Instruction stringlengths 362 7.83k | output_code stringlengths 1 945 |
|---|---|
Given snippet: <|code_start|>class CSVStorage(FileStorageBase):
name = 'csv'
extension = 'csv'
def load_accounts(self):
filename = self.get_accounts_filename()
if not os.path.exists(filename):
return []
with codecs.open(filename) as f:
return map(self._csv_ro... | return Account(row[0], row[1], float(row[2])) |
Using the snippet: <|code_start|>
def load_accounts(self):
filename = self.get_accounts_filename()
if not os.path.exists(filename):
return []
with codecs.open(filename) as f:
return map(self._csv_row_to_account, unicodecsv.reader(f))
def load_transactions(self, f... | return Transaction(row[0], row[1], datetime.datetime.strptime(row[2], "%Y-%m-%d").date(), |
Based on the snippet: <|code_start|>
def get_storage(name):
for o in globals().values():
if inspect.isclass(o) and issubclass(o, StorageBase) and o is not StorageBase and o.name == name:
return o
class StorageBase(object):
def __init__(self, config):
self.config = config
def ... | for date in period_to_months(start_date, end_date): |
Given the following code snippet before the placeholder: <|code_start|>
def get_storage(name):
for o in globals().values():
if inspect.isclass(o) and issubclass(o, StorageBase) and o is not StorageBase and o.name == name:
return o
class StorageBase(object):
def __init__(self, config):
... | return filter_transactions_period(transactions, start_date, end_date) |
Based on the snippet: <|code_start|>
class Command(BaseCommand):
help = "Create set of new pastes"
args = "[how many]"
def handle(self, how_many=100, **options):
for i in range(int(how_many)):
<|code_end|>
, predict the immediate next line with the help of imports:
from django.core.management.bas... | w = Wklejka(**wklejka()) |
Based on the snippet: <|code_start|>
def get_txt(self, obj):
url = obj.get_txt_url()
response = self.client.get(url)
self.assertEquals(response.status_code, 200)
self.assertEquals(response._headers['content-type'],
('Content-Type', 'text/plain; charset=utf-8... | new_obj = Wklejka.objects.get(pk=obj.id) |
Based on the snippet: <|code_start|> def test_private_url(self):
w = Wklejka(is_private=True, hash="foobar", user=self.user)
w.save()
self.get(w)
self.get_txt(w)
self.get_dl(w)
self.get_del(w)
self.post_del(w)
def test_banned_lexer(self):
w = Wklej... | userprofile = UserProfile(user=self.user) |
Here is a snippet: <|code_start|>
class UserProfile(models.Model):
user = models.ForeignKey(User, unique=True)
display_name = models.CharField(max_length=30)
current_salt = models.CharField(max_length=50)
def __unicode__(self):
return self.user.username
def username(self):
return ... | new_salt = generate_salt() |
Predict the next line after this snippet: <|code_start|>
class WklejkaTestCase(TestCase):
def test_author(self):
user = User(username="joedoe")
<|code_end|>
using the current file's imports:
from apps.wklej.models import Wklejka
from django.contrib.auth.models import User
from django.test import TestCa... | self.wklejka = Wklejka( |
Predict the next line after this snippet: <|code_start|>#coding: utf-8
def single(request, id=0, hash=''):
"""
This is very important view because it displays a single paste.
It's actually the most viewed view ever
"""
if id:
<|code_end|>
using the current file's imports:
from django.contrib.a... | w = get_object_or_404(Wklejka, pk=id, is_private=False) |
Continue the code snippet: <|code_start|>#coding: utf-8
def single(request, id=0, hash=''):
"""
This is very important view because it displays a single paste.
It's actually the most viewed view ever
"""
if id:
w = get_object_or_404(Wklejka, pk=id, is_private=False)
elif hash:
... | if hl in BANNED_LEXERS: |
Based on the snippet: <|code_start|>dispatcher = SimpleXMLRPCDispatcher(allow_none=False, encoding=None) # Py 2.5
# model
def rpc_handler(request):
"""
the actual handler:
if you setup your urls.py properly, all calls to the xml-rpc service
should be routed through here.
If post data is defined,... | w = Wklejka(nickname=autor, body=tresc, syntax=syntax) |
Next line prediction: <|code_start|> """
Pozwala zdalnie dodawac wpisy do wkleja.
"""
w = Wklejka(nickname=autor, body=tresc, syntax=syntax)
w.save()
return w.get_absolute_url()
def dodaj_prywatny_wpis(tresc, syntax, autor="Anonim"):
"""
Pozwala zdalnie dodawać prywatne wpisy do wklej... | p = UserProfile.objects.get(current_salt=salt) |
Using the snippet: <|code_start|>#coding: utf-8
class WklejAdmin(admin.ModelAdmin):
list_display = ['user', 'nickname', 'syntax', 'is_private']
search_fields = ['user', 'nickname', 'comment', 'body', 'ip']
list_filter = ['is_private', 'is_deleted', 'is_spam']
raw_id_fields = ['parent', ]
<|code_end... | admin.site.register(Wklejka, WklejAdmin) |
Given snippet: <|code_start|>#-*- coding: utf-8 -*-
class WklejkaForm(forms.ModelForm):
nickname = forms.CharField(required=False)
class Meta:
<|code_end|>
, continue by predicting the next line. Consider current file imports:
from django import forms
from apps.wklej.models import Wklejka
from lib.antispa... | model = Wklejka |
Next line prediction: <|code_start|>#-*- coding: utf-8 -*-
class WklejkaForm(forms.ModelForm):
nickname = forms.CharField(required=False)
class Meta:
model = Wklejka
fields = '__all__'
def clean_nickname(self):
if len(self.cleaned_data['nickname']) == 0:
self.cleane... | if settings.USE_CAPTCHA and check_for_link_spam(self.cleaned_data['body']): |
Next line prediction: <|code_start|> return self.cleaned_data['nickname']
def clean_body(self):
if settings.USE_CAPTCHA and check_for_link_spam(self.cleaned_data['body']):
raise forms.ValidationError("This paste looks like spam.")
return self.cleaned_data['body']
# TODO: FIXME:... | widget=forms.Select(choices=LEXERS)) |
Given the code snippet: <|code_start|>#-*- coding: utf-8 -*-
def homepage(request):
"""
This view is responsible for displaying form on the homepage.
This is actualy all what it's doing. it displays, validate, and submits
new paste into database.
"""
if not request.method == 'POST':
... | form = WklejkaForm(initial={'syntax': syntax}) |
Predict the next line after this snippet: <|code_start|>#-*- coding: utf-8 -*-
def homepage(request):
"""
This view is responsible for displaying form on the homepage.
This is actualy all what it's doing. it displays, validate, and submits
new paste into database.
"""
if not request.method =... | form = WklejkaCaptchaForm(request.POST) |
Next line prediction: <|code_start|>
class UserProfileTest(TestCase):
def setUp(self):
self.user = User(username="foobar")
self.user.save()
self.wklejka = Wklejka(user=self.user, body="foobarbaz").save()
<|code_end|>
. Use current file imports:
(from apps.userstuff.models import UserProfi... | self.userprofile = UserProfile(user=self.user) |
Given the code snippet: <|code_start|>
class UserProfileTest(TestCase):
def setUp(self):
self.user = User(username="foobar")
self.user.save()
<|code_end|>
, generate the next line using the imports in this file:
from apps.userstuff.models import UserProfile
from apps.wklej.models import Wklejka
f... | self.wklejka = Wklejka(user=self.user, body="foobarbaz").save() |
Predict the next line after this snippet: <|code_start|>
### single paste:
url(r'^id/(?P<id>\d+)/$', 'wklej.views.single', name="single"),
# and it's txt version:
url(r'^id/(?P<id>\d+)/txt/$', 'wklej.views.txt', name="txt"),
# and it's downloadable:
url(r'^id/(?P<id>\d+)/dl/$', 'wklej.views.down... | {'profile_callback': UserProfile.objects.create}, |
Using the snippet: <|code_start|> 'django.contrib.auth.views.password_reset',
{"template_name": 'registration/password_reset_form.html'},
name="password_reset"),
url(r'^reset/(?P<uidb36>[0-9A-Za-z]+)-(?P<token>.+)/$',
'django.contrib.auth.views.password_reset_confirm',
{'temp... | (r'^xmlrpc/$', rpc_handler), |
Given the code snippet: <|code_start|>
'''
connection = pika.BlockingConnection(pika.ConnectionParameters(
host=host))
channel = connection.channel()
channel.exchange_declare(exchange=exchange_info[0],
exchange_type=exchange_info[1])
chann... | if signal == application_created: |
Here is a snippet: <|code_start|>
connection = pika.BlockingConnection(pika.ConnectionParameters(
host=host))
channel = connection.channel()
channel.exchange_declare(exchange=exchange_info[0],
exchange_type=exchange_info[1])
channel.basic_publish(e... | elif signal == application_accepted_by_reviewer: |
Using the snippet: <|code_start|> host=host))
channel = connection.channel()
channel.exchange_declare(exchange=exchange_info[0],
exchange_type=exchange_info[1])
channel.basic_publish(exchange=exchange_info[0],
routing_key=routing,
... | elif signal == application_rejected_by_reviewer: |
Here is a snippet: <|code_start|>
class CommitteeTestCase(TestCase):
def test_fields(self):
'''
This model requires a committee member
and the optional count should default to 0.
'''
<|code_end|>
. Write the next line using the current file imports:
from django... | self.assertRaises(IntegrityError, Committee.objects.create) |
Predict the next line after this snippet: <|code_start|>
class CommitteeTestCase(TestCase):
def test_fields(self):
'''
This model requires a committee member
and the optional count should default to 0.
'''
self.assertRaises(IntegrityError, Committee.obje... | self.assertIsInstance(Committee.objects, CommitteeManager) |
Continue the code snippet: <|code_start|>'''
This will test the forms code for the ethicsapplication application
Created on Jul 25, 2012
@author: jasonmarshall
'''
class FormsTest(TestCase):
def test_EthicsApplication_form_title(self):
'''
Check that the form provdes a field that cannot ... | form = EthicsApplicationForm() |
Here is a snippet: <|code_start|>
class FullApplicationChecklistLinkTestCase(TestCase):
def test_fields(self):
'''
This model should specify the following fields:
checklist_question - ForeignKey(Question)
included_group - ForeignKey (QuestionGroup)
orde... | self.assertRaises(IntegrityError, FullApplicationChecklistLink.objects.create) |
Next line prediction: <|code_start|>
class FullApplicationChecklistLinkTestCase(TestCase):
def test_fields(self):
'''
This model should specify the following fields:
checklist_question - ForeignKey(Question)
included_group - ForeignKey (QuestionGroup)
o... | self.assertIsInstance(FullApplicationChecklistLink.objects, FullApplicationChecklistLinkManager) |
Given the following code snippet before the placeholder: <|code_start|> It is thisobject that will be manipulated by the workflow engine.
'''
title = models.CharField(max_length=255, default=None) #default=None stops null strings which effectively makes it mandatory
principle_investigator = ... | application_created.send(sender=self, application=self) |
Next line prediction: <|code_start|># copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS ... | fupload = FileUpload.get_by_path(filename) |
Given the code snippet: <|code_start|># Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, dist... | Page.query |
Predict the next line for this snippet: <|code_start|>"""
class test_branchScale_ExpCM(unittest.TestCase):
"""Tests `branchScale` of `ExpCM_empirical_phi` model."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-argument... | phi = numpy.random.dirichlet([7] * N_NT) |
Here is a snippet: <|code_start|>"""Tests branch scaling.
Makes sure we can correctly re-scale branch lengths into
units of substitutions per site.
Written by Jesse Bloom.
"""
class test_branchScale_ExpCM(unittest.TestCase):
"""Tests `branchScale` of `ExpCM_empirical_phi` model."""
# use approach here to ... | rprefs = numpy.random.dirichlet([1] * N_AA) |
Here is a snippet: <|code_start|>"""Tests branch scaling.
Makes sure we can correctly re-scale branch lengths into
units of substitutions per site.
Written by Jesse Bloom.
"""
class test_branchScale_ExpCM(unittest.TestCase):
"""Tests `branchScale` of `ExpCM_empirical_phi` model."""
# use approach here to ... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Continue the code snippet: <|code_start|> # create initial ExpCM
g = numpy.random.dirichlet([3] * N_NT)
omega = 0.7
kappa = 2.5
beta = 1.2
self.expcm = (phydmslib.models
.ExpCM_empirical_phi(self.prefs, g=g, omega=omega,
... | for x in range(N_CODON): |
Given the following code snippet before the placeholder: <|code_start|>"""Tests `phydmslib.models.ExpCM_empirical_phi` class.
Written by Jesse Bloom.
"""
class testExpCM_empirical_phi(unittest.TestCase):
"""Tests ``ExpCM`` with empirical phi."""
def test_ExpCM_empirical_phi(self):
"""Initialize `E... | g = numpy.random.dirichlet([3] * N_NT) |
Predict the next line for this snippet: <|code_start|> omega = 0.7
kappa = 2.5
beta = 1.2
self.expcm = (phydmslib.models
.ExpCM_empirical_phi(self.prefs, g=g, omega=omega,
kappa=kappa, beta=beta))
self.assertTrue(num... | nt_freqs[w] += self.expcm.prx[r][x] * CODON_NT_COUNT[w][x] |
Given snippet: <|code_start|>"""Tests `phydmslib.models.ExpCM_empirical_phi` class.
Written by Jesse Bloom.
"""
class testExpCM_empirical_phi(unittest.TestCase):
"""Tests ``ExpCM`` with empirical phi."""
def test_ExpCM_empirical_phi(self):
"""Initialize `ExpCM_empirical_phi`, test, update, test ag... | self.prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Predict the next line after this snippet: <|code_start|>"""Tests `phydmslib.models.ExpCM_empirical_phi` class.
Written by Jesse Bloom.
"""
class testExpCM_empirical_phi(unittest.TestCase):
"""Tests ``ExpCM`` with empirical phi."""
def test_ExpCM_empirical_phi(self):
"""Initialize `ExpCM_empirical_... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Here is a snippet: <|code_start|> [pirAy, random.uniform(0.01, 0.5)],
[omega, random.uniform(0.1, 2.0)]]
self.assertTrue(abs(values[1][1] - values[2][1]) > diffpref,
"choose another random number seed as pirAx and "
... | if CODON_TO_AA[x] == CODON_TO_AA[y]: |
Given the code snippet: <|code_start|> (1 - (pirAx / pirAy)**beta))
dFrxy_dpirAx = ((-omega * beta / pirAx) *
((pirAx / pirAy)**beta *
(sympy.ln((pirAx / pirAy)**beta) - 1) + 1) /
((1 - (pirAx / pirAy)**beta)**2))
dFr... | for x in range(N_CODON): |
Given the following code snippet before the placeholder: <|code_start|> (self
.assertTrue((numpy
.allclose(float(dFrxy_dpirAx_equal
.subs(values.items())
... | rprefs = numpy.random.dirichlet([0.7] * N_AA) |
Given the following code snippet before the placeholder: <|code_start|> ), (-expcm_fitprefs
.tildeFrxy[r][x][y]) /
values[pirAx]))))
... | self.prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Given snippet: <|code_start|> self.assertTrue(numpy.allclose(
float(dFrxy_dpirAy_equal
.subs(values.items())),
expcm_fitprefs.tildeFrxy[r][x][y] /
... | phi=numpy.random.dirichlet([5] * N_NT) |
Here is a snippet: <|code_start|> """Test that `TreeLikelihood` initializes properly."""
tl = (phydmslib.treelikelihood
.TreeLikelihood(self.tree,
self.alignment,
self.model,
underflowfreq=self.underfl... | x = random.randint(0, N_CODON - 1) |
Given snippet: <|code_start|>
class test_BrLenDerivatives_ExpCM(unittest.TestCase):
"""`TreeLikelihood` branch length derivatives for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phydms... | e_pw = numpy.ndarray((3, N_NT), dtype='float') |
Here is a snippet: <|code_start|> os.remove(tempfile)
# simulate alignment with pyvolve
pyvolvetree = pyvolve.read_tree(tree=self.newick)
self.nsites = 50
self.nseqs = self.tree.count_terminals()
e_pw = numpy.ndarray((3, N_NT), dtype='float')
e_pw.fill(0.25)
... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Continue the code snippet: <|code_start|> with open(tempfile, 'w') as f:
f.write(self.newick)
self.tree = Bio.Phylo.read(tempfile, 'newick')
os.remove(tempfile)
# simulate alignment with pyvolve
pyvolvetree = pyvolve.read_tree(tree=self.newick)
self.nsites = 5... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Given snippet: <|code_start|>"""Tests ``--diffprefsbysite`` option to ``phydms`` on simulated data.
Written by Jesse Bloom.
"""
matplotlib.use('pdf')
class test_DiffPrefsBySiteExpCM(unittest.TestCase):
"""Tests ``--diffprefsbysite`` to ``phydms`` for `ExpCM`."""
gammaomega_arg = []
def setUp(self):
... | aas = [INDEX_TO_AA[a] for a in range(N_AA)] |
Next line prediction: <|code_start|>"""Tests ``--diffprefsbysite`` option to ``phydms`` on simulated data.
Written by Jesse Bloom.
"""
matplotlib.use('pdf')
class test_DiffPrefsBySiteExpCM(unittest.TestCase):
"""Tests ``--diffprefsbysite`` to ``phydms`` for `ExpCM`."""
gammaomega_arg = []
def setUp(s... | aas = [INDEX_TO_AA[a] for a in range(N_AA)] |
Using the snippet: <|code_start|>
matplotlib.use('pdf')
class test_DiffPrefsBySiteExpCM(unittest.TestCase):
"""Tests ``--diffprefsbysite`` to ``phydms`` for `ExpCM`."""
gammaomega_arg = []
def setUp(self):
"""Set up test."""
random.seed(1)
numpy.random.seed(1)
self.tree =... | rprefs[AA_TO_INDEX[self.targetaas[r]]] = hipref |
Using the snippet: <|code_start|> J. Kyte & R. F. Doolittle:
"A simple method for displaying the hydropathic character of a
protein." J Mol Biol, 157, 105-132
More positive values indicate higher hydrophobicity,
while more negative values indicate lower hydrophobicity.
The returned ... | aas = sorted(AA_TO_INDEX.keys()) |
Using the snippet: <|code_start|> 'kd'(Kyte-Doolittle hydrophobicity scale, default),
'mw' (molecular weight),
'functionalgroup' (functional groups: small, nucleophilic, hydrophobic,
aromatic, basic, acidic, and amide),
'charge' (charge at neutral pH), and
'singlecolor'. If 'charge' i... | if set(characters) == set(NT_TO_INDEX.keys()): |
Given the following code snippet before the placeholder: <|code_start|> # re-set to old value, make sure return to original values
tl.paramsarray = copy.deepcopy(paramsarray)
self.assertTrue(numpy.allclose(logl, tl.loglik))
for (param, value) in modelparams.items():
self.asser... | partials = numpy.zeros(shape=(self.nsites, N_CODON)) |
Here is a snippet: <|code_start|>
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phydmslib.models.ExpCM
DISTRIBUTIONMODEL = None
def setUp(self):
"""Set up parameters for test."""
r... | e_pw = numpy.ndarray((3, N_NT), dtype="float") |
Given the code snippet: <|code_start|> info = "_temp_info.txt"
rates = "_temp_ratefile.txt"
evolver = pyvolve.Evolver(partitions=partitions, tree=pyvolvetree)
evolver(seqfile=alignment, infofile=info, ratefile=rates)
self.alignment = [(s.description, str(s.seq))
... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Predict the next line after this snippet: <|code_start|> yngkp_m0 = phydmslib.models.YNGKP_M0(e_pw, self.nsites)
partitions = phydmslib.simulate.pyvolvePartitions(yngkp_m0)
alignment = "_temp_simulatedalignment.fasta"
info = "_temp_info.txt"
rates = "_temp_ratefile.txt"
ev... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Here is a snippet: <|code_start|> i = name[-1] # node number
self.brlen[int(i)] = float(brlen)
# simulate alignment with pyvolve
pyvolvetree = pyvolve.read_tree(tree=self.newick)
self.nsites = 60
self.nseqs = self.tree.count_terminals()
e_pw = num... | self.codons[i][r] = CODON_TO_INDEX[codon] |
Here is a snippet: <|code_start|>"""Tests `phydmslib.models.GammaDistributedBetaModel` class.
Written by Jesse Bloom and Sarah Hilton.
"""
class test_GammaBeta_ExpCM(unittest.TestCase):
"""Test gamma distributed beta for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Here is a snippet: <|code_start|>
Written by Jesse Bloom and Sarah Hilton.
"""
class test_GammaBeta_ExpCM(unittest.TestCase):
"""Test gamma distributed beta for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with... | paramvalues = {"eta": numpy.random.dirichlet([5] * (N_NT - 1)), |
Next line prediction: <|code_start|>"""Tests `phydmslib.models.GammaDistributedBetaModel` class.
Written by Jesse Bloom and Sarah Hilton.
"""
class test_GammaBeta_ExpCM(unittest.TestCase):
"""Test gamma distributed beta for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Based on the snippet: <|code_start|>
class test_simulateAlignment_ExpCM(unittest.TestCase):
"""Tests `simulateAlignment` of `simulate.py` module."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phyd... | phi = numpy.random.dirichlet([7] * N_NT) |
Predict the next line after this snippet: <|code_start|>
Makes sure we can correctly simulate an alignment given a model and a tree.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateAlignment_ExpCM(unittest.TestCase):
"""Tests `simulateAlignment` of `simulate.py` module."""
# use approach he... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Next line prediction: <|code_start|>"""Tests alignment simulation.
Makes sure we can correctly simulate an alignment given a model and a tree.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateAlignment_ExpCM(unittest.TestCase):
"""Tests `simulateAlignment` of `simulate.py` module."""
# use ... | rprefs = numpy.random.dirichlet([1] * N_AA) |
Using the snippet: <|code_start|>"""Tests the calculation of spielmanwr, following Spielman and Wilke, 2015.
Written by Jesse Bloom and Sarah Hilton.
"""
class testExpCM_spielmanwr(unittest.TestCase):
"""Test the calculation of `spielmanwr` using the model `ExpCM`."""
# use approach here to run multiple t... | g = numpy.random.dirichlet([5] * N_NT) |
Continue the code snippet: <|code_start|>"""Tests the calculation of spielmanwr, following Spielman and Wilke, 2015.
Written by Jesse Bloom and Sarah Hilton.
"""
class testExpCM_spielmanwr(unittest.TestCase):
"""Test the calculation of `spielmanwr` using the model `ExpCM`."""
# use approach here to run mu... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Next line prediction: <|code_start|>"""Tests the calculation of spielmanwr, following Spielman and Wilke, 2015.
Written by Jesse Bloom and Sarah Hilton.
"""
class testExpCM_spielmanwr(unittest.TestCase):
"""Test the calculation of `spielmanwr` using the model `ExpCM`."""
# use approach here to run multipl... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Predict the next line after this snippet: <|code_start|> # http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phydmslib.models.ExpCM
def testExpCM_spielmanwr(self):
"""Test the `ExpCM` function `_spielman_wr`."""
# create models
ra... | for x in range(N_CODON): |
Predict the next line after this snippet: <|code_start|>
def testExpCM_spielmanwr(self):
"""Test the `ExpCM` function `_spielman_wr`."""
# create models
random.seed(1)
numpy.random.seed(1)
nsites = 10
g = numpy.random.dirichlet([5] * N_NT)
prefs = []
m... | if CODON_SINGLEMUT[x][y] and CODON_NONSYN[x][y]: |
Based on the snippet: <|code_start|>
def testExpCM_spielmanwr(self):
"""Test the `ExpCM` function `_spielman_wr`."""
# create models
random.seed(1)
numpy.random.seed(1)
nsites = 10
g = numpy.random.dirichlet([5] * N_NT)
prefs = []
minpref = 0.01
... | if CODON_SINGLEMUT[x][y] and CODON_NONSYN[x][y]: |
Based on the snippet: <|code_start|>"""
class test_simulateRandomSeed_ExpCM(unittest.TestCase):
"""Tests `simulate.simulateAlignment` module with different seeds."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-argumen... | phi = numpy.random.dirichlet([7] * N_NT) |
Continue the code snippet: <|code_start|>"""Tests random number seeding in aligment simulation.
Makes sure the random numbering seeding gives reproducible results.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateRandomSeed_ExpCM(unittest.TestCase):
"""Tests `simulate.simulateAlignment` module w... | rprefs = numpy.random.dirichlet([1] * N_AA) |
Based on the snippet: <|code_start|>"""Tests random number seeding in aligment simulation.
Makes sure the random numbering seeding gives reproducible results.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateRandomSeed_ExpCM(unittest.TestCase):
"""Tests `simulate.simulateAlignment` module with d... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Predict the next line after this snippet: <|code_start|> "--brlen", "scale"])
omegabysitefile = simulateprefix + "_omegabysite.txt"
omegas = pandas.read_csv(omegabysitefile, sep="\t", comment="#")
divpressureomegas = omegas[omegas["site"].isin(divpressuresites)]
... | e_pw = numpy.full((3, N_NT), 1.0 / N_NT, dtype="float") |
Here is a snippet: <|code_start|>"""Tests `phydmslib.models.YNGKP_M0` class.
Written by Jesse Bloom.
Edited by Sarah Hilton
Uses `sympy` to make sure attributes and derivatives of attributes
are correct for `YNGKP_M0` implemented in `phydmslib.models`.
"""
class testYNGKP_M0(unittest.TestCase):
"""Test YNGKP ... | self.e_pa = numpy.random.uniform(0.12, 1.0, size=(3, N_NT)) |
Continue the code snippet: <|code_start|> omega = 0.4
kappa = 2.5
self.YNGKP_M0 = phydmslib.models.YNGKP_M0(
self.e_pa, self.nsites, omega=omega, kappa=kappa)
self.assertTrue(numpy.allclose(omega, self.YNGKP_M0.omega))
self.assertTrue(numpy.allclose(kappa, self.YNGKP_M... | diag = numpy.eye(N_CODON, dtype="bool") |
Next line prediction: <|code_start|> divsites = []
assert all((1 <= r <= model.nsites for r in divsites))
partitions = []
for r in range(model.nsites):
matrix = numpy.zeros((len(codons), len(codons)), dtype='float')
for (xi, x) in enumerate(codons):
for (yi, y) in enumer... | qxy *= model.phi[NT_TO_INDEX[ynt]] |
Given the code snippet: <|code_start|>
assert all((1 <= r <= model.nsites for r in divsites))
partitions = []
for r in range(model.nsites):
matrix = numpy.zeros((len(codons), len(codons)), dtype='float')
for (xi, x) in enumerate(codons):
for (yi, y) in enumerate(codons):
... | pix = model.pi[r][AA_TO_INDEX[xaa]]**model.beta |
Given snippet: <|code_start|>
partitions = []
for r in range(model.nsites):
matrix = numpy.zeros((len(codons), len(codons)), dtype='float')
for (xi, x) in enumerate(codons):
for (yi, y) in enumerate(codons):
ntdiffs = [(x[j], y[j]) for j in range(3) if x[j] != y[j]]
... | if abs(pix - piy) > ALMOST_ZERO: |
Given the following code snippet before the placeholder: <|code_start|>"""Tests alignment simulation.
Makes sure we can correctly simulate an alignment given an `ExpCM` with
divpressure and a tree.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateAlignment_ExpCM_divselection(unittest.TestCase):
... | rprefs = numpy.random.dirichlet([1] * N_AA) |
Predict the next line after this snippet: <|code_start|>Makes sure we can correctly simulate an alignment given an `ExpCM` with
divpressure and a tree.
Written by Sarah Hilton and Jesse Bloom.
"""
class test_simulateAlignment_ExpCM_divselection(unittest.TestCase):
"""Tests `simulateAlignment` of `simulate.py` m... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Given the following code snippet before the placeholder: <|code_start|> """Tests `simulateAlignment` of `simulate.py` module."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phydmslib.models.ExpCM_emp... | g = numpy.random.dirichlet([7] * N_NT) |
Continue the code snippet: <|code_start|>
def tfunc(x):
"""Negative log likelihood when `x` is branch lengths."""
self.t = x
return -self.loglik
def tdfunc(x):
"""Negative gradient loglik with respect to branch lengths."""
self.t = x
... | 'bounds': [(ALMOST_ZERO, None)] * len(self.t), |
Continue the code snippet: <|code_start|> else:
self._dLshape[param] = (len(paramvalue),
self.nsites, N_CODON)
else:
raise ValueError("Cannot handle param: {0}, {1}".format(
... | elif codon in CODON_TO_INDEX: |
Given the code snippet: <|code_start|> assert all({len(seq) == 3 * self.nsites for (head, seq) in alignment})
assert set({head for (head, seq) in alignment}
) == {clade.name for clade in tree.get_terminals()}
self.alignment = copy.deepcopy(alignment)
self.nseqs = len(al... | self._Lshape = (self.model.ncats, self.nsites, N_CODON) |
Next line prediction: <|code_start|> """`TreeLikelihood` branch length optimization for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = phydmslib.models.ExpCM
DISTRIBUTIONMODEL = None
... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Based on the snippet: <|code_start|>
class test_BrLenOptimize_ExpCM(unittest.TestCase):
"""`TreeLikelihood` branch length optimization for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questions/17260469/instantiate-python-unittest-testcase-with-arguments
MODEL = ph... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Predict the next line for this snippet: <|code_start|>"""Tests `phydmslib.models.GammaDistributedOmegaModel` class.
Written by Jesse Bloom.
"""
class test_GammaDistributedOmega_ExpCM(unittest.TestCase):
"""Test gamma distributed omega for `ExpCM`."""
# use approach here to run multiple tests:
# http:/... | rprefs = numpy.random.dirichlet([0.5] * N_AA) |
Given snippet: <|code_start|>"""Tests `phydmslib.models.GammaDistributedOmegaModel` class.
Written by Jesse Bloom.
"""
class test_GammaDistributedOmega_ExpCM(unittest.TestCase):
"""Test gamma distributed omega for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.com/questi... | prefs.append(dict(zip(sorted(AA_TO_INDEX.keys()), rprefs))) |
Given the code snippet: <|code_start|>"""Tests `phydmslib.models.GammaDistributedOmegaModel` class.
Written by Jesse Bloom.
"""
class test_GammaDistributedOmega_ExpCM(unittest.TestCase):
"""Test gamma distributed omega for `ExpCM`."""
# use approach here to run multiple tests:
# http://stackoverflow.c... | paramvalues = {"eta": numpy.random.dirichlet([5] * (N_NT - 1)), |
Given the code snippet: <|code_start|> `kappa`, `omega`, `beta`, `mu`, `phi`
Model params described in main class doc string.
`freeparams` (list of strings)
Specifies free parameters.
"""
self._nsites = len(prefs)
assert self.nsites > 0, "No... | self.pi_codon = numpy.full((self.nsites, N_CODON), -1, dtype='float') |
Continue the code snippet: <|code_start|> def _update_pi_vars(self):
"""Update variables that depend on `pi`.
These are `pi_codon`, `ln_pi_codon`, `piAx_piAy`, `piAx_piAy_beta`,
`ln_piAx_piAy_beta`.
Update using current `pi` and `beta`.
"""
with numpy.errstate(divide... | where=numpy.logical_and(CODON_NONSYN, numpy.fabs(1 - self.piAx_piAy_beta) # noqa: E501 |
Given the following code snippet before the placeholder: <|code_start|> dM_param[j] = (broadcastMatrixVectorMultiply(self.A,
broadcastGetCols(broadcastMatrixMultiply(self.B[param][j] * V, self.Ainv), tips))) # noqa: E501
if gaps is not None:... | self.Qxy[CODON_TRANSITION] *= self.kappa |
Given the code snippet: <|code_start|> gene-wide `omega`.
Returns:
`wr` (list)
list of `omega_r` values of length `nsites`
Following
`Spielman and Wilke,
MBE, 32:1097-1108 <https://doi.org/10.1093/molbev/msv003>`_,
we c... | j = numpy.where((CODON_SINGLEMUT[i] * CODON_NONSYN[i]) == 1)[0] |
Given the code snippet: <|code_start|> `dprx` (dict)
Keyed by strings in `freeparams`, each value is `numpy.ndarray`
of floats giving derivative of `prx` with respect to that param,
or 0 if if `prx` does not depend on parameter. The shape of each
array is `(nsites,... | 'pi': (ALMOST_ZERO, 1), |
Given the code snippet: <|code_start|> """Update `B`."""
for param in self.freeparams:
if param == 'mu':
continue
paramval = getattr(self, param)
if isinstance(paramval, float):
self.B[param] = (broadcastMatrixMultiply(self.Ainv,
... | boolterm += ((i <= CODON_NT_INDEX[j]).astype('float') |
Here is a snippet: <|code_start|> return bs
@property
def nsites(self):
"""See docs for `Model` abstract base class."""
return self._nsites
@property
def freeparams(self):
"""See docs for `Model` abstract base class."""
return self._freeparams
@property
... | codonFrequency = STOP_CODON_TO_NT_INDICES[x] * phi_reshape |
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