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what-studio/profiling | profiling/viewer.py | StatisticsWidget.get_mark | def get_mark(self):
"""Gets an expanded, collapsed, or leaf icon."""
if self.is_leaf:
char = self.icon_chars[2]
else:
char = self.icon_chars[int(self.expanded)]
return urwid.SelectableIcon(('mark', char), 0) | python | def get_mark(self):
"""Gets an expanded, collapsed, or leaf icon."""
if self.is_leaf:
char = self.icon_chars[2]
else:
char = self.icon_chars[int(self.expanded)]
return urwid.SelectableIcon(('mark', char), 0) | [
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what-studio/profiling | profiling/viewer.py | StatisticsTable.get_path | def get_path(self):
"""Gets the path to the focused statistics. Each step is a hash of
statistics object.
"""
path = deque()
__, node = self.get_focus()
while not node.is_root():
stats = node.get_value()
path.appendleft(hash(stats))
nod... | python | def get_path(self):
"""Gets the path to the focused statistics. Each step is a hash of
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"""
path = deque()
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while not node.is_root():
stats = node.get_value()
path.appendleft(hash(stats))
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what-studio/profiling | profiling/viewer.py | StatisticsTable.find_node | def find_node(self, node, path):
"""Finds a node by the given path from the given node."""
for hash_value in path:
if isinstance(node, LeafStatisticsNode):
break
for stats in node.get_child_keys():
if hash(stats) == hash_value:
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"""Finds a node by the given path from the given node."""
for hash_value in path:
if isinstance(node, LeafStatisticsNode):
break
for stats in node.get_child_keys():
if hash(stats) == hash_value:
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what-studio/profiling | profiling/viewer.py | StatisticsViewer.update_result | def update_result(self):
"""Updates the result on the table."""
try:
if self.paused:
result = self._paused_result
else:
result = self._final_result
except AttributeError:
self.table.update_frame()
return
stat... | python | def update_result(self):
"""Updates the result on the table."""
try:
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result = self._paused_result
else:
result = self._final_result
except AttributeError:
self.table.update_frame()
return
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what-studio/profiling | profiling/__main__.py | option_getter | def option_getter(type):
"""Gets an unbound method to get a configuration option as the given type.
"""
option_getters = {None: ConfigParser.get,
int: ConfigParser.getint,
float: ConfigParser.getfloat,
bool: ConfigParser.getboolean}
retur... | python | def option_getter(type):
"""Gets an unbound method to get a configuration option as the given type.
"""
option_getters = {None: ConfigParser.get,
int: ConfigParser.getint,
float: ConfigParser.getfloat,
bool: ConfigParser.getboolean}
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what-studio/profiling | profiling/__main__.py | config_default | def config_default(option, default=None, type=None, section=cli.name):
"""Guesses a default value of a CLI option from the configuration.
::
@click.option('--locale', default=config_default('locale'))
"""
def f(option=option, default=default, type=type, section=section):
config = read_... | python | def config_default(option, default=None, type=None, section=cli.name):
"""Guesses a default value of a CLI option from the configuration.
::
@click.option('--locale', default=config_default('locale'))
"""
def f(option=option, default=default, type=type, section=section):
config = read_... | [
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what-studio/profiling | profiling/__main__.py | config_flag | def config_flag(option, value, default=False, section=cli.name):
"""Guesses whether a CLI flag should be turned on or off from the
configuration. If the configuration option value is same with the given
value, it returns ``True``.
::
@click.option('--ko-kr', 'locale', is_flag=True,
... | python | def config_flag(option, value, default=False, section=cli.name):
"""Guesses whether a CLI flag should be turned on or off from the
configuration. If the configuration option value is same with the given
value, it returns ``True``.
::
@click.option('--ko-kr', 'locale', is_flag=True,
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what-studio/profiling | profiling/__main__.py | get_title | def get_title(src_name, src_type=None):
"""Normalizes a source name as a string to be used for viewer's title."""
if src_type == 'tcp':
return '{0}:{1}'.format(*src_name)
return os.path.basename(src_name) | python | def get_title(src_name, src_type=None):
"""Normalizes a source name as a string to be used for viewer's title."""
if src_type == 'tcp':
return '{0}:{1}'.format(*src_name)
return os.path.basename(src_name) | [
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what-studio/profiling | profiling/__main__.py | spawn_thread | def spawn_thread(func, *args, **kwargs):
"""Spawns a daemon thread."""
thread = threading.Thread(target=func, args=args, kwargs=kwargs)
thread.daemon = True
thread.start()
return thread | python | def spawn_thread(func, *args, **kwargs):
"""Spawns a daemon thread."""
thread = threading.Thread(target=func, args=args, kwargs=kwargs)
thread.daemon = True
thread.start()
return thread | [
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what-studio/profiling | profiling/__main__.py | spawn | def spawn(mode, func, *args, **kwargs):
"""Spawns a thread-like object which runs the given function concurrently.
Available modes:
- `threading`
- `greenlet`
- `eventlet`
"""
if mode is None:
# 'threading' is the default mode.
mode = 'threading'
elif mode not in spawn... | python | def spawn(mode, func, *args, **kwargs):
"""Spawns a thread-like object which runs the given function concurrently.
Available modes:
- `threading`
- `greenlet`
- `eventlet`
"""
if mode is None:
# 'threading' is the default mode.
mode = 'threading'
elif mode not in spawn... | [
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what-studio/profiling | profiling/__main__.py | profile | def profile(script, argv, profiler_factory,
pickle_protocol, dump_filename, mono):
"""Profile a Python script."""
filename, code, globals_ = script
sys.argv[:] = [filename] + list(argv)
__profile__(filename, code, globals_, profiler_factory,
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pickle_protocol, dump_filename, mono):
"""Profile a Python script."""
filename, code, globals_ = script
sys.argv[:] = [filename] + list(argv)
__profile__(filename, code, globals_, profiler_factory,
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what-studio/profiling | profiling/__main__.py | live_profile | def live_profile(script, argv, profiler_factory, interval, spawn, signum,
pickle_protocol, mono):
"""Profile a Python script continuously."""
filename, code, globals_ = script
sys.argv[:] = [filename] + list(argv)
parent_sock, child_sock = socket.socketpair()
stderr_r_fd, stderr_w_f... | python | def live_profile(script, argv, profiler_factory, interval, spawn, signum,
pickle_protocol, mono):
"""Profile a Python script continuously."""
filename, code, globals_ = script
sys.argv[:] = [filename] + list(argv)
parent_sock, child_sock = socket.socketpair()
stderr_r_fd, stderr_w_f... | [
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what-studio/profiling | profiling/__main__.py | view | def view(src, mono):
"""Inspect statistics by TUI view."""
src_type, src_name = src
title = get_title(src_name, src_type)
viewer, loop = make_viewer(mono)
if src_type == 'dump':
time = datetime.fromtimestamp(os.path.getmtime(src_name))
with open(src_name, 'rb') as f:
prof... | python | def view(src, mono):
"""Inspect statistics by TUI view."""
src_type, src_name = src
title = get_title(src_name, src_type)
viewer, loop = make_viewer(mono)
if src_type == 'dump':
time = datetime.fromtimestamp(os.path.getmtime(src_name))
with open(src_name, 'rb') as f:
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what-studio/profiling | profiling/__main__.py | timeit_profile | def timeit_profile(stmt, number, repeat, setup,
profiler_factory, pickle_protocol, dump_filename, mono,
**_ignored):
"""Profile a Python statement like timeit."""
del _ignored
globals_ = {}
exec_(setup, globals_)
if number is None:
# determine number so ... | python | def timeit_profile(stmt, number, repeat, setup,
profiler_factory, pickle_protocol, dump_filename, mono,
**_ignored):
"""Profile a Python statement like timeit."""
del _ignored
globals_ = {}
exec_(setup, globals_)
if number is None:
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what-studio/profiling | profiling/stats.py | spread_stats | def spread_stats(stats, spreader=False):
"""Iterates all descendant statistics under the given root statistics.
When ``spreader=True``, each iteration yields a descendant statistics and
`spread()` function together. You should call `spread()` if you want to
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"""... | python | def spread_stats(stats, spreader=False):
"""Iterates all descendant statistics under the given root statistics.
When ``spreader=True``, each iteration yields a descendant statistics and
`spread()` function together. You should call `spread()` if you want to
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what-studio/profiling | profiling/stats.py | Statistics.own_time | def own_time(self):
"""The exclusive execution time."""
sub_time = sum(stats.deep_time for stats in self)
return max(0., self.deep_time - sub_time) | python | def own_time(self):
"""The exclusive execution time."""
sub_time = sum(stats.deep_time for stats in self)
return max(0., self.deep_time - sub_time) | [
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what-studio/profiling | profiling/stats.py | FlatFrozenStatistics.flatten | def flatten(cls, stats):
"""Makes a flat statistics from the given statistics."""
flat_children = {}
for _stats in spread_stats(stats):
key = (_stats.name, _stats.filename, _stats.lineno, _stats.module)
try:
flat_stats = flat_children[key]
exce... | python | def flatten(cls, stats):
"""Makes a flat statistics from the given statistics."""
flat_children = {}
for _stats in spread_stats(stats):
key = (_stats.name, _stats.filename, _stats.lineno, _stats.module)
try:
flat_stats = flat_children[key]
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what-studio/profiling | setup.py | requirements | def requirements(filename):
"""Reads requirements from a file."""
with open(filename) as f:
return [x.strip() for x in f.readlines() if x.strip()] | python | def requirements(filename):
"""Reads requirements from a file."""
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what-studio/profiling | profiling/sampling/__init__.py | SamplingProfiler.sample | def sample(self, frame):
"""Samples the given frame."""
frames = self.frame_stack(frame)
if frames:
frames.pop()
parent_stats = self.stats
for f in frames:
parent_stats = parent_stats.ensure_child(f.f_code, void)
stats = parent_stats.ensure_child(f... | python | def sample(self, frame):
"""Samples the given frame."""
frames = self.frame_stack(frame)
if frames:
frames.pop()
parent_stats = self.stats
for f in frames:
parent_stats = parent_stats.ensure_child(f.f_code, void)
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what-studio/profiling | profiling/utils.py | deferral | def deferral():
"""Defers a function call when it is being required like Go.
::
with deferral() as defer:
sys.setprofile(f)
defer(sys.setprofile, None)
# do something.
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deferred = []
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"""Defers a function call when it is being required like Go.
::
with deferral() as defer:
sys.setprofile(f)
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# do something.
"""
deferred = []
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what-studio/profiling | profiling/utils.py | Runnable.start | def start(self, *args, **kwargs):
"""Starts the instance.
:raises RuntimeError: has been already started.
:raises TypeError: :meth:`run` is not canonical.
"""
if self.is_running():
raise RuntimeError('Already started')
self._running = self.run(*args, **kwarg... | python | def start(self, *args, **kwargs):
"""Starts the instance.
:raises RuntimeError: has been already started.
:raises TypeError: :meth:`run` is not canonical.
"""
if self.is_running():
raise RuntimeError('Already started')
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what-studio/profiling | profiling/utils.py | Runnable.stop | def stop(self):
"""Stops the instance.
:raises RuntimeError: has not been started.
:raises TypeError: :meth:`run` is not canonical.
"""
if not self.is_running():
raise RuntimeError('Not started')
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"""Stops the instance.
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what-studio/profiling | profiling/remote/select.py | SelectProfilingServer.sockets | def sockets(self):
"""Returns the set of the sockets."""
if self.listener is None:
return self.clients
else:
return self.clients.union([self.listener]) | python | def sockets(self):
"""Returns the set of the sockets."""
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return self.clients
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what-studio/profiling | profiling/remote/select.py | SelectProfilingServer.select_sockets | def select_sockets(self, timeout=None):
"""EINTR safe version of `select`. It focuses on just incoming
sockets.
"""
if timeout is not None:
t = time.time()
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try:
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"""EINTR safe version of `select`. It focuses on just incoming
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"""
if timeout is not None:
t = time.time()
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ready, __, __ = select.select(self.sockets(), (), (), timeout)
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what-studio/profiling | profiling/remote/select.py | SelectProfilingServer.dispatch_sockets | def dispatch_sockets(self, timeout=None):
"""Dispatches incoming sockets."""
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if sock is self.listener:
listener = sock
sock, addr = listener.accept()
self.connected(sock)
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"""Dispatches incoming sockets."""
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listener = sock
sock, addr = listener.accept()
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what-studio/profiling | profiling/tracing/__init__.py | TracingProfiler.record_entering | def record_entering(self, time, code, frame_key, parent_stats):
"""Entered to a function call."""
stats = parent_stats.ensure_child(code, RecordingStatistics)
self._times_entered[(code, frame_key)] = time
stats.own_hits += 1 | python | def record_entering(self, time, code, frame_key, parent_stats):
"""Entered to a function call."""
stats = parent_stats.ensure_child(code, RecordingStatistics)
self._times_entered[(code, frame_key)] = time
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what-studio/profiling | profiling/tracing/__init__.py | TracingProfiler.record_leaving | def record_leaving(self, time, code, frame_key, parent_stats):
"""Left from a function call."""
try:
stats = parent_stats.get_child(code)
time_entered = self._times_entered.pop((code, frame_key))
except KeyError:
return
time_elapsed = time - time_enter... | python | def record_leaving(self, time, code, frame_key, parent_stats):
"""Left from a function call."""
try:
stats = parent_stats.get_child(code)
time_entered = self._times_entered.pop((code, frame_key))
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semiversus/python-broqer | broqer/op/subscribers/sink.py | build_sink | def build_sink(function: Callable[..., None] = None, *,
unpack: bool = False):
""" Decorator to wrap a function to return a Sink subscriber.
:param function: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
"""
def _build_sink(function: Callable[..., N... | python | def build_sink(function: Callable[..., None] = None, *,
unpack: bool = False):
""" Decorator to wrap a function to return a Sink subscriber.
:param function: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
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semiversus/python-broqer | broqer/op/map_.py | build_map | def build_map(function: Callable[[Any], Any] = None,
unpack: bool = False):
""" Decorator to wrap a function to return a Map operator.
:param function: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
"""
def _build_map(function: Callable[[Any], Any]):
... | python | def build_map(function: Callable[[Any], Any] = None,
unpack: bool = False):
""" Decorator to wrap a function to return a Map operator.
:param function: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
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semiversus/python-broqer | broqer/op/subscribers/trace.py | Trace._trace_handler | def _trace_handler(publisher, value, label=None):
""" Default trace handler is printing the timestamp, the publisher name
and the emitted value
"""
line = '--- %8.3f: ' % (time() - Trace._timestamp_start)
line += repr(publisher) if label is None else label
line += ' %r' %... | python | def _trace_handler(publisher, value, label=None):
""" Default trace handler is printing the timestamp, the publisher name
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"""
line = '--- %8.3f: ' % (time() - Trace._timestamp_start)
line += repr(publisher) if label is None else label
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semiversus/python-broqer | broqer/op/subscribers/sink_async.py | build_sink_async | def build_sink_async(coro=None, *, mode=None, unpack: bool = False):
""" Decorator to wrap a coroutine to return a SinkAsync subscriber.
:param coro: coroutine to be wrapped
:param mode: behavior when a value is currently processed
:param unpack: value from emits will be unpacked (*value)
"""
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""" Decorator to wrap a coroutine to return a SinkAsync subscriber.
:param coro: coroutine to be wrapped
:param mode: behavior when a value is currently processed
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semiversus/python-broqer | broqer/op/accumulate.py | build_accumulate | def build_accumulate(function: Callable[[Any, Any], Tuple[Any, Any]] = None, *,
init: Any = NONE):
""" Decorator to wrap a function to return an Accumulate operator.
:param function: function to be wrapped
:param init: optional initialization for state
"""
_init = init
def... | python | def build_accumulate(function: Callable[[Any, Any], Tuple[Any, Any]] = None, *,
init: Any = NONE):
""" Decorator to wrap a function to return an Accumulate operator.
:param function: function to be wrapped
:param init: optional initialization for state
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_init = init
def... | [
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semiversus/python-broqer | broqer/hub/utils/datatype_check.py | resolve_meta_key | def resolve_meta_key(hub, key, meta):
""" Resolve a value when it's a string and starts with '>' """
if key not in meta:
return None
value = meta[key]
if isinstance(value, str) and value[0] == '>':
topic = value[1:]
if topic not in hub:
raise KeyError('topic %s not fo... | python | def resolve_meta_key(hub, key, meta):
""" Resolve a value when it's a string and starts with '>' """
if key not in meta:
return None
value = meta[key]
if isinstance(value, str) and value[0] == '>':
topic = value[1:]
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semiversus/python-broqer | broqer/hub/utils/datatype_check.py | DTTopic.checked_emit | def checked_emit(self, value: Any) -> asyncio.Future:
""" Casting and checking in one call """
if not isinstance(self._subject, Subscriber):
raise TypeError('Topic %r has to be a subscriber' % self._path)
value = self.cast(value)
self.check(value)
return self._subje... | python | def checked_emit(self, value: Any) -> asyncio.Future:
""" Casting and checking in one call """
if not isinstance(self._subject, Subscriber):
raise TypeError('Topic %r has to be a subscriber' % self._path)
value = self.cast(value)
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semiversus/python-broqer | broqer/hub/utils/datatype_check.py | DTRegistry.add_datatype | def add_datatype(self, name: str, datatype: DT):
""" Register the datatype with it's name """
self._datatypes[name] = datatype | python | def add_datatype(self, name: str, datatype: DT):
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semiversus/python-broqer | broqer/hub/utils/datatype_check.py | DTRegistry.cast | def cast(self, topic, value):
""" Cast a string to the value based on the datatype """
datatype_key = topic.meta.get('datatype', 'none')
result = self._datatypes[datatype_key].cast(topic, value)
validate_dt = topic.meta.get('validate', None)
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""" Cast a string to the value based on the datatype """
datatype_key = topic.meta.get('datatype', 'none')
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semiversus/python-broqer | broqer/hub/utils/datatype_check.py | DTRegistry.check | def check(self, topic, value):
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""" Checking the value if it fits into the given specification """
datatype_key = topic.meta.get('datatype', 'none')
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semiversus/python-broqer | broqer/op/partition.py | Partition.flush | def flush(self):
""" Emits the current queue and clears the queue """
self.notify(tuple(self._queue))
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""" Emits the current queue and clears the queue """
self.notify(tuple(self._queue))
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semiversus/python-broqer | broqer/op/sample.py | Sample._periodic_callback | def _periodic_callback(self):
""" Will be started on first emit """
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self._error_callback(*sys.exc_info())
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# if there are... | python | def _periodic_callback(self):
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self._error_callback(*sys.exc_info())
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semiversus/python-broqer | broqer/op/reduce.py | build_reduce | def build_reduce(function: Callable[[Any, Any], Any] = None, *,
init: Any = NONE):
""" Decorator to wrap a function to return a Reduce operator.
:param function: function to be wrapped
:param init: optional initialization for state
"""
_init = init
def _build_reduce(function: ... | python | def build_reduce(function: Callable[[Any, Any], Any] = None, *,
init: Any = NONE):
""" Decorator to wrap a function to return a Reduce operator.
:param function: function to be wrapped
:param init: optional initialization for state
"""
_init = init
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semiversus/python-broqer | broqer/op/sliding_window.py | SlidingWindow.flush | def flush(self):
""" Flush the queue - this will emit the current queue """
if not self._emit_partial and len(self._state) != self._state.maxlen:
self.notify(tuple(self._state))
self._state.clear() | python | def flush(self):
""" Flush the queue - this will emit the current queue """
if not self._emit_partial and len(self._state) != self._state.maxlen:
self.notify(tuple(self._state))
self._state.clear() | [
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semiversus/python-broqer | broqer/op/map_async.py | build_map_async | def build_map_async(coro=None, *, mode=None, unpack: bool = False):
""" Decorator to wrap a coroutine to return a MapAsync operator.
:param coro: coroutine to be wrapped
:param mode: behavior when a value is currently processed
:param unpack: value from emits will be unpacked (*value)
"""
_mode... | python | def build_map_async(coro=None, *, mode=None, unpack: bool = False):
""" Decorator to wrap a coroutine to return a MapAsync operator.
:param coro: coroutine to be wrapped
:param mode: behavior when a value is currently processed
:param unpack: value from emits will be unpacked (*value)
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semiversus/python-broqer | broqer/op/map_async.py | MapAsync._future_done | def _future_done(self, future):
""" Will be called when the coroutine is done """
try:
# notify the subscribers (except result is an exception or NONE)
result = future.result() # may raise exception
if result is not NONE:
self.notify(result) # may al... | python | def _future_done(self, future):
""" Will be called when the coroutine is done """
try:
# notify the subscribers (except result is an exception or NONE)
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semiversus/python-broqer | broqer/op/map_async.py | MapAsync._run_coro | def _run_coro(self, value):
""" Start the coroutine as task """
# when LAST_DISTINCT is used only start coroutine when value changed
if self._options.mode is MODE.LAST_DISTINCT and \
value == self._last_emit:
self._future = None
return
# store th... | python | def _run_coro(self, value):
""" Start the coroutine as task """
# when LAST_DISTINCT is used only start coroutine when value changed
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semiversus/python-broqer | broqer/op/filter_.py | build_filter | def build_filter(predicate: Callable[[Any], bool] = None, *,
unpack: bool = False):
""" Decorator to wrap a function to return a Filter operator.
:param predicate: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
"""
def _build_filter(predicate: Call... | python | def build_filter(predicate: Callable[[Any], bool] = None, *,
unpack: bool = False):
""" Decorator to wrap a function to return a Filter operator.
:param predicate: function to be wrapped
:param unpack: value from emits will be unpacked (*value)
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semiversus/python-broqer | broqer/op/operator_overloading.py | apply_operator_overloading | def apply_operator_overloading():
""" Function to apply operator overloading to Publisher class """
# operator overloading is (unfortunately) not working for the following
# cases:
# int, float, str - should return appropriate type instead of a Publisher
# len - should return an integer
# "x in ... | python | def apply_operator_overloading():
""" Function to apply operator overloading to Publisher class """
# operator overloading is (unfortunately) not working for the following
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# len - should return an integer
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semiversus/python-broqer | broqer/hub/hub.py | Topic.assign | def assign(self, subject):
""" Assigns the given subject to the topic """
if not isinstance(subject, (Publisher, Subscriber)):
raise TypeError('Assignee has to be Publisher or Subscriber')
# check if not already assigned
if self._subject is not None:
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""" Assigns the given subject to the topic """
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semiversus/python-broqer | broqer/hub/hub.py | Hub.freeze | def freeze(self, freeze: bool = True):
""" Freezing the hub means that each topic has to be assigned and no
new topics can be created after this point.
"""
for topic in self._topics.values():
topic.freeze()
self._frozen = freeze | python | def freeze(self, freeze: bool = True):
""" Freezing the hub means that each topic has to be assigned and no
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"""
for topic in self._topics.values():
topic.freeze()
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semiversus/python-broqer | broqer/op/throttle.py | Throttle.reset | def reset(self):
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semiversus/python-broqer | broqer/op/debounce.py | Debounce.reset | def reset(self):
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semiversus/python-broqer | broqer/publisher.py | Publisher.inherit_type | def inherit_type(self, type_cls: Type[TInherit]) \
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astropy/photutils | photutils/extern/sigma_clipping.py | _move_tuple_axes_first | def _move_tuple_axes_first(array, axis):
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"""
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astropy/photutils | photutils/extern/sigma_clipping.py | _nanmean | def _nanmean(array, axis=None):
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astropy/photutils | photutils/extern/sigma_clipping.py | _nanmedian | def _nanmedian(array, axis=None):
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astropy/photutils | photutils/extern/sigma_clipping.py | _nanstd | def _nanstd(array, axis=None, ddof=0):
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astropy/photutils | photutils/extern/sigma_clipping.py | sigma_clip | def sigma_clip(data, sigma=3, sigma_lower=None, sigma_upper=None, maxiters=5,
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Perform sigma-clipping on the provided data.
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astropy/photutils | photutils/extern/sigma_clipping.py | sigma_clipped_stats | def sigma_clipped_stats(data, mask=None, mask_value=None, sigma=3.0,
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cenfunc='median', stdfunc='std', std_ddof=0,
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Calculate sigma-clipped statistics on the provided data.
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astropy/photutils | photutils/extern/sigma_clipping.py | SigmaClip._sigmaclip_noaxis | def _sigmaclip_noaxis(self, data, masked=True, return_bounds=False,
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"""
Sigma clip the data when ``axis`` is None.
In this simple case, we remove clipped elements from the
flattened array during each iteration.
"""
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astropy/photutils | photutils/extern/sigma_clipping.py | SigmaClip._sigmaclip_withaxis | def _sigmaclip_withaxis(self, data, axis=None, masked=True,
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astropy/photutils | photutils/aperture/core.py | PixelAperture.do_photometry | def do_photometry(self, data, error=None, mask=None, method='exact',
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"""
Perform aperture photometry on the input data.
Parameters
----------
data : array_like or `~astropy.units.Quantity` instance
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Perform aperture photometry on the input data.
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data : array_like or `~astropy.units.Quantity` instance
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... | python | def _to_sky_params(self, wcs, mode='all'):
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Convert the pixel aperture parameters to those for a sky
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astropy/photutils | photutils/segmentation/properties.py | source_properties | def source_properties(data, segment_img, error=None, mask=None,
background=None, filter_kernel=None, wcs=None,
labels=None):
"""
Calculate photometry and morphological properties of sources defined
by a labeled segmentation image.
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----------
... | python | def source_properties(data, segment_img, error=None, mask=None,
background=None, filter_kernel=None, wcs=None,
labels=None):
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Calculate photometry and morphological properties of sources defined
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Construct a `~astropy.table.QTable` of source properties from a
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties._total_mask | def _total_mask(self):
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.to_table | def to_table(self, columns=None, exclude_columns=None):
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.data_cutout_ma | def data_cutout_ma(self):
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A 2D `~numpy.ma.MaskedArray` cutout from the data.
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A 2D `~numpy.ma.MaskedArray` cutout from the data.
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.coords | def coords(self):
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The sky coordinates of the centroid within the source segment,
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.sky_bbox_ul | def sky_bbox_ul(self):
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.sky_bbox_lr | def sky_bbox_lr(self):
"""
The sky coordinates of the lower-right vertex of the minimal
bounding box of the source segment, returned as a
`~astropy.coordinates.SkyCoord` object.
The bounding box encloses all of the source segment pixels in
their entirety, thus the vertic... | python | def sky_bbox_lr(self):
"""
The sky coordinates of the lower-right vertex of the minimal
bounding box of the source segment, returned as a
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.sky_bbox_ur | def sky_bbox_ur(self):
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The sky coordinates of the upper-right vertex of the minimal
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.min_value | def min_value(self):
"""
The minimum pixel value of the ``data`` within the source
segment.
"""
if self._is_completely_masked:
return np.nan * self._data_unit
else:
return np.min(self.values) | python | def min_value(self):
"""
The minimum pixel value of the ``data`` within the source
segment.
"""
if self._is_completely_masked:
return np.nan * self._data_unit
else:
return np.min(self.values) | [
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.max_value | def max_value(self):
"""
The maximum pixel value of the ``data`` within the source
segment.
"""
if self._is_completely_masked:
return np.nan * self._data_unit
else:
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"""
The maximum pixel value of the ``data`` within the source
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"""
if self._is_completely_masked:
return np.nan * self._data_unit
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.source_sum | def source_sum(self):
"""
The sum of the unmasked ``data`` values within the source segment.
.. math:: F = \\sum_{i \\in S} (I_i - B_i)
where :math:`F` is ``source_sum``, :math:`(I_i - B_i)` is the
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"""
The sum of the unmasked ``data`` values within the source segment.
.. math:: F = \\sum_{i \\in S} (I_i - B_i)
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.source_sum_err | def source_sum_err(self):
"""
The uncertainty of `~photutils.SourceProperties.source_sum`,
propagated from the input ``error`` array.
``source_sum_err`` is the quadrature sum of the total errors
over the non-masked pixels within the source segment:
.. math:: \\Delta F =... | python | def source_sum_err(self):
"""
The uncertainty of `~photutils.SourceProperties.source_sum`,
propagated from the input ``error`` array.
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.background_sum | def background_sum(self):
"""
The sum of ``background`` values within the source segment.
Pixel values that are masked in the input ``data``, including
any non-finite pixel values (i.e. NaN, infs) that are
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"""
The sum of ``background`` values within the source segment.
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.background_mean | def background_mean(self):
"""
The mean of ``background`` values within the source segment.
Pixel values that are masked in the input ``data``, including
any non-finite pixel values (i.e. NaN, infs) that are
automatically masked, are also masked in the background array.
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"""
The mean of ``background`` values within the source segment.
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.background_at_centroid | def background_at_centroid(self):
"""
The value of the ``background`` at the position of the source
centroid.
The background value at fractional position values are
determined using bilinear interpolation.
"""
from scipy.ndimage import map_coordinates
i... | python | def background_at_centroid(self):
"""
The value of the ``background`` at the position of the source
centroid.
The background value at fractional position values are
determined using bilinear interpolation.
"""
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.perimeter | def perimeter(self):
"""
The total perimeter of the source segment, approximated lines
through the centers of the border pixels using a 4-connectivity.
If any masked pixels make holes within the source segment, then
the perimeter around the inner hole (e.g. an annulus) will also... | python | def perimeter(self):
"""
The total perimeter of the source segment, approximated lines
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.inertia_tensor | def inertia_tensor(self):
"""
The inertia tensor of the source for the rotation around its
center of mass.
"""
mu = self.moments_central
a = mu[0, 2]
b = -mu[1, 1]
c = mu[2, 0]
return np.array([[a, b], [b, c]]) * u.pix**2 | python | def inertia_tensor(self):
"""
The inertia tensor of the source for the rotation around its
center of mass.
"""
mu = self.moments_central
a = mu[0, 2]
b = -mu[1, 1]
c = mu[2, 0]
return np.array([[a, b], [b, c]]) * u.pix**2 | [
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.covariance | def covariance(self):
"""
The covariance matrix of the 2D Gaussian function that has the
same second-order moments as the source.
"""
mu = self.moments_central
if mu[0, 0] != 0:
m = mu / mu[0, 0]
covariance = self._check_covariance(
... | python | def covariance(self):
"""
The covariance matrix of the 2D Gaussian function that has the
same second-order moments as the source.
"""
mu = self.moments_central
if mu[0, 0] != 0:
m = mu / mu[0, 0]
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.covariance_eigvals | def covariance_eigvals(self):
"""
The two eigenvalues of the `covariance` matrix in decreasing
order.
"""
if not np.isnan(np.sum(self.covariance)):
eigvals = np.linalg.eigvals(self.covariance)
if np.any(eigvals < 0): # negative variance
... | python | def covariance_eigvals(self):
"""
The two eigenvalues of the `covariance` matrix in decreasing
order.
"""
if not np.isnan(np.sum(self.covariance)):
eigvals = np.linalg.eigvals(self.covariance)
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.eccentricity | def eccentricity(self):
"""
The eccentricity of the 2D Gaussian function that has the same
second-order moments as the source.
The eccentricity is the fraction of the distance along the
semimajor axis at which the focus lies.
.. math:: e = \\sqrt{1 - \\frac{b^2}{a^2}}
... | python | def eccentricity(self):
"""
The eccentricity of the 2D Gaussian function that has the same
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The eccentricity is the fraction of the distance along the
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.. math:: e = \\sqrt{1 - \\frac{b^2}{a^2}}
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astropy/photutils | photutils/segmentation/properties.py | SourceProperties.orientation | def orientation(self):
"""
The angle in radians between the ``x`` axis and the major axis
of the 2D Gaussian function that has the same second-order
moments as the source. The angle increases in the
counter-clockwise direction.
"""
a, b, b, c = self.covariance.f... | python | def orientation(self):
"""
The angle in radians between the ``x`` axis and the major axis
of the 2D Gaussian function that has the same second-order
moments as the source. The angle increases in the
counter-clockwise direction.
"""
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astropy/photutils | photutils/utils/stats.py | _mesh_values | def _mesh_values(data, box_size):
"""
Extract all the data values in boxes of size ``box_size``.
Values from incomplete boxes, either because of the image edges or
masked pixels, are not returned.
Parameters
----------
data : 2D `~numpy.ma.MaskedArray`
The input masked array.
... | python | def _mesh_values(data, box_size):
"""
Extract all the data values in boxes of size ``box_size``.
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Parameters
----------
data : 2D `~numpy.ma.MaskedArray`
The input masked array.
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astropy/photutils | photutils/utils/stats.py | std_blocksum | def std_blocksum(data, block_sizes, mask=None):
"""
Calculate the standard deviation of block-summed data values at
sizes of ``block_sizes``.
Values from incomplete blocks, either because of the image edges or
masked pixels, are not included.
Parameters
----------
data : array-like
... | python | def std_blocksum(data, block_sizes, mask=None):
"""
Calculate the standard deviation of block-summed data values at
sizes of ``block_sizes``.
Values from incomplete blocks, either because of the image edges or
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Parameters
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data : array-like
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astropy/photutils | photutils/psf/photometry.py | BasicPSFPhotometry.nstar | def nstar(self, image, star_groups):
"""
Fit, as appropriate, a compound or single model to the given
``star_groups``. Groups are fitted sequentially from the
smallest to the biggest. In each iteration, ``image`` is
subtracted by the previous fitted group.
Parameters
... | python | def nstar(self, image, star_groups):
"""
Fit, as appropriate, a compound or single model to the given
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smallest to the biggest. In each iteration, ``image`` is
subtracted by the previous fitted group.
Parameters
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astropy/photutils | photutils/psf/photometry.py | BasicPSFPhotometry._get_uncertainties | def _get_uncertainties(self, star_group_size):
"""
Retrieve uncertainties on fitted parameters from the fitter
object.
Parameters
----------
star_group_size : int
Number of stars in the given group.
Returns
-------
unc_tab : `~astropy... | python | def _get_uncertainties(self, star_group_size):
"""
Retrieve uncertainties on fitted parameters from the fitter
object.
Parameters
----------
star_group_size : int
Number of stars in the given group.
Returns
-------
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astropy/photutils | photutils/psf/photometry.py | BasicPSFPhotometry._model_params2table | def _model_params2table(self, fit_model, star_group_size):
"""
Place fitted parameters into an astropy table.
Parameters
----------
fit_model : `astropy.modeling.Fittable2DModel` instance
PSF or PRF model to fit the data. Could be one of the models
in thi... | python | def _model_params2table(self, fit_model, star_group_size):
"""
Place fitted parameters into an astropy table.
Parameters
----------
fit_model : `astropy.modeling.Fittable2DModel` instance
PSF or PRF model to fit the data. Could be one of the models
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astropy/photutils | photutils/psf/photometry.py | IterativelySubtractedPSFPhotometry._do_photometry | def _do_photometry(self, param_tab, n_start=1):
"""
Helper function which performs the iterations of the photometry
process.
Parameters
----------
param_names : list
Names of the columns which represent the initial guesses.
For example, ['x_0', '... | python | def _do_photometry(self, param_tab, n_start=1):
"""
Helper function which performs the iterations of the photometry
process.
Parameters
----------
param_names : list
Names of the columns which represent the initial guesses.
For example, ['x_0', '... | [
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astropy/photutils | photutils/utils/wcs_helpers.py | pixel_scale_angle_at_skycoord | def pixel_scale_angle_at_skycoord(skycoord, wcs, offset=1. * u.arcsec):
"""
Calculate the pixel scale and WCS rotation angle at the position of
a SkyCoord coordinate.
Parameters
----------
skycoord : `~astropy.coordinates.SkyCoord`
The SkyCoord coordinate.
wcs : `~astropy.wcs.WCS`
... | python | def pixel_scale_angle_at_skycoord(skycoord, wcs, offset=1. * u.arcsec):
"""
Calculate the pixel scale and WCS rotation angle at the position of
a SkyCoord coordinate.
Parameters
----------
skycoord : `~astropy.coordinates.SkyCoord`
The SkyCoord coordinate.
wcs : `~astropy.wcs.WCS`
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The world coordinate system (WCS) transformation to use.
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astropy/photutils | photutils/utils/wcs_helpers.py | pixel_to_icrs_coords | def pixel_to_icrs_coords(x, y, wcs):
"""
Convert pixel coordinates to ICRS Right Ascension and Declination.
This is merely a convenience function to extract RA and Dec. from a
`~astropy.coordinates.SkyCoord` instance so they can be put in
separate columns in a `~astropy.table.Table`.
Parameter... | python | def pixel_to_icrs_coords(x, y, wcs):
"""
Convert pixel coordinates to ICRS Right Ascension and Declination.
This is merely a convenience function to extract RA and Dec. from a
`~astropy.coordinates.SkyCoord` instance so they can be put in
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