write_partition(self.partition)
self.scorer.analyse_cache_dir(**kwargs)
self.likelihood = self.scorer.get_partition_score(self.partition)
self.scorer.clean_cache()
changed = self.... | [
"def",
"maximise",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"self",
".",
"scorer",
".",
"write_partition",
"(",
"self",
".",
"partition",
")",
"self",
".",
"scorer",
".",
"analyse_cache_dir",
"(",
"*",
"*",
"kwargs",
")",
"self",
".",
"likelihoo... | The Maximisation step of the CEM algorithm | [
"The",
"Maximisation",
"step",
"of",
"the",
"CEM",
"algorithm"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L818-L826 |
46,210 | kgori/treeCl | treeCl/collection.py | Optimiser.set_partition | def set_partition(self, partition):
"""
Store the partition in self.partition, and
move the old self.partition into self.prev_partition
"""
assert len(partition) == self.numgrp
self.partition, self.prev_partition = partition, self.partition | python | def set_partition(self, partition):
"""
Store the partition in self.partition, and
move the old self.partition into self.prev_partition
"""
assert len(partition) == self.numgrp
self.partition, self.prev_partition = partition, self.partition | [
"def",
"set_partition",
"(",
"self",
",",
"partition",
")",
":",
"assert",
"len",
"(",
"partition",
")",
"==",
"self",
".",
"numgrp",
"self",
".",
"partition",
",",
"self",
".",
"prev_partition",
"=",
"partition",
",",
"self",
".",
"partition"
] | Store the partition in self.partition, and
move the old self.partition into self.prev_partition | [
"Store",
"the",
"partition",
"in",
"self",
".",
"partition",
"and",
"move",
"the",
"old",
"self",
".",
"partition",
"into",
"self",
".",
"prev_partition"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L844-L850 |
46,211 | kgori/treeCl | treeCl/collection.py | Optimiser.get_changed | def get_changed(self, p1, p2):
"""
Return the loci that are in clusters that have changed between
partitions p1 and p2
"""
if p1 is None or p2 is None:
return list(range(len(self.insts)))
return set(flatten_list(set(p1) - set(p2))) | python | def get_changed(self, p1, p2):
"""
Return the loci that are in clusters that have changed between
partitions p1 and p2
"""
if p1 is None or p2 is None:
return list(range(len(self.insts)))
return set(flatten_list(set(p1) - set(p2))) | [
"def",
"get_changed",
"(",
"self",
",",
"p1",
",",
"p2",
")",
":",
"if",
"p1",
"is",
"None",
"or",
"p2",
"is",
"None",
":",
"return",
"list",
"(",
"range",
"(",
"len",
"(",
"self",
".",
"insts",
")",
")",
")",
"return",
"set",
"(",
"flatten_list"... | Return the loci that are in clusters that have changed between
partitions p1 and p2 | [
"Return",
"the",
"loci",
"that",
"are",
"in",
"clusters",
"that",
"have",
"changed",
"between",
"partitions",
"p1",
"and",
"p2"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L868-L875 |
46,212 | kgori/treeCl | treeCl/collection.py | Optimiser._update_likelihood_model | def _update_likelihood_model(self, inst, partition_parameters, tree):
"""
Set parameters of likelihood model - inst -
using values in dictionary - partition_parameters -,
and - tree -
"""
# Build transition matrix from dict
model = partition_parameters['model']
... | python | def _update_likelihood_model(self, inst, partition_parameters, tree):
"""
Set parameters of likelihood model - inst -
using values in dictionary - partition_parameters -,
and - tree -
"""
# Build transition matrix from dict
model = partition_parameters['model']
... | [
"def",
"_update_likelihood_model",
"(",
"self",
",",
"inst",
",",
"partition_parameters",
",",
"tree",
")",
":",
"# Build transition matrix from dict",
"model",
"=",
"partition_parameters",
"[",
"'model'",
"]",
"freqs",
"=",
"partition_parameters",
".",
"get",
"(",
... | Set parameters of likelihood model - inst -
using values in dictionary - partition_parameters -,
and - tree - | [
"Set",
"parameters",
"of",
"likelihood",
"model",
"-",
"inst",
"-",
"using",
"values",
"in",
"dictionary",
"-",
"partition_parameters",
"-",
"and",
"-",
"tree",
"-"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L911-L935 |
46,213 | kgori/treeCl | treeCl/collection.py | Optimiser._fill_empty_groups_old | def _fill_empty_groups_old(self, probs, assignment):
""" Does the simple thing - if any group is empty, but needs to have at
least one member, assign the data point with highest probability of
membership """
new_assignment = np.array(assignment.tolist())
for k in range(self.numgr... | python | def _fill_empty_groups_old(self, probs, assignment):
""" Does the simple thing - if any group is empty, but needs to have at
least one member, assign the data point with highest probability of
membership """
new_assignment = np.array(assignment.tolist())
for k in range(self.numgr... | [
"def",
"_fill_empty_groups_old",
"(",
"self",
",",
"probs",
",",
"assignment",
")",
":",
"new_assignment",
"=",
"np",
".",
"array",
"(",
"assignment",
".",
"tolist",
"(",
")",
")",
"for",
"k",
"in",
"range",
"(",
"self",
".",
"numgrp",
")",
":",
"if",
... | Does the simple thing - if any group is empty, but needs to have at
least one member, assign the data point with highest probability of
membership | [
"Does",
"the",
"simple",
"thing",
"-",
"if",
"any",
"group",
"is",
"empty",
"but",
"needs",
"to",
"have",
"at",
"least",
"one",
"member",
"assign",
"the",
"data",
"point",
"with",
"highest",
"probability",
"of",
"membership"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/collection.py#L1005-L1016 |
46,214 | kgori/treeCl | treeCl/bootstrap.py | jac | def jac(x,a):
""" Jacobian matrix given Christophe's suggestion of f """
return (x-a) / np.sqrt(((x-a)**2).sum(1))[:,np.newaxis] | python | def jac(x,a):
""" Jacobian matrix given Christophe's suggestion of f """
return (x-a) / np.sqrt(((x-a)**2).sum(1))[:,np.newaxis] | [
"def",
"jac",
"(",
"x",
",",
"a",
")",
":",
"return",
"(",
"x",
"-",
"a",
")",
"/",
"np",
".",
"sqrt",
"(",
"(",
"(",
"x",
"-",
"a",
")",
"**",
"2",
")",
".",
"sum",
"(",
"1",
")",
")",
"[",
":",
",",
"np",
".",
"newaxis",
"]"
] | Jacobian matrix given Christophe's suggestion of f | [
"Jacobian",
"matrix",
"given",
"Christophe",
"s",
"suggestion",
"of",
"f"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L70-L72 |
46,215 | kgori/treeCl | treeCl/bootstrap.py | gradient | def gradient(x, a, c):
""" J'.G """
return jac(x, a).T.dot(g(x, a, c)) | python | def gradient(x, a, c):
""" J'.G """
return jac(x, a).T.dot(g(x, a, c)) | [
"def",
"gradient",
"(",
"x",
",",
"a",
",",
"c",
")",
":",
"return",
"jac",
"(",
"x",
",",
"a",
")",
".",
"T",
".",
"dot",
"(",
"g",
"(",
"x",
",",
"a",
",",
"c",
")",
")"
] | J'.G | [
"J",
".",
"G"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L74-L76 |
46,216 | kgori/treeCl | treeCl/bootstrap.py | hessian | def hessian(x, a):
""" J'.J """
j = jac(x, a)
return j.T.dot(j) | python | def hessian(x, a):
""" J'.J """
j = jac(x, a)
return j.T.dot(j) | [
"def",
"hessian",
"(",
"x",
",",
"a",
")",
":",
"j",
"=",
"jac",
"(",
"x",
",",
"a",
")",
"return",
"j",
".",
"T",
".",
"dot",
"(",
"j",
")"
] | J'.J | [
"J",
".",
"J"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L78-L81 |
46,217 | kgori/treeCl | treeCl/bootstrap.py | grad_desc_update | def grad_desc_update(x, a, c, step=0.01):
"""
Given a value of x, return a better x
using gradient descent
"""
return x - step * gradient(x,a,c) | python | def grad_desc_update(x, a, c, step=0.01):
"""
Given a value of x, return a better x
using gradient descent
"""
return x - step * gradient(x,a,c) | [
"def",
"grad_desc_update",
"(",
"x",
",",
"a",
",",
"c",
",",
"step",
"=",
"0.01",
")",
":",
"return",
"x",
"-",
"step",
"*",
"gradient",
"(",
"x",
",",
"a",
",",
"c",
")"
] | Given a value of x, return a better x
using gradient descent | [
"Given",
"a",
"value",
"of",
"x",
"return",
"a",
"better",
"x",
"using",
"gradient",
"descent"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L83-L88 |
46,218 | kgori/treeCl | treeCl/bootstrap.py | optimise_levenberg_marquardt | def optimise_levenberg_marquardt(x, a, c, damping=0.001, tolerance=0.001):
"""
Optimise value of x using levenberg-marquardt
"""
x_new = x
x_old = x-1 # dummy value
f_old = f(x_new, a, c)
while np.abs(x_new - x_old).sum() > tolerance:
x_old = x_new
x_tmp = levenberg_marquardt... | python | def optimise_levenberg_marquardt(x, a, c, damping=0.001, tolerance=0.001):
"""
Optimise value of x using levenberg-marquardt
"""
x_new = x
x_old = x-1 # dummy value
f_old = f(x_new, a, c)
while np.abs(x_new - x_old).sum() > tolerance:
x_old = x_new
x_tmp = levenberg_marquardt... | [
"def",
"optimise_levenberg_marquardt",
"(",
"x",
",",
"a",
",",
"c",
",",
"damping",
"=",
"0.001",
",",
"tolerance",
"=",
"0.001",
")",
":",
"x_new",
"=",
"x",
"x_old",
"=",
"x",
"-",
"1",
"# dummy value",
"f_old",
"=",
"f",
"(",
"x_new",
",",
"a",
... | Optimise value of x using levenberg-marquardt | [
"Optimise",
"value",
"of",
"x",
"using",
"levenberg",
"-",
"marquardt"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L143-L160 |
46,219 | kgori/treeCl | treeCl/bootstrap.py | run_out_of_sample_mds | def run_out_of_sample_mds(boot_collection, ref_collection, ref_distance_matrix, index, dimensions, task=_fast_geo, rooted=False, **kwargs):
"""
index = index of the locus the bootstrap sample corresponds to - only important if
using recalc=True in kwargs
"""
fit = np.empty((len(boot_collecti... | python | def run_out_of_sample_mds(boot_collection, ref_collection, ref_distance_matrix, index, dimensions, task=_fast_geo, rooted=False, **kwargs):
"""
index = index of the locus the bootstrap sample corresponds to - only important if
using recalc=True in kwargs
"""
fit = np.empty((len(boot_collecti... | [
"def",
"run_out_of_sample_mds",
"(",
"boot_collection",
",",
"ref_collection",
",",
"ref_distance_matrix",
",",
"index",
",",
"dimensions",
",",
"task",
"=",
"_fast_geo",
",",
"rooted",
"=",
"False",
",",
"*",
"*",
"kwargs",
")",
":",
"fit",
"=",
"np",
".",
... | index = index of the locus the bootstrap sample corresponds to - only important if
using recalc=True in kwargs | [
"index",
"=",
"index",
"of",
"the",
"locus",
"the",
"bootstrap",
"sample",
"corresponds",
"to",
"-",
"only",
"important",
"if",
"using",
"recalc",
"=",
"True",
"in",
"kwargs"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L190-L206 |
46,220 | kgori/treeCl | treeCl/bootstrap.py | stress | def stress(ref_cds, est_cds):
"""
Kruskal's stress
"""
ref_dists = pdist(ref_cds)
est_dists = pdist(est_cds)
return np.sqrt(((ref_dists - est_dists)**2).sum() / (ref_dists**2).sum()) | python | def stress(ref_cds, est_cds):
"""
Kruskal's stress
"""
ref_dists = pdist(ref_cds)
est_dists = pdist(est_cds)
return np.sqrt(((ref_dists - est_dists)**2).sum() / (ref_dists**2).sum()) | [
"def",
"stress",
"(",
"ref_cds",
",",
"est_cds",
")",
":",
"ref_dists",
"=",
"pdist",
"(",
"ref_cds",
")",
"est_dists",
"=",
"pdist",
"(",
"est_cds",
")",
"return",
"np",
".",
"sqrt",
"(",
"(",
"(",
"ref_dists",
"-",
"est_dists",
")",
"**",
"2",
")",... | Kruskal's stress | [
"Kruskal",
"s",
"stress"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L224-L230 |
46,221 | kgori/treeCl | treeCl/bootstrap.py | rmsd | def rmsd(ref_cds, est_cds):
"""
Root-mean-squared-difference
"""
ref_dists = pdist(ref_cds)
est_dists = pdist(est_cds)
return np.sqrt(((ref_dists - est_dists)**2).mean()) | python | def rmsd(ref_cds, est_cds):
"""
Root-mean-squared-difference
"""
ref_dists = pdist(ref_cds)
est_dists = pdist(est_cds)
return np.sqrt(((ref_dists - est_dists)**2).mean()) | [
"def",
"rmsd",
"(",
"ref_cds",
",",
"est_cds",
")",
":",
"ref_dists",
"=",
"pdist",
"(",
"ref_cds",
")",
"est_dists",
"=",
"pdist",
"(",
"est_cds",
")",
"return",
"np",
".",
"sqrt",
"(",
"(",
"(",
"ref_dists",
"-",
"est_dists",
")",
"**",
"2",
")",
... | Root-mean-squared-difference | [
"Root",
"-",
"mean",
"-",
"squared",
"-",
"difference"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L237-L243 |
46,222 | kgori/treeCl | treeCl/bootstrap.py | OptimiseDistanceFit.levenberg_marquardt | def levenberg_marquardt(self, start_x=None, damping=1.0e-3, tolerance=1.0e-6):
"""
Optimise value of x using levenberg marquardt
"""
if start_x is None:
start_x = self._analytical_fitter.fit(self._c)
return optimise_levenberg_marquardt(start_x, self._a, self._c, toler... | python | def levenberg_marquardt(self, start_x=None, damping=1.0e-3, tolerance=1.0e-6):
"""
Optimise value of x using levenberg marquardt
"""
if start_x is None:
start_x = self._analytical_fitter.fit(self._c)
return optimise_levenberg_marquardt(start_x, self._a, self._c, toler... | [
"def",
"levenberg_marquardt",
"(",
"self",
",",
"start_x",
"=",
"None",
",",
"damping",
"=",
"1.0e-3",
",",
"tolerance",
"=",
"1.0e-6",
")",
":",
"if",
"start_x",
"is",
"None",
":",
"start_x",
"=",
"self",
".",
"_analytical_fitter",
".",
"fit",
"(",
"sel... | Optimise value of x using levenberg marquardt | [
"Optimise",
"value",
"of",
"x",
"using",
"levenberg",
"marquardt"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L316-L322 |
46,223 | kgori/treeCl | treeCl/bootstrap.py | AnalyticalFit._make_A_and_part_of_b_adjacent | def _make_A_and_part_of_b_adjacent(self, ref_crds):
"""
Make A and part of b. See docstring of this class
for answer to "What are A and b?"
"""
rot = self._rotate_rows(ref_crds)
A = 2*(rot - ref_crds)
partial_b = (rot**2 - ref_crds**2).sum(1)
return A, par... | python | def _make_A_and_part_of_b_adjacent(self, ref_crds):
"""
Make A and part of b. See docstring of this class
for answer to "What are A and b?"
"""
rot = self._rotate_rows(ref_crds)
A = 2*(rot - ref_crds)
partial_b = (rot**2 - ref_crds**2).sum(1)
return A, par... | [
"def",
"_make_A_and_part_of_b_adjacent",
"(",
"self",
",",
"ref_crds",
")",
":",
"rot",
"=",
"self",
".",
"_rotate_rows",
"(",
"ref_crds",
")",
"A",
"=",
"2",
"*",
"(",
"rot",
"-",
"ref_crds",
")",
"partial_b",
"=",
"(",
"rot",
"**",
"2",
"-",
"ref_crd... | Make A and part of b. See docstring of this class
for answer to "What are A and b?" | [
"Make",
"A",
"and",
"part",
"of",
"b",
".",
"See",
"docstring",
"of",
"this",
"class",
"for",
"answer",
"to",
"What",
"are",
"A",
"and",
"b?"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/bootstrap.py#L442-L450 |
46,224 | pudo/jsonmapping | jsonmapping/elastic.py | generate_schema_mapping | def generate_schema_mapping(resolver, schema_uri, depth=1):
""" Try and recursively iterate a JSON schema and to generate an ES mapping
that encasulates it. """
visitor = SchemaVisitor({'$ref': schema_uri}, resolver)
return _generate_schema_mapping(visitor, set(), depth) | python | def generate_schema_mapping(resolver, schema_uri, depth=1):
""" Try and recursively iterate a JSON schema and to generate an ES mapping
that encasulates it. """
visitor = SchemaVisitor({'$ref': schema_uri}, resolver)
return _generate_schema_mapping(visitor, set(), depth) | [
"def",
"generate_schema_mapping",
"(",
"resolver",
",",
"schema_uri",
",",
"depth",
"=",
"1",
")",
":",
"visitor",
"=",
"SchemaVisitor",
"(",
"{",
"'$ref'",
":",
"schema_uri",
"}",
",",
"resolver",
")",
"return",
"_generate_schema_mapping",
"(",
"visitor",
","... | Try and recursively iterate a JSON schema and to generate an ES mapping
that encasulates it. | [
"Try",
"and",
"recursively",
"iterate",
"a",
"JSON",
"schema",
"and",
"to",
"generate",
"an",
"ES",
"mapping",
"that",
"encasulates",
"it",
"."
] | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/elastic.py#L6-L10 |
46,225 | kgori/treeCl | treeCl/tasks.py | phyml_task | def phyml_task(alignment_file, model, **kwargs):
"""
Kwargs are passed to the Phyml process command line
"""
import re
fl = os.path.abspath(alignment_file)
ph = Phyml(verbose=False)
if model in ['JC69', 'K80', 'F81', 'F84', 'HKY85', 'TN93', 'GTR']:
datatype = 'nt'
elif re.search(... | python | def phyml_task(alignment_file, model, **kwargs):
"""
Kwargs are passed to the Phyml process command line
"""
import re
fl = os.path.abspath(alignment_file)
ph = Phyml(verbose=False)
if model in ['JC69', 'K80', 'F81', 'F84', 'HKY85', 'TN93', 'GTR']:
datatype = 'nt'
elif re.search(... | [
"def",
"phyml_task",
"(",
"alignment_file",
",",
"model",
",",
"*",
"*",
"kwargs",
")",
":",
"import",
"re",
"fl",
"=",
"os",
".",
"path",
".",
"abspath",
"(",
"alignment_file",
")",
"ph",
"=",
"Phyml",
"(",
"verbose",
"=",
"False",
")",
"if",
"model... | Kwargs are passed to the Phyml process command line | [
"Kwargs",
"are",
"passed",
"to",
"the",
"Phyml",
"process",
"command",
"line"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tasks.py#L111-L145 |
46,226 | pudo/jsonmapping | jsonmapping/util.py | validate_mapping | def validate_mapping(mapping):
""" Validate a mapping configuration file against the relevant schema. """
file_path = os.path.join(os.path.dirname(__file__),
'schemas', 'mapping.json')
with open(file_path, 'r') as fh:
validator = Draft4Validator(json.load(fh))
va... | python | def validate_mapping(mapping):
""" Validate a mapping configuration file against the relevant schema. """
file_path = os.path.join(os.path.dirname(__file__),
'schemas', 'mapping.json')
with open(file_path, 'r') as fh:
validator = Draft4Validator(json.load(fh))
va... | [
"def",
"validate_mapping",
"(",
"mapping",
")",
":",
"file_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"os",
".",
"path",
".",
"dirname",
"(",
"__file__",
")",
",",
"'schemas'",
",",
"'mapping.json'",
")",
"with",
"open",
"(",
"file_path",
",",
"'... | Validate a mapping configuration file against the relevant schema. | [
"Validate",
"a",
"mapping",
"configuration",
"file",
"against",
"the",
"relevant",
"schema",
"."
] | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/util.py#L7-L14 |
46,227 | kgori/treeCl | treeCl/plotter.py | Plotter.heatmap | def heatmap(self, partition=None, cmap=CM.Blues):
""" Plots a visual representation of a distance matrix """
if isinstance(self.dm, DistanceMatrix):
length = self.dm.values.shape[0]
else:
length = self.dm.shape[0]
datamax = float(np.abs(self.dm).max())
fi... | python | def heatmap(self, partition=None, cmap=CM.Blues):
""" Plots a visual representation of a distance matrix """
if isinstance(self.dm, DistanceMatrix):
length = self.dm.values.shape[0]
else:
length = self.dm.shape[0]
datamax = float(np.abs(self.dm).max())
fi... | [
"def",
"heatmap",
"(",
"self",
",",
"partition",
"=",
"None",
",",
"cmap",
"=",
"CM",
".",
"Blues",
")",
":",
"if",
"isinstance",
"(",
"self",
".",
"dm",
",",
"DistanceMatrix",
")",
":",
"length",
"=",
"self",
".",
"dm",
".",
"values",
".",
"shape"... | Plots a visual representation of a distance matrix | [
"Plots",
"a",
"visual",
"representation",
"of",
"a",
"distance",
"matrix"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/plotter.py#L249-L274 |
46,228 | kgori/treeCl | treeCl/concatenation.py | Concatenation.get_tree_collection_strings | def get_tree_collection_strings(self, scale=1, guide_tree=None):
""" Function to get input strings for tree_collection
tree_collection needs distvar, genome_map and labels -
these are returned in the order above
"""
records = [self.collection[i] for i in self.indices]
ret... | python | def get_tree_collection_strings(self, scale=1, guide_tree=None):
""" Function to get input strings for tree_collection
tree_collection needs distvar, genome_map and labels -
these are returned in the order above
"""
records = [self.collection[i] for i in self.indices]
ret... | [
"def",
"get_tree_collection_strings",
"(",
"self",
",",
"scale",
"=",
"1",
",",
"guide_tree",
"=",
"None",
")",
":",
"records",
"=",
"[",
"self",
".",
"collection",
"[",
"i",
"]",
"for",
"i",
"in",
"self",
".",
"indices",
"]",
"return",
"TreeCollectionTa... | Function to get input strings for tree_collection
tree_collection needs distvar, genome_map and labels -
these are returned in the order above | [
"Function",
"to",
"get",
"input",
"strings",
"for",
"tree_collection",
"tree_collection",
"needs",
"distvar",
"genome_map",
"and",
"labels",
"-",
"these",
"are",
"returned",
"in",
"the",
"order",
"above"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/concatenation.py#L90-L96 |
46,229 | getsentry/libsourcemap | libsourcemap/highlevel.py | from_json | def from_json(buffer, auto_flatten=True, raise_for_index=True):
"""Parses a JSON string into either a view or an index. If auto flatten
is enabled a sourcemap index that does not contain external references is
automatically flattened into a view. By default if an index would be
returned an `IndexedSou... | python | def from_json(buffer, auto_flatten=True, raise_for_index=True):
"""Parses a JSON string into either a view or an index. If auto flatten
is enabled a sourcemap index that does not contain external references is
automatically flattened into a view. By default if an index would be
returned an `IndexedSou... | [
"def",
"from_json",
"(",
"buffer",
",",
"auto_flatten",
"=",
"True",
",",
"raise_for_index",
"=",
"True",
")",
":",
"buffer",
"=",
"to_bytes",
"(",
"buffer",
")",
"view_out",
"=",
"_ffi",
".",
"new",
"(",
"'lsm_view_t **'",
")",
"index_out",
"=",
"_ffi",
... | Parses a JSON string into either a view or an index. If auto flatten
is enabled a sourcemap index that does not contain external references is
automatically flattened into a view. By default if an index would be
returned an `IndexedSourceMap` error is raised instead which holds the
index. | [
"Parses",
"a",
"JSON",
"string",
"into",
"either",
"a",
"view",
"or",
"an",
"index",
".",
"If",
"auto",
"flatten",
"is",
"enabled",
"a",
"sourcemap",
"index",
"that",
"does",
"not",
"contain",
"external",
"references",
"is",
"automatically",
"flattened",
"in... | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L62-L89 |
46,230 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.from_memdb | def from_memdb(buffer):
"""Creates a sourcemap view from MemDB bytes."""
buffer = to_bytes(buffer)
return View._from_ptr(rustcall(
_lib.lsm_view_from_memdb,
buffer, len(buffer))) | python | def from_memdb(buffer):
"""Creates a sourcemap view from MemDB bytes."""
buffer = to_bytes(buffer)
return View._from_ptr(rustcall(
_lib.lsm_view_from_memdb,
buffer, len(buffer))) | [
"def",
"from_memdb",
"(",
"buffer",
")",
":",
"buffer",
"=",
"to_bytes",
"(",
"buffer",
")",
"return",
"View",
".",
"_from_ptr",
"(",
"rustcall",
"(",
"_lib",
".",
"lsm_view_from_memdb",
",",
"buffer",
",",
"len",
"(",
"buffer",
")",
")",
")"
] | Creates a sourcemap view from MemDB bytes. | [
"Creates",
"a",
"sourcemap",
"view",
"from",
"MemDB",
"bytes",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L114-L119 |
46,231 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.from_memdb_file | def from_memdb_file(path):
"""Creates a sourcemap view from MemDB at a given file."""
path = to_bytes(path)
return View._from_ptr(rustcall(_lib.lsm_view_from_memdb_file, path)) | python | def from_memdb_file(path):
"""Creates a sourcemap view from MemDB at a given file."""
path = to_bytes(path)
return View._from_ptr(rustcall(_lib.lsm_view_from_memdb_file, path)) | [
"def",
"from_memdb_file",
"(",
"path",
")",
":",
"path",
"=",
"to_bytes",
"(",
"path",
")",
"return",
"View",
".",
"_from_ptr",
"(",
"rustcall",
"(",
"_lib",
".",
"lsm_view_from_memdb_file",
",",
"path",
")",
")"
] | Creates a sourcemap view from MemDB at a given file. | [
"Creates",
"a",
"sourcemap",
"view",
"from",
"MemDB",
"at",
"a",
"given",
"file",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L122-L125 |
46,232 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.dump_memdb | def dump_memdb(self, with_source_contents=True, with_names=True):
"""Dumps a sourcemap in MemDB format into bytes."""
len_out = _ffi.new('unsigned int *')
buf = rustcall(
_lib.lsm_view_dump_memdb,
self._get_ptr(), len_out,
with_source_contents, with_names)
... | python | def dump_memdb(self, with_source_contents=True, with_names=True):
"""Dumps a sourcemap in MemDB format into bytes."""
len_out = _ffi.new('unsigned int *')
buf = rustcall(
_lib.lsm_view_dump_memdb,
self._get_ptr(), len_out,
with_source_contents, with_names)
... | [
"def",
"dump_memdb",
"(",
"self",
",",
"with_source_contents",
"=",
"True",
",",
"with_names",
"=",
"True",
")",
":",
"len_out",
"=",
"_ffi",
".",
"new",
"(",
"'unsigned int *'",
")",
"buf",
"=",
"rustcall",
"(",
"_lib",
".",
"lsm_view_dump_memdb",
",",
"s... | Dumps a sourcemap in MemDB format into bytes. | [
"Dumps",
"a",
"sourcemap",
"in",
"MemDB",
"format",
"into",
"bytes",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L138-L149 |
46,233 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.lookup_token | def lookup_token(self, line, col):
"""Given a minified location, this tries to locate the closest
token that is a match. Returns `None` if no match can be found.
"""
# Silently ignore underflows
if line < 0 or col < 0:
return None
tok_out = _ffi.new('lsm_toke... | python | def lookup_token(self, line, col):
"""Given a minified location, this tries to locate the closest
token that is a match. Returns `None` if no match can be found.
"""
# Silently ignore underflows
if line < 0 or col < 0:
return None
tok_out = _ffi.new('lsm_toke... | [
"def",
"lookup_token",
"(",
"self",
",",
"line",
",",
"col",
")",
":",
"# Silently ignore underflows",
"if",
"line",
"<",
"0",
"or",
"col",
"<",
"0",
":",
"return",
"None",
"tok_out",
"=",
"_ffi",
".",
"new",
"(",
"'lsm_token_t *'",
")",
"if",
"rustcall"... | Given a minified location, this tries to locate the closest
token that is a match. Returns `None` if no match can be found. | [
"Given",
"a",
"minified",
"location",
"this",
"tries",
"to",
"locate",
"the",
"closest",
"token",
"that",
"is",
"a",
"match",
".",
"Returns",
"None",
"if",
"no",
"match",
"can",
"be",
"found",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L151-L161 |
46,234 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.get_original_function_name | def get_original_function_name(self, line, col, minified_name,
minified_source):
"""Given a token location and a minified function name and the
minified source file this returns the original function name if it
can be found of the minified function in scope.
... | python | def get_original_function_name(self, line, col, minified_name,
minified_source):
"""Given a token location and a minified function name and the
minified source file this returns the original function name if it
can be found of the minified function in scope.
... | [
"def",
"get_original_function_name",
"(",
"self",
",",
"line",
",",
"col",
",",
"minified_name",
",",
"minified_source",
")",
":",
"# Silently ignore underflows",
"if",
"line",
"<",
"0",
"or",
"col",
"<",
"0",
":",
"return",
"None",
"minified_name",
"=",
"mini... | Given a token location and a minified function name and the
minified source file this returns the original function name if it
can be found of the minified function in scope. | [
"Given",
"a",
"token",
"location",
"and",
"a",
"minified",
"function",
"name",
"and",
"the",
"minified",
"source",
"file",
"this",
"returns",
"the",
"original",
"function",
"name",
"if",
"it",
"can",
"be",
"found",
"of",
"the",
"minified",
"function",
"in",
... | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L163-L185 |
46,235 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.get_source_contents | def get_source_contents(self, src_id):
"""Given a source ID this returns the embedded sourcecode if there
is. The sourcecode is returned as UTF-8 bytes for more efficient
processing.
"""
len_out = _ffi.new('unsigned int *')
must_free = _ffi.new('int *')
rv = rust... | python | def get_source_contents(self, src_id):
"""Given a source ID this returns the embedded sourcecode if there
is. The sourcecode is returned as UTF-8 bytes for more efficient
processing.
"""
len_out = _ffi.new('unsigned int *')
must_free = _ffi.new('int *')
rv = rust... | [
"def",
"get_source_contents",
"(",
"self",
",",
"src_id",
")",
":",
"len_out",
"=",
"_ffi",
".",
"new",
"(",
"'unsigned int *'",
")",
"must_free",
"=",
"_ffi",
".",
"new",
"(",
"'int *'",
")",
"rv",
"=",
"rustcall",
"(",
"_lib",
".",
"lsm_view_get_source_c... | Given a source ID this returns the embedded sourcecode if there
is. The sourcecode is returned as UTF-8 bytes for more efficient
processing. | [
"Given",
"a",
"source",
"ID",
"this",
"returns",
"the",
"embedded",
"sourcecode",
"if",
"there",
"is",
".",
"The",
"sourcecode",
"is",
"returned",
"as",
"UTF",
"-",
"8",
"bytes",
"for",
"more",
"efficient",
"processing",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L187-L201 |
46,236 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.has_source_contents | def has_source_contents(self, src_id):
"""Checks if some sources exist."""
return bool(rustcall(_lib.lsm_view_has_source_contents,
self._get_ptr(), src_id)) | python | def has_source_contents(self, src_id):
"""Checks if some sources exist."""
return bool(rustcall(_lib.lsm_view_has_source_contents,
self._get_ptr(), src_id)) | [
"def",
"has_source_contents",
"(",
"self",
",",
"src_id",
")",
":",
"return",
"bool",
"(",
"rustcall",
"(",
"_lib",
".",
"lsm_view_has_source_contents",
",",
"self",
".",
"_get_ptr",
"(",
")",
",",
"src_id",
")",
")"
] | Checks if some sources exist. | [
"Checks",
"if",
"some",
"sources",
"exist",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L203-L206 |
46,237 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.get_source_name | def get_source_name(self, src_id):
"""Returns the name of the given source."""
len_out = _ffi.new('unsigned int *')
rv = rustcall(_lib.lsm_view_get_source_name,
self._get_ptr(), src_id, len_out)
if rv:
return decode_rust_str(rv, len_out[0]) | python | def get_source_name(self, src_id):
"""Returns the name of the given source."""
len_out = _ffi.new('unsigned int *')
rv = rustcall(_lib.lsm_view_get_source_name,
self._get_ptr(), src_id, len_out)
if rv:
return decode_rust_str(rv, len_out[0]) | [
"def",
"get_source_name",
"(",
"self",
",",
"src_id",
")",
":",
"len_out",
"=",
"_ffi",
".",
"new",
"(",
"'unsigned int *'",
")",
"rv",
"=",
"rustcall",
"(",
"_lib",
".",
"lsm_view_get_source_name",
",",
"self",
".",
"_get_ptr",
"(",
")",
",",
"src_id",
... | Returns the name of the given source. | [
"Returns",
"the",
"name",
"of",
"the",
"given",
"source",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L208-L214 |
46,238 | getsentry/libsourcemap | libsourcemap/highlevel.py | View.iter_sources | def iter_sources(self):
"""Iterates over all source names and IDs."""
for src_id in xrange(self.get_source_count()):
yield src_id, self.get_source_name(src_id) | python | def iter_sources(self):
"""Iterates over all source names and IDs."""
for src_id in xrange(self.get_source_count()):
yield src_id, self.get_source_name(src_id) | [
"def",
"iter_sources",
"(",
"self",
")",
":",
"for",
"src_id",
"in",
"xrange",
"(",
"self",
".",
"get_source_count",
"(",
")",
")",
":",
"yield",
"src_id",
",",
"self",
".",
"get_source_name",
"(",
"src_id",
")"
] | Iterates over all source names and IDs. | [
"Iterates",
"over",
"all",
"source",
"names",
"and",
"IDs",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L221-L224 |
46,239 | getsentry/libsourcemap | libsourcemap/highlevel.py | Index.from_json | def from_json(buffer):
"""Creates an index from a JSON string."""
buffer = to_bytes(buffer)
return Index._from_ptr(rustcall(
_lib.lsm_index_from_json,
buffer, len(buffer))) | python | def from_json(buffer):
"""Creates an index from a JSON string."""
buffer = to_bytes(buffer)
return Index._from_ptr(rustcall(
_lib.lsm_index_from_json,
buffer, len(buffer))) | [
"def",
"from_json",
"(",
"buffer",
")",
":",
"buffer",
"=",
"to_bytes",
"(",
"buffer",
")",
"return",
"Index",
".",
"_from_ptr",
"(",
"rustcall",
"(",
"_lib",
".",
"lsm_index_from_json",
",",
"buffer",
",",
"len",
"(",
"buffer",
")",
")",
")"
] | Creates an index from a JSON string. | [
"Creates",
"an",
"index",
"from",
"a",
"JSON",
"string",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L253-L258 |
46,240 | getsentry/libsourcemap | libsourcemap/highlevel.py | Index.into_view | def into_view(self):
"""Converts the index into a view"""
try:
return View._from_ptr(rustcall(
_lib.lsm_index_into_view,
self._get_ptr()))
finally:
self._ptr = None | python | def into_view(self):
"""Converts the index into a view"""
try:
return View._from_ptr(rustcall(
_lib.lsm_index_into_view,
self._get_ptr()))
finally:
self._ptr = None | [
"def",
"into_view",
"(",
"self",
")",
":",
"try",
":",
"return",
"View",
".",
"_from_ptr",
"(",
"rustcall",
"(",
"_lib",
".",
"lsm_index_into_view",
",",
"self",
".",
"_get_ptr",
"(",
")",
")",
")",
"finally",
":",
"self",
".",
"_ptr",
"=",
"None"
] | Converts the index into a view | [
"Converts",
"the",
"index",
"into",
"a",
"view"
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L276-L283 |
46,241 | getsentry/libsourcemap | libsourcemap/highlevel.py | ProguardView.from_path | def from_path(filename):
"""Creates a sourcemap view from a file path."""
filename = to_bytes(filename)
if NULL_BYTE in filename:
raise ValueError('null byte in path')
return ProguardView._from_ptr(rustcall(
_lib.lsm_proguard_mapping_from_path,
filenam... | python | def from_path(filename):
"""Creates a sourcemap view from a file path."""
filename = to_bytes(filename)
if NULL_BYTE in filename:
raise ValueError('null byte in path')
return ProguardView._from_ptr(rustcall(
_lib.lsm_proguard_mapping_from_path,
filenam... | [
"def",
"from_path",
"(",
"filename",
")",
":",
"filename",
"=",
"to_bytes",
"(",
"filename",
")",
"if",
"NULL_BYTE",
"in",
"filename",
":",
"raise",
"ValueError",
"(",
"'null byte in path'",
")",
"return",
"ProguardView",
".",
"_from_ptr",
"(",
"rustcall",
"("... | Creates a sourcemap view from a file path. | [
"Creates",
"a",
"sourcemap",
"view",
"from",
"a",
"file",
"path",
"."
] | 94b5a34814fafee9dc23da8ec0ccca77f30e3370 | https://github.com/getsentry/libsourcemap/blob/94b5a34814fafee9dc23da8ec0ccca77f30e3370/libsourcemap/highlevel.py#L311-L318 |
46,242 | pudo/jsonmapping | jsonmapping/mapper.py | Mapper.apply | def apply(self, data):
""" Apply the given mapping to ``data``, recursively. The return type
is a tuple of a boolean and the resulting data element. The boolean
indicates whether any values were mapped in the child nodes of the
mapping. It is used to skip optional branches of the object ... | python | def apply(self, data):
""" Apply the given mapping to ``data``, recursively. The return type
is a tuple of a boolean and the resulting data element. The boolean
indicates whether any values were mapped in the child nodes of the
mapping. It is used to skip optional branches of the object ... | [
"def",
"apply",
"(",
"self",
",",
"data",
")",
":",
"if",
"self",
".",
"visitor",
".",
"is_object",
":",
"obj",
"=",
"{",
"}",
"if",
"self",
".",
"visitor",
".",
"parent",
"is",
"None",
":",
"obj",
"[",
"'$schema'",
"]",
"=",
"self",
".",
"visito... | Apply the given mapping to ``data``, recursively. The return type
is a tuple of a boolean and the resulting data element. The boolean
indicates whether any values were mapped in the child nodes of the
mapping. It is used to skip optional branches of the object graph. | [
"Apply",
"the",
"given",
"mapping",
"to",
"data",
"recursively",
".",
"The",
"return",
"type",
"is",
"a",
"tuple",
"of",
"a",
"boolean",
"and",
"the",
"resulting",
"data",
"element",
".",
"The",
"boolean",
"indicates",
"whether",
"any",
"values",
"were",
"... | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/mapper.py#L52-L79 |
46,243 | kgori/treeCl | treeCl/utils/translator.py | Translator.translate | def translate(self, text):
""" Translate text, returns the modified text. """
# Reset substitution counter
self.count = 0
# Process text
return self._make_regex().sub(self, text) | python | def translate(self, text):
""" Translate text, returns the modified text. """
# Reset substitution counter
self.count = 0
# Process text
return self._make_regex().sub(self, text) | [
"def",
"translate",
"(",
"self",
",",
"text",
")",
":",
"# Reset substitution counter",
"self",
".",
"count",
"=",
"0",
"# Process text",
"return",
"self",
".",
"_make_regex",
"(",
")",
".",
"sub",
"(",
"self",
",",
"text",
")"
] | Translate text, returns the modified text. | [
"Translate",
"text",
"returns",
"the",
"modified",
"text",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/utils/translator.py#L25-L32 |
46,244 | kgori/treeCl | treeCl/clustering.py | Spectral.cluster | def cluster(self, n, embed_dim=None, algo=spectral.SPECTRAL, method=methods.KMEANS):
"""
Cluster the embedded coordinates using spectral clustering
Parameters
----------
n: int
The number of clusters to return
embed_dim: ... | python | def cluster(self, n, embed_dim=None, algo=spectral.SPECTRAL, method=methods.KMEANS):
"""
Cluster the embedded coordinates using spectral clustering
Parameters
----------
n: int
The number of clusters to return
embed_dim: ... | [
"def",
"cluster",
"(",
"self",
",",
"n",
",",
"embed_dim",
"=",
"None",
",",
"algo",
"=",
"spectral",
".",
"SPECTRAL",
",",
"method",
"=",
"methods",
".",
"KMEANS",
")",
":",
"if",
"n",
"==",
"1",
":",
"return",
"Partition",
"(",
"[",
"1",
"]",
"... | Cluster the embedded coordinates using spectral clustering
Parameters
----------
n: int
The number of clusters to return
embed_dim: int
The dimensionality of the underlying coordinates
... | [
"Cluster",
"the",
"embedded",
"coordinates",
"using",
"spectral",
"clustering"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/clustering.py#L234-L279 |
46,245 | kgori/treeCl | treeCl/clustering.py | Spectral.spectral_embedding | def spectral_embedding(self, n):
"""
Embed the points using spectral decomposition of the laplacian of
the affinity matrix
Parameters
----------
n: int
The number of dimensions
"""
coords = spectral_embedding(self._affinity, n)
... | python | def spectral_embedding(self, n):
"""
Embed the points using spectral decomposition of the laplacian of
the affinity matrix
Parameters
----------
n: int
The number of dimensions
"""
coords = spectral_embedding(self._affinity, n)
... | [
"def",
"spectral_embedding",
"(",
"self",
",",
"n",
")",
":",
"coords",
"=",
"spectral_embedding",
"(",
"self",
".",
"_affinity",
",",
"n",
")",
"return",
"CoordinateMatrix",
"(",
"normalise_rows",
"(",
"coords",
")",
")"
] | Embed the points using spectral decomposition of the laplacian of
the affinity matrix
Parameters
----------
n: int
The number of dimensions | [
"Embed",
"the",
"points",
"using",
"spectral",
"decomposition",
"of",
"the",
"laplacian",
"of",
"the",
"affinity",
"matrix"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/clustering.py#L281-L292 |
46,246 | kgori/treeCl | treeCl/clustering.py | Spectral.kpca_embedding | def kpca_embedding(self, n):
"""
Embed the points using kernel PCA of the affinity matrix
Parameters
----------
n: int
The number of dimensions
"""
return self.dm.embedding(n, 'kpca', affinity_matrix=self._affinity) | python | def kpca_embedding(self, n):
"""
Embed the points using kernel PCA of the affinity matrix
Parameters
----------
n: int
The number of dimensions
"""
return self.dm.embedding(n, 'kpca', affinity_matrix=self._affinity) | [
"def",
"kpca_embedding",
"(",
"self",
",",
"n",
")",
":",
"return",
"self",
".",
"dm",
".",
"embedding",
"(",
"n",
",",
"'kpca'",
",",
"affinity_matrix",
"=",
"self",
".",
"_affinity",
")"
] | Embed the points using kernel PCA of the affinity matrix
Parameters
----------
n: int
The number of dimensions | [
"Embed",
"the",
"points",
"using",
"kernel",
"PCA",
"of",
"the",
"affinity",
"matrix"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/clustering.py#L309-L318 |
46,247 | kgori/treeCl | treeCl/clustering.py | MultidimensionalScaling.cluster | def cluster(self, n, embed_dim=None, algo=mds.CLASSICAL, method=methods.KMEANS):
"""
Cluster the embedded coordinates using multidimensional scaling
Parameters
----------
n: int
The number of clusters to return
embed_dim ... | python | def cluster(self, n, embed_dim=None, algo=mds.CLASSICAL, method=methods.KMEANS):
"""
Cluster the embedded coordinates using multidimensional scaling
Parameters
----------
n: int
The number of clusters to return
embed_dim ... | [
"def",
"cluster",
"(",
"self",
",",
"n",
",",
"embed_dim",
"=",
"None",
",",
"algo",
"=",
"mds",
".",
"CLASSICAL",
",",
"method",
"=",
"methods",
".",
"KMEANS",
")",
":",
"if",
"n",
"==",
"1",
":",
"return",
"Partition",
"(",
"[",
"1",
"]",
"*",
... | Cluster the embedded coordinates using multidimensional scaling
Parameters
----------
n: int
The number of clusters to return
embed_dim int
The dimensionality of the underlying coordinates
... | [
"Cluster",
"the",
"embedded",
"coordinates",
"using",
"multidimensional",
"scaling"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/clustering.py#L329-L371 |
46,248 | kgori/treeCl | treeCl/wrappers/abstract_wrapper.py | AbstractWrapper._log_thread | def _log_thread(self, pipe, queue):
"""
Start a thread logging output from pipe
"""
# thread function to log subprocess output (LOG is a queue)
def enqueue_output(out, q):
for line in iter(out.readline, b''):
q.put(line.rstrip())
out.close... | python | def _log_thread(self, pipe, queue):
"""
Start a thread logging output from pipe
"""
# thread function to log subprocess output (LOG is a queue)
def enqueue_output(out, q):
for line in iter(out.readline, b''):
q.put(line.rstrip())
out.close... | [
"def",
"_log_thread",
"(",
"self",
",",
"pipe",
",",
"queue",
")",
":",
"# thread function to log subprocess output (LOG is a queue)",
"def",
"enqueue_output",
"(",
"out",
",",
"q",
")",
":",
"for",
"line",
"in",
"iter",
"(",
"out",
".",
"readline",
",",
"b''"... | Start a thread logging output from pipe | [
"Start",
"a",
"thread",
"logging",
"output",
"from",
"pipe"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/wrappers/abstract_wrapper.py#L143-L159 |
46,249 | kgori/treeCl | treeCl/wrappers/abstract_wrapper.py | AbstractWrapper._search_for_executable | def _search_for_executable(self, executable):
"""
Search for file give in "executable". If it is not found, we try the environment PATH.
Returns either the absolute path to the found executable, or None if the executable
couldn't be found.
"""
if os.path.isfile(executable... | python | def _search_for_executable(self, executable):
"""
Search for file give in "executable". If it is not found, we try the environment PATH.
Returns either the absolute path to the found executable, or None if the executable
couldn't be found.
"""
if os.path.isfile(executable... | [
"def",
"_search_for_executable",
"(",
"self",
",",
"executable",
")",
":",
"if",
"os",
".",
"path",
".",
"isfile",
"(",
"executable",
")",
":",
"return",
"os",
".",
"path",
".",
"abspath",
"(",
"executable",
")",
"else",
":",
"envpath",
"=",
"os",
".",... | Search for file give in "executable". If it is not found, we try the environment PATH.
Returns either the absolute path to the found executable, or None if the executable
couldn't be found. | [
"Search",
"for",
"file",
"give",
"in",
"executable",
".",
"If",
"it",
"is",
"not",
"found",
"we",
"try",
"the",
"environment",
"PATH",
".",
"Returns",
"either",
"the",
"absolute",
"path",
"to",
"the",
"found",
"executable",
"or",
"None",
"if",
"the",
"ex... | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/wrappers/abstract_wrapper.py#L161-L176 |
46,250 | fedelemantuano/tika-app-python | tikapp/tikapp.py | TikaApp._command_template | def _command_template(self, switches, objectInput=None):
"""Template for Tika app commands
Args:
switches (list): list of switches to Tika app Jar
objectInput (object): file object/standard input to analyze
Return:
Standard output data (unicode Python 2, str... | python | def _command_template(self, switches, objectInput=None):
"""Template for Tika app commands
Args:
switches (list): list of switches to Tika app Jar
objectInput (object): file object/standard input to analyze
Return:
Standard output data (unicode Python 2, str... | [
"def",
"_command_template",
"(",
"self",
",",
"switches",
",",
"objectInput",
"=",
"None",
")",
":",
"command",
"=",
"[",
"\"java\"",
",",
"\"-jar\"",
",",
"self",
".",
"file_jar",
",",
"\"-eUTF-8\"",
"]",
"if",
"self",
".",
"memory_allocation",
":",
"comm... | Template for Tika app commands
Args:
switches (list): list of switches to Tika app Jar
objectInput (object): file object/standard input to analyze
Return:
Standard output data (unicode Python 2, str Python 3) | [
"Template",
"for",
"Tika",
"app",
"commands"
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/tikapp.py#L76-L112 |
46,251 | fedelemantuano/tika-app-python | tikapp/tikapp.py | TikaApp.detect_content_type | def detect_content_type(self, path=None, payload=None, objectInput=None):
"""
Return the content type of passed file or payload.
Args:
path (string): Path of file to analyze
payload (string): Payload base64 to analyze
objectInput (object): file object/standar... | python | def detect_content_type(self, path=None, payload=None, objectInput=None):
"""
Return the content type of passed file or payload.
Args:
path (string): Path of file to analyze
payload (string): Payload base64 to analyze
objectInput (object): file object/standar... | [
"def",
"detect_content_type",
"(",
"self",
",",
"path",
"=",
"None",
",",
"payload",
"=",
"None",
",",
"objectInput",
"=",
"None",
")",
":",
"# From Python detection content type from stdin doesn't work TO FIX",
"if",
"objectInput",
":",
"message",
"=",
"\"Detection c... | Return the content type of passed file or payload.
Args:
path (string): Path of file to analyze
payload (string): Payload base64 to analyze
objectInput (object): file object/standard input to analyze
Returns:
content type of file (string) | [
"Return",
"the",
"content",
"type",
"of",
"passed",
"file",
"or",
"payload",
"."
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/tikapp.py#L119-L140 |
46,252 | fedelemantuano/tika-app-python | tikapp/tikapp.py | TikaApp.extract_only_content | def extract_only_content(self, path=None, payload=None, objectInput=None):
"""
Return only the text content of passed file.
These parameters are in OR. Only one of them can be analyzed.
Args:
path (string): Path of file to analyze
payload (string): Payload base64... | python | def extract_only_content(self, path=None, payload=None, objectInput=None):
"""
Return only the text content of passed file.
These parameters are in OR. Only one of them can be analyzed.
Args:
path (string): Path of file to analyze
payload (string): Payload base64... | [
"def",
"extract_only_content",
"(",
"self",
",",
"path",
"=",
"None",
",",
"payload",
"=",
"None",
",",
"objectInput",
"=",
"None",
")",
":",
"if",
"objectInput",
":",
"switches",
"=",
"[",
"\"-t\"",
"]",
"result",
"=",
"self",
".",
"_command_template",
... | Return only the text content of passed file.
These parameters are in OR. Only one of them can be analyzed.
Args:
path (string): Path of file to analyze
payload (string): Payload base64 to analyze
objectInput (object): file object/standard input to analyze
Re... | [
"Return",
"only",
"the",
"text",
"content",
"of",
"passed",
"file",
".",
"These",
"parameters",
"are",
"in",
"OR",
".",
"Only",
"one",
"of",
"them",
"can",
"be",
"analyzed",
"."
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/tikapp.py#L143-L164 |
46,253 | fedelemantuano/tika-app-python | tikapp/tikapp.py | TikaApp.extract_all_content | def extract_all_content(
self,
path=None,
payload=None,
objectInput=None,
pretty_print=False,
convert_to_obj=False,
):
"""
This function returns a JSON of all contents and
metadata of passed file
Args:
path (string): Path o... | python | def extract_all_content(
self,
path=None,
payload=None,
objectInput=None,
pretty_print=False,
convert_to_obj=False,
):
"""
This function returns a JSON of all contents and
metadata of passed file
Args:
path (string): Path o... | [
"def",
"extract_all_content",
"(",
"self",
",",
"path",
"=",
"None",
",",
"payload",
"=",
"None",
",",
"objectInput",
"=",
"None",
",",
"pretty_print",
"=",
"False",
",",
"convert_to_obj",
"=",
"False",
",",
")",
":",
"f",
"=",
"file_path",
"(",
"path",
... | This function returns a JSON of all contents and
metadata of passed file
Args:
path (string): Path of file to analyze
payload (string): Payload base64 to analyze
objectInput (object): file object/standard input to analyze
pretty_print (boolean): If True a... | [
"This",
"function",
"returns",
"a",
"JSON",
"of",
"all",
"contents",
"and",
"metadata",
"of",
"passed",
"file"
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/tikapp.py#L190-L219 |
46,254 | fedelemantuano/tika-app-python | tikapp/utils.py | clean | def clean(func):
"""
This decorator removes the temp file from disk. This is the case where
you want to analyze from a payload.
"""
def wrapper(*args, **kwargs):
# tuple: output command, path given from command line,
# path of templ file when you give the payload
out, given_p... | python | def clean(func):
"""
This decorator removes the temp file from disk. This is the case where
you want to analyze from a payload.
"""
def wrapper(*args, **kwargs):
# tuple: output command, path given from command line,
# path of templ file when you give the payload
out, given_p... | [
"def",
"clean",
"(",
"func",
")",
":",
"def",
"wrapper",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"# tuple: output command, path given from command line,",
"# path of templ file when you give the payload",
"out",
",",
"given_path",
",",
"path",
"=",
"fun... | This decorator removes the temp file from disk. This is the case where
you want to analyze from a payload. | [
"This",
"decorator",
"removes",
"the",
"temp",
"file",
"from",
"disk",
".",
"This",
"is",
"the",
"case",
"where",
"you",
"want",
"to",
"analyze",
"from",
"a",
"payload",
"."
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/utils.py#L43-L61 |
46,255 | fedelemantuano/tika-app-python | tikapp/utils.py | file_path | def file_path(path=None, payload=None, objectInput=None):
"""
Given a file path, payload or file object, it writes file on disk and
returns the temp path.
Args:
path (string): path of real file
payload(string): payload in base64 of file
objectInput (object): file object/standard... | python | def file_path(path=None, payload=None, objectInput=None):
"""
Given a file path, payload or file object, it writes file on disk and
returns the temp path.
Args:
path (string): path of real file
payload(string): payload in base64 of file
objectInput (object): file object/standard... | [
"def",
"file_path",
"(",
"path",
"=",
"None",
",",
"payload",
"=",
"None",
",",
"objectInput",
"=",
"None",
")",
":",
"f",
"=",
"path",
"if",
"path",
"else",
"write_payload",
"(",
"payload",
",",
"objectInput",
")",
"if",
"not",
"os",
".",
"path",
".... | Given a file path, payload or file object, it writes file on disk and
returns the temp path.
Args:
path (string): path of real file
payload(string): payload in base64 of file
objectInput (object): file object/standard input to analyze
Returns:
Path of file | [
"Given",
"a",
"file",
"path",
"payload",
"or",
"file",
"object",
"it",
"writes",
"file",
"on",
"disk",
"and",
"returns",
"the",
"temp",
"path",
"."
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/utils.py#L64-L84 |
46,256 | fedelemantuano/tika-app-python | tikapp/utils.py | write_payload | def write_payload(payload=None, objectInput=None):
"""
This function writes a base64 payload or file object on disk.
Args:
payload (string): payload in base64
objectInput (object): file object/standard input to analyze
Returns:
Path of file
"""
temp = tempfile.mkstemp(... | python | def write_payload(payload=None, objectInput=None):
"""
This function writes a base64 payload or file object on disk.
Args:
payload (string): payload in base64
objectInput (object): file object/standard input to analyze
Returns:
Path of file
"""
temp = tempfile.mkstemp(... | [
"def",
"write_payload",
"(",
"payload",
"=",
"None",
",",
"objectInput",
"=",
"None",
")",
":",
"temp",
"=",
"tempfile",
".",
"mkstemp",
"(",
")",
"[",
"1",
"]",
"log",
".",
"debug",
"(",
"\"Write payload in temp file {!r}\"",
".",
"format",
"(",
"temp",
... | This function writes a base64 payload or file object on disk.
Args:
payload (string): payload in base64
objectInput (object): file object/standard input to analyze
Returns:
Path of file | [
"This",
"function",
"writes",
"a",
"base64",
"payload",
"or",
"file",
"object",
"on",
"disk",
"."
] | 9a462aa611af2032306c78a9c996c8545288c212 | https://github.com/fedelemantuano/tika-app-python/blob/9a462aa611af2032306c78a9c996c8545288c212/tikapp/utils.py#L87-L113 |
46,257 | pudo/jsonmapping | jsonmapping/statements.py | StatementsVisitor.get_subject | def get_subject(self, data):
""" Try to get a unique ID from the object. By default, this will be
the 'id' field of any given object, or a field specified by the
'rdfSubject' property. If no other option is available, a UUID will be
generated. """
if not isinstance(data, Mapping)... | python | def get_subject(self, data):
""" Try to get a unique ID from the object. By default, this will be
the 'id' field of any given object, or a field specified by the
'rdfSubject' property. If no other option is available, a UUID will be
generated. """
if not isinstance(data, Mapping)... | [
"def",
"get_subject",
"(",
"self",
",",
"data",
")",
":",
"if",
"not",
"isinstance",
"(",
"data",
",",
"Mapping",
")",
":",
"return",
"None",
"if",
"data",
".",
"get",
"(",
"self",
".",
"subject",
")",
":",
"return",
"data",
".",
"get",
"(",
"self"... | Try to get a unique ID from the object. By default, this will be
the 'id' field of any given object, or a field specified by the
'rdfSubject' property. If no other option is available, a UUID will be
generated. | [
"Try",
"to",
"get",
"a",
"unique",
"ID",
"from",
"the",
"object",
".",
"By",
"default",
"this",
"will",
"be",
"the",
"id",
"field",
"of",
"any",
"given",
"object",
"or",
"a",
"field",
"specified",
"by",
"the",
"rdfSubject",
"property",
".",
"If",
"no",... | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/statements.py#L22-L31 |
46,258 | pudo/jsonmapping | jsonmapping/statements.py | StatementsVisitor.triplify | def triplify(self, data, parent=None):
""" Recursively generate statements from the data supplied. """
if data is None:
return
if self.is_object:
for res in self._triplify_object(data, parent):
yield res
elif self.is_array:
for item in... | python | def triplify(self, data, parent=None):
""" Recursively generate statements from the data supplied. """
if data is None:
return
if self.is_object:
for res in self._triplify_object(data, parent):
yield res
elif self.is_array:
for item in... | [
"def",
"triplify",
"(",
"self",
",",
"data",
",",
"parent",
"=",
"None",
")",
":",
"if",
"data",
"is",
"None",
":",
"return",
"if",
"self",
".",
"is_object",
":",
"for",
"res",
"in",
"self",
".",
"_triplify_object",
"(",
"data",
",",
"parent",
")",
... | Recursively generate statements from the data supplied. | [
"Recursively",
"generate",
"statements",
"from",
"the",
"data",
"supplied",
"."
] | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/statements.py#L53-L71 |
46,259 | pudo/jsonmapping | jsonmapping/statements.py | StatementsVisitor._triplify_object | def _triplify_object(self, data, parent):
""" Create bi-directional statements for object relationships. """
subject = self.get_subject(data)
if self.path:
yield (subject, TYPE_SCHEMA, self.path, TYPE_SCHEMA)
if parent is not None:
yield (parent, self.predicate, ... | python | def _triplify_object(self, data, parent):
""" Create bi-directional statements for object relationships. """
subject = self.get_subject(data)
if self.path:
yield (subject, TYPE_SCHEMA, self.path, TYPE_SCHEMA)
if parent is not None:
yield (parent, self.predicate, ... | [
"def",
"_triplify_object",
"(",
"self",
",",
"data",
",",
"parent",
")",
":",
"subject",
"=",
"self",
".",
"get_subject",
"(",
"data",
")",
"if",
"self",
".",
"path",
":",
"yield",
"(",
"subject",
",",
"TYPE_SCHEMA",
",",
"self",
".",
"path",
",",
"T... | Create bi-directional statements for object relationships. | [
"Create",
"bi",
"-",
"directional",
"statements",
"for",
"object",
"relationships",
"."
] | 4cf0a20a393ba82e00651c6fd39522a67a0155de | https://github.com/pudo/jsonmapping/blob/4cf0a20a393ba82e00651c6fd39522a67a0155de/jsonmapping/statements.py#L73-L86 |
46,260 | praekelt/django-simple-autocomplete | simple_autocomplete/views.py | get_json | def get_json(request, token):
"""Return matching results as JSON"""
result = []
searchtext = request.GET['q']
if len(searchtext) >= 3:
pickled = _simple_autocomplete_queryset_cache.get(token, None)
if pickled is not None:
app_label, model_name, query = pickle.loads(pickled)
... | python | def get_json(request, token):
"""Return matching results as JSON"""
result = []
searchtext = request.GET['q']
if len(searchtext) >= 3:
pickled = _simple_autocomplete_queryset_cache.get(token, None)
if pickled is not None:
app_label, model_name, query = pickle.loads(pickled)
... | [
"def",
"get_json",
"(",
"request",
",",
"token",
")",
":",
"result",
"=",
"[",
"]",
"searchtext",
"=",
"request",
".",
"GET",
"[",
"'q'",
"]",
"if",
"len",
"(",
"searchtext",
")",
">=",
"3",
":",
"pickled",
"=",
"_simple_autocomplete_queryset_cache",
"."... | Return matching results as JSON | [
"Return",
"matching",
"results",
"as",
"JSON"
] | 925b639a6a7fac2350dda9656845d8bd9aa2e748 | https://github.com/praekelt/django-simple-autocomplete/blob/925b639a6a7fac2350dda9656845d8bd9aa2e748/simple_autocomplete/views.py#L14-L62 |
46,261 | kgori/treeCl | treeCl/parsers.py | RaxmlParser._dash_f_e_to_dict | def _dash_f_e_to_dict(self, info_filename, tree_filename):
"""
Raxml provides an option to fit model params to a tree,
selected with -f e.
The output is different and needs a different parser.
"""
with open(info_filename) as fl:
models, likelihood, partition_p... | python | def _dash_f_e_to_dict(self, info_filename, tree_filename):
"""
Raxml provides an option to fit model params to a tree,
selected with -f e.
The output is different and needs a different parser.
"""
with open(info_filename) as fl:
models, likelihood, partition_p... | [
"def",
"_dash_f_e_to_dict",
"(",
"self",
",",
"info_filename",
",",
"tree_filename",
")",
":",
"with",
"open",
"(",
"info_filename",
")",
"as",
"fl",
":",
"models",
",",
"likelihood",
",",
"partition_params",
"=",
"self",
".",
"_dash_f_e_parser",
".",
"parseFi... | Raxml provides an option to fit model params to a tree,
selected with -f e.
The output is different and needs a different parser. | [
"Raxml",
"provides",
"an",
"option",
"to",
"fit",
"model",
"params",
"to",
"a",
"tree",
"selected",
"with",
"-",
"f",
"e",
".",
"The",
"output",
"is",
"different",
"and",
"needs",
"a",
"different",
"parser",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/parsers.py#L222-L246 |
46,262 | kgori/treeCl | treeCl/parsers.py | RaxmlParser.to_dict | def to_dict(self, info_filename, tree_filename, dash_f_e=False):
"""
Parse raxml output and return a dict
Option dash_f_e=True will parse the output of a raxml -f e run,
which has different output
"""
logger.debug('info_filename: {} {}'
.format(info_f... | python | def to_dict(self, info_filename, tree_filename, dash_f_e=False):
"""
Parse raxml output and return a dict
Option dash_f_e=True will parse the output of a raxml -f e run,
which has different output
"""
logger.debug('info_filename: {} {}'
.format(info_f... | [
"def",
"to_dict",
"(",
"self",
",",
"info_filename",
",",
"tree_filename",
",",
"dash_f_e",
"=",
"False",
")",
":",
"logger",
".",
"debug",
"(",
"'info_filename: {} {}'",
".",
"format",
"(",
"info_filename",
",",
"'(FOUND)'",
"if",
"os",
".",
"path",
".",
... | Parse raxml output and return a dict
Option dash_f_e=True will parse the output of a raxml -f e run,
which has different output | [
"Parse",
"raxml",
"output",
"and",
"return",
"a",
"dict",
"Option",
"dash_f_e",
"=",
"True",
"will",
"parse",
"the",
"output",
"of",
"a",
"raxml",
"-",
"f",
"e",
"run",
"which",
"has",
"different",
"output"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/parsers.py#L248-L261 |
46,263 | kgori/treeCl | treeCl/utils/fileIO.py | freader | def freader(filename, gz=False, bz=False):
""" Returns a filereader object that can handle gzipped input """
filecheck(filename)
if filename.endswith('.gz'):
gz = True
elif filename.endswith('.bz2'):
bz = True
if gz:
return gzip.open(filename, 'rb')
elif bz:
ret... | python | def freader(filename, gz=False, bz=False):
""" Returns a filereader object that can handle gzipped input """
filecheck(filename)
if filename.endswith('.gz'):
gz = True
elif filename.endswith('.bz2'):
bz = True
if gz:
return gzip.open(filename, 'rb')
elif bz:
ret... | [
"def",
"freader",
"(",
"filename",
",",
"gz",
"=",
"False",
",",
"bz",
"=",
"False",
")",
":",
"filecheck",
"(",
"filename",
")",
"if",
"filename",
".",
"endswith",
"(",
"'.gz'",
")",
":",
"gz",
"=",
"True",
"elif",
"filename",
".",
"endswith",
"(",
... | Returns a filereader object that can handle gzipped input | [
"Returns",
"a",
"filereader",
"object",
"that",
"can",
"handle",
"gzipped",
"input"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/utils/fileIO.py#L132-L146 |
46,264 | kgori/treeCl | treeCl/utils/fileIO.py | fwriter | def fwriter(filename, gz=False, bz=False):
""" Returns a filewriter object that can write plain or gzipped output.
If gzip or bzip2 compression is asked for then the usual filename extension will be added."""
if filename.endswith('.gz'):
gz = True
elif filename.endswith('.bz2'):
bz = Tr... | python | def fwriter(filename, gz=False, bz=False):
""" Returns a filewriter object that can write plain or gzipped output.
If gzip or bzip2 compression is asked for then the usual filename extension will be added."""
if filename.endswith('.gz'):
gz = True
elif filename.endswith('.bz2'):
bz = Tr... | [
"def",
"fwriter",
"(",
"filename",
",",
"gz",
"=",
"False",
",",
"bz",
"=",
"False",
")",
":",
"if",
"filename",
".",
"endswith",
"(",
"'.gz'",
")",
":",
"gz",
"=",
"True",
"elif",
"filename",
".",
"endswith",
"(",
"'.bz2'",
")",
":",
"bz",
"=",
... | Returns a filewriter object that can write plain or gzipped output.
If gzip or bzip2 compression is asked for then the usual filename extension will be added. | [
"Returns",
"a",
"filewriter",
"object",
"that",
"can",
"write",
"plain",
"or",
"gzipped",
"output",
".",
"If",
"gzip",
"or",
"bzip2",
"compression",
"is",
"asked",
"for",
"then",
"the",
"usual",
"filename",
"extension",
"will",
"be",
"added",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/utils/fileIO.py#L149-L167 |
46,265 | kgori/treeCl | treeCl/utils/fileIO.py | glob_by_extensions | def glob_by_extensions(directory, extensions):
""" Returns files matched by all extensions in the extensions list """
directorycheck(directory)
files = []
xt = files.extend
for ex in extensions:
xt(glob.glob('{0}/*.{1}'.format(directory, ex)))
return files | python | def glob_by_extensions(directory, extensions):
""" Returns files matched by all extensions in the extensions list """
directorycheck(directory)
files = []
xt = files.extend
for ex in extensions:
xt(glob.glob('{0}/*.{1}'.format(directory, ex)))
return files | [
"def",
"glob_by_extensions",
"(",
"directory",
",",
"extensions",
")",
":",
"directorycheck",
"(",
"directory",
")",
"files",
"=",
"[",
"]",
"xt",
"=",
"files",
".",
"extend",
"for",
"ex",
"in",
"extensions",
":",
"xt",
"(",
"glob",
".",
"glob",
"(",
"... | Returns files matched by all extensions in the extensions list | [
"Returns",
"files",
"matched",
"by",
"all",
"extensions",
"in",
"the",
"extensions",
"list"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/utils/fileIO.py#L170-L177 |
46,266 | kgori/treeCl | treeCl/utils/fileIO.py | head | def head(filename, n=10):
""" prints the top `n` lines of a file """
with freader(filename) as fr:
for _ in range(n):
print(fr.readline().strip()) | python | def head(filename, n=10):
""" prints the top `n` lines of a file """
with freader(filename) as fr:
for _ in range(n):
print(fr.readline().strip()) | [
"def",
"head",
"(",
"filename",
",",
"n",
"=",
"10",
")",
":",
"with",
"freader",
"(",
"filename",
")",
"as",
"fr",
":",
"for",
"_",
"in",
"range",
"(",
"n",
")",
":",
"print",
"(",
"fr",
".",
"readline",
"(",
")",
".",
"strip",
"(",
")",
")"... | prints the top `n` lines of a file | [
"prints",
"the",
"top",
"n",
"lines",
"of",
"a",
"file"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/utils/fileIO.py#L190-L194 |
46,267 | synw/django-instant | instant/utils.py | channels_for_role | def channels_for_role(role):
"""
Get the channels for a role
"""
chans = []
chans_names = []
# default channels
if role == "public":
if ENABLE_PUBLIC_CHANNEL is True:
chan = dict(slug=PUBLIC_CHANNEL, path=None)
chans.append(chan)
chans_names.append... | python | def channels_for_role(role):
"""
Get the channels for a role
"""
chans = []
chans_names = []
# default channels
if role == "public":
if ENABLE_PUBLIC_CHANNEL is True:
chan = dict(slug=PUBLIC_CHANNEL, path=None)
chans.append(chan)
chans_names.append... | [
"def",
"channels_for_role",
"(",
"role",
")",
":",
"chans",
"=",
"[",
"]",
"chans_names",
"=",
"[",
"]",
"# default channels",
"if",
"role",
"==",
"\"public\"",
":",
"if",
"ENABLE_PUBLIC_CHANNEL",
"is",
"True",
":",
"chan",
"=",
"dict",
"(",
"slug",
"=",
... | Get the channels for a role | [
"Get",
"the",
"channels",
"for",
"a",
"role"
] | 784ab068a7e83f76723763437ecbcc9294ab029a | https://github.com/synw/django-instant/blob/784ab068a7e83f76723763437ecbcc9294ab029a/instant/utils.py#L41-L96 |
46,268 | kgori/treeCl | treeCl/tree.py | ILS.ils | def ils(self, node, sorting_times=None, force_topology_change=True):
"""
A constrained and approximation of ILS using nearest-neighbour interchange
Process
-------
A node with at least three descendents is selected from an ultrametric tree
(node '2', below)
... | python | def ils(self, node, sorting_times=None, force_topology_change=True):
"""
A constrained and approximation of ILS using nearest-neighbour interchange
Process
-------
A node with at least three descendents is selected from an ultrametric tree
(node '2', below)
... | [
"def",
"ils",
"(",
"self",
",",
"node",
",",
"sorting_times",
"=",
"None",
",",
"force_topology_change",
"=",
"True",
")",
":",
"# node = '2', par = '1', gpar = '0' -- in above diagram",
"n_2",
"=",
"node",
"n_1",
"=",
"n_2",
".",
"parent_node",
"if",
"n_1",
"==... | A constrained and approximation of ILS using nearest-neighbour interchange
Process
-------
A node with at least three descendents is selected from an ultrametric tree
(node '2', below)
---0--... ---0--... ---0--...
| | ... | [
"A",
"constrained",
"and",
"approximation",
"of",
"ILS",
"using",
"nearest",
"-",
"neighbour",
"interchange"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L464-L581 |
46,269 | kgori/treeCl | treeCl/tree.py | Tree.get_inner_edges | def get_inner_edges(self):
""" Returns a list of the internal edges of the tree. """
inner_edges = [e for e in self._tree.preorder_edge_iter() if e.is_internal()
and e.head_node and e.tail_node]
return inner_edges | python | def get_inner_edges(self):
""" Returns a list of the internal edges of the tree. """
inner_edges = [e for e in self._tree.preorder_edge_iter() if e.is_internal()
and e.head_node and e.tail_node]
return inner_edges | [
"def",
"get_inner_edges",
"(",
"self",
")",
":",
"inner_edges",
"=",
"[",
"e",
"for",
"e",
"in",
"self",
".",
"_tree",
".",
"preorder_edge_iter",
"(",
")",
"if",
"e",
".",
"is_internal",
"(",
")",
"and",
"e",
".",
"head_node",
"and",
"e",
".",
"tail_... | Returns a list of the internal edges of the tree. | [
"Returns",
"a",
"list",
"of",
"the",
"internal",
"edges",
"of",
"the",
"tree",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L897-L901 |
46,270 | kgori/treeCl | treeCl/tree.py | Tree.intersection | def intersection(self, other):
""" Returns the intersection of the taxon sets of two Trees """
taxa1 = self.labels
taxa2 = other.labels
return taxa1 & taxa2 | python | def intersection(self, other):
""" Returns the intersection of the taxon sets of two Trees """
taxa1 = self.labels
taxa2 = other.labels
return taxa1 & taxa2 | [
"def",
"intersection",
"(",
"self",
",",
"other",
")",
":",
"taxa1",
"=",
"self",
".",
"labels",
"taxa2",
"=",
"other",
".",
"labels",
"return",
"taxa1",
"&",
"taxa2"
] | Returns the intersection of the taxon sets of two Trees | [
"Returns",
"the",
"intersection",
"of",
"the",
"taxon",
"sets",
"of",
"two",
"Trees"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L907-L911 |
46,271 | kgori/treeCl | treeCl/tree.py | Tree.postorder | def postorder(self, skip_seed=False):
"""
Return a generator that yields the nodes of the tree in postorder.
If skip_seed=True then the root node is not included.
"""
for node in self._tree.postorder_node_iter():
if skip_seed and node is self._tree.seed_node:
... | python | def postorder(self, skip_seed=False):
"""
Return a generator that yields the nodes of the tree in postorder.
If skip_seed=True then the root node is not included.
"""
for node in self._tree.postorder_node_iter():
if skip_seed and node is self._tree.seed_node:
... | [
"def",
"postorder",
"(",
"self",
",",
"skip_seed",
"=",
"False",
")",
":",
"for",
"node",
"in",
"self",
".",
"_tree",
".",
"postorder_node_iter",
"(",
")",
":",
"if",
"skip_seed",
"and",
"node",
"is",
"self",
".",
"_tree",
".",
"seed_node",
":",
"conti... | Return a generator that yields the nodes of the tree in postorder.
If skip_seed=True then the root node is not included. | [
"Return",
"a",
"generator",
"that",
"yields",
"the",
"nodes",
"of",
"the",
"tree",
"in",
"postorder",
".",
"If",
"skip_seed",
"=",
"True",
"then",
"the",
"root",
"node",
"is",
"not",
"included",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L978-L986 |
46,272 | kgori/treeCl | treeCl/tree.py | Tree.preorder | def preorder(self, skip_seed=False):
"""
Return a generator that yields the nodes of the tree in preorder.
If skip_seed=True then the root node is not included.
"""
for node in self._tree.preorder_node_iter():
if skip_seed and node is self._tree.seed_node:
... | python | def preorder(self, skip_seed=False):
"""
Return a generator that yields the nodes of the tree in preorder.
If skip_seed=True then the root node is not included.
"""
for node in self._tree.preorder_node_iter():
if skip_seed and node is self._tree.seed_node:
... | [
"def",
"preorder",
"(",
"self",
",",
"skip_seed",
"=",
"False",
")",
":",
"for",
"node",
"in",
"self",
".",
"_tree",
".",
"preorder_node_iter",
"(",
")",
":",
"if",
"skip_seed",
"and",
"node",
"is",
"self",
".",
"_tree",
".",
"seed_node",
":",
"continu... | Return a generator that yields the nodes of the tree in preorder.
If skip_seed=True then the root node is not included. | [
"Return",
"a",
"generator",
"that",
"yields",
"the",
"nodes",
"of",
"the",
"tree",
"in",
"preorder",
".",
"If",
"skip_seed",
"=",
"True",
"then",
"the",
"root",
"node",
"is",
"not",
"included",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L988-L996 |
46,273 | kgori/treeCl | treeCl/tree.py | Tree.prune_to_subset | def prune_to_subset(self, subset, inplace=False):
""" Prunes the Tree to just the taxon set given in `subset` """
if not subset.issubset(self.labels):
print('"subset" is not a subset')
return
if not inplace:
t = self.copy()
else:
t = self
... | python | def prune_to_subset(self, subset, inplace=False):
""" Prunes the Tree to just the taxon set given in `subset` """
if not subset.issubset(self.labels):
print('"subset" is not a subset')
return
if not inplace:
t = self.copy()
else:
t = self
... | [
"def",
"prune_to_subset",
"(",
"self",
",",
"subset",
",",
"inplace",
"=",
"False",
")",
":",
"if",
"not",
"subset",
".",
"issubset",
"(",
"self",
".",
"labels",
")",
":",
"print",
"(",
"'\"subset\" is not a subset'",
")",
"return",
"if",
"not",
"inplace",... | Prunes the Tree to just the taxon set given in `subset` | [
"Prunes",
"the",
"Tree",
"to",
"just",
"the",
"taxon",
"set",
"given",
"in",
"subset"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L998-L1010 |
46,274 | kgori/treeCl | treeCl/tree.py | Tree.randomise_branch_lengths | def randomise_branch_lengths(
self,
i=(1, 1),
l=(1, 1),
distribution_func=random.gammavariate,
inplace=False,
):
""" Replaces branch lengths with values drawn from the specified
distribution_func. Parameters of the distribution are given in... | python | def randomise_branch_lengths(
self,
i=(1, 1),
l=(1, 1),
distribution_func=random.gammavariate,
inplace=False,
):
""" Replaces branch lengths with values drawn from the specified
distribution_func. Parameters of the distribution are given in... | [
"def",
"randomise_branch_lengths",
"(",
"self",
",",
"i",
"=",
"(",
"1",
",",
"1",
")",
",",
"l",
"=",
"(",
"1",
",",
"1",
")",
",",
"distribution_func",
"=",
"random",
".",
"gammavariate",
",",
"inplace",
"=",
"False",
",",
")",
":",
"if",
"not",
... | Replaces branch lengths with values drawn from the specified
distribution_func. Parameters of the distribution are given in the
tuples i and l, for interior and leaf nodes respectively. | [
"Replaces",
"branch",
"lengths",
"with",
"values",
"drawn",
"from",
"the",
"specified",
"distribution_func",
".",
"Parameters",
"of",
"the",
"distribution",
"are",
"given",
"in",
"the",
"tuples",
"i",
"and",
"l",
"for",
"interior",
"and",
"leaf",
"nodes",
"res... | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1012-L1034 |
46,275 | kgori/treeCl | treeCl/tree.py | Tree.randomise_labels | def randomise_labels(
self,
inplace=False,
):
""" Shuffles the leaf labels, but doesn't alter the tree structure """
if not inplace:
t = self.copy()
else:
t = self
names = list(t.labels)
random.shuffle(names)
for l in ... | python | def randomise_labels(
self,
inplace=False,
):
""" Shuffles the leaf labels, but doesn't alter the tree structure """
if not inplace:
t = self.copy()
else:
t = self
names = list(t.labels)
random.shuffle(names)
for l in ... | [
"def",
"randomise_labels",
"(",
"self",
",",
"inplace",
"=",
"False",
",",
")",
":",
"if",
"not",
"inplace",
":",
"t",
"=",
"self",
".",
"copy",
"(",
")",
"else",
":",
"t",
"=",
"self",
"names",
"=",
"list",
"(",
"t",
".",
"labels",
")",
"random"... | Shuffles the leaf labels, but doesn't alter the tree structure | [
"Shuffles",
"the",
"leaf",
"labels",
"but",
"doesn",
"t",
"alter",
"the",
"tree",
"structure"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1036-L1052 |
46,276 | kgori/treeCl | treeCl/tree.py | Tree.reversible_deroot | def reversible_deroot(self):
""" Stores info required to restore rootedness to derooted Tree. Returns
the edge that was originally rooted, the length of e1, and the length
of e2.
Dendropy Derooting Process:
In a rooted tree the root node is bifurcating. Derooting makes it
... | python | def reversible_deroot(self):
""" Stores info required to restore rootedness to derooted Tree. Returns
the edge that was originally rooted, the length of e1, and the length
of e2.
Dendropy Derooting Process:
In a rooted tree the root node is bifurcating. Derooting makes it
... | [
"def",
"reversible_deroot",
"(",
"self",
")",
":",
"root_edge",
"=",
"self",
".",
"_tree",
".",
"seed_node",
".",
"edge",
"lengths",
"=",
"dict",
"(",
"[",
"(",
"edge",
",",
"edge",
".",
"length",
")",
"for",
"edge",
"in",
"self",
".",
"_tree",
".",
... | Stores info required to restore rootedness to derooted Tree. Returns
the edge that was originally rooted, the length of e1, and the length
of e2.
Dendropy Derooting Process:
In a rooted tree the root node is bifurcating. Derooting makes it
trifurcating.
Call the two edg... | [
"Stores",
"info",
"required",
"to",
"restore",
"rootedness",
"to",
"derooted",
"Tree",
".",
"Returns",
"the",
"edge",
"that",
"was",
"originally",
"rooted",
"the",
"length",
"of",
"e1",
"and",
"the",
"length",
"of",
"e2",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1054-L1089 |
46,277 | kgori/treeCl | treeCl/tree.py | Tree.rlgt | def rlgt(self, time=None, times=1,
disallow_sibling_lgts=False):
""" Uses class LGT to perform random lateral gene transfer on
ultrametric tree """
lgt = LGT(self.copy())
for _ in range(times):
lgt.rlgt(time, disallow_sibling_lgts)
return lgt.tree | python | def rlgt(self, time=None, times=1,
disallow_sibling_lgts=False):
""" Uses class LGT to perform random lateral gene transfer on
ultrametric tree """
lgt = LGT(self.copy())
for _ in range(times):
lgt.rlgt(time, disallow_sibling_lgts)
return lgt.tree | [
"def",
"rlgt",
"(",
"self",
",",
"time",
"=",
"None",
",",
"times",
"=",
"1",
",",
"disallow_sibling_lgts",
"=",
"False",
")",
":",
"lgt",
"=",
"LGT",
"(",
"self",
".",
"copy",
"(",
")",
")",
"for",
"_",
"in",
"range",
"(",
"times",
")",
":",
"... | Uses class LGT to perform random lateral gene transfer on
ultrametric tree | [
"Uses",
"class",
"LGT",
"to",
"perform",
"random",
"lateral",
"gene",
"transfer",
"on",
"ultrametric",
"tree"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1130-L1138 |
46,278 | kgori/treeCl | treeCl/tree.py | Tree.scale | def scale(self, factor, inplace=True):
""" Multiplies all branch lengths by factor. """
if not inplace:
t = self.copy()
else:
t = self
t._tree.scale_edges(factor)
t._dirty = True
return t | python | def scale(self, factor, inplace=True):
""" Multiplies all branch lengths by factor. """
if not inplace:
t = self.copy()
else:
t = self
t._tree.scale_edges(factor)
t._dirty = True
return t | [
"def",
"scale",
"(",
"self",
",",
"factor",
",",
"inplace",
"=",
"True",
")",
":",
"if",
"not",
"inplace",
":",
"t",
"=",
"self",
".",
"copy",
"(",
")",
"else",
":",
"t",
"=",
"self",
"t",
".",
"_tree",
".",
"scale_edges",
"(",
"factor",
")",
"... | Multiplies all branch lengths by factor. | [
"Multiplies",
"all",
"branch",
"lengths",
"by",
"factor",
"."
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1164-L1172 |
46,279 | kgori/treeCl | treeCl/tree.py | Tree.strip | def strip(self, inplace=False):
""" Sets all edge lengths to None """
if not inplace:
t = self.copy()
else:
t = self
for e in t._tree.preorder_edge_iter():
e.length = None
t._dirty = True
return t | python | def strip(self, inplace=False):
""" Sets all edge lengths to None """
if not inplace:
t = self.copy()
else:
t = self
for e in t._tree.preorder_edge_iter():
e.length = None
t._dirty = True
return t | [
"def",
"strip",
"(",
"self",
",",
"inplace",
"=",
"False",
")",
":",
"if",
"not",
"inplace",
":",
"t",
"=",
"self",
".",
"copy",
"(",
")",
"else",
":",
"t",
"=",
"self",
"for",
"e",
"in",
"t",
".",
"_tree",
".",
"preorder_edge_iter",
"(",
")",
... | Sets all edge lengths to None | [
"Sets",
"all",
"edge",
"lengths",
"to",
"None"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1174-L1183 |
46,280 | kgori/treeCl | treeCl/tree.py | Tree._name_things | def _name_things(self):
""" Easy names for debugging """
edges = {}
nodes = {None: 'root'}
for n in self._tree.postorder_node_iter():
nodes[n] = '.'.join([str(x.taxon) for x in n.leaf_nodes()])
for e in self._tree.preorder_edge_iter():
edges[e] = ' ---> '.... | python | def _name_things(self):
""" Easy names for debugging """
edges = {}
nodes = {None: 'root'}
for n in self._tree.postorder_node_iter():
nodes[n] = '.'.join([str(x.taxon) for x in n.leaf_nodes()])
for e in self._tree.preorder_edge_iter():
edges[e] = ' ---> '.... | [
"def",
"_name_things",
"(",
"self",
")",
":",
"edges",
"=",
"{",
"}",
"nodes",
"=",
"{",
"None",
":",
"'root'",
"}",
"for",
"n",
"in",
"self",
".",
"_tree",
".",
"postorder_node_iter",
"(",
")",
":",
"nodes",
"[",
"n",
"]",
"=",
"'.'",
".",
"join... | Easy names for debugging | [
"Easy",
"names",
"for",
"debugging"
] | fed624b3db1c19cc07175ca04e3eda6905a8d305 | https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/tree.py#L1197-L1208 |
46,281 | pysal/spglm | spglm/glm.py | GLM.fit | def fit(self, ini_betas=None, tol=1.0e-6, max_iter=200, solve='iwls'):
"""
Method that fits a model with a particular estimation routine.
Parameters
----------
ini_betas : array
k*1, initial coefficient values, including constant.
... | python | def fit(self, ini_betas=None, tol=1.0e-6, max_iter=200, solve='iwls'):
"""
Method that fits a model with a particular estimation routine.
Parameters
----------
ini_betas : array
k*1, initial coefficient values, including constant.
... | [
"def",
"fit",
"(",
"self",
",",
"ini_betas",
"=",
"None",
",",
"tol",
"=",
"1.0e-6",
",",
"max_iter",
"=",
"200",
",",
"solve",
"=",
"'iwls'",
")",
":",
"self",
".",
"fit_params",
"[",
"'ini_betas'",
"]",
"=",
"ini_betas",
"self",
".",
"fit_params",
... | Method that fits a model with a particular estimation routine.
Parameters
----------
ini_betas : array
k*1, initial coefficient values, including constant.
Default is None, which calculates initial values during
estima... | [
"Method",
"that",
"fits",
"a",
"model",
"with",
"a",
"particular",
"estimation",
"routine",
"."
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/glm.py#L107-L135 |
46,282 | pysal/spglm | spglm/links.py | Logit.inverse | def inverse(self, z):
"""
Inverse of the logit transform
Parameters
----------
z : array-like
The value of the logit transform at `p`
Returns
-------
p : array
Probabilities
Notes
-----
g^(-1)(z) = exp(z)/... | python | def inverse(self, z):
"""
Inverse of the logit transform
Parameters
----------
z : array-like
The value of the logit transform at `p`
Returns
-------
p : array
Probabilities
Notes
-----
g^(-1)(z) = exp(z)/... | [
"def",
"inverse",
"(",
"self",
",",
"z",
")",
":",
"z",
"=",
"np",
".",
"asarray",
"(",
"z",
")",
"t",
"=",
"np",
".",
"exp",
"(",
"-",
"z",
")",
"return",
"1.",
"/",
"(",
"1.",
"+",
"t",
")"
] | Inverse of the logit transform
Parameters
----------
z : array-like
The value of the logit transform at `p`
Returns
-------
p : array
Probabilities
Notes
-----
g^(-1)(z) = exp(z)/(1+exp(z)) | [
"Inverse",
"of",
"the",
"logit",
"transform"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L149-L169 |
46,283 | pysal/spglm | spglm/links.py | Power.inverse | def inverse(self, z):
"""
Inverse of the power transform link function
Parameters
----------
`z` : array-like
Value of the transformed mean parameters at `p`
Returns
-------
`p` : array
Mean parameters
Notes
-----... | python | def inverse(self, z):
"""
Inverse of the power transform link function
Parameters
----------
`z` : array-like
Value of the transformed mean parameters at `p`
Returns
-------
`p` : array
Mean parameters
Notes
-----... | [
"def",
"inverse",
"(",
"self",
",",
"z",
")",
":",
"p",
"=",
"np",
".",
"power",
"(",
"z",
",",
"1.",
"/",
"self",
".",
"power",
")",
"return",
"p"
] | Inverse of the power transform link function
Parameters
----------
`z` : array-like
Value of the transformed mean parameters at `p`
Returns
-------
`p` : array
Mean parameters
Notes
-----
g^(-1)(z`) = `z`**(1/`power`) | [
"Inverse",
"of",
"the",
"power",
"transform",
"link",
"function"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L279-L299 |
46,284 | pysal/spglm | spglm/links.py | Power.deriv | def deriv(self, p):
"""
Derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g'(p) : array
Derivative of power transform of `p`
Notes
-----
g'(`p`) = `pow... | python | def deriv(self, p):
"""
Derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g'(p) : array
Derivative of power transform of `p`
Notes
-----
g'(`p`) = `pow... | [
"def",
"deriv",
"(",
"self",
",",
"p",
")",
":",
"return",
"self",
".",
"power",
"*",
"np",
".",
"power",
"(",
"p",
",",
"self",
".",
"power",
"-",
"1",
")"
] | Derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g'(p) : array
Derivative of power transform of `p`
Notes
-----
g'(`p`) = `power` * `p`**(`power` - 1) | [
"Derivative",
"of",
"the",
"power",
"transform"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L301-L319 |
46,285 | pysal/spglm | spglm/links.py | Power.deriv2 | def deriv2(self, p):
"""
Second derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g''(p) : array
Second derivative of the power transform of `p`
Notes
-----
... | python | def deriv2(self, p):
"""
Second derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g''(p) : array
Second derivative of the power transform of `p`
Notes
-----
... | [
"def",
"deriv2",
"(",
"self",
",",
"p",
")",
":",
"return",
"self",
".",
"power",
"*",
"(",
"self",
".",
"power",
"-",
"1",
")",
"*",
"np",
".",
"power",
"(",
"p",
",",
"self",
".",
"power",
"-",
"2",
")"
] | Second derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g''(p) : array
Second derivative of the power transform of `p`
Notes
-----
g''(`p`) = `power` * (`power` - 1) ... | [
"Second",
"derivative",
"of",
"the",
"power",
"transform"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L321-L339 |
46,286 | pysal/spglm | spglm/links.py | Power.inverse_deriv | def inverse_deriv(self, z):
"""
Derivative of the inverse of the power transform
Parameters
----------
z : array-like
`z` is usually the linear predictor for a GLM or GEE model.
Returns
-------
g^(-1)'(z) : array
The value of the ... | python | def inverse_deriv(self, z):
"""
Derivative of the inverse of the power transform
Parameters
----------
z : array-like
`z` is usually the linear predictor for a GLM or GEE model.
Returns
-------
g^(-1)'(z) : array
The value of the ... | [
"def",
"inverse_deriv",
"(",
"self",
",",
"z",
")",
":",
"return",
"np",
".",
"power",
"(",
"z",
",",
"(",
"1",
"-",
"self",
".",
"power",
")",
"/",
"self",
".",
"power",
")",
"/",
"self",
".",
"power"
] | Derivative of the inverse of the power transform
Parameters
----------
z : array-like
`z` is usually the linear predictor for a GLM or GEE model.
Returns
-------
g^(-1)'(z) : array
The value of the derivative of the inverse of the power transform... | [
"Derivative",
"of",
"the",
"inverse",
"of",
"the",
"power",
"transform"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L341-L356 |
46,287 | pysal/spglm | spglm/links.py | CDFLink.deriv | def deriv(self, p):
"""
Derivative of CDF link
Parameters
----------
p : array-like
mean parameters
Returns
-------
g'(p) : array
The derivative of CDF transform at `p`
Notes
-----
g'(`p`) = 1./ `dbn`.pdf(... | python | def deriv(self, p):
"""
Derivative of CDF link
Parameters
----------
p : array-like
mean parameters
Returns
-------
g'(p) : array
The derivative of CDF transform at `p`
Notes
-----
g'(`p`) = 1./ `dbn`.pdf(... | [
"def",
"deriv",
"(",
"self",
",",
"p",
")",
":",
"p",
"=",
"self",
".",
"_clean",
"(",
"p",
")",
"return",
"1.",
"/",
"self",
".",
"dbn",
".",
"pdf",
"(",
"self",
".",
"dbn",
".",
"ppf",
"(",
"p",
")",
")"
] | Derivative of CDF link
Parameters
----------
p : array-like
mean parameters
Returns
-------
g'(p) : array
The derivative of CDF transform at `p`
Notes
-----
g'(`p`) = 1./ `dbn`.pdf(`dbn`.ppf(`p`)) | [
"Derivative",
"of",
"CDF",
"link"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L602-L621 |
46,288 | pysal/spglm | spglm/links.py | cauchy.deriv2 | def deriv2(self, p):
"""
Second derivative of the Cauchy link function.
Parameters
----------
p: array-like
Probabilities
Returns
-------
g''(p) : array
Value of the second derivative of Cauchy link function at `p`
"""
... | python | def deriv2(self, p):
"""
Second derivative of the Cauchy link function.
Parameters
----------
p: array-like
Probabilities
Returns
-------
g''(p) : array
Value of the second derivative of Cauchy link function at `p`
"""
... | [
"def",
"deriv2",
"(",
"self",
",",
"p",
")",
":",
"a",
"=",
"np",
".",
"pi",
"*",
"(",
"p",
"-",
"0.5",
")",
"d2",
"=",
"2",
"*",
"np",
".",
"pi",
"**",
"2",
"*",
"np",
".",
"sin",
"(",
"a",
")",
"/",
"np",
".",
"cos",
"(",
"a",
")",
... | Second derivative of the Cauchy link function.
Parameters
----------
p: array-like
Probabilities
Returns
-------
g''(p) : array
Value of the second derivative of Cauchy link function at `p` | [
"Second",
"derivative",
"of",
"the",
"Cauchy",
"link",
"function",
"."
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L678-L694 |
46,289 | pysal/spglm | spglm/links.py | CLogLog.deriv | def deriv(self, p):
"""
Derivative of C-Log-Log transform link function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g'(p) : array
The derivative of the CLogLog transform link function
Notes
... | python | def deriv(self, p):
"""
Derivative of C-Log-Log transform link function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g'(p) : array
The derivative of the CLogLog transform link function
Notes
... | [
"def",
"deriv",
"(",
"self",
",",
"p",
")",
":",
"p",
"=",
"self",
".",
"_clean",
"(",
"p",
")",
"return",
"1.",
"/",
"(",
"(",
"p",
"-",
"1",
")",
"*",
"(",
"np",
".",
"log",
"(",
"1",
"-",
"p",
")",
")",
")"
] | Derivative of C-Log-Log transform link function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g'(p) : array
The derivative of the CLogLog transform link function
Notes
-----
g'(p) = - 1 / ((p-1)*log... | [
"Derivative",
"of",
"C",
"-",
"Log",
"-",
"Log",
"transform",
"link",
"function"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L749-L768 |
46,290 | pysal/spglm | spglm/links.py | CLogLog.deriv2 | def deriv2(self, p):
"""
Second derivative of the C-Log-Log ink function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the CLogLog link function
"""
p ... | python | def deriv2(self, p):
"""
Second derivative of the C-Log-Log ink function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the CLogLog link function
"""
p ... | [
"def",
"deriv2",
"(",
"self",
",",
"p",
")",
":",
"p",
"=",
"self",
".",
"_clean",
"(",
"p",
")",
"fl",
"=",
"np",
".",
"log",
"(",
"1",
"-",
"p",
")",
"d2",
"=",
"-",
"1",
"/",
"(",
"(",
"1",
"-",
"p",
")",
"**",
"2",
"*",
"fl",
")",... | Second derivative of the C-Log-Log ink function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the CLogLog link function | [
"Second",
"derivative",
"of",
"the",
"C",
"-",
"Log",
"-",
"Log",
"ink",
"function"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L770-L788 |
46,291 | pysal/spglm | spglm/links.py | NegativeBinomial.deriv2 | def deriv2(self,p):
'''
Second derivative of the negative binomial link function.
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the negative binomial transform link
... | python | def deriv2(self,p):
'''
Second derivative of the negative binomial link function.
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the negative binomial transform link
... | [
"def",
"deriv2",
"(",
"self",
",",
"p",
")",
":",
"numer",
"=",
"-",
"(",
"1",
"+",
"2",
"*",
"self",
".",
"alpha",
"*",
"p",
")",
"denom",
"=",
"(",
"p",
"+",
"self",
".",
"alpha",
"*",
"p",
"**",
"2",
")",
"**",
"2",
"return",
"numer",
... | Second derivative of the negative binomial link function.
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the negative binomial transform link
function
Notes
... | [
"Second",
"derivative",
"of",
"the",
"negative",
"binomial",
"link",
"function",
"."
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L900-L921 |
46,292 | pysal/spglm | spglm/links.py | NegativeBinomial.inverse_deriv | def inverse_deriv(self, z):
'''
Derivative of the inverse of the negative binomial transform
Parameters
-----------
z : array-like
Usually the linear predictor for a GLM or GEE model
Returns
-------
g^(-1)'(z) : array
The value of... | python | def inverse_deriv(self, z):
'''
Derivative of the inverse of the negative binomial transform
Parameters
-----------
z : array-like
Usually the linear predictor for a GLM or GEE model
Returns
-------
g^(-1)'(z) : array
The value of... | [
"def",
"inverse_deriv",
"(",
"self",
",",
"z",
")",
":",
"t",
"=",
"np",
".",
"exp",
"(",
"z",
")",
"return",
"t",
"/",
"(",
"self",
".",
"alpha",
"*",
"(",
"1",
"-",
"t",
")",
"**",
"2",
")"
] | Derivative of the inverse of the negative binomial transform
Parameters
-----------
z : array-like
Usually the linear predictor for a GLM or GEE model
Returns
-------
g^(-1)'(z) : array
The value of the derivative of the inverse of the negative
... | [
"Derivative",
"of",
"the",
"inverse",
"of",
"the",
"negative",
"binomial",
"transform"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/links.py#L923-L939 |
46,293 | biocommons/eutils | eutils/client.py | Client.einfo | def einfo(self, db=None):
"""query the einfo endpoint
:param db: string (optional)
:rtype: EInfo or EInfoDB object
If db is None, the reply is a list of databases, which is returned
in an EInfo object (which has a databases() method).
If db is not None, the reply is in... | python | def einfo(self, db=None):
"""query the einfo endpoint
:param db: string (optional)
:rtype: EInfo or EInfoDB object
If db is None, the reply is a list of databases, which is returned
in an EInfo object (which has a databases() method).
If db is not None, the reply is in... | [
"def",
"einfo",
"(",
"self",
",",
"db",
"=",
"None",
")",
":",
"if",
"db",
"is",
"None",
":",
"return",
"EInfoResult",
"(",
"self",
".",
"_qs",
".",
"einfo",
"(",
")",
")",
".",
"dblist",
"return",
"EInfoResult",
"(",
"self",
".",
"_qs",
".",
"ei... | query the einfo endpoint
:param db: string (optional)
:rtype: EInfo or EInfoDB object
If db is None, the reply is a list of databases, which is returned
in an EInfo object (which has a databases() method).
If db is not None, the reply is information about the specified
... | [
"query",
"the",
"einfo",
"endpoint"
] | 0ec7444fd520d2af56114122442ff8f60952db0b | https://github.com/biocommons/eutils/blob/0ec7444fd520d2af56114122442ff8f60952db0b/eutils/client.py#L52-L68 |
46,294 | biocommons/eutils | eutils/client.py | Client.esearch | def esearch(self, db, term):
"""query the esearch endpoint
"""
esr = ESearchResult(self._qs.esearch({'db': db, 'term': term}))
if esr.count > esr.retmax:
logger.warning("NCBI found {esr.count} results, but we truncated the reply at {esr.retmax}"
" resu... | python | def esearch(self, db, term):
"""query the esearch endpoint
"""
esr = ESearchResult(self._qs.esearch({'db': db, 'term': term}))
if esr.count > esr.retmax:
logger.warning("NCBI found {esr.count} results, but we truncated the reply at {esr.retmax}"
" resu... | [
"def",
"esearch",
"(",
"self",
",",
"db",
",",
"term",
")",
":",
"esr",
"=",
"ESearchResult",
"(",
"self",
".",
"_qs",
".",
"esearch",
"(",
"{",
"'db'",
":",
"db",
",",
"'term'",
":",
"term",
"}",
")",
")",
"if",
"esr",
".",
"count",
">",
"esr"... | query the esearch endpoint | [
"query",
"the",
"esearch",
"endpoint"
] | 0ec7444fd520d2af56114122442ff8f60952db0b | https://github.com/biocommons/eutils/blob/0ec7444fd520d2af56114122442ff8f60952db0b/eutils/client.py#L70-L77 |
46,295 | biocommons/eutils | eutils/client.py | Client.efetch | def efetch(self, db, id):
"""query the efetch endpoint
"""
db = db.lower()
xml = self._qs.efetch({'db': db, 'id': str(id)})
doc = le.XML(xml)
if db in ['gene']:
return EntrezgeneSet(doc)
if db in ['nuccore', 'nucest', 'protein']:
# TODO: GB... | python | def efetch(self, db, id):
"""query the efetch endpoint
"""
db = db.lower()
xml = self._qs.efetch({'db': db, 'id': str(id)})
doc = le.XML(xml)
if db in ['gene']:
return EntrezgeneSet(doc)
if db in ['nuccore', 'nucest', 'protein']:
# TODO: GB... | [
"def",
"efetch",
"(",
"self",
",",
"db",
",",
"id",
")",
":",
"db",
"=",
"db",
".",
"lower",
"(",
")",
"xml",
"=",
"self",
".",
"_qs",
".",
"efetch",
"(",
"{",
"'db'",
":",
"db",
",",
"'id'",
":",
"str",
"(",
"id",
")",
"}",
")",
"doc",
"... | query the efetch endpoint | [
"query",
"the",
"efetch",
"endpoint"
] | 0ec7444fd520d2af56114122442ff8f60952db0b | https://github.com/biocommons/eutils/blob/0ec7444fd520d2af56114122442ff8f60952db0b/eutils/client.py#L79-L96 |
46,296 | asweigart/pygbutton | pygbutton/__init__.py | PygButton.draw | def draw(self, surfaceObj):
"""Blit the current button's appearance to the surface object."""
if self._visible:
if self.buttonDown:
surfaceObj.blit(self.surfaceDown, self._rect)
elif self.mouseOverButton:
surfaceObj.blit(self.surfaceHighlight, self... | python | def draw(self, surfaceObj):
"""Blit the current button's appearance to the surface object."""
if self._visible:
if self.buttonDown:
surfaceObj.blit(self.surfaceDown, self._rect)
elif self.mouseOverButton:
surfaceObj.blit(self.surfaceHighlight, self... | [
"def",
"draw",
"(",
"self",
",",
"surfaceObj",
")",
":",
"if",
"self",
".",
"_visible",
":",
"if",
"self",
".",
"buttonDown",
":",
"surfaceObj",
".",
"blit",
"(",
"self",
".",
"surfaceDown",
",",
"self",
".",
"_rect",
")",
"elif",
"self",
".",
"mouse... | Blit the current button's appearance to the surface object. | [
"Blit",
"the",
"current",
"button",
"s",
"appearance",
"to",
"the",
"surface",
"object",
"."
] | 7fab6a0d53f2b1d2d1d83768464eb2bf2a24802b | https://github.com/asweigart/pygbutton/blob/7fab6a0d53f2b1d2d1d83768464eb2bf2a24802b/pygbutton/__init__.py#L182-L190 |
46,297 | pysal/spglm | spglm/family.py | Family._setlink | def _setlink(self, link):
"""
Helper method to set the link for a family.
Raises a ValueError exception if the link is not available. Note that
the error message might not be that informative because it tells you
that the link should be in the base class for the link function.
... | python | def _setlink(self, link):
"""
Helper method to set the link for a family.
Raises a ValueError exception if the link is not available. Note that
the error message might not be that informative because it tells you
that the link should be in the base class for the link function.
... | [
"def",
"_setlink",
"(",
"self",
",",
"link",
")",
":",
"# TODO: change the links class attribute in the families to hold",
"# meaningful information instead of a list of links instances such as",
"# [<statsmodels.family.links.Log object at 0x9a4240c>,",
"# <statsmodels.family.links.Power obje... | Helper method to set the link for a family.
Raises a ValueError exception if the link is not available. Note that
the error message might not be that informative because it tells you
that the link should be in the base class for the link function.
See glm.GLM for a list of appropriate... | [
"Helper",
"method",
"to",
"set",
"the",
"link",
"for",
"a",
"family",
"."
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/family.py#L39-L64 |
46,298 | pysal/spglm | spglm/family.py | Family.weights | def weights(self, mu):
r"""
Weights for IRLS steps
Parameters
----------
mu : array-like
The transformed mean response variable in the exponential family
Returns
-------
w : array
The weights for the IRLS steps
"""
... | python | def weights(self, mu):
r"""
Weights for IRLS steps
Parameters
----------
mu : array-like
The transformed mean response variable in the exponential family
Returns
-------
w : array
The weights for the IRLS steps
"""
... | [
"def",
"weights",
"(",
"self",
",",
"mu",
")",
":",
"return",
"1.",
"/",
"(",
"self",
".",
"link",
".",
"deriv",
"(",
"mu",
")",
"**",
"2",
"*",
"self",
".",
"variance",
"(",
"mu",
")",
")"
] | r"""
Weights for IRLS steps
Parameters
----------
mu : array-like
The transformed mean response variable in the exponential family
Returns
-------
w : array
The weights for the IRLS steps | [
"r",
"Weights",
"for",
"IRLS",
"steps"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/family.py#L96-L111 |
46,299 | pysal/spglm | spglm/family.py | Gaussian.resid_dev | def resid_dev(self, endog, mu, scale=1.):
"""
Gaussian deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional ... | python | def resid_dev(self, endog, mu, scale=1.):
"""
Gaussian deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional ... | [
"def",
"resid_dev",
"(",
"self",
",",
"endog",
",",
"mu",
",",
"scale",
"=",
"1.",
")",
":",
"return",
"(",
"endog",
"-",
"mu",
")",
"/",
"np",
".",
"sqrt",
"(",
"self",
".",
"variance",
"(",
"mu",
")",
")",
"/",
"scale"
] | Gaussian deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional argument to divide the residuals by scale. The default
... | [
"Gaussian",
"deviance",
"residuals"
] | 1339898adcb7e1638f1da83d57aa37392525f018 | https://github.com/pysal/spglm/blob/1339898adcb7e1638f1da83d57aa37392525f018/spglm/family.py#L500-L521 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.