huawei-noah/pycodegpt-CodeCLM-full-100m
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def getValidityConstr(self): <NEW_LINE> <INDENT> for period in self._sections.keys(): <NEW_LINE> <INDENT> section = self._sections[period] <NEW_LINE> hasClass = 0 <NEW_LINE> if section != None and section.courseType != CourseType.OFF: <NEW_LINE> <INDENT> hasClass = 1 <NEW_LINE> <DEDENT> expr = [(var, 1) for var in self._lpVars[period]] <NEW_LINE> yield (LpAffineExpression(expr) <= hasClass) | Yields expressions of if periods have 0 or 1 class. | 625941a26aa9bd52df03693e |
def _get_axis_labels(self, in_dataset): <NEW_LINE> <INDENT> labels = in_dataset.data_info.get('axis_labels')[0] <NEW_LINE> volX, volY, volZ = self._get_volume_dimensions() <NEW_LINE> labels = [str(volX) + '.voxel_x.voxels', str(volZ) + '.voxel_z.voxels'] <NEW_LINE> if volY: <NEW_LINE> <INDENT> labels.append(str(volY) + '.voxel_y.voxels') <NEW_LINE> <DEDENT> labels = {in_dataset: labels} <NEW_LINE> return labels | Get the new axis labels for the output dataset - this is now a volume.
Parameters
----------
in_dataset : :class:`savu.data.data_structures.data.Data`
The input dataset to the plugin.
Returns
-------
labels : dict
The axis labels for the dataset that is output from the plugin. | 625941a26aa9bd52df036940 |
def bonferroni_correction(pvals): <NEW_LINE> <INDENT> n = len(pvals) <NEW_LINE> return [min(x * n , 1.0) for x in pvals] | Bonferroni correction.
Reference: http://en.wikipedia.org/wiki/Bonferroni_correction | 625941a26aa9bd52df036944 |
def main(self): <NEW_LINE> <INDENT> sys.path.append(os.curdir) <NEW_LINE> sys.path.append(os.path.join(os.curdir, "applications")) <NEW_LINE> sys.path.append(os.path.join(os.curdir, "plugins")) <NEW_LINE> sys.path.append(os.path.join(os.curdir, "framework")) <NEW_LINE> if not self.settings.consolelog: <NEW_LINE> <INDENT> if self.settings.production: <NEW_LINE> <INDENT> cgitb.enable( display=False ,logdir=os.path.join(os.curdir, 'logs') ,format='text') <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> cgitb.enable() <NEW_LINE> <DEDENT> <DEDENT> from framework import router <NEW_LINE> try: <NEW_LINE> <INDENT> from applications import handlers <NEW_LINE> <DEDENT> except: <NEW_LINE> <INDENT> handlers = None <NEW_LINE> <DEDENT> router.Router(handlers, self.settings).route() | Set some things to work the framework.
Then launch the application | 625941a36aa9bd52df036948 |
def unlisten_multicast_group(self, multicast_address, source = None, network_interface = None, handler = None): <NEW_LINE> <INDENT> def converter(server): <NEW_LINE> <INDENT> return self <NEW_LINE> <DEDENT> if network_interface is not None and source is not None: <NEW_LINE> <INDENT> self.java_obj.unlistenMulticastGroup(multicast_address, network_interface, source, AsyncHandler(handler, converter)) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> self.java_obj.unlistenMulticastGroup(multicast_address, AsyncHandler(handler, converter)) <NEW_LINE> <DEDENT> return self | Leaves a multicast group and so stop listen for packets send to it on the given network interface.
The handler is notified once the operation completes.
@param multicast_address: the address of the multicast group to leave
@param source: the address of the source for which we will stop listen for mulicast packets
@param network_interface: the network interface on which to stop listen for packets.
@param handler: then handler to notify once the operation completes
@return self: returns itself for method-chaining | 625941a36aa9bd52df036952 |
def __handle_response(self, msg, handler): <NEW_LINE> <INDENT> packets = msg.packets <NEW_LINE> if packets[0] == flags.response: <NEW_LINE> <INDENT> self.__print__( "Response received for request id %s" % packets[1], level=1) <NEW_LINE> if self.requests.get(packets[1]): <NEW_LINE> <INDENT> addr = packets[2] <NEW_LINE> if addr: <NEW_LINE> <INDENT> _msg = cast(Tuple[MsgPackable, ...], self.requests.get(packets[1])) <NEW_LINE> self.requests.pop(packets[1]) <NEW_LINE> self.connect(addr[0][0], addr[0][1], addr[1]) <NEW_LINE> self.routing_table[addr[1]].send(*_msg) <NEW_LINE> <DEDENT> <DEDENT> return True <NEW_LINE> <DEDENT> return None | This callback is used to deal with response signals. Its two
primary jobs are:
- if it was your request, send the deferred message
- if it was someone else's request, relay the information
Args:
msg: A :py:class:`~py2p.base.Message`
handler: A :py:class:`~py2p.mesh.MeshConnection`
Returns:
Either ``True`` or ``None`` | 625941a36aa9bd52df036959 |
def get_darksky_data(self, service, location, timestamp=None): <NEW_LINE> <INDENT> service_json_name = '' <NEW_LINE> if service in SERVICES_MAPPING: <NEW_LINE> <INDENT> service_json_name = SERVICES_MAPPING[service]['json_name'] <NEW_LINE> <DEDENT> if "lat" in location and 'long' in location: <NEW_LINE> <INDENT> if timestamp: <NEW_LINE> <INDENT> timestamp = int((timestamp.replace(tzinfo=None) - datetime.datetime.utcfromtimestamp(0)). total_seconds()) <NEW_LINE> url = "https://api.darksky.net/forecast/{key}/{lat}," "{long},{timestamp}?units=us".format( key=self._api_key, lat=location['lat'], long=location['long'], timestamp=timestamp) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> url = "https://api.darksky.net/forecast/{key}/{lat}," "{long}?units=us".format( key=self._api_key, lat=location['lat'], long=location['long']) <NEW_LINE> <DEDENT> if self.performance_mode: <NEW_LINE> <INDENT> services = ["currently", "hourly", "minutely", "daily"] <NEW_LINE> if service_json_name and service_json_name in services: <NEW_LINE> <INDENT> services.remove(service_json_name) <NEW_LINE> url += "&exclude=" + ",".join(services) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> raise RuntimeError("Requested service {} is not provided" " by the Darksky API".format(service)) <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> raise ValueError('Invalid location. Expected format is: ' '"{"lat": "xxx.xxxx", "long": "xxx.xxxx"}"') <NEW_LINE> <DEDENT> _log.info("requesting url: {}".format(url)) <NEW_LINE> grequest = [grequests.get(url, verify=requests.certs.where(), headers=self.headers, timeout=3)] <NEW_LINE> gresponse = grequests.map(grequest)[0] <NEW_LINE> self.add_api_call() <NEW_LINE> if gresponse is None: <NEW_LINE> <INDENT> raise RuntimeError("get request did not return any " "response") <NEW_LINE> <DEDENT> try: <NEW_LINE> <INDENT> response = jsonapi.loads(gresponse.content) <NEW_LINE> return response <NEW_LINE> <DEDENT> except ValueError: <NEW_LINE> <INDENT> self.generate_response_error(url, gresponse.status_code) | Generic method called by the current and forecast service endpoint
methods to fetch a forecast request from the Darksky API. If
performance mode is set to True, the url adds exclusions for the
services provided by the API that were not requested.
:param service: requested service endpoint
:param location: location dictionary for building url
:param timestamp: timestamp of a record if this request is for the
Time Machine end point
:return: Darksky forecast request response | 625941a46aa9bd52df036973 |
def append(self, obj, **kw): <NEW_LINE> <INDENT> obj = self.sanitize(obj, **kw) <NEW_LINE> return super(MeshHookList, self).append(obj) | The input :py:class:`~.hook.MeshHook` *obj* will be appended into the
list. The *obj* argument is usually a :py:class:`~.hook.MeshHook` type
or a :py:class:`~.anchor.MeshAnchor` type, instead of an instance of
them. The method will automatically create the necessary Hook object
when detect acceptable type object passed as the first argument.
See :py:meth:`sanitize` for conditions of the input *obj* and *kw*.
>>> import solvcon as sc
>>> from solvcon.testing import create_trivial_2d_blk
>>> cse = MeshCase() # No arguments because of demonstration.
>>> hook_list = MeshHookList(cse)
>>> len(hook_list)
0
>>> # Create two hooks of the same type and content.
>>> hook_list.append(sc.MeshHook, dummy="name")
>>> hook_list.append(sc.MeshHook, dummy="name")
>>> hook_list[0].kws['dummy'], hook_list[1].kws['dummy']
('name', 'name')
>>> # The two hooks aren't identical.
>>> hook_list[0] is hook_list[1]
False | 625941a46aa9bd52df036975 |
def only_classmethods(cls): <NEW_LINE> <INDENT> for k, v in cls.__dict__.items(): <NEW_LINE> <INDENT> if (not k.startswith('__') and callable(v) and not isinstance(v, (classmethod, staticmethod))): <NEW_LINE> <INDENT> setattr(cls, k, classmethod(v)) <NEW_LINE> <DEDENT> <DEDENT> return cls | convert all normal methods to classmethods | 625941a56aa9bd52df03698d |
def model_filter(func): <NEW_LINE> <INDENT> def process_terms(terms): <NEW_LINE> <INDENT> new_terms = [] <NEW_LINE> cand = '' <NEW_LINE> for term in terms: <NEW_LINE> <INDENT> if term.startswith(sign) or cand.endswith(sign): <NEW_LINE> <INDENT> cand = cand + term <NEW_LINE> continue <NEW_LINE> <DEDENT> if cand: <NEW_LINE> <INDENT> new_terms.append(cand) <NEW_LINE> <DEDENT> cand = term <NEW_LINE> <DEDENT> if cand: <NEW_LINE> <INDENT> new_terms.append(cand) <NEW_LINE> <DEDENT> return new_terms <NEW_LINE> <DEDENT> @functools.wraps(func) <NEW_LINE> def wrapper(queryset, query, *args, **kwargs): <NEW_LINE> <INDENT> if isinstance(query, basestring): <NEW_LINE> <INDENT> query = query.split() <NEW_LINE> query = process_terms(query) <NEW_LINE> <DEDENT> if query: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> return func(queryset, query, *args, **kwargs) <NEW_LINE> <DEDENT> except (FieldError, TypeError) as e: <NEW_LINE> <INDENT> logging.error("%s", e.message) <NEW_LINE> return queryset.none() <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> return queryset <NEW_LINE> <DEDENT> <DEDENT> return wrapper | Decorator to format query before passing it to a filter function.
The purpose of the decorator is to:
a) Split the queries into multiple keywords (space/tab separated).
b) Concatenate terms that have the ADMIN_FIELD_SIGN ("=") between them.
b) Ignore any empty queries. | 625941a56aa9bd52df036993 |
def convertToTitle(self, n): <NEW_LINE> <INDENT> str = "" <NEW_LINE> stack = [] <NEW_LINE> while n // 26 != 0: <NEW_LINE> <INDENT> stack.append(n % 26) <NEW_LINE> n = n // 26 <NEW_LINE> <DEDENT> stack.append(n % 26) <NEW_LINE> i = 0 <NEW_LINE> while i < len(stack): <NEW_LINE> <INDENT> if stack[i] == 0: <NEW_LINE> <INDENT> if i+1 < len(stack): <NEW_LINE> <INDENT> stack[i] = 26 <NEW_LINE> stack[i+1] -= 1 <NEW_LINE> <DEDENT> <DEDENT> i += 1 <NEW_LINE> <DEDENT> if stack[-1] == 0: <NEW_LINE> <INDENT> stack.pop() <NEW_LINE> <DEDENT> while len(stack) != 0: <NEW_LINE> <INDENT> x = stack.pop() <NEW_LINE> str += chr((x - 1) + ord("A")) <NEW_LINE> <DEDENT> return str | :type n: int
:rtype: str | 625941a56aa9bd52df036997 |
def test_01(self): <NEW_LINE> <INDENT> flag = True <NEW_LINE> try: <NEW_LINE> <INDENT> from xobox.utils.compat import EX_OK <NEW_LINE> <DEDENT> except ImportError: <NEW_LINE> <INDENT> flag = False <NEW_LINE> <DEDENT> self.assertTrue(flag) | Test Case 01:
Verify EX_OK is provided
Test is passed if no exception is raised. | 625941a56aa9bd52df0369a3 |
def execute(self,statement): <NEW_LINE> <INDENT> self.engine.execute(statement) | 执行sql语句。
:param statement:
:return: | 625941a66aa9bd52df0369ad |
@app.route('/group/<group_codename>/events/<int:event_id>/delete', methods=['GET', 'POST']) <NEW_LINE> def event_delete(group_codename, event_id): <NEW_LINE> <INDENT> (infonav, this_group, this_event) = gbot.views.get_context(group_codename=group_codename, event_id=event_id) <NEW_LINE> current_member = gbot.views.get_current_member(group_codename, current_user) <NEW_LINE> if this_event.is_host(current_member): <NEW_LINE> <INDENT> form = gbot.forms.DeleteForm(request.form) <NEW_LINE> content = {'event_name':this_event.name} <NEW_LINE> if form.validate_on_submit(): <NEW_LINE> <INDENT> if form.delete == True: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> controllers.event.delete_event(request,event_id) <NEW_LINE> flash("You successfully cancelled the Event called " + str(this_event.name) + ".", "success") <NEW_LINE> return redirect(url_for(gbot.views.event.event_list, group_codename=group_codename)) <NEW_LINE> <DEDENT> except Exception as e: <NEW_LINE> <INDENT> flash("Oof, something just went wrong. Sorry about that. Check this out: " + str(e)) <NEW_LINE> return redirect(url_for(gbot.views.event.event_list, group_codename=group_codename)) <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> flash("Okay, " + str(this_event.name) + " is still happening!") <NEW_LINE> return redirect(url_for(gbot.views.event.event_detail, group_codename=group_codename, event_id=event_id)) <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> return render_template('pages/events/delete.html', infonav=infonav, form=form, content=content) | This page essentially confirms whether or not the current_member (who must be a host) REALLY wants to
delete the event. | 625941a66aa9bd52df0369b1 |
def reduce(self, start, limit, reduce_op=operator.add): <NEW_LINE> <INDENT> if limit is None: <NEW_LINE> <INDENT> limit = self.capacity <NEW_LINE> <DEDENT> if limit < 0: <NEW_LINE> <INDENT> limit += self.capacity <NEW_LINE> <DEDENT> if reduce_op == operator.add: <NEW_LINE> <INDENT> result = 0.0 <NEW_LINE> <DEDENT> elif reduce_op == min: <NEW_LINE> <INDENT> result = float('inf') <NEW_LINE> <DEDENT> elif reduce_op == max: <NEW_LINE> <INDENT> result = float('-inf') <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> raise RLGraphError("Unsupported reduce OP. Support ops are [add, min, max].") <NEW_LINE> <DEDENT> start += self.capacity <NEW_LINE> limit += self.capacity <NEW_LINE> while start < limit: <NEW_LINE> <INDENT> if start & 1: <NEW_LINE> <INDENT> result = reduce_op(result, self.values[start]) <NEW_LINE> start += 1 <NEW_LINE> <DEDENT> if limit & 1: <NEW_LINE> <INDENT> limit -= 1 <NEW_LINE> result = reduce_op(result, self.values[limit]) <NEW_LINE> <DEDENT> start = start >> 1 <NEW_LINE> limit = limit >> 1 <NEW_LINE> <DEDENT> return result | Applies an operation to specified segment.
Args:
start (int): Start index to apply reduction to.
limit (end): End index to apply reduction to.
reduce_op (Union(operator.add, min, max)): Reduce op to apply.
Returns:
Number: Result of reduce operation | 625941a66aa9bd52df0369b7 |
def plot_with_difference(original, fooled): <NEW_LINE> <INDENT> fooled_v = fooled.clone().view(3,224,224).cpu().detach() <NEW_LINE> fooled_back = inv_transform(fooled_v) <NEW_LINE> original_back = inv_transform(original.clone()) <NEW_LINE> plt.figure() <NEW_LINE> plt.subplot(131) <NEW_LINE> plt.imshow(original_back) <NEW_LINE> plt.title('original') <NEW_LINE> boi_diff = ImChop.difference(fooled_back, original_back) <NEW_LINE> plt.subplot(132) <NEW_LINE> plt.imshow(boi_diff) <NEW_LINE> plt.title('difference') <NEW_LINE> plt.subplot(133) <NEW_LINE> plt.imshow(fooled_back) <NEW_LINE> plt.title('fooling') <NEW_LINE> print("Total value difference:", np.array(boi_diff).sum(),"\nAverage value difference:", np.array(boi_diff).mean()) | Takes the normalised tensor of two images and plot them | 625941a66aa9bd52df0369bb |
def circ_moment(alpha, w, p=1, cent=False, dim=0): <NEW_LINE> <INDENT> if w.size == 0: <NEW_LINE> <INDENT> w = np.ones(alpha.shape) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> checkShapesEqual(w, alpha) <NEW_LINE> <DEDENT> if cent: <NEW_LINE> <INDENT> theta = np.array(circ_mean(alpha, w, dim)) <NEW_LINE> theta = theta[~np.isnan(theta)] <NEW_LINE> theta_size = len(theta) <NEW_LINE> alpha = circ_dist(alpha, np.tile(theta, (alpha.shape[0] / theta_size,))) <NEW_LINE> <DEDENT> n = alpha.shape[dim] <NEW_LINE> cbar = np.sum(np.cos(p*alpha) * w, axis=dim) * 1.0 / n <NEW_LINE> sbar = np.sum(np.sin(p*alpha) * w, axis=dim) * 1.0 / n <NEW_LINE> mp = cbar + 1j * sbar <NEW_LINE> rho_p = np.abs(mp) <NEW_LINE> mu_p = np.angle(mp) <NEW_LINE> return (mp, rho_p, mu_p) | Calculates the complex p-th centred or non-centred moment
of the angular data in angle.
Input:
alpha sample of angles
[w weightings in case of binned angle data]
[p p-th moment to be computed, default is p=1]
[cent if true, central moments are computed, default = false]
[dim compute along this dimension, default is 1st axis]
If dim argument is specified, all other optional arguments can be
left empty: circ_moment(alpha, [], [], [], dim)
Output:
mp complex p-th moment
rho_p magnitude of the p-th moment
mu_p angle of th p-th moment
References:
Statistical analysis of circular data, Fisher, p. 33/34 | 625941a66aa9bd52df0369c5 |
def _get_prefix_limit(self): <NEW_LINE> <INDENT> return self.__prefix_limit | Getter method for prefix_limit, mapped from YANG variable /bgp/neighbors/neighbor/afi_safis/afi_safi/l3vpn_ipv4_multicast/prefix_limit (container)
YANG Description: Configure the maximum number of prefixes that will be
accepted from a peer
| 625941a76aa9bd52df0369d5 |
def setup_platform(hass, config, add_entities, discovery_info=None): <NEW_LINE> <INDENT> import pywink <NEW_LINE> for sensor in pywink.get_sensors(): <NEW_LINE> <INDENT> _id = sensor.object_id() + sensor.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> if sensor.capability() in SENSOR_TYPES: <NEW_LINE> <INDENT> add_entities([WinkBinarySensorDevice(sensor, hass)]) <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> for key in pywink.get_keys(): <NEW_LINE> <INDENT> _id = key.object_id() + key.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkBinarySensorDevice(key, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for sensor in pywink.get_smoke_and_co_detectors(): <NEW_LINE> <INDENT> _id = sensor.object_id() + sensor.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkSmokeDetector(sensor, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for hub in pywink.get_hubs(): <NEW_LINE> <INDENT> _id = hub.object_id() + hub.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkHub(hub, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for remote in pywink.get_remotes(): <NEW_LINE> <INDENT> _id = remote.object_id() + remote.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkRemote(remote, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for button in pywink.get_buttons(): <NEW_LINE> <INDENT> _id = button.object_id() + button.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkButton(button, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for gang in pywink.get_gangs(): <NEW_LINE> <INDENT> _id = gang.object_id() + gang.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkGang(gang, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for door_bell_sensor in pywink.get_door_bells(): <NEW_LINE> <INDENT> _id = door_bell_sensor.object_id() + door_bell_sensor.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> add_entities([WinkBinarySensorDevice(door_bell_sensor, hass)]) <NEW_LINE> <DEDENT> <DEDENT> for camera_sensor in pywink.get_cameras(): <NEW_LINE> <INDENT> _id = camera_sensor.object_id() + camera_sensor.name() <NEW_LINE> if _id not in hass.data[DOMAIN]['unique_ids']: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> if camera_sensor.capability() in SENSOR_TYPES: <NEW_LINE> <INDENT> add_entities([WinkBinarySensorDevice(camera_sensor, hass)]) <NEW_LINE> <DEDENT> <DEDENT> except AttributeError: <NEW_LINE> <INDENT> _LOGGER.info("Device isn't a sensor, skipping") | Set up the Wink binary sensor platform. | 625941a76aa9bd52df0369d9 |
def dumps_request( self, method, params=(), id=0 ): <NEW_LINE> <INDENT> if not isinstance(method, (str, unicode)): <NEW_LINE> <INDENT> raise TypeError('"method" must be a string (or unicode string).') <NEW_LINE> <DEDENT> if not isinstance(params, (tuple, list)): <NEW_LINE> <INDENT> raise TypeError("params must be a tuple/list.") <NEW_LINE> <DEDENT> return '{"method": %s, "params": %s, "id": %s}' % (self.dumps(method), self.dumps(params), self.dumps(id)) | serialize JSON-RPC-Request
:Parameters:
- method: the method-name (str/unicode)
- params: the parameters (list/tuple)
- id: if id=None, this results in a Notification
:Returns: | {"method": "...", "params": ..., "id": ...}
| "method", "params" and "id" are always in this order.
:Raises: TypeError if method/params is of wrong type or
not JSON-serializable | 625941a76aa9bd52df0369db |
def p_consume_id_funcion(p): <NEW_LINE> <INDENT> global variable_nombre_funcion <NEW_LINE> if not func_table.existeFuncion(p[1]): <NEW_LINE> <INDENT> raise NameError("La funcion no existe") <NEW_LINE> <DEDENT> variable_nombre_funcion = p[1] | consume_id_funcion : ID | 625941a76aa9bd52df0369e3 |
def get_size(self): <NEW_LINE> <INDENT> return self.size | 获取队列元素个数
:return: | 625941a76aa9bd52df0369e7 |
def show_port(self, context, port_id): <NEW_LINE> <INDENT> return dict(port=self._show_port(context, port_id)) | Return the port for the client given the port id.
:param context - Request context.
:param port_id - The id of port to be queried.
:returns: A dict containing port data keyed by 'port'.
e.g. {'port': {'port_id': 'abcd',
'fixed_ip_address': '1.2.3.4'}} | 625941a86aa9bd52df0369ff |
def p_TypeArgumentList(p): <NEW_LINE> <INDENT> p[0] = mytuple(["TypeArgumentList"]+p[1:]) | TypeArgumentList : TypeArgument COMMATypeArgumentS
| IDENT COMMATypeArgumentS | 625941a86aa9bd52df036a03 |
def check_response_errors(response, session): <NEW_LINE> <INDENT> if response['status'] != 'ok': <NEW_LINE> <INDENT> from wi.utils.auth import logout <NEW_LINE> error_code = response['status'] <NEW_LINE> error_msg = get_error(error_code) <NEW_LINE> raise RestErrorException(error_msg) <NEW_LINE> <DEDENT> return response | Checks status of response response and throws appropriate error. | 625941a96aa9bd52df036a0f |
def construct_data(kills, pilots): <NEW_LINE> <INDENT> return '\n'.join(kills + pilots) | Construct textarea content for resubmission
Given a list of kills and a list of pilots, put them together in a
form that enables them to be fed back into this view | 625941a96aa9bd52df036a22 |
def process_tracklog_file_v1(point_file, track_file, protocol, database_path): <NEW_LINE> <INDENT> print("building track logs") <NEW_LINE> track_log_oids = {} <NEW_LINE> mission_field_names, mission_field_types = extract_mission_attributes_from_protocol( protocol ) <NEW_LINE> mission_fields_count = len(mission_field_names) <NEW_LINE> columns = ( ["SHAPE@"] + mission_field_names + protocol["csv"]["track_logs"]["field_names"] ) <NEW_LINE> types = protocol["csv"]["track_logs"]["field_types"] <NEW_LINE> table_name = protocol["csv"]["track_logs"]["name"] <NEW_LINE> table = os.path.join(database_path, table_name) <NEW_LINE> s_key = protocol["csv"]["track_logs"]["start_key_indexes"] <NEW_LINE> e_key = protocol["csv"]["track_logs"]["end_key_indexes"] <NEW_LINE> gps_keys = protocol["csv"]["gps_points"]["key_indexes"] <NEW_LINE> last_point = None <NEW_LINE> with arcpy.da.InsertCursor(table, columns) as cursor: <NEW_LINE> <INDENT> for line in csv.reader(track_file): <NEW_LINE> <INDENT> if sys.version_info[0] < 3: <NEW_LINE> <INDENT> items = [item.decode("utf-8") for item in line] <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> items = line <NEW_LINE> <DEDENT> protocol_items = items[:mission_fields_count] <NEW_LINE> other_items = items[mission_fields_count:] <NEW_LINE> start_time, end_time = other_items[s_key[T]], other_items[e_key[T]] <NEW_LINE> track, last_point = build_track_geometry( point_file, last_point, start_time, end_time, gps_keys ) <NEW_LINE> row = ( [track] + [ cast(item, mission_field_types[i]) for i, item in enumerate(protocol_items) ] + [cast(item, types[i]) for i, item in enumerate(other_items)] ) <NEW_LINE> track_log_oids[start_time] = cursor.insertRow(row) <NEW_LINE> <DEDENT> <DEDENT> return track_log_oids | Build a track log feature class and return the object IDs of the new track logs. | 625941aa6aa9bd52df036a28 |
def setSocialNetwork(self, newSocialNetwork): <NEW_LINE> <INDENT> self._socialNetwork = newSocialNetwork | Set a new SocialNetwork
Requires: newSocialNetwork SocialNetwork
Ensures: self.getSocialNetwork() == newSocialNetwork | 625941aa6aa9bd52df036a2a |
def matlab_style_gauss2D(shape=np.array([11,11]),sigma=1.5): <NEW_LINE> <INDENT> siz = (shape-np.array([1,1]))/2 <NEW_LINE> std = sigma <NEW_LINE> eps = 2.2204e-16 <NEW_LINE> x = np.arange(-siz[1], siz[1]+1, 1) <NEW_LINE> y = np.arange(-siz[0], siz[1]+1, 1) <NEW_LINE> m,n = np.meshgrid(x, y) <NEW_LINE> h = np.exp(-(m*m + n*n).astype(np.float32) / (2.*sigma*sigma)) <NEW_LINE> h[ h < eps*h.max() ] = 0 <NEW_LINE> sumh = h.sum() <NEW_LINE> if sumh != 0: <NEW_LINE> <INDENT> h = h.astype(np.float32) / sumh <NEW_LINE> <DEDENT> return h | 2D gaussian mask - should give the same result as MATLAB's
fspecial('gaussian',[shape],[sigma]) | 625941aa6aa9bd52df036a2c |
@home.route('/') <NEW_LINE> def homepage(): <NEW_LINE> <INDENT> return make_response(jsonify( { 'message':'welcome to the hello-books app you can register in order to get the most out of the app' } )), 200 | get requests for homepage | 625941aa6aa9bd52df036a38 |
def __init__(self, atoms, protcomplex, cclass, altconf): <NEW_LINE> <INDENT> Mol.__init__(self, altconf) <NEW_LINE> self.complex = cclass <NEW_LINE> self.full_mol = protcomplex <NEW_LINE> self.all_atoms = atoms <NEW_LINE> self.rings = self.find_rings(self.full_mol, self.all_atoms) <NEW_LINE> self.hydroph_atoms = self.hydrophobic_atoms(self.all_atoms) <NEW_LINE> self.hbond_acc_atoms = self.find_hba(self.all_atoms) <NEW_LINE> self.hbond_don_atom_pairs = self.find_hbd(self.all_atoms, self.hydroph_atoms) <NEW_LINE> self.charged = self.find_charged(self.full_mol) <NEW_LINE> self.halogenbond_acc = self.find_hal(self.all_atoms) | Find all relevant parts which could take part in interactions | 625941aa6aa9bd52df036a3e |
def hamming_weight(n: int) -> int: <NEW_LINE> <INDENT> count = 0 <NEW_LINE> while n != 0: <NEW_LINE> <INDENT> n &= n - 1 <NEW_LINE> count += 1 <NEW_LINE> <DEDENT> return count | # 191: Write a function that takes an unsigned integer and return the number of '1' bits it has
(also known as the Hamming weight). | 625941aa6aa9bd52df036a42 |
def convert_obs_groups_binning_def_michi_to_default(): <NEW_LINE> <INDENT> altitude_edges = Angle([0, 20, 23, 27, 30, 33, 37, 40, 44, 49, 53, 58, 64, 72, 90], 'degree') <NEW_LINE> azimuth_edges = Angle([-90, 90, 270], 'degree') <NEW_LINE> list_obs_group_axis = [ObservationGroupAxis('ALT', altitude_edges, 'bin_edges'), ObservationGroupAxis('AZ', azimuth_edges, 'bin_edges')] <NEW_LINE> obs_groups_michi = ObservationGroups(list_obs_group_axis) <NEW_LINE> print("Observation groups 'michi':") <NEW_LINE> print(obs_groups_michi.obs_groups_table) <NEW_LINE> outfile = 'bg_observation_groups_michi.ecsv' <NEW_LINE> print('Writing {}'.format(outfile)) <NEW_LINE> obs_groups_michi.write(outfile) <NEW_LINE> lookup_obs_groups_michi = Table() <NEW_LINE> n_cols = 1 + len(list_obs_group_axis) <NEW_LINE> n_rows = obs_groups_michi.n_groups <NEW_LINE> lookup_obs_groups_michi['GROUP_ID'] = np.zeros(n_rows, dtype=np.int) <NEW_LINE> lookup_obs_groups_michi['ALT_ID'] = np.zeros(n_rows, dtype=np.int) <NEW_LINE> lookup_obs_groups_michi['AZ_ID'] = np.zeros(n_rows, dtype=np.int) <NEW_LINE> count_groups = 0 <NEW_LINE> for alt_id in np.arange(len(altitude_edges) - 1): <NEW_LINE> <INDENT> for az_id in np.arange(len(azimuth_edges) - 1): <NEW_LINE> <INDENT> lookup_obs_groups_michi['GROUP_ID'][count_groups] = count_groups <NEW_LINE> lookup_obs_groups_michi['ALT_ID'][count_groups] = alt_id <NEW_LINE> lookup_obs_groups_michi['AZ_ID'][count_groups] = az_id <NEW_LINE> count_groups += 1 <NEW_LINE> <DEDENT> <DEDENT> print("lookup table:") <NEW_LINE> print(lookup_obs_groups_michi) <NEW_LINE> outfile = 'lookup_obs_groups_michi.ecsv' <NEW_LINE> print('Writing {}'.format(outfile)) <NEW_LINE> ascii.write(lookup_obs_groups_michi, outfile, format='ecsv', fast_writer=False) | Convert observation groups binning definition "michi" to "default".
| 625941aa6aa9bd52df036a48 |
def _file_wr(self, filename, data): <NEW_LINE> <INDENT> with open(filename, 'w') as f: <NEW_LINE> <INDENT> json.dump([data], f) | Helper function to write a file | 625941ab6aa9bd52df036a4c |
def monsterate(match): <NEW_LINE> <INDENT> if not match: <NEW_LINE> <INDENT> return '' <NEW_LINE> <DEDENT> bits = match.groupdict('') <NEW_LINE> body = match.group(0) <NEW_LINE> if bits['count'] == '1': <NEW_LINE> <INDENT> bits['count'] = '' <NEW_LINE> <DEDENT> if bits['name'] in names: <NEW_LINE> <INDENT> sys.stderr.write(f'found {bits["name"]}\n') <NEW_LINE> return body <NEW_LINE> <DEDENT> fail = list() <NEW_LINE> for name in translate(bits): <NEW_LINE> <INDENT> if name in MOBS: <NEW_LINE> <INDENT> body = 'MV%(mv)s, %(hd)sHD, %(atk)s%(special)s; %(ac)sAC, %(sv)s+, ML%(ml)s, %(cl)s/%(xp)s' % MOBS[name] <NEW_LINE> break <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> fail.append(name) <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> foo = '\n '.join(fail) <NEW_LINE> sys.stderr.write(f'missing {bits["name"]}\n{foo}') <NEW_LINE> <DEDENT> return '*%s*: %s' % (('%(count)s %(name)s' % bits).strip(), body) | Thing with monster. | 625941ab6aa9bd52df036a50 |
@api.route('/logout', methods=['GET']) <NEW_LINE> def logout(): <NEW_LINE> <INDENT> response = make_response( jsonify({'success': 'The user has been logged out.'}), 200 ) <NEW_LINE> response.delete_cookie('public_id') <NEW_LINE> unset_jwt_cookies(response) <NEW_LINE> return response | Logs out user and sends a response to clear access and refresh
tokens, public_id cookie, and returns success message
Returns {Object<json>} 200
success: {string} | 625941ac6aa9bd52df036a6e |
def dir_is_empty(path): <NEW_LINE> <INDENT> return isdir(path) and len(os.listdir(path)) == 0 | Check if a directory is empty | 625941ac6aa9bd52df036a74 |
def play_episode(act, embedding, features): <NEW_LINE> <INDENT> env = gym_environment.WSNEnvironment( problem_generator=lambda: (embedding, None), features=features, early_exit_factor=np.infty, additional_timeslot_reward=-1, restart_reward=0, success_reward=0, seedgen=None, ) <NEW_LINE> return _play_episode_in_env(act, env) | Play an entire episode and report the reward | 625941ac6aa9bd52df036a7a |
def resize(self, width=None, height=None, filter='triangle', blur=1): <NEW_LINE> <INDENT> if width is None: <NEW_LINE> <INDENT> width = self.width <NEW_LINE> <DEDENT> if height is None: <NEW_LINE> <INDENT> height = self.height <NEW_LINE> <DEDENT> if not isinstance(width, numbers.Integral): <NEW_LINE> <INDENT> raise TypeError('width must be a natural number, not ' + repr(width)) <NEW_LINE> <DEDENT> elif not isinstance(height, numbers.Integral): <NEW_LINE> <INDENT> raise TypeError('height must be a natural number, not ' + repr(height)) <NEW_LINE> <DEDENT> elif width < 1: <NEW_LINE> <INDENT> raise ValueError('width must be a natural number, not ' + repr(width)) <NEW_LINE> <DEDENT> elif height < 1: <NEW_LINE> <INDENT> raise ValueError('height must be a natural number, not ' + repr(height)) <NEW_LINE> <DEDENT> elif not isinstance(blur, numbers.Real): <NEW_LINE> <INDENT> raise TypeError('blur must be numbers.Real , not ' + repr(blur)) <NEW_LINE> <DEDENT> elif not isinstance(filter, (basestring, numbers.Integral)): <NEW_LINE> <INDENT> raise TypeError('filter must be one string defined in wand.image.' 'FILTER_TYPES or an integer, not ' + repr(filter)) <NEW_LINE> <DEDENT> if isinstance(filter, basestring): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> filter = FILTER_TYPES.index(filter) <NEW_LINE> <DEDENT> except IndexError: <NEW_LINE> <INDENT> raise ValueError(repr(filter) + ' is an invalid filter type; ' 'choose on in ' + repr(FILTER_TYPES)) <NEW_LINE> <DEDENT> <DEDENT> elif (isinstance(filter, numbers.Integral) and not (0 <= filter < len(FILTER_TYPES))): <NEW_LINE> <INDENT> raise ValueError(repr(filter) + ' is an invalid filter type') <NEW_LINE> <DEDENT> blur = ctypes.c_double(float(blur)) <NEW_LINE> library.MagickResizeImage(self.wand, width, height, filter, blur) | Resizes the image.
:param width: the width in the scaled image. default is the original
width
:type width: :class:`numbers.Integral`
:param height: the height in the scaled image. default is the original
height
:type height: :class:`numbers.Integral`
:param filter: a filter type to use for resizing. choose one in
:const:`FILTER_TYPES`. default is ``'triangle'``
:type filter: :class:`basestring`, :class:`numbers.Integral`
:param blur: the blur factor where > 1 is blurry, < 1 is sharp.
default is 1
:type blur: :class:`numbers.Real` | 625941ac6aa9bd52df036a88 |
def unload(self, key): <NEW_LINE> <INDENT> assert isinstance(key, PGPKey) <NEW_LINE> pkid = id(key) <NEW_LINE> if pkid in self._keys: <NEW_LINE> <INDENT> [ kd.remove(pkid) for kd in [self._pubkeys, self._privkeys] if pkid in kd ] <NEW_LINE> self._keys.pop(pkid) <NEW_LINE> for m, a in [ (m, a) for m in self._aliases for a, p in m.items() if p == pkid ]: <NEW_LINE> <INDENT> m.pop(a) <NEW_LINE> if a in self: <NEW_LINE> <INDENT> self._sort_alias(a) <NEW_LINE> <DEDENT> <DEDENT> if key.is_primary: <NEW_LINE> <INDENT> [ self.unload(sk) for sk in key.subkeys.values() ] | Unload a loaded key and its subkeys.
The easiest way to do this is to select a key using :py:meth:`PGPKeyring.key` first::
with keyring.key("DSA von TestKey") as key:
keyring.unload(key)
:param key: The key to unload.
:type key: :py:obj:`PGPKey` | 625941ad6aa9bd52df036a9b |
def _check_project_dir(project_dir, force=False): <NEW_LINE> <INDENT> if os.path.exists(project_dir) and not os.path.isdir(project_dir): <NEW_LINE> <INDENT> raise CommandError(f'The path {project_dir} already exists and is a file.') <NEW_LINE> <DEDENT> if not os.path.isdir(project_dir): <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> if force: <NEW_LINE> <INDENT> logger.info('\'%s\' already exists - removing', os.path.basename(project_dir)) <NEW_LINE> shutil.rmtree(project_dir) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> raise CommandError(f'\'{os.path.basename(project_dir)}\' already exists. Either remove this ' 'project or use the force option') | Check if a project directory with the given name already exists.
If such a project exists, only continue if the ``force`` flag has been
specified. | 625941ad6aa9bd52df036a9f |
def get_field_alias_grid_column_names_by_order(self): <NEW_LINE> <INDENT> self.column_name_list = self.get_grid_column_names_by_order(self.field_alias_grid_div_id) <NEW_LINE> return self.column_name_list | Implementing get field alias grid column names by order functionality
:return: column_name_list | 625941add7e4931a7ee9dc18 |
def StockTable(inputfilename,taxbracketfile): <NEW_LINE> <INDENT> input=open(inputfilename) <NEW_LINE> UniqTickers=UT.UniqueTickers(inputfilename) <NEW_LINE> data_string=json.load(input) <NEW_LINE> emailReportMsg="" <NEW_LINE> htmlOutput=" " <NEW_LINE> jsonOutput="{ \"date\":\""+DTH.GetDate()+"\",\n \"portfolio\":[" <NEW_LINE> csvOutput="" <NEW_LINE> for portfolio in data_string["portfolio"]: <NEW_LINE> <INDENT> if portfolio["display"] == "yes": <NEW_LINE> <INDENT> jsonOutput+="{\"portfolioname\":\"" + portfolio["portfolioName"]+"\", \"portfolioStocks\":[" <NEW_LINE> print('==================----------',portfolio["portfolioName"],'----------==================') <NEW_LINE> TCC.DefaultColorCoding() <NEW_LINE> H.PrintHeader2() <NEW_LINE> cumulative=Accumulator.Accumulator() <NEW_LINE> emailReportMsg+=portfolio["portfolioName"] <NEW_LINE> for data in portfolio["portfolioStocks"]: <NEW_LINE> <INDENT> data["taxBracketFile"]=taxbracketfile <NEW_LINE> stock=S.Stock(data,UniqTickers.tickerDict[data["ticker"]]) <NEW_LINE> cumulative.Add(stock.totalpurchaseprice, stock.commission_to_buy, stock.dollarGain,stock.dailyChange_func() ,stock.currentWorth_func() ) <NEW_LINE> stock.PrintColorized3() <NEW_LINE> message=stock.PrintForTxtMessage() <NEW_LINE> emailReportMsg+=stock.JSON() <NEW_LINE> jsonOutput+=stock.JSON()+"," <NEW_LINE> csvOutput+=stock.CSV()+"\n" <NEW_LINE> <DEDENT> jsonOutput=jsonOutput.rstrip(',') <NEW_LINE> jsonOutput+="]," <NEW_LINE> jsonOutput+="\n" <NEW_LINE> jsonOutput+="\"cumulative Result\":"+cumulative.JSONify()+"}," <NEW_LINE> emailReportMsg+=cumulative.JSONify()+",\n" <NEW_LINE> cumulative.Print() <NEW_LINE> TCC.DefaultColorCoding() <NEW_LINE> <DEDENT> <DEDENT> jsonOutput=jsonOutput.rstrip(',') <NEW_LINE> jsonOutput+="] }" <NEW_LINE> input.close() <NEW_LINE> FileOutputHelper.WriteToDisk( FileOutputHelper.CreateOutputFilename(inputfilename,".out.json"),jsonOutput,'w') <NEW_LINE> FileOutputHelper.WriteToDisk( FileOutputHelper.CreateOutputFilename(inputfilename,"csv"),csvOutput,'a') <NEW_LINE> return stock.getDictionary() | #This methoad traverses a portfolio and outputs the performance of each stock in the portfolio
#as well as overall performance. | 625941add7e4931a7ee9dc1c |
def save(self): <NEW_LINE> <INDENT> self.config.set_space_placement(self.choice.GetStringSelection()) | Write all parameters to the config. | 625941ad6aa9bd52df036aa6 |
def debug(self): <NEW_LINE> <INDENT> print(str(self)) <NEW_LINE> print('<internal> %s: %s' % ('src', getattr(self, 'src', None))) <NEW_LINE> print('<internal> %s: %s' % ('meta', getattr(self, 'meta', None))) <NEW_LINE> for k, v in self._attrs.items(): <NEW_LINE> <INDENT> if k: <NEW_LINE> <INDENT> print('%s: %s' % (k, v)) | Print all attributes | 625941ae6aa9bd52df036aaa |
def __init__(self, name, title, description, datatype, gateway=None, device=None): <NEW_LINE> <INDENT> if name in parameters and isinstance(parameters[name], Parameter): <NEW_LINE> <INDENT> raise Exception('parameter with same name already exists') <NEW_LINE> <DEDENT> self.name = name <NEW_LINE> self.title = title <NEW_LINE> self.description = description <NEW_LINE> self.datatype = datatype <NEW_LINE> self.gateway = gateway <NEW_LINE> self.device = device <NEW_LINE> self.connection = None <NEW_LINE> if name in parameters: <NEW_LINE> <INDENT> self._referenced = parameters[name] <NEW_LINE> <DEDENT> parameters[name] = self | init the object parameter.
:param gateway: optional, in case of device or asset relative to a gateway
:param device: optional, in case of asset relative to a device
:param name: name of the parameter, Should be unique, within the application (checked), used to identify the value.
:param title: a human readable title
:param description: a user readable description.
:param datatype: the datatype of the varaible. Currently supported values: 'asset', 'sensor', 'actuator', 'device', 'gateway' | 625941ae6aa9bd52df036ab0 |
def get_recommendations(srs): <NEW_LINE> <INDENT> assert len(srs) == 1 and srs[0].__class__ == Subreddit <NEW_LINE> sr = srs[0] <NEW_LINE> recs = _get_recommendations(sr._id36) <NEW_LINE> if not recs: <NEW_LINE> <INDENT> return [] <NEW_LINE> <DEDENT> srs = Subreddit._byID36(recs, return_dict=True, data=True) <NEW_LINE> return srs | Return the subreddits recommended if you like the given subreddit | 625941ae6aa9bd52df036ab8 |
def MakePrediction(self, X, parameters, hidden_func, output_func): <NEW_LINE> <INDENT> X = X.T <NEW_LINE> AL, _ = self.ForwardProp(X, parameters, hidden_func, output_func) <NEW_LINE> if output_func=='softmax': <NEW_LINE> <INDENT> y_pred = np.argmax(AL, axis=0) <NEW_LINE> <DEDENT> if output_func=='sigmoid': <NEW_LINE> <INDENT> y_pred = ((AL >0.5)*1).reshape(-1) <NEW_LINE> <DEDENT> return y_pred | Make prediction of the data X
---------
Input
- X : Input data (m, n_x)
- parameters : parameters W, b of each layers of the NN model
Output
- y_pred : Predicted labels for X (m,) | 625941ae293b9510aa2c2fb3 |
def on_disconnect(self): <NEW_LINE> <INDENT> logger.error('Disconnected from server!') | Handler for disconnection events | 625941ae6aa9bd52df036abc |
def op_2(program, pc, opcode): <NEW_LINE> <INDENT> multiplicand1, multiplicand2 = get_parameters(program, pc, opcode, 2) <NEW_LINE> output_register = program[pc + 3] <NEW_LINE> program[output_register] = multiplicand1 * multiplicand2 <NEW_LINE> return 4 | Multiplication Operation | 625941ae293b9510aa2c2fb5 |
def draw_random_bst(n): <NEW_LINE> <INDENT> from random import randint <NEW_LINE> nums = set() <NEW_LINE> max_num = 10 * n <NEW_LINE> if 0 < n < MAX_HEIGHT: <NEW_LINE> <INDENT> while len(nums) != n: <NEW_LINE> <INDENT> nums.add(randint(1, max_num)) <NEW_LINE> <DEDENT> <DEDENT> draw_bst(list(nums)) | Draw random binary search tree of n nodes
| 625941ae3317a56b86939981 |
def reset(self): <NEW_LINE> <INDENT> self._timestep = np.array([0]) | See base class (Policy) for description.
Subclasses are expected to feed self._timestep to their q_func graphs and
increment self._timestep in `sample_action`. | 625941aed7e4931a7ee9dc38 |
def test_cut(self): <NEW_LINE> <INDENT> url = self.tpl + '/cut' <NEW_LINE> res = requests.post(url, data=self.data) <NEW_LINE> self.assertEqual(res.status_code, 200) <NEW_LINE> result = res.json() <NEW_LINE> self.assertEqual(result['text'], self.text) <NEW_LINE> self.assertEqual(''.join(result['words']), self.text) | 测试默认分词模式 | 625941ae6aa9bd52df036ac1 |
def execute(self, env, out): <NEW_LINE> <INDENT> raise NotImplementedError('abstract') | Appends output to out, or returns the result if an expression. | 625941ae3346ee7daa2b2a87 |
def Realize(self): <NEW_LINE> <INDENT> status = True <NEW_LINE> self._collapse_stack = [] <NEW_LINE> for child in self.GetChildren(): <NEW_LINE> <INDENT> if not isinstance(child, RibbonControl): <NEW_LINE> <INDENT> continue <NEW_LINE> <DEDENT> if not child.Realize(): <NEW_LINE> <INDENT> status = False <NEW_LINE> <DEDENT> child.SetSize(wx.Size(*child.GetMinSize())) <NEW_LINE> <DEDENT> x, y = self.GetSize() <NEW_LINE> if x > 0 and y > 0: <NEW_LINE> <INDENT> status = self.Layout() and status <NEW_LINE> <DEDENT> return status | Perform a full re-layout of all panels on the page.
Should be called after panels are added to the page, or the sizing behaviour of
a panel on the page changes (i.e. due to children being added to it). Usually
called automatically when :meth:`RibbonBar.Realize() <lib.agw.ribbon.bar.RibbonBar.Realize>` is called. Will invoke
:meth:`RibbonPanel.Realize() <lib.agw.ribbon.panel.RibbonPanel.Realize>` for all child panels.
:note: Reimplemented from :class:`~wx.lib.agw.ribbon.control.RibbonControl`. | 625941aed7e4931a7ee9dc3e |
def __init__(self, data): <NEW_LINE> <INDENT> question_url, question_title, question_desc, question_stats, answers, comments, dup_url = data <NEW_LINE> self.dup_url = dup_url <NEW_LINE> self.question_title = question_title <NEW_LINE> self.question_desc = question_desc <NEW_LINE> self.question_stats = question_stats <NEW_LINE> self.url = question_url <NEW_LINE> self.answer_text = AnswerText(answers, comments) <NEW_LINE> answer_frame = self.make_frame() <NEW_LINE> urwid.WidgetWrap.__init__(self, answer_frame) | Construct the Question Page.
:param data: tuple of (question_url, question_title, question_desc, question_stats, answers, comments, dup_url) | 625941ae3317a56b86939989 |
def draw_hull(self): <NEW_LINE> <INDENT> plt.plot(self._points[:,0], self._points[:,1], 'o') <NEW_LINE> for simplex in self.hull.simplices: <NEW_LINE> <INDENT> plt.plot(self._points[simplex, 0], self._points[simplex, 1], 'k-') | Draws, but does not display, all points along with an outlined
convex hull. A call to plt.show() must be made to show this shape. | 625941ae3346ee7daa2b2a8d |
def resolve(self, max_rounds: int = 10) -> Set[InstallRequirement]: <NEW_LINE> <INDENT> if self.clear_caches: <NEW_LINE> <INDENT> self.dependency_cache.clear() <NEW_LINE> self.repository.clear_caches() <NEW_LINE> <DEDENT> with update_env_context_manager(PIP_EXISTS_ACTION="i"): <NEW_LINE> <INDENT> for current_round in count(start=1): <NEW_LINE> <INDENT> if current_round > max_rounds: <NEW_LINE> <INDENT> raise RuntimeError( "No stable configuration of concrete packages " "could be found for the given constraints after " "{max_rounds} rounds of resolving.\n" "This is likely a bug.".format(max_rounds=max_rounds) ) <NEW_LINE> <DEDENT> log.debug("") <NEW_LINE> log.debug(magenta(f"{f'ROUND {current_round}':^60}")) <NEW_LINE> has_changed, best_matches = self._resolve_one_round() <NEW_LINE> log.debug("-" * 60) <NEW_LINE> log.debug( "Result of round {}: {}".format( current_round, "not stable" if has_changed else "stable, done", ) ) <NEW_LINE> if not has_changed: <NEW_LINE> <INDENT> break <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> results = {req for req in best_matches if not req.constraint} <NEW_LINE> self.unsafe_constraints = set() <NEW_LINE> if not self.allow_unsafe: <NEW_LINE> <INDENT> reverse_dependencies = self.reverse_dependencies(results) <NEW_LINE> for req in results.copy(): <NEW_LINE> <INDENT> required_by = reverse_dependencies.get(req.name.lower(), set()) <NEW_LINE> if req.name in UNSAFE_PACKAGES or ( required_by and all(name in UNSAFE_PACKAGES for name in required_by) ): <NEW_LINE> <INDENT> self.unsafe_constraints.add(req) <NEW_LINE> results.remove(req) <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> return results | Finds concrete package versions for all the given InstallRequirements
and their recursive dependencies. The end result is a flat list of
(name, version) tuples. (Or an editable package.)
Resolves constraints one round at a time, until they don't change
anymore. Protects against infinite loops by breaking out after a max
number rounds. | 625941af6aa9bd52df036acb |
def clear_journal_entry_terms(self): <NEW_LINE> <INDENT> raise errors.Unimplemented() | Clears all journal entry terms.
*compliance: mandatory -- This method must be implemented.* | 625941af3317a56b8693998d |
def stack_to_scaled(self, stack_coords, tgt_zoom, src_zoom=0): <NEW_LINE> <INDENT> return { dim: self.stack_to_scaled_coord(dim, proj_coord, tgt_zoom, src_zoom) for dim, proj_coord in stack_coords.items() } | Convert a point in stack space into a point in stack space at a different zoom level.
Whether z coordinates are scaled is controlled by the `scale_z` constructor argument/ instance variable.
Parameters
----------
stack_coords : dict
x, y, and/or z coordinates in stack / voxel space
tgt_zoom : float
Desired zoom level out of the output coordinates
src_zoom : float
Zoom level of the given coordinates (default 0)
Returns
-------
dict
Rescaled coordinates | 625941af5166f23b2e1a4e82 |
def get_endpoint_profiles(self, kaauser, group_id): <NEW_LINE> <INDENT> url = 'http://{}:{}/kaaAdmin/rest/api/endpointProfileBodyByGroupId?endpointGroupId={}'.format(self.host, self.port, str(group_id)) <NEW_LINE> req = requests.get(url, auth=(kaauser.name, kaauser.password)) <NEW_LINE> if req.status_code != requests.codes.ok: <NEW_LINE> <INDENT> raise KaaNodeError('Unable to get endpoint profiles. ' 'Return code: {}'.format(req.status_code)) <NEW_LINE> <DEDENT> return req.json() | Returns a list of endpoint profiles by the the endpoint group ID.
:param kaauser: The Kaa server IP address.
:type kaauser: KaaUser.
:param group_id: A unique endpoint group identifier. | 625941af6aa9bd52df036acd |
def noun_stem (s): <NEW_LINE> <INDENT> if s in identical_plurals: <NEW_LINE> <INDENT> return s <NEW_LINE> <DEDENT> elif s[-3:] == "man": <NEW_LINE> <INDENT> return s[:-2] + "en" <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return verb_stem(s) | extracts the stem from a plural noun, or returns empty string | 625941af3317a56b8693998f |
def delete(self): <NEW_LINE> <INDENT> selectedItems = self.piirtoalusta.scene.selectedItems() <NEW_LINE> command = CommandDelete(self.piirtoalusta.scene, selectedItems) <NEW_LINE> self.piirtoalusta.undoStack.push(command) | Poistaa valitut esineet ja/tai ryhmät | 625941af293b9510aa2c2fc7 |
def testdx(self): <NEW_LINE> <INDENT> gr = GaussianRestraint(*self.all) <NEW_LINE> for i in range(100): <NEW_LINE> <INDENT> map(self.change_value, self.all) <NEW_LINE> map(self.change_sign, self.locations) <NEW_LINE> gr.evaluate(True) <NEW_LINE> self.assertAlmostEqual(Nuisance(self.x).get_nuisance_derivative(), self.deriv_x(*self.all)) | Test GaussianRestraint(13) x derivative | 625941af293b9510aa2c2fc9 |
def setCalibParsDefault (self) : <NEW_LINE> <INDENT> for type in self.list_of_clib_types : <NEW_LINE> <INDENT> self.cpars[type] = self.getCalibParsDefault (type) <NEW_LINE> self.cpars_status[type] = 'DEFAULT' | Loads default calibration parameters from singleton object.
| 625941afadb09d7d5db6c4c5 |
def value_interval_cmp(value, interval): <NEW_LINE> <INDENT> if interval[0] <= value <= interval[1]: <NEW_LINE> <INDENT> return 0 <NEW_LINE> <DEDENT> elif value < interval[0]: <NEW_LINE> <INDENT> return -1 <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return 1 | Comparator that indicates if a value is within, higher or lower than an interval | 625941afd7e4931a7ee9dc4a |
def download_file(url: str, local_file: str) -> str: <NEW_LINE> <INDENT> log('Downloading {} to {}'.format(url, local_file)) <NEW_LINE> with requests.get(url, stream=True) as r: <NEW_LINE> <INDENT> r.raise_for_status() <NEW_LINE> with local_file.open(mode='wb') as f: <NEW_LINE> <INDENT> for chunk in r.iter_content(chunk_size=8192): <NEW_LINE> <INDENT> f.write(chunk) <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> return local_file | Download a file from an arbitrary URL to a local file | 625941afadb09d7d5db6c4c7 |
def __repr__(self): <NEW_LINE> <INDENT> return 'TippyGameState({}, {}, False)'.format(repr(self.next_player), repr(self.board)) | (TippyGameState) -> str
Return a string representation of TippyGameState self
that evaluates to an equivalent TippyGameState
>>> board = matrix(3)
>>> t = TippyGameState('p1', board)
>>> t
TippyGameState('p1', [['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']], False) | 625941af293b9510aa2c2fcd |
def phase_by_window_spec(self,source,windowSpec,trial_type): <NEW_LINE> <INDENT> selection = [] <NEW_LINE> for specix,spec in enumerate(windowSpec): <NEW_LINE> <INDENT> ix = self._fetch_windowspec_indices([spec],trial_type,precision=precision) <NEW_LINE> if len(ix)>0: <NEW_LINE> <INDENT> selection.append(( self.windowsByPart[trial_type][ix[0]][0], self.timeSplitTrials[trial_type][ix[0]], self.templateSplitTrials[trial_type][ix[0]] )) <NEW_LINE> try: <NEW_LINE> <INDENT> if source=='subject' or source=='s': <NEW_LINE> <INDENT> data = pickle.load(open('%s/subject_phase_%s_%d.p'%(self.dr,trial_type,ix[0]),'rb')) <NEW_LINE> phases,vs = data['phases'],data['vs'] <NEW_LINE> <DEDENT> elif source=='template' or source=='t': <NEW_LINE> <INDENT> data = pickle.load(open('%s/template_phase_%s_%d.p'%(self.dr,trial_type,ix[0]),'rb')) <NEW_LINE> phases,vs = data['phases'],data['vs'] <NEW_LINE> <DEDENT> phases = [np.vstack(p) for p in phases] <NEW_LINE> selection.append(( self.windowsByPart[trial_type][ix[0]][0],phases )) <NEW_LINE> <DEDENT> except IOError: <NEW_LINE> <INDENT> print("Trial %d in trial type %s not found."%(ix[0],trial_type)) <NEW_LINE> <DEDENT> <DEDENT> if trial_type.isalpha(): <NEW_LINE> <INDENT> selection += self.phase_by_window_spec(source, [windowSpec[specix]], trial_type+'0', precision=precision) <NEW_LINE> <DEDENT> <DEDENT> return selection | Parameters
----------
source : str
windowSpec : list
trial_type : str | 625941af925a0f43d2549ba5 |
def get_tdar_items_by_site_keyword_objs(self, keyword_objs): <NEW_LINE> <INDENT> output = False <NEW_LINE> keyword_uris = [] <NEW_LINE> if isinstance(keyword_objs, list): <NEW_LINE> <INDENT> for keyword_obj in keyword_objs: <NEW_LINE> <INDENT> if isinstance(keyword_obj, dict): <NEW_LINE> <INDENT> if 'id' in keyword_obj: <NEW_LINE> <INDENT> keyword_uris.append(keyword_obj['id']) <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> <DEDENT> if len(keyword_uris) > 0: <NEW_LINE> <INDENT> output = self.search_by_site_keyword_uris(keyword_uris, True) <NEW_LINE> <DEDENT> return output | gets site information by tdar keyword objects | 625941af3317a56b86939997 |
def display_start_menu(update, context): <NEW_LINE> <INDENT> update.message.reply_text( lernen_menu_message(), reply_markup=lernen_menu(), parse_mode="HTML", ) | Show learning journey articles | 625941afadb09d7d5db6c4c9 |
def decideTheBestTree(test_set,prun_tree_list): <NEW_LINE> <INDENT> correct_rate_max = predictCorrectRate(test_set, prun_tree_list[0]) <NEW_LINE> best_tree = prun_tree_list[0] <NEW_LINE> for i in range(len(prun_tree_list)): <NEW_LINE> <INDENT> correct_rate = predictCorrectRate(test_set, prun_tree_list[i]) <NEW_LINE> if correct_rate > correct_rate_max: <NEW_LINE> <INDENT> correct_rate_max = correct_rate <NEW_LINE> best_tree = prun_tree_list[i] <NEW_LINE> <DEDENT> <DEDENT> print('对于该测试集，最佳剪枝树是：') <NEW_LINE> drawTree(best_tree) <NEW_LINE> return best_tree | 函数功能：找到最优决策树
输入参数：test_set：测试集； prun_tree_list：剪枝树列表
输出参数：对于这个测试集而言最优的决策树 | 625941af925a0f43d2549ba7 |
def test_empty_list(self): <NEW_LINE> <INDENT> response = self.client.get(self.test_link) <NEW_LINE> self.assertEqual(response.status_code, 200) <NEW_LINE> self.assertContains(response, "empty-message") | view has no showstoppers on returning empty list | 625941af6aa9bd52df036ad7 |
def testHistogram(self): <NEW_LINE> <INDENT> self.testslicer.plotHistogram(self.metricdata, title='Mean of random test data', xlabel=None, ylabel='Area (1000s of square degrees)', fignum=None, legendLabel=None, addLegend=False, legendloc='upper left', bins=100, cumulative=False, histRange=None, logScale=False, flipXaxis=False, scale=None) <NEW_LINE> plt.figure() <NEW_LINE> plt.hist(self.metricdata.compressed(), bins=100) <NEW_LINE> plt.title('Histogram straight from metric data') <NEW_LINE> self.testslicer.plotHistogram(self.metricdata2, title='Random test data', xlabel=None, ylabel='Area (1000s of square degrees)', fignum=None, legendLabel=None, addLegend=False, legendloc='upper left', bins=100, cumulative=False, histRange=None, logScale=False, flipXaxis=False, scale=None) | Test plotting the histogram (mean of random data). | 625941af3317a56b8693999a |
def _get_query_string(self, params): <NEW_LINE> <INDENT> pairs = [(self._unicode_safe(k), self._unicode_safe(v)) for k, v in params.iteritems()] <NEW_LINE> pairs.sort() <NEW_LINE> query_string = '&'.join(['%s=%s' % pair for pair in pairs]) <NEW_LINE> return query_string | URL Encode Parameters as query string | 625941af596a8972360897f8 |
def __init__(self, user, skip=None, *args, **kwargs): <NEW_LINE> <INDENT> if skip is None: <NEW_LINE> <INDENT> skip = [] <NEW_LINE> <DEDENT> super(AgentFilterForm, self).__init__(*args, **kwargs) <NEW_LINE> self.fields['related_user'].required = True <NEW_LINE> self.fields['related_user'].label = _("Related user") | Sets allowed values | 625941af046cf37aa974ca80 |
def test_ticket47553_moddn_staging_prod_1(topology): <NEW_LINE> <INDENT> topology.master1.log.info("\n\n######################### MOVE staging -> Prod (1) ######################\n") <NEW_LINE> _bind_normal(topology) <NEW_LINE> old_rdn = "cn=%s1" % NEW_ACCOUNT <NEW_LINE> old_dn = "%s,%s" % (old_rdn, STAGING_DN) <NEW_LINE> new_rdn = old_rdn <NEW_LINE> new_superior = PRODUCTION_DN <NEW_LINE> try: <NEW_LINE> <INDENT> topology.master1.log.info("Try to MODDN %s -> %s,%s" % (old_dn, new_rdn, new_superior)) <NEW_LINE> topology.master1.rename_s(old_dn, new_rdn, newsuperior=new_superior) <NEW_LINE> assert 0 <NEW_LINE> <DEDENT> except AssertionError: <NEW_LINE> <INDENT> topology.master1.log.info("Exception (not really expected exception but that is fine as it fails to rename)") <NEW_LINE> <DEDENT> except Exception as e: <NEW_LINE> <INDENT> topology.master1.log.info("Exception (expected): %s" % type(e).__name__) <NEW_LINE> assert isinstance(e, ldap.INSUFFICIENT_ACCESS) <NEW_LINE> <DEDENT> topology.master1.log.info("\n\n######################### MOVE to substring/ from equality filter ######################\n") <NEW_LINE> _bind_manager(topology) <NEW_LINE> _moddn_aci_staging_to_production(topology, mod_type=ldap.MOD_ADD, target_from=STAGING_DN, target_to=PRODUCTION_PATTERN) <NEW_LINE> _bind_normal(topology) <NEW_LINE> topology.master1.log.info("Try to MODDN %s -> %s,%s" % (old_dn, new_rdn, new_superior)) <NEW_LINE> topology.master1.rename_s(old_dn, new_rdn, newsuperior=new_superior) <NEW_LINE> _bind_manager(topology) <NEW_LINE> _moddn_aci_staging_to_production(topology, mod_type=ldap.MOD_DELETE, target_from=STAGING_DN, target_to=PRODUCTION_PATTERN) <NEW_LINE> _bind_normal(topology) | This test case MOVE entry NEW_ACCOUNT1 from staging to prod
target_to/target_from: substring/equality filter | 625941af6aa9bd52df036ad9 |
def download_artifacts(job_name, local_fname): <NEW_LINE> <INDENT> sm_client = boto3.Session().client('sagemaker') <NEW_LINE> response = sm_client.describe_trial_component(TrialComponentName=job_name) <NEW_LINE> model_artifacts_full_path = response['OutputArtifacts']['SageMaker.ModelArtifact']['Value'] <NEW_LINE> p = re.compile('(?<=s3://).*?/') <NEW_LINE> s = p.search(model_artifacts_full_path) <NEW_LINE> object_name_start = s.span()[1] <NEW_LINE> object_name = model_artifacts_full_path[object_name_start:] <NEW_LINE> bucket_name = s.group()[:-1] <NEW_LINE> s3 = boto3.client('s3') <NEW_LINE> s3.download_file(bucket_name, object_name, local_fname) | Given a trial name in a SageMaker Experiment, extract the model file and download it locally | 625941afd164cc6175782a87 |
def recalc_face_normals(bm, faces): <NEW_LINE> <INDENT> pass | Computes an “outside” normal for the specified input faces.
:param bm: The bmesh to operate on.
:type bm: bmesh.types.BMesh
:param faces: Undocumented.
:type faces: list of (bmesh.types.BMFace) | 625941af3346ee7daa2b2aa1 |
def test_w_refseqs_file(self): <NEW_LINE> <INDENT> inseqs = parse_fasta(self.inseqs1) <NEW_LINE> actual = qiime_blast_seqs(inseqs, refseqs=self.refseqs1) <NEW_LINE> self.assertEqual(len(actual), 5) <NEW_LINE> self.assertEqual(actual['s2_like_seq'][0][0]['SUBJECT ID'], 's2') <NEW_LINE> self.assertEqual(actual['s105'][0][2]['SUBJECT ID'], 's1') | qiime_blast_seqs functions with refseqs file
| 625941af293b9510aa2c2fd3 |
def __stop(self): <NEW_LINE> <INDENT> self._running = False | Stop console loop
| 625941af3317a56b869399a0 |
def __fetch_and_update_regions(self): <NEW_LINE> <INDENT> regions = list( set([row['location'] for row in self.__rows])) <NEW_LINE> for region in regions: <NEW_LINE> <INDENT> get_or_create(db.session, Region, name=region) | Fetches and updates regions table | 625941af6aa9bd52df036ae1 |
def dice_coeff(Q, D): <NEW_LINE> <INDENT> Q, D = set(Q), set(D) <NEW_LINE> try: <NEW_LINE> <INDENT> return 2.0 * len(Q & D) / (len(Q) + len(D)) <NEW_LINE> <DEDENT> except: <NEW_LINE> <INDENT> pass | Similarity | 625941af3317a56b869399a4 |
def parse_module(self, program_text: str, incremental_step: int = 0) -> List[Tuple[str, str, str]]: <NEW_LINE> <INDENT> m = re.search('# cmd: mypy -m ([a-zA-Z0-9_. ]+)$', program_text, flags=re.MULTILINE) <NEW_LINE> if incremental_step > 1: <NEW_LINE> <INDENT> alt_regex = '# cmd{}: mypy -m ([a-zA-Z0-9_. ]+)$'.format(incremental_step) <NEW_LINE> alt_m = re.search(alt_regex, program_text, flags=re.MULTILINE) <NEW_LINE> if alt_m is not None: <NEW_LINE> <INDENT> m = alt_m <NEW_LINE> <DEDENT> <DEDENT> if m: <NEW_LINE> <INDENT> module_names = m.group(1) <NEW_LINE> out = [] <NEW_LINE> search_paths = SearchPaths((test_temp_dir,), (), (), ()) <NEW_LINE> cache = FindModuleCache(search_paths) <NEW_LINE> for module_name in module_names.split(' '): <NEW_LINE> <INDENT> path = cache.find_module(module_name) <NEW_LINE> assert isinstance(path, str), "Can't find ad hoc case file: %s" % module_name <NEW_LINE> with open(path, encoding='utf8') as f: <NEW_LINE> <INDENT> program_text = f.read() <NEW_LINE> <DEDENT> out.append((module_name, path, program_text)) <NEW_LINE> <DEDENT> return out <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return [('__main__', 'main', program_text)] | Return the module and program names for a test case.
Normally, the unit tests will parse the default ('__main__')
module and follow all the imports listed there. You can override
this behavior and instruct the tests to check multiple modules
by using a comment like this in the test case input:
# cmd: mypy -m foo.bar foo.baz
You can also use `# cmdN:` to have a different cmd for incremental
step N (2, 3, ...).
Return a list of tuples (module name, file name, program text). | 625941afd164cc6175782a8c |
def thanks(year=None): <NEW_LINE> <INDENT> nov_first = datetime.date(_year, 11, 1) if not year else datetime.date(int(year), 11, 1) <NEW_LINE> weekday_seq = nov_first.weekday() <NEW_LINE> if weekday_seq > 3: <NEW_LINE> <INDENT> current_day = 32 - weekday_seq <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> current_day = 25 - weekday_seq <NEW_LINE> <DEDENT> return datetime.date(nov_first.year, 11, current_day) | 4rd Thursday in Nov
:param year: int
:return: Thanksgiving Day | 625941af596a897236089804 |
def test_restart_cf4(run_in_tmpdir): <NEW_LINE> <INDENT> op = dummy_operator.DummyOperator() <NEW_LINE> output_dir = "test_restart_cf4" <NEW_LINE> op.output_dir = output_dir <NEW_LINE> dt = [0.75] <NEW_LINE> power = 1.0 <NEW_LINE> openmc.deplete.cf4(op, dt, power, print_out=False) <NEW_LINE> prev_res = openmc.deplete.ResultsList(op.output_dir / "depletion_results.h5") <NEW_LINE> op = dummy_operator.DummyOperator(prev_res) <NEW_LINE> op.output_dir = output_dir <NEW_LINE> openmc.deplete.cf4(op, dt, power, print_out=False) <NEW_LINE> res = openmc.deplete.ResultsList(op.output_dir / "depletion_results.h5") <NEW_LINE> _, y1 = res.get_atoms("1", "1") <NEW_LINE> _, y2 = res.get_atoms("1", "2") <NEW_LINE> s1 = [2.06101629, 1.37783588] <NEW_LINE> s2 = [2.57241318, 2.63731630] <NEW_LINE> assert y1[1] == approx(s1[0]) <NEW_LINE> assert y2[1] == approx(s1[1]) <NEW_LINE> assert y1[3] == approx(s2[0]) <NEW_LINE> assert y2[3] == approx(s2[1]) | Integral regression test of integrator algorithm using CF4. | 625941af046cf37aa974ca8c |
def pipeline(self,processing_col): <NEW_LINE> <INDENT> self.lowercase(processing_col,'lowercase') <NEW_LINE> self.url_removal('lowercase','urlremoval') <NEW_LINE> self.html_tag('urlremoval','html_tag') <NEW_LINE> self.rm_punc('html_tag','rmpunc') <NEW_LINE> self.remove_emoji('rmpunc','rmemoji') <NEW_LINE> self.word_token('rmemoji','tokens') <NEW_LINE> self.lemmatiz('tokens','lemma') <NEW_LINE> self.rm_stopwords('lemma','rmstopwords') <NEW_LINE> self.freq_words('rmstopwords') <NEW_LINE> self.rm_freq_rare_words_('rmstopwords') | This is the default pipeline we can use in most of the text data.
In this first we are lowercasing the text data, after lower case we are removing the url, html tag and punctuations.
Once punctuations are removed, we are removing the emojis. After removal of emojis we are tokenizing it into word tokens, And lemmatizing it.
Once lemma is created we are removing the stop words and after that we are calculating the frequency distribution.
Based on frequency distribution we are making 2 columns - rm_freq_word and rm_rare_word in both of them we are trying to remove frequent word and rare words.
We can further add contract expansion and spell checking based on the project we are doing. | 625941af2c8b7c6e89b35506 |
def display(self): <NEW_LINE> <INDENT> if self.dim == 2: <NEW_LINE> <INDENT> self.image = plt.imshow(self.config) <NEW_LINE> plt.show() | Plot the current spin configuration, if `self.dim == 2`.
| 625941af4a966d76dd550d4c |
def get_function_or_wrapper(self, func, before_change_func, wrapper, is_method): <NEW_LINE> <INDENT> if self.is_forbidden(func): <NEW_LINE> <INDENT> return func <NEW_LINE> <DEDENT> if self.is_decorator(before_change_func): <NEW_LINE> <INDENT> if self.is_method(before_change_func): <NEW_LINE> <INDENT> self.remove(before_change_func) <NEW_LINE> self.add(wrapper, func, is_method=is_method) <NEW_LINE> return wrapper <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> if not is_method: <NEW_LINE> <INDENT> self.remove(before_change_func) <NEW_LINE> self.add(wrapper, func, is_method=is_method) <NEW_LINE> return wrapper <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return before_change_func <NEW_LINE> <DEDENT> <DEDENT> <DEDENT> self.remove(func) <NEW_LINE> self.add(wrapper, func, is_method=is_method) <NEW_LINE> return wrapper | Здесь принимается решение, декорировать функцию или оставить оригинал.
Если декорирование функции ранее было запрещено, вернется оригинал.
Если функция ранее уже была задекорирована, тут надо смотреть на приоритеты. У декоратора класса приоритет ниже, чем у декоратора функций. Если функция ранее была задекорирована через декоратор класса, она передекорируется в любом случае. Если через декоратор функций - то только в том случае, если сейчас ее декорируют не через декоратор класса. | 625941afd7e4931a7ee9dc5d |
def get_nom(self): <NEW_LINE> <INDENT> return self.nom | :return: Retorna el nom del jugador | 625941af5166f23b2e1a4e9b |
def reset_energie(self): <NEW_LINE> <INDENT> self.energie_courante = self.energie_depart | Remet l’énergie courante du personnage à sa valeur de départ. | 625941af097d151d1a222b9f |
def enable_voice(self): <NEW_LINE> <INDENT> self._jarvis.enable_voice = True | Use text to speech for every text passed to jarvis.say() | 625941af7b180e01f3dc454c |
def calcTempInEV(self, expFitCoeffWithVoltUnits): <NEW_LINE> <INDENT> eV=1.60218e-19; <NEW_LINE> q=1.6e-19 <NEW_LINE> return q*expFitCoeffWithVoltUnits/eV | Calulates temperature from langmuir exp fit
Parameters
----------
expFitCoeffWithVoltUnits : float
| 625941afd164cc6175782a8f |
def __init__(self, data, input_dims=None, output_dims=None): <NEW_LINE> <INDENT> if isinstance(data, (list, np.ndarray)): <NEW_LINE> <INDENT> ptm = np.asarray(data, dtype=complex) <NEW_LINE> dout, din = ptm.shape <NEW_LINE> if input_dims: <NEW_LINE> <INDENT> input_dim = np.product(input_dims) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> input_dim = int(np.sqrt(din)) <NEW_LINE> <DEDENT> if output_dims: <NEW_LINE> <INDENT> output_dim = np.product(input_dims) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> output_dim = int(np.sqrt(dout)) <NEW_LINE> <DEDENT> if output_dim**2 != dout or input_dim**2 != din or input_dim != output_dim: <NEW_LINE> <INDENT> raise QiskitError("Invalid shape for PTM matrix.") <NEW_LINE> <DEDENT> <DEDENT> else: <NEW_LINE> <INDENT> if isinstance(data, (QuantumCircuit, Instruction)): <NEW_LINE> <INDENT> data = SuperOp._init_instruction(data) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> data = self._init_transformer(data) <NEW_LINE> <DEDENT> input_dim, output_dim = data.dim <NEW_LINE> rep = getattr(data, '_channel_rep', 'Operator') <NEW_LINE> ptm = _to_ptm(rep, data._data, input_dim, output_dim) <NEW_LINE> if input_dims is None: <NEW_LINE> <INDENT> input_dims = data.input_dims() <NEW_LINE> <DEDENT> if output_dims is None: <NEW_LINE> <INDENT> output_dims = data.output_dims() <NEW_LINE> <DEDENT> <DEDENT> num_qubits = int(np.log2(input_dim)) <NEW_LINE> if 2**num_qubits != input_dim: <NEW_LINE> <INDENT> raise QiskitError("Input is not an n-qubit Pauli transfer matrix.") <NEW_LINE> <DEDENT> input_dims = self._automatic_dims(input_dims, input_dim) <NEW_LINE> output_dims = self._automatic_dims(output_dims, output_dim) <NEW_LINE> super().__init__(ptm, input_dims, output_dims, 'PTM') | Initialize a PTM quantum channel operator.
Args:
data (QuantumCircuit or
Instruction or
BaseOperator or
matrix): data to initialize superoperator.
input_dims (tuple): the input subsystem dimensions.
[Default: None]
output_dims (tuple): the output subsystem dimensions.
[Default: None]
Raises:
QiskitError: if input data is not an N-qubit channel or
cannot be initialized as a PTM.
Additional Information:
If the input or output dimensions are None, they will be
automatically determined from the input data. The PTM
representation is only valid for N-qubit channels. | 625941af8a43f66fc4b53daf |
def set_app_lifetime(self, env, app_lifetime): <NEW_LINE> <INDENT> env.app_lifetime = app_lifetime | sets the lifetime of the application
Input: env: AutomotiveEnvironmentSpec: specification of the Environment
Output: - | 625941af596a897236089808 |
def test_get_trajectory_lengths(self): <NEW_LINE> <INDENT> TF_TEST_MASK = tf.constant(NP_TEST_MASK) <NEW_LINE> TF_TEST_MASK_TF_F64 = tf.cast(TF_TEST_MASK, tf.float64) <NEW_LINE> NP_TEST_MASK_NP_F64 = NP_TEST_MASK.astype(np.float64) <NEW_LINE> ALL_MASKS = [ TF_TEST_MASK, NP_TEST_MASK, TF_TEST_MASK_TF_F64, NP_TEST_MASK_NP_F64 ] <NEW_LINE> for mask in ALL_MASKS: <NEW_LINE> <INDENT> computed_lengths = tbs.get_trajectory_lengths(mask) <NEW_LINE> self.assertTrue(np.allclose(computed_lengths, self.expected_lengths)) | Checks if the length of each trajectory in the batch is correct. | 625941afd7e4931a7ee9dc61 |
def set_undo_callback(self, callback): <NEW_LINE> <INDENT> raise NotImplementedError | Define the callback function that is called whenever an undo operation
is executed.
The callback function receives a single argument that is a text string
that defines the operation. | 625941af925a0f43d2549bb9 |
def get_ip_lb_services(ovh_client): <NEW_LINE> <INDENT> return ovh_client.get('/ip/loadBalancing') | Get all legacy load balancing services
GET /ip/LoadBalancing | 625941af6aa9bd52df036ae9 |
@api.route('/comments/<int:id>/like/', methods=["GET", "POST", "DELETE"]) <NEW_LINE> @auth.login_required <NEW_LINE> def new_comments_id_like(id): <NEW_LINE> <INDENT> comment = Comments.query.get_or_404(id) <NEW_LINE> if request.method == "POST": <NEW_LINE> <INDENT> if comment.liked: <NEW_LINE> <INDENT> return jsonify({ 'error': '你已经点赞过该评论' }) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> comment.user.append(g.current_user) <NEW_LINE> db.session.add(comment) <NEW_LINE> db.session.commit() <NEW_LINE> comment.likes = len(comment.user.all()) <NEW_LINE> db.session.add(comment) <NEW_LINE> db.session.commit() <NEW_LINE> comment = Comments.query.get_or_404(id) <NEW_LINE> return jsonify({ 'likes': comment.likes }), 201 <NEW_LINE> <DEDENT> <DEDENT> elif request.method == "DELETE": <NEW_LINE> <INDENT> if comment.liked: <NEW_LINE> <INDENT> comment.user.remove(g.current_user) <NEW_LINE> db.session.add(comment) <NEW_LINE> db.session.commit() <NEW_LINE> comment.likes = len(comment.user.all()) <NEW_LINE> db.session.add(comment) <NEW_LINE> db.session.commit() <NEW_LINE> comment = Comments.query.get_or_404(id) <NEW_LINE> return jsonify( comment.to_json() ), 200 <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return jsonify({ "error": "你还没有点赞这个评论哦!" }), 403 | 点赞特定id的课程
:param id:
:return: | 625941af3346ee7daa2b2aad |
def timestamp_2_readable(time_stamp): <NEW_LINE> <INDENT> return datetime.fromtimestamp(time_stamp).strftime('%Y-%m-%d %H:%M:%S') | 时间戳转换为可读时间
:param time_stamp: 时间戳，当前时间：time.time()
:return: 可读时间字符串 | 625941b073bcbd0ca4b2bdbd |
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Dataset Card for Python-Text2Code
This dataset supports the EACL paper Text-to-Code Generation with Modality-relative Pre-training
- Repository: https://github.com/huawei-noah/noah-research/tree/master/NLP/text2code_mrpt
- Point of Contact: Fenia Christopoulou, Gerasimos Lampouras
Dataset Description
The data were crawled from existing, public repositories from GitHub before May 2021 and were meant to be used for additional model training for the task of Code Synthesis (i.e. Text-to-Code generation) in Python.
Details
Files that met the following criteria were kept: (a) the file size is under 1MB; (b) the code is Python3 compatible, using Abstract Syntactic Tree (AST) parsing; (c) there are fewer than 100 characters per line on average; (d) and there are fewer than 1,000 characters in any single line.
We applied AST parsing (via Tree-sitter) on the remaining Python files to extract valid functions and
their corresponding docstrings.
Docstrings were used a "problem descriptions" and were separated from the code. Functions without a docstring were discarded.
We replaced new lines, indentation and dedentation with <NEW_LINE>, <INDENT> and <DEDENT>, respectively, to normalise spaces, which effectively reduced the length
of the sequences.
Finally, only instances with a maximum length of 1024 tokens (docstring+code) were kept.
The final dataset contains 23,526,586 text-to-code pairs in Python.
Check the paper for additional details!
Data Fields
Each instance contains 3 fields:
id: Unique ID of each paircode: The python codedocstring: The docstring/problem description associated with this code
Data Splits
There is a single data split in the dataset. We randomly sampled 0.1% of the dataset to serve as validation set.
Citation
BibTeX:
@inproceedings{christopoulou-etal-2024-text,
title = "Text-to-Code Generation with Modality-relative Pre-training",
author = "Christopoulou, Fenia and
Zhang, Guchun and
Lampouras, Gerasimos",
editor = "Graham, Yvette and
Purver, Matthew",
booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = mar,
year = "2024",
address = "St. Julian{'}s, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.eacl-long.72",
pages = "1194--1208"
}
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Number of rows:
23,526,586