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troeger/opensubmit | web/opensubmit/models/submission.py | Submission.can_reupload | def can_reupload(self, user=None):
"""Determines whether a submission can be re-uploaded.
Returns a boolean value.
Requires: can_modify.
Re-uploads are allowed only when test executions have failed."""
# Re-uploads are allowed only when test executions have failed.
if ... | python | def can_reupload(self, user=None):
"""Determines whether a submission can be re-uploaded.
Returns a boolean value.
Requires: can_modify.
Re-uploads are allowed only when test executions have failed."""
# Re-uploads are allowed only when test executions have failed.
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troeger/opensubmit | web/opensubmit/models/submission.py | Submission.get_initial_state | def get_initial_state(self):
'''
Return first state for this submission after upload,
which depends on the kind of assignment.
'''
if not self.assignment.attachment_is_tested():
return Submission.SUBMITTED
else:
if self.assignment.attachmen... | python | def get_initial_state(self):
'''
Return first state for this submission after upload,
which depends on the kind of assignment.
'''
if not self.assignment.attachment_is_tested():
return Submission.SUBMITTED
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troeger/opensubmit | web/opensubmit/models/submission.py | Submission.info_file | def info_file(self, delete=True):
'''
Prepares an open temporary file with information about the submission.
Closing it will delete it, which must be considered by the caller.
This file is not readable, since the tempfile library wants either readable or writable files.
... | python | def info_file(self, delete=True):
'''
Prepares an open temporary file with information about the submission.
Closing it will delete it, which must be considered by the caller.
This file is not readable, since the tempfile library wants either readable or writable files.
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troeger/opensubmit | web/opensubmit/models/submission.py | Submission.copy_file_upload | def copy_file_upload(self, targetdir):
'''
Copies the currently valid file upload into the given directory.
If possible, the content is un-archived in the target directory.
'''
assert(self.file_upload)
# unpack student data to temporary directory
# os.chro... | python | def copy_file_upload(self, targetdir):
'''
Copies the currently valid file upload into the given directory.
If possible, the content is un-archived in the target directory.
'''
assert(self.file_upload)
# unpack student data to temporary directory
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idlesign/django-sitemessage | sitemessage/messengers/telegram.py | TelegramMessenger._send_command | def _send_command(self, method_name, data=None):
"""Sends a command to API.
:param str method_name:
:param dict data:
:return:
"""
try:
response = self.lib.post(self._tpl_url % {'token': self.auth_token, 'method': method_name}, data=data)
json = r... | python | def _send_command(self, method_name, data=None):
"""Sends a command to API.
:param str method_name:
:param dict data:
:return:
"""
try:
response = self.lib.post(self._tpl_url % {'token': self.auth_token, 'method': method_name}, data=data)
json = r... | [
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troeger/opensubmit | web/opensubmit/admin/submissionfile.py | SubmissionFileAdmin.get_queryset | def get_queryset(self, request):
''' Restrict the listed submission files for the current user.'''
qs = super(SubmissionFileAdmin, self).get_queryset(request)
if request.user.is_superuser:
return qs
else:
return qs.filter(Q(submissions__assignment__course__tutors_... | python | def get_queryset(self, request):
''' Restrict the listed submission files for the current user.'''
qs = super(SubmissionFileAdmin, self).get_queryset(request)
if request.user.is_superuser:
return qs
else:
return qs.filter(Q(submissions__assignment__course__tutors_... | [
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idlesign/django-sitemessage | sitemessage/messages/__init__.py | register_builtin_message_types | def register_builtin_message_types():
"""Registers the built-in message types."""
from .plain import PlainTextMessage
from .email import EmailTextMessage, EmailHtmlMessage
register_message_types(PlainTextMessage, EmailTextMessage, EmailHtmlMessage) | python | def register_builtin_message_types():
"""Registers the built-in message types."""
from .plain import PlainTextMessage
from .email import EmailTextMessage, EmailHtmlMessage
register_message_types(PlainTextMessage, EmailTextMessage, EmailHtmlMessage) | [
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troeger/opensubmit | web/opensubmit/admin/assignment.py | view_links | def view_links(obj):
''' Link to performance data and duplicate overview.'''
result=format_html('')
result+=format_html('<a href="%s" style="white-space: nowrap">Show duplicates</a><br/>'%reverse('duplicates', args=(obj.pk,)))
result+=format_html('<a href="%s" style="white-space: nowrap">Show submission... | python | def view_links(obj):
''' Link to performance data and duplicate overview.'''
result=format_html('')
result+=format_html('<a href="%s" style="white-space: nowrap">Show duplicates</a><br/>'%reverse('duplicates', args=(obj.pk,)))
result+=format_html('<a href="%s" style="white-space: nowrap">Show submission... | [
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troeger/opensubmit | web/opensubmit/admin/assignment.py | AssignmentAdminForm.clean | def clean(self):
'''
Check if such an assignment configuration makes sense, and reject it otherwise.
This mainly relates to interdependencies between the different fields, since
single field constraints are already clatified by the Django model configuration.
'''
... | python | def clean(self):
'''
Check if such an assignment configuration makes sense, and reject it otherwise.
This mainly relates to interdependencies between the different fields, since
single field constraints are already clatified by the Django model configuration.
'''
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troeger/opensubmit | web/opensubmit/admin/assignment.py | AssignmentAdmin.get_queryset | def get_queryset(self, request):
''' Restrict the listed assignments for the current user.'''
qs = super(AssignmentAdmin, self).get_queryset(request)
if not request.user.is_superuser:
qs = qs.filter(course__active=True).filter(Q(course__tutors__pk=request.user.pk) | Q(course__owner=r... | python | def get_queryset(self, request):
''' Restrict the listed assignments for the current user.'''
qs = super(AssignmentAdmin, self).get_queryset(request)
if not request.user.is_superuser:
qs = qs.filter(course__active=True).filter(Q(course__tutors__pk=request.user.pk) | Q(course__owner=r... | [
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troeger/opensubmit | web/opensubmit/social/env.py | ServerEnvAuth.get_user_details | def get_user_details(self, response):
""" Complete with additional information from environment, as available. """
result = {
'username': response[self.ENV_USERNAME],
'email': response.get(self.ENV_EMAIL, None),
'first_name': response.get(self.ENV_FIRST_NAME, None),
... | python | def get_user_details(self, response):
""" Complete with additional information from environment, as available. """
result = {
'username': response[self.ENV_USERNAME],
'email': response.get(self.ENV_EMAIL, None),
'first_name': response.get(self.ENV_FIRST_NAME, None),
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.file_link | def file_link(self, instance):
'''
Renders the link to the student upload file.
'''
sfile = instance.file_upload
if not sfile:
return mark_safe('No file submitted by student.')
else:
return mark_safe('<a href="%s">%s</a><br/>(<a href="%s" targe... | python | def file_link(self, instance):
'''
Renders the link to the student upload file.
'''
sfile = instance.file_upload
if not sfile:
return mark_safe('No file submitted by student.')
else:
return mark_safe('<a href="%s">%s</a><br/>(<a href="%s" targe... | [
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.get_queryset | def get_queryset(self, request):
''' Restrict the listed submission for the current user.'''
qs = super(SubmissionAdmin, self).get_queryset(request)
if request.user.is_superuser:
return qs
else:
return qs.filter(Q(assignment__course__tutors__pk=request.user.pk) | ... | python | def get_queryset(self, request):
''' Restrict the listed submission for the current user.'''
qs = super(SubmissionAdmin, self).get_queryset(request)
if request.user.is_superuser:
return qs
else:
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.formfield_for_dbfield | def formfield_for_dbfield(self, db_field, **kwargs):
''' Offer grading choices from the assignment definition as potential form
field values for 'grading'.
When no object is given in the form, the this is a new manual submission
'''
if db_field.name == "grading":
... | python | def formfield_for_dbfield(self, db_field, **kwargs):
''' Offer grading choices from the assignment definition as potential form
field values for 'grading'.
When no object is given in the form, the this is a new manual submission
'''
if db_field.name == "grading":
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.save_model | def save_model(self, request, obj, form, change):
''' Our custom addition to the view
adds an easy radio button choice for the new state. This is meant to be for tutors.
We need to peel this choice from the form data and set the state accordingly.
The radio buttons have no de... | python | def save_model(self, request, obj, form, change):
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adds an easy radio button choice for the new state. This is meant to be for tutors.
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.setGradingNotFinishedStateAction | def setGradingNotFinishedStateAction(self, request, queryset):
'''
Set all marked submissions to "grading not finished".
This is intended to support grading corrections on a larger scale.
'''
for subm in queryset:
subm.state = Submission.GRADING_IN_PROGRESS
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'''
Set all marked submissions to "grading not finished".
This is intended to support grading corrections on a larger scale.
'''
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subm.state = Submission.GRADING_IN_PROGRESS
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This is intended to support grading corrections on a larger scale.
'''
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'''
Set all marked submissions to "grading finished".
This is intended to support grading corrections on a larger scale.
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.closeAndNotifyAction | def closeAndNotifyAction(self, request, queryset):
''' Close all submissions were the tutor sayed that the grading is finished,
and inform the student. CLosing only graded submissions is a safeguard,
since backend users tend to checkbox-mark all submissions without thinking.
'''
... | python | def closeAndNotifyAction(self, request, queryset):
''' Close all submissions were the tutor sayed that the grading is finished,
and inform the student. CLosing only graded submissions is a safeguard,
since backend users tend to checkbox-mark all submissions without thinking.
'''
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troeger/opensubmit | web/opensubmit/admin/submission.py | SubmissionAdmin.downloadArchiveAction | def downloadArchiveAction(self, request, queryset):
'''
Download selected submissions as archive, for targeted correction.
'''
output = io.BytesIO()
z = zipfile.ZipFile(output, 'w')
for sub in queryset:
sub.add_to_zipfile(z)
z.close()
# go ba... | python | def downloadArchiveAction(self, request, queryset):
'''
Download selected submissions as archive, for targeted correction.
'''
output = io.BytesIO()
z = zipfile.ZipFile(output, 'w')
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.directory_name_with_course | def directory_name_with_course(self):
''' The assignment name in a format that is suitable for a directory name. '''
coursename = self.course.directory_name()
assignmentname = self.title.replace(" ", "_").replace("\\", "_").replace(",","").lower()
return coursename + os.sep + assignment... | python | def directory_name_with_course(self):
''' The assignment name in a format that is suitable for a directory name. '''
coursename = self.course.directory_name()
assignmentname = self.title.replace(" ", "_").replace("\\", "_").replace(",","").lower()
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.grading_url | def grading_url(self):
'''
Determines the teacher backend link to the filtered list of gradable submissions for this assignment.
'''
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'''
Determines the teacher backend link to the filtered list of gradable submissions for this assignment.
'''
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.has_perf_results | def has_perf_results(self):
'''
Figure out if any submission for this assignment has performance data being available.
'''
num_results = SubmissionTestResult.objects.filter(perf_data__isnull=False).filter(submission_file__submissions__assignment=self).count()
return num_resul... | python | def has_perf_results(self):
'''
Figure out if any submission for this assignment has performance data being available.
'''
num_results = SubmissionTestResult.objects.filter(perf_data__isnull=False).filter(submission_file__submissions__assignment=self).count()
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.url | def url(self, request):
'''
Return absolute URL for assignment description.
'''
if self.pk:
if self.has_description():
return request.build_absolute_uri(reverse('assignment_description_file', args=[self.pk]))
else:
return self.d... | python | def url(self, request):
'''
Return absolute URL for assignment description.
'''
if self.pk:
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.can_create_submission | def can_create_submission(self, user=None):
'''
Central access control for submitting things related to assignments.
'''
if user:
# Super users, course owners and tutors should be able to test their validations
# before the submission is officially possible.
... | python | def can_create_submission(self, user=None):
'''
Central access control for submitting things related to assignments.
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troeger/opensubmit | web/opensubmit/models/assignment.py | Assignment.duplicate_files | def duplicate_files(self):
'''
Search for duplicates of submission file uploads for this assignment.
This includes the search in other course, whether inactive or not.
Returns a list of lists, where each latter is a set of duplicate submissions
with at least on of them for this a... | python | def duplicate_files(self):
'''
Search for duplicates of submission file uploads for this assignment.
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troeger/opensubmit | executor/opensubmitexec/cmdline.py | download_and_run | def download_and_run(config):
'''
Main operation of the executor.
Returns True when a job was downloaded and executed.
Returns False when no job could be downloaded.
'''
job = fetch_job(config)
if job:
job._run_validate()
return True
else:
return False | python | def download_and_run(config):
'''
Main operation of the executor.
Returns True when a job was downloaded and executed.
Returns False when no job could be downloaded.
'''
job = fetch_job(config)
if job:
job._run_validate()
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troeger/opensubmit | executor/opensubmitexec/cmdline.py | copy_and_run | def copy_and_run(config, src_dir):
'''
Local-only operation of the executor.
Intended for validation script developers,
and the test suite.
Please not that this function only works correctly
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- validator.py
- validator.zip
Ret... | python | def copy_and_run(config, src_dir):
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Local-only operation of the executor.
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troeger/opensubmit | executor/opensubmitexec/cmdline.py | console_script | def console_script():
'''
The main entry point for the production
administration script 'opensubmit-exec',
installed by setuptools.
'''
if len(sys.argv) == 1:
print("opensubmit-exec [configcreate <server_url>|configtest|run|test <dir>|unlock|help] [-c config_file]")
r... | python | def console_script():
'''
The main entry point for the production
administration script 'opensubmit-exec',
installed by setuptools.
'''
if len(sys.argv) == 1:
print("opensubmit-exec [configcreate <server_url>|configtest|run|test <dir>|unlock|help] [-c config_file]")
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timothydmorton/VESPA | vespa/hashutils.py | hashdict | def hashdict(d):
"""Hash a dictionary
"""
k = 0
for key,val in d.items():
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return k | python | def hashdict(d):
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k = 0
for key,val in d.items():
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timothydmorton/VESPA | vespa/orbits/populations.py | TripleOrbitPopulation.from_df | def from_df(cls, df_long, df_short):
"""
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``DataFrame`` objects must be of appropriate form to pass
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:fun... | python | def from_df(cls, df_long, df_short):
"""
Builds TripleOrbitPopulation from DataFrame
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timothydmorton/VESPA | vespa/orbits/populations.py | TripleOrbitPopulation.load_hdf | def load_hdf(cls, filename, path=''):
"""
Load TripleOrbitPopulation from saved .h5 file.
:param filename:
HDF file name.
:param path:
Path within HDF file where data is stored.
"""
df_long = pd.read_hdf(filename,'{}/long/df'.format(path))
... | python | def load_hdf(cls, filename, path=''):
"""
Load TripleOrbitPopulation from saved .h5 file.
:param filename:
HDF file name.
:param path:
Path within HDF file where data is stored.
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timothydmorton/VESPA | vespa/orbits/populations.py | OrbitPopulation.RV_timeseries | def RV_timeseries(self,ts,recalc=False):
"""
Radial Velocity time series for star 1 at given times ts.
:param ts:
Times. If not ``Quantity``, assumed to be in days.
:type ts:
array-like or ``Quantity``
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"""
Radial Velocity time series for star 1 at given times ts.
:param ts:
Times. If not ``Quantity``, assumed to be in days.
:type ts:
array-like or ``Quantity``
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timothydmorton/VESPA | vespa/orbits/populations.py | OrbitPopulation.from_df | def from_df(cls, df):
"""Creates an OrbitPopulation from a DataFrame.
:param df:
:class:`pandas.DataFrame` object. Must contain the following
columns: ``['M1','M2','P','ecc','mean_anomaly','obsx','obsy','obsz']``,
i.e., as what is accessed via :attr:`OrbitPopulation... | python | def from_df(cls, df):
"""Creates an OrbitPopulation from a DataFrame.
:param df:
:class:`pandas.DataFrame` object. Must contain the following
columns: ``['M1','M2','P','ecc','mean_anomaly','obsx','obsy','obsz']``,
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timothydmorton/VESPA | vespa/orbits/populations.py | OrbitPopulation.load_hdf | def load_hdf(cls, filename, path=''):
"""Loads OrbitPopulation from HDF file.
:param filename:
HDF file
:param path:
Path within HDF file store where :class:`OrbitPopulation` is saved.
"""
df = pd.read_hdf(filename,'{}/df'.format(path))
return cl... | python | def load_hdf(cls, filename, path=''):
"""Loads OrbitPopulation from HDF file.
:param filename:
HDF file
:param path:
Path within HDF file store where :class:`OrbitPopulation` is saved.
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timothydmorton/VESPA | vespa/stars/utils.py | draw_pers_eccs | def draw_pers_eccs(n,**kwargs):
"""
Draw random periods and eccentricities according to empirical survey data.
"""
pers = draw_raghavan_periods(n)
eccs = draw_eccs(n,pers,**kwargs)
return pers,eccs | python | def draw_pers_eccs(n,**kwargs):
"""
Draw random periods and eccentricities according to empirical survey data.
"""
pers = draw_raghavan_periods(n)
eccs = draw_eccs(n,pers,**kwargs)
return pers,eccs | [
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timothydmorton/VESPA | vespa/stars/utils.py | draw_eccs | def draw_eccs(n,per=10,binsize=0.1,fuzz=0.05,maxecc=0.97):
"""draws eccentricities appropriate to given periods, generated according to empirical data from Multiple Star Catalog
"""
if np.size(per) == 1 or np.std(np.atleast_1d(per))==0:
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per = per[0]
if per==0:
... | python | def draw_eccs(n,per=10,binsize=0.1,fuzz=0.05,maxecc=0.97):
"""draws eccentricities appropriate to given periods, generated according to empirical data from Multiple Star Catalog
"""
if np.size(per) == 1 or np.std(np.atleast_1d(per))==0:
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timothydmorton/VESPA | vespa/stars/utils.py | withinroche | def withinroche(semimajors,M1,R1,M2,R2):
"""
Returns boolean array that is True where two stars are within Roche lobe
"""
q = M1/M2
return ((R1+R2)*RSUN) > (rochelobe(q)*semimajors*AU) | python | def withinroche(semimajors,M1,R1,M2,R2):
"""
Returns boolean array that is True where two stars are within Roche lobe
"""
q = M1/M2
return ((R1+R2)*RSUN) > (rochelobe(q)*semimajors*AU) | [
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timothydmorton/VESPA | vespa/stars/utils.py | semimajor | def semimajor(P,mstar=1):
"""Returns semimajor axis in AU given P in days, mstar in solar masses.
"""
return ((P*DAY/2/np.pi)**2*G*mstar*MSUN)**(1./3)/AU | python | def semimajor(P,mstar=1):
"""Returns semimajor axis in AU given P in days, mstar in solar masses.
"""
return ((P*DAY/2/np.pi)**2*G*mstar*MSUN)**(1./3)/AU | [
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timothydmorton/VESPA | vespa/stars/utils.py | fluxfrac | def fluxfrac(*mags):
"""Returns fraction of total flux in first argument, assuming all are magnitudes.
"""
Ftot = 0
for mag in mags:
Ftot += 10**(-0.4*mag)
F1 = 10**(-0.4*mags[0])
return F1/Ftot | python | def fluxfrac(*mags):
"""Returns fraction of total flux in first argument, assuming all are magnitudes.
"""
Ftot = 0
for mag in mags:
Ftot += 10**(-0.4*mag)
F1 = 10**(-0.4*mags[0])
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timothydmorton/VESPA | vespa/stars/utils.py | dfromdm | def dfromdm(dm):
"""Returns distance given distance modulus.
"""
if np.size(dm)>1:
dm = np.atleast_1d(dm)
return 10**(1+dm/5) | python | def dfromdm(dm):
"""Returns distance given distance modulus.
"""
if np.size(dm)>1:
dm = np.atleast_1d(dm)
return 10**(1+dm/5) | [
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timothydmorton/VESPA | vespa/stars/utils.py | distancemodulus | def distancemodulus(d):
"""Returns distance modulus given d in parsec.
"""
if type(d)==Quantity:
x = d.to('pc').value
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x = d #assumed to be pc
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"""Returns distance modulus given d in parsec.
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if type(d)==Quantity:
x = d.to('pc').value
else:
x = d #assumed to be pc
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dellis23/ansible-toolkit | ansible_toolkit/utils.py | get_files | def get_files(path):
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"""
Returns a recursive list of all non-hidden files in and below the current
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"""
return_files = []
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# Skip hidden files
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timothydmorton/VESPA | vespa/transitsignal.py | TransitSignal.save_pkl | def save_pkl(self, filename):
"""
Pickles TransitSignal.
"""
with open(filename, 'wb') as fout:
pickle.dump(self, fout) | python | def save_pkl(self, filename):
"""
Pickles TransitSignal.
"""
with open(filename, 'wb') as fout:
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timothydmorton/VESPA | vespa/transitsignal.py | TransitSignal.plot | def plot(self, fig=None, plot_trap=False, name=False, trap_color='g',
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Makes a simple plot of signal
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Argument for :func:`plotutils.setfig`.
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"""
Makes a simple plot of signal
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Argument for :func:`plotutils.setfig`.
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] | 0446b54d48009f3655cfd1a3957ceea21d3adcaa | https://github.com/timothydmorton/VESPA/blob/0446b54d48009f3655cfd1a3957ceea21d3adcaa/vespa/transitsignal.py#L166-L224 | train | 64,243 |
timothydmorton/VESPA | vespa/statutils.py | kdeconf | def kdeconf(kde,conf=0.683,xmin=None,xmax=None,npts=500,
shortest=True,conftol=0.001,return_max=False):
"""
Returns desired confidence interval for provided KDE object
"""
if xmin is None:
xmin = kde.dataset.min()
if xmax is None:
xmax = kde.dataset.max()
x = np.linsp... | python | def kdeconf(kde,conf=0.683,xmin=None,xmax=None,npts=500,
shortest=True,conftol=0.001,return_max=False):
"""
Returns desired confidence interval for provided KDE object
"""
if xmin is None:
xmin = kde.dataset.min()
if xmax is None:
xmax = kde.dataset.max()
x = np.linsp... | [
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timothydmorton/VESPA | vespa/statutils.py | qstd | def qstd(x,quant=0.05,top=False,bottom=False):
"""returns std, ignoring outer 'quant' pctiles
"""
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n = np.size(x)
lo = s[int(n*quant)]
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if top:
w = np.where(x>=lo)
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w = np.where(x<=hi)
else:
w = np.where((x>=lo... | python | def qstd(x,quant=0.05,top=False,bottom=False):
"""returns std, ignoring outer 'quant' pctiles
"""
s = np.sort(x)
n = np.size(x)
lo = s[int(n*quant)]
hi = s[int(n*(1-quant))]
if top:
w = np.where(x>=lo)
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w = np.where(x<=hi)
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w = np.where((x>=lo... | [
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timothydmorton/VESPA | vespa/plotutils.py | plot2dhist | def plot2dhist(xdata,ydata,cmap='binary',interpolation='nearest',
fig=None,logscale=True,xbins=None,ybins=None,
nbins=50,pts_only=False,**kwargs):
"""Plots a 2d density histogram of provided data
:param xdata,ydata: (array-like)
Data to plot.
:param cmap: (optional)
... | python | def plot2dhist(xdata,ydata,cmap='binary',interpolation='nearest',
fig=None,logscale=True,xbins=None,ybins=None,
nbins=50,pts_only=False,**kwargs):
"""Plots a 2d density histogram of provided data
:param xdata,ydata: (array-like)
Data to plot.
:param cmap: (optional)
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timothydmorton/VESPA | vespa/transit_basic.py | ldcoeffs | def ldcoeffs(teff,logg=4.5,feh=0):
"""
Returns limb-darkening coefficients in Kepler band.
"""
teffs = np.atleast_1d(teff)
loggs = np.atleast_1d(logg)
Tmin,Tmax = (LDPOINTS[:,0].min(),LDPOINTS[:,0].max())
gmin,gmax = (LDPOINTS[:,1].min(),LDPOINTS[:,1].max())
teffs[(teffs < Tmin)] = Tmi... | python | def ldcoeffs(teff,logg=4.5,feh=0):
"""
Returns limb-darkening coefficients in Kepler band.
"""
teffs = np.atleast_1d(teff)
loggs = np.atleast_1d(logg)
Tmin,Tmax = (LDPOINTS[:,0].min(),LDPOINTS[:,0].max())
gmin,gmax = (LDPOINTS[:,1].min(),LDPOINTS[:,1].max())
teffs[(teffs < Tmin)] = Tmi... | [
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timothydmorton/VESPA | vespa/transit_basic.py | impact_parameter | def impact_parameter(a, R, inc, ecc=0, w=0, return_occ=False):
"""a in AU, R in Rsun, inc & w in radians
"""
b_tra = a*AU*np.cos(inc)/(R*RSUN) * (1-ecc**2)/(1 + ecc*np.sin(w))
if return_occ:
b_tra = a*AU*np.cos(inc)/(R*RSUN) * (1-ecc**2)/(1 - ecc*np.sin(w))
return b_tra, b_occ
else:... | python | def impact_parameter(a, R, inc, ecc=0, w=0, return_occ=False):
"""a in AU, R in Rsun, inc & w in radians
"""
b_tra = a*AU*np.cos(inc)/(R*RSUN) * (1-ecc**2)/(1 + ecc*np.sin(w))
if return_occ:
b_tra = a*AU*np.cos(inc)/(R*RSUN) * (1-ecc**2)/(1 - ecc*np.sin(w))
return b_tra, b_occ
else:... | [
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timothydmorton/VESPA | vespa/transit_basic.py | minimum_inclination | def minimum_inclination(P,M1,M2,R1,R2):
"""
Returns the minimum inclination at which two bodies from two given sets eclipse
Only counts systems not within each other's Roche radius
:param P:
Orbital periods.
:param M1,M2,R1,R2:
Masses and radii of primary and secondary stars. ... | python | def minimum_inclination(P,M1,M2,R1,R2):
"""
Returns the minimum inclination at which two bodies from two given sets eclipse
Only counts systems not within each other's Roche radius
:param P:
Orbital periods.
:param M1,M2,R1,R2:
Masses and radii of primary and secondary stars. ... | [
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timothydmorton/VESPA | vespa/transit_basic.py | eclipse_pars | def eclipse_pars(P,M1,M2,R1,R2,ecc=0,inc=90,w=0,sec=False):
"""retuns p,b,aR from P,M1,M2,R1,R2,ecc,inc,w"""
a = semimajor(P,M1+M2)
if sec:
b = a*AU*np.cos(inc*np.pi/180)/(R1*RSUN) * (1-ecc**2)/(1 - ecc*np.sin(w*np.pi/180))
#aR = a*AU/(R2*RSUN) #I feel like this was to correct a bug, but thi... | python | def eclipse_pars(P,M1,M2,R1,R2,ecc=0,inc=90,w=0,sec=False):
"""retuns p,b,aR from P,M1,M2,R1,R2,ecc,inc,w"""
a = semimajor(P,M1+M2)
if sec:
b = a*AU*np.cos(inc*np.pi/180)/(R1*RSUN) * (1-ecc**2)/(1 - ecc*np.sin(w*np.pi/180))
#aR = a*AU/(R2*RSUN) #I feel like this was to correct a bug, but thi... | [
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timothydmorton/VESPA | vespa/transit_basic.py | fit_traptransit | def fit_traptransit(ts,fs,p0):
"""
Fits trapezoid model to provided ts,fs
"""
pfit,success = leastsq(traptransit_resid,p0,args=(ts,fs))
if success not in [1,2,3,4]:
raise NoFitError
#logging.debug('success = {}'.format(success))
return pfit | python | def fit_traptransit(ts,fs,p0):
"""
Fits trapezoid model to provided ts,fs
"""
pfit,success = leastsq(traptransit_resid,p0,args=(ts,fs))
if success not in [1,2,3,4]:
raise NoFitError
#logging.debug('success = {}'.format(success))
return pfit | [
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dellis23/ansible-toolkit | ansible_toolkit/vault.py | backup | def backup(path, password_file=None):
"""
Replaces the contents of a file with its decrypted counterpart, storing the
original encrypted version and a hash of the file contents for later
retrieval.
"""
vault = VaultLib(get_vault_password(password_file))
with open(path, 'r') as f:
enc... | python | def backup(path, password_file=None):
"""
Replaces the contents of a file with its decrypted counterpart, storing the
original encrypted version and a hash of the file contents for later
retrieval.
"""
vault = VaultLib(get_vault_password(password_file))
with open(path, 'r') as f:
enc... | [
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dellis23/ansible-toolkit | ansible_toolkit/vault.py | restore | def restore(path, password_file=None):
"""
Retrieves a file from the atk vault and restores it to its original
location, re-encrypting it if it has changed.
:param path: path to original file
"""
vault = VaultLib(get_vault_password(password_file))
atk_path = os.path.join(ATK_VAULT, path)
... | python | def restore(path, password_file=None):
"""
Retrieves a file from the atk vault and restores it to its original
location, re-encrypting it if it has changed.
:param path: path to original file
"""
vault = VaultLib(get_vault_password(password_file))
atk_path = os.path.join(ATK_VAULT, path)
... | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.append | def append(self, other):
"""Appends stars from another StarPopulations, in place.
:param other:
Another :class:`StarPopulation`; must have same columns as ``self``.
"""
if not isinstance(other,StarPopulation):
raise TypeError('Only StarPopulation objects can be ... | python | def append(self, other):
"""Appends stars from another StarPopulations, in place.
:param other:
Another :class:`StarPopulation`; must have same columns as ``self``.
"""
if not isinstance(other,StarPopulation):
raise TypeError('Only StarPopulation objects can be ... | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.bands | def bands(self):
"""
Bandpasses for which StarPopulation has magnitude data
"""
bands = []
for c in self.stars.columns:
if re.search('_mag',c):
bands.append(c)
return bands | python | def bands(self):
"""
Bandpasses for which StarPopulation has magnitude data
"""
bands = []
for c in self.stars.columns:
if re.search('_mag',c):
bands.append(c)
return bands | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.distance | def distance(self,value):
"""New distance value must be a ``Quantity`` object
"""
self.stars['distance'] = value.to('pc').value
old_distmod = self.stars['distmod'].copy()
new_distmod = distancemodulus(self.stars['distance'])
for m in self.bands:
self.stars[m... | python | def distance(self,value):
"""New distance value must be a ``Quantity`` object
"""
self.stars['distance'] = value.to('pc').value
old_distmod = self.stars['distmod'].copy()
new_distmod = distancemodulus(self.stars['distance'])
for m in self.bands:
self.stars[m... | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.distok | def distok(self):
"""
Boolean array showing which stars pass all distribution constraints.
A "distribution constraint" is a constraint that affects the
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"""
ok = np.ones(len(self.stars)).astype(bool)
for name in ... | python | def distok(self):
"""
Boolean array showing which stars pass all distribution constraints.
A "distribution constraint" is a constraint that affects the
distribution of stars, rather than just the number.
"""
ok = np.ones(len(self.stars)).astype(bool)
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.countok | def countok(self):
"""
Boolean array showing which stars pass all count constraints.
A "count constraint" is a constraint that affects the number of stars.
"""
ok = np.ones(len(self.stars)).astype(bool)
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"""
Boolean array showing which stars pass all count constraints.
A "count constraint" is a constraint that affects the number of stars.
"""
ok = np.ones(len(self.stars)).astype(bool)
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.prophist2d | def prophist2d(self,propx,propy, mask=None,
logx=False,logy=False,
fig=None,selected=False,**kwargs):
"""Makes a 2d density histogram of two given properties
:param propx,propy:
Names of properties to histogram. Must be names of columns
in ... | python | def prophist2d(self,propx,propy, mask=None,
logx=False,logy=False,
fig=None,selected=False,**kwargs):
"""Makes a 2d density histogram of two given properties
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Names of properties to histogram. Must be names of columns
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.prophist | def prophist(self,prop,fig=None,log=False, mask=None,
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Name of property to plot. Must be column of ``self.stars``.
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selected=False,**kwargs):
"""Plots a 1-d histogram of desired property.
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Name of property to plot. Must be column of ``self.stars``.
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.constraint_stats | def constraint_stats(self,primarylist=None):
"""Returns information about effect of constraints on population.
:param primarylist:
List of constraint names that you want specific information on
(i.e., not blended within "multiple constraints".)
:return:
``dict`... | python | def constraint_stats(self,primarylist=None):
"""Returns information about effect of constraints on population.
:param primarylist:
List of constraint names that you want specific information on
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.constraint_piechart | def constraint_piechart(self,primarylist=None,
fig=None,title='',colordict=None,
legend=True,nolabels=False):
"""Makes piechart illustrating constraints on population
:param primarylist: (optional)
List of most import constraints to sh... | python | def constraint_piechart(self,primarylist=None,
fig=None,title='',colordict=None,
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.constraints | def constraints(self):
"""
Constraints applied to the population.
"""
try:
return self._constraints
except AttributeError:
self._constraints = ConstraintDict()
return self._constraints | python | def constraints(self):
"""
Constraints applied to the population.
"""
try:
return self._constraints
except AttributeError:
self._constraints = ConstraintDict()
return self._constraints | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.hidden_constraints | def hidden_constraints(self):
"""
Constraints applied to the population, but temporarily removed.
"""
try:
return self._hidden_constraints
except AttributeError:
self._hidden_constraints = ConstraintDict()
return self._hidden_constraints | python | def hidden_constraints(self):
"""
Constraints applied to the population, but temporarily removed.
"""
try:
return self._hidden_constraints
except AttributeError:
self._hidden_constraints = ConstraintDict()
return self._hidden_constraints | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.apply_constraint | def apply_constraint(self,constraint,selectfrac_skip=False,
distribution_skip=False,overwrite=False):
"""Apply a constraint to the population
:param constraint:
Constraint to apply.
:type constraint:
:class:`Constraint`
:param selectfrac... | python | def apply_constraint(self,constraint,selectfrac_skip=False,
distribution_skip=False,overwrite=False):
"""Apply a constraint to the population
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Constraint to apply.
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.replace_constraint | def replace_constraint(self,name,selectfrac_skip=False,distribution_skip=False):
"""
Re-apply constraint that had been removed
:param name:
Name of constraint to replace
:param selectfrac_skip,distribution_skip: (optional)
Same as :func:`StarPopulation.apply_con... | python | def replace_constraint(self,name,selectfrac_skip=False,distribution_skip=False):
"""
Re-apply constraint that had been removed
:param name:
Name of constraint to replace
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.constrain_property | def constrain_property(self,prop,lo=-np.inf,hi=np.inf,
measurement=None,thresh=3,
selectfrac_skip=False,distribution_skip=False):
"""Apply constraint that constrains property.
:param prop:
Name of property. Must be column in ``self.star... | python | def constrain_property(self,prop,lo=-np.inf,hi=np.inf,
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.apply_trend_constraint | def apply_trend_constraint(self, limit, dt, distribution_skip=False,
**kwargs):
"""
Constrains change in RV to be less than limit over time dt.
Only works if ``dRV`` and ``Plong`` attributes are defined
for population.
:param limit:
Ra... | python | def apply_trend_constraint(self, limit, dt, distribution_skip=False,
**kwargs):
"""
Constrains change in RV to be less than limit over time dt.
Only works if ``dRV`` and ``Plong`` attributes are defined
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.apply_cc | def apply_cc(self, cc, distribution_skip=False,
**kwargs):
"""
Apply contrast-curve constraint to population.
Only works if object has ``Rsky``, ``dmag`` attributes
:param cc:
Contrast curve.
:type cc:
:class:`ContrastCurveConstraint`
... | python | def apply_cc(self, cc, distribution_skip=False,
**kwargs):
"""
Apply contrast-curve constraint to population.
Only works if object has ``Rsky``, ``dmag`` attributes
:param cc:
Contrast curve.
:type cc:
:class:`ContrastCurveConstraint`
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.apply_vcc | def apply_vcc(self, vcc, distribution_skip=False,
**kwargs):
"""
Applies "velocity contrast curve" to population.
That is, the constraint that comes from not seeing two sets
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Only works if population has ``dmag``... | python | def apply_vcc(self, vcc, distribution_skip=False,
**kwargs):
"""
Applies "velocity contrast curve" to population.
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.set_maxrad | def set_maxrad(self,maxrad, distribution_skip=True):
"""
Adds a constraint that rejects everything with Rsky > maxrad
Requires ``Rsky`` attribute, which should always have units.
:param maxrad:
The maximum angular value of Rsky.
:type maxrad:
:class:`ast... | python | def set_maxrad(self,maxrad, distribution_skip=True):
"""
Adds a constraint that rejects everything with Rsky > maxrad
Requires ``Rsky`` attribute, which should always have units.
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The maximum angular value of Rsky.
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.constraint_df | def constraint_df(self):
"""
A DataFrame representing all constraints, hidden or not
"""
df = pd.DataFrame()
for name,c in self.constraints.items():
df[name] = c.ok
for name,c in self.hidden_constraints.items():
df[name] = c.ok
return df | python | def constraint_df(self):
"""
A DataFrame representing all constraints, hidden or not
"""
df = pd.DataFrame()
for name,c in self.constraints.items():
df[name] = c.ok
for name,c in self.hidden_constraints.items():
df[name] = c.ok
return df | [
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.save_hdf | def save_hdf(self,filename,path='',properties=None,
overwrite=False, append=False):
"""Saves to HDF5 file.
Subclasses should be sure to define
``_properties`` attribute to ensure that all
correct attributes get saved. Load a saved population
with :func:`StarPop... | python | def save_hdf(self,filename,path='',properties=None,
overwrite=False, append=False):
"""Saves to HDF5 file.
Subclasses should be sure to define
``_properties`` attribute to ensure that all
correct attributes get saved. Load a saved population
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timothydmorton/VESPA | vespa/stars/populations.py | StarPopulation.load_hdf | def load_hdf(cls, filename, path=''):
"""Loads StarPopulation from .h5 file
Correct properties should be restored to object, and object
will be original type that was saved. Complement to
:func:`StarPopulation.save_hdf`.
Example usage::
>>> from vespa.stars import... | python | def load_hdf(cls, filename, path=''):
"""Loads StarPopulation from .h5 file
Correct properties should be restored to object, and object
will be original type that was saved. Complement to
:func:`StarPopulation.save_hdf`.
Example usage::
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timothydmorton/VESPA | vespa/stars/populations.py | BinaryPopulation.binary_fraction | def binary_fraction(self,query='mass_A >= 0'):
"""
Binary fraction of stars passing given query
:param query:
Query to pass to stars ``DataFrame``.
"""
subdf = self.stars.query(query)
nbinaries = (subdf['mass_B'] > 0).sum()
frac = nbinaries/len(subdf... | python | def binary_fraction(self,query='mass_A >= 0'):
"""
Binary fraction of stars passing given query
:param query:
Query to pass to stars ``DataFrame``.
"""
subdf = self.stars.query(query)
nbinaries = (subdf['mass_B'] > 0).sum()
frac = nbinaries/len(subdf... | [
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timothydmorton/VESPA | vespa/stars/populations.py | BinaryPopulation.dmag | def dmag(self,band):
"""
Difference in magnitude between primary and secondary stars
:param band:
Photometric bandpass.
"""
mag2 = self.stars['{}_mag_B'.format(band)]
mag1 = self.stars['{}_mag_A'.format(band)]
return mag2-mag1 | python | def dmag(self,band):
"""
Difference in magnitude between primary and secondary stars
:param band:
Photometric bandpass.
"""
mag2 = self.stars['{}_mag_B'.format(band)]
mag1 = self.stars['{}_mag_A'.format(band)]
return mag2-mag1 | [
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timothydmorton/VESPA | vespa/stars/populations.py | BinaryPopulation.rsky_distribution | def rsky_distribution(self,rmax=None,smooth=0.1,nbins=100):
"""
Distribution of projected separations
Returns a :class:`simpledists.Hist_Distribution` object.
:param rmax: (optional)
Maximum radius to calculate distribution.
:param dr: (optional)
Bin wi... | python | def rsky_distribution(self,rmax=None,smooth=0.1,nbins=100):
"""
Distribution of projected separations
Returns a :class:`simpledists.Hist_Distribution` object.
:param rmax: (optional)
Maximum radius to calculate distribution.
:param dr: (optional)
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timothydmorton/VESPA | vespa/stars/populations.py | Simulated_BinaryPopulation.generate | def generate(self, M, age=9.6, feh=0.0,
ichrone='mist', n=1e4, bands=None, **kwargs):
"""
Function that generates population.
Called by ``__init__`` if ``M`` is passed.
"""
ichrone = get_ichrone(ichrone, bands=bands)
if np.size(M) > 1:
n = np... | python | def generate(self, M, age=9.6, feh=0.0,
ichrone='mist', n=1e4, bands=None, **kwargs):
"""
Function that generates population.
Called by ``__init__`` if ``M`` is passed.
"""
ichrone = get_ichrone(ichrone, bands=bands)
if np.size(M) > 1:
n = np... | [
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timothydmorton/VESPA | vespa/stars/populations.py | TriplePopulation.dmag | def dmag(self, band):
"""
Difference in magnitudes between fainter and brighter components in band.
:param band:
Photometric bandpass.
"""
m1 = self.stars['{}_mag_A'.format(band)]
m2 = addmags(self.stars['{}_mag_B'.format(band)],
self.st... | python | def dmag(self, band):
"""
Difference in magnitudes between fainter and brighter components in band.
:param band:
Photometric bandpass.
"""
m1 = self.stars['{}_mag_A'.format(band)]
m2 = addmags(self.stars['{}_mag_B'.format(band)],
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timothydmorton/VESPA | vespa/stars/populations.py | TriplePopulation.dRV | def dRV(self, dt, band='g'):
"""Returns dRV of star A, if A is brighter than B+C, or of star B if B+C is brighter
"""
return (self.orbpop.dRV_1(dt)*self.A_brighter(band) +
self.orbpop.dRV_2(dt)*self.BC_brighter(band)) | python | def dRV(self, dt, band='g'):
"""Returns dRV of star A, if A is brighter than B+C, or of star B if B+C is brighter
"""
return (self.orbpop.dRV_1(dt)*self.A_brighter(band) +
self.orbpop.dRV_2(dt)*self.BC_brighter(band)) | [
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timothydmorton/VESPA | vespa/stars/populations.py | TriplePopulation.triple_fraction | def triple_fraction(self,query='mass_A > 0', unc=False):
"""
Triple fraction of stars following given query
"""
subdf = self.stars.query(query)
ntriples = ((subdf['mass_B'] > 0) & (subdf['mass_C'] > 0)).sum()
frac = ntriples/len(subdf)
if unc:
return f... | python | def triple_fraction(self,query='mass_A > 0', unc=False):
"""
Triple fraction of stars following given query
"""
subdf = self.stars.query(query)
ntriples = ((subdf['mass_B'] > 0) & (subdf['mass_C'] > 0)).sum()
frac = ntriples/len(subdf)
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timothydmorton/VESPA | vespa/stars/populations.py | Observed_BinaryPopulation.starmodel_props | def starmodel_props(self):
"""Default mag_err is 0.05, arbitrarily
"""
props = {}
mags = self.mags
mag_errs = self.mag_errs
for b in mags.keys():
if np.size(mags[b])==2:
props[b] = mags[b]
elif np.size(mags[b])==1:
m... | python | def starmodel_props(self):
"""Default mag_err is 0.05, arbitrarily
"""
props = {}
mags = self.mags
mag_errs = self.mag_errs
for b in mags.keys():
if np.size(mags[b])==2:
props[b] = mags[b]
elif np.size(mags[b])==1:
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timothydmorton/VESPA | vespa/stars/populations.py | BGStarPopulation.dmag | def dmag(self,band):
"""
Magnitude difference between primary star and BG stars
"""
if self.mags is None:
raise ValueError('dmag is not defined because primary mags are not defined for this population.')
return self.stars['{}_mag'.format(band)] - self.mags[band] | python | def dmag(self,band):
"""
Magnitude difference between primary star and BG stars
"""
if self.mags is None:
raise ValueError('dmag is not defined because primary mags are not defined for this population.')
return self.stars['{}_mag'.format(band)] - self.mags[band] | [
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Update screen if necessary and release the lock so receiveThread can run
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timothydmorton/VESPA | vespa/stars/constraints.py | Constraint.resample | def resample(self, inds):
"""Returns copy of constraint, with mask rearranged according to indices
"""
new = copy.deepcopy(self)
for arr in self.arrays:
x = getattr(new, arr)
setattr(new, arr, x[inds])
return new | python | def resample(self, inds):
"""Returns copy of constraint, with mask rearranged according to indices
"""
new = copy.deepcopy(self)
for arr in self.arrays:
x = getattr(new, arr)
setattr(new, arr, x[inds])
return new | [
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timothydmorton/VESPA | vespa/fpp.py | save | def save(self, overwrite=True):
"""
Saves PopulationSet and TransitSignal.
Shouldn't need to use this if you're using
:func:`FPPCalculation.from_ini`.
Saves :class`PopulationSet` to ``[folder]/popset.h5]``
and :class:`TransitSignal` to ``[folder]/trsig.pkl``.
:... | python | def save(self, overwrite=True):
"""
Saves PopulationSet and TransitSignal.
Shouldn't need to use this if you're using
:func:`FPPCalculation.from_ini`.
Saves :class`PopulationSet` to ``[folder]/popset.h5]``
and :class:`TransitSignal` to ``[folder]/trsig.pkl``.
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timothydmorton/VESPA | vespa/fpp.py | load | def load(cls, folder):
"""
Loads PopulationSet from folder
``popset.h5`` and ``trsig.pkl`` must exist in folder.
:param folder:
Folder from which to load.
"""
popset = PopulationSet.load_hdf(os.path.join(folder,'popset.h5'))
sigfile = os.path.join(fo... | python | def load(cls, folder):
"""
Loads PopulationSet from folder
``popset.h5`` and ``trsig.pkl`` must exist in folder.
:param folder:
Folder from which to load.
"""
popset = PopulationSet.load_hdf(os.path.join(folder,'popset.h5'))
sigfile = os.path.join(fo... | [
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timothydmorton/VESPA | vespa/fpp.py | FPPplots | def FPPplots(self, folder=None, format='png', tag=None, **kwargs):
"""
Make FPP diagnostic plots
Makes likelihood "fuzz plot" for each model, a FPP summary figure,
a plot of the :class:`TransitSignal`, and writes a ``results.txt``
file.
:param folder: (optional)
... | python | def FPPplots(self, folder=None, format='png', tag=None, **kwargs):
"""
Make FPP diagnostic plots
Makes likelihood "fuzz plot" for each model, a FPP summary figure,
a plot of the :class:`TransitSignal`, and writes a ``results.txt``
file.
:param folder: (optional)
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timothydmorton/VESPA | vespa/fpp.py | write_results | def write_results(self,folder=None, filename='results.txt', to_file=True):
"""
Writes text file of calculation summary.
:param folder: (optional)
Folder to which to write ``results.txt``.
:param filename:
Filename to write. Default=``results.txt``.
:pa... | python | def write_results(self,folder=None, filename='results.txt', to_file=True):
"""
Writes text file of calculation summary.
:param folder: (optional)
Folder to which to write ``results.txt``.
:param filename:
Filename to write. Default=``results.txt``.
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timothydmorton/VESPA | vespa/fpp.py | save_popset | def save_popset(self,filename='popset.h5',**kwargs):
"""Saves the PopulationSet
Calls :func:`PopulationSet.save_hdf`.
"""
self.popset.save_hdf(os.path.join(self.folder,filename)) | python | def save_popset(self,filename='popset.h5',**kwargs):
"""Saves the PopulationSet
Calls :func:`PopulationSet.save_hdf`.
"""
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timothydmorton/VESPA | vespa/fpp.py | save_signal | def save_signal(self,filename=None):
"""
Saves TransitSignal.
Calls :func:`TransitSignal.save`; default filename is
``trsig.pkl`` in ``self.folder``.
"""
if filename is None:
filename = os.path.join(self.folder,'trsig.pkl')
self.trsig.save(filename) | python | def save_signal(self,filename=None):
"""
Saves TransitSignal.
Calls :func:`TransitSignal.save`; default filename is
``trsig.pkl`` in ``self.folder``.
"""
if filename is None:
filename = os.path.join(self.folder,'trsig.pkl')
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timothydmorton/VESPA | vespa/kepler.py | modelshift_weaksec | def modelshift_weaksec(koi):
"""
Max secondary depth based on model-shift secondary test from Jeff Coughlin
secondary metric: mod_depth_sec_dv * (1 + 3*mod_fred_dv / mod_sig_sec_dv)
"""
num = KOIDATA.ix[ku.koiname(koi), 'koi_tce_plnt_num']
if np.isnan(num):
num = 1
kid = KOIDATA.ix[... | python | def modelshift_weaksec(koi):
"""
Max secondary depth based on model-shift secondary test from Jeff Coughlin
secondary metric: mod_depth_sec_dv * (1 + 3*mod_fred_dv / mod_sig_sec_dv)
"""
num = KOIDATA.ix[ku.koiname(koi), 'koi_tce_plnt_num']
if np.isnan(num):
num = 1
kid = KOIDATA.ix[... | [
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timothydmorton/VESPA | vespa/kepler.py | use_property | def use_property(kepid, prop):
"""Returns true if provenance of property is SPE or AST
"""
try:
prov = kicu.DATA.ix[kepid, '{}_prov'.format(prop)]
return any([prov.startswith(s) for s in ['SPE', 'AST']])
except KeyError:
raise MissingStellarError('{} not in stellar table?'.format... | python | def use_property(kepid, prop):
"""Returns true if provenance of property is SPE or AST
"""
try:
prov = kicu.DATA.ix[kepid, '{}_prov'.format(prop)]
return any([prov.startswith(s) for s in ['SPE', 'AST']])
except KeyError:
raise MissingStellarError('{} not in stellar table?'.format... | [
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timothydmorton/VESPA | vespa/kepler.py | star_config | def star_config(koi, bands=['g','r','i','z','J','H','K'],
unc=dict(g=0.05, r=0.05, i=0.05, z=0.05,
J=0.02, H=0.02, K=0.02), **kwargs):
"""returns star config object for given KOI
"""
folder = os.path.join(KOI_FPPDIR, ku.koiname(koi))
if not os.path.exists(folder... | python | def star_config(koi, bands=['g','r','i','z','J','H','K'],
unc=dict(g=0.05, r=0.05, i=0.05, z=0.05,
J=0.02, H=0.02, K=0.02), **kwargs):
"""returns star config object for given KOI
"""
folder = os.path.join(KOI_FPPDIR, ku.koiname(koi))
if not os.path.exists(folder... | [
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timothydmorton/VESPA | vespa/kepler.py | fpp_config | def fpp_config(koi, **kwargs):
"""returns config object for given KOI
"""
folder = os.path.join(KOI_FPPDIR, ku.koiname(koi))
if not os.path.exists(folder):
os.makedirs(folder)
config = ConfigObj(os.path.join(folder,'fpp.ini'))
koi = ku.koiname(koi)
rowefit = jrowe_fit(koi)
con... | python | def fpp_config(koi, **kwargs):
"""returns config object for given KOI
"""
folder = os.path.join(KOI_FPPDIR, ku.koiname(koi))
if not os.path.exists(folder):
os.makedirs(folder)
config = ConfigObj(os.path.join(folder,'fpp.ini'))
koi = ku.koiname(koi)
rowefit = jrowe_fit(koi)
con... | [
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timothydmorton/VESPA | vespa/kepler.py | KOI_FPPCalculation.apply_default_constraints | def apply_default_constraints(self):
"""Applies default secthresh & exclusion radius constraints
"""
try:
self.apply_secthresh(pipeline_weaksec(self.koi))
except NoWeakSecondaryError:
logging.warning('No secondary eclipse threshold set for {}'.format(self.koi))
... | python | def apply_default_constraints(self):
"""Applies default secthresh & exclusion radius constraints
"""
try:
self.apply_secthresh(pipeline_weaksec(self.koi))
except NoWeakSecondaryError:
logging.warning('No secondary eclipse threshold set for {}'.format(self.koi))
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dellis23/ansible-toolkit | ansible_toolkit/git_diff.py | get_old_sha | def get_old_sha(diff_part):
"""
Returns the SHA for the original file that was changed in a diff part.
"""
r = re.compile(r'index ([a-fA-F\d]*)')
return r.search(diff_part).groups()[0] | python | def get_old_sha(diff_part):
"""
Returns the SHA for the original file that was changed in a diff part.
"""
r = re.compile(r'index ([a-fA-F\d]*)')
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dellis23/ansible-toolkit | ansible_toolkit/git_diff.py | get_old_filename | def get_old_filename(diff_part):
"""
Returns the filename for the original file that was changed in a diff part.
"""
regexps = (
# e.g. "+++ a/foo/bar"
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# e.g. "+++ /dev/null"
r'^\-\-\- (.*)',
)
for regexp in regexps:
r = re.compile(regexp, ... | python | def get_old_filename(diff_part):
"""
Returns the filename for the original file that was changed in a diff part.
"""
regexps = (
# e.g. "+++ a/foo/bar"
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