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intuition-io/insights | insights/plugins/hipchat.py | Bot.message | def message(self, body, room_id, style='text'):
''' Send a message to the given room '''
# TODO Automatically detect body format ?
path = 'rooms/message'
data = {
'room_id': room_id,
'message': body,
'from': self.name,
'notify': 1,
'message_format': style,
'color': self.bg_color
}
log.info('sending message to hipchat', message=body, room=room_id)
feedback = self._api_call(path, data, requests.post)
log.debug(feedback)
return feedback | python | def message(self, body, room_id, style='text'):
''' Send a message to the given room '''
# TODO Automatically detect body format ?
path = 'rooms/message'
data = {
'room_id': room_id,
'message': body,
'from': self.name,
'notify': 1,
'message_format': style,
'color': self.bg_color
}
log.info('sending message to hipchat', message=body, room=room_id)
feedback = self._api_call(path, data, requests.post)
log.debug(feedback)
return feedback | [
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| a4eae53a1886164db96751d2b0964aa2acb7c2d7 | https://github.com/intuition-io/insights/blob/a4eae53a1886164db96751d2b0964aa2acb7c2d7/insights/plugins/hipchat.py#L53-L68 | train |
tethysplatform/condorpy | condorpy/job.py | Job.job_file | def job_file(self):
"""The path to the submit description file representing this job.
"""
job_file_name = '%s.job' % (self.name)
job_file_path = os.path.join(self.initial_dir, job_file_name)
self._job_file = job_file_path
return self._job_file | python | def job_file(self):
"""The path to the submit description file representing this job.
"""
job_file_name = '%s.job' % (self.name)
job_file_path = os.path.join(self.initial_dir, job_file_name)
self._job_file = job_file_path
return self._job_file | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L173-L180 | train |
tethysplatform/condorpy | condorpy/job.py | Job.log_file | def log_file(self):
"""The path to the log file for this job.
"""
log_file = self.get('log')
if not log_file:
log_file = '%s.log' % (self.name)
self.set('log', log_file)
return os.path.join(self.initial_dir, self.get('log')) | python | def log_file(self):
"""The path to the log file for this job.
"""
log_file = self.get('log')
if not log_file:
log_file = '%s.log' % (self.name)
self.set('log', log_file)
return os.path.join(self.initial_dir, self.get('log')) | [
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tethysplatform/condorpy | condorpy/job.py | Job.initial_dir | def initial_dir(self):
"""The initial directory defined for the job.
All input files, and log files are relative to this directory. Output files will be copied into this
directory by default. This directory will be created if it doesn't already exist when the job is submitted.
Note:
The executable file is defined relative to the current working directory, NOT to the initial directory.
The initial directory is created in the current working directory.
"""
initial_dir = self.get('initialdir')
if not initial_dir:
initial_dir = os.curdir #TODO does this conflict with the working directory?
if self._remote and os.path.isabs(initial_dir):
raise RemoteError('Cannot define an absolute path as an initial_dir on a remote scheduler')
return initial_dir | python | def initial_dir(self):
"""The initial directory defined for the job.
All input files, and log files are relative to this directory. Output files will be copied into this
directory by default. This directory will be created if it doesn't already exist when the job is submitted.
Note:
The executable file is defined relative to the current working directory, NOT to the initial directory.
The initial directory is created in the current working directory.
"""
initial_dir = self.get('initialdir')
if not initial_dir:
initial_dir = os.curdir #TODO does this conflict with the working directory?
if self._remote and os.path.isabs(initial_dir):
raise RemoteError('Cannot define an absolute path as an initial_dir on a remote scheduler')
return initial_dir | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L194-L210 | train |
tethysplatform/condorpy | condorpy/job.py | Job.submit | def submit(self, queue=None, options=[]):
"""Submits the job either locally or to a remote server if it is defined.
Args:
queue (int, optional): The number of sub-jobs to run. This argmuent will set the num_jobs attribute of
this object. Defaults to None, meaning the value of num_jobs will be used.
options (list of str, optional): A list of command line options for the condor_submit command. For
details on valid options see: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html.
Defaults to an empty list.
"""
if not self.executable:
log.error('Job %s was submitted with no executable', self.name)
raise NoExecutable('You cannot submit a job without an executable')
self._num_jobs = queue or self.num_jobs
self._write_job_file()
args = ['condor_submit']
args.extend(options)
args.append(self.job_file)
log.info('Submitting job %s with options: %s', self.name, args)
return super(Job, self).submit(args) | python | def submit(self, queue=None, options=[]):
"""Submits the job either locally or to a remote server if it is defined.
Args:
queue (int, optional): The number of sub-jobs to run. This argmuent will set the num_jobs attribute of
this object. Defaults to None, meaning the value of num_jobs will be used.
options (list of str, optional): A list of command line options for the condor_submit command. For
details on valid options see: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html.
Defaults to an empty list.
"""
if not self.executable:
log.error('Job %s was submitted with no executable', self.name)
raise NoExecutable('You cannot submit a job without an executable')
self._num_jobs = queue or self.num_jobs
self._write_job_file()
args = ['condor_submit']
args.extend(options)
args.append(self.job_file)
log.info('Submitting job %s with options: %s', self.name, args)
return super(Job, self).submit(args) | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L212-L236 | train |
tethysplatform/condorpy | condorpy/job.py | Job.wait | def wait(self, options=[], sub_job_num=None):
"""Wait for the job, or a sub-job to complete.
Args:
options (list of str, optional): A list of command line options for the condor_wait command. For
details on valid options see: http://research.cs.wisc.edu/htcondor/manual/current/condor_wait.html.
Defaults to an empty list.
job_num (int, optional): The number
"""
args = ['condor_wait']
args.extend(options)
job_id = '%s.%s' % (self.cluster_id, sub_job_num) if sub_job_num else str(self.cluster_id)
if self._remote:
abs_log_file = self.log_file
else:
abs_log_file = os.path.abspath(self.log_file)
args.extend([abs_log_file, job_id])
out, err = self._execute(args)
return out, err | python | def wait(self, options=[], sub_job_num=None):
"""Wait for the job, or a sub-job to complete.
Args:
options (list of str, optional): A list of command line options for the condor_wait command. For
details on valid options see: http://research.cs.wisc.edu/htcondor/manual/current/condor_wait.html.
Defaults to an empty list.
job_num (int, optional): The number
"""
args = ['condor_wait']
args.extend(options)
job_id = '%s.%s' % (self.cluster_id, sub_job_num) if sub_job_num else str(self.cluster_id)
if self._remote:
abs_log_file = self.log_file
else:
abs_log_file = os.path.abspath(self.log_file)
args.extend([abs_log_file, job_id])
out, err = self._execute(args)
return out, err | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L247-L265 | train |
tethysplatform/condorpy | condorpy/job.py | Job.get | def get(self, attr, value=None, resolve=True):
"""Get the value of an attribute from submit description file.
Args:
attr (str): The name of the attribute whose value should be returned.
value (str, optional): A default value to return if 'attr' doesn't exist. Defaults to None.
resolve (bool, optional): If True then resolve references to other attributes in the value of 'attr'. If
False then return the raw value of 'attr'. Defaults to True.
Returns:
str: The value assigned to 'attr' if 'attr' exists, otherwise 'value'.
"""
try:
if resolve:
value = self._resolve_attribute(attr)
else:
value = self.attributes[attr]
except KeyError:
pass
return value | python | def get(self, attr, value=None, resolve=True):
"""Get the value of an attribute from submit description file.
Args:
attr (str): The name of the attribute whose value should be returned.
value (str, optional): A default value to return if 'attr' doesn't exist. Defaults to None.
resolve (bool, optional): If True then resolve references to other attributes in the value of 'attr'. If
False then return the raw value of 'attr'. Defaults to True.
Returns:
str: The value assigned to 'attr' if 'attr' exists, otherwise 'value'.
"""
try:
if resolve:
value = self._resolve_attribute(attr)
else:
value = self.attributes[attr]
except KeyError:
pass
return value | [
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Args:
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resolve (bool, optional): If True then resolve references to other attributes in the value of 'attr'. If
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L267-L286 | train |
tethysplatform/condorpy | condorpy/job.py | Job.set | def set(self, attr, value):
"""Set the value of an attribute in the submit description file.
The value can be passed in as a Python type (i.e. a list, a tuple or a Python boolean).
The Python values will be reformatted into strings based on the standards described in
the HTCondor manual: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html
Args:
attr (str): The name of the attribute to set.
value (str): The value to assign to 'attr'.
"""
def escape_new_syntax(value, double_quote_escape='"'):
value = str(value)
value = value.replace("'", "''")
value = value.replace('"', '%s"' % double_quote_escape)
if ' ' in value or '\t' in value:
value = "'%s'" % value
return value
def escape_new_syntax_pre_post_script(value):
return escape_new_syntax(value, '\\')
def escape_remap(value):
value = value.replace('=', '\=')
value = value.replace(';', '\;')
return value
def join_function_template(join_string, escape_func):
return lambda value: join_string.join([escape_func(i) for i in value])
def quote_join_function_template(join_string, escape_func):
return lambda value: join_function_template(join_string, escape_func)(value)
join_functions = {'rempas': quote_join_function_template('; ', escape_remap),
'arguments': quote_join_function_template(' ', escape_new_syntax),
'Arguments': quote_join_function_template(' ', escape_new_syntax_pre_post_script)
}
if value is False:
value = 'false'
elif value is True:
value = 'true'
elif isinstance(value, list) or isinstance(value, tuple):
join_function = join_function_template(', ', str)
for key in list(join_functions.keys()):
if attr.endswith(key):
join_function = join_functions[key]
value = join_function(value)
self.attributes[attr] = value | python | def set(self, attr, value):
"""Set the value of an attribute in the submit description file.
The value can be passed in as a Python type (i.e. a list, a tuple or a Python boolean).
The Python values will be reformatted into strings based on the standards described in
the HTCondor manual: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html
Args:
attr (str): The name of the attribute to set.
value (str): The value to assign to 'attr'.
"""
def escape_new_syntax(value, double_quote_escape='"'):
value = str(value)
value = value.replace("'", "''")
value = value.replace('"', '%s"' % double_quote_escape)
if ' ' in value or '\t' in value:
value = "'%s'" % value
return value
def escape_new_syntax_pre_post_script(value):
return escape_new_syntax(value, '\\')
def escape_remap(value):
value = value.replace('=', '\=')
value = value.replace(';', '\;')
return value
def join_function_template(join_string, escape_func):
return lambda value: join_string.join([escape_func(i) for i in value])
def quote_join_function_template(join_string, escape_func):
return lambda value: join_function_template(join_string, escape_func)(value)
join_functions = {'rempas': quote_join_function_template('; ', escape_remap),
'arguments': quote_join_function_template(' ', escape_new_syntax),
'Arguments': quote_join_function_template(' ', escape_new_syntax_pre_post_script)
}
if value is False:
value = 'false'
elif value is True:
value = 'true'
elif isinstance(value, list) or isinstance(value, tuple):
join_function = join_function_template(', ', str)
for key in list(join_functions.keys()):
if attr.endswith(key):
join_function = join_functions[key]
value = join_function(value)
self.attributes[attr] = value | [
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| Set the value of an attribute in the submit description file.
The value can be passed in as a Python type (i.e. a list, a tuple or a Python boolean).
The Python values will be reformatted into strings based on the standards described in
the HTCondor manual: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html
Args:
attr (str): The name of the attribute to set.
value (str): The value to assign to 'attr'. | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L288-L339 | train |
tethysplatform/condorpy | condorpy/job.py | Job._update_status | def _update_status(self, sub_job_num=None):
"""Gets the job status.
Return:
str: The current status of the job
"""
job_id = '%s.%s' % (self.cluster_id, sub_job_num) if sub_job_num else str(self.cluster_id)
format = ['-format', '"%d"', 'JobStatus']
cmd = 'condor_q {0} {1} && condor_history {0} {1}'.format(job_id, ' '.join(format))
args = [cmd]
out, err = self._execute(args, shell=True, run_in_job_dir=False)
if err:
log.error('Error while updating status for job %s: %s', job_id, err)
raise HTCondorError(err)
if not out:
log.error('Error while updating status for job %s: Job not found.', job_id)
raise HTCondorError('Job not found.')
out = out.replace('\"', '')
log.info('Job %s status: %s', job_id, out)
if not sub_job_num:
if len(out) >= self.num_jobs:
out = out[:self.num_jobs]
else:
msg = 'There are {0} sub-jobs, but {1} status(es).'.format(self.num_jobs, len(out))
log.error(msg)
raise HTCondorError(msg)
#initialize status dictionary
status_dict = dict()
for val in CONDOR_JOB_STATUSES.values():
status_dict[val] = 0
for status_code_str in out:
status_code = 0
try:
status_code = int(status_code_str)
except ValueError:
pass
key = CONDOR_JOB_STATUSES[status_code]
status_dict[key] += 1
return status_dict | python | def _update_status(self, sub_job_num=None):
"""Gets the job status.
Return:
str: The current status of the job
"""
job_id = '%s.%s' % (self.cluster_id, sub_job_num) if sub_job_num else str(self.cluster_id)
format = ['-format', '"%d"', 'JobStatus']
cmd = 'condor_q {0} {1} && condor_history {0} {1}'.format(job_id, ' '.join(format))
args = [cmd]
out, err = self._execute(args, shell=True, run_in_job_dir=False)
if err:
log.error('Error while updating status for job %s: %s', job_id, err)
raise HTCondorError(err)
if not out:
log.error('Error while updating status for job %s: Job not found.', job_id)
raise HTCondorError('Job not found.')
out = out.replace('\"', '')
log.info('Job %s status: %s', job_id, out)
if not sub_job_num:
if len(out) >= self.num_jobs:
out = out[:self.num_jobs]
else:
msg = 'There are {0} sub-jobs, but {1} status(es).'.format(self.num_jobs, len(out))
log.error(msg)
raise HTCondorError(msg)
#initialize status dictionary
status_dict = dict()
for val in CONDOR_JOB_STATUSES.values():
status_dict[val] = 0
for status_code_str in out:
status_code = 0
try:
status_code = int(status_code_str)
except ValueError:
pass
key = CONDOR_JOB_STATUSES[status_code]
status_dict[key] += 1
return status_dict | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L350-L394 | train |
tethysplatform/condorpy | condorpy/job.py | Job._resolve_attribute | def _resolve_attribute(self, attribute):
"""Recursively replaces references to other attributes with their value.
Args:
attribute (str): The name of the attribute to resolve.
Returns:
str: The resolved value of 'attribute'.
"""
value = self.attributes[attribute]
if not value:
return None
resolved_value = re.sub('\$\((.*?)\)',self._resolve_attribute_match, value)
return resolved_value | python | def _resolve_attribute(self, attribute):
"""Recursively replaces references to other attributes with their value.
Args:
attribute (str): The name of the attribute to resolve.
Returns:
str: The resolved value of 'attribute'.
"""
value = self.attributes[attribute]
if not value:
return None
resolved_value = re.sub('\$\((.*?)\)',self._resolve_attribute_match, value)
return resolved_value | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L417-L431 | train |
tethysplatform/condorpy | condorpy/job.py | Job._resolve_attribute_match | def _resolve_attribute_match(self, match):
"""Replaces a reference to an attribute with the value of the attribute.
Args:
match (re.match object): A match object containing a match to a reference to an attribute.
"""
if match.group(1) == 'cluster':
return str(self.cluster_id)
return self.get(match.group(1), match.group(0)) | python | def _resolve_attribute_match(self, match):
"""Replaces a reference to an attribute with the value of the attribute.
Args:
match (re.match object): A match object containing a match to a reference to an attribute.
"""
if match.group(1) == 'cluster':
return str(self.cluster_id)
return self.get(match.group(1), match.group(0)) | [
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| a5aaaef0d73198f7d9756dda7abe98b4e209f1f4 | https://github.com/tethysplatform/condorpy/blob/a5aaaef0d73198f7d9756dda7abe98b4e209f1f4/condorpy/job.py#L433-L443 | train |
ktdreyer/txkoji | txkoji/channel.py | Channel.total_capacity | def total_capacity(self):
"""
Find the total task capacity available for this channel.
Query all the enabled hosts for this channel and sum up all the
capacities.
Each task has a "weight". Each task will be in "FREE" state until
there is enough capacity for the task's "weight" on a host.
:returns: deferred that when fired returns a float value: the total
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"""
# Ensure this task's channel has spare capacity for this task.
total_capacity = 0
hosts = yield self.hosts(enabled=True)
for host in hosts:
total_capacity += host.capacity
defer.returnValue(total_capacity) | python | def total_capacity(self):
"""
Find the total task capacity available for this channel.
Query all the enabled hosts for this channel and sum up all the
capacities.
Each task has a "weight". Each task will be in "FREE" state until
there is enough capacity for the task's "weight" on a host.
:returns: deferred that when fired returns a float value: the total
task weight that this channel can have open simultaneously.
"""
# Ensure this task's channel has spare capacity for this task.
total_capacity = 0
hosts = yield self.hosts(enabled=True)
for host in hosts:
total_capacity += host.capacity
defer.returnValue(total_capacity) | [
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| a7de380f29f745bf11730b27217208f6d4da7733 | https://github.com/ktdreyer/txkoji/blob/a7de380f29f745bf11730b27217208f6d4da7733/txkoji/channel.py#L33-L51 | train |
tjcsl/cslbot | cslbot/commands/google.py | cmd | def cmd(send, msg, args):
"""Googles something.
Syntax: {command} <term>
"""
if not msg:
send("Google what?")
return
key = args['config']['api']['googleapikey']
cx = args['config']['api']['googlesearchid']
data = get('https://www.googleapis.com/customsearch/v1', params={'key': key, 'cx': cx, 'q': msg}).json()
if 'items' not in data:
send("Google didn't say much.")
else:
url = data['items'][0]['link']
send("Google says %s" % url) | python | def cmd(send, msg, args):
"""Googles something.
Syntax: {command} <term>
"""
if not msg:
send("Google what?")
return
key = args['config']['api']['googleapikey']
cx = args['config']['api']['googlesearchid']
data = get('https://www.googleapis.com/customsearch/v1', params={'key': key, 'cx': cx, 'q': msg}).json()
if 'items' not in data:
send("Google didn't say much.")
else:
url = data['items'][0]['link']
send("Google says %s" % url) | [
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| aebe07be47141f61d7c180706bddfb707f19b2b5 | https://github.com/tjcsl/cslbot/blob/aebe07be47141f61d7c180706bddfb707f19b2b5/cslbot/commands/google.py#L24-L40 | train |
rraadd88/rohan | rohan/dandage/__init__.py | get_deps | def get_deps(cfg=None,deps=[]):
"""
Installs conda dependencies.
:param cfg: configuration dict
"""
if not cfg is None:
if not 'deps' in cfg:
cfg['deps']=deps
else:
deps=cfg['deps']
if not len(deps)==0:
for dep in deps:
if not dep in cfg:
runbashcmd(f'conda install {dep}',test=cfg['test'])
cfg[dep]=dep
logging.info(f"{len(deps)} deps installed.")
return cfg | python | def get_deps(cfg=None,deps=[]):
"""
Installs conda dependencies.
:param cfg: configuration dict
"""
if not cfg is None:
if not 'deps' in cfg:
cfg['deps']=deps
else:
deps=cfg['deps']
if not len(deps)==0:
for dep in deps:
if not dep in cfg:
runbashcmd(f'conda install {dep}',test=cfg['test'])
cfg[dep]=dep
logging.info(f"{len(deps)} deps installed.")
return cfg | [
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| b0643a3582a2fffc0165ace69fb80880d92bfb10 | https://github.com/rraadd88/rohan/blob/b0643a3582a2fffc0165ace69fb80880d92bfb10/rohan/dandage/__init__.py#L7-L24 | train |
Syndace/python-xeddsa | xeddsa/xeddsa.py | XEdDSA.mont_pub_from_mont_priv | def mont_pub_from_mont_priv(cls, mont_priv):
"""
Restore the Montgomery public key from a Montgomery private key.
:param mont_priv: A bytes-like object encoding the private key with length
MONT_PRIV_KEY_SIZE.
:returns: A bytes-like object encoding the public key with length
MONT_PUB_KEY_SIZE.
"""
if not isinstance(mont_priv, bytes):
raise TypeError("Wrong type passed for the mont_priv parameter.")
if len(mont_priv) != cls.MONT_PRIV_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_priv parameter.")
return bytes(cls._mont_pub_from_mont_priv(bytearray(mont_priv))) | python | def mont_pub_from_mont_priv(cls, mont_priv):
"""
Restore the Montgomery public key from a Montgomery private key.
:param mont_priv: A bytes-like object encoding the private key with length
MONT_PRIV_KEY_SIZE.
:returns: A bytes-like object encoding the public key with length
MONT_PUB_KEY_SIZE.
"""
if not isinstance(mont_priv, bytes):
raise TypeError("Wrong type passed for the mont_priv parameter.")
if len(mont_priv) != cls.MONT_PRIV_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_priv parameter.")
return bytes(cls._mont_pub_from_mont_priv(bytearray(mont_priv))) | [
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| a11721524c96ce354cca3628e003c6fcf7ce3e42 | https://github.com/Syndace/python-xeddsa/blob/a11721524c96ce354cca3628e003c6fcf7ce3e42/xeddsa/xeddsa.py#L85-L101 | train |
Syndace/python-xeddsa | xeddsa/xeddsa.py | XEdDSA.mont_priv_to_ed_pair | def mont_priv_to_ed_pair(cls, mont_priv):
"""
Derive a Twisted Edwards key pair from given Montgomery private key.
:param mont_priv: A bytes-like object encoding the private key with length
MONT_PRIV_KEY_SIZE.
:returns: A tuple of bytes-like objects encoding the private key with length
ED_PRIV_KEY_SIZE and the public key with length ED_PUB_KEY_SIZE.
"""
if not isinstance(mont_priv, bytes):
raise TypeError("Wrong type passed for the mont_priv parameter.")
if len(mont_priv) != cls.MONT_PRIV_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_priv parameter.")
ed_priv, ed_pub = cls._mont_priv_to_ed_pair(bytearray(mont_priv))
return bytes(ed_priv), bytes(ed_pub) | python | def mont_priv_to_ed_pair(cls, mont_priv):
"""
Derive a Twisted Edwards key pair from given Montgomery private key.
:param mont_priv: A bytes-like object encoding the private key with length
MONT_PRIV_KEY_SIZE.
:returns: A tuple of bytes-like objects encoding the private key with length
ED_PRIV_KEY_SIZE and the public key with length ED_PUB_KEY_SIZE.
"""
if not isinstance(mont_priv, bytes):
raise TypeError("Wrong type passed for the mont_priv parameter.")
if len(mont_priv) != cls.MONT_PRIV_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_priv parameter.")
ed_priv, ed_pub = cls._mont_priv_to_ed_pair(bytearray(mont_priv))
return bytes(ed_priv), bytes(ed_pub) | [
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| a11721524c96ce354cca3628e003c6fcf7ce3e42 | https://github.com/Syndace/python-xeddsa/blob/a11721524c96ce354cca3628e003c6fcf7ce3e42/xeddsa/xeddsa.py#L116-L134 | train |
Syndace/python-xeddsa | xeddsa/xeddsa.py | XEdDSA.mont_pub_to_ed_pub | def mont_pub_to_ed_pub(cls, mont_pub):
"""
Derive a Twisted Edwards public key from given Montgomery public key.
:param mont_pub: A bytes-like object encoding the public key with length
MONT_PUB_KEY_SIZE.
:returns: A bytes-like object encoding the public key with length ED_PUB_KEY_SIZE.
"""
if not isinstance(mont_pub, bytes):
raise TypeError("Wrong type passed for the mont_pub parameter.")
if len(mont_pub) != cls.MONT_PUB_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_pub parameter.")
return bytes(cls._mont_pub_to_ed_pub(bytearray(mont_pub))) | python | def mont_pub_to_ed_pub(cls, mont_pub):
"""
Derive a Twisted Edwards public key from given Montgomery public key.
:param mont_pub: A bytes-like object encoding the public key with length
MONT_PUB_KEY_SIZE.
:returns: A bytes-like object encoding the public key with length ED_PUB_KEY_SIZE.
"""
if not isinstance(mont_pub, bytes):
raise TypeError("Wrong type passed for the mont_pub parameter.")
if len(mont_pub) != cls.MONT_PUB_KEY_SIZE:
raise ValueError("Invalid value passed for the mont_pub parameter.")
return bytes(cls._mont_pub_to_ed_pub(bytearray(mont_pub))) | [
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| a11721524c96ce354cca3628e003c6fcf7ce3e42 | https://github.com/Syndace/python-xeddsa/blob/a11721524c96ce354cca3628e003c6fcf7ce3e42/xeddsa/xeddsa.py#L150-L165 | train |
Syndace/python-xeddsa | xeddsa/xeddsa.py | XEdDSA.sign | def sign(self, data, nonce = None):
"""
Sign data using the Montgomery private key stored by this XEdDSA instance.
:param data: A bytes-like object containing the data to sign.
:param nonce: A bytes-like object with length 64 or None.
:returns: A bytes-like object encoding the signature with length SIGNATURE_SIZE.
If the nonce parameter is None, a new nonce is generated and used.
:raises MissingKeyException: If the Montgomery private key is not available.
"""
cls = self.__class__
if not self.__mont_priv:
raise MissingKeyException(
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)
if not isinstance(data, bytes):
raise TypeError("The data parameter must be a bytes-like object.")
if nonce == None:
nonce = os.urandom(64)
if not isinstance(nonce, bytes):
raise TypeError("Wrong type passed for the nonce parameter.")
if len(nonce) != 64:
raise ValueError("Invalid value passed for the nonce parameter.")
ed_priv, ed_pub = cls._mont_priv_to_ed_pair(bytearray(self.__mont_priv))
return bytes(cls._sign(
bytearray(data),
bytearray(nonce),
ed_priv,
ed_pub
)) | python | def sign(self, data, nonce = None):
"""
Sign data using the Montgomery private key stored by this XEdDSA instance.
:param data: A bytes-like object containing the data to sign.
:param nonce: A bytes-like object with length 64 or None.
:returns: A bytes-like object encoding the signature with length SIGNATURE_SIZE.
If the nonce parameter is None, a new nonce is generated and used.
:raises MissingKeyException: If the Montgomery private key is not available.
"""
cls = self.__class__
if not self.__mont_priv:
raise MissingKeyException(
"Cannot sign using this XEdDSA instance, Montgomery private key missing."
)
if not isinstance(data, bytes):
raise TypeError("The data parameter must be a bytes-like object.")
if nonce == None:
nonce = os.urandom(64)
if not isinstance(nonce, bytes):
raise TypeError("Wrong type passed for the nonce parameter.")
if len(nonce) != 64:
raise ValueError("Invalid value passed for the nonce parameter.")
ed_priv, ed_pub = cls._mont_priv_to_ed_pair(bytearray(self.__mont_priv))
return bytes(cls._sign(
bytearray(data),
bytearray(nonce),
ed_priv,
ed_pub
)) | [
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| a11721524c96ce354cca3628e003c6fcf7ce3e42 | https://github.com/Syndace/python-xeddsa/blob/a11721524c96ce354cca3628e003c6fcf7ce3e42/xeddsa/xeddsa.py#L179-L218 | train |
Syndace/python-xeddsa | xeddsa/xeddsa.py | XEdDSA.verify | def verify(self, data, signature):
"""
Verify signed data using the Montgomery public key stored by this XEdDSA instance.
:param data: A bytes-like object containing the data that was signed.
:param signature: A bytes-like object encoding the signature with length
SIGNATURE_SIZE.
:returns: A boolean indicating whether the signature was valid or not.
"""
cls = self.__class__
if not isinstance(data, bytes):
raise TypeError("The data parameter must be a bytes-like object.")
if not isinstance(signature, bytes):
raise TypeError("Wrong type passed for the signature parameter.")
if len(signature) != cls.SIGNATURE_SIZE:
raise ValueError("Invalid value passed for the signature parameter.")
return cls._verify(
bytearray(data),
bytearray(signature),
cls._mont_pub_to_ed_pub(bytearray(self.__mont_pub))
) | python | def verify(self, data, signature):
"""
Verify signed data using the Montgomery public key stored by this XEdDSA instance.
:param data: A bytes-like object containing the data that was signed.
:param signature: A bytes-like object encoding the signature with length
SIGNATURE_SIZE.
:returns: A boolean indicating whether the signature was valid or not.
"""
cls = self.__class__
if not isinstance(data, bytes):
raise TypeError("The data parameter must be a bytes-like object.")
if not isinstance(signature, bytes):
raise TypeError("Wrong type passed for the signature parameter.")
if len(signature) != cls.SIGNATURE_SIZE:
raise ValueError("Invalid value passed for the signature parameter.")
return cls._verify(
bytearray(data),
bytearray(signature),
cls._mont_pub_to_ed_pub(bytearray(self.__mont_pub))
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| a11721524c96ce354cca3628e003c6fcf7ce3e42 | https://github.com/Syndace/python-xeddsa/blob/a11721524c96ce354cca3628e003c6fcf7ce3e42/xeddsa/xeddsa.py#L234-L259 | train |
ZanderBrown/nudatus | nudatus.py | mangle | def mangle(text):
"""
Takes a script and mangles it
TokenError is thrown when encountering bad syntax
"""
text_bytes = text.encode('utf-8')
# Wrap the input script as a byte stream
buff = BytesIO(text_bytes)
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mangled = BytesIO()
last_tok = token.INDENT
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last_line_text = ''
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# Build tokens from the script
tokens = tokenizer(buff.readline)
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# Reset the column
last_col = 0
# If the last line ended in a '\' (continuation)
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# Recreate it
mangled.write(b' \\\n')
# We don't want to be calling the this multiple times
striped = text.strip()
# Tokens or characters for opening or closing a list/dict
list_dict_open = [token.LSQB, token.LBRACE, '[', '{']
list_dict_close = [token.RSQB, token.RBRACE, ']', '}']
# If this is a list or dict
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open_list_dicts += 1
elif t in list_dict_close or striped in list_dict_close:
# Decrease the dict / list level
open_list_dicts -= 1
# Remove docstrings
# Docstrings are strings not used in an expression,
# unfortunatly it isn't as simple as "t is string and t
# not in expression"
if t == token.STRING and (last_tok == token.INDENT or (
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last_tok == token.DEDENT or last_tok == tokenize.ENCODING)
and open_list_dicts == 0)):
# Output number of lines corresponding those in
# the docstring comment
mangled.write(b'\n' * (len(text.split('\n')) - 1))
# Or is it a standard comment
elif t == tokenize.COMMENT:
# Plain comment, just don't write it
pass
else:
# Recreate indentation, ideally we should use tabs
if col_s > last_col:
mangled.write(b' ' * (col_s - last_col))
# On Python 3 the first token specifies the encoding
# but we already know it's utf-8 and writing it just
# gives us an invalid script
if t != tokenize.ENCODING:
mangled.write(text.encode('utf-8'))
# Store the previous state
last_tok = t
last_col = col_e
last_line = line_e
last_line_text = line
# Return a string
return mangled.getvalue().decode('utf-8') | python | def mangle(text):
"""
Takes a script and mangles it
TokenError is thrown when encountering bad syntax
"""
text_bytes = text.encode('utf-8')
# Wrap the input script as a byte stream
buff = BytesIO(text_bytes)
# Byte stream for the mangled script
mangled = BytesIO()
last_tok = token.INDENT
last_line = -1
last_col = 0
last_line_text = ''
open_list_dicts = 0
# Build tokens from the script
tokens = tokenizer(buff.readline)
for t, text, (line_s, col_s), (line_e, col_e), line in tokens:
# If this is a new line (except the very first)
if line_s > last_line and last_line != -1:
# Reset the column
last_col = 0
# If the last line ended in a '\' (continuation)
if last_line_text.rstrip()[-1:] == '\\':
# Recreate it
mangled.write(b' \\\n')
# We don't want to be calling the this multiple times
striped = text.strip()
# Tokens or characters for opening or closing a list/dict
list_dict_open = [token.LSQB, token.LBRACE, '[', '{']
list_dict_close = [token.RSQB, token.RBRACE, ']', '}']
# If this is a list or dict
if t in list_dict_open or striped in list_dict_open:
# Increase the dict / list level
open_list_dicts += 1
elif t in list_dict_close or striped in list_dict_close:
# Decrease the dict / list level
open_list_dicts -= 1
# Remove docstrings
# Docstrings are strings not used in an expression,
# unfortunatly it isn't as simple as "t is string and t
# not in expression"
if t == token.STRING and (last_tok == token.INDENT or (
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last_tok == token.DEDENT or last_tok == tokenize.ENCODING)
and open_list_dicts == 0)):
# Output number of lines corresponding those in
# the docstring comment
mangled.write(b'\n' * (len(text.split('\n')) - 1))
# Or is it a standard comment
elif t == tokenize.COMMENT:
# Plain comment, just don't write it
pass
else:
# Recreate indentation, ideally we should use tabs
if col_s > last_col:
mangled.write(b' ' * (col_s - last_col))
# On Python 3 the first token specifies the encoding
# but we already know it's utf-8 and writing it just
# gives us an invalid script
if t != tokenize.ENCODING:
mangled.write(text.encode('utf-8'))
# Store the previous state
last_tok = t
last_col = col_e
last_line = line_e
last_line_text = line
# Return a string
return mangled.getvalue().decode('utf-8') | [
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| Takes a script and mangles it
TokenError is thrown when encountering bad syntax | [
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| 29a9627b09c3498fb6f9370f6e6d1c9a876453d8 | https://github.com/ZanderBrown/nudatus/blob/29a9627b09c3498fb6f9370f6e6d1c9a876453d8/nudatus.py#L36-L115 | train |
ZanderBrown/nudatus | nudatus.py | main | def main(argv=None):
"""
Command line entry point
"""
if not argv:
argv = sys.argv[1:]
parser = argparse.ArgumentParser(description=_HELP_TEXT)
parser.add_argument('input', nargs='?', default=None)
parser.add_argument('output', nargs='?', default=None)
parser.add_argument('--version', action='version',
version='%(prog)s ' + get_version())
args = parser.parse_args(argv)
if not args.input:
print("No file specified", file=sys.stderr)
sys.exit(1)
try:
with open(args.input, 'r') as f:
res = mangle(f.read())
if not args.output:
print(res, end='')
else:
with open(args.output, 'w') as o:
o.write(res)
except Exception as ex:
print("Error mangling {}: {!s}".format(args.input, ex),
file=sys.stderr)
sys.exit(1) | python | def main(argv=None):
"""
Command line entry point
"""
if not argv:
argv = sys.argv[1:]
parser = argparse.ArgumentParser(description=_HELP_TEXT)
parser.add_argument('input', nargs='?', default=None)
parser.add_argument('output', nargs='?', default=None)
parser.add_argument('--version', action='version',
version='%(prog)s ' + get_version())
args = parser.parse_args(argv)
if not args.input:
print("No file specified", file=sys.stderr)
sys.exit(1)
try:
with open(args.input, 'r') as f:
res = mangle(f.read())
if not args.output:
print(res, end='')
else:
with open(args.output, 'w') as o:
o.write(res)
except Exception as ex:
print("Error mangling {}: {!s}".format(args.input, ex),
file=sys.stderr)
sys.exit(1) | [
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| 29a9627b09c3498fb6f9370f6e6d1c9a876453d8 | https://github.com/ZanderBrown/nudatus/blob/29a9627b09c3498fb6f9370f6e6d1c9a876453d8/nudatus.py#L127-L156 | train |
raymondEhlers/pachyderm | pachyderm/histogram.py | get_histograms_in_list | def get_histograms_in_list(filename: str, list_name: str = None) -> Dict[str, Any]:
""" Get histograms from the file and make them available in a dict.
Lists are recursively explored, with all lists converted to dictionaries, such that the return
dictionaries which only contains hists and dictionaries of hists (ie there are no ROOT ``TCollection``
derived objects).
Args:
filename: Filename of the ROOT file containing the list.
list_name: Name of the list to retrieve.
Returns:
Contains hists with keys as their names. Lists are recursively added, mirroring
the structure under which the hists were stored.
Raises:
ValueError: If the list could not be found in the given file.
"""
hists: dict = {}
with RootOpen(filename = filename, mode = "READ") as fIn:
if list_name is not None:
hist_list = fIn.Get(list_name)
else:
hist_list = [obj.ReadObj() for obj in fIn.GetListOfKeys()]
if not hist_list:
fIn.ls()
# Closing this file appears (but is not entirely confirmed) to be extremely important! Otherwise,
# the memory will leak, leading to ROOT memory issues!
fIn.Close()
raise ValueError(f"Could not find list with name \"{list_name}\". Possible names are listed above.")
# Retrieve objects in the hist list
for obj in hist_list:
_retrieve_object(hists, obj)
return hists | python | def get_histograms_in_list(filename: str, list_name: str = None) -> Dict[str, Any]:
""" Get histograms from the file and make them available in a dict.
Lists are recursively explored, with all lists converted to dictionaries, such that the return
dictionaries which only contains hists and dictionaries of hists (ie there are no ROOT ``TCollection``
derived objects).
Args:
filename: Filename of the ROOT file containing the list.
list_name: Name of the list to retrieve.
Returns:
Contains hists with keys as their names. Lists are recursively added, mirroring
the structure under which the hists were stored.
Raises:
ValueError: If the list could not be found in the given file.
"""
hists: dict = {}
with RootOpen(filename = filename, mode = "READ") as fIn:
if list_name is not None:
hist_list = fIn.Get(list_name)
else:
hist_list = [obj.ReadObj() for obj in fIn.GetListOfKeys()]
if not hist_list:
fIn.ls()
# Closing this file appears (but is not entirely confirmed) to be extremely important! Otherwise,
# the memory will leak, leading to ROOT memory issues!
fIn.Close()
raise ValueError(f"Could not find list with name \"{list_name}\". Possible names are listed above.")
# Retrieve objects in the hist list
for obj in hist_list:
_retrieve_object(hists, obj)
return hists | [
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Args:
filename: Filename of the ROOT file containing the list.
list_name: Name of the list to retrieve.
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Contains hists with keys as their names. Lists are recursively added, mirroring
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Raises:
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| aaa1d8374fd871246290ce76f1796f2f7582b01d | https://github.com/raymondEhlers/pachyderm/blob/aaa1d8374fd871246290ce76f1796f2f7582b01d/pachyderm/histogram.py#L52-L86 | train |
raymondEhlers/pachyderm | pachyderm/histogram.py | _retrieve_object | def _retrieve_object(output_dict: Dict[str, Any], obj: Any) -> None:
""" Function to recursively retrieve histograms from a list in a ROOT file.
``SetDirectory(True)`` is applied to TH1 derived hists and python is explicitly given
ownership of the retrieved objects.
Args:
output_dict (dict): Dict under which hists should be stored.
obj (ROOT.TObject derived): Object(s) to be stored. If it is a collection,
it will be recursed through.
Returns:
None: Changes in the dict are reflected in the output_dict which was passed.
"""
import ROOT
# Store TH1 or THn
if isinstance(obj, ROOT.TH1) or isinstance(obj, ROOT.THnBase):
# Ensure that it is not lost after the file is closed
# Only works for TH1
if isinstance(obj, ROOT.TH1):
obj.SetDirectory(0)
# Explicitly note that python owns the object
# From more on memory management with ROOT and python, see:
# https://root.cern.ch/root/html/guides/users-guide/PythonRuby.html#memory-handling
ROOT.SetOwnership(obj, False)
# Store the object
output_dict[obj.GetName()] = obj
# Recurse over lists
if isinstance(obj, ROOT.TCollection):
# Keeping it in order simply makes it easier to follow
output_dict[obj.GetName()] = {}
# Iterate over the objects in the collection and recursively store them
for obj_temp in list(obj):
_retrieve_object(output_dict[obj.GetName()], obj_temp) | python | def _retrieve_object(output_dict: Dict[str, Any], obj: Any) -> None:
""" Function to recursively retrieve histograms from a list in a ROOT file.
``SetDirectory(True)`` is applied to TH1 derived hists and python is explicitly given
ownership of the retrieved objects.
Args:
output_dict (dict): Dict under which hists should be stored.
obj (ROOT.TObject derived): Object(s) to be stored. If it is a collection,
it will be recursed through.
Returns:
None: Changes in the dict are reflected in the output_dict which was passed.
"""
import ROOT
# Store TH1 or THn
if isinstance(obj, ROOT.TH1) or isinstance(obj, ROOT.THnBase):
# Ensure that it is not lost after the file is closed
# Only works for TH1
if isinstance(obj, ROOT.TH1):
obj.SetDirectory(0)
# Explicitly note that python owns the object
# From more on memory management with ROOT and python, see:
# https://root.cern.ch/root/html/guides/users-guide/PythonRuby.html#memory-handling
ROOT.SetOwnership(obj, False)
# Store the object
output_dict[obj.GetName()] = obj
# Recurse over lists
if isinstance(obj, ROOT.TCollection):
# Keeping it in order simply makes it easier to follow
output_dict[obj.GetName()] = {}
# Iterate over the objects in the collection and recursively store them
for obj_temp in list(obj):
_retrieve_object(output_dict[obj.GetName()], obj_temp) | [
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| aaa1d8374fd871246290ce76f1796f2f7582b01d | https://github.com/raymondEhlers/pachyderm/blob/aaa1d8374fd871246290ce76f1796f2f7582b01d/pachyderm/histogram.py#L88-L124 | train |
raymondEhlers/pachyderm | pachyderm/histogram.py | get_array_from_hist2D | def get_array_from_hist2D(hist: Hist, set_zero_to_NaN: bool = True, return_bin_edges: bool = False) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
""" Extract x, y, and bin values from a 2D ROOT histogram.
Converts the histogram into a numpy array, and suitably processes it for a surface plot
by removing 0s (which can cause problems when taking logs), and returning a set of (x, y) mesh
values utilziing either the bin edges or bin centers.
Note:
This is a different format than the 1D version!
Args:
hist (ROOT.TH2): Histogram to be converted.
set_zero_to_NaN: If true, set 0 in the array to NaN. Useful with matplotlib so that it will
ignore the values when plotting. See comments in this function for more details. Default: True.
return_bin_edges: Return x and y using bin edges instead of bin centers.
Returns:
Contains (x values, y values, numpy array of hist data) where (x, y) are values on a
grid (from np.meshgrid) using the selected bin values.
"""
# Process the hist into a suitable state
# NOTE: The shape specific can be somewhat confusing (ie. I would naviely expected to specify the x first.)
# This says that the ``GetYaxis().GetNbins()`` number of rows and ``GetXaxis().GetNbins()`` number of columns.
shape = (hist.GetYaxis().GetNbins(), hist.GetXaxis().GetNbins())
# To keep consistency with the root_numpy 2D hist format, we transpose the final result
# This format has x values as columns.
hist_array = np.array([hist.GetBinContent(x) for x in range(1, hist.GetNcells()) if not hist.IsBinUnderflow(x) and not hist.IsBinOverflow(x)])
# The hist_array was linear, so we need to shape it into our expected 2D values.
hist_array = hist_array.reshape(shape)
# Transpose the array to better match expectations
# In particular, by transposing the array, it means that ``thist_array[1][0]`` gives the 2nd x
# value (x_index = 1) and the 1st y value (y_index = 1). This is as we would expect. This is also
# the same convention as used by root_numpy
hist_array = hist_array.T
# Set all 0s to nan to get similar behavior to ROOT. In ROOT, it will basically ignore 0s. This is
# especially important for log plots. Matplotlib doesn't handle 0s as well, since it attempts to
# plot them and then will throw exceptions when the log is taken.
# By setting to nan, matplotlib basically ignores them similar to ROOT
# NOTE: This requires a few special functions later which ignore nan when calculating min and max.
if set_zero_to_NaN:
hist_array[hist_array == 0] = np.nan
if return_bin_edges:
# Bin edges
x_bin_edges = get_bin_edges_from_axis(hist.GetXaxis())
y_bin_edges = get_bin_edges_from_axis(hist.GetYaxis())
# NOTE: The addition of epsilon to the max is extremely important! Otherwise, the x and y
# ranges will be one bin short since ``arange`` is not inclusive. This could also be resolved
# by using ``linspace``, but I think this approach is perfectly fine.
# NOTE: This epsilon is smaller than the one in ``utils`` because we are sometimes dealing
# with small times (~ns). The other value is larger because (I seem to recall) that
# smaller values didn't always place nice with ROOT, but it is fine here, since we're
# working with numpy.
# NOTE: This should be identical to taking the min and max of the axis using
# ``TAxis.GetXmin()`` and ``TAxis.GetXmax()``, but I prefer this approach.
epsilon = 1e-9
x_range = np.arange(
np.amin(x_bin_edges),
np.amax(x_bin_edges) + epsilon,
hist.GetXaxis().GetBinWidth(1)
)
y_range = np.arange(
np.amin(y_bin_edges),
np.amax(y_bin_edges) + epsilon,
hist.GetYaxis().GetBinWidth(1)
)
else:
# We want an array of bin centers
x_range = np.array([hist.GetXaxis().GetBinCenter(i) for i in range(1, hist.GetXaxis().GetNbins() + 1)])
y_range = np.array([hist.GetYaxis().GetBinCenter(i) for i in range(1, hist.GetYaxis().GetNbins() + 1)])
X, Y = np.meshgrid(x_range, y_range)
return (X, Y, hist_array) | python | def get_array_from_hist2D(hist: Hist, set_zero_to_NaN: bool = True, return_bin_edges: bool = False) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
""" Extract x, y, and bin values from a 2D ROOT histogram.
Converts the histogram into a numpy array, and suitably processes it for a surface plot
by removing 0s (which can cause problems when taking logs), and returning a set of (x, y) mesh
values utilziing either the bin edges or bin centers.
Note:
This is a different format than the 1D version!
Args:
hist (ROOT.TH2): Histogram to be converted.
set_zero_to_NaN: If true, set 0 in the array to NaN. Useful with matplotlib so that it will
ignore the values when plotting. See comments in this function for more details. Default: True.
return_bin_edges: Return x and y using bin edges instead of bin centers.
Returns:
Contains (x values, y values, numpy array of hist data) where (x, y) are values on a
grid (from np.meshgrid) using the selected bin values.
"""
# Process the hist into a suitable state
# NOTE: The shape specific can be somewhat confusing (ie. I would naviely expected to specify the x first.)
# This says that the ``GetYaxis().GetNbins()`` number of rows and ``GetXaxis().GetNbins()`` number of columns.
shape = (hist.GetYaxis().GetNbins(), hist.GetXaxis().GetNbins())
# To keep consistency with the root_numpy 2D hist format, we transpose the final result
# This format has x values as columns.
hist_array = np.array([hist.GetBinContent(x) for x in range(1, hist.GetNcells()) if not hist.IsBinUnderflow(x) and not hist.IsBinOverflow(x)])
# The hist_array was linear, so we need to shape it into our expected 2D values.
hist_array = hist_array.reshape(shape)
# Transpose the array to better match expectations
# In particular, by transposing the array, it means that ``thist_array[1][0]`` gives the 2nd x
# value (x_index = 1) and the 1st y value (y_index = 1). This is as we would expect. This is also
# the same convention as used by root_numpy
hist_array = hist_array.T
# Set all 0s to nan to get similar behavior to ROOT. In ROOT, it will basically ignore 0s. This is
# especially important for log plots. Matplotlib doesn't handle 0s as well, since it attempts to
# plot them and then will throw exceptions when the log is taken.
# By setting to nan, matplotlib basically ignores them similar to ROOT
# NOTE: This requires a few special functions later which ignore nan when calculating min and max.
if set_zero_to_NaN:
hist_array[hist_array == 0] = np.nan
if return_bin_edges:
# Bin edges
x_bin_edges = get_bin_edges_from_axis(hist.GetXaxis())
y_bin_edges = get_bin_edges_from_axis(hist.GetYaxis())
# NOTE: The addition of epsilon to the max is extremely important! Otherwise, the x and y
# ranges will be one bin short since ``arange`` is not inclusive. This could also be resolved
# by using ``linspace``, but I think this approach is perfectly fine.
# NOTE: This epsilon is smaller than the one in ``utils`` because we are sometimes dealing
# with small times (~ns). The other value is larger because (I seem to recall) that
# smaller values didn't always place nice with ROOT, but it is fine here, since we're
# working with numpy.
# NOTE: This should be identical to taking the min and max of the axis using
# ``TAxis.GetXmin()`` and ``TAxis.GetXmax()``, but I prefer this approach.
epsilon = 1e-9
x_range = np.arange(
np.amin(x_bin_edges),
np.amax(x_bin_edges) + epsilon,
hist.GetXaxis().GetBinWidth(1)
)
y_range = np.arange(
np.amin(y_bin_edges),
np.amax(y_bin_edges) + epsilon,
hist.GetYaxis().GetBinWidth(1)
)
else:
# We want an array of bin centers
x_range = np.array([hist.GetXaxis().GetBinCenter(i) for i in range(1, hist.GetXaxis().GetNbins() + 1)])
y_range = np.array([hist.GetYaxis().GetBinCenter(i) for i in range(1, hist.GetYaxis().GetNbins() + 1)])
X, Y = np.meshgrid(x_range, y_range)
return (X, Y, hist_array) | [
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| Extract x, y, and bin values from a 2D ROOT histogram.
Converts the histogram into a numpy array, and suitably processes it for a surface plot
by removing 0s (which can cause problems when taking logs), and returning a set of (x, y) mesh
values utilziing either the bin edges or bin centers.
Note:
This is a different format than the 1D version!
Args:
hist (ROOT.TH2): Histogram to be converted.
set_zero_to_NaN: If true, set 0 in the array to NaN. Useful with matplotlib so that it will
ignore the values when plotting. See comments in this function for more details. Default: True.
return_bin_edges: Return x and y using bin edges instead of bin centers.
Returns:
Contains (x values, y values, numpy array of hist data) where (x, y) are values on a
grid (from np.meshgrid) using the selected bin values. | [
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| aaa1d8374fd871246290ce76f1796f2f7582b01d | https://github.com/raymondEhlers/pachyderm/blob/aaa1d8374fd871246290ce76f1796f2f7582b01d/pachyderm/histogram.py#L527-L600 | train |
raymondEhlers/pachyderm | pachyderm/histogram.py | get_bin_edges_from_axis | def get_bin_edges_from_axis(axis) -> np.ndarray:
""" Get bin edges from a ROOT hist axis.
Note:
Doesn't include over- or underflow bins!
Args:
axis (ROOT.TAxis): Axis from which the bin edges should be extracted.
Returns:
Array containing the bin edges.
"""
# Don't include over- or underflow bins
bins = range(1, axis.GetNbins() + 1)
# Bin edges
bin_edges = np.empty(len(bins) + 1)
bin_edges[:-1] = [axis.GetBinLowEdge(i) for i in bins]
bin_edges[-1] = axis.GetBinUpEdge(axis.GetNbins())
return bin_edges | python | def get_bin_edges_from_axis(axis) -> np.ndarray:
""" Get bin edges from a ROOT hist axis.
Note:
Doesn't include over- or underflow bins!
Args:
axis (ROOT.TAxis): Axis from which the bin edges should be extracted.
Returns:
Array containing the bin edges.
"""
# Don't include over- or underflow bins
bins = range(1, axis.GetNbins() + 1)
# Bin edges
bin_edges = np.empty(len(bins) + 1)
bin_edges[:-1] = [axis.GetBinLowEdge(i) for i in bins]
bin_edges[-1] = axis.GetBinUpEdge(axis.GetNbins())
return bin_edges | [
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| aaa1d8374fd871246290ce76f1796f2f7582b01d | https://github.com/raymondEhlers/pachyderm/blob/aaa1d8374fd871246290ce76f1796f2f7582b01d/pachyderm/histogram.py#L602-L620 | train |
lowandrew/OLCTools | spadespipeline/sistr.py | Sistr.sistr | def sistr(self):
"""Perform sistr analyses on Salmonella"""
logging.info('Performing sistr analyses')
with progressbar(self.metadata) as bar:
for sample in bar:
# Create the analysis-type specific attribute
setattr(sample, self.analysistype, GenObject())
if sample.general.bestassemblyfile != 'NA':
try:
# Only process strains that have been determined to be Salmonella
if sample.general.referencegenus == 'Salmonella':
# Set and create the path of the directory to store the strain-specific reports
sample[self.analysistype].reportdir = os.path.join(sample.general.outputdirectory,
self.analysistype)
# Name of the .json output file
sample[self.analysistype].jsonoutput = os.path.join(sample[self.analysistype].reportdir,
'{}.json'.format(sample.name))
# Set the sistr system call
sample.commands.sistr = \
'sistr -f json -o {} -t {} -T {} {}'\
.format(sample[self.analysistype].jsonoutput,
self.cpus,
os.path.join(sample[self.analysistype].reportdir, 'tmp'),
sample.general.bestassemblyfile)
#
sample[self.analysistype].logout = os.path.join(sample[self.analysistype].reportdir, 'logout')
sample[self.analysistype].logerr = os.path.join(sample[self.analysistype].reportdir, 'logerr')
# Only run the analyses if the output json file does not exist
if not os.path.isfile(sample[self.analysistype].jsonoutput):
out, err = run_subprocess(sample.commands.sistr)
write_to_logfile(sample.commands.sistr, sample.commands.sistr, self.logfile,
sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
write_to_logfile(out, err, self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
self.queue.task_done()
except (ValueError, KeyError):
pass
self.queue.join()
self.report() | python | def sistr(self):
"""Perform sistr analyses on Salmonella"""
logging.info('Performing sistr analyses')
with progressbar(self.metadata) as bar:
for sample in bar:
# Create the analysis-type specific attribute
setattr(sample, self.analysistype, GenObject())
if sample.general.bestassemblyfile != 'NA':
try:
# Only process strains that have been determined to be Salmonella
if sample.general.referencegenus == 'Salmonella':
# Set and create the path of the directory to store the strain-specific reports
sample[self.analysistype].reportdir = os.path.join(sample.general.outputdirectory,
self.analysistype)
# Name of the .json output file
sample[self.analysistype].jsonoutput = os.path.join(sample[self.analysistype].reportdir,
'{}.json'.format(sample.name))
# Set the sistr system call
sample.commands.sistr = \
'sistr -f json -o {} -t {} -T {} {}'\
.format(sample[self.analysistype].jsonoutput,
self.cpus,
os.path.join(sample[self.analysistype].reportdir, 'tmp'),
sample.general.bestassemblyfile)
#
sample[self.analysistype].logout = os.path.join(sample[self.analysistype].reportdir, 'logout')
sample[self.analysistype].logerr = os.path.join(sample[self.analysistype].reportdir, 'logerr')
# Only run the analyses if the output json file does not exist
if not os.path.isfile(sample[self.analysistype].jsonoutput):
out, err = run_subprocess(sample.commands.sistr)
write_to_logfile(sample.commands.sistr, sample.commands.sistr, self.logfile,
sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
write_to_logfile(out, err, self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
self.queue.task_done()
except (ValueError, KeyError):
pass
self.queue.join()
self.report() | [
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| Perform sistr analyses on Salmonella | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/spadespipeline/sistr.py#L18-L57 | train |
lowandrew/OLCTools | spadespipeline/sistr.py | Sistr.report | def report(self):
"""Creates sistr reports"""
# Initialise strings to store report data
header = '\t'.join(self.headers) + '\n'
data = ''
for sample in self.metadata:
if sample.general.bestassemblyfile != 'NA':
# Each strain is a fresh row
row = ''
try:
# Read in the output .json file into the metadata
sample[self.analysistype].jsondata = json.load(open(sample[self.analysistype].jsonoutput, 'r'))
# Set the name of the report.
# Note that this is a tab-separated file, as there can be commas in the results
sample[self.analysistype].report = os.path.join(sample[self.analysistype].reportdir,
'{}.tsv'.format(sample.name))
# Iterate through all the headers to use as keys in the json-formatted output
for category in self.headers:
# Tab separate all the results
row += '{}\t'.format(sample[self.analysistype].jsondata[0][category])
# Create attributes for each category
setattr(sample[self.analysistype], category,
str(sample[self.analysistype].jsondata[0][category]))
# End the results with a newline
row += '\n'
data += row
# Create and write headers and results to the strain-specific report
with open(sample[self.analysistype].report, 'w') as strainreport:
strainreport.write(header)
strainreport.write(row)
except (KeyError, AttributeError):
pass
# Create and write headers and cumulative results to the combined report
with open(os.path.join(self.reportdir, 'sistr.tsv'), 'w') as report:
report.write(header)
report.write(data) | python | def report(self):
"""Creates sistr reports"""
# Initialise strings to store report data
header = '\t'.join(self.headers) + '\n'
data = ''
for sample in self.metadata:
if sample.general.bestassemblyfile != 'NA':
# Each strain is a fresh row
row = ''
try:
# Read in the output .json file into the metadata
sample[self.analysistype].jsondata = json.load(open(sample[self.analysistype].jsonoutput, 'r'))
# Set the name of the report.
# Note that this is a tab-separated file, as there can be commas in the results
sample[self.analysistype].report = os.path.join(sample[self.analysistype].reportdir,
'{}.tsv'.format(sample.name))
# Iterate through all the headers to use as keys in the json-formatted output
for category in self.headers:
# Tab separate all the results
row += '{}\t'.format(sample[self.analysistype].jsondata[0][category])
# Create attributes for each category
setattr(sample[self.analysistype], category,
str(sample[self.analysistype].jsondata[0][category]))
# End the results with a newline
row += '\n'
data += row
# Create and write headers and results to the strain-specific report
with open(sample[self.analysistype].report, 'w') as strainreport:
strainreport.write(header)
strainreport.write(row)
except (KeyError, AttributeError):
pass
# Create and write headers and cumulative results to the combined report
with open(os.path.join(self.reportdir, 'sistr.tsv'), 'w') as report:
report.write(header)
report.write(data) | [
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| Creates sistr reports | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/spadespipeline/sistr.py#L59-L95 | train |
portfors-lab/sparkle | sparkle/gui/stim/abstract_editor.py | AbstractEditorWidget.purgeDeletedWidgets | def purgeDeletedWidgets():
"""Finds old references to stashed fields and deletes them"""
toremove = []
for field in AbstractEditorWidget.funit_fields:
if sip.isdeleted(field):
toremove.append(field)
for field in toremove:
AbstractEditorWidget.funit_fields.remove(field)
toremove = []
for field in AbstractEditorWidget.tunit_fields:
if sip.isdeleted(field):
toremove.append(field)
for field in toremove:
AbstractEditorWidget.tunit_fields.remove(field) | python | def purgeDeletedWidgets():
"""Finds old references to stashed fields and deletes them"""
toremove = []
for field in AbstractEditorWidget.funit_fields:
if sip.isdeleted(field):
toremove.append(field)
for field in toremove:
AbstractEditorWidget.funit_fields.remove(field)
toremove = []
for field in AbstractEditorWidget.tunit_fields:
if sip.isdeleted(field):
toremove.append(field)
for field in toremove:
AbstractEditorWidget.tunit_fields.remove(field) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/gui/stim/abstract_editor.py#L22-L36 | train |
lowandrew/OLCTools | spadespipeline/fastqmover.py | FastqMover.movefastq | def movefastq(self):
"""Find .fastq files for each sample and move them to an appropriately named folder"""
logging.info('Moving FASTQ files')
# Iterate through each sample
for sample in self.metadata.runmetadata.samples:
# Retrieve the output directory
outputdir = os.path.join(self.path, sample.name)
# Find any fastq files with the sample name
fastqfiles = sorted(glob(os.path.join(self.path, '{}_*.fastq*'.format(sample.name)))) \
if sorted(glob(os.path.join(self.path, '{}_*.fastq*'.format(sample.name)))) \
else sorted(glob(os.path.join(self.path, '{}.fastq*'.format(sample.name)))) \
if sorted(glob(os.path.join(self.path, '{}.fastq*'.format(sample.name)))) \
else sorted(glob(os.path.join(self.path, '{}*.fastq*'.format(sample.name))))
# Only try and move the files if the files exist
if fastqfiles:
make_path(outputdir)
# Symlink the fastq files to the directory
try:
list(map(lambda x: os.symlink(os.path.join('..', os.path.basename(x)),
os.path.join(outputdir, os.path.basename(x))), fastqfiles))
except OSError:
pass
# Find any fastq files with the sample name
fastqfiles = [fastq for fastq in sorted(glob(os.path.join(outputdir, '{}*.fastq*'.format(sample.name))))
if 'trimmed' not in fastq and 'normalised' not in fastq and 'corrected' not in fastq
and 'paired' not in fastq and 'unpaired' not in fastq]
else:
if outputdir:
# Find any fastq files with the sample name
fastqfiles = [fastq for fastq in sorted(glob(os.path.join(
outputdir, '{}*.fastq*'.format(outputdir, sample.name))))
if 'trimmed' not in fastq and 'normalised' not in fastq and 'corrected' not in fastq
and 'paired' not in fastq and 'unpaired' not in fastq]
sample.general.fastqfiles = fastqfiles | python | def movefastq(self):
"""Find .fastq files for each sample and move them to an appropriately named folder"""
logging.info('Moving FASTQ files')
# Iterate through each sample
for sample in self.metadata.runmetadata.samples:
# Retrieve the output directory
outputdir = os.path.join(self.path, sample.name)
# Find any fastq files with the sample name
fastqfiles = sorted(glob(os.path.join(self.path, '{}_*.fastq*'.format(sample.name)))) \
if sorted(glob(os.path.join(self.path, '{}_*.fastq*'.format(sample.name)))) \
else sorted(glob(os.path.join(self.path, '{}.fastq*'.format(sample.name)))) \
if sorted(glob(os.path.join(self.path, '{}.fastq*'.format(sample.name)))) \
else sorted(glob(os.path.join(self.path, '{}*.fastq*'.format(sample.name))))
# Only try and move the files if the files exist
if fastqfiles:
make_path(outputdir)
# Symlink the fastq files to the directory
try:
list(map(lambda x: os.symlink(os.path.join('..', os.path.basename(x)),
os.path.join(outputdir, os.path.basename(x))), fastqfiles))
except OSError:
pass
# Find any fastq files with the sample name
fastqfiles = [fastq for fastq in sorted(glob(os.path.join(outputdir, '{}*.fastq*'.format(sample.name))))
if 'trimmed' not in fastq and 'normalised' not in fastq and 'corrected' not in fastq
and 'paired' not in fastq and 'unpaired' not in fastq]
else:
if outputdir:
# Find any fastq files with the sample name
fastqfiles = [fastq for fastq in sorted(glob(os.path.join(
outputdir, '{}*.fastq*'.format(outputdir, sample.name))))
if 'trimmed' not in fastq and 'normalised' not in fastq and 'corrected' not in fastq
and 'paired' not in fastq and 'unpaired' not in fastq]
sample.general.fastqfiles = fastqfiles | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/spadespipeline/fastqmover.py#L11-L44 | train |
oracal/cineworld | cineworld/cineworld.py | CW.get_list | def get_list(self, datatype, url, **kwargs):
"""base function for connecting to API"""
search_url = [url, '?']
kwargs.update({'key': self.api_key})
search_url.append(urlencode(kwargs))
data = json.loads(urlopen(''.join(search_url)).read())
return data[datatype] | python | def get_list(self, datatype, url, **kwargs):
"""base function for connecting to API"""
search_url = [url, '?']
kwargs.update({'key': self.api_key})
search_url.append(urlencode(kwargs))
data = json.loads(urlopen(''.join(search_url)).read())
return data[datatype] | [
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| 073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5 | https://github.com/oracal/cineworld/blob/073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5/cineworld/cineworld.py#L40-L46 | train |
oracal/cineworld | cineworld/cineworld.py | CW.film_search | def film_search(self, title):
"""film search using fuzzy matching"""
films = []
#check for cache or update
if not hasattr(self, 'film_list'):
self.get_film_list()
#iterate over films and check for fuzzy string match
for film in self.film_list:
strength = WRatio(title, film['title'])
if strength > 80:
film.update({u'strength':strength})
films.append(film)
#sort films by the strength of the fuzzy string match
films_sorted = sorted(films, key=itemgetter('strength'), reverse = True)
return films_sorted | python | def film_search(self, title):
"""film search using fuzzy matching"""
films = []
#check for cache or update
if not hasattr(self, 'film_list'):
self.get_film_list()
#iterate over films and check for fuzzy string match
for film in self.film_list:
strength = WRatio(title, film['title'])
if strength > 80:
film.update({u'strength':strength})
films.append(film)
#sort films by the strength of the fuzzy string match
films_sorted = sorted(films, key=itemgetter('strength'), reverse = True)
return films_sorted | [
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| 073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5 | https://github.com/oracal/cineworld/blob/073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5/cineworld/cineworld.py#L81-L95 | train |
oracal/cineworld | cineworld/cineworld.py | CW.get_film_id | def get_film_id(self, title, three_dimensional=False):
"""get the film id using the title in conjunction with the searching function"""
films = self.film_search(title)
for film in films:
if (film['title'].find('3D') is - 1) is not three_dimensional:
return film['edi']
return -1 | python | def get_film_id(self, title, three_dimensional=False):
"""get the film id using the title in conjunction with the searching function"""
films = self.film_search(title)
for film in films:
if (film['title'].find('3D') is - 1) is not three_dimensional:
return film['edi']
return -1 | [
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| 073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5 | https://github.com/oracal/cineworld/blob/073b18ce4f3acf4c44b26a5af1cc0d3c71b8b5d5/cineworld/cineworld.py#L97-L103 | train |
portfors-lab/sparkle | sparkle/run/search_runner.py | SearchRunner.set_current_stim_parameter | def set_current_stim_parameter(self, param, val):
"""Sets a parameter on the current stimulus
:param param: name of the parameter of the stimulus to set
:type param: str
:param val: new value to set the parameter to
"""
component = self._stimulus.component(0,1)
component.set(param, val) | python | def set_current_stim_parameter(self, param, val):
"""Sets a parameter on the current stimulus
:param param: name of the parameter of the stimulus to set
:type param: str
:param val: new value to set the parameter to
"""
component = self._stimulus.component(0,1)
component.set(param, val) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/search_runner.py#L74-L82 | train |
portfors-lab/sparkle | sparkle/run/search_runner.py | SearchRunner.save_to_file | def save_to_file(self, data, stamp):
"""Saves data to current dataset.
:param data: data to save to file
:type data: numpy.ndarray
:param stamp: time stamp of when the data was acquired
:type stamp: str
"""
self.datafile.append(self.current_dataset_name, data)
# save stimulu info
info = dict(self._stimulus.componentDoc().items() + self._stimulus.testDoc().items())
print 'saving doc', info
info['time_stamps'] = [stamp]
info['samplerate_ad'] = self.player.aifs
self.datafile.append_trace_info(self.current_dataset_name, info) | python | def save_to_file(self, data, stamp):
"""Saves data to current dataset.
:param data: data to save to file
:type data: numpy.ndarray
:param stamp: time stamp of when the data was acquired
:type stamp: str
"""
self.datafile.append(self.current_dataset_name, data)
# save stimulu info
info = dict(self._stimulus.componentDoc().items() + self._stimulus.testDoc().items())
print 'saving doc', info
info['time_stamps'] = [stamp]
info['samplerate_ad'] = self.player.aifs
self.datafile.append_trace_info(self.current_dataset_name, info) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/search_runner.py#L181-L195 | train |
lsst-sqre/sqre-codekit | codekit/progressbar.py | countdown_timer | def countdown_timer(seconds=10):
"""Show a simple countdown progress bar
Parameters
----------
seconds
Period of time the progress bar takes to reach zero.
"""
tick = 0.1 # seconds
n_ticks = int(seconds / tick)
widgets = ['Pause for panic: ', progressbar.ETA(), ' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(
widgets=widgets, max_value=n_ticks
).start()
for i in range(n_ticks):
pbar.update(i)
sleep(tick)
pbar.finish() | python | def countdown_timer(seconds=10):
"""Show a simple countdown progress bar
Parameters
----------
seconds
Period of time the progress bar takes to reach zero.
"""
tick = 0.1 # seconds
n_ticks = int(seconds / tick)
widgets = ['Pause for panic: ', progressbar.ETA(), ' ', progressbar.Bar()]
pbar = progressbar.ProgressBar(
widgets=widgets, max_value=n_ticks
).start()
for i in range(n_ticks):
pbar.update(i)
sleep(tick)
pbar.finish() | [
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| 98122404cd9065d4d1d570867fe518042669126c | https://github.com/lsst-sqre/sqre-codekit/blob/98122404cd9065d4d1d570867fe518042669126c/codekit/progressbar.py#L19-L40 | train |
sirfoga/pyhal | hal/files/save_as.py | FileSaver.write_dicts_to_csv | def write_dicts_to_csv(self, dicts):
"""Saves .csv file with posts data
:param dicts: Dictionaries with same values
"""
csv_headers = sorted(dicts[0].keys())
with open(self.path, "w") as out_file: # write to file
dict_writer = csv.DictWriter(
out_file, csv_headers, delimiter=",", quotechar="\""
)
dict_writer.writeheader()
dict_writer.writerows(dicts) | python | def write_dicts_to_csv(self, dicts):
"""Saves .csv file with posts data
:param dicts: Dictionaries with same values
"""
csv_headers = sorted(dicts[0].keys())
with open(self.path, "w") as out_file: # write to file
dict_writer = csv.DictWriter(
out_file, csv_headers, delimiter=",", quotechar="\""
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dict_writer.writeheader()
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/files/save_as.py#L18-L29 | train |
sirfoga/pyhal | hal/files/save_as.py | FileSaver.write_matrix_to_csv | def write_matrix_to_csv(self, headers, data):
"""Saves .csv file with data
:param headers: column names
:param data: Data
"""
with open(self.path, "w") as out_file: # write to file
data_writer = csv.writer(out_file, delimiter=",")
data_writer.writerow(headers) # write headers
data_writer.writerows(data) | python | def write_matrix_to_csv(self, headers, data):
"""Saves .csv file with data
:param headers: column names
:param data: Data
"""
with open(self.path, "w") as out_file: # write to file
data_writer = csv.writer(out_file, delimiter=",")
data_writer.writerow(headers) # write headers
data_writer.writerows(data) | [
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/files/save_as.py#L31-L40 | train |
sirfoga/pyhal | hal/files/save_as.py | FileSaver.write_dicts_to_json | def write_dicts_to_json(self, data):
"""Saves .json file with data
:param data: Data
"""
with open(self.path, "w") as out:
json.dump(
data, # data
out, # file handler
indent=4, sort_keys=True # pretty print
) | python | def write_dicts_to_json(self, data):
"""Saves .json file with data
:param data: Data
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with open(self.path, "w") as out:
json.dump(
data, # data
out, # file handler
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/files/save_as.py#L42-L52 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.start_listening | def start_listening(self):
"""Start listener threads for acquistion callback queues"""
self._qlisten()
self._halt_threads = False
for t in self.queue_threads:
t.start() | python | def start_listening(self):
"""Start listener threads for acquistion callback queues"""
self._qlisten()
self._halt_threads = False
for t in self.queue_threads:
t.start() | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L87-L92 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.stop_listening | def stop_listening(self):
"""Stop listener threads for acquistion queues"""
self._halt_threads = True
# wake them up so that they can die
for name, queue_waker in self.recieved_signals.items():
q, wake_event = queue_waker
wake_event.set() | python | def stop_listening(self):
"""Stop listener threads for acquistion queues"""
self._halt_threads = True
# wake them up so that they can die
for name, queue_waker in self.recieved_signals.items():
q, wake_event = queue_waker
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L94-L100 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_queue_callback | def set_queue_callback(self, name, func):
"""Sets a function to execute when the named acquistion queue
has data placed in it.
:param name: name of the queue to pull data from
:type name: str
:param func: function reference to execute, expects queue contents as argument(s)
:type func: callable
"""
if name in self.acquisition_hooks:
self.acquisition_hooks[name].append(func)
else:
self.acquisition_hooks[name] = [func] | python | def set_queue_callback(self, name, func):
"""Sets a function to execute when the named acquistion queue
has data placed in it.
:param name: name of the queue to pull data from
:type name: str
:param func: function reference to execute, expects queue contents as argument(s)
:type func: callable
"""
if name in self.acquisition_hooks:
self.acquisition_hooks[name].append(func)
else:
self.acquisition_hooks[name] = [func] | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L102-L114 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_calibration | def set_calibration(self, datakey, calf=None, frange=None):
"""Sets a calibration for all of the acquisition operations,
from an already gathered calibration data set.
:param datakey: name of the calibration to set. This key must be present in the current data file. A value of ``None`` clears calibration.
:type datakey: str
:param calf: Calibration frequency for the attenuation vector to be in relation to. All other frequencies will be in attenutaion from this frequency.
:type calf: int
:param frange: Frequency range, low and high, for which to restrict the calibration to
:type frange: (int, int)
"""
if datakey is None:
calibration_vector, calibration_freqs = None, None
else:
if calf is None:
raise Exception('calibration reference frequency must be specified')
try:
cal = self.datafile.get_calibration(datakey, calf)
except:
print "Error: unable to load calibration data from: ", datakey
raise
calibration_vector, calibration_freqs = cal
# clear one cache -- affects all StimulusModels
StimulusModel.clearCache()
logger = logging.getLogger('main')
logger.debug('clearing cache')
logger.debug('setting explore calibration')
self.explorer.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting protocol calibration')
self.protocoler.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting chart calibration')
self.charter.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting calibrator calibration')
self.bs_calibrator.stash_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting tone calibrator calibration')
self.tone_calibrator.stash_calibration(calibration_vector, calibration_freqs, frange, datakey) | python | def set_calibration(self, datakey, calf=None, frange=None):
"""Sets a calibration for all of the acquisition operations,
from an already gathered calibration data set.
:param datakey: name of the calibration to set. This key must be present in the current data file. A value of ``None`` clears calibration.
:type datakey: str
:param calf: Calibration frequency for the attenuation vector to be in relation to. All other frequencies will be in attenutaion from this frequency.
:type calf: int
:param frange: Frequency range, low and high, for which to restrict the calibration to
:type frange: (int, int)
"""
if datakey is None:
calibration_vector, calibration_freqs = None, None
else:
if calf is None:
raise Exception('calibration reference frequency must be specified')
try:
cal = self.datafile.get_calibration(datakey, calf)
except:
print "Error: unable to load calibration data from: ", datakey
raise
calibration_vector, calibration_freqs = cal
# clear one cache -- affects all StimulusModels
StimulusModel.clearCache()
logger = logging.getLogger('main')
logger.debug('clearing cache')
logger.debug('setting explore calibration')
self.explorer.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting protocol calibration')
self.protocoler.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting chart calibration')
self.charter.set_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting calibrator calibration')
self.bs_calibrator.stash_calibration(calibration_vector, calibration_freqs, frange, datakey)
logger.debug('setting tone calibrator calibration')
self.tone_calibrator.stash_calibration(calibration_vector, calibration_freqs, frange, datakey) | [
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:type datakey: str
:param calf: Calibration frequency for the attenuation vector to be in relation to. All other frequencies will be in attenutaion from this frequency.
:type calf: int
:param frange: Frequency range, low and high, for which to restrict the calibration to
:type frange: (int, int) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L127-L162 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_calibration_duration | def set_calibration_duration(self, dur):
"""Sets the stimulus duration for the calibration stimulus. Sets for calibration chirp, test tone, and calibration curve tones
:param dur: Duration (seconds) of output signal
:type dur: float
"""
self.bs_calibrator.set_duration(dur)
self.tone_calibrator.set_duration(dur) | python | def set_calibration_duration(self, dur):
"""Sets the stimulus duration for the calibration stimulus. Sets for calibration chirp, test tone, and calibration curve tones
:param dur: Duration (seconds) of output signal
:type dur: float
"""
self.bs_calibrator.set_duration(dur)
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L171-L178 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_calibration_reps | def set_calibration_reps(self, reps):
"""Sets the number of repetitions for calibration stimuli
:param reps: Number of times a unique stimulus is presented in calibration operations
:type reps: int
"""
self.bs_calibrator.set_reps(reps)
self.tone_calibrator.set_reps(reps) | python | def set_calibration_reps(self, reps):
"""Sets the number of repetitions for calibration stimuli
:param reps: Number of times a unique stimulus is presented in calibration operations
:type reps: int
"""
self.bs_calibrator.set_reps(reps)
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L180-L187 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.load_data_file | def load_data_file(self, fname, filemode='a'):
"""Opens an existing data file to append to
:param fname: File path of the location for the data file to open
:type fname: str
"""
self.close_data()
self.datafile = open_acqdata(fname, filemode=filemode)
self.explorer.set(datafile=self.datafile)
self.protocoler.set(datafile=self.datafile)
self.charter.set(datafile=self.datafile)
self.bs_calibrator.set(datafile=self.datafile)
self.tone_calibrator.set(datafile=self.datafile)
self.set_calibration(None)
self.current_cellid = dict(self.datafile.get_info('')).get('total cells', 0) | python | def load_data_file(self, fname, filemode='a'):
"""Opens an existing data file to append to
:param fname: File path of the location for the data file to open
:type fname: str
"""
self.close_data()
self.datafile = open_acqdata(fname, filemode=filemode)
self.explorer.set(datafile=self.datafile)
self.protocoler.set(datafile=self.datafile)
self.charter.set(datafile=self.datafile)
self.bs_calibrator.set(datafile=self.datafile)
self.tone_calibrator.set(datafile=self.datafile)
self.set_calibration(None)
self.current_cellid = dict(self.datafile.get_info('')).get('total cells', 0) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L189-L205 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_threshold | def set_threshold(self, threshold):
"""Sets spike detection threshold
:param threshold: electrical potential to determine spikes (V)
:type threshold: float
"""
self.explorer.set_threshold(threshold)
self.protocoler.set_threshold(threshold) | python | def set_threshold(self, threshold):
"""Sets spike detection threshold
:param threshold: electrical potential to determine spikes (V)
:type threshold: float
"""
self.explorer.set_threshold(threshold)
self.protocoler.set_threshold(threshold) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L214-L221 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set | def set(self, **kwargs):
"""Sets acquisition parameters for all acquisition types
See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.set>`
"""
self.explorer.set(**kwargs)
self.protocoler.set(**kwargs)
self.tone_calibrator.set(**kwargs)
self.charter.set(**kwargs)
self.bs_calibrator.set(**kwargs)
self.mphone_calibrator.set(**kwargs) | python | def set(self, **kwargs):
"""Sets acquisition parameters for all acquisition types
See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.set>`
"""
self.explorer.set(**kwargs)
self.protocoler.set(**kwargs)
self.tone_calibrator.set(**kwargs)
self.charter.set(**kwargs)
self.bs_calibrator.set(**kwargs)
self.mphone_calibrator.set(**kwargs) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L223-L233 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.set_mphone_calibration | def set_mphone_calibration(self, sens, db):
"""Sets the microphone calibration, for the purpose of calculating recorded dB levels
:param sens: microphone sensitivity (V)
:type sens: float
:param db: dB SPL that the calibration was measured at
:type db: int
"""
self.bs_calibrator.set_mphone_calibration(sens, db)
self.tone_calibrator.set_mphone_calibration(sens, db) | python | def set_mphone_calibration(self, sens, db):
"""Sets the microphone calibration, for the purpose of calculating recorded dB levels
:param sens: microphone sensitivity (V)
:type sens: float
:param db: dB SPL that the calibration was measured at
:type db: int
"""
self.bs_calibrator.set_mphone_calibration(sens, db)
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L276-L285 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.run_chart_protocol | def run_chart_protocol(self, interval):
"""Runs the stimuli presentation during a chart acquisition
:param interval: The repetition interval between stimuli presentations (seconds)
:type interval: float
:returns: :py:class:`threading.Thread` -- the acquisition thread
"""
self.charter.setup(interval)
return self.charter.run() | python | def run_chart_protocol(self, interval):
"""Runs the stimuli presentation during a chart acquisition
:param interval: The repetition interval between stimuli presentations (seconds)
:type interval: float
:returns: :py:class:`threading.Thread` -- the acquisition thread
"""
self.charter.setup(interval)
return self.charter.run() | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L332-L340 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.process_calibration | def process_calibration(self, save=True, calf=20000):
"""Processes a completed calibration
:param save: Wether to save this calibration to file
:type save: bool
:param calf: Frequency for which to reference attenuation curve from
:type calf: int
:returns: str -- name of a saved calibration
"""
if self.selected_calibration_index == 2:
raise Exception("Calibration curve processing not currently supported")
else:
results, calname, freq, db = self.bs_calibrator.process_calibration(save)
return calname, db | python | def process_calibration(self, save=True, calf=20000):
"""Processes a completed calibration
:param save: Wether to save this calibration to file
:type save: bool
:param calf: Frequency for which to reference attenuation curve from
:type calf: int
:returns: str -- name of a saved calibration
"""
if self.selected_calibration_index == 2:
raise Exception("Calibration curve processing not currently supported")
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return calname, db | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L342-L355 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.close_data | def close_data(self):
"""Closes the current data file"""
# save the total number of cells to make re-loading convient
if self.datafile is not None:
if self.datafile.filemode != 'r':
self.datafile.set_metadata('', {'total cells': self.current_cellid})
self.datafile.close()
self.datafile = None | python | def close_data(self):
"""Closes the current data file"""
# save the total number of cells to make re-loading convient
if self.datafile is not None:
if self.datafile.filemode != 'r':
self.datafile.set_metadata('', {'total cells': self.current_cellid})
self.datafile.close()
self.datafile = None | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L369-L376 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.calibration_stimulus | def calibration_stimulus(self, mode):
"""Gets the stimulus model for calibration
:param mode: Type of stimulus to get: tone or noise
:type mode: str
:returns: :class:`StimulusModel<sparkle.stim.stimulus_model.StimulusModel>`
"""
if mode == 'tone':
return self.tone_calibrator.stimulus
elif mode =='noise':
return self.bs_calibrator.stimulus | python | def calibration_stimulus(self, mode):
"""Gets the stimulus model for calibration
:param mode: Type of stimulus to get: tone or noise
:type mode: str
:returns: :class:`StimulusModel<sparkle.stim.stimulus_model.StimulusModel>`
"""
if mode == 'tone':
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return self.bs_calibrator.stimulus | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L388-L398 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.calibration_template | def calibration_template(self):
"""Gets the template documentation for the both the tone curve calibration and noise calibration
:returns: dict -- all information necessary to recreate calibration objects
"""
temp = {}
temp['tone_doc'] = self.tone_calibrator.stimulus.templateDoc()
comp_doc = []
for calstim in self.bs_calibrator.get_stims():
comp_doc.append(calstim.stateDict())
temp['noise_doc'] = comp_doc
return temp | python | def calibration_template(self):
"""Gets the template documentation for the both the tone curve calibration and noise calibration
:returns: dict -- all information necessary to recreate calibration objects
"""
temp = {}
temp['tone_doc'] = self.tone_calibrator.stimulus.templateDoc()
comp_doc = []
for calstim in self.bs_calibrator.get_stims():
comp_doc.append(calstim.stateDict())
temp['noise_doc'] = comp_doc
return temp | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L421-L432 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.load_calibration_template | def load_calibration_template(self, template):
"""Reloads calibration settings from saved template doc
:param template: Values for calibration stimuli (see calibration_template function)
:type template: dict
"""
self.tone_calibrator.stimulus.clearComponents()
self.tone_calibrator.stimulus.loadFromTemplate(template['tone_doc'], self.tone_calibrator.stimulus)
comp_doc = template['noise_doc']
for state, calstim in zip(comp_doc, self.bs_calibrator.get_stims()):
calstim.loadState(state) | python | def load_calibration_template(self, template):
"""Reloads calibration settings from saved template doc
:param template: Values for calibration stimuli (see calibration_template function)
:type template: dict
"""
self.tone_calibrator.stimulus.clearComponents()
self.tone_calibrator.stimulus.loadFromTemplate(template['tone_doc'], self.tone_calibrator.stimulus)
comp_doc = template['noise_doc']
for state, calstim in zip(comp_doc, self.bs_calibrator.get_stims()):
calstim.loadState(state) | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L434-L444 | train |
portfors-lab/sparkle | sparkle/run/acquisition_manager.py | AcquisitionManager.attenuator_connection | def attenuator_connection(self, connect=True):
"""Checks the connection to the attenuator, and attempts to connect if not connected.
Will also set an appropriate ouput minimum for stimuli, if connection successful
:returns: bool - whether there is a connection
"""
# all or none will be connected
acquisition_modules = [self.explorer, self.protocoler, self.bs_calibrator, self.tone_calibrator, self.charter]
if connect:
if not acquisition_modules[0].player.attenuator_connected():
#attempt to re-connect first
for module in acquisition_modules:
success = module.player.connect_attenuator()
if success is None:
StimulusModel.setMinVoltage(0.0)
return False
else:
StimulusModel.setMinVoltage(0.005)
return True
else:
StimulusModel.setMinVoltage(0.005)
return True
else:
for module in acquisition_modules:
module.player.connect_attenuator(False)
StimulusModel.setMinVoltage(0.0)
return False | python | def attenuator_connection(self, connect=True):
"""Checks the connection to the attenuator, and attempts to connect if not connected.
Will also set an appropriate ouput minimum for stimuli, if connection successful
:returns: bool - whether there is a connection
"""
# all or none will be connected
acquisition_modules = [self.explorer, self.protocoler, self.bs_calibrator, self.tone_calibrator, self.charter]
if connect:
if not acquisition_modules[0].player.attenuator_connected():
#attempt to re-connect first
for module in acquisition_modules:
success = module.player.connect_attenuator()
if success is None:
StimulusModel.setMinVoltage(0.0)
return False
else:
StimulusModel.setMinVoltage(0.005)
return True
else:
StimulusModel.setMinVoltage(0.005)
return True
else:
for module in acquisition_modules:
module.player.connect_attenuator(False)
StimulusModel.setMinVoltage(0.0)
return False | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/run/acquisition_manager.py#L456-L482 | train |
agramian/subprocess-manager | subprocess_manager/nbstream_readerwriter.py | NonBlockingStreamReaderWriter.readline | def readline(self, timeout = 0.1):
"""Try to read a line from the stream queue.
"""
try:
return self._q.get(block = timeout is not None,
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"""Try to read a line from the stream queue.
"""
try:
return self._q.get(block = timeout is not None,
timeout = timeout)
except Empty:
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| fff9ff2ddab644a86f96e1ccf5df142c482a8247 | https://github.com/agramian/subprocess-manager/blob/fff9ff2ddab644a86f96e1ccf5df142c482a8247/subprocess_manager/nbstream_readerwriter.py#L54-L61 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | CommandHistory.verification_events | def verification_events(self):
"""
Events related to command verification.
:type: List[:class:`.CommandHistoryEvent`]
"""
queued = self._assemble_event('Verifier_Queued')
started = self._assemble_event('Verifier_Started')
return [x for x in [queued, started] if x] | python | def verification_events(self):
"""
Events related to command verification.
:type: List[:class:`.CommandHistoryEvent`]
"""
queued = self._assemble_event('Verifier_Queued')
started = self._assemble_event('Verifier_Started')
return [x for x in [queued, started] if x] | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L122-L130 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | CommandHistory.events | def events(self):
"""
All events.
:type: List[:class:`.CommandHistoryEvent`]
"""
events = [self.acknowledge_event] + self.verification_events
return [x for x in events if x] | python | def events(self):
"""
All events.
:type: List[:class:`.CommandHistoryEvent`]
"""
events = [self.acknowledge_event] + self.verification_events
return [x for x in events if x] | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L133-L140 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.generation_time | def generation_time(self):
"""
The generation time as set by Yamcs.
:type: :class:`~datetime.datetime`
"""
entry = self._proto.commandQueueEntry
if entry.HasField('generationTimeUTC'):
return parse_isostring(entry.generationTimeUTC)
return None | python | def generation_time(self):
"""
The generation time as set by Yamcs.
:type: :class:`~datetime.datetime`
"""
entry = self._proto.commandQueueEntry
if entry.HasField('generationTimeUTC'):
return parse_isostring(entry.generationTimeUTC)
return None | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L173-L182 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.username | def username(self):
"""The username of the issuer."""
entry = self._proto.commandQueueEntry
if entry.HasField('username'):
return entry.username
return None | python | def username(self):
"""The username of the issuer."""
entry = self._proto.commandQueueEntry
if entry.HasField('username'):
return entry.username
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L185-L190 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.queue | def queue(self):
"""The name of the queue that this command was assigned to."""
entry = self._proto.commandQueueEntry
if entry.HasField('queueName'):
return entry.queueName
return None | python | def queue(self):
"""The name of the queue that this command was assigned to."""
entry = self._proto.commandQueueEntry
if entry.HasField('queueName'):
return entry.queueName
return None | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L193-L198 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.origin | def origin(self):
"""
The origin of this command. This is often empty, but may
also be a hostname.
"""
entry = self._proto.commandQueueEntry
if entry.cmdId.HasField('origin'):
return entry.cmdId.origin
return None | python | def origin(self):
"""
The origin of this command. This is often empty, but may
also be a hostname.
"""
entry = self._proto.commandQueueEntry
if entry.cmdId.HasField('origin'):
return entry.cmdId.origin
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L201-L209 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.sequence_number | def sequence_number(self):
"""
The sequence number of this command. This is the sequence
number assigned by the issuing client.
"""
entry = self._proto.commandQueueEntry
if entry.cmdId.HasField('sequenceNumber'):
return entry.cmdId.sequenceNumber
return None | python | def sequence_number(self):
"""
The sequence number of this command. This is the sequence
number assigned by the issuing client.
"""
entry = self._proto.commandQueueEntry
if entry.cmdId.HasField('sequenceNumber'):
return entry.cmdId.sequenceNumber
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L212-L220 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | IssuedCommand.create_command_history_subscription | def create_command_history_subscription(self, on_data=None, timeout=60):
"""
Create a new command history subscription for this command.
:param on_data: Function that gets called with :class:`.CommandHistory`
updates.
:param float timeout: The amount of seconds to wait for the request
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:return: Future that can be used to manage the background websocket
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:rtype: .CommandHistorySubscription
"""
return self._client.create_command_history_subscription(
issued_command=self, on_data=on_data, timeout=timeout) | python | def create_command_history_subscription(self, on_data=None, timeout=60):
"""
Create a new command history subscription for this command.
:param on_data: Function that gets called with :class:`.CommandHistory`
updates.
:param float timeout: The amount of seconds to wait for the request
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:return: Future that can be used to manage the background websocket
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:rtype: .CommandHistorySubscription
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return self._client.create_command_history_subscription(
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L243-L256 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | Alarm.acknowledged_by | def acknowledged_by(self):
"""Username of the acknowledger."""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgedBy')):
return self._proto.acknowledgeInfo.acknowledgedBy
return None | python | def acknowledged_by(self):
"""Username of the acknowledger."""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgedBy')):
return self._proto.acknowledgeInfo.acknowledgedBy
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L315-L320 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | Alarm.acknowledge_message | def acknowledge_message(self):
"""Comment provided when acknowledging the alarm."""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgeMessage')):
return self._proto.acknowledgeInfo.acknowledgeMessage
return None | python | def acknowledge_message(self):
"""Comment provided when acknowledging the alarm."""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgeMessage')):
return self._proto.acknowledgeInfo.acknowledgeMessage
return None | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L323-L328 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | Alarm.acknowledge_time | def acknowledge_time(self):
"""
Processor time when the alarm was acknowledged.
:type: :class:`~datetime.datetime`
"""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgeTime')):
return parse_isostring(self._proto.acknowledgeInfo.acknowledgeTime)
return None | python | def acknowledge_time(self):
"""
Processor time when the alarm was acknowledged.
:type: :class:`~datetime.datetime`
"""
if (self.is_acknowledged and
self._proto.acknowledgeInfo.HasField('acknowledgeTime')):
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L331-L340 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | ParameterValue.name | def name(self):
"""
An identifying name for the parameter value. Typically this is the
fully-qualified XTCE name, but it may also be an alias depending
on how the parameter update was requested.
"""
if self._proto.id.namespace:
return self._proto.id.namespace + '/' + self._proto.id.name
return self._proto.id.name | python | def name(self):
"""
An identifying name for the parameter value. Typically this is the
fully-qualified XTCE name, but it may also be an alias depending
on how the parameter update was requested.
"""
if self._proto.id.namespace:
return self._proto.id.namespace + '/' + self._proto.id.name
return self._proto.id.name | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L410-L418 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | ParameterValue.validity_duration | def validity_duration(self):
"""
How long this parameter value is valid.
.. note: There is also an option when subscribing to get updated when
the parameter values expire.
:type: :class:`~datetime.timedelta`
"""
if self._proto.HasField('expireMillis'):
return timedelta(milliseconds=self._proto.expireMillis)
return None | python | def validity_duration(self):
"""
How long this parameter value is valid.
.. note: There is also an option when subscribing to get updated when
the parameter values expire.
:type: :class:`~datetime.timedelta`
"""
if self._proto.HasField('expireMillis'):
return timedelta(milliseconds=self._proto.expireMillis)
return None | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L444-L455 | train |
yamcs/yamcs-python | yamcs-client/yamcs/tmtc/model.py | ParameterValue.range_condition | def range_condition(self):
"""
If the value is out of limits, this indicates ``LOW`` or ``HIGH``.
"""
if self._proto.HasField('rangeCondition'):
return pvalue_pb2.RangeCondition.Name(self._proto.rangeCondition)
return None | python | def range_condition(self):
"""
If the value is out of limits, this indicates ``LOW`` or ``HIGH``.
"""
if self._proto.HasField('rangeCondition'):
return pvalue_pb2.RangeCondition.Name(self._proto.rangeCondition)
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/tmtc/model.py#L482-L488 | train |
lowandrew/OLCTools | sipprCommon/sippingmethods.py | Sippr.reversebait | def reversebait(self, maskmiddle='f', k=19):
"""
Use the freshly-baited FASTQ files to bait out sequence from the original target files. This will reduce the
number of possibly targets against which the baited reads must be aligned
"""
logging.info('Performing reverse kmer baiting of targets with FASTQ files')
if self.kmer_size is None:
kmer = k
else:
kmer = self.kmer_size
with progressbar(self.runmetadata) as bar:
for sample in bar:
if sample.general.bestassemblyfile != 'NA' and sample[self.analysistype].runanalysis:
outfile = os.path.join(sample[self.analysistype].outputdir, 'baitedtargets.fa')
sample[self.analysistype].revbbdukcmd = \
'bbduk.sh -Xmx{mem} ref={ref} in={in1} k={kmer} threads={cpus} mincovfraction={mcf} ' \
'maskmiddle={mm} outm={outm}' \
.format(mem=self.mem,
ref=sample[self.analysistype].baitedfastq,
in1=sample[self.analysistype].baitfile,
kmer=kmer,
cpus=str(self.cpus),
mcf=self.cutoff,
mm=maskmiddle,
outm=outfile)
# Run the system call (if necessary)
if not os.path.isfile(outfile):
out, err = run_subprocess(sample[self.analysistype].revbbdukcmd)
write_to_logfile(sample[self.analysistype].bbdukcmd,
sample[self.analysistype].bbdukcmd,
self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
write_to_logfile(out,
err,
self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
# Set the baitfile to use in the mapping steps as the newly created outfile
sample[self.analysistype].baitfile = outfile | python | def reversebait(self, maskmiddle='f', k=19):
"""
Use the freshly-baited FASTQ files to bait out sequence from the original target files. This will reduce the
number of possibly targets against which the baited reads must be aligned
"""
logging.info('Performing reverse kmer baiting of targets with FASTQ files')
if self.kmer_size is None:
kmer = k
else:
kmer = self.kmer_size
with progressbar(self.runmetadata) as bar:
for sample in bar:
if sample.general.bestassemblyfile != 'NA' and sample[self.analysistype].runanalysis:
outfile = os.path.join(sample[self.analysistype].outputdir, 'baitedtargets.fa')
sample[self.analysistype].revbbdukcmd = \
'bbduk.sh -Xmx{mem} ref={ref} in={in1} k={kmer} threads={cpus} mincovfraction={mcf} ' \
'maskmiddle={mm} outm={outm}' \
.format(mem=self.mem,
ref=sample[self.analysistype].baitedfastq,
in1=sample[self.analysistype].baitfile,
kmer=kmer,
cpus=str(self.cpus),
mcf=self.cutoff,
mm=maskmiddle,
outm=outfile)
# Run the system call (if necessary)
if not os.path.isfile(outfile):
out, err = run_subprocess(sample[self.analysistype].revbbdukcmd)
write_to_logfile(sample[self.analysistype].bbdukcmd,
sample[self.analysistype].bbdukcmd,
self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
write_to_logfile(out,
err,
self.logfile, sample.general.logout, sample.general.logerr,
sample[self.analysistype].logout, sample[self.analysistype].logerr)
# Set the baitfile to use in the mapping steps as the newly created outfile
sample[self.analysistype].baitfile = outfile | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/sipprCommon/sippingmethods.py#L193-L230 | train |
lowandrew/OLCTools | sipprCommon/sippingmethods.py | Sippr.clipper | def clipper(self):
"""
Filter out results based on the presence of cigar features such as internal soft-clipping
"""
for sample in self.runmetadata:
# Create a dictionary to store all the samples that do not have features
replacementresults = dict()
try:
# SixteenS analyses seem to fail if results are filtered out
if self.analysistype != 'sixteens_full' and self.analysistype != 'resfinder':
# Iterate through all the baited genes
for gene in sample[self.analysistype].faidict:
try:
percentidentity = sample[self.analysistype].results[gene]
try:
# Create a list to store whether a feature is present in enough reads to discard the
# sample
passingfeature = list()
for location, feature in sample[self.analysistype].features[gene].items():
# If the feature is present in under 30% of the reads, set the passing variable
# to true
if len(feature) < int(float(sample[self.analysistype].avgdepth[gene])) * 0.3:
passingfeature.append(True)
# Otherwise set it to false
else:
passingfeature.append(False)
# If all the features are 'true' (present in fewer than 30% of the reads), add this
# contig to the list of passing results
if all(passingfeature):
replacementresults[gene] = percentidentity
# If the allele does not have any features, it is added to the passing list
except KeyError:
replacementresults[gene] = percentidentity
except KeyError:
pass
# Update the .results attribute with the filtered dictionary
sample[self.analysistype].results = replacementresults
except AttributeError:
pass | python | def clipper(self):
"""
Filter out results based on the presence of cigar features such as internal soft-clipping
"""
for sample in self.runmetadata:
# Create a dictionary to store all the samples that do not have features
replacementresults = dict()
try:
# SixteenS analyses seem to fail if results are filtered out
if self.analysistype != 'sixteens_full' and self.analysistype != 'resfinder':
# Iterate through all the baited genes
for gene in sample[self.analysistype].faidict:
try:
percentidentity = sample[self.analysistype].results[gene]
try:
# Create a list to store whether a feature is present in enough reads to discard the
# sample
passingfeature = list()
for location, feature in sample[self.analysistype].features[gene].items():
# If the feature is present in under 30% of the reads, set the passing variable
# to true
if len(feature) < int(float(sample[self.analysistype].avgdepth[gene])) * 0.3:
passingfeature.append(True)
# Otherwise set it to false
else:
passingfeature.append(False)
# If all the features are 'true' (present in fewer than 30% of the reads), add this
# contig to the list of passing results
if all(passingfeature):
replacementresults[gene] = percentidentity
# If the allele does not have any features, it is added to the passing list
except KeyError:
replacementresults[gene] = percentidentity
except KeyError:
pass
# Update the .results attribute with the filtered dictionary
sample[self.analysistype].results = replacementresults
except AttributeError:
pass | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/sipprCommon/sippingmethods.py#L739-L777 | train |
sirfoga/pyhal | hal/help.py | main | def main():
"""Pretty-print the bug information as JSON"""
reporter = BugReporter()
print("JSON report:")
print(reporter.as_json())
print()
print("Markdown report:")
print(reporter.as_markdown())
print("SQL report:")
print(reporter.as_sql())
print("Choose the appropriate format (if you're submitting a Github Issue "
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"""Pretty-print the bug information as JSON"""
reporter = BugReporter()
print("JSON report:")
print(reporter.as_json())
print()
print("Markdown report:")
print(reporter.as_markdown())
print("SQL report:")
print(reporter.as_sql())
print("Choose the appropriate format (if you're submitting a Github Issue "
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/help.py#L97-L113 | train |
sirfoga/pyhal | hal/help.py | BugReporter.get_platform_info | def get_platform_info():
"""Gets platform info
:return: platform info
"""
try:
system_name = platform.system()
release_name = platform.release()
except:
system_name = "Unknown"
release_name = "Unknown"
return {
'system': system_name,
'release': release_name,
} | python | def get_platform_info():
"""Gets platform info
:return: platform info
"""
try:
system_name = platform.system()
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sirfoga/pyhal | hal/help.py | BugReporter.get_bug_report | def get_bug_report():
"""Generate information for a bug report
:return: information for bug report
"""
platform_info = BugReporter.get_platform_info()
module_info = {
'version': hal_version.__version__,
'build': hal_version.__build__
}
return {
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'pyhal': module_info
} | python | def get_bug_report():
"""Generate information for a bug report
:return: information for bug report
"""
platform_info = BugReporter.get_platform_info()
module_info = {
'version': hal_version.__version__,
'build': hal_version.__build__
}
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yamcs/yamcs-python | yamcs-client/yamcs/core/helpers.py | to_isostring | def to_isostring(dt):
"""
Converts the given datetime to an ISO String.
This assumes the datetime is UTC.
"""
if dt.tzinfo is not None and dt.tzinfo.utcoffset(dt) > timedelta(0):
logging.warn('Warning: aware datetimes are interpreted as if they were naive')
# -3 to change microseconds to milliseconds
return dt.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z' | python | def to_isostring(dt):
"""
Converts the given datetime to an ISO String.
This assumes the datetime is UTC.
"""
if dt.tzinfo is not None and dt.tzinfo.utcoffset(dt) > timedelta(0):
logging.warn('Warning: aware datetimes are interpreted as if they were naive')
# -3 to change microseconds to milliseconds
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yamcs/yamcs-python | yamcs-client/yamcs/core/helpers.py | parse_value | def parse_value(proto):
"""
Convers a Protobuf `Value` from the API into a python native value
"""
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return parse_isostring(proto.stringValue)
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elif proto.HasField('arrayValue'):
return [parse_value(v) for v in proto.arrayValue]
elif proto.HasField('aggregateValue'):
return OrderedDict(zip(proto.aggregateValue.name, proto.aggregateValue.value))
else:
logging.warn('Unrecognized value type for update %s', proto)
return None | python | def parse_value(proto):
"""
Convers a Protobuf `Value` from the API into a python native value
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if proto.HasField('floatValue'):
return proto.floatValue
elif proto.HasField('doubleValue'):
return proto.doubleValue
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return proto.sint32Value
elif proto.HasField('uint32Value'):
return proto.uint32Value
elif proto.HasField('binaryValue'):
return proto.binaryValue
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# Don't use the actual 'timestampValue' field, it contains a number
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# the ISO String also set by Yamcs.
return parse_isostring(proto.stringValue)
elif proto.HasField('stringValue'):
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elif proto.HasField('aggregateValue'):
return OrderedDict(zip(proto.aggregateValue.name, proto.aggregateValue.value))
else:
logging.warn('Unrecognized value type for update %s', proto)
return None | [
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| 1082fee8a299010cc44416bbb7518fac0ef08b48 | https://github.com/yamcs/yamcs-python/blob/1082fee8a299010cc44416bbb7518fac0ef08b48/yamcs-client/yamcs/core/helpers.py#L30-L63 | train |
sirfoga/pyhal | hal/charts/correlation.py | create_correlation_matrix_plot | def create_correlation_matrix_plot(correlation_matrix, title, feature_list):
"""Creates plot for correlation matrix
:param correlation_matrix: Correlation matrix of features
:param title: Title of plot
:param feature_list: List of names of features
:return: Shows the given correlation matrix as image
"""
chart = SimpleChart(title)
ax1 = chart.get_ax()
ax1.set_xticks(list(range(len(feature_list))))
ax1.set_xticklabels([feature_list[i] for i in range(len(feature_list))],
rotation=90)
ax1.set_yticks(list(range(len(feature_list))))
ax1.set_yticklabels([feature_list[i] for i in range(len(feature_list))])
cax = ax1.imshow(correlation_matrix, interpolation="nearest",
cmap=cm.get_cmap("jet", 30))
chart.get_fig().colorbar(cax, ticks=np.linspace(-1, 1, 21))
plt.gcf().subplots_adjust(bottom=0.25) | python | def create_correlation_matrix_plot(correlation_matrix, title, feature_list):
"""Creates plot for correlation matrix
:param correlation_matrix: Correlation matrix of features
:param title: Title of plot
:param feature_list: List of names of features
:return: Shows the given correlation matrix as image
"""
chart = SimpleChart(title)
ax1 = chart.get_ax()
ax1.set_xticks(list(range(len(feature_list))))
ax1.set_xticklabels([feature_list[i] for i in range(len(feature_list))],
rotation=90)
ax1.set_yticks(list(range(len(feature_list))))
ax1.set_yticklabels([feature_list[i] for i in range(len(feature_list))])
cax = ax1.imshow(correlation_matrix, interpolation="nearest",
cmap=cm.get_cmap("jet", 30))
chart.get_fig().colorbar(cax, ticks=np.linspace(-1, 1, 21))
plt.gcf().subplots_adjust(bottom=0.25) | [
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/charts/correlation.py#L11-L31 | train |
IS-ENES-Data/esgf-pid | esgfpid/utils/logutils.py | log_every_x_times | def log_every_x_times(logger, counter, x, msg, *args, **kwargs):
'''
Works like logdebug, but only prints first and
and every xth message.
'''
if counter==1 or counter % x == 0:
#msg = msg + (' (counter %i)' % counter)
logdebug(logger, msg, *args, **kwargs) | python | def log_every_x_times(logger, counter, x, msg, *args, **kwargs):
'''
Works like logdebug, but only prints first and
and every xth message.
'''
if counter==1 or counter % x == 0:
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mpds-io/python-api-client | mpds_client/retrieve_MPDS.py | MPDSDataRetrieval.get_dataframe | def get_dataframe(self, *args, **kwargs):
"""
Retrieve data as a Pandas dataframe.
Args:
search: (dict) Search query like {"categ_A": "val_A", "categ_B": "val_B"},
documented at https://developer.mpds.io/#Categories
phases: (list) Phase IDs, according to the MPDS distinct phases concept
fields: (dict) Data of interest for C-, S-, and P-entries,
e.g. for phase diagrams: {'C': ['naxes', 'arity', 'shapes']},
documented at https://developer.mpds.io/#JSON-schemata
columns: (list) Column names for Pandas dataframe
Returns: (object) Pandas dataframe object containing the results
"""
columns = kwargs.get('columns')
if columns:
del kwargs['columns']
else:
columns = self.default_titles
return pd.DataFrame(self.get_data(*args, **kwargs), columns=columns) | python | def get_dataframe(self, *args, **kwargs):
"""
Retrieve data as a Pandas dataframe.
Args:
search: (dict) Search query like {"categ_A": "val_A", "categ_B": "val_B"},
documented at https://developer.mpds.io/#Categories
phases: (list) Phase IDs, according to the MPDS distinct phases concept
fields: (dict) Data of interest for C-, S-, and P-entries,
e.g. for phase diagrams: {'C': ['naxes', 'arity', 'shapes']},
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columns: (list) Column names for Pandas dataframe
Returns: (object) Pandas dataframe object containing the results
"""
columns = kwargs.get('columns')
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| edfdd79c6aac44d0a5f7f785e252a88acc95b6fe | https://github.com/mpds-io/python-api-client/blob/edfdd79c6aac44d0a5f7f785e252a88acc95b6fe/mpds_client/retrieve_MPDS.py#L319-L340 | train |
portfors-lab/sparkle | sparkle/gui/stim/auto_parameter_view.py | AutoParameterTableView.grabImage | def grabImage(self, index):
"""Returns an image of the parameter row.
Re-implemented from :meth:`AbstractDragView<sparkle.gui.abstract_drag_view.AbstractDragView.grabImage>`
"""
# grab an image of the cell we are moving
# assume all rows same height
row_height = self.rowHeight(0)
# -5 becuase it a a little off
y = (row_height*index.row()) + row_height - 5
x = self.width()
rect = QtCore.QRect(5,y,x,row_height)
pixmap = QtGui.QPixmap()
pixmap = pixmap.grabWidget(self, rect)
return pixmap | python | def grabImage(self, index):
"""Returns an image of the parameter row.
Re-implemented from :meth:`AbstractDragView<sparkle.gui.abstract_drag_view.AbstractDragView.grabImage>`
"""
# grab an image of the cell we are moving
# assume all rows same height
row_height = self.rowHeight(0)
# -5 becuase it a a little off
y = (row_height*index.row()) + row_height - 5
x = self.width()
rect = QtCore.QRect(5,y,x,row_height)
pixmap = QtGui.QPixmap()
pixmap = pixmap.grabWidget(self, rect)
return pixmap | [
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/gui/stim/auto_parameter_view.py#L37-L51 | train |
portfors-lab/sparkle | sparkle/gui/stim/auto_parameter_view.py | AutoParameterTableView.mousePressEvent | def mousePressEvent(self, event):
"""Begins edit on cell clicked, if allowed, and passes event to super class"""
index = self.indexAt(event.pos())
if index.isValid():
self.selectRow(index.row())
# selecting the row sets the current index to 0,0 for tab
# order to work correctly, we must set the current index
self.setCurrentIndex(index)
self.parameterChanged.emit(self.model().selection(index))
self.edit(index, QtGui.QAbstractItemView.DoubleClicked, event)
super(AutoParameterTableView, self).mousePressEvent(event) | python | def mousePressEvent(self, event):
"""Begins edit on cell clicked, if allowed, and passes event to super class"""
index = self.indexAt(event.pos())
if index.isValid():
self.selectRow(index.row())
# selecting the row sets the current index to 0,0 for tab
# order to work correctly, we must set the current index
self.setCurrentIndex(index)
self.parameterChanged.emit(self.model().selection(index))
self.edit(index, QtGui.QAbstractItemView.DoubleClicked, event)
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| 5fad1cf2bec58ec6b15d91da20f6236a74826110 | https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/gui/stim/auto_parameter_view.py#L53-L63 | train |
outini/python-pylls | pylls/client.py | CachetAPIClient.request | def request(self, path, method, data=None, **kwargs):
"""Handle requests to API
:param str path: API endpoint's path to request
:param str method: HTTP method to use
:param dict data: Data to send (optional)
:return: Parsed json response as :class:`dict`
Additional named argument may be passed and are directly transmitted
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"""
if self.api_token:
self.request_headers['X-Cachet-Token'] = self.api_token
if not path.startswith('http://') and not path.startswith('https://'):
url = "%s/%s" % (self.api_endpoint, path)
else:
url = path
if data is None:
data = {}
response = self.r_session.request(method, url,
data=json.dumps(data),
headers=self.request_headers,
timeout=self.timeout,
verify=self.verify,
**kwargs)
# If API returns an error, we simply raise and let caller handle it
response.raise_for_status()
try:
return response.json()
except ValueError:
return {'data': response.text} | python | def request(self, path, method, data=None, **kwargs):
"""Handle requests to API
:param str path: API endpoint's path to request
:param str method: HTTP method to use
:param dict data: Data to send (optional)
:return: Parsed json response as :class:`dict`
Additional named argument may be passed and are directly transmitted
to :meth:`request` method of :class:`requests.Session` object.
"""
if self.api_token:
self.request_headers['X-Cachet-Token'] = self.api_token
if not path.startswith('http://') and not path.startswith('https://'):
url = "%s/%s" % (self.api_endpoint, path)
else:
url = path
if data is None:
data = {}
response = self.r_session.request(method, url,
data=json.dumps(data),
headers=self.request_headers,
timeout=self.timeout,
verify=self.verify,
**kwargs)
# If API returns an error, we simply raise and let caller handle it
response.raise_for_status()
try:
return response.json()
except ValueError:
return {'data': response.text} | [
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| f9fa220594bc1974469097d9bad690a42d0d0f0f | https://github.com/outini/python-pylls/blob/f9fa220594bc1974469097d9bad690a42d0d0f0f/pylls/client.py#L86-L121 | train |
outini/python-pylls | pylls/client.py | CachetAPIClient.paginate_request | def paginate_request(self, path, method, data=None, **kwargs):
"""Handle paginated requests to API
:param str path: API endpoint's path to request
:param str method: HTTP method to use
:param dict data: Data to send (optional)
:return: Response data items (:class:`Generator`)
Cachet pagination is handled and next pages requested on demand.
Additional named argument may be passed and are directly transmitted
to :meth:`request` method of :class:`requests.Session` object.
"""
next_page = path
while next_page:
response = self.request(next_page, method, data=data, **kwargs)
if not isinstance(response.get('data'), list):
next_page = None
yield response['data']
else:
for entry in response['data']:
yield entry
# Get next page if it exists
try:
links = response['meta']['pagination']['links']
next_page = links.get('next_page')
except KeyError:
next_page = None | python | def paginate_request(self, path, method, data=None, **kwargs):
"""Handle paginated requests to API
:param str path: API endpoint's path to request
:param str method: HTTP method to use
:param dict data: Data to send (optional)
:return: Response data items (:class:`Generator`)
Cachet pagination is handled and next pages requested on demand.
Additional named argument may be passed and are directly transmitted
to :meth:`request` method of :class:`requests.Session` object.
"""
next_page = path
while next_page:
response = self.request(next_page, method, data=data, **kwargs)
if not isinstance(response.get('data'), list):
next_page = None
yield response['data']
else:
for entry in response['data']:
yield entry
# Get next page if it exists
try:
links = response['meta']['pagination']['links']
next_page = links.get('next_page')
except KeyError:
next_page = None | [
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| f9fa220594bc1974469097d9bad690a42d0d0f0f | https://github.com/outini/python-pylls/blob/f9fa220594bc1974469097d9bad690a42d0d0f0f/pylls/client.py#L123-L152 | train |
etal/biocma | biocma/sugar.py | maybe_open | def maybe_open(infile, mode='r'):
"""Take a file name or a handle, and return a handle.
Simplifies creating functions that automagically accept either a file name
or an already opened file handle.
"""
# ENH: Exception safety?
if isinstance(infile, basestring):
handle = open(infile, mode)
do_close = True
else:
handle = infile
do_close = False
yield handle
if do_close:
handle.close() | python | def maybe_open(infile, mode='r'):
"""Take a file name or a handle, and return a handle.
Simplifies creating functions that automagically accept either a file name
or an already opened file handle.
"""
# ENH: Exception safety?
if isinstance(infile, basestring):
handle = open(infile, mode)
do_close = True
else:
handle = infile
do_close = False
yield handle
if do_close:
handle.close() | [
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sirfoga/pyhal | hal/internet/parser.py | HtmlTable._get_row_tag | def _get_row_tag(row, tag):
"""Parses row and gets columns matching tag
:param row: HTML row
:param tag: tag to get
:return: list of labels in row
"""
is_empty = True
data = []
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if data[-1]:
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if not is_empty:
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return None | python | def _get_row_tag(row, tag):
"""Parses row and gets columns matching tag
:param row: HTML row
:param tag: tag to get
:return: list of labels in row
"""
is_empty = True
data = []
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if not is_empty:
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return None | [
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/internet/parser.py#L22-L42 | train |
sirfoga/pyhal | hal/internet/parser.py | HtmlTable._parse_row | def _parse_row(row):
"""Parses HTML row
:param row: HTML row
:return: list of values in row
"""
data = []
labels = HtmlTable._get_row_tag(row, "th")
if labels:
data += labels
columns = HtmlTable._get_row_tag(row, "td")
if columns:
data += columns
return data | python | def _parse_row(row):
"""Parses HTML row
:param row: HTML row
:return: list of values in row
"""
data = []
labels = HtmlTable._get_row_tag(row, "th")
if labels:
data += labels
columns = HtmlTable._get_row_tag(row, "td")
if columns:
data += columns
return data | [
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| 4394d8a1f7e45bea28a255ec390f4962ee64d33a | https://github.com/sirfoga/pyhal/blob/4394d8a1f7e45bea28a255ec390f4962ee64d33a/hal/internet/parser.py#L45-L62 | train |
sirfoga/pyhal | hal/internet/parser.py | HtmlTable.parse | def parse(self):
"""Parses data in table
:return: List of list of values in table
"""
data = [] # add name of section
for row in self.soup.find_all("tr"): # cycle through all rows
parsed = self._parse_row(row)
if parsed:
data.append(parsed)
return data | python | def parse(self):
"""Parses data in table
:return: List of list of values in table
"""
data = [] # add name of section
for row in self.soup.find_all("tr"): # cycle through all rows
parsed = self._parse_row(row)
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data.append(parsed)
return data | [
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moin18/utilspie | utilspie/importutils/import_utils.py | delete_module | def delete_module(modname):
"""
Delete module and sub-modules from `sys.module`
"""
try:
_ = sys.modules[modname]
except KeyError:
raise ValueError("Module not found in sys.modules: '{}'".format(modname))
for module in list(sys.modules.keys()):
if module and module.startswith(modname):
del sys.modules[module] | python | def delete_module(modname):
"""
Delete module and sub-modules from `sys.module`
"""
try:
_ = sys.modules[modname]
except KeyError:
raise ValueError("Module not found in sys.modules: '{}'".format(modname))
for module in list(sys.modules.keys()):
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| ea96860b93fd058019a829847258e39323fef31f | https://github.com/moin18/utilspie/blob/ea96860b93fd058019a829847258e39323fef31f/utilspie/importutils/import_utils.py#L8-L19 | train |
moin18/utilspie | utilspie/importutils/import_utils.py | reload_module | def reload_module(module):
"""
Reload the Python module
"""
try:
# For Python 2.x
reload(module)
except (ImportError, NameError):
# For <= Python3.3:
import imp
imp.reload(module)
except (ImportError, NameError):
# For >= Python3.4
import importlib
importlib.reload(module) | python | def reload_module(module):
"""
Reload the Python module
"""
try:
# For Python 2.x
reload(module)
except (ImportError, NameError):
# For <= Python3.3:
import imp
imp.reload(module)
except (ImportError, NameError):
# For >= Python3.4
import importlib
importlib.reload(module) | [
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| ea96860b93fd058019a829847258e39323fef31f | https://github.com/moin18/utilspie/blob/ea96860b93fd058019a829847258e39323fef31f/utilspie/importutils/import_utils.py#L22-L36 | train |
moin18/utilspie | utilspie/importutils/import_utils.py | lazy_load_modules | def lazy_load_modules(*modules):
"""
Decorator to load module to perform related operation for specific function
and delete the module from imports once the task is done. GC frees the memory
related to module during clean-up.
"""
def decorator(function):
def wrapper(*args, **kwargs):
module_dict = {}
for module_string in modules:
module = __import__(module_string)
# Add `module` entry in `sys.modules`. After deleting the module
# from `sys.modules` and re-importing the module don't update
# the module entry in `sys.modules` dict
sys.modules[module.__package__] = module
reload_module(module)
module_dict[module_string] = module
func_response = function(*args, **kwargs)
for module_string, module in module_dict.items():
# delete idna module
delete_module(module_string)
del module # delete reference to idna
return func_response
return wrapper
return decorator | python | def lazy_load_modules(*modules):
"""
Decorator to load module to perform related operation for specific function
and delete the module from imports once the task is done. GC frees the memory
related to module during clean-up.
"""
def decorator(function):
def wrapper(*args, **kwargs):
module_dict = {}
for module_string in modules:
module = __import__(module_string)
# Add `module` entry in `sys.modules`. After deleting the module
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# the module entry in `sys.modules` dict
sys.modules[module.__package__] = module
reload_module(module)
module_dict[module_string] = module
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for module_string, module in module_dict.items():
# delete idna module
delete_module(module_string)
del module # delete reference to idna
return func_response
return wrapper
return decorator | [
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| ea96860b93fd058019a829847258e39323fef31f | https://github.com/moin18/utilspie/blob/ea96860b93fd058019a829847258e39323fef31f/utilspie/importutils/import_utils.py#L39-L68 | train |
NoviceLive/intellicoder | intellicoder/init.py | LevelFormatter.format | def format(self, record):
"""
Format the record using the corresponding formatter.
"""
if record.levelno == DEBUG:
return self.debug_formatter.format(record)
if record.levelno == INFO:
return self.info_formatter.format(record)
if record.levelno == ERROR:
return self.error_formatter.format(record)
if record.levelno == WARNING:
return self.warning_formatter.format(record)
if record.levelno == CRITICAL:
return self.critical_formatter.format(record) | python | def format(self, record):
"""
Format the record using the corresponding formatter.
"""
if record.levelno == DEBUG:
return self.debug_formatter.format(record)
if record.levelno == INFO:
return self.info_formatter.format(record)
if record.levelno == ERROR:
return self.error_formatter.format(record)
if record.levelno == WARNING:
return self.warning_formatter.format(record)
if record.levelno == CRITICAL:
return self.critical_formatter.format(record) | [
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| 6cac5ebfce65c370dbebe47756a1789b120ef982 | https://github.com/NoviceLive/intellicoder/blob/6cac5ebfce65c370dbebe47756a1789b120ef982/intellicoder/init.py#L85-L98 | train |
dalloriam/engel | engel/widgets/structure.py | Head.load_stylesheet | def load_stylesheet(self, id, path):
"""
Proper way to dynamically inject a stylesheet in a page.
:param path: Path of the stylesheet to inject.
"""
self.add_child(HeadLink(id=id, link_type="stylesheet", path=path)) | python | def load_stylesheet(self, id, path):
"""
Proper way to dynamically inject a stylesheet in a page.
:param path: Path of the stylesheet to inject.
"""
self.add_child(HeadLink(id=id, link_type="stylesheet", path=path)) | [
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| f3477cd546e885bc53e755b3eb1452ce43ef5697 | https://github.com/dalloriam/engel/blob/f3477cd546e885bc53e755b3eb1452ce43ef5697/engel/widgets/structure.py#L31-L37 | train |
dalloriam/engel | engel/widgets/structure.py | List.add_child | def add_child(self, widget):
"""
Append a widget to the list.
:param widget: Object inheriting :class:`~.widgets.base.BaseElement`
"""
li_itm = _li(id=self.id + str(self._count))
li_itm.add_child(widget)
super(List, self).add_child(li_itm)
self._items.append((widget, li_itm))
self._count += 1 | python | def add_child(self, widget):
"""
Append a widget to the list.
:param widget: Object inheriting :class:`~.widgets.base.BaseElement`
"""
li_itm = _li(id=self.id + str(self._count))
li_itm.add_child(widget)
super(List, self).add_child(li_itm)
self._items.append((widget, li_itm))
self._count += 1 | [
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| f3477cd546e885bc53e755b3eb1452ce43ef5697 | https://github.com/dalloriam/engel/blob/f3477cd546e885bc53e755b3eb1452ce43ef5697/engel/widgets/structure.py#L70-L81 | train |
dalloriam/engel | engel/widgets/structure.py | List.remove_child | def remove_child(self, widget):
"""
Remove a widget from the list.
:param widget: Object inheriting :class:`~.widgets.base.BaseElement`
"""
raw = list(filter(lambda x: x[0] == widget, self._items))
if raw:
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self._items.remove(raw[0])
super(List, self).remove_child(wrapped)
else:
raise ValueError("Child not in list.") | python | def remove_child(self, widget):
"""
Remove a widget from the list.
:param widget: Object inheriting :class:`~.widgets.base.BaseElement`
"""
raw = list(filter(lambda x: x[0] == widget, self._items))
if raw:
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| f3477cd546e885bc53e755b3eb1452ce43ef5697 | https://github.com/dalloriam/engel/blob/f3477cd546e885bc53e755b3eb1452ce43ef5697/engel/widgets/structure.py#L83-L95 | train |
ArabellaTech/django-basic-cms | basic_cms/admin/views.py | move_page | def move_page(request, page_id, extra_context=None):
"""Move the page to the requested target, at the given
position."""
page = Page.objects.get(pk=page_id)
target = request.POST.get('target', None)
position = request.POST.get('position', None)
if target is not None and position is not None:
try:
target = Page.objects.get(pk=target)
except Page.DoesNotExist:
pass
# TODO: should use the django message system
# to display this message
# _('Page could not been moved.')
else:
page.invalidate()
target.invalidate()
from mptt.exceptions import InvalidMove
invalid_move = False
try:
page.move_to(target, position)
except InvalidMove:
invalid_move = True
return list_pages_ajax(request, invalid_move)
return HttpResponseRedirect('../../') | python | def move_page(request, page_id, extra_context=None):
"""Move the page to the requested target, at the given
position."""
page = Page.objects.get(pk=page_id)
target = request.POST.get('target', None)
position = request.POST.get('position', None)
if target is not None and position is not None:
try:
target = Page.objects.get(pk=target)
except Page.DoesNotExist:
pass
# TODO: should use the django message system
# to display this message
# _('Page could not been moved.')
else:
page.invalidate()
target.invalidate()
from mptt.exceptions import InvalidMove
invalid_move = False
try:
page.move_to(target, position)
except InvalidMove:
invalid_move = True
return list_pages_ajax(request, invalid_move)
return HttpResponseRedirect('../../') | [
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| 863f3c6098606f663994930cd8e7723ad0c07caf | https://github.com/ArabellaTech/django-basic-cms/blob/863f3c6098606f663994930cd8e7723ad0c07caf/basic_cms/admin/views.py#L113-L138 | train |
NoviceLive/intellicoder | intellicoder/sources.py | reloc_var | def reloc_var(var_name, reloc_delta, pointer, var_type):
"""
Build C source code to relocate a variable.
"""
template = '{0} {3}{1} = RELOC_VAR(_{1}, {2}, {0});\n'
return template.format(
var_type, var_name, reloc_delta,
'*' if pointer else ''
) | python | def reloc_var(var_name, reloc_delta, pointer, var_type):
"""
Build C source code to relocate a variable.
"""
template = '{0} {3}{1} = RELOC_VAR(_{1}, {2}, {0});\n'
return template.format(
var_type, var_name, reloc_delta,
'*' if pointer else ''
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| 6cac5ebfce65c370dbebe47756a1789b120ef982 | https://github.com/NoviceLive/intellicoder/blob/6cac5ebfce65c370dbebe47756a1789b120ef982/intellicoder/sources.py#L138-L146 | train |
NoviceLive/intellicoder | intellicoder/sources.py | make_c_args | def make_c_args(arg_pairs):
"""
Build a C argument list from return type and arguments pairs.
"""
logging.debug(arg_pairs)
c_args = [
'{} {}'.format(arg_type, arg_name) if arg_name else arg_type
for dummy_number, arg_type, arg_name in sorted(arg_pairs)
]
return ', '.join(c_args) | python | def make_c_args(arg_pairs):
"""
Build a C argument list from return type and arguments pairs.
"""
logging.debug(arg_pairs)
c_args = [
'{} {}'.format(arg_type, arg_name) if arg_name else arg_type
for dummy_number, arg_type, arg_name in sorted(arg_pairs)
]
return ', '.join(c_args) | [
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| 6cac5ebfce65c370dbebe47756a1789b120ef982 | https://github.com/NoviceLive/intellicoder/blob/6cac5ebfce65c370dbebe47756a1789b120ef982/intellicoder/sources.py#L166-L175 | train |
lowandrew/OLCTools | spadespipeline/phix.py | PhiX.interop_parse | def interop_parse(self):
"""
Use interop to parse the files in the InterOp folder to extract the number of reads mapping to PhiX as well as
the error rate
"""
# Parse the files and load the data
try:
run_metrics = py_interop_run_metrics.run_metrics()
valid_to_load = py_interop_run.uchar_vector(py_interop_run.MetricCount, 0)
py_interop_run_metrics.list_summary_metrics_to_load(valid_to_load)
run_metrics.read(self.path, valid_to_load)
summary = py_interop_summary.run_summary()
py_interop_summary.summarize_run_metrics(run_metrics, summary)
# PhiX error rate for run over all "usable cycles"
errorrate = summary.total_summary().error_rate()
# Percent aligned PhiX
pctaligned = summary.total_summary().percent_aligned()
# Add the error rate and the percent of reads that align to PhiX to the metadata object
for sample in self.metadata:
sample.run.error_rate = '{:.2f}'.format(errorrate)
sample.run.phix_aligned = '{:.2f}'.format(pctaligned)
except:
for sample in self.metadata:
sample.run.error_rate = 'ND'
sample.run.phix_aligned = 'ND' | python | def interop_parse(self):
"""
Use interop to parse the files in the InterOp folder to extract the number of reads mapping to PhiX as well as
the error rate
"""
# Parse the files and load the data
try:
run_metrics = py_interop_run_metrics.run_metrics()
valid_to_load = py_interop_run.uchar_vector(py_interop_run.MetricCount, 0)
py_interop_run_metrics.list_summary_metrics_to_load(valid_to_load)
run_metrics.read(self.path, valid_to_load)
summary = py_interop_summary.run_summary()
py_interop_summary.summarize_run_metrics(run_metrics, summary)
# PhiX error rate for run over all "usable cycles"
errorrate = summary.total_summary().error_rate()
# Percent aligned PhiX
pctaligned = summary.total_summary().percent_aligned()
# Add the error rate and the percent of reads that align to PhiX to the metadata object
for sample in self.metadata:
sample.run.error_rate = '{:.2f}'.format(errorrate)
sample.run.phix_aligned = '{:.2f}'.format(pctaligned)
except:
for sample in self.metadata:
sample.run.error_rate = 'ND'
sample.run.phix_aligned = 'ND' | [
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| 88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a | https://github.com/lowandrew/OLCTools/blob/88aa90ac85f84d0bbeb03e43c29b0a9d36e4ce2a/spadespipeline/phix.py#L31-L55 | train |
NoviceLive/intellicoder | intellicoder/msbuild/builders.py | Builder.make_inc | def make_inc(incs):
"""
Make include directory for link.exe.
"""
inc_args = [['/I', inc] for inc in incs]
return list(chain.from_iterable(inc_args)) | python | def make_inc(incs):
"""
Make include directory for link.exe.
"""
inc_args = [['/I', inc] for inc in incs]
return list(chain.from_iterable(inc_args)) | [
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| 6cac5ebfce65c370dbebe47756a1789b120ef982 | https://github.com/NoviceLive/intellicoder/blob/6cac5ebfce65c370dbebe47756a1789b120ef982/intellicoder/msbuild/builders.py#L113-L118 | train |
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