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nailgun/entity_mixins.py
EntityCreateMixin.create_json
def create_json(self, create_missing=None): """Create an entity. Call :meth:`create_raw`. Check the response status code, decode JSON and return the decoded JSON as a dict. :return: A dict. The server's response, with all JSON decoded. :raises: ``requests.exceptions.HTTPError`` if the response has an HTTP 4XX or 5XX status code. :raises: ``ValueError`` If the response JSON can not be decoded. """ response = self.create_raw(create_missing) response.raise_for_status() return response.json()
python
def create_json(self, create_missing=None): """Create an entity. Call :meth:`create_raw`. Check the response status code, decode JSON and return the decoded JSON as a dict. :return: A dict. The server's response, with all JSON decoded. :raises: ``requests.exceptions.HTTPError`` if the response has an HTTP 4XX or 5XX status code. :raises: ``ValueError`` If the response JSON can not be decoded. """ response = self.create_raw(create_missing) response.raise_for_status() return response.json()
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tbone/db/models.py
create_collection
async def create_collection(db, model_class: MongoCollectionMixin): ''' Creates a MongoDB collection and all the declared indices in the model's ``Meta`` class :param db: A database handle :type db: motor.motor_asyncio.AsyncIOMotorClient :param model_class: The model to create :type model_class: Subclass of ``Model`` mixed with ``MongoCollectionMixin`` ''' name = model_class.get_collection_name() if name: try: # create collection coll = await db.create_collection(name, **model_class._meta.creation_args) except CollectionInvalid: # collection already exists coll = db[name] # create indices if hasattr(model_class._meta, 'indices') and isinstance(model_class._meta.indices, list): for index in model_class._meta.indices: try: index_kwargs = { 'name': index.get('name', '_'.join([x[0] for x in index['fields']])), 'unique': index.get('unique', False), 'sparse': index.get('sparse', False), 'expireAfterSeconds': index.get('expireAfterSeconds', None), 'background': True } if 'partialFilterExpression' in index: index_kwargs['partialFilterExpression'] = index.get('partialFilterExpression', {}) await db[name].create_index( index['fields'], **index_kwargs ) except OperationFailure as ex: pass # index already exists ? TODO: do something with this return coll return None
python
async def create_collection(db, model_class: MongoCollectionMixin): ''' Creates a MongoDB collection and all the declared indices in the model's ``Meta`` class :param db: A database handle :type db: motor.motor_asyncio.AsyncIOMotorClient :param model_class: The model to create :type model_class: Subclass of ``Model`` mixed with ``MongoCollectionMixin`` ''' name = model_class.get_collection_name() if name: try: # create collection coll = await db.create_collection(name, **model_class._meta.creation_args) except CollectionInvalid: # collection already exists coll = db[name] # create indices if hasattr(model_class._meta, 'indices') and isinstance(model_class._meta.indices, list): for index in model_class._meta.indices: try: index_kwargs = { 'name': index.get('name', '_'.join([x[0] for x in index['fields']])), 'unique': index.get('unique', False), 'sparse': index.get('sparse', False), 'expireAfterSeconds': index.get('expireAfterSeconds', None), 'background': True } if 'partialFilterExpression' in index: index_kwargs['partialFilterExpression'] = index.get('partialFilterExpression', {}) await db[name].create_index( index['fields'], **index_kwargs ) except OperationFailure as ex: pass # index already exists ? TODO: do something with this return coll return None
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JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/modules/mavproxy_wp.py
WPModule.get_default_frame
def get_default_frame(self): '''default frame for waypoints''' if self.settings.terrainalt == 'Auto': if self.get_mav_param('TERRAIN_FOLLOW',0) == 1: return mavutil.mavlink.MAV_FRAME_GLOBAL_TERRAIN_ALT return mavutil.mavlink.MAV_FRAME_GLOBAL_RELATIVE_ALT if self.settings.terrainalt == 'True': return mavutil.mavlink.MAV_FRAME_GLOBAL_TERRAIN_ALT return mavutil.mavlink.MAV_FRAME_GLOBAL_RELATIVE_ALT
python
def get_default_frame(self): '''default frame for waypoints''' if self.settings.terrainalt == 'Auto': if self.get_mav_param('TERRAIN_FOLLOW',0) == 1: return mavutil.mavlink.MAV_FRAME_GLOBAL_TERRAIN_ALT return mavutil.mavlink.MAV_FRAME_GLOBAL_RELATIVE_ALT if self.settings.terrainalt == 'True': return mavutil.mavlink.MAV_FRAME_GLOBAL_TERRAIN_ALT return mavutil.mavlink.MAV_FRAME_GLOBAL_RELATIVE_ALT
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msiedlarek/wiring
wiring/scanning/scan.py
scan_to_graph
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python
def scan_to_graph(python_modules, graph, ignore=tuple()): """ Scans `python_modules` with :py:func:`scan` and registers found providers in `graph`. `ignore` argument is passed through to :py:func:`scan`. """ def callback(specification, provider): graph.register_provider(specification, provider) scan(python_modules, callback, ignore=ignore)
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QualiSystems/vCenterShell
package/cloudshell/cp/vcenter/network/vnic/vnic_service.py
VNicService.device_is_attached_to_network
def device_is_attached_to_network(device, network_name): """ Checks if the device has a backing with of the right network name :param <vim.vm.Device> device: instance of adapter :param <str> network_name: network name :return: """ try: backing = device.backing except: return False if hasattr(backing, 'network') and hasattr(backing.network, 'name'): return network_name == backing.network.name elif hasattr(backing, 'port') and hasattr(backing.port, 'portgroupKey'): return network_name == backing.port.portgroupKey return False
python
def device_is_attached_to_network(device, network_name): """ Checks if the device has a backing with of the right network name :param <vim.vm.Device> device: instance of adapter :param <str> network_name: network name :return: """ try: backing = device.backing except: return False if hasattr(backing, 'network') and hasattr(backing.network, 'name'): return network_name == backing.network.name elif hasattr(backing, 'port') and hasattr(backing.port, 'portgroupKey'): return network_name == backing.port.portgroupKey return False
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openspending/ckanext-budgets
ckanext/budgets/plugin.py
BudgetDataPackagePlugin.are_budget_data_package_fields_filled_in
def are_budget_data_package_fields_filled_in(self, resource): """ Check if the budget data package fields are all filled in because if not then this can't be a budget data package """ fields = ['country', 'currency', 'year', 'status'] return all([self.in_resource(f, resource) for f in fields])
python
def are_budget_data_package_fields_filled_in(self, resource): """ Check if the budget data package fields are all filled in because if not then this can't be a budget data package """ fields = ['country', 'currency', 'year', 'status'] return all([self.in_resource(f, resource) for f in fields])
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cvxopt/chompack
src/python/misc.py
symmetrize
def symmetrize(A): """ Returns a symmetric matrix from a sparse square matrix :math:`A`. Only the lower triangular entries of :math:`A` are accessed. """ assert type(A) is spmatrix, "argument must be a sparse matrix" assert A.size[0] == A.size[1], "argument must me a square matrix" idx = [i for i,ij in enumerate(zip(A.I,A.J)) if ij[0] > ij[1]] return tril(A) + spmatrix(A.V[idx], A.J[idx], A.I[idx], A.size)
python
def symmetrize(A): """ Returns a symmetric matrix from a sparse square matrix :math:`A`. Only the lower triangular entries of :math:`A` are accessed. """ assert type(A) is spmatrix, "argument must be a sparse matrix" assert A.size[0] == A.size[1], "argument must me a square matrix" idx = [i for i,ij in enumerate(zip(A.I,A.J)) if ij[0] > ij[1]] return tril(A) + spmatrix(A.V[idx], A.J[idx], A.I[idx], A.size)
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Fantomas42/django-blog-zinnia
zinnia/views/mixins/entry_protection.py
EntryProtectionMixin.get
def get(self, request, *args, **kwargs): """ Do the login and password protection. """ response = super(EntryProtectionMixin, self).get( request, *args, **kwargs) if self.object.login_required and not request.user.is_authenticated: return self.login() if (self.object.password and self.object.password != self.request.session.get(self.session_key % self.object.pk)): return self.password() return response
python
def get(self, request, *args, **kwargs): """ Do the login and password protection. """ response = super(EntryProtectionMixin, self).get( request, *args, **kwargs) if self.object.login_required and not request.user.is_authenticated: return self.login() if (self.object.password and self.object.password != self.request.session.get(self.session_key % self.object.pk)): return self.password() return response
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svenevs/exhale
exhale/utils.py
sanitize
def sanitize(name): """ Sanitize the specified ``name`` for use with breathe directives. **Parameters** ``name`` (:class:`python:str`) The name to be sanitized. **Return** :class:`python:str` The input ``name`` sanitized to use with breathe directives (primarily for use with ``.. doxygenfunction::``). Replacements such as ``"&lt;" -> "<"`` are performed, as well as removing spaces ``"< " -> "<"`` must be done. Breathe is particularly sensitive with respect to whitespace. """ return name.replace( "&lt;", "<" ).replace( "&gt;", ">" ).replace( "&amp;", "&" ).replace( "< ", "<" ).replace( " >", ">" ).replace( " &", "&" ).replace( "& ", "&" )
python
def sanitize(name): """ Sanitize the specified ``name`` for use with breathe directives. **Parameters** ``name`` (:class:`python:str`) The name to be sanitized. **Return** :class:`python:str` The input ``name`` sanitized to use with breathe directives (primarily for use with ``.. doxygenfunction::``). Replacements such as ``"&lt;" -> "<"`` are performed, as well as removing spaces ``"< " -> "<"`` must be done. Breathe is particularly sensitive with respect to whitespace. """ return name.replace( "&lt;", "<" ).replace( "&gt;", ">" ).replace( "&amp;", "&" ).replace( "< ", "<" ).replace( " >", ">" ).replace( " &", "&" ).replace( "& ", "&" )
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alejandroautalan/pygubu
pygubudesigner/previewer.py
PreviewHelper._get_slot
def _get_slot(self): "Returns the next coordinates for a preview" x = y = 10 for k, p in self.previews.items(): y += p.height() + self.padding return x, y
python
def _get_slot(self): "Returns the next coordinates for a preview" x = y = 10 for k, p in self.previews.items(): y += p.height() + self.padding return x, y
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samastur/pyimagediet
pyimagediet/process.py
determine_type
def determine_type(filename): '''Determine the file type and return it.''' ftype = magic.from_file(filename, mime=True).decode('utf8') if ftype == 'text/plain': ftype = 'text' elif ftype == 'image/svg+xml': ftype = 'svg' else: ftype = ftype.split('/')[1] return ftype
python
def determine_type(filename): '''Determine the file type and return it.''' ftype = magic.from_file(filename, mime=True).decode('utf8') if ftype == 'text/plain': ftype = 'text' elif ftype == 'image/svg+xml': ftype = 'svg' else: ftype = ftype.split('/')[1] return ftype
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DeepHorizons/iarm
iarm_kernel/iarmkernel.py
ArmKernel.magic_postpone_execution
def magic_postpone_execution(self, line): """ Postpone execution of instructions until explicitly run Usage: Call this magic with `true` or nothing to postpone execution, or call with `false` to execute each instruction when evaluated. This defaults to True. Note that each cell is executed only executed after all lines in the cell have been evaluated properly. `%postpone_execution` or `%postpone_execution true` or `%postpone_execution false` """ line = line.strip().lower() if not line or line == 'true': self.interpreter.postpone_execution = True elif line == 'false': self.interpreter.postpone_execution = False else: stream_content = {'name': 'stderr', 'text': "unknwon value '{}'".format(line)} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': ValueError.__name__, 'evalue': "unknwon value '{}'".format(line), 'traceback': '???'}
python
def magic_postpone_execution(self, line): """ Postpone execution of instructions until explicitly run Usage: Call this magic with `true` or nothing to postpone execution, or call with `false` to execute each instruction when evaluated. This defaults to True. Note that each cell is executed only executed after all lines in the cell have been evaluated properly. `%postpone_execution` or `%postpone_execution true` or `%postpone_execution false` """ line = line.strip().lower() if not line or line == 'true': self.interpreter.postpone_execution = True elif line == 'false': self.interpreter.postpone_execution = False else: stream_content = {'name': 'stderr', 'text': "unknwon value '{}'".format(line)} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': ValueError.__name__, 'evalue': "unknwon value '{}'".format(line), 'traceback': '???'}
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sternoru/goscalecms
goscale/views.py
signup
def signup(request, **kwargs): """ Overrides allauth.account.views.signup """ if not ALLAUTH: return http.HttpResponse(_('allauth not installed...')) if request.method == "POST" and 'login' in request.POST: form_class = LoginForm form = form_class(request.POST) redirect_field_name = "next" success_url = get_default_redirect(request, redirect_field_name) if form.is_valid(): return form.login(request, redirect_url=success_url) response = allauth_signup(request, **kwargs) return response
python
def signup(request, **kwargs): """ Overrides allauth.account.views.signup """ if not ALLAUTH: return http.HttpResponse(_('allauth not installed...')) if request.method == "POST" and 'login' in request.POST: form_class = LoginForm form = form_class(request.POST) redirect_field_name = "next" success_url = get_default_redirect(request, redirect_field_name) if form.is_valid(): return form.login(request, redirect_url=success_url) response = allauth_signup(request, **kwargs) return response
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agoragames/haigha
haigha/frames/frame.py
Frame.read_frames
def read_frames(cls, reader): ''' Read one or more frames from an IO stream. Buffer must support file object interface. After reading, caller will need to check if there are bytes remaining in the stream. If there are, then that implies that there is one or more incomplete frames and more data needs to be read. The position of the cursor in the frame stream will mark the point at which the last good frame was read. If the caller is expecting a sequence of frames and only received a part of that sequence, they are responsible for buffering those frames until the rest of the frames in the sequence have arrived. ''' rval = deque() while True: frame_start_pos = reader.tell() try: frame = Frame._read_frame(reader) except Reader.BufferUnderflow: # No more data in the stream frame = None except Reader.ReaderError as e: # Some other format error raise Frame.FormatError, str(e), sys.exc_info()[-1] except struct.error as e: raise Frame.FormatError, str(e), sys.exc_info()[-1] if frame is None: reader.seek(frame_start_pos) break rval.append(frame) return rval
python
def read_frames(cls, reader): ''' Read one or more frames from an IO stream. Buffer must support file object interface. After reading, caller will need to check if there are bytes remaining in the stream. If there are, then that implies that there is one or more incomplete frames and more data needs to be read. The position of the cursor in the frame stream will mark the point at which the last good frame was read. If the caller is expecting a sequence of frames and only received a part of that sequence, they are responsible for buffering those frames until the rest of the frames in the sequence have arrived. ''' rval = deque() while True: frame_start_pos = reader.tell() try: frame = Frame._read_frame(reader) except Reader.BufferUnderflow: # No more data in the stream frame = None except Reader.ReaderError as e: # Some other format error raise Frame.FormatError, str(e), sys.exc_info()[-1] except struct.error as e: raise Frame.FormatError, str(e), sys.exc_info()[-1] if frame is None: reader.seek(frame_start_pos) break rval.append(frame) return rval
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train
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agile-geoscience/welly
welly/curve.py
Curve.interpolate_where
def interpolate_where(self, condition): """ Remove then interpolate across """ raise NotImplementedError() self[self < 0] = np.nan return self.interpolate()
python
def interpolate_where(self, condition): """ Remove then interpolate across """ raise NotImplementedError() self[self < 0] = np.nan return self.interpolate()
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tanghaibao/goatools
goatools/grouper/plotobj.py
PltGroupedGos._plot_go_group
def _plot_go_group(self, hdrgo, usrgos, pltargs, go2parentids): """Plot an exploratory GO DAG for a single Group of user GOs.""" gosubdagplotnts = self._get_gosubdagplotnts(hdrgo, usrgos, pltargs, go2parentids) # Create pngs and return png names pngs = [obj.wrplt(pltargs.fout_dir, pltargs.plt_ext) for obj in gosubdagplotnts] return pngs
python
def _plot_go_group(self, hdrgo, usrgos, pltargs, go2parentids): """Plot an exploratory GO DAG for a single Group of user GOs.""" gosubdagplotnts = self._get_gosubdagplotnts(hdrgo, usrgos, pltargs, go2parentids) # Create pngs and return png names pngs = [obj.wrplt(pltargs.fout_dir, pltargs.plt_ext) for obj in gosubdagplotnts] return pngs
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quintusdias/glymur
glymur/jp2box.py
FragmentTableBox._validate
def _validate(self, writing=False): """Self-validate the box before writing.""" box_ids = [box.box_id for box in self.box] if len(box_ids) != 1 or box_ids[0] != 'flst': msg = ("Fragment table boxes must have a single fragment list " "box as a child box.") self._dispatch_validation_error(msg, writing=writing)
python
def _validate(self, writing=False): """Self-validate the box before writing.""" box_ids = [box.box_id for box in self.box] if len(box_ids) != 1 or box_ids[0] != 'flst': msg = ("Fragment table boxes must have a single fragment list " "box as a child box.") self._dispatch_validation_error(msg, writing=writing)
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apache/incubator-mxnet
python/mxnet/ndarray/sparse.py
_new_alloc_handle
def _new_alloc_handle(stype, shape, ctx, delay_alloc, dtype, aux_types, aux_shapes=None): """Return a new handle with specified storage type, shape, dtype and context. Empty handle is only used to hold results Returns ------- handle A new empty ndarray handle """ hdl = NDArrayHandle() for aux_t in aux_types: if np.dtype(aux_t) != np.dtype("int64"): raise NotImplementedError("only int64 is supported for aux types") aux_type_ids = [int(_DTYPE_NP_TO_MX[np.dtype(aux_t).type]) for aux_t in aux_types] aux_shapes = [(0,) for aux_t in aux_types] if aux_shapes is None else aux_shapes aux_shape_lens = [len(aux_shape) for aux_shape in aux_shapes] aux_shapes = py_sum(aux_shapes, ()) num_aux = mx_uint(len(aux_types)) check_call(_LIB.MXNDArrayCreateSparseEx( ctypes.c_int(int(_STORAGE_TYPE_STR_TO_ID[stype])), c_array_buf(mx_uint, native_array('I', shape)), mx_uint(len(shape)), ctypes.c_int(ctx.device_typeid), ctypes.c_int(ctx.device_id), ctypes.c_int(int(delay_alloc)), ctypes.c_int(int(_DTYPE_NP_TO_MX[np.dtype(dtype).type])), num_aux, c_array_buf(ctypes.c_int, native_array('i', aux_type_ids)), c_array_buf(mx_uint, native_array('I', aux_shape_lens)), c_array_buf(mx_uint, native_array('I', aux_shapes)), ctypes.byref(hdl))) return hdl
python
def _new_alloc_handle(stype, shape, ctx, delay_alloc, dtype, aux_types, aux_shapes=None): """Return a new handle with specified storage type, shape, dtype and context. Empty handle is only used to hold results Returns ------- handle A new empty ndarray handle """ hdl = NDArrayHandle() for aux_t in aux_types: if np.dtype(aux_t) != np.dtype("int64"): raise NotImplementedError("only int64 is supported for aux types") aux_type_ids = [int(_DTYPE_NP_TO_MX[np.dtype(aux_t).type]) for aux_t in aux_types] aux_shapes = [(0,) for aux_t in aux_types] if aux_shapes is None else aux_shapes aux_shape_lens = [len(aux_shape) for aux_shape in aux_shapes] aux_shapes = py_sum(aux_shapes, ()) num_aux = mx_uint(len(aux_types)) check_call(_LIB.MXNDArrayCreateSparseEx( ctypes.c_int(int(_STORAGE_TYPE_STR_TO_ID[stype])), c_array_buf(mx_uint, native_array('I', shape)), mx_uint(len(shape)), ctypes.c_int(ctx.device_typeid), ctypes.c_int(ctx.device_id), ctypes.c_int(int(delay_alloc)), ctypes.c_int(int(_DTYPE_NP_TO_MX[np.dtype(dtype).type])), num_aux, c_array_buf(ctypes.c_int, native_array('i', aux_type_ids)), c_array_buf(mx_uint, native_array('I', aux_shape_lens)), c_array_buf(mx_uint, native_array('I', aux_shapes)), ctypes.byref(hdl))) return hdl
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https://github.com/apache/incubator-mxnet/blob/1af29e9c060a4c7d60eeaacba32afdb9a7775ba7/python/mxnet/ndarray/sparse.py#L72-L104
8,518
pdkit/pdkit
pdkit/gait_processor.py
GaitProcessor.gait
def gait(self, x): """ Extract gait features from estimated heel strikes and accelerometer data. :param x: The time series to assess freeze of gait on. This could be x, y, z or mag_sum_acc. :type x: pandas.Series :return number_of_steps: Estimated number of steps based on heel strikes [number of steps]. :rtype number_of_steps: int :return velocity: Velocity (if distance is provided) [meters/second]. :rtype velocity: float :return avg_step_length: Average step length (if distance is provided) [meters]. :rtype avg_step_length: float :return avg_stride_length: Average stride length (if distance is provided) [meters]. :rtyoe avg_stride_length: float :return cadence: Number of steps divided by duration [steps/second]. :rtype cadence: float :return array step_durations: Step duration [seconds]. :rtype step_durations: np.ndarray :return float avg_step_duration: Average step duration [seconds]. :rtype avg_step_duration: float :return float sd_step_durations: Standard deviation of step durations [seconds]. :rtype sd_step_durations: np.ndarray :return list strides: Stride timings for each side [seconds]. :rtype strides: numpy.ndarray :return float avg_number_of_strides: Estimated number of strides based on alternating heel strikes [number of strides]. :rtype avg_number_of_strides: float :return list stride_durations: Estimated stride durations [seconds]. :rtype stride_durations: numpy.ndarray :return float avg_stride_duration: Average stride duration [seconds]. :rtype avg_stride_duration: float :return float sd_step_durations: Standard deviation of stride durations [seconds]. :rtype sd_step_duration: float :return float step_regularity: Measure of step regularity along axis [percentage consistency of the step-to-step pattern]. :rtype step_regularity: float :return float stride_regularity: Measure of stride regularity along axis [percentage consistency of the stride-to-stride pattern]. :rtype stride_regularity: float :return float symmetry: Measure of gait symmetry along axis [difference between step and stride regularity]. :rtype symmetry: float """ data = x strikes, _ = self.heel_strikes(data) step_durations = [] for i in range(1, np.size(strikes)): step_durations.append(strikes[i] - strikes[i-1]) avg_step_duration = np.mean(step_durations) sd_step_durations = np.std(step_durations) number_of_steps = np.size(strikes) strides1 = strikes[0::2] strides2 = strikes[1::2] stride_durations1 = [] for i in range(1, np.size(strides1)): stride_durations1.append(strides1[i] - strides1[i-1]) stride_durations2 = [] for i in range(1, np.size(strides2)): stride_durations2.append(strides2[i] - strides2[i-1]) strides = [strides1, strides2] stride_durations = [stride_durations1, stride_durations2] avg_number_of_strides = np.mean([np.size(strides1), np.size(strides2)]) avg_stride_duration = np.mean((np.mean(stride_durations1), np.mean(stride_durations2))) sd_stride_durations = np.mean((np.std(stride_durations1), np.std(stride_durations2))) step_period = np.int(np.round(1 / avg_step_duration)) stride_period = np.int(np.round(1 / avg_stride_duration)) step_regularity, stride_regularity, symmetry = self.gait_regularity_symmetry(data, average_step_duration=avg_step_duration, average_stride_duration=avg_stride_duration) cadence = None if self.duration: cadence = number_of_steps / self.duration velocity = None avg_step_length = None avg_stride_length = None if self.distance: velocity = self.distance / self.duration avg_step_length = number_of_steps / self.distance avg_stride_length = avg_number_of_strides / self.distance return [number_of_steps, cadence, velocity, avg_step_length, avg_stride_length, step_durations, avg_step_duration, sd_step_durations, strides, stride_durations, avg_number_of_strides, avg_stride_duration, sd_stride_durations, step_regularity, stride_regularity, symmetry]
python
def gait(self, x): """ Extract gait features from estimated heel strikes and accelerometer data. :param x: The time series to assess freeze of gait on. This could be x, y, z or mag_sum_acc. :type x: pandas.Series :return number_of_steps: Estimated number of steps based on heel strikes [number of steps]. :rtype number_of_steps: int :return velocity: Velocity (if distance is provided) [meters/second]. :rtype velocity: float :return avg_step_length: Average step length (if distance is provided) [meters]. :rtype avg_step_length: float :return avg_stride_length: Average stride length (if distance is provided) [meters]. :rtyoe avg_stride_length: float :return cadence: Number of steps divided by duration [steps/second]. :rtype cadence: float :return array step_durations: Step duration [seconds]. :rtype step_durations: np.ndarray :return float avg_step_duration: Average step duration [seconds]. :rtype avg_step_duration: float :return float sd_step_durations: Standard deviation of step durations [seconds]. :rtype sd_step_durations: np.ndarray :return list strides: Stride timings for each side [seconds]. :rtype strides: numpy.ndarray :return float avg_number_of_strides: Estimated number of strides based on alternating heel strikes [number of strides]. :rtype avg_number_of_strides: float :return list stride_durations: Estimated stride durations [seconds]. :rtype stride_durations: numpy.ndarray :return float avg_stride_duration: Average stride duration [seconds]. :rtype avg_stride_duration: float :return float sd_step_durations: Standard deviation of stride durations [seconds]. :rtype sd_step_duration: float :return float step_regularity: Measure of step regularity along axis [percentage consistency of the step-to-step pattern]. :rtype step_regularity: float :return float stride_regularity: Measure of stride regularity along axis [percentage consistency of the stride-to-stride pattern]. :rtype stride_regularity: float :return float symmetry: Measure of gait symmetry along axis [difference between step and stride regularity]. :rtype symmetry: float """ data = x strikes, _ = self.heel_strikes(data) step_durations = [] for i in range(1, np.size(strikes)): step_durations.append(strikes[i] - strikes[i-1]) avg_step_duration = np.mean(step_durations) sd_step_durations = np.std(step_durations) number_of_steps = np.size(strikes) strides1 = strikes[0::2] strides2 = strikes[1::2] stride_durations1 = [] for i in range(1, np.size(strides1)): stride_durations1.append(strides1[i] - strides1[i-1]) stride_durations2 = [] for i in range(1, np.size(strides2)): stride_durations2.append(strides2[i] - strides2[i-1]) strides = [strides1, strides2] stride_durations = [stride_durations1, stride_durations2] avg_number_of_strides = np.mean([np.size(strides1), np.size(strides2)]) avg_stride_duration = np.mean((np.mean(stride_durations1), np.mean(stride_durations2))) sd_stride_durations = np.mean((np.std(stride_durations1), np.std(stride_durations2))) step_period = np.int(np.round(1 / avg_step_duration)) stride_period = np.int(np.round(1 / avg_stride_duration)) step_regularity, stride_regularity, symmetry = self.gait_regularity_symmetry(data, average_step_duration=avg_step_duration, average_stride_duration=avg_stride_duration) cadence = None if self.duration: cadence = number_of_steps / self.duration velocity = None avg_step_length = None avg_stride_length = None if self.distance: velocity = self.distance / self.duration avg_step_length = number_of_steps / self.distance avg_stride_length = avg_number_of_strides / self.distance return [number_of_steps, cadence, velocity, avg_step_length, avg_stride_length, step_durations, avg_step_duration, sd_step_durations, strides, stride_durations, avg_number_of_strides, avg_stride_duration, sd_stride_durations, step_regularity, stride_regularity, symmetry]
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Extract gait features from estimated heel strikes and accelerometer data. :param x: The time series to assess freeze of gait on. This could be x, y, z or mag_sum_acc. :type x: pandas.Series :return number_of_steps: Estimated number of steps based on heel strikes [number of steps]. :rtype number_of_steps: int :return velocity: Velocity (if distance is provided) [meters/second]. :rtype velocity: float :return avg_step_length: Average step length (if distance is provided) [meters]. :rtype avg_step_length: float :return avg_stride_length: Average stride length (if distance is provided) [meters]. :rtyoe avg_stride_length: float :return cadence: Number of steps divided by duration [steps/second]. :rtype cadence: float :return array step_durations: Step duration [seconds]. :rtype step_durations: np.ndarray :return float avg_step_duration: Average step duration [seconds]. :rtype avg_step_duration: float :return float sd_step_durations: Standard deviation of step durations [seconds]. :rtype sd_step_durations: np.ndarray :return list strides: Stride timings for each side [seconds]. :rtype strides: numpy.ndarray :return float avg_number_of_strides: Estimated number of strides based on alternating heel strikes [number of strides]. :rtype avg_number_of_strides: float :return list stride_durations: Estimated stride durations [seconds]. :rtype stride_durations: numpy.ndarray :return float avg_stride_duration: Average stride duration [seconds]. :rtype avg_stride_duration: float :return float sd_step_durations: Standard deviation of stride durations [seconds]. :rtype sd_step_duration: float :return float step_regularity: Measure of step regularity along axis [percentage consistency of the step-to-step pattern]. :rtype step_regularity: float :return float stride_regularity: Measure of stride regularity along axis [percentage consistency of the stride-to-stride pattern]. :rtype stride_regularity: float :return float symmetry: Measure of gait symmetry along axis [difference between step and stride regularity]. :rtype symmetry: float
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def hashcomplement(a, b, strict=False): """ Alternative implementation of :func:`petl.transform.setops.complement`, where the complement is executed by constructing an in-memory set for all rows found in the right hand table, then iterating over rows from the left hand table. May be faster and/or more resource efficient where the right table is small and the left table is large. .. versionchanged:: 1.1.0 If `strict` is `True` then strict set-like behaviour is used, i.e., only rows in `a` not found in `b` are returned. """ return HashComplementView(a, b, strict=strict)
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python
def get_status(self, channel=Channel.CHANNEL_CH0): """ Returns the error status of a specific CAN channel. :param int channel: CAN channel, to be used (:data:`Channel.CHANNEL_CH0` or :data:`Channel.CHANNEL_CH1`). :return: Tuple with CAN and USB status (see structure :class:`Status`). :rtype: tuple(int, int) """ status = Status() UcanGetStatusEx(self._handle, channel, byref(status)) return status.can_status, status.usb_status
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def parseAcceptHeader(value): """Parse an accept header, ignoring any accept-extensions returns a list of tuples containing main MIME type, MIME subtype, and quality markdown. str -> [(str, str, float)] """ chunks = [chunk.strip() for chunk in value.split(',')] accept = [] for chunk in chunks: parts = [s.strip() for s in chunk.split(';')] mtype = parts.pop(0) if '/' not in mtype: # This is not a MIME type, so ignore the bad data continue main, sub = mtype.split('/', 1) for ext in parts: if '=' in ext: k, v = ext.split('=', 1) if k == 'q': try: q = float(v) break except ValueError: # Ignore poorly formed q-values pass else: q = 1.0 accept.append((q, main, sub)) accept.sort() accept.reverse() return [(main, sub, q) for (q, main, sub) in accept]
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def _run(*args, **kwargs): """ Run current executable via subprocess and given args """ verbose = kwargs.pop("verbose", False) if verbose: click.secho(" ".join([repr(i) for i in args]), bg='blue', fg='white') executable = args[0] if not os.path.isfile(executable): raise RuntimeError("First argument %r is not a existing file!" % executable) if not os.access(executable, os.X_OK): raise RuntimeError("First argument %r exist, but is not executeable!" % executable) return subprocess.Popen(args, **kwargs)
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def _run(*args, **kwargs): """ Run current executable via subprocess and given args """ verbose = kwargs.pop("verbose", False) if verbose: click.secho(" ".join([repr(i) for i in args]), bg='blue', fg='white') executable = args[0] if not os.path.isfile(executable): raise RuntimeError("First argument %r is not a existing file!" % executable) if not os.access(executable, os.X_OK): raise RuntimeError("First argument %r exist, but is not executeable!" % executable) return subprocess.Popen(args, **kwargs)
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python
def i2c_master_write_read(self, i2c_address, data, length): """Make an I2C write/read access. First an I2C write access is issued. No stop condition will be generated. Instead the read access begins with a repeated start. This method is useful for accessing most addressable I2C devices like EEPROMs, port expander, etc. Basically, this is just a convenient function which internally uses `i2c_master_write` and `i2c_master_read`. """ self.i2c_master_write(i2c_address, data, I2C_NO_STOP) return self.i2c_master_read(i2c_address, length)
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deepmind/sonnet
sonnet/python/modules/scale_gradient.py
_scale_gradient_op
def _scale_gradient_op(dtype): """Create an op that scales gradients using a Defun. The tensorflow Defun decorator creates an op and tensorflow caches these ops automatically according to `func_name`. Using a Defun decorator twice with the same `func_name` does not create a new op, instead the cached op is used. This method produces a new op the first time it is called with a given `dtype` argument, and then uses the cached op each time it is called after that with the same `dtype`. The scale value is given as an argument for the forward pass method so that it can be used in the backwards pass. Args: dtype: the dtype of the net whose gradient is being scaled. Returns: The op that scales gradients. """ def scale_gradient_backward(op, grad): scale = op.inputs[1] scaled_grad = grad * scale return scaled_grad, None # Note that if the forward pass implementation involved the creation of ops, # _scale_gradient_op would require some memoization mechanism. def scale_gradient_forward(x, scale): del scale # Unused. return x func_name = "ScaleGradient_{}".format(dtype.name) return function.Defun( dtype, dtype, python_grad_func=scale_gradient_backward, func_name=func_name)(scale_gradient_forward)
python
def _scale_gradient_op(dtype): """Create an op that scales gradients using a Defun. The tensorflow Defun decorator creates an op and tensorflow caches these ops automatically according to `func_name`. Using a Defun decorator twice with the same `func_name` does not create a new op, instead the cached op is used. This method produces a new op the first time it is called with a given `dtype` argument, and then uses the cached op each time it is called after that with the same `dtype`. The scale value is given as an argument for the forward pass method so that it can be used in the backwards pass. Args: dtype: the dtype of the net whose gradient is being scaled. Returns: The op that scales gradients. """ def scale_gradient_backward(op, grad): scale = op.inputs[1] scaled_grad = grad * scale return scaled_grad, None # Note that if the forward pass implementation involved the creation of ops, # _scale_gradient_op would require some memoization mechanism. def scale_gradient_forward(x, scale): del scale # Unused. return x func_name = "ScaleGradient_{}".format(dtype.name) return function.Defun( dtype, dtype, python_grad_func=scale_gradient_backward, func_name=func_name)(scale_gradient_forward)
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williamfzc/ConnectionTracer
ConnectionTracer/connection.py
reboot_adb_server
def reboot_adb_server(): """ execute 'adb devices' to start adb server """ _reboot_count = 0 _max_retry = 1 def _reboot(): nonlocal _reboot_count if _reboot_count >= _max_retry: raise RuntimeError('fail after retry {} times'.format(_max_retry)) _reboot_count += 1 return_code = subprocess.call(['adb', 'devices'], stdout=subprocess.DEVNULL) if bool(return_code): warnings.warn('return not zero, execute "adb version" failed') raise EnvironmentError('adb did not work :(') return _reboot
python
def reboot_adb_server(): """ execute 'adb devices' to start adb server """ _reboot_count = 0 _max_retry = 1 def _reboot(): nonlocal _reboot_count if _reboot_count >= _max_retry: raise RuntimeError('fail after retry {} times'.format(_max_retry)) _reboot_count += 1 return_code = subprocess.call(['adb', 'devices'], stdout=subprocess.DEVNULL) if bool(return_code): warnings.warn('return not zero, execute "adb version" failed') raise EnvironmentError('adb did not work :(') return _reboot
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spacetelescope/drizzlepac
drizzlepac/tweakutils.py
read_ASCII_cols
def read_ASCII_cols(infile, cols=[1, 2, 3]): # noqa: N802 """ Interpret input ASCII file to return arrays for specified columns. Notes ----- The specification of the columns should be expected to have lists for each 'column', with all columns in each list combined into a single entry. For example:: cols = ['1,2,3','4,5,6',7] where '1,2,3' represent the X/RA values, '4,5,6' represent the Y/Dec values and 7 represents the flux value for a total of 3 requested columns of data to be returned. Returns ------- outarr : list of arrays The return value will be a list of numpy arrays, one for each 'column'. """ # build dictionary representing format of each row # Format of dictionary: {'colname':col_number,...} # This provides the mapping between column name and column number coldict = {} with open(infile, 'r') as f: flines = f.readlines() for l in flines: # interpret each line from catalog file if l[0].lstrip() == '#' or l.lstrip() == '': continue else: # convert first row of data into column definitions using indices coldict = {str(i + 1): i for i, _ in enumerate(l.split())} break numcols = len(cols) outarr = [[] for _ in range(numcols)] convert_radec = False # Now, map specified columns to columns in file and populate output arrays for l in flines: # interpret each line from catalog file l = l.strip() lspl = l.split() # skip blank lines, comment lines, or lines with # fewer columns than requested by user if not l or len(lspl) < numcols or l[0] == '#' or "INDEF" in l: continue # For each 'column' requested by user, pull data from row for c, i in zip(cols, list(range(numcols))): cnames = parse_colname(c) if len(cnames) > 1: # interpret multi-column specification as one value outval = '' for cn in cnames: cnum = coldict[cn] cval = lspl[cnum] outval += cval + ' ' outarr[i].append(outval) convert_radec = True else: # pull single value from row for this column cnum = coldict[cnames[0]] if isfloat(lspl[cnum]): cval = float(lspl[cnum]) else: cval = lspl[cnum] # Check for multi-column values given as "nn:nn:nn.s" if ':' in cval: cval = cval.replace(':', ' ') convert_radec = True outarr[i].append(cval) # convert multi-column RA/Dec specifications if convert_radec: outra = [] outdec = [] for ra, dec in zip(outarr[0], outarr[1]): radd, decdd = radec_hmstodd(ra, dec) outra.append(radd) outdec.append(decdd) outarr[0] = outra outarr[1] = outdec # convert all lists to numpy arrays for c in range(len(outarr)): outarr[c] = np.array(outarr[c]) return outarr
python
def read_ASCII_cols(infile, cols=[1, 2, 3]): # noqa: N802 """ Interpret input ASCII file to return arrays for specified columns. Notes ----- The specification of the columns should be expected to have lists for each 'column', with all columns in each list combined into a single entry. For example:: cols = ['1,2,3','4,5,6',7] where '1,2,3' represent the X/RA values, '4,5,6' represent the Y/Dec values and 7 represents the flux value for a total of 3 requested columns of data to be returned. Returns ------- outarr : list of arrays The return value will be a list of numpy arrays, one for each 'column'. """ # build dictionary representing format of each row # Format of dictionary: {'colname':col_number,...} # This provides the mapping between column name and column number coldict = {} with open(infile, 'r') as f: flines = f.readlines() for l in flines: # interpret each line from catalog file if l[0].lstrip() == '#' or l.lstrip() == '': continue else: # convert first row of data into column definitions using indices coldict = {str(i + 1): i for i, _ in enumerate(l.split())} break numcols = len(cols) outarr = [[] for _ in range(numcols)] convert_radec = False # Now, map specified columns to columns in file and populate output arrays for l in flines: # interpret each line from catalog file l = l.strip() lspl = l.split() # skip blank lines, comment lines, or lines with # fewer columns than requested by user if not l or len(lspl) < numcols or l[0] == '#' or "INDEF" in l: continue # For each 'column' requested by user, pull data from row for c, i in zip(cols, list(range(numcols))): cnames = parse_colname(c) if len(cnames) > 1: # interpret multi-column specification as one value outval = '' for cn in cnames: cnum = coldict[cn] cval = lspl[cnum] outval += cval + ' ' outarr[i].append(outval) convert_radec = True else: # pull single value from row for this column cnum = coldict[cnames[0]] if isfloat(lspl[cnum]): cval = float(lspl[cnum]) else: cval = lspl[cnum] # Check for multi-column values given as "nn:nn:nn.s" if ':' in cval: cval = cval.replace(':', ' ') convert_radec = True outarr[i].append(cval) # convert multi-column RA/Dec specifications if convert_radec: outra = [] outdec = [] for ra, dec in zip(outarr[0], outarr[1]): radd, decdd = radec_hmstodd(ra, dec) outra.append(radd) outdec.append(decdd) outarr[0] = outra outarr[1] = outdec # convert all lists to numpy arrays for c in range(len(outarr)): outarr[c] = np.array(outarr[c]) return outarr
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blockstack/blockstack-core
blockstack/lib/atlas.py
AtlasZonefileCrawler.find_zonefile_origins
def find_zonefile_origins( self, missing_zfinfo, peer_hostports ): """ Find out which peers can serve which zonefiles """ zonefile_origins = {} # map peer hostport to list of zonefile hashes # which peers can serve each zonefile? for zfhash in missing_zfinfo.keys(): for peer_hostport in peer_hostports: if not zonefile_origins.has_key(peer_hostport): zonefile_origins[peer_hostport] = [] if peer_hostport in missing_zfinfo[zfhash]['peers']: zonefile_origins[peer_hostport].append( zfhash ) return zonefile_origins
python
def find_zonefile_origins( self, missing_zfinfo, peer_hostports ): """ Find out which peers can serve which zonefiles """ zonefile_origins = {} # map peer hostport to list of zonefile hashes # which peers can serve each zonefile? for zfhash in missing_zfinfo.keys(): for peer_hostport in peer_hostports: if not zonefile_origins.has_key(peer_hostport): zonefile_origins[peer_hostport] = [] if peer_hostport in missing_zfinfo[zfhash]['peers']: zonefile_origins[peer_hostport].append( zfhash ) return zonefile_origins
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fred49/linshare-api
linshareapi/cache.py
Invalid.override_familly
def override_familly(self, args): """Look in the current wrapped object to find a cache configuration to override the current default configuration.""" resourceapi = args[0] cache_cfg = resourceapi.cache if cache_cfg.has_key('familly'): self.familly = cache_cfg['familly'] if cache_cfg.has_key('whole_familly'): self.whole_familly = cache_cfg['whole_familly'] if self.familly is None: raise Exception("Invalid familly value for Cache decorator.")
python
def override_familly(self, args): """Look in the current wrapped object to find a cache configuration to override the current default configuration.""" resourceapi = args[0] cache_cfg = resourceapi.cache if cache_cfg.has_key('familly'): self.familly = cache_cfg['familly'] if cache_cfg.has_key('whole_familly'): self.whole_familly = cache_cfg['whole_familly'] if self.familly is None: raise Exception("Invalid familly value for Cache decorator.")
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mapnik/Cascadenik
cascadenik/compile.py
expand_source_declarations
def expand_source_declarations(map_el, dirs, local_conf): """ This provides mechanism for externalizing and sharing data sources. The datasource configs are python files, and layers reference sections within that config: <DataSourcesConfig src="datasources.cfg" /> <Layer class="road major" source_name="planet_osm_major_roads" /> <Layer class="road minor" source_name="planet_osm_minor_roads" /> See example_dscfg.mml and example.cfg at the root of the cascadenik directory for an example. """ ds = sources.DataSources(dirs.source, local_conf) # build up the configuration for spec in map_el.findall('DataSourcesConfig'): map_el.remove(spec) src_text, local_base = fetch_embedded_or_remote_src(spec, dirs) if not src_text: continue ds.add_config(src_text, local_base) # now transform the xml # add in base datasources for base_name in ds.templates: b = Element("Datasource", name=base_name) for pname, pvalue in ds.sources[base_name]['parameters'].items(): p = Element("Parameter", name=pname) p.text = str(pvalue) b.append(p) map_el.insert(0, b) # expand layer data sources for layer in map_el.findall('Layer'): if 'source_name' not in layer.attrib: continue if layer.attrib['source_name'] not in ds.sources: raise Exception("Datasource '%s' referenced, but not defined in layer:\n%s" % (layer.attrib['source_name'], ElementTree.tostring(layer))) # create the nested datasource object b = Element("Datasource") dsrc = ds.sources[layer.attrib['source_name']] if 'template' in dsrc: b.attrib['base'] = dsrc['template'] # set the SRS if present if 'layer_srs' in dsrc: layer.attrib['srs'] = dsrc['layer_srs'] for pname, pvalue in dsrc['parameters'].items(): p = Element("Parameter", name=pname) p.text = pvalue b.append(p) layer.append(b) del layer.attrib['source_name']
python
def expand_source_declarations(map_el, dirs, local_conf): """ This provides mechanism for externalizing and sharing data sources. The datasource configs are python files, and layers reference sections within that config: <DataSourcesConfig src="datasources.cfg" /> <Layer class="road major" source_name="planet_osm_major_roads" /> <Layer class="road minor" source_name="planet_osm_minor_roads" /> See example_dscfg.mml and example.cfg at the root of the cascadenik directory for an example. """ ds = sources.DataSources(dirs.source, local_conf) # build up the configuration for spec in map_el.findall('DataSourcesConfig'): map_el.remove(spec) src_text, local_base = fetch_embedded_or_remote_src(spec, dirs) if not src_text: continue ds.add_config(src_text, local_base) # now transform the xml # add in base datasources for base_name in ds.templates: b = Element("Datasource", name=base_name) for pname, pvalue in ds.sources[base_name]['parameters'].items(): p = Element("Parameter", name=pname) p.text = str(pvalue) b.append(p) map_el.insert(0, b) # expand layer data sources for layer in map_el.findall('Layer'): if 'source_name' not in layer.attrib: continue if layer.attrib['source_name'] not in ds.sources: raise Exception("Datasource '%s' referenced, but not defined in layer:\n%s" % (layer.attrib['source_name'], ElementTree.tostring(layer))) # create the nested datasource object b = Element("Datasource") dsrc = ds.sources[layer.attrib['source_name']] if 'template' in dsrc: b.attrib['base'] = dsrc['template'] # set the SRS if present if 'layer_srs' in dsrc: layer.attrib['srs'] = dsrc['layer_srs'] for pname, pvalue in dsrc['parameters'].items(): p = Element("Parameter", name=pname) p.text = pvalue b.append(p) layer.append(b) del layer.attrib['source_name']
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invenio_client/connector.py
InvenioConnector._init_browser
def _init_browser(self): """Overide in appropriate way to prepare a logged in browser.""" self.browser = splinter.Browser('phantomjs') self.browser.visit(self.server_url + "/youraccount/login") try: self.browser.fill('nickname', self.user) self.browser.fill('password', self.password) except: self.browser.fill('p_un', self.user) self.browser.fill('p_pw', self.password) self.browser.fill('login_method', self.login_method) self.browser.find_by_css('input[type=submit]').click()
python
def _init_browser(self): """Overide in appropriate way to prepare a logged in browser.""" self.browser = splinter.Browser('phantomjs') self.browser.visit(self.server_url + "/youraccount/login") try: self.browser.fill('nickname', self.user) self.browser.fill('password', self.password) except: self.browser.fill('p_un', self.user) self.browser.fill('p_pw', self.password) self.browser.fill('login_method', self.login_method) self.browser.find_by_css('input[type=submit]').click()
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pmagpy/ipmag.py
inc_from_lat
def inc_from_lat(lat): """ Calculate inclination predicted from latitude using the dipole equation Parameter ---------- lat : latitude in degrees Returns ------- inc : inclination calculated using the dipole equation """ rad = old_div(np.pi, 180.) inc = old_div(np.arctan(2 * np.tan(lat * rad)), rad) return inc
python
def inc_from_lat(lat): """ Calculate inclination predicted from latitude using the dipole equation Parameter ---------- lat : latitude in degrees Returns ------- inc : inclination calculated using the dipole equation """ rad = old_div(np.pi, 180.) inc = old_div(np.arctan(2 * np.tan(lat * rad)), rad) return inc
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apputils/settings/general.py
Configuration._load_modules
def _load_modules(self): """ Load modules-related configuration listened in modules section Before loading: "modules": { "mal": "myanimelist.json", "ann": "animenewsnetwork.json" } After loading: "modules": { "mal": { .... }, "ann": { .... } } """ if self.exists("modules"): for item in self._json["modules"]: try: json_data = json.loads(self._load_from_configs(self._json["modules"][item])) self._json["modules"][item] = json_data except Exception as err: raise FileNotFoundError("Couldn't load module {} configuration from {}: {}".format(item, self._json["modules"][item], err))
python
def _load_modules(self): """ Load modules-related configuration listened in modules section Before loading: "modules": { "mal": "myanimelist.json", "ann": "animenewsnetwork.json" } After loading: "modules": { "mal": { .... }, "ann": { .... } } """ if self.exists("modules"): for item in self._json["modules"]: try: json_data = json.loads(self._load_from_configs(self._json["modules"][item])) self._json["modules"][item] = json_data except Exception as err: raise FileNotFoundError("Couldn't load module {} configuration from {}: {}".format(item, self._json["modules"][item], err))
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hendrix/contrib/cache/backends/memory_cache.py
MemoryCacheBackend.addResource
def addResource(self, content, uri, headers): """ Adds the a hendrix.contrib.cache.resource.CachedResource to the ReverseProxy cache connection """ self.cache[uri] = CachedResource(content, headers)
python
def addResource(self, content, uri, headers): """ Adds the a hendrix.contrib.cache.resource.CachedResource to the ReverseProxy cache connection """ self.cache[uri] = CachedResource(content, headers)
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delphi/translators/for2py/arrays.py
array_values
def array_values(expr): """Given an expression expr denoting a list of values, array_values(expr) returns a list of values for that expression.""" if isinstance(expr, Array): return expr.get_elems(all_subs(expr._bounds)) elif isinstance(expr, list): vals = [array_values(x) for x in expr] return flatten(vals) else: return [expr]
python
def array_values(expr): """Given an expression expr denoting a list of values, array_values(expr) returns a list of values for that expression.""" if isinstance(expr, Array): return expr.get_elems(all_subs(expr._bounds)) elif isinstance(expr, list): vals = [array_values(x) for x in expr] return flatten(vals) else: return [expr]
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brocade/pynos
pynos/versions/ver_7/ver_7_1_0/yang/brocade_snmp.py
brocade_snmp.snmp_server_group_write
def snmp_server_group_write(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") snmp_server = ET.SubElement(config, "snmp-server", xmlns="urn:brocade.com:mgmt:brocade-snmp") group = ET.SubElement(snmp_server, "group") group_name_key = ET.SubElement(group, "group-name") group_name_key.text = kwargs.pop('group_name') group_version_key = ET.SubElement(group, "group-version") group_version_key.text = kwargs.pop('group_version') write = ET.SubElement(group, "write") write.text = kwargs.pop('write') callback = kwargs.pop('callback', self._callback) return callback(config)
python
def snmp_server_group_write(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") snmp_server = ET.SubElement(config, "snmp-server", xmlns="urn:brocade.com:mgmt:brocade-snmp") group = ET.SubElement(snmp_server, "group") group_name_key = ET.SubElement(group, "group-name") group_name_key.text = kwargs.pop('group_name') group_version_key = ET.SubElement(group, "group-version") group_version_key.text = kwargs.pop('group_version') write = ET.SubElement(group, "write") write.text = kwargs.pop('write') callback = kwargs.pop('callback', self._callback) return callback(config)
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xtrementl/focus
focus/plugin/modules/tasks.py
_print_tasks
def _print_tasks(env, tasks, mark_active=False): """ Prints task information using io stream. `env` ``Environment`` object. `tasks` List of tuples (task_name, options, block_options). `mark_active` Set to ``True`` to mark active task. """ if env.task.active and mark_active: active_task = env.task.name else: active_task = None for task, options, blocks in tasks: # print heading invalid = False if task == active_task: method = 'success' else: if options is None and blocks is None: method = 'error' invalid = True else: method = 'write' opts = list(options or []) blks = list(blocks or []) write = getattr(env.io, method) write('~' * 80) write(' ' + task) write('~' * 80) env.io.write('') # non-block options if opts: for opt, values in opts: env.io.write(' {0}: {1}'.format(opt, ', '.join(str(v) for v in values))) env.io.write('') # block options if blks: had_options = False for block, options in blks: if options: had_options = True env.io.write(' {{ {0} }}'.format(block)) for opt, values in options: env.io.write(' {0}: {1}'.format(opt, ', '.join(str(v) for v in values))) env.io.write('') if not had_options: blks = None if not opts and not blks: if invalid: env.io.write(' Invalid task.') else: env.io.write(' Empty task.') env.io.write('')
python
def _print_tasks(env, tasks, mark_active=False): """ Prints task information using io stream. `env` ``Environment`` object. `tasks` List of tuples (task_name, options, block_options). `mark_active` Set to ``True`` to mark active task. """ if env.task.active and mark_active: active_task = env.task.name else: active_task = None for task, options, blocks in tasks: # print heading invalid = False if task == active_task: method = 'success' else: if options is None and blocks is None: method = 'error' invalid = True else: method = 'write' opts = list(options or []) blks = list(blocks or []) write = getattr(env.io, method) write('~' * 80) write(' ' + task) write('~' * 80) env.io.write('') # non-block options if opts: for opt, values in opts: env.io.write(' {0}: {1}'.format(opt, ', '.join(str(v) for v in values))) env.io.write('') # block options if blks: had_options = False for block, options in blks: if options: had_options = True env.io.write(' {{ {0} }}'.format(block)) for opt, values in options: env.io.write(' {0}: {1}'.format(opt, ', '.join(str(v) for v in values))) env.io.write('') if not had_options: blks = None if not opts and not blks: if invalid: env.io.write(' Invalid task.') else: env.io.write(' Empty task.') env.io.write('')
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denisenkom/django-sqlserver
sqlserver/base.py
_get_new_connection
def _get_new_connection(self, conn_params): """Opens a connection to the database.""" self.__connection_string = conn_params.get('connection_string', '') conn = self.Database.connect(**conn_params) return conn
python
def _get_new_connection(self, conn_params): """Opens a connection to the database.""" self.__connection_string = conn_params.get('connection_string', '') conn = self.Database.connect(**conn_params) return conn
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aws/sagemaker-python-sdk
src/sagemaker/session.py
Session.default_bucket
def default_bucket(self): """Return the name of the default bucket to use in relevant Amazon SageMaker interactions. Returns: str: The name of the default bucket, which is of the form: ``sagemaker-{region}-{AWS account ID}``. """ if self._default_bucket: return self._default_bucket account = self.boto_session.client('sts').get_caller_identity()['Account'] region = self.boto_session.region_name default_bucket = 'sagemaker-{}-{}'.format(region, account) s3 = self.boto_session.resource('s3') try: # 'us-east-1' cannot be specified because it is the default region: # https://github.com/boto/boto3/issues/125 if region == 'us-east-1': s3.create_bucket(Bucket=default_bucket) else: s3.create_bucket(Bucket=default_bucket, CreateBucketConfiguration={'LocationConstraint': region}) LOGGER.info('Created S3 bucket: {}'.format(default_bucket)) except ClientError as e: error_code = e.response['Error']['Code'] message = e.response['Error']['Message'] if error_code == 'BucketAlreadyOwnedByYou': pass elif error_code == 'OperationAborted' and 'conflicting conditional operation' in message: # If this bucket is already being concurrently created, we don't need to create it again. pass elif error_code == 'TooManyBuckets': # Succeed if the default bucket exists s3.meta.client.head_bucket(Bucket=default_bucket) else: raise self._default_bucket = default_bucket return self._default_bucket
python
def default_bucket(self): """Return the name of the default bucket to use in relevant Amazon SageMaker interactions. Returns: str: The name of the default bucket, which is of the form: ``sagemaker-{region}-{AWS account ID}``. """ if self._default_bucket: return self._default_bucket account = self.boto_session.client('sts').get_caller_identity()['Account'] region = self.boto_session.region_name default_bucket = 'sagemaker-{}-{}'.format(region, account) s3 = self.boto_session.resource('s3') try: # 'us-east-1' cannot be specified because it is the default region: # https://github.com/boto/boto3/issues/125 if region == 'us-east-1': s3.create_bucket(Bucket=default_bucket) else: s3.create_bucket(Bucket=default_bucket, CreateBucketConfiguration={'LocationConstraint': region}) LOGGER.info('Created S3 bucket: {}'.format(default_bucket)) except ClientError as e: error_code = e.response['Error']['Code'] message = e.response['Error']['Message'] if error_code == 'BucketAlreadyOwnedByYou': pass elif error_code == 'OperationAborted' and 'conflicting conditional operation' in message: # If this bucket is already being concurrently created, we don't need to create it again. pass elif error_code == 'TooManyBuckets': # Succeed if the default bucket exists s3.meta.client.head_bucket(Bucket=default_bucket) else: raise self._default_bucket = default_bucket return self._default_bucket
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ccmlib/common.py
wait_for_any_log
def wait_for_any_log(nodes, pattern, timeout, filename='system.log', marks=None): """ Look for a pattern in the system.log of any in a given list of nodes. @param nodes The list of nodes whose logs to scan @param pattern The target pattern @param timeout How long to wait for the pattern. Note that strictly speaking, timeout is not really a timeout, but a maximum number of attempts. This implies that the all the grepping takes no time at all, so it is somewhat inaccurate, but probably close enough. @param marks A dict of nodes to marks in the file. Keys must match the first param list. @return The first node in whose log the pattern was found """ if marks is None: marks = {} for _ in range(timeout): for node in nodes: found = node.grep_log(pattern, filename=filename, from_mark=marks.get(node, None)) if found: return node time.sleep(1) raise TimeoutError(time.strftime("%d %b %Y %H:%M:%S", time.gmtime()) + " Unable to find: " + repr(pattern) + " in any node log within " + str(timeout) + "s")
python
def wait_for_any_log(nodes, pattern, timeout, filename='system.log', marks=None): """ Look for a pattern in the system.log of any in a given list of nodes. @param nodes The list of nodes whose logs to scan @param pattern The target pattern @param timeout How long to wait for the pattern. Note that strictly speaking, timeout is not really a timeout, but a maximum number of attempts. This implies that the all the grepping takes no time at all, so it is somewhat inaccurate, but probably close enough. @param marks A dict of nodes to marks in the file. Keys must match the first param list. @return The first node in whose log the pattern was found """ if marks is None: marks = {} for _ in range(timeout): for node in nodes: found = node.grep_log(pattern, filename=filename, from_mark=marks.get(node, None)) if found: return node time.sleep(1) raise TimeoutError(time.strftime("%d %b %Y %H:%M:%S", time.gmtime()) + " Unable to find: " + repr(pattern) + " in any node log within " + str(timeout) + "s")
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paragbaxi/qualysapi
qualysapi/connector.py
QGConnector.url_api_version
def url_api_version(self, api_version): """ Return base API url string for the QualysGuard api_version and server. """ # Set base url depending on API version. if api_version == 1: # QualysGuard API v1 url. url = "https://%s/msp/" % (self.server,) elif api_version == 2: # QualysGuard API v2 url. url = "https://%s/" % (self.server,) elif api_version == 'was': # QualysGuard REST v3 API url (Portal API). url = "https://%s/qps/rest/3.0/" % (self.server,) elif api_version == 'am': # QualysGuard REST v1 API url (Portal API). url = "https://%s/qps/rest/1.0/" % (self.server,) elif api_version == 'am2': # QualysGuard REST v1 API url (Portal API). url = "https://%s/qps/rest/2.0/" % (self.server,) else: raise Exception("Unknown QualysGuard API Version Number (%s)" % (api_version,)) logger.debug("Base url =\n%s" % (url)) return url
python
def url_api_version(self, api_version): """ Return base API url string for the QualysGuard api_version and server. """ # Set base url depending on API version. if api_version == 1: # QualysGuard API v1 url. url = "https://%s/msp/" % (self.server,) elif api_version == 2: # QualysGuard API v2 url. url = "https://%s/" % (self.server,) elif api_version == 'was': # QualysGuard REST v3 API url (Portal API). url = "https://%s/qps/rest/3.0/" % (self.server,) elif api_version == 'am': # QualysGuard REST v1 API url (Portal API). url = "https://%s/qps/rest/1.0/" % (self.server,) elif api_version == 'am2': # QualysGuard REST v1 API url (Portal API). url = "https://%s/qps/rest/2.0/" % (self.server,) else: raise Exception("Unknown QualysGuard API Version Number (%s)" % (api_version,)) logger.debug("Base url =\n%s" % (url)) return url
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ssalentin/plip
plip/modules/chimeraplip.py
ChimeraVisualizer.update_model_dict
def update_model_dict(self): """Updates the model dictionary""" dct = {} models = self.chimera.openModels for md in models.list(): dct[md.name] = md.id self.model_dict = dct
python
def update_model_dict(self): """Updates the model dictionary""" dct = {} models = self.chimera.openModels for md in models.list(): dct[md.name] = md.id self.model_dict = dct
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manns/pyspread
pyspread/src/gui/_widgets.py
PythonSTC.expand
def expand(self, line, do_expand, force=False, vislevels=0, level=-1): """Multi-purpose expand method from original STC class""" lastchild = self.GetLastChild(line, level) line += 1 while line <= lastchild: if force: if vislevels > 0: self.ShowLines(line, line) else: self.HideLines(line, line) elif do_expand: self.ShowLines(line, line) if level == -1: level = self.GetFoldLevel(line) if level & stc.STC_FOLDLEVELHEADERFLAG: if force: self.SetFoldExpanded(line, vislevels - 1) line = self.expand(line, do_expand, force, vislevels - 1) else: expandsub = do_expand and self.GetFoldExpanded(line) line = self.expand(line, expandsub, force, vislevels - 1) else: line += 1 return line
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def expand(self, line, do_expand, force=False, vislevels=0, level=-1): """Multi-purpose expand method from original STC class""" lastchild = self.GetLastChild(line, level) line += 1 while line <= lastchild: if force: if vislevels > 0: self.ShowLines(line, line) else: self.HideLines(line, line) elif do_expand: self.ShowLines(line, line) if level == -1: level = self.GetFoldLevel(line) if level & stc.STC_FOLDLEVELHEADERFLAG: if force: self.SetFoldExpanded(line, vislevels - 1) line = self.expand(line, do_expand, force, vislevels - 1) else: expandsub = do_expand and self.GetFoldExpanded(line) line = self.expand(line, expandsub, force, vislevels - 1) else: line += 1 return line
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camptocamp/Studio
studio/controllers/datasources.py
DatasourcesController.showmapfile
def showmapfile(self,datastore_id=None, datasource_id=None): """ GET /datastores/{datastore_id}/datasources/{datasource_id}/mapfile: Get the JSON representation of a specific datasource's default MapFile LAYER block. """ datastore = self._get_datastore_by_id(datastore_id) if datastore is None: abort(404) classification = None if 'classification' in request.params and 'attribute' in request.params: classification = {} classification['type'] = request.params['classification'] classification['attribute'] = request.params['attribute'] if classification['type'] == "quantile": classification['intervals'] = request.params['intervals'] palette = {} palette['type']='ramp' if 'colortype' in request.params: palette['type'] = request.params['colortype'] if 'startcolor' in request.params: c = request.params['startcolor'] if c.startswith('#'): c = c[1:] palette['startcolor'] = [int(c[0:2],16),int(c[2:4],16),int(c[4:6],16)] if 'endcolor' in request.params: c = request.params['endcolor'] if c.startswith('#'): c = c[1:] palette['endcolor'] = [int(c[0:2],16),int(c[2:4],16),int(c[4:6],16)] if 'interpolation' in request.params: palette['interpolation'] = request.params['interpolation'] if 'theme' in request.params: palette['theme'] = int(request.params['theme']) classification['palette'] = palette mapfile = get_mapfile(datastore.ogrstring, datasource_id, classification) if 'metadata' not in mapfile: mapfile['metadata']={} mapfile['metadata']['datastoreid']=datastore_id mapfile['metadata']['datasourceid']=datasource_id if mapfile is None: abort(404) return mapfile
python
def showmapfile(self,datastore_id=None, datasource_id=None): """ GET /datastores/{datastore_id}/datasources/{datasource_id}/mapfile: Get the JSON representation of a specific datasource's default MapFile LAYER block. """ datastore = self._get_datastore_by_id(datastore_id) if datastore is None: abort(404) classification = None if 'classification' in request.params and 'attribute' in request.params: classification = {} classification['type'] = request.params['classification'] classification['attribute'] = request.params['attribute'] if classification['type'] == "quantile": classification['intervals'] = request.params['intervals'] palette = {} palette['type']='ramp' if 'colortype' in request.params: palette['type'] = request.params['colortype'] if 'startcolor' in request.params: c = request.params['startcolor'] if c.startswith('#'): c = c[1:] palette['startcolor'] = [int(c[0:2],16),int(c[2:4],16),int(c[4:6],16)] if 'endcolor' in request.params: c = request.params['endcolor'] if c.startswith('#'): c = c[1:] palette['endcolor'] = [int(c[0:2],16),int(c[2:4],16),int(c[4:6],16)] if 'interpolation' in request.params: palette['interpolation'] = request.params['interpolation'] if 'theme' in request.params: palette['theme'] = int(request.params['theme']) classification['palette'] = palette mapfile = get_mapfile(datastore.ogrstring, datasource_id, classification) if 'metadata' not in mapfile: mapfile['metadata']={} mapfile['metadata']['datastoreid']=datastore_id mapfile['metadata']['datasourceid']=datasource_id if mapfile is None: abort(404) return mapfile
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slundberg/shap
shap/benchmark/models.py
cric__ridge
def cric__ridge(): """ Ridge Regression """ model = sklearn.linear_model.LogisticRegression(penalty="l2") # we want to explain the raw probability outputs of the trees model.predict = lambda X: model.predict_proba(X)[:,1] return model
python
def cric__ridge(): """ Ridge Regression """ model = sklearn.linear_model.LogisticRegression(penalty="l2") # we want to explain the raw probability outputs of the trees model.predict = lambda X: model.predict_proba(X)[:,1] return model
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devassistant/devassistant
devassistant/yaml_loader.py
YamlLoader.load_yaml_by_relpath
def load_yaml_by_relpath(cls, directories, rel_path, log_debug=False): """Load a yaml file with path that is relative to one of given directories. Args: directories: list of directories to search name: relative path of the yaml file to load log_debug: log all messages as debug Returns: tuple (fullpath, loaded yaml structure) or None if not found """ for d in directories: if d.startswith(os.path.expanduser('~')) and not os.path.exists(d): os.makedirs(d) possible_path = os.path.join(d, rel_path) if os.path.exists(possible_path): loaded = cls.load_yaml_by_path(possible_path, log_debug=log_debug) if loaded is not None: return (possible_path, cls.load_yaml_by_path(possible_path)) return None
python
def load_yaml_by_relpath(cls, directories, rel_path, log_debug=False): """Load a yaml file with path that is relative to one of given directories. Args: directories: list of directories to search name: relative path of the yaml file to load log_debug: log all messages as debug Returns: tuple (fullpath, loaded yaml structure) or None if not found """ for d in directories: if d.startswith(os.path.expanduser('~')) and not os.path.exists(d): os.makedirs(d) possible_path = os.path.join(d, rel_path) if os.path.exists(possible_path): loaded = cls.load_yaml_by_path(possible_path, log_debug=log_debug) if loaded is not None: return (possible_path, cls.load_yaml_by_path(possible_path)) return None
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squaresLab/BugZoo
bugzoo/mgr/tool.py
ToolManager.upload
def upload(self, tool: Tool) -> bool: """ Attempts to upload the Docker image for a given tool to `DockerHub <https://hub.docker.com>`_. """ return self.__installation.build.upload(tool.image)
python
def upload(self, tool: Tool) -> bool: """ Attempts to upload the Docker image for a given tool to `DockerHub <https://hub.docker.com>`_. """ return self.__installation.build.upload(tool.image)
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pyamg/pyamg
pyamg/util/linalg.py
pinv_array
def pinv_array(a, cond=None): """Calculate the Moore-Penrose pseudo inverse of each block of the three dimensional array a. Parameters ---------- a : {dense array} Is of size (n, m, m) cond : {float} Used by gelss to filter numerically zeros singular values. If None, a suitable value is chosen for you. Returns ------- Nothing, a is modified in place so that a[k] holds the pseudoinverse of that block. Notes ----- By using lapack wrappers, this can be much faster for large n, than directly calling pinv2 Examples -------- >>> import numpy as np >>> from pyamg.util.linalg import pinv_array >>> a = np.array([[[1.,2.],[1.,1.]], [[1.,1.],[3.,3.]]]) >>> ac = a.copy() >>> # each block of a is inverted in-place >>> pinv_array(a) """ n = a.shape[0] m = a.shape[1] if m == 1: # Pseudo-inverse of 1 x 1 matrices is trivial zero_entries = (a == 0.0).nonzero()[0] a[zero_entries] = 1.0 a[:] = 1.0/a a[zero_entries] = 0.0 del zero_entries else: # The block size is greater than 1 # Create necessary arrays and function pointers for calculating pinv gelss, gelss_lwork = get_lapack_funcs(('gelss', 'gelss_lwork'), (np.ones((1,), dtype=a.dtype))) RHS = np.eye(m, dtype=a.dtype) lwork = _compute_lwork(gelss_lwork, m, m, m) # Choose tolerance for which singular values are zero in *gelss below if cond is None: t = a.dtype.char eps = np.finfo(np.float).eps feps = np.finfo(np.single).eps geps = np.finfo(np.longfloat).eps _array_precision = {'f': 0, 'd': 1, 'g': 2, 'F': 0, 'D': 1, 'G': 2} cond = {0: feps*1e3, 1: eps*1e6, 2: geps*1e6}[_array_precision[t]] # Invert each block of a for kk in range(n): gelssoutput = gelss(a[kk], RHS, cond=cond, lwork=lwork, overwrite_a=True, overwrite_b=False) a[kk] = gelssoutput[1]
python
def pinv_array(a, cond=None): """Calculate the Moore-Penrose pseudo inverse of each block of the three dimensional array a. Parameters ---------- a : {dense array} Is of size (n, m, m) cond : {float} Used by gelss to filter numerically zeros singular values. If None, a suitable value is chosen for you. Returns ------- Nothing, a is modified in place so that a[k] holds the pseudoinverse of that block. Notes ----- By using lapack wrappers, this can be much faster for large n, than directly calling pinv2 Examples -------- >>> import numpy as np >>> from pyamg.util.linalg import pinv_array >>> a = np.array([[[1.,2.],[1.,1.]], [[1.,1.],[3.,3.]]]) >>> ac = a.copy() >>> # each block of a is inverted in-place >>> pinv_array(a) """ n = a.shape[0] m = a.shape[1] if m == 1: # Pseudo-inverse of 1 x 1 matrices is trivial zero_entries = (a == 0.0).nonzero()[0] a[zero_entries] = 1.0 a[:] = 1.0/a a[zero_entries] = 0.0 del zero_entries else: # The block size is greater than 1 # Create necessary arrays and function pointers for calculating pinv gelss, gelss_lwork = get_lapack_funcs(('gelss', 'gelss_lwork'), (np.ones((1,), dtype=a.dtype))) RHS = np.eye(m, dtype=a.dtype) lwork = _compute_lwork(gelss_lwork, m, m, m) # Choose tolerance for which singular values are zero in *gelss below if cond is None: t = a.dtype.char eps = np.finfo(np.float).eps feps = np.finfo(np.single).eps geps = np.finfo(np.longfloat).eps _array_precision = {'f': 0, 'd': 1, 'g': 2, 'F': 0, 'D': 1, 'G': 2} cond = {0: feps*1e3, 1: eps*1e6, 2: geps*1e6}[_array_precision[t]] # Invert each block of a for kk in range(n): gelssoutput = gelss(a[kk], RHS, cond=cond, lwork=lwork, overwrite_a=True, overwrite_b=False) a[kk] = gelssoutput[1]
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samuelcolvin/pydantic
pydantic/class_validators.py
make_generic_validator
def make_generic_validator(validator: AnyCallable) -> 'ValidatorCallable': """ Make a generic function which calls a validator with the right arguments. Unfortunately other approaches (eg. return a partial of a function that builds the arguments) is slow, hence this laborious way of doing things. It's done like this so validators don't all need **kwargs in their signature, eg. any combination of the arguments "values", "fields" and/or "config" are permitted. """ sig = signature(validator) args = list(sig.parameters.keys()) first_arg = args.pop(0) if first_arg == 'self': raise ConfigError( f'Invalid signature for validator {validator}: {sig}, "self" not permitted as first argument, ' f'should be: (cls, value, values, config, field), "values", "config" and "field" are all optional.' ) elif first_arg == 'cls': # assume the second argument is value return wraps(validator)(_generic_validator_cls(validator, sig, set(args[1:]))) else: # assume the first argument was value which has already been removed return wraps(validator)(_generic_validator_basic(validator, sig, set(args)))
python
def make_generic_validator(validator: AnyCallable) -> 'ValidatorCallable': """ Make a generic function which calls a validator with the right arguments. Unfortunately other approaches (eg. return a partial of a function that builds the arguments) is slow, hence this laborious way of doing things. It's done like this so validators don't all need **kwargs in their signature, eg. any combination of the arguments "values", "fields" and/or "config" are permitted. """ sig = signature(validator) args = list(sig.parameters.keys()) first_arg = args.pop(0) if first_arg == 'self': raise ConfigError( f'Invalid signature for validator {validator}: {sig}, "self" not permitted as first argument, ' f'should be: (cls, value, values, config, field), "values", "config" and "field" are all optional.' ) elif first_arg == 'cls': # assume the second argument is value return wraps(validator)(_generic_validator_cls(validator, sig, set(args[1:]))) else: # assume the first argument was value which has already been removed return wraps(validator)(_generic_validator_basic(validator, sig, set(args)))
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nugget/python-insteonplm
insteonplm/devices/__init__.py
ControlFlags.byte
def byte(self): """Return a byte representation of ControlFlags.""" flags = int(self._in_use) << 7 \ | int(self._controller) << 6 \ | int(self._bit5) << 5 \ | int(self._bit4) << 4 \ | int(self._used_before) << 1 return flags
python
def byte(self): """Return a byte representation of ControlFlags.""" flags = int(self._in_use) << 7 \ | int(self._controller) << 6 \ | int(self._bit5) << 5 \ | int(self._bit4) << 4 \ | int(self._used_before) << 1 return flags
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ANTsX/ANTsPy
ants/utils/scalar_rgb_vector.py
rgb_to_vector
def rgb_to_vector(image): """ Convert an RGB ANTsImage to a Vector ANTsImage Arguments --------- image : ANTsImage RGB image to be converted Returns ------- ANTsImage Example ------- >>> import ants >>> mni = ants.image_read(ants.get_data('mni')) >>> mni_rgb = mni.scalar_to_rgb() >>> mni_vector = mni.rgb_to_vector() >>> mni_rgb2 = mni.vector_to_rgb() """ if image.pixeltype != 'unsigned char': image = image.clone('unsigned char') idim = image.dimension libfn = utils.get_lib_fn('RgbToVector%i' % idim) new_ptr = libfn(image.pointer) new_img = iio.ANTsImage(pixeltype=image.pixeltype, dimension=image.dimension, components=3, pointer=new_ptr, is_rgb=False) return new_img
python
def rgb_to_vector(image): """ Convert an RGB ANTsImage to a Vector ANTsImage Arguments --------- image : ANTsImage RGB image to be converted Returns ------- ANTsImage Example ------- >>> import ants >>> mni = ants.image_read(ants.get_data('mni')) >>> mni_rgb = mni.scalar_to_rgb() >>> mni_vector = mni.rgb_to_vector() >>> mni_rgb2 = mni.vector_to_rgb() """ if image.pixeltype != 'unsigned char': image = image.clone('unsigned char') idim = image.dimension libfn = utils.get_lib_fn('RgbToVector%i' % idim) new_ptr = libfn(image.pointer) new_img = iio.ANTsImage(pixeltype=image.pixeltype, dimension=image.dimension, components=3, pointer=new_ptr, is_rgb=False) return new_img
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MouseLand/rastermap
rastermap/roi.py
triangle_area
def triangle_area(p0, p1, p2): if p2.ndim < 2: p2 = p2[np.newaxis, :] '''p2 can be a vector''' area = 0.5 * np.abs(p0[0] * p1[1] - p0[0] * p2[:,1] + p1[0] * p2[:,1] - p1[0] * p0[1] + p2[:,0] * p0[1] - p2[:,0] * p1[1]) return area
python
def triangle_area(p0, p1, p2): if p2.ndim < 2: p2 = p2[np.newaxis, :] '''p2 can be a vector''' area = 0.5 * np.abs(p0[0] * p1[1] - p0[0] * p2[:,1] + p1[0] * p2[:,1] - p1[0] * p0[1] + p2[:,0] * p0[1] - p2[:,0] * p1[1]) return area
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marcomusy/vtkplotter
vtkplotter/vtkio.py
Video.addFrame
def addFrame(self): """Add frame to current video.""" fr = "/tmp/vpvid/" + str(len(self.frames)) + ".png" screenshot(fr) self.frames.append(fr)
python
def addFrame(self): """Add frame to current video.""" fr = "/tmp/vpvid/" + str(len(self.frames)) + ".png" screenshot(fr) self.frames.append(fr)
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juju/charm-helpers
charmhelpers/fetch/centos.py
add_source
def add_source(source, key=None): """Add a package source to this system. @param source: a URL with a rpm package @param key: A key to be added to the system's keyring and used to verify the signatures on packages. Ideally, this should be an ASCII format GPG public key including the block headers. A GPG key id may also be used, but be aware that only insecure protocols are available to retrieve the actual public key from a public keyserver placing your Juju environment at risk. """ if source is None: log('Source is not present. Skipping') return if source.startswith('http'): directory = '/etc/yum.repos.d/' for filename in os.listdir(directory): with open(directory + filename, 'r') as rpm_file: if source in rpm_file.read(): break else: log("Add source: {!r}".format(source)) # write in the charms.repo with open(directory + 'Charms.repo', 'a') as rpm_file: rpm_file.write('[%s]\n' % source[7:].replace('/', '_')) rpm_file.write('name=%s\n' % source[7:]) rpm_file.write('baseurl=%s\n\n' % source) else: log("Unknown source: {!r}".format(source)) if key: if '-----BEGIN PGP PUBLIC KEY BLOCK-----' in key: with NamedTemporaryFile('w+') as key_file: key_file.write(key) key_file.flush() key_file.seek(0) subprocess.check_call(['rpm', '--import', key_file.name]) else: subprocess.check_call(['rpm', '--import', key])
python
def add_source(source, key=None): """Add a package source to this system. @param source: a URL with a rpm package @param key: A key to be added to the system's keyring and used to verify the signatures on packages. Ideally, this should be an ASCII format GPG public key including the block headers. A GPG key id may also be used, but be aware that only insecure protocols are available to retrieve the actual public key from a public keyserver placing your Juju environment at risk. """ if source is None: log('Source is not present. Skipping') return if source.startswith('http'): directory = '/etc/yum.repos.d/' for filename in os.listdir(directory): with open(directory + filename, 'r') as rpm_file: if source in rpm_file.read(): break else: log("Add source: {!r}".format(source)) # write in the charms.repo with open(directory + 'Charms.repo', 'a') as rpm_file: rpm_file.write('[%s]\n' % source[7:].replace('/', '_')) rpm_file.write('name=%s\n' % source[7:]) rpm_file.write('baseurl=%s\n\n' % source) else: log("Unknown source: {!r}".format(source)) if key: if '-----BEGIN PGP PUBLIC KEY BLOCK-----' in key: with NamedTemporaryFile('w+') as key_file: key_file.write(key) key_file.flush() key_file.seek(0) subprocess.check_call(['rpm', '--import', key_file.name]) else: subprocess.check_call(['rpm', '--import', key])
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salt/transport/zeromq.py
_set_tcp_keepalive
def _set_tcp_keepalive(zmq_socket, opts): ''' Ensure that TCP keepalives are set as specified in "opts". Warning: Failure to set TCP keepalives on the salt-master can result in not detecting the loss of a minion when the connection is lost or when it's host has been terminated without first closing the socket. Salt's Presence System depends on this connection status to know if a minion is "present". Warning: Failure to set TCP keepalives on minions can result in frequent or unexpected disconnects! ''' if hasattr(zmq, 'TCP_KEEPALIVE') and opts: if 'tcp_keepalive' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE, opts['tcp_keepalive'] ) if 'tcp_keepalive_idle' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_IDLE, opts['tcp_keepalive_idle'] ) if 'tcp_keepalive_cnt' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_CNT, opts['tcp_keepalive_cnt'] ) if 'tcp_keepalive_intvl' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_INTVL, opts['tcp_keepalive_intvl'] )
python
def _set_tcp_keepalive(zmq_socket, opts): ''' Ensure that TCP keepalives are set as specified in "opts". Warning: Failure to set TCP keepalives on the salt-master can result in not detecting the loss of a minion when the connection is lost or when it's host has been terminated without first closing the socket. Salt's Presence System depends on this connection status to know if a minion is "present". Warning: Failure to set TCP keepalives on minions can result in frequent or unexpected disconnects! ''' if hasattr(zmq, 'TCP_KEEPALIVE') and opts: if 'tcp_keepalive' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE, opts['tcp_keepalive'] ) if 'tcp_keepalive_idle' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_IDLE, opts['tcp_keepalive_idle'] ) if 'tcp_keepalive_cnt' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_CNT, opts['tcp_keepalive_cnt'] ) if 'tcp_keepalive_intvl' in opts: zmq_socket.setsockopt( zmq.TCP_KEEPALIVE_INTVL, opts['tcp_keepalive_intvl'] )
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graphite_api/functions.py
legendValue
def legendValue(requestContext, seriesList, *valueTypes): """ Takes one metric or a wildcard seriesList and a string in quotes. Appends a value to the metric name in the legend. Currently one or several of: `last`, `avg`, `total`, `min`, `max`. The last argument can be `si` (default) or `binary`, in that case values will be formatted in the corresponding system. Example:: &target=legendValue(Sales.widgets.largeBlue, 'avg', 'max', 'si') """ valueFuncs = { 'avg': lambda s: safeDiv(safeSum(s), safeLen(s)), 'total': safeSum, 'min': safeMin, 'max': safeMax, 'last': safeLast, } system = None if valueTypes[-1] in ('si', 'binary'): system = valueTypes[-1] valueTypes = valueTypes[:-1] for valueType in valueTypes: valueFunc = valueFuncs.get(valueType, lambda s: '(?)') if system is None: for series in seriesList: series.name += " (%s: %s)" % (valueType, valueFunc(series)) else: for series in seriesList: value = valueFunc(series) formatted = None if value is not None: formatted = "%.2f%s" % format_units(value, system=system) series.name = "%-20s%-5s%-10s" % (series.name, valueType, formatted) return seriesList
python
def legendValue(requestContext, seriesList, *valueTypes): """ Takes one metric or a wildcard seriesList and a string in quotes. Appends a value to the metric name in the legend. Currently one or several of: `last`, `avg`, `total`, `min`, `max`. The last argument can be `si` (default) or `binary`, in that case values will be formatted in the corresponding system. Example:: &target=legendValue(Sales.widgets.largeBlue, 'avg', 'max', 'si') """ valueFuncs = { 'avg': lambda s: safeDiv(safeSum(s), safeLen(s)), 'total': safeSum, 'min': safeMin, 'max': safeMax, 'last': safeLast, } system = None if valueTypes[-1] in ('si', 'binary'): system = valueTypes[-1] valueTypes = valueTypes[:-1] for valueType in valueTypes: valueFunc = valueFuncs.get(valueType, lambda s: '(?)') if system is None: for series in seriesList: series.name += " (%s: %s)" % (valueType, valueFunc(series)) else: for series in seriesList: value = valueFunc(series) formatted = None if value is not None: formatted = "%.2f%s" % format_units(value, system=system) series.name = "%-20s%-5s%-10s" % (series.name, valueType, formatted) return seriesList
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googleapis/google-cloud-python
tasks/google/cloud/tasks_v2/gapic/cloud_tasks_client.py
CloudTasksClient.task_path
def task_path(cls, project, location, queue, task): """Return a fully-qualified task string.""" return google.api_core.path_template.expand( "projects/{project}/locations/{location}/queues/{queue}/tasks/{task}", project=project, location=location, queue=queue, task=task, )
python
def task_path(cls, project, location, queue, task): """Return a fully-qualified task string.""" return google.api_core.path_template.expand( "projects/{project}/locations/{location}/queues/{queue}/tasks/{task}", project=project, location=location, queue=queue, task=task, )
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mushkevych/scheduler
synergy/system/event_clock.py
EventClock.next_run_in
def next_run_in(self, utc_now=None): """ :param utc_now: optional parameter to be used by Unit Tests as a definition of "now" :return: timedelta instance presenting amount of time before the trigger is triggered next time or None if the EventClock instance is not running """ if utc_now is None: utc_now = datetime.utcnow() if self.is_alive(): smallest_timedelta = timedelta(days=99, hours=0, minutes=0, seconds=0, microseconds=0, milliseconds=0) for event_time in self.timestamps: next_trigger = event_time.next_trigger_frequency(utc_now) if next_trigger - utc_now < smallest_timedelta: smallest_timedelta = next_trigger - utc_now return smallest_timedelta else: return None
python
def next_run_in(self, utc_now=None): """ :param utc_now: optional parameter to be used by Unit Tests as a definition of "now" :return: timedelta instance presenting amount of time before the trigger is triggered next time or None if the EventClock instance is not running """ if utc_now is None: utc_now = datetime.utcnow() if self.is_alive(): smallest_timedelta = timedelta(days=99, hours=0, minutes=0, seconds=0, microseconds=0, milliseconds=0) for event_time in self.timestamps: next_trigger = event_time.next_trigger_frequency(utc_now) if next_trigger - utc_now < smallest_timedelta: smallest_timedelta = next_trigger - utc_now return smallest_timedelta else: return None
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molmod/molmod
molmod/pairff.py
PairFF.update_coordinates
def update_coordinates(self, coordinates=None): """Update the coordinates (and derived quantities) Argument: coordinates -- new Cartesian coordinates of the system """ if coordinates is not None: self.coordinates = coordinates self.numc = len(self.coordinates) self.distances = np.zeros((self.numc, self.numc), float) self.deltas = np.zeros((self.numc, self.numc, 3), float) self.directions = np.zeros((self.numc, self.numc, 3), float) self.dirouters = np.zeros((self.numc, self.numc, 3, 3), float) for index1, coordinate1 in enumerate(self.coordinates): for index2, coordinate2 in enumerate(self.coordinates): delta = coordinate1 - coordinate2 self.deltas[index1, index2] = delta distance = np.linalg.norm(delta) self.distances[index1, index2] = distance if index1 != index2: tmp = delta/distance self.directions[index1, index2] = tmp self.dirouters[index1, index2] = np.outer(tmp, tmp)
python
def update_coordinates(self, coordinates=None): """Update the coordinates (and derived quantities) Argument: coordinates -- new Cartesian coordinates of the system """ if coordinates is not None: self.coordinates = coordinates self.numc = len(self.coordinates) self.distances = np.zeros((self.numc, self.numc), float) self.deltas = np.zeros((self.numc, self.numc, 3), float) self.directions = np.zeros((self.numc, self.numc, 3), float) self.dirouters = np.zeros((self.numc, self.numc, 3, 3), float) for index1, coordinate1 in enumerate(self.coordinates): for index2, coordinate2 in enumerate(self.coordinates): delta = coordinate1 - coordinate2 self.deltas[index1, index2] = delta distance = np.linalg.norm(delta) self.distances[index1, index2] = distance if index1 != index2: tmp = delta/distance self.directions[index1, index2] = tmp self.dirouters[index1, index2] = np.outer(tmp, tmp)
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vreon/figment
examples/theworldfoundry/theworldfoundry/components/spatial.py
Spatial.emit
def emit(self, sound, exclude=set()): """Send text to entities nearby this one.""" nearby = self.nearby() try: exclude = set(exclude) except TypeError: exclude = set([exclude]) exclude.add(self.entity) listeners = nearby - exclude for listener in listeners: listener.tell(sound)
python
def emit(self, sound, exclude=set()): """Send text to entities nearby this one.""" nearby = self.nearby() try: exclude = set(exclude) except TypeError: exclude = set([exclude]) exclude.add(self.entity) listeners = nearby - exclude for listener in listeners: listener.tell(sound)
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speechinformaticslab/vfclust
vfclust/vfclust.py
VFClustEngine.print_output
def print_output(self): """ Outputs final list of measures to screen a csv file. The .csv file created has the same name as the input file, with "vfclust_TYPE_CATEGORY" appended to the filename, where TYPE indicates the type of task performed done (SEMANTIC or PHONETIC) and CATEGORY indicates the category requirement of the stimulus (i.e. 'f' or 'animals' for phonetic and semantic fluency test, respectively. """ if self.response_format == "csv": for key in self.measures: if "TIMING_" in key: self.measures[key] = "NA" if not self.quiet: print print self.type.upper() + " RESULTS:" keys = [e for e in self.measures if 'COUNT_' in e] keys.sort() print "Counts:" print_table([(entry, str(self.measures[entry])) for entry in keys]) keys = [e for e in self.measures if 'COLLECTION_' in e] keys.sort() print print "Collection measures:" print_table([(entry, str(self.measures[entry])) for entry in keys]) if self.response_format == "TextGrid": keys = [e for e in self.measures if 'TIMING_' in e] keys.sort() print print "Time-based measures:" print_table([(entry, str(self.measures[entry])) for entry in keys]) #write to CSV file if self.target_file: with open(self.target_file, 'w') as outfile: header = ['file_id'] + \ [self.type + "_" + e for e in self.measures if 'COUNT_' in e] + \ [self.type + "_" + e for e in self.measures if 'COLLECTION_' in e] + \ [self.type + "_" + e for e in self.measures if 'TIMING_' in e] writer = csv.writer(outfile, quoting=csv.QUOTE_MINIMAL) writer.writerow(header) #the split/join gets rid of the type appended just above writer.writerow([self.measures["file_id"]] + [self.measures["_".join(e.split('_')[1:])] for e in header[1:]])
python
def print_output(self): """ Outputs final list of measures to screen a csv file. The .csv file created has the same name as the input file, with "vfclust_TYPE_CATEGORY" appended to the filename, where TYPE indicates the type of task performed done (SEMANTIC or PHONETIC) and CATEGORY indicates the category requirement of the stimulus (i.e. 'f' or 'animals' for phonetic and semantic fluency test, respectively. """ if self.response_format == "csv": for key in self.measures: if "TIMING_" in key: self.measures[key] = "NA" if not self.quiet: print print self.type.upper() + " RESULTS:" keys = [e for e in self.measures if 'COUNT_' in e] keys.sort() print "Counts:" print_table([(entry, str(self.measures[entry])) for entry in keys]) keys = [e for e in self.measures if 'COLLECTION_' in e] keys.sort() print print "Collection measures:" print_table([(entry, str(self.measures[entry])) for entry in keys]) if self.response_format == "TextGrid": keys = [e for e in self.measures if 'TIMING_' in e] keys.sort() print print "Time-based measures:" print_table([(entry, str(self.measures[entry])) for entry in keys]) #write to CSV file if self.target_file: with open(self.target_file, 'w') as outfile: header = ['file_id'] + \ [self.type + "_" + e for e in self.measures if 'COUNT_' in e] + \ [self.type + "_" + e for e in self.measures if 'COLLECTION_' in e] + \ [self.type + "_" + e for e in self.measures if 'TIMING_' in e] writer = csv.writer(outfile, quoting=csv.QUOTE_MINIMAL) writer.writerow(header) #the split/join gets rid of the type appended just above writer.writerow([self.measures["file_id"]] + [self.measures["_".join(e.split('_')[1:])] for e in header[1:]])
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python
def options_string_builder(option_mapping, args): """Return arguments for CLI invocation of kal.""" options_string = "" for option, flag in option_mapping.items(): if option in args: options_string += str(" %s %s" % (flag, str(args[option]))) return options_string
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noahbenson/neuropythy
neuropythy/optimize/core.py
gaussian
def gaussian(f=Ellipsis, mu=0, sigma=1, scale=1, invert=False, normalize=False): ''' gaussian() yields a potential function f(x) that calculates a Gaussian function over x; the formula used is given below. gaussian(g) yields a function h(x) such that, if f(x) is yielded by gaussian(), h(x) = f(g(x)). The formula employed by the Gaussian function is as follows, with mu, sigma, and scale all being parameters that one can provide via optional arguments: scale * exp(0.5 * ((x - mu) / sigma)**2) The following optional arguments may be given: * mu (default: 0) specifies the mean of the Gaussian. * sigma (default: 1) specifies the standard deviation (sigma) parameger of the Gaussian. * scale (default: 1) specifies the scale to use. * invert (default: False) specifies whether the Gaussian should be inverted. If inverted, then the formula, scale * exp(...), is replaced with scale * (1 - exp(...)). * normalize (default: False) specifies whether the result should be multiplied by the inverse of the area under the uninverted and unscaled curve; i.e., if normalize is True, the entire result is multiplied by 1/sqrt(2*pi*sigma**2). ''' f = to_potential(f) F = exp(-0.5 * ((f - mu) / sigma)**2) if invert: F = 1 - F F = F * scale if normalize: F = F / (np.sqrt(2.0*np.pi) * sigma) return F
python
def gaussian(f=Ellipsis, mu=0, sigma=1, scale=1, invert=False, normalize=False): ''' gaussian() yields a potential function f(x) that calculates a Gaussian function over x; the formula used is given below. gaussian(g) yields a function h(x) such that, if f(x) is yielded by gaussian(), h(x) = f(g(x)). The formula employed by the Gaussian function is as follows, with mu, sigma, and scale all being parameters that one can provide via optional arguments: scale * exp(0.5 * ((x - mu) / sigma)**2) The following optional arguments may be given: * mu (default: 0) specifies the mean of the Gaussian. * sigma (default: 1) specifies the standard deviation (sigma) parameger of the Gaussian. * scale (default: 1) specifies the scale to use. * invert (default: False) specifies whether the Gaussian should be inverted. If inverted, then the formula, scale * exp(...), is replaced with scale * (1 - exp(...)). * normalize (default: False) specifies whether the result should be multiplied by the inverse of the area under the uninverted and unscaled curve; i.e., if normalize is True, the entire result is multiplied by 1/sqrt(2*pi*sigma**2). ''' f = to_potential(f) F = exp(-0.5 * ((f - mu) / sigma)**2) if invert: F = 1 - F F = F * scale if normalize: F = F / (np.sqrt(2.0*np.pi) * sigma) return F
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src/IoticAgent/IOT/Point.py
Feed.set_recent_config
def set_recent_config(self, max_samples=0): """Update/configure recent data settings for this Feed. If the container does not support recent storage or it is not enabled for this owner, this function will have no effect. `max_samples` (optional) (int) how many shares to store for later retrieval. If not supported by container, this argument will be ignored. A value of zero disables this feature whilst a negative value requests the maximum sample store amount. Returns QAPI recent config function payload #!python { "maxSamples": 0 } Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException) containing the error if the infrastructure detects a problem Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException) if there is a communications problem between you and the infrastructure """ evt = self._client._request_point_recent_config(self._type, self.lid, self.pid, max_samples) self._client._wait_and_except_if_failed(evt) return evt.payload
python
def set_recent_config(self, max_samples=0): """Update/configure recent data settings for this Feed. If the container does not support recent storage or it is not enabled for this owner, this function will have no effect. `max_samples` (optional) (int) how many shares to store for later retrieval. If not supported by container, this argument will be ignored. A value of zero disables this feature whilst a negative value requests the maximum sample store amount. Returns QAPI recent config function payload #!python { "maxSamples": 0 } Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException) containing the error if the infrastructure detects a problem Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException) if there is a communications problem between you and the infrastructure """ evt = self._client._request_point_recent_config(self._type, self.lid, self.pid, max_samples) self._client._wait_and_except_if_failed(evt) return evt.payload
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odlgroup/odl
odl/operator/default_ops.py
PowerOperator._call
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python
def _call(self, x, out=None): """Take the power of ``x`` and write to ``out`` if given.""" if out is None: return x ** self.exponent elif self.__domain_is_field: raise ValueError('cannot use `out` with field') else: out.assign(x) out **= self.exponent
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ThreatConnect-Inc/tcex
tcex/tcex_ti/mappings/victim.py
Victim.update_network_asset
def update_network_asset(self, asset_id, name, asset_type): """ Updates a Network Asset Args: name: The name provided to the network asset asset_type: The type provided to the network asset asset_id: Returns: """ self.update_asset('NETWORK', asset_id, name, asset_type)
python
def update_network_asset(self, asset_id, name, asset_type): """ Updates a Network Asset Args: name: The name provided to the network asset asset_type: The type provided to the network asset asset_id: Returns: """ self.update_asset('NETWORK', asset_id, name, asset_type)
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humilis/humilis-lambdautils
lambdautils/state.py
set_state
def set_state(key, value, namespace=None, table_name=None, environment=None, layer=None, stage=None, shard_id=None, consistent=True, serializer=json.dumps, wait_exponential_multiplier=500, wait_exponential_max=5000, stop_max_delay=10000, ttl=None): """Set Lambda state value.""" if table_name is None: table_name = _state_table_name(environment=environment, layer=layer, stage=stage) if not table_name: msg = ("Can't produce state table name: unable to set state " "item '{}'".format(key)) logger.error(msg) raise StateTableError(msg) return dynamodb = boto3.resource("dynamodb") table = dynamodb.Table(table_name) logger.info("Putting {} -> {} in DynamoDB table {}".format(key, value, table_name)) if serializer: try: value = serializer(value) except TypeError: logger.error( "Value for state key '{}' is not json-serializable".format( key)) raise if namespace: key = "{}:{}".format(namespace, key) if shard_id: key = "{}:{}".format(shard_id, key) item = {"id": key, "value": value} if ttl: item["ttl"] = {"N": str(int(time.time() + ttl))} @retry(retry_on_exception=_is_critical_exception, wait_exponential_multiplier=500, wait_exponential_max=5000, stop_max_delay=10000) def put_item(): try: return table.put_item(Item=item) except Exception as err: if _is_dynamodb_critical_exception(err): raise CriticalError(err) else: raise resp = put_item() logger.info("Response from DynamoDB: '{}'".format(resp)) return resp
python
def set_state(key, value, namespace=None, table_name=None, environment=None, layer=None, stage=None, shard_id=None, consistent=True, serializer=json.dumps, wait_exponential_multiplier=500, wait_exponential_max=5000, stop_max_delay=10000, ttl=None): """Set Lambda state value.""" if table_name is None: table_name = _state_table_name(environment=environment, layer=layer, stage=stage) if not table_name: msg = ("Can't produce state table name: unable to set state " "item '{}'".format(key)) logger.error(msg) raise StateTableError(msg) return dynamodb = boto3.resource("dynamodb") table = dynamodb.Table(table_name) logger.info("Putting {} -> {} in DynamoDB table {}".format(key, value, table_name)) if serializer: try: value = serializer(value) except TypeError: logger.error( "Value for state key '{}' is not json-serializable".format( key)) raise if namespace: key = "{}:{}".format(namespace, key) if shard_id: key = "{}:{}".format(shard_id, key) item = {"id": key, "value": value} if ttl: item["ttl"] = {"N": str(int(time.time() + ttl))} @retry(retry_on_exception=_is_critical_exception, wait_exponential_multiplier=500, wait_exponential_max=5000, stop_max_delay=10000) def put_item(): try: return table.put_item(Item=item) except Exception as err: if _is_dynamodb_critical_exception(err): raise CriticalError(err) else: raise resp = put_item() logger.info("Response from DynamoDB: '{}'".format(resp)) return resp
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8,568
mjirik/io3d
io3d/datareader.py
DataReader._read_with_sitk
def _read_with_sitk(datapath): """Reads file using SimpleITK. Returns array of pixels (image located in datapath) and its metadata. :param datapath: path to file (img or dicom) :return: tuple (data3d, metadata), where data3d is array of pixels """ try: import SimpleITK as Sitk except ImportError as e: logger.error("Unable to import SimpleITK. On Windows try version 1.0.1") image = Sitk.ReadImage(datapath) data3d = dcmtools.get_pixel_array_from_sitk(image) # data3d, original_dtype = dcmreaddata.get_pixel_array_from_dcmobj(image) metadata = _metadata(image, datapath) return data3d, metadata
python
def _read_with_sitk(datapath): """Reads file using SimpleITK. Returns array of pixels (image located in datapath) and its metadata. :param datapath: path to file (img or dicom) :return: tuple (data3d, metadata), where data3d is array of pixels """ try: import SimpleITK as Sitk except ImportError as e: logger.error("Unable to import SimpleITK. On Windows try version 1.0.1") image = Sitk.ReadImage(datapath) data3d = dcmtools.get_pixel_array_from_sitk(image) # data3d, original_dtype = dcmreaddata.get_pixel_array_from_dcmobj(image) metadata = _metadata(image, datapath) return data3d, metadata
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plotnine/scales/scale.py
scale.map_df
def map_df(self, df): """ Map df """ if len(df) == 0: return aesthetics = set(self.aesthetics) & set(df.columns) for ae in aesthetics: df[ae] = self.map(df[ae]) return df
python
def map_df(self, df): """ Map df """ if len(df) == 0: return aesthetics = set(self.aesthetics) & set(df.columns) for ae in aesthetics: df[ae] = self.map(df[ae]) return df
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ioc_writer/ioc_api.py
fix_schema_node_ordering
def fix_schema_node_ordering(parent): """ Fix the ordering of children under the criteria node to ensure that IndicatorItem/Indicator order is preserved, as per XML Schema. :return: """ children = parent.getchildren() i_nodes = [node for node in children if node.tag == 'IndicatorItem'] ii_nodes = [node for node in children if node.tag == 'Indicator'] if not ii_nodes: return # Remove all the children for node in children: parent.remove(node) # Add the Indicator nodes back for node in i_nodes: parent.append(node) # Now add the IndicatorItem nodes back for node in ii_nodes: parent.append(node) # Now recurse for node in ii_nodes: fix_schema_node_ordering(node)
python
def fix_schema_node_ordering(parent): """ Fix the ordering of children under the criteria node to ensure that IndicatorItem/Indicator order is preserved, as per XML Schema. :return: """ children = parent.getchildren() i_nodes = [node for node in children if node.tag == 'IndicatorItem'] ii_nodes = [node for node in children if node.tag == 'Indicator'] if not ii_nodes: return # Remove all the children for node in children: parent.remove(node) # Add the Indicator nodes back for node in i_nodes: parent.append(node) # Now add the IndicatorItem nodes back for node in ii_nodes: parent.append(node) # Now recurse for node in ii_nodes: fix_schema_node_ordering(node)
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LettError/MutatorMath
Lib/mutatorMath/objects/mutator.py
Mutator.collectLocations
def collectLocations(self): """ Return a dictionary with all objects. """ pts = [] for l, (value, deltaName) in self.items(): pts.append(Location(l)) return pts
python
def collectLocations(self): """ Return a dictionary with all objects. """ pts = [] for l, (value, deltaName) in self.items(): pts.append(Location(l)) return pts
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diamondman/proteusisc
proteusisc/promise.py
TDOPromiseCollection.add
def add(self, promise, bitoffset, *, _offsetideal=None): """Add a promise to the promise collection at an optional offset. Args: promise: A TDOPromise to add to this collection. bitoffset: An integer offset for this new promise in the collection. _offsetideal: An integer offset for this new promise in the collection if the associated primitive supports arbitrary TDO control. """ #This Assumes that things are added in order. #Sorting or checking should likely be added. if _offsetideal is None: _offsetideal = bitoffset if isinstance(promise, TDOPromise): newpromise = promise.makesubatoffset( bitoffset, _offsetideal=_offsetideal) self._promises.append(newpromise) elif isinstance(promise, TDOPromiseCollection): for p in promise._promises: self.add(p, bitoffset, _offsetideal=_offsetideal)
python
def add(self, promise, bitoffset, *, _offsetideal=None): """Add a promise to the promise collection at an optional offset. Args: promise: A TDOPromise to add to this collection. bitoffset: An integer offset for this new promise in the collection. _offsetideal: An integer offset for this new promise in the collection if the associated primitive supports arbitrary TDO control. """ #This Assumes that things are added in order. #Sorting or checking should likely be added. if _offsetideal is None: _offsetideal = bitoffset if isinstance(promise, TDOPromise): newpromise = promise.makesubatoffset( bitoffset, _offsetideal=_offsetideal) self._promises.append(newpromise) elif isinstance(promise, TDOPromiseCollection): for p in promise._promises: self.add(p, bitoffset, _offsetideal=_offsetideal)
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erocarrera/pefile
peutils.py
is_probably_packed
def is_probably_packed( pe ): """Returns True is there is a high likelihood that a file is packed or contains compressed data. The sections of the PE file will be analyzed, if enough sections look like containing compressed data and the data makes up for more than 20% of the total file size, the function will return True. """ # Calculate the lenth of the data up to the end of the last section in the # file. Overlay data won't be taken into account # total_pe_data_length = len( pe.trim() ) # Assume that the file is packed when no data is available if not total_pe_data_length: return True has_significant_amount_of_compressed_data = False # If some of the sections have high entropy and they make for more than 20% of the file's size # it's assumed that it could be an installer or a packed file total_compressed_data = 0 for section in pe.sections: s_entropy = section.get_entropy() s_length = len( section.get_data() ) # The value of 7.4 is empircal, based on looking at a few files packed # by different packers if s_entropy > 7.4: total_compressed_data += s_length if ((1.0 * total_compressed_data)/total_pe_data_length) > .2: has_significant_amount_of_compressed_data = True return has_significant_amount_of_compressed_data
python
def is_probably_packed( pe ): """Returns True is there is a high likelihood that a file is packed or contains compressed data. The sections of the PE file will be analyzed, if enough sections look like containing compressed data and the data makes up for more than 20% of the total file size, the function will return True. """ # Calculate the lenth of the data up to the end of the last section in the # file. Overlay data won't be taken into account # total_pe_data_length = len( pe.trim() ) # Assume that the file is packed when no data is available if not total_pe_data_length: return True has_significant_amount_of_compressed_data = False # If some of the sections have high entropy and they make for more than 20% of the file's size # it's assumed that it could be an installer or a packed file total_compressed_data = 0 for section in pe.sections: s_entropy = section.get_entropy() s_length = len( section.get_data() ) # The value of 7.4 is empircal, based on looking at a few files packed # by different packers if s_entropy > 7.4: total_compressed_data += s_length if ((1.0 * total_compressed_data)/total_pe_data_length) > .2: has_significant_amount_of_compressed_data = True return has_significant_amount_of_compressed_data
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f3at/feat
src/feat/web/webserver.py
Site.cleanup
def cleanup(self): ''' Cleans up existing connections giving them time to finish the currect request. ''' self.debug("Cleanup called on Site.") if not self.connections: return defer.succeed(None) self.debug("Waiting for all the connections to close.") result = self._notifier.wait('idle') for connection in self.connections: connection.persistent = False if not connection.requests: connection.transport.loseConnection() else: request = connection.requests[0] peer = connection.transport.getPeer() self.debug("Site is still processing a %s request from %s:%s" " to path: %s. It will be given a time to finish", request.method, peer.host, peer.port, request.path) return result
python
def cleanup(self): ''' Cleans up existing connections giving them time to finish the currect request. ''' self.debug("Cleanup called on Site.") if not self.connections: return defer.succeed(None) self.debug("Waiting for all the connections to close.") result = self._notifier.wait('idle') for connection in self.connections: connection.persistent = False if not connection.requests: connection.transport.loseConnection() else: request = connection.requests[0] peer = connection.transport.getPeer() self.debug("Site is still processing a %s request from %s:%s" " to path: %s. It will be given a time to finish", request.method, peer.host, peer.port, request.path) return result
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sighingnow/parsec.py
src/parsec/__init__.py
letter
def letter(): '''Parse a letter in alphabet.''' @Parser def letter_parser(text, index=0): if index < len(text) and text[index].isalpha(): return Value.success(index + 1, text[index]) else: return Value.failure(index, 'a letter') return letter_parser
python
def letter(): '''Parse a letter in alphabet.''' @Parser def letter_parser(text, index=0): if index < len(text) and text[index].isalpha(): return Value.success(index + 1, text[index]) else: return Value.failure(index, 'a letter') return letter_parser
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mdiener/grace
grace/py27/slimit/parser.py
Parser.p_with_statement
def p_with_statement(self, p): """with_statement : WITH LPAREN expr RPAREN statement""" p[0] = ast.With(expr=p[3], statement=p[5])
python
def p_with_statement(self, p): """with_statement : WITH LPAREN expr RPAREN statement""" p[0] = ast.With(expr=p[3], statement=p[5])
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mozilla/django-tidings
tidings/events.py
Event._watches_belonging_to_user
def _watches_belonging_to_user(cls, user_or_email, object_id=None, **filters): """Return a QuerySet of watches having the given user or email, having (only) the given filters, and having the event_type and content_type attrs of the class. Matched Watches may be either confirmed and unconfirmed. They may include duplicates if the get-then-create race condition in :meth:`notify()` allowed them to be created. If you pass an email, it will be matched against only the email addresses of anonymous watches. At the moment, the only integration point planned between anonymous and registered watches is the claiming of anonymous watches of the same email address on user registration confirmation. If you pass the AnonymousUser, this will return an empty QuerySet. """ # If we have trouble distinguishing subsets and such, we could store a # number_of_filters on the Watch. cls._validate_filters(filters) if isinstance(user_or_email, string_types): user_condition = Q(email=user_or_email) elif user_or_email.is_authenticated: user_condition = Q(user=user_or_email) else: return Watch.objects.none() # Filter by stuff in the Watch row: watches = getattr(Watch, 'uncached', Watch.objects).filter( user_condition, Q(content_type=ContentType.objects.get_for_model( cls.content_type)) if cls.content_type else Q(), Q(object_id=object_id) if object_id else Q(), event_type=cls.event_type).extra( where=['(SELECT count(*) FROM tidings_watchfilter WHERE ' 'tidings_watchfilter.watch_id=' 'tidings_watch.id)=%s'], params=[len(filters)]) # Optimization: If the subselect ends up being slow, store the number # of filters in each Watch row or try a GROUP BY. # Apply 1-to-many filters: for k, v in iteritems(filters): watches = watches.filter(filters__name=k, filters__value=hash_to_unsigned(v)) return watches
python
def _watches_belonging_to_user(cls, user_or_email, object_id=None, **filters): """Return a QuerySet of watches having the given user or email, having (only) the given filters, and having the event_type and content_type attrs of the class. Matched Watches may be either confirmed and unconfirmed. They may include duplicates if the get-then-create race condition in :meth:`notify()` allowed them to be created. If you pass an email, it will be matched against only the email addresses of anonymous watches. At the moment, the only integration point planned between anonymous and registered watches is the claiming of anonymous watches of the same email address on user registration confirmation. If you pass the AnonymousUser, this will return an empty QuerySet. """ # If we have trouble distinguishing subsets and such, we could store a # number_of_filters on the Watch. cls._validate_filters(filters) if isinstance(user_or_email, string_types): user_condition = Q(email=user_or_email) elif user_or_email.is_authenticated: user_condition = Q(user=user_or_email) else: return Watch.objects.none() # Filter by stuff in the Watch row: watches = getattr(Watch, 'uncached', Watch.objects).filter( user_condition, Q(content_type=ContentType.objects.get_for_model( cls.content_type)) if cls.content_type else Q(), Q(object_id=object_id) if object_id else Q(), event_type=cls.event_type).extra( where=['(SELECT count(*) FROM tidings_watchfilter WHERE ' 'tidings_watchfilter.watch_id=' 'tidings_watch.id)=%s'], params=[len(filters)]) # Optimization: If the subselect ends up being slow, store the number # of filters in each Watch row or try a GROUP BY. # Apply 1-to-many filters: for k, v in iteritems(filters): watches = watches.filter(filters__name=k, filters__value=hash_to_unsigned(v)) return watches
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saltstack/salt
salt/modules/tuned.py
active
def active(): ''' Return current active profile CLI Example: .. code-block:: bash salt '*' tuned.active ''' # turn off all profiles result = __salt__['cmd.run']('tuned-adm active') pattern = re.compile(r'''(?P<stmt>Current active profile:) (?P<profile>\w+.*)''') match = re.match(pattern, result) return '{0}'.format(match.group('profile'))
python
def active(): ''' Return current active profile CLI Example: .. code-block:: bash salt '*' tuned.active ''' # turn off all profiles result = __salt__['cmd.run']('tuned-adm active') pattern = re.compile(r'''(?P<stmt>Current active profile:) (?P<profile>\w+.*)''') match = re.match(pattern, result) return '{0}'.format(match.group('profile'))
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Return current active profile CLI Example: .. code-block:: bash salt '*' tuned.active
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rosshamish/catanlog
catanlog.py
CatanLog.log_player_trades_with_other_player
def log_player_trades_with_other_player(self, player, to_other, other, to_player): """ :param player: catan.game.Player :param to_other: list of tuples, [(int, game.board.Terrain), (int, game.board.Terrain)] :param other: catan.board.Player :param to_player: list of tuples, [(int, game.board.Terrain), (int, game.board.Terrain)] """ self._log('{0} trades '.format(player.color)) # to_other items self._log('[') for i, (num, res) in enumerate(to_other): if i > 0: self._log(', ') self._log('{0} {1}'.format(num, res.value)) self._log(']') self._log(' to player {0} for '.format(other.color)) # to_player items self._log('[') for i, (num, res) in enumerate(to_player): if i > 0: self._log(', ') self._log('{0} {1}'.format(num, res.value)) self._log(']') self._log('\n')
python
def log_player_trades_with_other_player(self, player, to_other, other, to_player): """ :param player: catan.game.Player :param to_other: list of tuples, [(int, game.board.Terrain), (int, game.board.Terrain)] :param other: catan.board.Player :param to_player: list of tuples, [(int, game.board.Terrain), (int, game.board.Terrain)] """ self._log('{0} trades '.format(player.color)) # to_other items self._log('[') for i, (num, res) in enumerate(to_other): if i > 0: self._log(', ') self._log('{0} {1}'.format(num, res.value)) self._log(']') self._log(' to player {0} for '.format(other.color)) # to_player items self._log('[') for i, (num, res) in enumerate(to_player): if i > 0: self._log(', ') self._log('{0} {1}'.format(num, res.value)) self._log(']') self._log('\n')
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bunq/sdk_python
bunq/sdk/model/generated/object_.py
EventObject.get_referenced_object
def get_referenced_object(self): """ :rtype: core.BunqModel :raise: BunqException """ if self._BunqMeTab is not None: return self._BunqMeTab if self._BunqMeTabResultResponse is not None: return self._BunqMeTabResultResponse if self._BunqMeFundraiserResult is not None: return self._BunqMeFundraiserResult if self._Card is not None: return self._Card if self._CardDebit is not None: return self._CardDebit if self._DraftPayment is not None: return self._DraftPayment if self._FeatureAnnouncement is not None: return self._FeatureAnnouncement if self._IdealMerchantTransaction is not None: return self._IdealMerchantTransaction if self._Invoice is not None: return self._Invoice if self._ScheduledPayment is not None: return self._ScheduledPayment if self._ScheduledPaymentBatch is not None: return self._ScheduledPaymentBatch if self._ScheduledInstance is not None: return self._ScheduledInstance if self._MasterCardAction is not None: return self._MasterCardAction if self._BankSwitchServiceNetherlandsIncomingPayment is not None: return self._BankSwitchServiceNetherlandsIncomingPayment if self._Payment is not None: return self._Payment if self._PaymentBatch is not None: return self._PaymentBatch if self._RequestInquiryBatch is not None: return self._RequestInquiryBatch if self._RequestInquiry is not None: return self._RequestInquiry if self._RequestResponse is not None: return self._RequestResponse if self._RewardRecipient is not None: return self._RewardRecipient if self._RewardSender is not None: return self._RewardSender if self._ShareInviteBankInquiryBatch is not None: return self._ShareInviteBankInquiryBatch if self._ShareInviteBankInquiry is not None: return self._ShareInviteBankInquiry if self._ShareInviteBankResponse is not None: return self._ShareInviteBankResponse if self._SofortMerchantTransaction is not None: return self._SofortMerchantTransaction if self._TabResultInquiry is not None: return self._TabResultInquiry if self._TabResultResponse is not None: return self._TabResultResponse if self._TransferwiseTransfer is not None: return self._TransferwiseTransfer raise exception.BunqException(self._ERROR_NULL_FIELDS)
python
def get_referenced_object(self): """ :rtype: core.BunqModel :raise: BunqException """ if self._BunqMeTab is not None: return self._BunqMeTab if self._BunqMeTabResultResponse is not None: return self._BunqMeTabResultResponse if self._BunqMeFundraiserResult is not None: return self._BunqMeFundraiserResult if self._Card is not None: return self._Card if self._CardDebit is not None: return self._CardDebit if self._DraftPayment is not None: return self._DraftPayment if self._FeatureAnnouncement is not None: return self._FeatureAnnouncement if self._IdealMerchantTransaction is not None: return self._IdealMerchantTransaction if self._Invoice is not None: return self._Invoice if self._ScheduledPayment is not None: return self._ScheduledPayment if self._ScheduledPaymentBatch is not None: return self._ScheduledPaymentBatch if self._ScheduledInstance is not None: return self._ScheduledInstance if self._MasterCardAction is not None: return self._MasterCardAction if self._BankSwitchServiceNetherlandsIncomingPayment is not None: return self._BankSwitchServiceNetherlandsIncomingPayment if self._Payment is not None: return self._Payment if self._PaymentBatch is not None: return self._PaymentBatch if self._RequestInquiryBatch is not None: return self._RequestInquiryBatch if self._RequestInquiry is not None: return self._RequestInquiry if self._RequestResponse is not None: return self._RequestResponse if self._RewardRecipient is not None: return self._RewardRecipient if self._RewardSender is not None: return self._RewardSender if self._ShareInviteBankInquiryBatch is not None: return self._ShareInviteBankInquiryBatch if self._ShareInviteBankInquiry is not None: return self._ShareInviteBankInquiry if self._ShareInviteBankResponse is not None: return self._ShareInviteBankResponse if self._SofortMerchantTransaction is not None: return self._SofortMerchantTransaction if self._TabResultInquiry is not None: return self._TabResultInquiry if self._TabResultResponse is not None: return self._TabResultResponse if self._TransferwiseTransfer is not None: return self._TransferwiseTransfer raise exception.BunqException(self._ERROR_NULL_FIELDS)
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kstaniek/condoor
condoor/__main__.py
URL.convert
def convert(self, value, param, ctx): """Convert to URL scheme.""" if not isinstance(value, tuple): parsed = urlparse.urlparse(value) if parsed.scheme not in ('telnet', 'ssh'): self.fail('invalid URL scheme (%s). Only telnet and ssh URLs are ' 'allowed' % parsed, param, ctx) return value
python
def convert(self, value, param, ctx): """Convert to URL scheme.""" if not isinstance(value, tuple): parsed = urlparse.urlparse(value) if parsed.scheme not in ('telnet', 'ssh'): self.fail('invalid URL scheme (%s). Only telnet and ssh URLs are ' 'allowed' % parsed, param, ctx) return value
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contentful/contentful-management.py
contentful_management/editor_interface.py
EditorInterface.base_url
def base_url(self, space_id, content_type_id, environment_id=None, **kwargs): """ Returns the URI for the editor interface. """ return "spaces/{0}{1}/content_types/{2}/editor_interface".format( space_id, '/environments/{0}'.format(environment_id) if environment_id is not None else '', content_type_id )
python
def base_url(self, space_id, content_type_id, environment_id=None, **kwargs): """ Returns the URI for the editor interface. """ return "spaces/{0}{1}/content_types/{2}/editor_interface".format( space_id, '/environments/{0}'.format(environment_id) if environment_id is not None else '', content_type_id )
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mitsei/dlkit
dlkit/records/assessment/qti/inline_choice_records.py
InlineChoiceTextQuestionFormRecord._init_metadata
def _init_metadata(self): """stub""" QuestionTextFormRecord._init_metadata(self) self._choices_metadata = { 'element_id': Id(self.my_osid_object_form._authority, self.my_osid_object_form._namespace, 'choices'), 'element_label': 'Choices', 'instructions': 'Enter as many choices as you wish', 'required': True, 'read_only': False, 'linked': False, 'array': True, 'default_object_values': [{}], 'syntax': 'OBJECT', 'object_set': [] } self._choice_text_metadata = { 'element_id': Id(self.my_osid_object_form._authority, self.my_osid_object_form._namespace, 'choice_text'), 'element_label': 'choice text', 'instructions': 'enter the text for this choice', 'required': True, 'read_only': False, 'linked': False, 'array': False, 'default_string_values': [{ 'text': '', 'languageTypeId': str(DEFAULT_LANGUAGE_TYPE), 'scriptTypeId': str(DEFAULT_SCRIPT_TYPE), 'formatTypeId': str(DEFAULT_FORMAT_TYPE), }], 'syntax': 'STRING', 'minimum_string_length': 0, 'maximum_string_length': 1024, 'string_set': [] }
python
def _init_metadata(self): """stub""" QuestionTextFormRecord._init_metadata(self) self._choices_metadata = { 'element_id': Id(self.my_osid_object_form._authority, self.my_osid_object_form._namespace, 'choices'), 'element_label': 'Choices', 'instructions': 'Enter as many choices as you wish', 'required': True, 'read_only': False, 'linked': False, 'array': True, 'default_object_values': [{}], 'syntax': 'OBJECT', 'object_set': [] } self._choice_text_metadata = { 'element_id': Id(self.my_osid_object_form._authority, self.my_osid_object_form._namespace, 'choice_text'), 'element_label': 'choice text', 'instructions': 'enter the text for this choice', 'required': True, 'read_only': False, 'linked': False, 'array': False, 'default_string_values': [{ 'text': '', 'languageTypeId': str(DEFAULT_LANGUAGE_TYPE), 'scriptTypeId': str(DEFAULT_SCRIPT_TYPE), 'formatTypeId': str(DEFAULT_FORMAT_TYPE), }], 'syntax': 'STRING', 'minimum_string_length': 0, 'maximum_string_length': 1024, 'string_set': [] }
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8,584
spacetelescope/stsci.tools
lib/stsci/tools/basicpar.py
IrafPar._setChoiceDict
def _setChoiceDict(self): """Create dictionary for choice list""" # value is name of choice parameter (same as key) self.choiceDict = {} for c in self.choice: self.choiceDict[c] = c
python
def _setChoiceDict(self): """Create dictionary for choice list""" # value is name of choice parameter (same as key) self.choiceDict = {} for c in self.choice: self.choiceDict[c] = c
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dhermes/bezier
scripts/doc_template_release.py
main
def main(): """Populate the templates with release-specific fields. Requires user input for the CircleCI, AppVeyor, Coveralls.io and Travis build IDs. """ version = get_version() circleci_build = six.moves.input("CircleCI Build ID: ") appveyor_build = six.moves.input("AppVeyor Build ID: ") coveralls_build = six.moves.input("Coveralls Build ID: ") travis_build = six.moves.input("Travis Build ID: ") populate_readme( version, circleci_build, appveyor_build, coveralls_build, travis_build ) populate_index( version, circleci_build, appveyor_build, coveralls_build, travis_build ) populate_native_libraries(version) populate_development(version)
python
def main(): """Populate the templates with release-specific fields. Requires user input for the CircleCI, AppVeyor, Coveralls.io and Travis build IDs. """ version = get_version() circleci_build = six.moves.input("CircleCI Build ID: ") appveyor_build = six.moves.input("AppVeyor Build ID: ") coveralls_build = six.moves.input("Coveralls Build ID: ") travis_build = six.moves.input("Travis Build ID: ") populate_readme( version, circleci_build, appveyor_build, coveralls_build, travis_build ) populate_index( version, circleci_build, appveyor_build, coveralls_build, travis_build ) populate_native_libraries(version) populate_development(version)
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cyrus-/cypy
cypy/np/plotting.py
raster
def raster(times, indices, max_time=None, max_index=None, x_label="Timestep", y_label="Index", **kwargs): """Plots a raster plot given times and indices of events.""" # set default size to 1 if 's' not in kwargs: kwargs['s'] = 1 scatter(times, indices, **kwargs) if max_time is None: max_time = max(times) if max_index is None: max_index = max(indices) axis((0, max_time, 0, max_index)) if x_label is not None: xlabel(x_label) if y_label is not None: ylabel(y_label)
python
def raster(times, indices, max_time=None, max_index=None, x_label="Timestep", y_label="Index", **kwargs): """Plots a raster plot given times and indices of events.""" # set default size to 1 if 's' not in kwargs: kwargs['s'] = 1 scatter(times, indices, **kwargs) if max_time is None: max_time = max(times) if max_index is None: max_index = max(indices) axis((0, max_time, 0, max_index)) if x_label is not None: xlabel(x_label) if y_label is not None: ylabel(y_label)
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saltstack/salt
salt/modules/virt.py
_parse_caps_devices_features
def _parse_caps_devices_features(node): ''' Parse the devices or features list of the domain capatilities ''' result = {} for child in node: if child.get('supported') == 'yes': enums = [_parse_caps_enum(node) for node in child.findall('enum')] result[child.tag] = {item[0]: item[1] for item in enums if item[0]} return result
python
def _parse_caps_devices_features(node): ''' Parse the devices or features list of the domain capatilities ''' result = {} for child in node: if child.get('supported') == 'yes': enums = [_parse_caps_enum(node) for node in child.findall('enum')] result[child.tag] = {item[0]: item[1] for item in enums if item[0]} return result
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noxdafox/clipspy
clips/classes.py
Instance.unmake
def unmake(self): """This method is equivalent to delete except that it uses message-passing instead of directly deleting the instance. """ if lib.EnvUnmakeInstance(self._env, self._ist) != 1: raise CLIPSError(self._env)
python
def unmake(self): """This method is equivalent to delete except that it uses message-passing instead of directly deleting the instance. """ if lib.EnvUnmakeInstance(self._env, self._ist) != 1: raise CLIPSError(self._env)
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datajoint/datajoint-python
datajoint/autopopulate.py
AutoPopulate.key_source
def key_source(self): """ :return: the relation whose primary key values are passed, sequentially, to the ``make`` method when populate() is called. The default value is the join of the parent relations. Users may override to change the granularity or the scope of populate() calls. """ def parent_gen(self): if self.target.full_table_name not in self.connection.dependencies: self.connection.dependencies.load() for parent_name, fk_props in self.target.parents(primary=True).items(): if not parent_name.isdigit(): # simple foreign key yield FreeTable(self.connection, parent_name).proj() else: grandparent = list(self.connection.dependencies.in_edges(parent_name))[0][0] yield FreeTable(self.connection, grandparent).proj(**{ attr: ref for attr, ref in fk_props['attr_map'].items() if ref != attr}) if self._key_source is None: parents = parent_gen(self) try: self._key_source = next(parents) except StopIteration: raise DataJointError('A relation must have primary dependencies for auto-populate to work') from None for q in parents: self._key_source *= q return self._key_source
python
def key_source(self): """ :return: the relation whose primary key values are passed, sequentially, to the ``make`` method when populate() is called. The default value is the join of the parent relations. Users may override to change the granularity or the scope of populate() calls. """ def parent_gen(self): if self.target.full_table_name not in self.connection.dependencies: self.connection.dependencies.load() for parent_name, fk_props in self.target.parents(primary=True).items(): if not parent_name.isdigit(): # simple foreign key yield FreeTable(self.connection, parent_name).proj() else: grandparent = list(self.connection.dependencies.in_edges(parent_name))[0][0] yield FreeTable(self.connection, grandparent).proj(**{ attr: ref for attr, ref in fk_props['attr_map'].items() if ref != attr}) if self._key_source is None: parents = parent_gen(self) try: self._key_source = next(parents) except StopIteration: raise DataJointError('A relation must have primary dependencies for auto-populate to work') from None for q in parents: self._key_source *= q return self._key_source
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pypa/pipenv
pipenv/utils.py
translate_markers
def translate_markers(pipfile_entry): """Take a pipfile entry and normalize its markers Provide a pipfile entry which may have 'markers' as a key or it may have any valid key from `packaging.markers.marker_context.keys()` and standardize the format into {'markers': 'key == "some_value"'}. :param pipfile_entry: A dictionariy of keys and values representing a pipfile entry :type pipfile_entry: dict :returns: A normalized dictionary with cleaned marker entries """ if not isinstance(pipfile_entry, Mapping): raise TypeError("Entry is not a pipfile formatted mapping.") from .vendor.distlib.markers import DEFAULT_CONTEXT as marker_context from .vendor.packaging.markers import Marker from .vendor.vistir.misc import dedup allowed_marker_keys = ["markers"] + [k for k in marker_context.keys()] provided_keys = list(pipfile_entry.keys()) if hasattr(pipfile_entry, "keys") else [] pipfile_markers = [k for k in provided_keys if k in allowed_marker_keys] new_pipfile = dict(pipfile_entry).copy() marker_set = set() if "markers" in new_pipfile: marker = str(Marker(new_pipfile.pop("markers"))) if 'extra' not in marker: marker_set.add(marker) for m in pipfile_markers: entry = "{0}".format(pipfile_entry[m]) if m != "markers": marker_set.add(str(Marker("{0}{1}".format(m, entry)))) new_pipfile.pop(m) if marker_set: new_pipfile["markers"] = str(Marker(" or ".join( "{0}".format(s) if " and " in s else s for s in sorted(dedup(marker_set)) ))).replace('"', "'") return new_pipfile
python
def translate_markers(pipfile_entry): """Take a pipfile entry and normalize its markers Provide a pipfile entry which may have 'markers' as a key or it may have any valid key from `packaging.markers.marker_context.keys()` and standardize the format into {'markers': 'key == "some_value"'}. :param pipfile_entry: A dictionariy of keys and values representing a pipfile entry :type pipfile_entry: dict :returns: A normalized dictionary with cleaned marker entries """ if not isinstance(pipfile_entry, Mapping): raise TypeError("Entry is not a pipfile formatted mapping.") from .vendor.distlib.markers import DEFAULT_CONTEXT as marker_context from .vendor.packaging.markers import Marker from .vendor.vistir.misc import dedup allowed_marker_keys = ["markers"] + [k for k in marker_context.keys()] provided_keys = list(pipfile_entry.keys()) if hasattr(pipfile_entry, "keys") else [] pipfile_markers = [k for k in provided_keys if k in allowed_marker_keys] new_pipfile = dict(pipfile_entry).copy() marker_set = set() if "markers" in new_pipfile: marker = str(Marker(new_pipfile.pop("markers"))) if 'extra' not in marker: marker_set.add(marker) for m in pipfile_markers: entry = "{0}".format(pipfile_entry[m]) if m != "markers": marker_set.add(str(Marker("{0}{1}".format(m, entry)))) new_pipfile.pop(m) if marker_set: new_pipfile["markers"] = str(Marker(" or ".join( "{0}".format(s) if " and " in s else s for s in sorted(dedup(marker_set)) ))).replace('"', "'") return new_pipfile
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train
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Rapptz/discord.py
discord/iterators.py
GuildIterator._retrieve_guilds_before_strategy
async def _retrieve_guilds_before_strategy(self, retrieve): """Retrieve guilds using before parameter.""" before = self.before.id if self.before else None data = await self.get_guilds(retrieve, before=before) if len(data): if self.limit is not None: self.limit -= retrieve self.before = Object(id=int(data[-1]['id'])) return data
python
async def _retrieve_guilds_before_strategy(self, retrieve): """Retrieve guilds using before parameter.""" before = self.before.id if self.before else None data = await self.get_guilds(retrieve, before=before) if len(data): if self.limit is not None: self.limit -= retrieve self.before = Object(id=int(data[-1]['id'])) return data
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robehickman/simple-http-file-sync
shttpfs/plain_storage.py
plain_storage.get_single_file_info
def get_single_file_info(self, rel_path): """ Gets last change time for a single file """ f_path = self.get_full_file_path(rel_path) return get_single_file_info(f_path, rel_path)
python
def get_single_file_info(self, rel_path): """ Gets last change time for a single file """ f_path = self.get_full_file_path(rel_path) return get_single_file_info(f_path, rel_path)
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tango-controls/pytango
tango/databaseds/database.py
DataBase.DbGetAttributeAlias
def DbGetAttributeAlias(self, argin): """ Get the attribute name for the given alias. If alias not found in database, returns an empty string. :param argin: The attribute alias name :type: tango.DevString :return: The attribute name (device/attribute) :rtype: tango.DevString """ self._log.debug("In DbGetAttributeAlias()") return self.db.get_attribute_alias(argin)
python
def DbGetAttributeAlias(self, argin): """ Get the attribute name for the given alias. If alias not found in database, returns an empty string. :param argin: The attribute alias name :type: tango.DevString :return: The attribute name (device/attribute) :rtype: tango.DevString """ self._log.debug("In DbGetAttributeAlias()") return self.db.get_attribute_alias(argin)
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apple/turicreate
deps/src/libxml2-2.9.1/python/libxml2.py
xmlNode.replaceNode
def replaceNode(self, cur): """Unlink the old node from its current context, prune the new one at the same place. If @cur was already inserted in a document it is first unlinked from its existing context. """ if cur is None: cur__o = None else: cur__o = cur._o ret = libxml2mod.xmlReplaceNode(self._o, cur__o) if ret is None:raise treeError('xmlReplaceNode() failed') __tmp = xmlNode(_obj=ret) return __tmp
python
def replaceNode(self, cur): """Unlink the old node from its current context, prune the new one at the same place. If @cur was already inserted in a document it is first unlinked from its existing context. """ if cur is None: cur__o = None else: cur__o = cur._o ret = libxml2mod.xmlReplaceNode(self._o, cur__o) if ret is None:raise treeError('xmlReplaceNode() failed') __tmp = xmlNode(_obj=ret) return __tmp
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ktbyers/netmiko
netmiko/_textfsm/_texttable.py
TextTable.Map
def Map(self, function): """Applies the function to every row in the table. Args: function: A function applied to each row. Returns: A new TextTable() Raises: TableError: When transform is not invalid row entry. The transform must be compatible with Append(). """ new_table = self.__class__() # pylint: disable=protected-access new_table._table = [self.header] for row in self: filtered_row = function(row) if filtered_row: new_table.Append(filtered_row) return new_table
python
def Map(self, function): """Applies the function to every row in the table. Args: function: A function applied to each row. Returns: A new TextTable() Raises: TableError: When transform is not invalid row entry. The transform must be compatible with Append(). """ new_table = self.__class__() # pylint: disable=protected-access new_table._table = [self.header] for row in self: filtered_row = function(row) if filtered_row: new_table.Append(filtered_row) return new_table
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inasafe/inasafe
safe/report/impact_report.py
InaSAFEReportContext.north_arrow
def north_arrow(self, north_arrow_path): """Set image that will be used as north arrow in reports. :param north_arrow_path: Path to the north arrow image. :type north_arrow_path: str """ if isinstance(north_arrow_path, str) and os.path.exists( north_arrow_path): self._north_arrow = north_arrow_path else: self._north_arrow = default_north_arrow_path()
python
def north_arrow(self, north_arrow_path): """Set image that will be used as north arrow in reports. :param north_arrow_path: Path to the north arrow image. :type north_arrow_path: str """ if isinstance(north_arrow_path, str) and os.path.exists( north_arrow_path): self._north_arrow = north_arrow_path else: self._north_arrow = default_north_arrow_path()
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sdss/sdss_access
python/sdss_access/sync/rsync.py
RsyncAccess.remote
def remote(self, username=None, password=None, inquire=None): """ Configures remote access """ self.set_netloc(sdss=True) # simplifies things to have a single sdss machine in .netrc self.set_auth(username=username, password=password, inquire=inquire) self.set_netloc(dtn=not self.public) self.set_remote_base(scheme="rsync")
python
def remote(self, username=None, password=None, inquire=None): """ Configures remote access """ self.set_netloc(sdss=True) # simplifies things to have a single sdss machine in .netrc self.set_auth(username=username, password=password, inquire=inquire) self.set_netloc(dtn=not self.public) self.set_remote_base(scheme="rsync")
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https://github.com/sdss/sdss_access/blob/76375bbf37d39d2e4ccbed90bdfa9a4298784470/python/sdss_access/sync/rsync.py#L28-L34
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newville/wxmplot
wxmplot/baseframe.py
BaseFrame.unzoom_all
def unzoom_all(self,event=None): """zoom out full data range """ if self.panel is not None: self.panel.unzoom_all(event=event)
python
def unzoom_all(self,event=None): """zoom out full data range """ if self.panel is not None: self.panel.unzoom_all(event=event)
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https://github.com/newville/wxmplot/blob/8e0dc037453e5cdf18c968dc5a3d29efd761edee/wxmplot/baseframe.py#L80-L83
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saltstack/salt
salt/utils/crypt.py
pem_finger
def pem_finger(path=None, key=None, sum_type='sha256'): ''' Pass in either a raw pem string, or the path on disk to the location of a pem file, and the type of cryptographic hash to use. The default is SHA256. The fingerprint of the pem will be returned. If neither a key nor a path are passed in, a blank string will be returned. ''' if not key: if not os.path.isfile(path): return '' with salt.utils.files.fopen(path, 'rb') as fp_: key = b''.join([x for x in fp_.readlines() if x.strip()][1:-1]) pre = getattr(hashlib, sum_type)(key).hexdigest() finger = '' for ind, _ in enumerate(pre): if ind % 2: # Is odd finger += '{0}:'.format(pre[ind]) else: finger += pre[ind] return finger.rstrip(':')
python
def pem_finger(path=None, key=None, sum_type='sha256'): ''' Pass in either a raw pem string, or the path on disk to the location of a pem file, and the type of cryptographic hash to use. The default is SHA256. The fingerprint of the pem will be returned. If neither a key nor a path are passed in, a blank string will be returned. ''' if not key: if not os.path.isfile(path): return '' with salt.utils.files.fopen(path, 'rb') as fp_: key = b''.join([x for x in fp_.readlines() if x.strip()][1:-1]) pre = getattr(hashlib, sum_type)(key).hexdigest() finger = '' for ind, _ in enumerate(pre): if ind % 2: # Is odd finger += '{0}:'.format(pre[ind]) else: finger += pre[ind] return finger.rstrip(':')
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https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/crypt.py#L117-L140