id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 51 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
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250,700 | closeio/tasktiger | tasktiger/__init__.py | TaskTiger.get_queue_sizes | def get_queue_sizes(self, queue):
"""
Get the queue's number of tasks in each state.
Returns dict with queue size for the QUEUED, SCHEDULED, and ACTIVE
states. Does not include size of error queue.
"""
states = [QUEUED, SCHEDULED, ACTIVE]
pipeline = self.connect... | python | def get_queue_sizes(self, queue):
states = [QUEUED, SCHEDULED, ACTIVE]
pipeline = self.connection.pipeline()
for state in states:
pipeline.zcard(self._key(state, queue))
results = pipeline.execute()
return dict(zip(states, results)) | [
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250,701 | closeio/tasktiger | tasktiger/__init__.py | TaskTiger.get_queue_system_lock | def get_queue_system_lock(self, queue):
"""
Get system lock timeout
Returns time system lock expires or None if lock does not exist
"""
key = self._key(LOCK_REDIS_KEY, queue)
return Semaphore.get_system_lock(self.connection, key) | python | def get_queue_system_lock(self, queue):
key = self._key(LOCK_REDIS_KEY, queue)
return Semaphore.get_system_lock(self.connection, key) | [
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250,702 | closeio/tasktiger | tasktiger/__init__.py | TaskTiger.set_queue_system_lock | def set_queue_system_lock(self, queue, timeout):
"""
Set system lock on a queue.
Max workers for this queue must be used for this to have any effect.
This will keep workers from processing tasks for this queue until
the timeout has expired. Active tasks will continue processing... | python | def set_queue_system_lock(self, queue, timeout):
key = self._key(LOCK_REDIS_KEY, queue)
Semaphore.set_system_lock(self.connection, key, timeout) | [
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250,703 | closeio/tasktiger | tasktiger/worker.py | Worker._install_signal_handlers | def _install_signal_handlers(self):
"""
Sets up signal handlers for safely stopping the worker.
"""
def request_stop(signum, frame):
self._stop_requested = True
self.log.info('stop requested, waiting for task to finish')
signal.signal(signal.SIGINT, reques... | python | def _install_signal_handlers(self):
def request_stop(signum, frame):
self._stop_requested = True
self.log.info('stop requested, waiting for task to finish')
signal.signal(signal.SIGINT, request_stop)
signal.signal(signal.SIGTERM, request_stop) | [
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250,704 | closeio/tasktiger | tasktiger/worker.py | Worker._uninstall_signal_handlers | def _uninstall_signal_handlers(self):
"""
Restores default signal handlers.
"""
signal.signal(signal.SIGINT, signal.SIG_DFL)
signal.signal(signal.SIGTERM, signal.SIG_DFL) | python | def _uninstall_signal_handlers(self):
signal.signal(signal.SIGINT, signal.SIG_DFL)
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250,705 | closeio/tasktiger | tasktiger/worker.py | Worker._filter_queues | def _filter_queues(self, queues):
"""
Applies the queue filter to the given list of queues and returns the
queues that match. Note that a queue name matches any subqueues
starting with the name, followed by a date. For example, "foo" will
match both "foo" and "foo.bar".
"... | python | def _filter_queues(self, queues):
def match(queue):
"""
Returns whether the given queue should be included by checking each
part of the queue name.
"""
for part in reversed_dotted_parts(queue):
if part in self.exclude_queues:
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250,706 | closeio/tasktiger | tasktiger/worker.py | Worker._worker_queue_scheduled_tasks | def _worker_queue_scheduled_tasks(self):
"""
Helper method that takes due tasks from the SCHEDULED queue and puts
them in the QUEUED queue for execution. This should be called
periodically.
"""
queues = set(self._filter_queues(self.connection.smembers(
sel... | python | def _worker_queue_scheduled_tasks(self):
queues = set(self._filter_queues(self.connection.smembers(
self._key(SCHEDULED))))
now = time.time()
for queue in queues:
# Move due items from the SCHEDULED queue to the QUEUED queue. If
# items were moved, remove... | [
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250,707 | closeio/tasktiger | tasktiger/worker.py | Worker._wait_for_new_tasks | def _wait_for_new_tasks(self, timeout=0, batch_timeout=0):
"""
Check activity channel and wait as necessary.
This method is also used to slow down the main processing loop to reduce
the effects of rapidly sending Redis commands. This method will exit
for any of these conditions... | python | def _wait_for_new_tasks(self, timeout=0, batch_timeout=0):
new_queue_found = False
start_time = batch_exit = time.time()
while True:
# Check to see if batch_exit has been updated
if batch_exit > start_time:
pubsub_sleep = batch_exit - time.time()
... | [
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250,708 | closeio/tasktiger | tasktiger/worker.py | Worker._execute_forked | def _execute_forked(self, tasks, log):
"""
Executes the tasks in the forked process. Multiple tasks can be passed
for batch processing. However, they must all use the same function and
will share the execution entry.
"""
success = False
execution = {}
as... | python | def _execute_forked(self, tasks, log):
success = False
execution = {}
assert len(tasks)
task_func = tasks[0].serialized_func
assert all([task_func == task.serialized_func for task in tasks[1:]])
execution['time_started'] = time.time()
exc = None
exc_in... | [
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250,709 | closeio/tasktiger | tasktiger/worker.py | Worker._get_queue_batch_size | def _get_queue_batch_size(self, queue):
"""Get queue batch size."""
# Fetch one item unless this is a batch queue.
# XXX: It would be more efficient to loop in reverse order and break.
batch_queues = self.config['BATCH_QUEUES']
batch_size = 1
for part in dotted_parts(que... | python | def _get_queue_batch_size(self, queue):
# Fetch one item unless this is a batch queue.
# XXX: It would be more efficient to loop in reverse order and break.
batch_queues = self.config['BATCH_QUEUES']
batch_size = 1
for part in dotted_parts(queue):
if part in batch_que... | [
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250,710 | closeio/tasktiger | tasktiger/worker.py | Worker._get_queue_lock | def _get_queue_lock(self, queue, log):
"""Get queue lock for max worker queues.
For max worker queues it returns a Lock if acquired and whether
it failed to acquire the lock.
"""
max_workers = self.max_workers_per_queue
# Check if this is single worker queue
for... | python | def _get_queue_lock(self, queue, log):
max_workers = self.max_workers_per_queue
# Check if this is single worker queue
for part in dotted_parts(queue):
if part in self.single_worker_queues:
log.debug('single worker queue')
max_workers = 1
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250,711 | closeio/tasktiger | tasktiger/worker.py | Worker._heartbeat | def _heartbeat(self, queue, task_ids):
"""
Updates the heartbeat for the given task IDs to prevent them from
timing out and being requeued.
"""
now = time.time()
self.connection.zadd(self._key(ACTIVE, queue),
**{task_id: now for task_id in tas... | python | def _heartbeat(self, queue, task_ids):
now = time.time()
self.connection.zadd(self._key(ACTIVE, queue),
**{task_id: now for task_id in task_ids}) | [
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250,712 | closeio/tasktiger | tasktiger/worker.py | Worker._execute | def _execute(self, queue, tasks, log, locks, queue_lock, all_task_ids):
"""
Executes the given tasks. Returns a boolean indicating whether
the tasks were executed successfully.
"""
# The tasks must use the same function.
assert len(tasks)
task_func = tasks[0].ser... | python | def _execute(self, queue, tasks, log, locks, queue_lock, all_task_ids):
# The tasks must use the same function.
assert len(tasks)
task_func = tasks[0].serialized_func
assert all([task_func == task.serialized_func for task in tasks[1:]])
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250,713 | closeio/tasktiger | tasktiger/worker.py | Worker._process_queue_message | def _process_queue_message(self, message_queue, new_queue_found, batch_exit,
start_time, timeout, batch_timeout):
"""Process a queue message from activity channel."""
for queue in self._filter_queues([message_queue]):
if queue not in self._queue_set:
... | python | def _process_queue_message(self, message_queue, new_queue_found, batch_exit,
start_time, timeout, batch_timeout):
for queue in self._filter_queues([message_queue]):
if queue not in self._queue_set:
if not new_queue_found:
new_queue_f... | [
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250,714 | closeio/tasktiger | tasktiger/worker.py | Worker._process_queue_tasks | def _process_queue_tasks(self, queue, queue_lock, task_ids, now, log):
"""Process tasks in queue."""
processed_count = 0
# Get all tasks
serialized_tasks = self.connection.mget([
self._key('task', task_id) for task_id in task_ids
])
# Parse tasks
ta... | python | def _process_queue_tasks(self, queue, queue_lock, task_ids, now, log):
processed_count = 0
# Get all tasks
serialized_tasks = self.connection.mget([
self._key('task', task_id) for task_id in task_ids
])
# Parse tasks
tasks = []
for task_id, serialize... | [
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250,715 | closeio/tasktiger | tasktiger/worker.py | Worker._process_from_queue | def _process_from_queue(self, queue):
"""
Internal method to process a task batch from the given queue.
Args:
queue: Queue name to be processed
Returns:
Task IDs: List of tasks that were processed (even if there was an
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now = time.time()
log = self.log.bind(queue=queue)
batch_size = self._get_queue_batch_size(queue)
queue_lock, failed_to_acquire = self._get_queue_lock(queue, log)
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250,716 | closeio/tasktiger | tasktiger/worker.py | Worker._execute_task_group | def _execute_task_group(self, queue, tasks, all_task_ids, queue_lock):
"""
Executes the given tasks in the queue. Updates the heartbeat for task
IDs passed in all_task_ids. This internal method is only meant to be
called from within _process_from_queue.
"""
log = self.log... | python | def _execute_task_group(self, queue, tasks, all_task_ids, queue_lock):
log = self.log.bind(queue=queue)
locks = []
# Keep track of the acquired locks: If two tasks in the list require
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lock_ids = set()
ready_tasks = []
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250,717 | closeio/tasktiger | tasktiger/worker.py | Worker._finish_task_processing | def _finish_task_processing(self, queue, task, success):
"""
After a task is executed, this method is called and ensures that
the task gets properly removed from the ACTIVE queue and, in case of an
error, retried or marked as failed.
"""
log = self.log.bind(queue=queue, t... | python | def _finish_task_processing(self, queue, task, success):
log = self.log.bind(queue=queue, task_id=task.id)
def _mark_done():
# Remove the task from active queue
task._move(from_state=ACTIVE)
log.info('done')
if success:
_mark_done()
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250,718 | closeio/tasktiger | tasktiger/worker.py | Worker.run | def run(self, once=False, force_once=False):
"""
Main loop of the worker.
Use once=True to execute any queued tasks and then exit.
Use force_once=True with once=True to always exit after one processing
loop even if tasks remain queued.
"""
self.log.info('ready',... | python | def run(self, once=False, force_once=False):
self.log.info('ready', id=self.id,
queues=sorted(self.only_queues),
exclude_queues=sorted(self.exclude_queues),
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250,719 | closeio/tasktiger | tasktiger/redis_scripts.py | RedisScripts.can_replicate_commands | def can_replicate_commands(self):
"""
Whether Redis supports single command replication.
"""
if not hasattr(self, '_can_replicate_commands'):
info = self.redis.info('server')
version_info = info['redis_version'].split('.')
major, minor = int(version_in... | python | def can_replicate_commands(self):
if not hasattr(self, '_can_replicate_commands'):
info = self.redis.info('server')
version_info = info['redis_version'].split('.')
major, minor = int(version_info[0]), int(version_info[1])
result = major > 3 or major == 3 and minor... | [
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250,720 | closeio/tasktiger | tasktiger/redis_scripts.py | RedisScripts.zpoppush | def zpoppush(self, source, destination, count, score, new_score,
client=None, withscores=False, on_success=None,
if_exists=None):
"""
Pops the first ``count`` members from the ZSET ``source`` and adds them
to the ZSET ``destination`` with a score of ``new_score`... | python | def zpoppush(self, source, destination, count, score, new_score,
client=None, withscores=False, on_success=None,
if_exists=None):
if score is None:
score = '+inf' # Include all elements.
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250,721 | closeio/tasktiger | tasktiger/redis_scripts.py | RedisScripts.execute_pipeline | def execute_pipeline(self, pipeline, client=None):
"""
Executes the given Redis pipeline as a Lua script. When an error
occurs, the transaction stops executing, and an exception is raised.
This differs from Redis transactions, where execution continues after an
error. On success,... | python | def execute_pipeline(self, pipeline, client=None):
client = client or self.redis
executing_pipeline = None
try:
# Prepare args
stack = pipeline.command_stack
script_args = [int(self.can_replicate_commands), len(stack)]
for args, options in stack:... | [
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250,722 | closeio/tasktiger | tasktiger/_internal.py | gen_unique_id | def gen_unique_id(serialized_name, args, kwargs):
"""
Generates and returns a hex-encoded 256-bit ID for the given task name and
args. Used to generate IDs for unique tasks or for task locks.
"""
return hashlib.sha256(json.dumps({
'func': serialized_name,
'args': args,
'kwarg... | python | def gen_unique_id(serialized_name, args, kwargs):
return hashlib.sha256(json.dumps({
'func': serialized_name,
'args': args,
'kwargs': kwargs,
}, sort_keys=True).encode('utf8')).hexdigest() | [
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250,723 | closeio/tasktiger | tasktiger/_internal.py | serialize_func_name | def serialize_func_name(func):
"""
Returns the dotted serialized path to the passed function.
"""
if func.__module__ == '__main__':
raise ValueError('Functions from the __main__ module cannot be '
'processed by workers.')
try:
# This will only work on Python ... | python | def serialize_func_name(func):
if func.__module__ == '__main__':
raise ValueError('Functions from the __main__ module cannot be '
'processed by workers.')
try:
# This will only work on Python 3.3 or above, but it will allow us to use static/classmethods
func_name... | [
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250,724 | closeio/tasktiger | tasktiger/_internal.py | dotted_parts | def dotted_parts(s):
"""
For a string "a.b.c", yields "a", "a.b", "a.b.c".
"""
idx = -1
while s:
idx = s.find('.', idx+1)
if idx == -1:
yield s
break
yield s[:idx] | python | def dotted_parts(s):
idx = -1
while s:
idx = s.find('.', idx+1)
if idx == -1:
yield s
break
yield s[:idx] | [
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250,725 | closeio/tasktiger | tasktiger/_internal.py | reversed_dotted_parts | def reversed_dotted_parts(s):
"""
For a string "a.b.c", yields "a.b.c", "a.b", "a".
"""
idx = -1
if s:
yield s
while s:
idx = s.rfind('.', 0, idx)
if idx == -1:
break
yield s[:idx] | python | def reversed_dotted_parts(s):
idx = -1
if s:
yield s
while s:
idx = s.rfind('.', 0, idx)
if idx == -1:
break
yield s[:idx] | [
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250,726 | closeio/tasktiger | tasktiger/logging.py | tasktiger_processor | def tasktiger_processor(logger, method_name, event_dict):
"""
TaskTiger structlog processor.
Inject the current task id for non-batch tasks.
"""
if g['current_tasks'] is not None and not g['current_task_is_batch']:
event_dict['task_id'] = g['current_tasks'][0].id
return event_dict | python | def tasktiger_processor(logger, method_name, event_dict):
if g['current_tasks'] is not None and not g['current_task_is_batch']:
event_dict['task_id'] = g['current_tasks'][0].id
return event_dict | [
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250,727 | closeio/tasktiger | tasktiger/task.py | Task.should_retry_on | def should_retry_on(self, exception_class, logger=None):
"""
Whether this task should be retried when the given exception occurs.
"""
for n in (self.retry_on or []):
try:
if issubclass(exception_class, import_attribute(n)):
return True
... | python | def should_retry_on(self, exception_class, logger=None):
for n in (self.retry_on or []):
try:
if issubclass(exception_class, import_attribute(n)):
return True
except TaskImportError:
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250,728 | closeio/tasktiger | tasktiger/task.py | Task.update_scheduled_time | def update_scheduled_time(self, when):
"""
Updates a scheduled task's date to the given date. If the task is not
scheduled, a TaskNotFound exception is raised.
"""
tiger = self.tiger
ts = get_timestamp(when)
assert ts
pipeline = tiger.connection.pipeline... | python | def update_scheduled_time(self, when):
tiger = self.tiger
ts = get_timestamp(when)
assert ts
pipeline = tiger.connection.pipeline()
key = tiger._key(SCHEDULED, self.queue)
tiger.scripts.zadd(key, ts, self.id, mode='xx', client=pipeline)
pipeline.zscore(key, self... | [
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250,729 | closeio/tasktiger | tasktiger/task.py | Task.n_executions | def n_executions(self):
"""
Queries and returns the number of past task executions.
"""
pipeline = self.tiger.connection.pipeline()
pipeline.exists(self.tiger._key('task', self.id))
pipeline.llen(self.tiger._key('task', self.id, 'executions'))
exists, n_executions... | python | def n_executions(self):
pipeline = self.tiger.connection.pipeline()
pipeline.exists(self.tiger._key('task', self.id))
pipeline.llen(self.tiger._key('task', self.id, 'executions'))
exists, n_executions = pipeline.execute()
if not exists:
raise TaskNotFound('Task {} not... | [
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250,730 | aewallin/allantools | allantools/noise_kasdin.py | Noise.set_input | def set_input(self, nr=2, qd=1, b=0):
""" Set inputs after initialization
Parameters
-------
nr: integer
length of generated time-series
number must be power of two
qd: float
discrete variance
b: float
noise type:
... | python | def set_input(self, nr=2, qd=1, b=0):
self.nr = nr
self.qd = qd
self.b = b | [
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Parameters
-------
nr: integer
length of generated time-series
number must be power of two
qd: float
discrete variance
b: float
noise type:
0 : White Phase Modulation (WPM)
... | [
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250,731 | aewallin/allantools | allantools/noise_kasdin.py | Noise.generateNoise | def generateNoise(self):
""" Generate noise time series based on input parameters
Returns
-------
time_series: np.array
Time series with colored noise.
len(time_series) == nr
"""
# Fill wfb array with white noise based on given discrete variance
... | python | def generateNoise(self):
# Fill wfb array with white noise based on given discrete variance
wfb = np.zeros(self.nr*2)
wfb[:self.nr] = np.random.normal(0, np.sqrt(self.qd), self.nr)
# Generate the hfb coefficients based on the noise type
mhb = -self.b/2.0
hfb = np.zeros(se... | [
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time_series: np.array
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250,732 | aewallin/allantools | allantools/noise_kasdin.py | Noise.adev | def adev(self, tau0, tau):
""" return predicted ADEV of noise-type at given tau
"""
prefactor = self.adev_from_qd(tau0=tau0, tau=tau)
c = self.c_avar()
avar = pow(prefactor, 2)*pow(tau, c)
return np.sqrt(avar) | python | def adev(self, tau0, tau):
prefactor = self.adev_from_qd(tau0=tau0, tau=tau)
c = self.c_avar()
avar = pow(prefactor, 2)*pow(tau, c)
return np.sqrt(avar) | [
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250,733 | aewallin/allantools | allantools/noise_kasdin.py | Noise.mdev | def mdev(self, tau0, tau):
""" return predicted MDEV of noise-type at given tau
"""
prefactor = self.mdev_from_qd(tau0=tau0, tau=tau)
c = self.c_mvar()
mvar = pow(prefactor, 2)*pow(tau, c)
return np.sqrt(mvar) | python | def mdev(self, tau0, tau):
prefactor = self.mdev_from_qd(tau0=tau0, tau=tau)
c = self.c_mvar()
mvar = pow(prefactor, 2)*pow(tau, c)
return np.sqrt(mvar) | [
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250,734 | aewallin/allantools | allantools/noise.py | scipy_psd | def scipy_psd(x, f_sample=1.0, nr_segments=4):
""" PSD routine from scipy
we can compare our own numpy result against this one
"""
f_axis, psd_of_x = scipy.signal.welch(x, f_sample, nperseg=len(x)/nr_segments)
return f_axis, psd_of_x | python | def scipy_psd(x, f_sample=1.0, nr_segments=4):
f_axis, psd_of_x = scipy.signal.welch(x, f_sample, nperseg=len(x)/nr_segments)
return f_axis, psd_of_x | [
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250,735 | aewallin/allantools | allantools/noise.py | iterpink | def iterpink(depth=20):
"""Generate a sequence of samples of pink noise.
pink noise generator
from http://pydoc.net/Python/lmj.sound/0.1.1/lmj.sound.noise/
Based on the Voss-McCartney algorithm, discussion and code examples at
http://www.firstpr.com.au/dsp/pink-noise/
depth: Use this many sam... | python | def iterpink(depth=20):
values = numpy.random.randn(depth)
smooth = numpy.random.randn(depth)
source = numpy.random.randn(depth)
sumvals = values.sum()
i = 0
while True:
yield sumvals + smooth[i]
# advance the index by 1. if the index wraps, generate noise to use in
# th... | [
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pink noise generator
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Based on the Voss-McCartney algorithm, discussion and code examples at
http://www.firstpr.com.au/dsp/pink-noise/
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250,736 | aewallin/allantools | examples/noise-color-demo.py | plotline | def plotline(plt, alpha, taus, style,label=""):
""" plot a line with the slope alpha """
y = [pow(tt, alpha) for tt in taus]
plt.loglog(taus, y, style,label=label) | python | def plotline(plt, alpha, taus, style,label=""):
y = [pow(tt, alpha) for tt in taus]
plt.loglog(taus, y, style,label=label) | [
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250,737 | aewallin/allantools | examples/b1_noise_id_figure.py | b1_noise_id | def b1_noise_id(x, af, rate):
""" B1 ratio for noise identification
ratio of Standard Variace to AVAR
"""
(taus,devs,errs,ns) = at.adev(x,taus=[af*rate],data_type="phase", rate=rate)
oadev_x = devs[0]
y = np.diff(x)
y_cut = np.array( y[:len(y)-(len(y)%af)] ) # cut to length
ass... | python | def b1_noise_id(x, af, rate):
(taus,devs,errs,ns) = at.adev(x,taus=[af*rate],data_type="phase", rate=rate)
oadev_x = devs[0]
y = np.diff(x)
y_cut = np.array( y[:len(y)-(len(y)%af)] ) # cut to length
assert len(y_cut)%af == 0
y_shaped = y_cut.reshape( ( int(len(y_cut)/af), af) )
y_averaged =... | [
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250,738 | aewallin/allantools | allantools/plot.py | Plot.plot | def plot(self, atDataset,
errorbars=False,
grid=False):
""" use matplotlib methods for plotting
Parameters
----------
atDataset : allantools.Dataset()
a dataset with computed data
errorbars : boolean
Plot errorbars. Defaults to F... | python | def plot(self, atDataset,
errorbars=False,
grid=False):
if errorbars:
self.ax.errorbar(atDataset.out["taus"],
atDataset.out["stat"],
yerr=atDataset.out["stat_err"],
)
else:
... | [
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Parameters
----------
atDataset : allantools.Dataset()
a dataset with computed data
errorbars : boolean
Plot errorbars. Defaults to False
grid : boolean
Plot grid. Defaults to False | [
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250,739 | aewallin/allantools | allantools/ci.py | greenhall_table2 | def greenhall_table2(alpha, d):
""" Table 2 from Greenhall 2004 """
row_idx = int(-alpha+2) # map 2-> row0 and -4-> row6
assert(row_idx in [0, 1, 2, 3, 4, 5])
col_idx = int(d-1)
table2 = [[(3.0/2.0, 1.0/2.0), (35.0/18.0, 1.0), (231.0/100.0, 3.0/2.0)], # alpha=+2
[(78.6, 25.2), (790.0, ... | python | def greenhall_table2(alpha, d):
row_idx = int(-alpha+2) # map 2-> row0 and -4-> row6
assert(row_idx in [0, 1, 2, 3, 4, 5])
col_idx = int(d-1)
table2 = [[(3.0/2.0, 1.0/2.0), (35.0/18.0, 1.0), (231.0/100.0, 3.0/2.0)], # alpha=+2
[(78.6, 25.2), (790.0, 410.0), (9950.0, 6520.0)],
... | [
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250,740 | aewallin/allantools | allantools/ci.py | greenhall_table1 | def greenhall_table1(alpha, d):
""" Table 1 from Greenhall 2004 """
row_idx = int(-alpha+2) # map 2-> row0 and -4-> row6
col_idx = int(d-1)
table1 = [[(2.0/3.0, 1.0/3.0), (7.0/9.0, 1.0/2.0), (22.0/25.0, 2.0/3.0)], # alpha=+2
[(0.840, 0.345), (0.997, 0.616), (1.141, 0.843)],
[... | python | def greenhall_table1(alpha, d):
row_idx = int(-alpha+2) # map 2-> row0 and -4-> row6
col_idx = int(d-1)
table1 = [[(2.0/3.0, 1.0/3.0), (7.0/9.0, 1.0/2.0), (22.0/25.0, 2.0/3.0)], # alpha=+2
[(0.840, 0.345), (0.997, 0.616), (1.141, 0.843)],
[(1.079, 0.368), (1.033, 0.607), (1.184, ... | [
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250,741 | aewallin/allantools | allantools/ci.py | edf_mtotdev | def edf_mtotdev(N, m, alpha):
""" Equivalent degrees of freedom for Modified Total Deviation
NIST SP1065 page 41, Table 8
"""
assert(alpha in [2, 1, 0, -1, -2])
NIST_SP1065_table8 = [(1.90, 2.1), (1.20, 1.40), (1.10, 1.2), (0.85, 0.50), (0.75, 0.31)]
#(b, c) = NIST_SP1065_table8[ abs(al... | python | def edf_mtotdev(N, m, alpha):
assert(alpha in [2, 1, 0, -1, -2])
NIST_SP1065_table8 = [(1.90, 2.1), (1.20, 1.40), (1.10, 1.2), (0.85, 0.50), (0.75, 0.31)]
#(b, c) = NIST_SP1065_table8[ abs(alpha-2) ]
(b, c) = NIST_SP1065_table8[abs(alpha-2)]
edf = b*(float(N)/float(m))-c
print("mtotdev b,c= ", (... | [
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250,742 | aewallin/allantools | allantools/ci.py | edf_simple | def edf_simple(N, m, alpha):
"""Equivalent degrees of freedom.
Simple approximate formulae.
Parameters
----------
N : int
the number of phase samples
m : int
averaging factor, tau = m * tau0
alpha: int
exponent of f for the frequency PSD:
'wp' returns white p... | python | def edf_simple(N, m, alpha):
N = float(N)
m = float(m)
if alpha in [2, 1, 0, -1, -2]:
# NIST SP 1065, Table 5
if alpha == +2:
edf = (N + 1) * (N - 2*m) / (2 * (N - m))
if alpha == 0:
edf = (((3 * (N - 1) / (2 * m)) - (2 * (N - 2) / N)) *
((... | [
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"# NIST SP 106... | Equivalent degrees of freedom.
Simple approximate formulae.
Parameters
----------
N : int
the number of phase samples
m : int
averaging factor, tau = m * tau0
alpha: int
exponent of f for the frequency PSD:
'wp' returns white phase noise. alpha=+2
... | [
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250,743 | aewallin/allantools | examples/gradev-demo.py | example1 | def example1():
"""
Compute the GRADEV of a white phase noise. Compares two different
scenarios. 1) The original data and 2) ADEV estimate with gap robust ADEV.
"""
N = 1000
f = 1
y = np.random.randn(1,N)[0,:]
x = [xx for xx in np.linspace(1,len(y),len(y))]
x_ax, y_ax, (err_l, err_h... | python | def example1():
N = 1000
f = 1
y = np.random.randn(1,N)[0,:]
x = [xx for xx in np.linspace(1,len(y),len(y))]
x_ax, y_ax, (err_l, err_h), ns = allan.gradev(y,data_type='phase',rate=f,taus=x)
plt.errorbar(x_ax, y_ax,yerr=[err_l,err_h],label='GRADEV, no gaps')
y[int(np.floor(0.4*N)):i... | [
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250,744 | aewallin/allantools | examples/gradev-demo.py | example2 | def example2():
"""
Compute the GRADEV of a nonstationary white phase noise.
"""
N=1000 # number of samples
f = 1 # data samples per second
s=1+5/N*np.arange(0,N)
y=s*np.random.randn(1,N)[0,:]
x = [xx for xx in np.linspace(1,len(y),len(y))]
x_ax, y_ax, (err_l, err_h) , ns = allan.gra... | python | def example2():
N=1000 # number of samples
f = 1 # data samples per second
s=1+5/N*np.arange(0,N)
y=s*np.random.randn(1,N)[0,:]
x = [xx for xx in np.linspace(1,len(y),len(y))]
x_ax, y_ax, (err_l, err_h) , ns = allan.gradev(y,data_type='phase',rate=f,taus=x)
plt.loglog(x_ax, y_ax,'b.',label="... | [
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250,745 | aewallin/allantools | allantools/allantools.py | tdev | def tdev(data, rate=1.0, data_type="phase", taus=None):
""" Time deviation.
Based on modified Allan variance.
.. math::
\\sigma^2_{TDEV}( \\tau ) = { \\tau^2 \\over 3 }
\\sigma^2_{MDEV}( \\tau )
Note that TDEV has a unit of seconds.
Parameters
----------
data: np.arra... | python | def tdev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(taus, md, mde, ns) = mdev(phase, rate=rate, taus=taus)
td = taus * md / np.sqrt(3.0)
tde = td / np.sqrt(ns)
return taus, td, tde, ns | [
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\\sigma^2_{MDEV}( \\tau )
Note that TDEV has a unit of seconds.
Parameters
----------
data: np.array
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250,746 | aewallin/allantools | allantools/allantools.py | mdev | def mdev(data, rate=1.0, data_type="phase", taus=None):
""" Modified Allan deviation.
Used to distinguish between White and Flicker Phase Modulation.
.. math::
\\sigma^2_{MDEV}(m\\tau_0) = { 1 \\over 2 (m \\tau_0 )^2 (N-3m+1) }
\\sum_{j=1}^{N-3m+1} \\lbrace
\\sum_{i=j}^{j+m-1... | python | def mdev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, ms, taus_used) = tau_generator(phase, rate, taus=taus)
data, taus = np.array(phase), np.array(taus)
md = np.zeros_like(ms)
mderr = np.zeros_like(ms)
ns = np.zeros_like(ms)
# this i... | [
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Used to distinguish between White and Flicker Phase Modulation.
.. math::
\\sigma^2_{MDEV}(m\\tau_0) = { 1 \\over 2 (m \\tau_0 )^2 (N-3m+1) }
\\sum_{j=1}^{N-3m+1} \\lbrace
\\sum_{i=j}^{j+m-1} {x}_{i+2m} - 2x_{i+m} + x_{i} \\rbrace^2
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250,747 | aewallin/allantools | allantools/allantools.py | adev | def adev(data, rate=1.0, data_type="phase", taus=None):
""" Allan deviation.
Classic - use only if required - relatively poor confidence.
.. math::
\\sigma^2_{ADEV}(\\tau) = { 1 \\over 2 \\tau^2 }
\\langle ( {x}_{n+2} - 2x_{n+1} + x_{n} )^2 \\rangle
= { 1 \\over 2 (N-2) \\tau^2... | python | def adev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, m, taus_used) = tau_generator(phase, rate, taus)
ad = np.zeros_like(taus_used)
ade = np.zeros_like(taus_used)
adn = np.zeros_like(taus_used)
for idx, mj in enumerate(m): # loop throug... | [
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\\langle ( {x}_{n+2} - 2x_{n+1} + x_{n} )^2 \\rangle
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250,748 | aewallin/allantools | allantools/allantools.py | ohdev | def ohdev(data, rate=1.0, data_type="phase", taus=None):
""" Overlapping Hadamard deviation.
Better confidence than normal Hadamard.
.. math::
\\sigma^2_{OHDEV}(m\\tau_0) = { 1 \\over 6 (m \\tau_0 )^2 (N-3m) }
\\sum_{i=1}^{N-3m} ( {x}_{i+3m} - 3x_{i+2m} + 3x_{i+m} - x_{i} )^2
wher... | python | def ohdev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, m, taus_used) = tau_generator(phase, rate, taus)
hdevs = np.zeros_like(taus_used)
hdeverrs = np.zeros_like(taus_used)
ns = np.zeros_like(taus_used)
for idx, mj in enumerate(m):
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Better confidence than normal Hadamard.
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\\sum_{i=1}^{N-3m} ( {x}_{i+3m} - 3x_{i+2m} + 3x_{i+m} - x_{i} )^2
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250,749 | aewallin/allantools | allantools/allantools.py | calc_hdev_phase | def calc_hdev_phase(phase, rate, mj, stride):
""" main calculation fungtion for HDEV and OHDEV
Parameters
----------
phase: np.array
Phase data in seconds.
rate: float
The sampling rate for phase or frequency, in Hz
mj: int
M index value for stride
stride: int
... | python | def calc_hdev_phase(phase, rate, mj, stride):
tau0 = 1.0 / float(rate)
mj = int(mj)
stride = int(stride)
d3 = phase[3 * mj::stride]
d2 = phase[2 * mj::stride]
d1 = phase[1 * mj::stride]
d0 = phase[::stride]
n = min(len(d0), len(d1), len(d2), len(d3))
v_arr = d3[:n] - 3 * d2[:n] + 3... | [
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Parameters
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phase: np.array
Phase data in seconds.
rate: float
The sampling rate for phase or frequency, in Hz
mj: int
M index value for stride
stride: int
Size of stride
Returns
-------
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250,750 | aewallin/allantools | allantools/allantools.py | totdev | def totdev(data, rate=1.0, data_type="phase", taus=None):
""" Total deviation.
Better confidence at long averages for Allan.
.. math::
\\sigma^2_{TOTDEV}( m\\tau_0 ) = { 1 \\over 2 (m\\tau_0)^2 (N-2) }
\\sum_{i=2}^{N-1} ( {x}^*_{i-m} - 2x^*_{i} + x^*_{i+m} )^2
Where :math:`x^... | python | def totdev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, m, taus_used) = tau_generator(phase, rate, taus)
N = len(phase)
# totdev requires a new dataset
# Begin by adding reflected data before dataset
x1 = 2.0 * phase[0] * np.ones((N - 2,))... | [
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Better confidence at long averages for Allan.
.. math::
\\sigma^2_{TOTDEV}( m\\tau_0 ) = { 1 \\over 2 (m\\tau_0)^2 (N-2) }
\\sum_{i=2}^{N-1} ( {x}^*_{i-m} - 2x^*_{i} + x^*_{i+m} )^2
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250,751 | aewallin/allantools | allantools/allantools.py | mtotdev | def mtotdev(data, rate=1.0, data_type="phase", taus=None):
""" PRELIMINARY - REQUIRES FURTHER TESTING.
Modified Total deviation.
Better confidence at long averages for modified Allan
FIXME: bias-correction http://www.wriley.com/CI2.pdf page 6
The variance is scaled up (divided by t... | python | def mtotdev(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, ms, taus_used) = tau_generator(phase, rate, taus,
maximum_m=float(len(phase))/3.0)
devs = np.zeros_like(taus_used)
deverrs = np.zeros_like(taus_used... | [
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Better confidence at long averages for modified Allan
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250,752 | aewallin/allantools | allantools/allantools.py | htotdev | def htotdev(data, rate=1.0, data_type="phase", taus=None):
""" PRELIMINARY - REQUIRES FURTHER TESTING.
Hadamard Total deviation.
Better confidence at long averages for Hadamard deviation
FIXME: bias corrections from http://www.wriley.com/CI2.pdf
W FM 0.995 alpha= 0
F... | python | def htotdev(data, rate=1.0, data_type="phase", taus=None):
if data_type == "phase":
phase = data
freq = phase2frequency(phase, rate)
elif data_type == "freq":
phase = frequency2phase(data, rate)
freq = data
else:
raise Exception("unknown data_type: " + data_type)
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250,753 | aewallin/allantools | allantools/allantools.py | theo1 | def theo1(data, rate=1.0, data_type="phase", taus=None):
""" PRELIMINARY - REQUIRES FURTHER TESTING.
Theo1 is a two-sample variance with improved confidence and
extended averaging factor range.
.. math::
\\sigma^2_{THEO1}(m\\tau_0) = { 1 \\over (m \\tau_0 )^2 (N-m) }
... | python | def theo1(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
tau0 = 1.0/rate
(phase, ms, taus_used) = tau_generator(phase, rate, taus, even=True)
devs = np.zeros_like(taus_used)
deverrs = np.zeros_like(taus_used)
ns = np.zeros_like(taus_used)
N = ... | [
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250,754 | aewallin/allantools | allantools/allantools.py | tierms | def tierms(data, rate=1.0, data_type="phase", taus=None):
""" Time Interval Error RMS.
Parameters
----------
data: np.array
Input data. Provide either phase or frequency (fractional,
adimensional).
rate: float
The sampling rate for data, in Hz. Defaults to 1.0
data_type:... | python | def tierms(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(data, m, taus_used) = tau_generator(phase, rate, taus)
count = len(phase)
devs = np.zeros_like(taus_used)
deverrs = np.zeros_like(taus_used)
ns = np.zeros_like(taus_used)
for idx, mj i... | [
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250,755 | aewallin/allantools | allantools/allantools.py | mtie | def mtie(data, rate=1.0, data_type="phase", taus=None):
""" Maximum Time Interval Error.
Parameters
----------
data: np.array
Input data. Provide either phase or frequency (fractional,
adimensional).
rate: float
The sampling rate for data, in Hz. Defaults to 1.0
data_typ... | python | def mtie(data, rate=1.0, data_type="phase", taus=None):
phase = input_to_phase(data, rate, data_type)
(phase, m, taus_used) = tau_generator(phase, rate, taus)
devs = np.zeros_like(taus_used)
deverrs = np.zeros_like(taus_used)
ns = np.zeros_like(taus_used)
for idx, mj in enumerate(m):
rw... | [
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The sampling rate for data, in Hz. Defaults to 1.0
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250,756 | aewallin/allantools | allantools/allantools.py | mtie_phase_fast | def mtie_phase_fast(phase, rate=1.0, data_type="phase", taus=None):
""" fast binary decomposition algorithm for MTIE
See: STEFANO BREGNI "Fast Algorithms for TVAR and MTIE Computation in
Characterization of Network Synchronization Performance"
"""
rate = float(rate)
phase = np.asarray(p... | python | def mtie_phase_fast(phase, rate=1.0, data_type="phase", taus=None):
rate = float(rate)
phase = np.asarray(phase)
k_max = int(np.floor(np.log2(len(phase))))
phase = phase[0:pow(2, k_max)] # truncate data to 2**k_max datapoints
assert len(phase) == pow(2, k_max)
#k = 1
taus = [ pow(2,k) for k ... | [
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250,757 | aewallin/allantools | allantools/allantools.py | gradev | def gradev(data, rate=1.0, data_type="phase", taus=None,
ci=0.9, noisetype='wp'):
""" gap resistant overlapping Allan deviation
Parameters
----------
data: np.array
Input data. Provide either phase or frequency (fractional,
adimensional). Warning : phase data works better (fr... | python | def gradev(data, rate=1.0, data_type="phase", taus=None,
ci=0.9, noisetype='wp'):
if (data_type == "freq"):
print("Warning : phase data is preferred as input to gradev()")
phase = input_to_phase(data, rate, data_type)
(data, m, taus_used) = tau_generator(phase, rate, taus)
ad = np.ze... | [
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250,758 | aewallin/allantools | allantools/allantools.py | input_to_phase | def input_to_phase(data, rate, data_type):
""" Take either phase or frequency as input and return phase
"""
if data_type == "phase":
return data
elif data_type == "freq":
return frequency2phase(data, rate)
else:
raise Exception("unknown data_type: " + data_type) | python | def input_to_phase(data, rate, data_type):
if data_type == "phase":
return data
elif data_type == "freq":
return frequency2phase(data, rate)
else:
raise Exception("unknown data_type: " + data_type) | [
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250,759 | aewallin/allantools | allantools/allantools.py | trim_data | def trim_data(x):
"""
Trim leading and trailing NaNs from dataset
This is done by browsing the array from each end and store the index of the
first non-NaN in each case, the return the appropriate slice of the array
"""
# Find indices for first and last valid data
first = 0
while np.isna... | python | def trim_data(x):
# Find indices for first and last valid data
first = 0
while np.isnan(x[first]):
first += 1
last = len(x)
while np.isnan(x[last - 1]):
last -= 1
return x[first:last] | [
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250,760 | aewallin/allantools | allantools/allantools.py | three_cornered_hat_phase | def three_cornered_hat_phase(phasedata_ab, phasedata_bc,
phasedata_ca, rate, taus, function):
"""
Three Cornered Hat Method
Given three clocks A, B, C, we seek to find their variances
:math:`\\sigma^2_A`, :math:`\\sigma^2_B`, :math:`\\sigma^2_C`.
We measure three phase ... | python | def three_cornered_hat_phase(phasedata_ab, phasedata_bc,
phasedata_ca, rate, taus, function):
(tau_ab, dev_ab, err_ab, ns_ab) = function(phasedata_ab,
data_type='phase',
rate=rate, taus=taus)
... | [
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.. math::
\\sigma^2_{AB} = ... | [
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250,761 | aewallin/allantools | allantools/allantools.py | frequency2phase | def frequency2phase(freqdata, rate):
""" integrate fractional frequency data and output phase data
Parameters
----------
freqdata: np.array
Data array of fractional frequency measurements (nondimensional)
rate: float
The sampling rate for phase or frequency, in Hz
Returns
-... | python | def frequency2phase(freqdata, rate):
dt = 1.0 / float(rate)
# Protect against NaN values in input array (issue #60)
# Reintroduces data trimming as in commit 503cb82
freqdata = trim_data(freqdata)
phasedata = np.cumsum(freqdata) * dt
phasedata = np.insert(phasedata, 0, 0) # FIXME: why do we do t... | [
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250,762 | aewallin/allantools | allantools/allantools.py | phase2radians | def phase2radians(phasedata, v0):
""" Convert phase in seconds to phase in radians
Parameters
----------
phasedata: np.array
Data array of phase in seconds
v0: float
Nominal oscillator frequency in Hz
Returns
-------
fi:
phase data in radians
"""
fi = [2... | python | def phase2radians(phasedata, v0):
fi = [2*np.pi*v0*xx for xx in phasedata]
return fi | [
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phasedata: np.array
Data array of phase in seconds
v0: float
Nominal oscillator frequency in Hz
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-------
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250,763 | aewallin/allantools | allantools/allantools.py | frequency2fractional | def frequency2fractional(frequency, mean_frequency=-1):
""" Convert frequency in Hz to fractional frequency
Parameters
----------
frequency: np.array
Data array of frequency in Hz
mean_frequency: float
(optional) The nominal mean frequency, in Hz
if omitted, defaults to mean... | python | def frequency2fractional(frequency, mean_frequency=-1):
if mean_frequency == -1:
mu = np.mean(frequency)
else:
mu = mean_frequency
y = [(x-mu)/mu for x in frequency]
return y | [
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250,764 | aewallin/allantools | allantools/dataset.py | Dataset.set_input | def set_input(self, data,
rate=1.0, data_type="phase", taus=None):
""" Optionnal method if you chose not to set inputs on init
Parameters
----------
data: np.array
Input data. Provide either phase or frequency (fractional,
adimensional)
... | python | def set_input(self, data,
rate=1.0, data_type="phase", taus=None):
self.inp["data"] = data
self.inp["rate"] = rate
self.inp["data_type"] = data_type
self.inp["taus"] = taus | [
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250,765 | aewallin/allantools | allantools/dataset.py | Dataset.compute | def compute(self, function):
"""Evaluate the passed function with the supplied data.
Stores result in self.out.
Parameters
----------
function: str
Name of the :mod:`allantools` function to evaluate
Returns
-------
result: dict
T... | python | def compute(self, function):
try:
func = getattr(allantools, function)
except AttributeError:
raise AttributeError("function must be defined in allantools")
whitelisted = ["theo1", "mtie", "tierms"]
if function[-3:] != "dev" and function not in whitelisted:
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250,766 | aewallin/allantools | examples/noise-color_and_PSD.py | many_psds | def many_psds(k=2,fs=1.0, b0=1.0, N=1024):
""" compute average of many PSDs """
psd=[]
for j in range(k):
print j
x = noise.white(N=2*4096,b0=b0,fs=fs)
f, tmp = noise.numpy_psd(x,fs)
if j==0:
psd = tmp
else:
psd = psd + tmp
return f, psd/k | python | def many_psds(k=2,fs=1.0, b0=1.0, N=1024):
psd=[]
for j in range(k):
print j
x = noise.white(N=2*4096,b0=b0,fs=fs)
f, tmp = noise.numpy_psd(x,fs)
if j==0:
psd = tmp
else:
psd = psd + tmp
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250,767 | singnet/snet-cli | snet_cli/commands.py | OrganizationCommand.list_my | def list_my(self):
""" Find organization that has the current identity as the owner or as the member """
org_list = self.call_contract_command("Registry", "listOrganizations", [])
rez_owner = []
rez_member = []
for idx, org_id in enumerate(org_list):
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org_list = self.call_contract_command("Registry", "listOrganizations", [])
rez_owner = []
rez_member = []
for idx, org_id in enumerate(org_list):
(found, org_id, org_name, owner, members, serviceNames, repositoryNames) = self.call_contract_command("Regist... | [
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250,768 | singnet/snet-cli | snet_cli/mpe_service_metadata.py | MPEServiceMetadata.add_group | def add_group(self, group_name, payment_address):
""" Return new group_id in base64 """
if (self.is_group_name_exists(group_name)):
raise Exception("the group \"%s\" is already present"%str(group_name))
group_id_base64 = base64.b64encode(secrets.token_bytes(32))
self.m["group... | python | def add_group(self, group_name, payment_address):
if (self.is_group_name_exists(group_name)):
raise Exception("the group \"%s\" is already present"%str(group_name))
group_id_base64 = base64.b64encode(secrets.token_bytes(32))
self.m["groups"] += [{"group_name" : group_name ,
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250,769 | singnet/snet-cli | snet_cli/mpe_service_metadata.py | MPEServiceMetadata.is_group_name_exists | def is_group_name_exists(self, group_name):
""" check if group with given name is already exists """
groups = self.m["groups"]
for g in groups:
if (g["group_name"] == group_name):
return True
return False | python | def is_group_name_exists(self, group_name):
groups = self.m["groups"]
for g in groups:
if (g["group_name"] == group_name):
return True
return False | [
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250,770 | singnet/snet-cli | snet_cli/mpe_service_metadata.py | MPEServiceMetadata.get_group_name_nonetrick | def get_group_name_nonetrick(self, group_name = None):
""" In all getter function in case of single payment group, group_name can be None """
groups = self.m["groups"]
if (len(groups) == 0):
raise Exception("Cannot find any groups in metadata")
if (not group_name):
... | python | def get_group_name_nonetrick(self, group_name = None):
groups = self.m["groups"]
if (len(groups) == 0):
raise Exception("Cannot find any groups in metadata")
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250,771 | singnet/snet-cli | snet_cli/utils_ipfs.py | get_from_ipfs_and_checkhash | def get_from_ipfs_and_checkhash(ipfs_client, ipfs_hash_base58, validate=True):
"""
Get file from ipfs
We must check the hash becasue we cannot believe that ipfs_client wasn't been compromise
"""
if validate:
from snet_cli.resources.proto.unixfs_pb2 import Data
from snet_cli.resources... | python | def get_from_ipfs_and_checkhash(ipfs_client, ipfs_hash_base58, validate=True):
if validate:
from snet_cli.resources.proto.unixfs_pb2 import Data
from snet_cli.resources.proto.merckledag_pb2 import MerkleNode
# No nice Python library to parse ipfs blocks, so do it ourselves.
block_da... | [
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250,772 | singnet/snet-cli | snet_cli/utils_ipfs.py | hash_to_bytesuri | def hash_to_bytesuri(s):
"""
Convert in and from bytes uri format used in Registry contract
"""
# TODO: we should pad string with zeros till closest 32 bytes word because of a bug in processReceipt (in snet_cli.contract.process_receipt)
s = "ipfs://" + s
return s.encode("ascii").ljust(32 * (len(... | python | def hash_to_bytesuri(s):
# TODO: we should pad string with zeros till closest 32 bytes word because of a bug in processReceipt (in snet_cli.contract.process_receipt)
s = "ipfs://" + s
return s.encode("ascii").ljust(32 * (len(s)//32 + 1), b"\0") | [
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250,773 | singnet/snet-cli | snet_cli/mpe_treasurer_command.py | MPETreasurerCommand._get_stub_and_request_classes | def _get_stub_and_request_classes(self, service_name):
""" import protobuf and return stub and request class """
# Compile protobuf if needed
codegen_dir = Path.home().joinpath(".snet", "mpe_client", "control_service")
proto_dir = Path(__file__).absolute().parent.joinpath("resources", ... | python | def _get_stub_and_request_classes(self, service_name):
# Compile protobuf if needed
codegen_dir = Path.home().joinpath(".snet", "mpe_client", "control_service")
proto_dir = Path(__file__).absolute().parent.joinpath("resources", "proto")
if (not codegen_dir.joinpath("control_service_pb2... | [
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250,774 | singnet/snet-cli | snet_cli/mpe_treasurer_command.py | MPETreasurerCommand._start_claim_channels | def _start_claim_channels(self, grpc_channel, channels_ids):
""" Safely run StartClaim for given channels """
unclaimed_payments = self._call_GetListUnclaimed(grpc_channel)
unclaimed_payments_dict = {p["channel_id"] : p for p in unclaimed_payments}
to_claim = []
for channel_id i... | python | def _start_claim_channels(self, grpc_channel, channels_ids):
unclaimed_payments = self._call_GetListUnclaimed(grpc_channel)
unclaimed_payments_dict = {p["channel_id"] : p for p in unclaimed_payments}
to_claim = []
for channel_id in channels_ids:
if (channel_id not in unclaim... | [
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250,775 | singnet/snet-cli | snet_cli/mpe_treasurer_command.py | MPETreasurerCommand._claim_in_progress_and_claim_channels | def _claim_in_progress_and_claim_channels(self, grpc_channel, channels):
""" Claim all 'pending' payments in progress and after we claim given channels """
# first we get the list of all 'payments in progress' in case we 'lost' some payments.
payments = self._call_GetListInProgress(grpc_channel)... | python | def _claim_in_progress_and_claim_channels(self, grpc_channel, channels):
# first we get the list of all 'payments in progress' in case we 'lost' some payments.
payments = self._call_GetListInProgress(grpc_channel)
if (len(payments) > 0):
self._printout("There are %i payments in 'prog... | [
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250,776 | singnet/snet-cli | snet_cli/config.py | Config.create_default_config | def create_default_config(self):
""" Create default configuration if config file does not exist """
# make config directory with the minimal possible permission
self._config_file.parent.mkdir(mode=0o700, exist_ok=True)
self["network.kovan"] = {"default_eth_rpc_endpoint": "https://kovan... | python | def create_default_config(self):
# make config directory with the minimal possible permission
self._config_file.parent.mkdir(mode=0o700, exist_ok=True)
self["network.kovan"] = {"default_eth_rpc_endpoint": "https://kovan.infura.io", "default_gas_price" : "medium"}
self["network.mainne... | [
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250,777 | singnet/snet-cli | snet_cli/utils_proto.py | switch_to_json_payload_encoding | def switch_to_json_payload_encoding(call_fn, response_class):
""" Switch payload encoding to JSON for GRPC call """
def json_serializer(*args, **kwargs):
return bytes(json_format.MessageToJson(args[0], True, preserving_proto_field_name=True), "utf-8")
def json_deserializer(*args, **kwargs):
... | python | def switch_to_json_payload_encoding(call_fn, response_class):
def json_serializer(*args, **kwargs):
return bytes(json_format.MessageToJson(args[0], True, preserving_proto_field_name=True), "utf-8")
def json_deserializer(*args, **kwargs):
resp = response_class()
json_format.Parse(args[0],... | [
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250,778 | singnet/snet-cli | snet_cli/mpe_account_command.py | MPEAccountCommand.print_agi_and_mpe_balances | def print_agi_and_mpe_balances(self):
""" Print balance of ETH, AGI, and MPE wallet """
if (self.args.account):
account = self.args.account
else:
account = self.ident.address
eth_wei = self.w3.eth.getBalance(account)
agi_cogs = self.call_contract_command(... | python | def print_agi_and_mpe_balances(self):
if (self.args.account):
account = self.args.account
else:
account = self.ident.address
eth_wei = self.w3.eth.getBalance(account)
agi_cogs = self.call_contract_command("SingularityNetToken", "balanceOf", [account])
mpe... | [
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250,779 | singnet/snet-cli | snet_cli/mpe_service_command.py | MPEServiceCommand.publish_proto_in_ipfs | def publish_proto_in_ipfs(self):
""" Publish proto files in ipfs and print hash """
ipfs_hash_base58 = utils_ipfs.publish_proto_in_ipfs(self._get_ipfs_client(), self.args.protodir)
self._printout(ipfs_hash_base58) | python | def publish_proto_in_ipfs(self):
ipfs_hash_base58 = utils_ipfs.publish_proto_in_ipfs(self._get_ipfs_client(), self.args.protodir)
self._printout(ipfs_hash_base58) | [
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250,780 | singnet/snet-cli | snet_cli/mpe_service_command.py | MPEServiceCommand.publish_proto_metadata_update | def publish_proto_metadata_update(self):
""" Publish protobuf model in ipfs and update existing metadata file """
metadata = load_mpe_service_metadata(self.args.metadata_file)
ipfs_hash_base58 = utils_ipfs.publish_proto_in_ipfs(self._get_ipfs_client(), self.args.protodir)
metadata.set_si... | python | def publish_proto_metadata_update(self):
metadata = load_mpe_service_metadata(self.args.metadata_file)
ipfs_hash_base58 = utils_ipfs.publish_proto_in_ipfs(self._get_ipfs_client(), self.args.protodir)
metadata.set_simple_field("model_ipfs_hash", ipfs_hash_base58)
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250,781 | singnet/snet-cli | snet_cli/mpe_channel_command.py | MPEChannelCommand._get_persistent_mpe_dir | def _get_persistent_mpe_dir(self):
""" get persistent storage for mpe """
mpe_address = self.get_mpe_address().lower()
registry_address = self.get_registry_address().lower()
return Path.home().joinpath(".snet", "mpe_client", "%s_%s"%(mpe_address, registry_address)) | python | def _get_persistent_mpe_dir(self):
mpe_address = self.get_mpe_address().lower()
registry_address = self.get_registry_address().lower()
return Path.home().joinpath(".snet", "mpe_client", "%s_%s"%(mpe_address, registry_address)) | [
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250,782 | singnet/snet-cli | snet_cli/mpe_channel_command.py | MPEChannelCommand._check_mpe_address_metadata | def _check_mpe_address_metadata(self, metadata):
""" we make sure that MultiPartyEscrow address from metadata is correct """
mpe_address = self.get_mpe_address()
if (str(mpe_address).lower() != str(metadata["mpe_address"]).lower()):
raise Exception("MultiPartyEscrow contract address ... | python | def _check_mpe_address_metadata(self, metadata):
mpe_address = self.get_mpe_address()
if (str(mpe_address).lower() != str(metadata["mpe_address"]).lower()):
raise Exception("MultiPartyEscrow contract address from metadata %s do not correspond to current MultiPartyEscrow address %s"%(metadata... | [
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250,783 | singnet/snet-cli | snet_cli/mpe_channel_command.py | MPEChannelCommand._init_or_update_registered_service_if_needed | def _init_or_update_registered_service_if_needed(self):
'''
similar to _init_or_update_service_if_needed but we get service_registraion from registry,
so we can update only registered services
'''
if (self.is_service_initialized()):
old_reg = self._read_service_info(s... | python | def _init_or_update_registered_service_if_needed(self):
'''
similar to _init_or_update_service_if_needed but we get service_registraion from registry,
so we can update only registered services
'''
if (self.is_service_initialized()):
old_reg = self._read_service_info(s... | [
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250,784 | singnet/snet-cli | snet_cli/mpe_channel_command.py | MPEChannelCommand._smart_get_initialized_channel_for_service | def _smart_get_initialized_channel_for_service(self, metadata, filter_by, is_try_initailize = True):
'''
- filter_by can be sender or signer
'''
channels = self._get_initialized_channels_for_service(self.args.org_id, self.args.service_id)
group_id = metadata.get_group_id(self.ar... | python | def _smart_get_initialized_channel_for_service(self, metadata, filter_by, is_try_initailize = True):
'''
- filter_by can be sender or signer
'''
channels = self._get_initialized_channels_for_service(self.args.org_id, self.args.service_id)
group_id = metadata.get_group_id(self.ar... | [
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250,785 | singnet/snet-cli | snet_cli/mpe_channel_command.py | MPEChannelCommand._get_all_filtered_channels | def _get_all_filtered_channels(self, topics_without_signature):
""" get all filtered chanels from blockchain logs """
mpe_address = self.get_mpe_address()
event_signature = self.ident.w3.sha3(text="ChannelOpen(uint256,uint256,address,address,address,bytes32,uint256,uint256)").hex()
t... | python | def _get_all_filtered_channels(self, topics_without_signature):
mpe_address = self.get_mpe_address()
event_signature = self.ident.w3.sha3(text="ChannelOpen(uint256,uint256,address,address,address,bytes32,uint256,uint256)").hex()
topics = [event_signature] + topics_without_signature
l... | [
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250,786 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.list_repo | def list_repo(self):
"""
Returns info about all Repos.
"""
req = proto.ListRepoRequest()
res = self.stub.ListRepo(req, metadata=self.metadata)
if hasattr(res, 'repo_info'):
return res.repo_info
return [] | python | def list_repo(self):
req = proto.ListRepoRequest()
res = self.stub.ListRepo(req, metadata=self.metadata)
if hasattr(res, 'repo_info'):
return res.repo_info
return [] | [
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250,787 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.delete_repo | def delete_repo(self, repo_name=None, force=False, all=False):
"""
Deletes a repo and reclaims the storage space it was using.
Params:
* repo_name: The name of the repo.
* force: If set to true, the repo will be removed regardless of
errors. This argument should be used ... | python | def delete_repo(self, repo_name=None, force=False, all=False):
if not all:
if repo_name:
req = proto.DeleteRepoRequest(repo=proto.Repo(name=repo_name), force=force)
self.stub.DeleteRepo(req, metadata=self.metadata)
else:
raise ValueError("E... | [
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250,788 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.start_commit | def start_commit(self, repo_name, branch=None, parent=None, description=None):
"""
Begins the process of committing data to a Repo. Once started you can
write to the Commit with PutFile and when all the data has been
written you must finish the Commit with FinishCommit. NOTE, data is
... | python | def start_commit(self, repo_name, branch=None, parent=None, description=None):
req = proto.StartCommitRequest(parent=proto.Commit(repo=proto.Repo(name=repo_name), id=parent), branch=branch,
description=description)
res = self.stub.StartCommit(req, metadata=self.met... | [
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250,789 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.finish_commit | def finish_commit(self, commit):
"""
Ends the process of committing data to a Repo and persists the
Commit. Once a Commit is finished the data becomes immutable and
future attempts to write to it with PutFile will error.
Params:
* commit: A tuple, string, or Commit objec... | python | def finish_commit(self, commit):
req = proto.FinishCommitRequest(commit=commit_from(commit))
res = self.stub.FinishCommit(req, metadata=self.metadata)
return res | [
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250,790 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.commit | def commit(self, repo_name, branch=None, parent=None, description=None):
"""A context manager for doing stuff inside a commit."""
commit = self.start_commit(repo_name, branch, parent, description)
try:
yield commit
except Exception as e:
print("An exception occurr... | python | def commit(self, repo_name, branch=None, parent=None, description=None):
commit = self.start_commit(repo_name, branch, parent, description)
try:
yield commit
except Exception as e:
print("An exception occurred during an open commit. "
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250,791 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.inspect_commit | def inspect_commit(self, commit):
"""
Returns info about a specific Commit.
Params:
* commit: A tuple, string, or Commit object representing the commit.
"""
req = proto.InspectCommitRequest(commit=commit_from(commit))
return self.stub.InspectCommit(req, metadata=... | python | def inspect_commit(self, commit):
req = proto.InspectCommitRequest(commit=commit_from(commit))
return self.stub.InspectCommit(req, metadata=self.metadata) | [
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250,792 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.list_commit | def list_commit(self, repo_name, to_commit=None, from_commit=None, number=0):
"""
Gets a list of CommitInfo objects.
Params:
* repo_name: If only `repo_name` is given, all commits in the repo are
returned.
* to_commit: Optional. Only the ancestors of `to`, including `to`... | python | def list_commit(self, repo_name, to_commit=None, from_commit=None, number=0):
req = proto.ListCommitRequest(repo=proto.Repo(name=repo_name), number=number)
if to_commit is not None:
req.to.CopyFrom(commit_from(to_commit))
if from_commit is not None:
getattr(req, 'from').C... | [
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250,793 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.delete_commit | def delete_commit(self, commit):
"""
Deletes a commit.
Params:
* commit: A tuple, string, or Commit object representing the commit.
"""
req = proto.DeleteCommitRequest(commit=commit_from(commit))
self.stub.DeleteCommit(req, metadata=self.metadata) | python | def delete_commit(self, commit):
req = proto.DeleteCommitRequest(commit=commit_from(commit))
self.stub.DeleteCommit(req, metadata=self.metadata) | [
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250,794 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.flush_commit | def flush_commit(self, commits, repos=tuple()):
"""
Blocks until all of the commits which have a set of commits as
provenance have finished. For commits to be considered they must have
all of the specified commits as provenance. This in effect waits for
all of the jobs that are t... | python | def flush_commit(self, commits, repos=tuple()):
req = proto.FlushCommitRequest(commit=[commit_from(c) for c in commits],
to_repo=[proto.Repo(name=r) for r in repos])
res = self.stub.FlushCommit(req, metadata=self.metadata)
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250,795 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.subscribe_commit | def subscribe_commit(self, repo_name, branch, from_commit_id=None):
"""
SubscribeCommit is like ListCommit but it keeps listening for commits as
they come in. This returns an iterator Commit objects.
Params:
* repo_name: Name of the repo.
* branch: Branch to subscribe to... | python | def subscribe_commit(self, repo_name, branch, from_commit_id=None):
repo = proto.Repo(name=repo_name)
req = proto.SubscribeCommitRequest(repo=repo, branch=branch)
if from_commit_id is not None:
getattr(req, 'from').CopyFrom(proto.Commit(repo=repo, id=from_commit_id))
res = se... | [
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250,796 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.list_branch | def list_branch(self, repo_name):
"""
Lists the active Branch objects on a Repo.
Params:
* repo_name: The name of the repo.
"""
req = proto.ListBranchRequest(repo=proto.Repo(name=repo_name))
res = self.stub.ListBranch(req, metadata=self.metadata)
if hasat... | python | def list_branch(self, repo_name):
req = proto.ListBranchRequest(repo=proto.Repo(name=repo_name))
res = self.stub.ListBranch(req, metadata=self.metadata)
if hasattr(res, 'branch_info'):
return res.branch_info
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] | 1c58cf91d30e03716a4f45213989e890f7b8a78c | https://github.com/pachyderm/python-pachyderm/blob/1c58cf91d30e03716a4f45213989e890f7b8a78c/src/python_pachyderm/pfs_client.py#L253-L264 |
250,797 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.set_branch | def set_branch(self, commit, branch_name):
"""
Sets a commit and its ancestors as a branch.
Params:
* commit: A tuple, string, or Commit object representing the commit.
* branch_name: The name for the branch to set.
"""
res = proto.SetBranchRequest(commit=commit_... | python | def set_branch(self, commit, branch_name):
res = proto.SetBranchRequest(commit=commit_from(commit), branch=branch_name)
self.stub.SetBranch(res, metadata=self.metadata) | [
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] | 1c58cf91d30e03716a4f45213989e890f7b8a78c | https://github.com/pachyderm/python-pachyderm/blob/1c58cf91d30e03716a4f45213989e890f7b8a78c/src/python_pachyderm/pfs_client.py#L266-L275 |
250,798 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.delete_branch | def delete_branch(self, repo_name, branch_name):
"""
Deletes a branch, but leaves the commits themselves intact. In other
words, those commits can still be accessed via commit IDs and other
branches they happen to be on.
Params:
* repo_name: The name of the repo.
... | python | def delete_branch(self, repo_name, branch_name):
res = proto.DeleteBranchRequest(repo=Repo(name=repo_name), branch=branch_name)
self.stub.DeleteBranch(res, metadata=self.metadata) | [
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* branch_name: The name of the branch to delete. | [
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250,799 | pachyderm/python-pachyderm | src/python_pachyderm/pfs_client.py | PfsClient.put_file_url | def put_file_url(self, commit, path, url, recursive=False):
"""
Puts a file using the content found at a URL. The URL is sent to the
server which performs the request.
Params:
* commit: A tuple, string, or Commit object representing the commit.
* path: The path to the fi... | python | def put_file_url(self, commit, path, url, recursive=False):
req = iter([
proto.PutFileRequest(
file=proto.File(commit=commit_from(commit), path=path),
url=url,
recursive=recursive
)
])
self.stub.PutFile(req, metadata=self.me... | [
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Params:
* commit: A tuple, string, or Commit object representing the commit.
* path: The path to the file.
* url: The url of the file to put.
* recursive: allow for re... | [
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] | 1c58cf91d30e03716a4f45213989e890f7b8a78c | https://github.com/pachyderm/python-pachyderm/blob/1c58cf91d30e03716a4f45213989e890f7b8a78c/src/python_pachyderm/pfs_client.py#L363-L382 |
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