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def convert_items(self, items): """Generator like `convert_iterable`, but for 2-tuple iterators.""" return ((key, self.convert(value, self)) for key, value in items)
Generator like `convert_iterable`, but for 2-tuple iterators.
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def convert_mapping(self, mapping): """Convenience method to track either a dict or a 2-tuple iterator.""" if isinstance(mapping, dict): return self.convert_items(iteritems(mapping)) return self.convert_items(mapping)
Convenience method to track either a dict or a 2-tuple iterator.
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def changelist_view(self, request, extra_context=None): """ If we only have a single preference object redirect to it, otherwise display listing. """ model = self.model if model.objects.all().count() > 1: return super(PreferencesAdmin, self).changelist_view(re...
If we only have a single preference object redirect to it, otherwise display listing.
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def md2rst(md_lines): 'Only converts headers' lvl2header_char = {1: '=', 2: '-', 3: '~'} for md_line in md_lines: if md_line.startswith('#'): header_indent, header_text = md_line.split(' ', 1) yield header_text header_char = lvl2header_char[len(header_indent)] ...
Only converts headers
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def aslist(generator): 'Function decorator to transform a generator into a list' def wrapper(*args, **kwargs): return list(generator(*args, **kwargs)) return wrapper
Function decorator to transform a generator into a list
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def get_package_release_from_pypi(pkg_name, version, pypi_json_api_url, allowed_classifiers): """ No classifier-based selection of Python packages is currently implemented: for now we don't fetch any .whl or .egg Eventually, we should select the best release available, based on the classifier & PEP 425: htt...
No classifier-based selection of Python packages is currently implemented: for now we don't fetch any .whl or .egg Eventually, we should select the best release available, based on the classifier & PEP 425: https://www.python.org/dev/peps/pep-0425/ E.g. a wheel when available but NOT for tornado 4.3 for example...
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def extract_classifier_and_extension(pkg_name, filename): """ Returns a PEP425-compliant classifier (or 'py2.py3-none-any' if it cannot be extracted), and the file extension TODO: return a classifier 3-members namedtuple instead of a single string """ basename, _, extension = filename.rpartition...
Returns a PEP425-compliant classifier (or 'py2.py3-none-any' if it cannot be extracted), and the file extension TODO: return a classifier 3-members namedtuple instead of a single string
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def coerce(cls, key, value): """Convert plain dictionary to NestedMutable.""" if value is None: return value if isinstance(value, cls): return value if isinstance(value, dict): return NestedMutableDict.coerce(key, value) if isinstance(value, li...
Convert plain dictionary to NestedMutable.
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def is_mod_function(mod, fun): """Checks if a function in a module was declared in that module. http://stackoverflow.com/a/1107150/3004221 Args: mod: the module fun: the function """ return inspect.isfunction(fun) and inspect.getmodule(fun) == mod
Checks if a function in a module was declared in that module. http://stackoverflow.com/a/1107150/3004221 Args: mod: the module fun: the function
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def is_mod_class(mod, cls): """Checks if a class in a module was declared in that module. Args: mod: the module cls: the class """ return inspect.isclass(cls) and inspect.getmodule(cls) == mod
Checks if a class in a module was declared in that module. Args: mod: the module cls: the class
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def list_functions(mod_name): """Lists all functions declared in a module. http://stackoverflow.com/a/1107150/3004221 Args: mod_name: the module name Returns: A list of functions declared in that module. """ mod = sys.modules[mod_name] return [func.__name__ for func in mod....
Lists all functions declared in a module. http://stackoverflow.com/a/1107150/3004221 Args: mod_name: the module name Returns: A list of functions declared in that module.
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def list_classes(mod_name): """Lists all classes declared in a module. Args: mod_name: the module name Returns: A list of functions declared in that module. """ mod = sys.modules[mod_name] return [cls.__name__ for cls in mod.__dict__.values() if is_mod_class(mod, cls...
Lists all classes declared in a module. Args: mod_name: the module name Returns: A list of functions declared in that module.
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def get_linenumbers(functions, module, searchstr='def {}(image):\n'): """Returns a dictionary which maps function names to line numbers. Args: functions: a list of function names module: the module to look the functions up searchstr: the string to search for Returns: A di...
Returns a dictionary which maps function names to line numbers. Args: functions: a list of function names module: the module to look the functions up searchstr: the string to search for Returns: A dictionary with functions as keys and their line numbers as values.
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def format_doc(fun): """Formats the documentation in a nicer way and for notebook cells.""" SEPARATOR = '=============================' func = cvloop.functions.__dict__[fun] doc_lines = ['{}'.format(l).strip() for l in func.__doc__.split('\n')] if hasattr(func, '__init__'): doc_lines.append...
Formats the documentation in a nicer way and for notebook cells.
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def main(): """Main function creates the cvloop.functions example notebook.""" notebook = { 'cells': [ { 'cell_type': 'markdown', 'metadata': {}, 'source': [ '# cvloop functions\n\n', 'This notebook shows...
Main function creates the cvloop.functions example notebook.
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def prepare_axes(axes, title, size, cmap=None): """Prepares an axes object for clean plotting. Removes x and y axes labels and ticks, sets the aspect ratio to be equal, uses the size to determine the drawing area and fills the image with random colors as visual feedback. Creates an AxesImage to be...
Prepares an axes object for clean plotting. Removes x and y axes labels and ticks, sets the aspect ratio to be equal, uses the size to determine the drawing area and fills the image with random colors as visual feedback. Creates an AxesImage to be shown inside the axes object and sets the needed p...
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def connect_event_handlers(self): """Connects event handlers to the figure.""" self.figure.canvas.mpl_connect('close_event', self.evt_release) self.figure.canvas.mpl_connect('pause_event', self.evt_toggle_pause)
Connects event handlers to the figure.
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def evt_toggle_pause(self, *args): # pylint: disable=unused-argument """Pauses and resumes the video source.""" if self.event_source._timer is None: # noqa: e501 pylint: disable=protected-access self.event_source.start() else: self.event_source.stop()
Pauses and resumes the video source.
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def print_info(self, capture): """Prints information about the unprocessed image. Reads one frame from the source to determine image colors, dimensions and data types. Args: capture: the source to read from. """ self.frame_offset += 1 ret, frame = ca...
Prints information about the unprocessed image. Reads one frame from the source to determine image colors, dimensions and data types. Args: capture: the source to read from.
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def determine_size(self, capture): """Determines the height and width of the image source. If no dimensions are available, this method defaults to a resolution of 640x480, thus returns (480, 640). If capture has a get method it is assumed to understand `cv2.CAP_PROP_FRAME_WIDTH`...
Determines the height and width of the image source. If no dimensions are available, this method defaults to a resolution of 640x480, thus returns (480, 640). If capture has a get method it is assumed to understand `cv2.CAP_PROP_FRAME_WIDTH` and `cv2.CAP_PROP_FRAME_HEIGHT` to get the ...
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def _init_draw(self): """Initializes the drawing of the frames by setting the images to random colors. This function is called by TimedAnimation. """ if self.original is not None: self.original.set_data(np.random.random((10, 10, 3))) self.processed.set_data(n...
Initializes the drawing of the frames by setting the images to random colors. This function is called by TimedAnimation.
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def read_frame(self): """Reads a frame and converts the color if needed. In case no frame is available, i.e. self.capture.read() returns False as the first return value, the event_source of the TimedAnimation is stopped, and if possible the capture source released. Returns: ...
Reads a frame and converts the color if needed. In case no frame is available, i.e. self.capture.read() returns False as the first return value, the event_source of the TimedAnimation is stopped, and if possible the capture source released. Returns: None if stopped, otherwi...
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def annotate(self, framedata): """Annotates the processed axis with given annotations for the provided framedata. Args: framedata: The current frame number. """ for artist in self.annotation_artists: artist.remove() self.annotation_artists = [] ...
Annotates the processed axis with given annotations for the provided framedata. Args: framedata: The current frame number.
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def _draw_frame(self, framedata): """Reads, processes and draws the frames. If needed for color maps, conversions to gray scale are performed. In case the images are no color images and no custom color maps are defined, the colormap `gray` is applied. This function is called by...
Reads, processes and draws the frames. If needed for color maps, conversions to gray scale are performed. In case the images are no color images and no custom color maps are defined, the colormap `gray` is applied. This function is called by TimedAnimation. Args: f...
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def update_info(self, custom=None): """Updates the figure's suptitle. Calls self.info_string() unless custom is provided. Args: custom: Overwrite it with this string, unless None. """ self.figure.suptitle(self.info_string() if custom is None else custom)
Updates the figure's suptitle. Calls self.info_string() unless custom is provided. Args: custom: Overwrite it with this string, unless None.
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def info_string(self, size=None, message='', frame=-1): """Returns information about the stream. Generates a string containing size, frame number, and info messages. Omits unnecessary information (e.g. empty messages and frame -1). This method is primarily used to update the suptitle o...
Returns information about the stream. Generates a string containing size, frame number, and info messages. Omits unnecessary information (e.g. empty messages and frame -1). This method is primarily used to update the suptitle of the plot figure. Returns: An info st...
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def main(): """Sanitizes the loaded *.ipynb.""" with open(sys.argv[1], 'r') as nbfile: notebook = json.load(nbfile) # remove kernelspec (venvs) try: del notebook['metadata']['kernelspec'] except KeyError: pass # remove outputs and metadata, set execution counts to None ...
Sanitizes the loaded *.ipynb.
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def create(self, comment, mentions=()): """ create comment :param comment: :param mentions: list of pair of code and type("USER", "GROUP", and so on) :return: """ data = { "app": self.app_id, "record": self.record_id, "comment"...
create comment :param comment: :param mentions: list of pair of code and type("USER", "GROUP", and so on) :return:
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def _consume(iterator, n=None): """Advance the iterator n-steps ahead. If n is none, consume entirely.""" # Use functions that consume iterators at C speed. if n is None: # feed the entire iterator into a zero-length deque collections.deque(iterator, maxlen=0) else: # advance to ...
Advance the iterator n-steps ahead. If n is none, consume entirely.
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def _slice_required_len(slice_obj): """ Calculate how many items must be in the collection to satisfy this slice returns `None` for slices may vary based on the length of the underlying collection such as `lst[-1]` or `lst[::]` """ if slice_obj.step and slice_obj.step != 1: return None ...
Calculate how many items must be in the collection to satisfy this slice returns `None` for slices may vary based on the length of the underlying collection such as `lst[-1]` or `lst[::]`
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def stylize(text, styles, reset=True): """conveniently styles your text as and resets ANSI codes at its end.""" terminator = attr("reset") if reset else "" return "{}{}{}".format("".join(styles), text, terminator)
conveniently styles your text as and resets ANSI codes at its end.
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def stylize_interactive(text, styles, reset=True): """stylize() variant that adds C0 control codes (SOH/STX) for readline safety.""" # problem: readline includes bare ANSI codes in width calculations. # solution: wrap nonprinting codes in SOH/STX when necessary. # see: https://github.com/dslackw/col...
stylize() variant that adds C0 control codes (SOH/STX) for readline safety.
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def attribute(self): """Set or reset attributes""" paint = { "bold": self.ESC + "1" + self.END, 1: self.ESC + "1" + self.END, "dim": self.ESC + "2" + self.END, 2: self.ESC + "2" + self.END, "underlined": self.ESC + "4" + self.END, ...
Set or reset attributes
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def foreground(self): """Print 256 foreground colors""" code = self.ESC + "38;5;" if str(self.color).isdigit(): self.reverse_dict() color = self.reserve_paint[str(self.color)] return code + self.paint[color] + self.END elif self.color.startswith("#"): ...
Print 256 foreground colors
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def reverse_dict(self): """reverse dictionary""" self.reserve_paint = dict(zip(self.paint.values(), self.paint.keys()))
reverse dictionary
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def reset(self, required=False): """ Perform a reset and check for presence pulse. :param bool required: require presence pulse """ reset = self._ow.reset() if required and reset: raise OneWireError("No presence pulse found. Check devices and wiring.") ...
Perform a reset and check for presence pulse. :param bool required: require presence pulse
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def readinto(self, buf, *, start=0, end=None): """ Read into ``buf`` from the device. The number of bytes read will be the length of ``buf``. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buf[start:end]``. This will not cause an allocation like ...
Read into ``buf`` from the device. The number of bytes read will be the length of ``buf``. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buf[start:end]``. This will not cause an allocation like ``buf[start:end]`` will so it saves memory. :param byt...
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def write(self, buf, *, start=0, end=None): """ Write the bytes from ``buf`` to the device. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buffer[start:end]``. This will not cause an allocation like ``buffer[start:end]`` will so it saves memory. ...
Write the bytes from ``buf`` to the device. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buffer[start:end]``. This will not cause an allocation like ``buffer[start:end]`` will so it saves memory. :param bytearray buf: buffer containing the bytes to write ...
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def scan(self): """Scan for devices on the bus and return a list of addresses.""" devices = [] diff = 65 rom = False count = 0 for _ in range(0xff): rom, diff = self._search_rom(rom, diff) if rom: count += 1 if count...
Scan for devices on the bus and return a list of addresses.
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def crc8(data): """ Perform the 1-Wire CRC check on the provided data. :param bytearray data: 8 byte array representing 64 bit ROM code """ crc = 0 for byte in data: crc ^= byte for _ in range(8): if crc & 0x01: ...
Perform the 1-Wire CRC check on the provided data. :param bytearray data: 8 byte array representing 64 bit ROM code
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def _deserialize(cls, json_body, get_value_and_type): """ deserialize json to model :param json_body: json data :param get_value_and_type: function(f: json_field) -> value, field_type_string(see FieldType) :return: """ instance = cls() is_set = False ...
deserialize json to model :param json_body: json data :param get_value_and_type: function(f: json_field) -> value, field_type_string(see FieldType) :return:
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def _serialize(self, convert_to_key_and_value, ignore_missing=False): """ serialize model object to dictionary :param convert_to_key_and_value: function(field_name, value, property_detail) -> key, value :return: """ serialized = {} properties = self._get_property...
serialize model object to dictionary :param convert_to_key_and_value: function(field_name, value, property_detail) -> key, value :return:
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def readinto(self, buf, *, start=0, end=None): """ Read into ``buf`` from the device. The number of bytes read will be the length of ``buf``. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buf[start:end]``. This will not cause an allocation like ...
Read into ``buf`` from the device. The number of bytes read will be the length of ``buf``. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buf[start:end]``. This will not cause an allocation like ``buf[start:end]`` will so it saves memory. :param byt...
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def write(self, buf, *, start=0, end=None): """ Write the bytes from ``buf`` to the device. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buffer[start:end]``. This will not cause an allocation like ``buffer[start:end]`` will so it saves memory. ...
Write the bytes from ``buf`` to the device. If ``start`` or ``end`` is provided, then the buffer will be sliced as if ``buffer[start:end]``. This will not cause an allocation like ``buffer[start:end]`` will so it saves memory. :param bytearray buf: buffer containing the bytes to write ...
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def preferences_class_prepared(sender, *args, **kwargs): """ Adds various preferences members to preferences.preferences, thus enabling easy access from code. """ cls = sender if issubclass(cls, Preferences): # Add singleton manager to subclasses. cls.add_to_class('singleton', Si...
Adds various preferences members to preferences.preferences, thus enabling easy access from code.
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def site_cleanup(sender, action, instance, **kwargs): """ Make sure there is only a single preferences object per site. So remove sites from pre-existing preferences objects. """ if action == 'post_add': if isinstance(instance, Preferences) \ and hasattr(instance.__class__, 'obje...
Make sure there is only a single preferences object per site. So remove sites from pre-existing preferences objects.
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def get_queryset(self): """ Return the first preferences object for the current site. If preferences do not exist create it. """ queryset = super(SingletonManager, self).get_queryset() # Get current site current_site = None if getattr(settings, 'SITE_ID'...
Return the first preferences object for the current site. If preferences do not exist create it.
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def load_iterable(self, iterable, session=None): '''Load an ``iterable``. By default it returns a generator of data loaded via the :meth:`loads` method. :param iterable: an iterable over data to load. :param session: Optional :class:`stdnet.odm.Session`. :return: an ite...
Load an ``iterable``. By default it returns a generator of data loaded via the :meth:`loads` method. :param iterable: an iterable over data to load. :param session: Optional :class:`stdnet.odm.Session`. :return: an iterable over decoded data.
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def search_model(self, q, text, lookup=None): '''Implements :meth:`stdnet.odm.SearchEngine.search_model`. It return a new :class:`stdnet.odm.QueryElem` instance from the input :class:`Query` and the *text* to search.''' words = self.words_from_text(text, for_search=True) if not words: ...
Implements :meth:`stdnet.odm.SearchEngine.search_model`. It return a new :class:`stdnet.odm.QueryElem` instance from the input :class:`Query` and the *text* to search.
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def _search(self, words, include=None, exclude=None, lookup=None): '''Full text search. Return a list of queries to intersect.''' lookup = lookup or 'contains' query = self.router.worditem.query() if include: query = query.filter(model_type__in=include) if exclu...
Full text search. Return a list of queries to intersect.
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def redis_client(address=None, connection_pool=None, timeout=None, parser=None, **kwargs): '''Get a new redis client. :param address: a ``host``, ``port`` tuple. :param connection_pool: optional connection pool. :param timeout: socket timeout. :param timeout: socket timeout. ''...
Get a new redis client. :param address: a ``host``, ``port`` tuple. :param connection_pool: optional connection pool. :param timeout: socket timeout. :param timeout: socket timeout.
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def to_bytes(s, encoding=None, errors='strict'): """Returns a bytestring version of 's', encoded as specified in 'encoding'.""" encoding = encoding or 'utf-8' if isinstance(s, bytes): if encoding != 'utf-8': return s.decode('utf-8', errors).encode(encoding, errors) else: ...
Returns a bytestring version of 's', encoded as specified in 'encoding'.
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def to_string(s, encoding=None, errors='strict'): """Inverse of to_bytes""" encoding = encoding or 'utf-8' if isinstance(s, bytes): return s.decode(encoding, errors) if not is_string(s): s = string_type(s) return s
Inverse of to_bytes
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def date_decimal_hook(dct): '''The default JSON decoder hook. It is the inverse of :class:`stdnet.utils.jsontools.JSONDateDecimalEncoder`.''' if '__datetime__' in dct: return todatetime(dct['__datetime__']) elif '__date__' in dct: return todatetime(dct['__date__']).date() elif '__decimal...
The default JSON decoder hook. It is the inverse of :class:`stdnet.utils.jsontools.JSONDateDecimalEncoder`.
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def flat_to_nested(data, instance=None, attname=None, separator=None, loads=None): '''Convert a flat representation of a dictionary to a nested representation. Fields in the flat representation are separated by the *splitter* parameters. :parameter data: a flat dictionary of key value pairs. :pa...
Convert a flat representation of a dictionary to a nested representation. Fields in the flat representation are separated by the *splitter* parameters. :parameter data: a flat dictionary of key value pairs. :parameter instance: optional instance of a model. :parameter attribute: optional attribute of a model. :paramet...
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def dict_flat_generator(value, attname=None, splitter=JSPLITTER, dumps=None, prefix=None, error=ValueError, recursive=True): '''Convert a nested dictionary into a flat dictionary representation''' if not isinstance(value, dict) or not recursive: if not pre...
Convert a nested dictionary into a flat dictionary representation
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def addmul_number_dicts(series): '''Multiply dictionaries by a numeric values and add them together. :parameter series: a tuple of two elements tuples. Each serie is of the form:: (weight,dictionary) where ``weight`` is a number and ``dictionary`` is a dictionary with numeric values. :parameter s...
Multiply dictionaries by a numeric values and add them together. :parameter series: a tuple of two elements tuples. Each serie is of the form:: (weight,dictionary) where ``weight`` is a number and ``dictionary`` is a dictionary with numeric values. :parameter skip: optional list of field names to ski...
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def Download(campaign=0, queue='build', email=None, walltime=8, **kwargs): ''' Submits a cluster job to the build queue to download all TPFs for a given campaign. :param int campaign: The `K2` campaign to run :param str queue: The name of the queue to submit to. Default `build` :param str email...
Submits a cluster job to the build queue to download all TPFs for a given campaign. :param int campaign: The `K2` campaign to run :param str queue: The name of the queue to submit to. Default `build` :param str email: The email to send job status notifications to. \ Default `None` :param...
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def _Download(campaign, subcampaign): ''' Download all stars from a given campaign. This is called from ``missions/k2/download.pbs`` ''' # Are we doing a subcampaign? if subcampaign != -1: campaign = campaign + 0.1 * subcampaign # Get all star IDs for this campaign stars = [s[0...
Download all stars from a given campaign. This is called from ``missions/k2/download.pbs``
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def Run(campaign=0, EPIC=None, nodes=5, ppn=12, walltime=100, mpn=None, email=None, queue=None, **kwargs): ''' Submits a cluster job to compute and plot data for all targets in a given campaign. :param campaign: The K2 campaign number. If this is an :py:class:`int`, \ returns all tar...
Submits a cluster job to compute and plot data for all targets in a given campaign. :param campaign: The K2 campaign number. If this is an :py:class:`int`, \ returns all targets in that campaign. If a :py:class:`float` \ in the form `X.Y`, runs the `Y^th` decile of campaign `X`. :para...
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def _Publish(campaign, subcampaign, strkwargs): ''' The actual function that publishes a given campaign; this must be called from ``missions/k2/publish.pbs``. ''' # Get kwargs from string kwargs = pickle.loads(strkwargs.replace('%%%', '\n').encode('utf-8')) # Check the cadence cadence...
The actual function that publishes a given campaign; this must be called from ``missions/k2/publish.pbs``.
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def Status(season=range(18), model='nPLD', purge=False, injection=False, cadence='lc', **kwargs): ''' Shows the progress of the de-trending runs for the specified campaign(s). ''' # Mission compatibility campaign = season # Injection? if injection: return InjectionStatu...
Shows the progress of the de-trending runs for the specified campaign(s).
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def InjectionStatus(campaign=range(18), model='nPLD', purge=False, depths=[0.01, 0.001, 0.0001], **kwargs): ''' Shows the progress of the injection de-trending runs for the specified campaign(s). ''' if not hasattr(campaign, '__len__'): if type(campaign) is int: ...
Shows the progress of the injection de-trending runs for the specified campaign(s).
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def EverestModel(ID, model='nPLD', publish=False, csv=False, **kwargs): ''' A wrapper around an :py:obj:`everest` model for PBS runs. ''' if model != 'Inject': from ... import detrender # HACK: We need to explicitly mask short cadence planets if kwargs.get('cadence', 'lc') == ...
A wrapper around an :py:obj:`everest` model for PBS runs.
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def PrimaryHDU(model): ''' Construct the primary HDU file containing basic header info. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=0) if 'KEPMAG' not in [c[0] for c in cards]: cards.append(('KEPMAG', model.mag, 'Kepler magnitude')) # Add EVEREST info ...
Construct the primary HDU file containing basic header info.
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def LightcurveHDU(model): ''' Construct the data HDU file containing the arrays and the observing info. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=1) # Add EVEREST info cards.append(('COMMENT', '************************')) cards.append(('COMMENT', '* E...
Construct the data HDU file containing the arrays and the observing info.
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def PixelsHDU(model): ''' Construct the HDU containing the pixel-level light curve. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=2) # Add EVEREST info cards = [] cards.append(('COMMENT', '************************')) cards.append(('COMMENT', '* EVERES...
Construct the HDU containing the pixel-level light curve.
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def ApertureHDU(model): ''' Construct the HDU containing the aperture used to de-trend. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=3) # Add EVEREST info cards.append(('COMMENT', '************************')) cards.append(('COMMENT', '* EVEREST INFO ...
Construct the HDU containing the aperture used to de-trend.
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def ImagesHDU(model): ''' Construct the HDU containing sample postage stamp images of the target. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=4) # Add EVEREST info cards.append(('COMMENT', '************************')) cards.append(('COMMENT', '* EVEREST...
Construct the HDU containing sample postage stamp images of the target.
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def HiResHDU(model): ''' Construct the HDU containing the hi res image of the target. ''' # Get mission cards cards = model._mission.HDUCards(model.meta, hdu=5) # Add EVEREST info cards.append(('COMMENT', '************************')) cards.append(('COMMENT', '* EVEREST INFO *'...
Construct the HDU containing the hi res image of the target.
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def MakeFITS(model, fitsfile=None): ''' Generate a FITS file for a given :py:mod:`everest` run. :param model: An :py:mod:`everest` model instance ''' # Get the fits file name if fitsfile is None: outfile = os.path.join(model.dir, model._mission.FITSFile( model.ID, model.se...
Generate a FITS file for a given :py:mod:`everest` run. :param model: An :py:mod:`everest` model instance
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def get_serializer(name, **options): '''Retrieve a serializer register as *name*. If the serializer is not available a ``ValueError`` exception will raise. A common usage pattern:: qs = MyModel.objects.query().sort_by('id') s = odm.get_serializer('json') s.dump(qs) ''' if name in _serializ...
Retrieve a serializer register as *name*. If the serializer is not available a ``ValueError`` exception will raise. A common usage pattern:: qs = MyModel.objects.query().sort_by('id') s = odm.get_serializer('json') s.dump(qs)
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def register_serializer(name, serializer): '''\ Register a new serializer to the library. :parameter name: serializer name (it can override existing serializers). :parameter serializer: an instance or a derived class of a :class:`stdnet.odm.Serializer` class or a callable. ''' if not isclass(serial...
\ Register a new serializer to the library. :parameter name: serializer name (it can override existing serializers). :parameter serializer: an instance or a derived class of a :class:`stdnet.odm.Serializer` class or a callable.
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def MaskSolve(A, b, w=5, progress=True, niter=None): ''' Finds the solution `x` to the linear problem A x = b for all contiguous `w`-sized masks applied to the rows and columns of `A` and to the entries of `b`. Returns an array `X` of shape `(N - w + 1, N - w)`, where t...
Finds the solution `x` to the linear problem A x = b for all contiguous `w`-sized masks applied to the rows and columns of `A` and to the entries of `b`. Returns an array `X` of shape `(N - w + 1, N - w)`, where the `nth` row is the solution to the equation A[![n,n+w)]...
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def MaskSolveSlow(A, b, w=5, progress=True, niter=None): ''' Identical to `MaskSolve`, but computes the solution the brute-force way. ''' # Number of data points N = b.shape[0] # How many iterations? Default is to go through # the entire dataset if niter is None: ...
Identical to `MaskSolve`, but computes the solution the brute-force way.
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def unmasked(self, depth=0.01): """Return the unmasked overfitting metric for a given transit depth.""" return 1 - (np.hstack(self._O2) + np.hstack(self._O3) / depth) / np.hstack(self._O1)
Return the unmasked overfitting metric for a given transit depth.
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def show(self): """Show the overfitting PDF summary.""" try: if platform.system().lower().startswith('darwin'): subprocess.call(['open', self.pdf]) elif os.name == 'nt': os.startfile(self.pdf) elif os.name == 'posix': su...
Show the overfitting PDF summary.
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def season(self): """ Return the current observing season. For *K2*, this is the observing campaign, while for *Kepler*, it is the current quarter. """ try: self._season except AttributeError: self._season = self._mission.Season(self.ID) ...
Return the current observing season. For *K2*, this is the observing campaign, while for *Kepler*, it is the current quarter.
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def fcor(self): ''' The CBV-corrected de-trended flux. ''' if self.XCBV is None: return None else: return self.flux - self._mission.FitCBVs(self)
The CBV-corrected de-trended flux.
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def mask(self): ''' The array of indices to be masked. This is the union of the sets of outliers, bad (flagged) cadences, transit cadences, and :py:obj:`NaN` cadences. ''' return np.array(list(set(np.concatenate([self.outmask, self.badmask, self....
The array of indices to be masked. This is the union of the sets of outliers, bad (flagged) cadences, transit cadences, and :py:obj:`NaN` cadences.
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def X(self, i, j=slice(None, None, None)): ''' Computes the design matrix at the given *PLD* order and the given indices. The columns are the *PLD* vectors for the target at the corresponding order, computed as the product of the fractional pixel flux of all sets of :py:obj:`n` p...
Computes the design matrix at the given *PLD* order and the given indices. The columns are the *PLD* vectors for the target at the corresponding order, computed as the product of the fractional pixel flux of all sets of :py:obj:`n` pixels, where :py:obj:`n` is the *PLD* order.
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def plot_info(self, dvs): ''' Plots miscellaneous de-trending information on the data validation summary figure. :param dvs: A :py:class:`dvs.DVS` figure instance ''' axl, axc, axr = dvs.title() axc.annotate("%s %d" % (self._mission.IDSTRING, self.ID), ...
Plots miscellaneous de-trending information on the data validation summary figure. :param dvs: A :py:class:`dvs.DVS` figure instance
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def compute(self): ''' Compute the model for the current value of lambda. ''' # Is there a transit model? if self.transit_model is not None: return self.compute_joint() log.info('Computing the model...') # Loop over all chunks model = [None...
Compute the model for the current value of lambda.
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def compute_joint(self): ''' Compute the model in a single step, allowing for a light curve-wide transit model. This is a bit more expensive to compute. ''' # Init log.info('Computing the joint model...') A = [None for b in self.breakpoints] B = [None fo...
Compute the model in a single step, allowing for a light curve-wide transit model. This is a bit more expensive to compute.
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def apply_mask(self, x=None): ''' Returns the outlier mask, an array of indices corresponding to the non-outliers. :param numpy.ndarray x: If specified, returns the masked version of \ :py:obj:`x` instead. Default :py:obj:`None` ''' if x is None: ...
Returns the outlier mask, an array of indices corresponding to the non-outliers. :param numpy.ndarray x: If specified, returns the masked version of \ :py:obj:`x` instead. Default :py:obj:`None`
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def get_chunk(self, b, x=None, pad=True): ''' Returns the indices corresponding to a given light curve chunk. :param int b: The index of the chunk to return :param numpy.ndarray x: If specified, applies the mask to array \ :py:obj:`x`. Default :py:obj:`None` ''' ...
Returns the indices corresponding to a given light curve chunk. :param int b: The index of the chunk to return :param numpy.ndarray x: If specified, applies the mask to array \ :py:obj:`x`. Default :py:obj:`None`
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def get_weights(self): ''' Computes the PLD weights vector :py:obj:`w`. ..warning :: Deprecated and not thoroughly tested. ''' log.info("Computing PLD weights...") # Loop over all chunks weights = [None for i in range(len(self.breakpoints))] for b, brk...
Computes the PLD weights vector :py:obj:`w`. ..warning :: Deprecated and not thoroughly tested.
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def get_cdpp_arr(self, flux=None): ''' Returns the CDPP value in *ppm* for each of the chunks in the light curve. ''' if flux is None: flux = self.flux return np.array([self._mission.CDPP(flux[self.get_masked_chunk(b)], cadence=self.c...
Returns the CDPP value in *ppm* for each of the chunks in the light curve.
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def get_cdpp(self, flux=None): ''' Returns the scalar CDPP for the light curve. ''' if flux is None: flux = self.flux return self._mission.CDPP(self.apply_mask(flux), cadence=self.cadence)
Returns the scalar CDPP for the light curve.
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def plot_aperture(self, axes, labelsize=8): ''' Plots the aperture and the pixel images at the beginning, middle, and end of the time series. Also plots a high resolution image of the target, if available. ''' log.info('Plotting the aperture...') # Get colormap...
Plots the aperture and the pixel images at the beginning, middle, and end of the time series. Also plots a high resolution image of the target, if available.
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def overfit(self, tau=None, plot=True, clobber=False, w=9, **kwargs): r""" Compute the masked & unmasked overfitting metrics for the light curve. This routine injects a transit model given by `tau` at every cadence in the light curve and recovers the transit depth when (1) leaving ...
r""" Compute the masked & unmasked overfitting metrics for the light curve. This routine injects a transit model given by `tau` at every cadence in the light curve and recovers the transit depth when (1) leaving the transit unmasked and (2) masking the transit prior to performing ...
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def lnlike(self, model, refactor=False, pos_tol=2.5, neg_tol=50., full_output=False): r""" Return the likelihood of the astrophysical model `model`. Returns the likelihood of `model` marginalized over the PLD model. :param ndarray model: A vector of the same shape as `se...
r""" Return the likelihood of the astrophysical model `model`. Returns the likelihood of `model` marginalized over the PLD model. :param ndarray model: A vector of the same shape as `self.time` \ corresponding to the astrophysical model. :param bool refactor: Re-compute ...
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def Inject(ID, inj_model='nPLD', t0=None, per=None, dur=0.1, depth=0.001, mask=False, trn_win=5, poly_order=3, make_fits=False, **kwargs): ''' Run one of the :py:obj:`everest` models with injected transits and attempt to recover the transit depth at the end with a simple linear regression wit...
Run one of the :py:obj:`everest` models with injected transits and attempt to recover the transit depth at the end with a simple linear regression with a polynomial baseline. The depth is stored in the :py:obj:`inject` attribute of the model (a dictionary) as :py:obj:`rec_depth`. A control injection is ...
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def object(self, session): '''Instance of :attr:`model_type` with id :attr:`object_id`.''' if not hasattr(self, '_object'): pkname = self.model_type._meta.pkname() query = session.query(self.model_type).filter(**{pkname: ...
Instance of :attr:`model_type` with id :attr:`object_id`.
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def GetData(ID, season = None, cadence = 'lc', clobber = False, delete_raw = False, aperture_name = None, saturated_aperture_name = None, max_pixels = None, download_only = False, saturation_tolerance = None, bad_bits = None, **kwargs): ''' Returns a :py:obj:`DataContainer` ins...
Returns a :py:obj:`DataContainer` instance with the raw data for the target. :param int ID: The target ID number :param int season: The observing season. Default :py:obj:`None` :param str cadence: The light curve cadence. Default `lc` :param bool clobber: Overwrite existing files? Default :py:obj:`False` :...
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def GetNeighbors(ID, model = None, neighbors = None, mag_range = None, cdpp_range = None, aperture_name = None, cadence = 'lc', **kwargs): ''' Return `neighbors` random bright stars on the same module as `EPIC`. :param int ID: The target ID number :param str model: The :py...
Return `neighbors` random bright stars on the same module as `EPIC`. :param int ID: The target ID number :param str model: The :py:obj:`everest` model name. Only used when imposing CDPP bounds. Default :py:obj:`None` :param int neighbors: Number of neighbors to return. Default None :param str aperture_name: ...
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def get(ID, pipeline='everest2', campaign=None): ''' Returns the `time` and `flux` for a given EPIC `ID` and a given `pipeline` name. ''' log.info('Downloading %s light curve for %d...' % (pipeline, ID)) # Dev version hack if EVEREST_DEV: if pipeline.lower() == 'everest2' or pipel...
Returns the `time` and `flux` for a given EPIC `ID` and a given `pipeline` name.
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def plot(ID, pipeline='everest2', show=True, campaign=None): ''' Plots the de-trended flux for the given EPIC `ID` and for the specified `pipeline`. ''' # Get the data time, flux = get(ID, pipeline=pipeline, campaign=campaign) # Remove nans mask = np.where(np.isnan(flux))[0] time ...
Plots the de-trended flux for the given EPIC `ID` and for the specified `pipeline`.
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def get_cdpp(campaign, pipeline='everest2'): ''' Computes the CDPP for a given `campaign` and a given `pipeline`. Stores the results in a file under "/missions/k2/tables/". ''' # Imports from .k2 import CDPP from .utils import GetK2Campaign # Check pipeline assert pipeline.lower()...
Computes the CDPP for a given `campaign` and a given `pipeline`. Stores the results in a file under "/missions/k2/tables/".
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def get_outliers(campaign, pipeline='everest2', sigma=5): ''' Computes the number of outliers for a given `campaign` and a given `pipeline`. Stores the results in a file under "/missions/k2/tables/". :param int sigma: The sigma level at which to clip outliers. Default 5 ''' # Imports ...
Computes the number of outliers for a given `campaign` and a given `pipeline`. Stores the results in a file under "/missions/k2/tables/". :param int sigma: The sigma level at which to clip outliers. Default 5
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