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def _filter_fields(self, filter_function): fields = [] if self.parent_type: fields.extend(self.parent_type._filter_fields(filter_function)) fields.extend(filter(filter_function, self.fields)) return fields
Utility to iterate through all fields (super types first) of a type. :param filter: A function that takes in a Field object. If it returns True, the field is part of the generated output. If False, it is omitted.
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def submit(self, stanza): body = _encode(**stanza) self.service.post(self.path, body=body) return self
Adds keys to the current configuration stanza as a dictionary of key-value pairs. :param stanza: A dictionary of key-value pairs for the stanza. :type stanza: ``dict`` :return: The :class:`Stanza` object.
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def remove_blocked_work_units(self, work_spec_name, work_unit_names): return self._remove_some_work_units( work_spec_name, work_unit_names, suffix=_BLOCKED)
Remove some work units in the blocked list. If `work_unit_names` is :const:`None` (which must be passed explicitly), all pending work units in `work_spec_name` are removed; otherwise only the specific named work units will be. Note that none of the "remove" functions will restart blocked work units, so if you have called e.g. :meth:`remove_available_work_units` for a predecessor job, you may need to also call this method for its successor. :param str work_spec_name: name of the work spec :param list work_unit_names: names of the work units, or :const:`None` for all in `work_spec_name` :return: number of work units removed
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def _deposit_withdraw(self, type, amount, coinbase_account_id): data = { :type, :amount, :coinbase_account_id } return self._post(, data=data)
`<https://docs.exchange.coinbase.com/#depositwithdraw>`_
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def render_view(view_name, **args): try: root_xml = get_view_root(view_name) return render(root_xml, **args) except CoreError as error: error.add_view_info(ViewInfo(view_name, None)) raise except: info = exc_info() error = ViewError(, ViewInfo(view_name, None)) error.add_cause(info[1]) raise error from info[1]
Process view and return root Node
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def restrict(self, point): items = [f.restrict(point) for f in self._items] return self.__class__(items, self.shape, self.ftype)
Apply the ``restrict`` method to all functions. Returns a new farray.
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def stop(self, stop_I): return pd.read_sql_query("SELECT * FROM stops WHERE stop_I={stop_I}".format(stop_I=stop_I), self.conn)
Get all stop data as a pandas DataFrame for all stops, or an individual stop' Parameters ---------- stop_I : int stop index Returns ------- stop: pandas.DataFrame
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def _check_markers(task_ids, offset=10): shuffle(task_ids) has_errors = False for index in xrange(0, len(task_ids), offset): keys = [ndb.Key(FuriousAsyncMarker, id) for id in task_ids[index:index + offset]] markers = ndb.get_multi(keys) if not all(markers): logging.debug("Not all Asyncs fail? Check the success property on the has_errors = not all((marker.success for marker in markers)) return True, has_errors
Returns a flag for markers being found for the task_ids. If all task ids have markers True will be returned. Otherwise it will return False as soon as a None result is hit.
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def get_differentially_expressed_genes(self, diff_type: str) -> VertexSeq: if diff_type == "up": diff_expr = self.graph.vs.select(up_regulated_eq=True) elif diff_type == "down": diff_expr = self.graph.vs.select(down_regulated_eq=True) else: diff_expr = self.graph.vs.select(diff_expressed_eq=True) return diff_expr
Get the differentially expressed genes based on diff_type. :param str diff_type: Differential expression type chosen by the user; all, down, or up. :return list: A list of differentially expressed genes.
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def stats(self): printDebug("Classes.....: %d" % len(self.classes)) printDebug("Properties..: %d" % len(self.properties))
shotcut to pull out useful info for interactive use
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def create_doc_jar(self, target, open_jar, version): javadoc = self._java_doc(target) scaladoc = self._scala_doc(target) if javadoc or scaladoc: jar_path = self.artifact_path(open_jar, version, suffix=) with self.open_jar(jar_path, overwrite=True, compressed=True) as open_jar: def add_docs(docs): if docs: for basedir, doc_files in docs.items(): for doc_file in doc_files: open_jar.write(os.path.join(basedir, doc_file), doc_file) add_docs(javadoc) add_docs(scaladoc) return jar_path else: return None
Returns a doc jar if either scala or java docs are available for the given target.
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def find_last(fileobj, serial): try: fileobj.seek(-256*256, 2) except IOError: fileobj.seek(0) data = fileobj.read() try: index = data.rindex(b"OggS") except ValueError: raise error("unable to find final Ogg header") bytesobj = cBytesIO(data[index:]) best_page = None try: page = OggPage(bytesobj) except error: pass else: if page.serial == serial: if page.last: return page else: best_page = page else: best_page = None fileobj.seek(0) try: page = OggPage(fileobj) while not page.last: page = OggPage(fileobj) while page.serial != serial: page = OggPage(fileobj) best_page = page return page except error: return best_page except EOFError: return best_page
Find the last page of the stream 'serial'. If the file is not multiplexed this function is fast. If it is, it must read the whole the stream. This finds the last page in the actual file object, or the last page in the stream (with eos set), whichever comes first.
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def _verify_subnet_association(route_table_desc, subnet_id): s route table association route_table_desc the description of a route table, as returned from boto_vpc.describe_route_table subnet_id the subnet id to verify .. versionadded:: 2016.11.0 associationsassociationssubnet_id'] == subnet_id: return True return False
Helper function verify a subnet's route table association route_table_desc the description of a route table, as returned from boto_vpc.describe_route_table subnet_id the subnet id to verify .. versionadded:: 2016.11.0
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def update_fluent_cached_urls(item, dry_run=False): change_report = [] if hasattr(item, ): for translation in item.translations.all(): old_url = translation._cached_url item._update_cached_url(translation) change_report.append( (translation, , old_url, translation._cached_url)) if not dry_run: translation.save() if not dry_run: item._expire_url_caches() if item.is_draft: children = [child for child in item.children.all() if child.is_draft] else: children = [child for child in item.get_draft().children.all() if child.is_published] for child in children: update_fluent_cached_urls(child, dry_run=dry_run) return change_report
Regenerate the cached URLs for an item's translations. This is a fiddly business: we use "hidden" methods instead of the public ones to avoid unnecessary and unwanted slug changes to ensure uniqueness, the logic for which doesn't work with our publishing.
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def get_all(self, name, failobj=None): values = [] name = name.lower() for k, v in self._headers: if k.lower() == name: values.append(self.policy.header_fetch_parse(k, v)) if not values: return failobj return values
Return a list of all the values for the named field. These will be sorted in the order they appeared in the original message, and may contain duplicates. Any fields deleted and re-inserted are always appended to the header list. If no such fields exist, failobj is returned (defaults to None).
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def iteration(self): i = 0 conv = np.inf old_conv = -np.inf conv_list = [] m = self.original if isinstance(self.original, pd.DataFrame): ipfn_method = self.ipfn_df elif isinstance(self.original, np.ndarray): ipfn_method = self.ipfn_np self.original = self.original.astype() else: print() sys.exit(0) while ((i <= self.max_itr and conv > self.conv_rate) and (i <= self.max_itr and abs(conv - old_conv) > self.rate_tolerance)): old_conv = conv m, conv = ipfn_method(m, self.aggregates, self.dimensions, self.weight_col) conv_list.append(conv) i += 1 converged = 1 if i <= self.max_itr: if not conv > self.conv_rate: print() elif not abs(conv - old_conv) > self.rate_tolerance: print() else: print() converged = 0 if self.verbose == 0: return m elif self.verbose == 1: return m, converged elif self.verbose == 2: return m, converged, pd.DataFrame({: range(i), : conv_list}).set_index() else: print() sys.exit(0)
Runs the ipfn algorithm. Automatically detects of working with numpy ndarray or pandas dataframes.
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def content(): table_of_contents = m.Message() message = m.Message() _create_section_header( message, table_of_contents, , tr(), heading_level=1) _create_section_header( message, table_of_contents, , tr(), heading_level=2) message.add(m.Paragraph(definitions.messages.disclaimer())) _create_section_header( message, table_of_contents, , tr(), heading_level=2) bullets = m.BulletedList() for item in definitions.limitations(): bullets.add(item) message.add(bullets) _create_section_header( message, table_of_contents, , tr(), heading_level=1) last_group = None table = None for key, value in list(definitions.concepts.items()): current_group = value[] if current_group != last_group: if last_group is not None: message.add(table) _create_section_header( message, table_of_contents, current_group.replace(, ), current_group, heading_level=2) table = _start_glossary_table(current_group) last_group = current_group row = m.Row() term = value[].replace(, ).title() description = m.Message(value[]) for citation in value[]: if citation[] in [None, ]: continue if citation[] in [None, ]: description.add(m.Paragraph(citation[])) else: description.add(m.Paragraph( m.Link(citation[], citation[]))) row.add(m.Cell(term)) row.add(m.Cell(description)) url = _definition_icon_url(value) if url: row.add(m.Cell(m.Image(url, **MEDIUM_ICON_STYLE))) else: row.add(m.Cell()) table.add(row) ))) table = m.Table(style_class=) row = m.Row() row.add(m.Cell(tr(), header=True)) row.add(m.Cell(tr(), header=True)) table.add(row) for item in html_frame_elements: row = m.Row() row.add(m.Cell(item[])) row.add(m.Cell(item[])) table.add(row) message.add(table) _create_section_header( message, table_of_contents, , tr(), heading_level=1) message.add(developer_help()) full_message = m.Message() style = SECTION_STYLE style[] = header = m.Heading(tr(), **style) full_message.add(header) full_message.add(table_of_contents) full_message.add(message) return full_message
Helper method that returns just the content. This method was added so that the text could be reused in the dock_help module. .. versionadded:: 4.0.0 :returns: A message object without brand element. :rtype: safe.messaging.message.Message
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def patched(attrs, updates): orig = patch(attrs, updates.items()) try: yield orig finally: patch(attrs, orig.items())
A context in which some attributes temporarily have a modified value.
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def add_cnt_64bit(self,oid,value,label=None): self.add_oid_entry(oid,,int(value)%18446744073709551615,label=label)
Short helper to add a 64 bit counter value to the MIB subtree.
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def _write_jpy_config(target_dir=None, install_dir=None): if not target_dir: target_dir = _build_dir() args = [sys.executable, os.path.join(target_dir, ), , jvm_dll_file, , jdk_home_dir, , , , ] if install_dir: args.append() args.append(install_dir) log.info( % (target_dir, install_dir)) return subprocess.call(args)
Write out a well-formed jpyconfig.properties file for easier Java integration in a given location.
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def _new_output_char(self, char): self.text.config(state=tkinter.NORMAL) self.text.insert("end", char) self.text.see("end") self.text.config(state=tkinter.DISABLED)
insert in text field
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def process_upload(photo_list, form, parent_object, user, status=): status += "beginning upload processing. Gathering and normalizing fields....<br>" for upload_file in photo_list: upload_file.name = upload_file.name.lower().replace(, ) upload_name = upload_file.name status += .format(upload_name) if upload_name.endswith() or upload_name.endswith(): status += "Found jpg. Attempting to save... <br>" try: dupe = ArticleImage.objects.get(photo__contains=upload_name, article=parent_object) except ObjectDoesNotExist: dupe = None if not dupe: try: upload = ArticleImage( article=parent_object, photo=upload_file ) upload.save() status += "Saved and uploaded jpg." except Exception as error: status += "Error saving image: {}".format(error) time.sleep(1) return status
Helper function that actually processes and saves the upload(s). Segregated out for readability.
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def get_urls(self): urls = self.get_subfields("856", "u", i1="4", i2="2") return map(lambda x: x.replace("&amp;", "&"), urls)
Content of field ``856u42``. Typically URL pointing to producers homepage. Returns: list: List of URLs defined by producer.
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def set_console(self, console): self.console = console yield from self._hypervisor.send(.format(name=self._name, console=self.console))
Sets the TCP console port. :param console: console port (integer)
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def send_message( self, request: str, response_expected: bool, **kwargs: Any ) -> Response: payload = str(request) + self.delimiter self.socket.send(payload.encode(self.encoding)) response = bytes() decoded = None while True: response += self.socket.recv(1024) decoded = response.decode(self.encoding) if len(decoded) < self.delimiter_length: continue elif decoded[-self.delimiter_length :] == self.delimiter: break assert decoded is not None return Response(decoded[: -self.delimiter_length])
Transport the message to the server and return the response. Args: request: The JSON-RPC request string. response_expected: Whether the request expects a response. Returns: A Response object.
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def switch_off(self, *args): if self.off_check(*args): return self._switch.switch(False) else: return False
Sets the state of the switch to False if off_check() returns True, given the arguments provided in kwargs. :param kwargs: variable length dictionary of key-pair arguments :return: Boolean. Returns True if the operation is successful
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def run_command(command): process = subprocess.Popen( shlex.split(command), stdout=subprocess.PIPE, stderr=subprocess.PIPE, close_fds=True) output, stderr = [stream.decode(sys.getdefaultencoding(), ) for stream in process.communicate()] if process.returncode != 0: raise AirflowConfigException( "Cannot execute {}. Error code is: {}. Output: {}, Stderr: {}" .format(command, process.returncode, output, stderr) ) return output
Runs command and returns stdout
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def eventFilter( self, object, event ): if ( event.type() == event.KeyPress ): if ( event.key() in (Qt.Key_Return, Qt.Key_Enter) ): self.addQuery() return True return False
Filters the object for particular events. :param object | <QObject> event | <QEvent> :return <bool> | consumed
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def show_hydrophobic(self): hydroph = self.plcomplex.hydrophobic_contacts if not len(hydroph.bs_ids) == 0: self.select_by_ids(, hydroph.bs_ids, restrict=self.protname) self.select_by_ids(, hydroph.lig_ids, restrict=self.ligname) for i in hydroph.pairs_ids: cmd.select(, % (i[0], self.protname)) cmd.select(, % (i[1], self.ligname)) cmd.distance(, , ) if self.object_exists(): cmd.set(, 0.5, ) cmd.set(, , ) else: cmd.select(, )
Visualizes hydrophobic contacts.
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def changed(self, message=None, *args): if message is not None: self.logger.debug(, self._repr(), message % args) self.logger.debug(, self._repr()) if self.parent is not None: self.parent.changed() elif isinstance(self, Mutable): super(TrackedObject, self).changed()
Marks the object as changed. If a `parent` attribute is set, the `changed()` method on the parent will be called, propagating the change notification up the chain. The message (if provided) will be debug logged.
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def allreduce(self, x, mesh_axes, reduction_fn_string): if not mesh_axes: return x x = x.to_laid_out_tensor() if reduction_fn_string == "SUM": group_assignment = self._create_group_assignment(mesh_axes) group_size = len(group_assignment[0]) tf_in = x.one_slice dtype = tf_in.dtype if dtype == tf.float32: cast_to_float32 = False elif dtype == tf.bfloat16: cast_to_float32 = ( group_size > self._allreduce_in_bfloat16_max_group_size) else: tf.logging.info("Casting %s to float32 for allreduce" % tf_in.dtype) cast_to_float32 = True if cast_to_float32: tf_in = tf.cast(tf_in, tf.float32) tf_out = tpu_ops.cross_replica_sum(tf_in, group_assignment) if cast_to_float32: tf_out = tf.cast(tf_out, dtype) return self.LaidOutTensor([tf_out]) else: for axis in mesh_axes: x = self.allconcat(x, axis, 0, stack=True) x = self.LaidOutTensor( [mtf.reduction_fn(reduction_fn_string)(x.one_slice, 0)]) return x
Grouped allreduce, (summed across the given dimensions). Args: x: a LaidOutTensor mesh_axes: a list of integers reduction_fn_string: "SUM" Returns: a LaidOutTensor Raises: ValueError: if the reduction is not yet implemented.
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def intersection(self, *args): if type(self.obj[0]) is int: a = self.obj else: a = tuple(self.obj[0]) setobj = set(a) for i, v in enumerate(args): setobj = setobj & set(args[i]) return self._wrap(list(setobj))
Produce an array that contains every item shared between all the passed-in arrays.
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def sample_storage_size(self): try: coll_stats = self.database.command(, ) sample_storage_size = coll_stats[]/1024.0/1024.0 return sample_storage_size except pymongo.errors.OperationFailure: return 0
Get the storage size of the samples storage collection.
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def place_oceans_at_map_borders(world): ocean_border = int(min(30, max(world.width / 5, world.height / 5))) def place_ocean(x, y, i): world.layers[].data[y, x] = \ (world.layers[].data[y, x] * i) / ocean_border for x in range(world.width): for i in range(ocean_border): place_ocean(x, i, i) place_ocean(x, world.height - i - 1, i) for y in range(world.height): for i in range(ocean_border): place_ocean(i, y, i) place_ocean(world.width - i - 1, y, i)
Lower the elevation near the border of the map
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def move(self, source_path, destination_path): self.copy(source_path, destination_path) self.remove(source_path)
Rename/move an object from one GCS location to another.
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def _get_dS2S(self, imt_per): if imt_per == 0: dS2S = 0.05 elif 0 < imt_per < 0.15: dS2S = self._interp_function(-0.15, 0.05, 0.15, 0, imt_per) elif 0.15 <= imt_per < 0.45: dS2S = self._interp_function(0.4, -0.15, 0.45, 0.15, imt_per) elif 0.45 <= imt_per < 3.2: dS2S = 0.4 elif 3.2 <= imt_per < 5: dS2S = self._interp_function(0.08, 0.4, 5, 3.2, imt_per) elif 5 <= imt_per <= 10: dS2S = 0.08 else: dS2S = 0 return dS2S
Table 4 of 2013 report
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def init_environment(): base_path = os.path.abspath(os.path.dirname(__file__)) env_path = .format(base_path) if os.path.exists(env_path): with open(env_path) as f: lines = f.readlines() for line in lines: var = line.strip().split() if len(var) == 2: os.environ[var[0]] = var[1]
Allow variables assigned in .env available using os.environ.get('VAR_NAME')
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def one_thread_per_process(): try: import mkl is_mkl = True except ImportError: is_mkl = False if is_mkl: n_threads = mkl.get_max_threads() mkl.set_num_threads(1) try: yield finally: mkl.set_num_threads(n_threads) else: yield
Return a context manager where only one thread is allocated to a process. This function is intended to be used as a with statement like:: >>> with process_per_thread(): ... do_something() # one thread per process Notes: This function only works when MKL (Intel Math Kernel Library) is installed and used in, for example, NumPy and SciPy. Otherwise this function does nothing.
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def b_operator(self, P): r A, B, Q, R, beta = self.A, self.B, self.Q, self.R, self.beta S1 = Q + beta * dot(B.T, dot(P, B)) S2 = beta * dot(B.T, dot(P, A)) S3 = beta * dot(A.T, dot(P, A)) F = solve(S1, S2) if not self.pure_forecasting else np.zeros( (self.k, self.n)) new_P = R - dot(S2.T, F) + S3 return F, new_P
r""" The B operator, mapping P into .. math:: B(P) := R - \beta^2 A'PB(Q + \beta B'PB)^{-1}B'PA + \beta A'PA and also returning .. math:: F := (Q + \beta B'PB)^{-1} \beta B'PA Parameters ---------- P : array_like(float, ndim=2) A matrix that should be n x n Returns ------- F : array_like(float, ndim=2) The F matrix as defined above new_p : array_like(float, ndim=2) The matrix P after applying the B operator
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def is_ext_pack_usable(self, name): if not isinstance(name, basestring): raise TypeError("name can only be an instance of type basestring") usable = self._call("isExtPackUsable", in_p=[name]) return usable
Check if the given extension pack is loaded and usable. in name of type str The name of the extension pack to check for. return usable of type bool Is the given extension pack loaded and usable.
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def register_widgets(): Page.create_content_type( ApplicationWidget, APPLICATIONS=settings.APPLICATION_CHOICES) for _optgroup, _widgets in six.iteritems(settings.WIDGETS): optgroup = _optgroup if _optgroup != else None for widget in _widgets: kwargs = {: optgroup} if isinstance(widget, six.string_types): try: WidgetCls = get_class_from_string(widget) except: exc_info = sys.exc_info() raise six.reraise(*exc_info) elif isinstance(widget, tuple): try: WidgetCls = get_class_from_string(widget[0]) if len(widget) > 1: kwargs.update(widget[1]) except Exception as e: raise Exception( % (mod, e)) else: WidgetCls = widget Page.create_content_type( WidgetCls, **kwargs)
Register all collected widgets from settings WIDGETS = [('mymodule.models.MyWidget', {'mykwargs': 'mykwarg'})] WIDGETS = ['mymodule.models.MyWidget', MyClass]
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def mkdir(self, req, parent, name, mode): self.reply_err(req, errno.EROFS)
Create a directory Valid replies: reply_entry reply_err
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def addLayer(self,layer,z=-1): if not isinstance(layer,Layer): raise TypeError("layer must be an instance of Layer!") if z==-1: self.layers.append(layer) else: self.layers.insert(z,layer)
Adds a new layer to the stack, optionally at the specified z-value. ``layer`` must be an instance of Layer or subclasses. ``z`` can be used to override the index of the layer in the stack. Defaults to ``-1`` for appending.
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def future(self, rev=None): if rev is not None: self.seek(rev) return WindowDictFutureView(self._future)
Return a Mapping of items after the given revision. Default revision is the last one looked up.
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def get_design_run_results(self, data_view_id, run_uuid): url = routes.get_data_view_design_results(data_view_id, run_uuid) response = self._get(url).json() result = response["data"] return DesignResults( best_materials=result.get("best_material_results"), next_experiments=result.get("next_experiment_results") )
Retrieves the results of an existing designrun :param data_view_id: The ID number of the data view to which the run belongs, as a string :type data_view_id: str :param run_uuid: The UUID of the design run to retrieve results from :type run_uuid: str :return: A :class:`DesignResults` object
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def user_parse(data): user_ = data.get(, {}) yield , data.get() or user_.get() yield , user_.get(, {}).get() first_name, _, last_name = data.get( , {}).get(, ).partition() yield , first_name yield , last_name
Parse information from the provider.
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def save_as_plt(self, fname, pixel_array=None, vmin=None, vmax=None, cmap=None, format=None, origin=None): from matplotlib.backends.backend_agg \ import FigureCanvasAgg as FigureCanvas from matplotlib.figure import Figure from pylab import cm if pixel_array is None: pixel_array = self.numpy if cmap is None: cmap = cm.bone fig = Figure(figsize=pixel_array.shape[::-1], dpi=1, frameon=False) canvas = FigureCanvas(fig) fig.figimage(pixel_array, cmap=cmap, vmin=vmin, vmax=vmax, origin=origin) fig.savefig(fname, dpi=1, format=format) return True
This method saves the image from a numpy array using matplotlib :param fname: Location and name of the image file to be saved. :param pixel_array: Numpy pixel array, i.e. ``numpy()`` return value :param vmin: matplotlib vmin :param vmax: matplotlib vmax :param cmap: matplotlib color map :param format: matplotlib format :param origin: matplotlib origin This method will return True if successful
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def tell(self): if self._shifts: t = self._file.tell() if t == self._shifts[0]: return 0 elif t == self._shifts[-1]: return len(self._shifts) - 1 elif t in self._shifts: return bisect_left(self._shifts, t) else: return bisect_left(self._shifts, t) - 1 raise self._implement_error
:return: number of records processed from the original file
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def identify_phase(T, P, Tm=None, Tb=None, Tc=None, Psat=None): rslgl if Tm and T <= Tm: return elif Tc and T >= Tc: return elif Psat: if P <= Psat: return elif P > Psat: return elif Tb: if 9E4 < P < 1.1E5: if T < Tb: return else: return elif P > 1.1E5 and T <= Tb: return else: return None else: return None
r'''Determines the phase of a one-species chemical system according to basic rules, using whatever information is available. Considers only the phases liquid, solid, and gas; does not consider two-phase scenarios, as should occurs between phase boundaries. * If the melting temperature is known and the temperature is under or equal to it, consider it a solid. * If the critical temperature is known and the temperature is greater or equal to it, consider it a gas. * If the vapor pressure at `T` is known and the pressure is under or equal to it, consider it a gas. If the pressure is greater than the vapor pressure, consider it a liquid. * If the melting temperature, critical temperature, and vapor pressure are not known, attempt to use the boiling point to provide phase information. If the pressure is between 90 kPa and 110 kPa (approximately normal), consider it a liquid if it is under the boiling temperature and a gas if above the boiling temperature. * If the pressure is above 110 kPa and the boiling temperature is known, consider it a liquid if the temperature is under the boiling temperature. * Return None otherwise. Parameters ---------- T : float Temperature, [K] P : float Pressure, [Pa] Tm : float, optional Normal melting temperature, [K] Tb : float, optional Normal boiling point, [K] Tc : float, optional Critical temperature, [K] Psat : float, optional Vapor pressure of the fluid at `T`, [Pa] Returns ------- phase : str Either 's', 'l', 'g', or None if the phase cannot be determined Notes ----- No special attential is paid to any phase transition. For the case where the melting point is not provided, the possibility of the fluid being solid is simply ignored. Examples -------- >>> identify_phase(T=280, P=101325, Tm=273.15, Psat=991) 'l'
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def string(self): r if isinstance(self.expr, TexCmd) and len(self.expr.args) == 1: return self.expr.args[0].value
r"""This is valid if and only if 1. the expression is a :class:`.TexCmd` AND 2. the command has only one argument. :rtype: Union[None,str] >>> from TexSoup import TexSoup >>> soup = TexSoup(r'''\textbf{Hello}''') >>> soup.textbf.string 'Hello' >>> soup.textbf.string = 'Hello World' >>> soup.textbf.string 'Hello World' >>> soup.textbf \textbf{Hello World}
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def reference_index(self, ref_id): try: indexes = range(self.reference_count()) return next(i for i in indexes if self.reference_id(i) == ref_id) except StopIteration as e: raise ReferenceNotFoundError("ID: " + ref_id) from e
Return the first reference with this ID.
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def untrace_class(cls): for name, method in inspect.getmembers(cls, inspect.ismethod): untrace_method(cls, method) for name, function in inspect.getmembers(cls, inspect.isfunction): untrace_method(cls, function) for name, accessor in inspect.getmembers(cls, lambda x: type(x) is property): untrace_property(cls, accessor) set_untraced(cls) return True
Untraces given class. :param cls: Class to untrace. :type cls: object :return: Definition success. :rtype: bool
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def _get_color(self, age): if age == self.tree.age: return self.leaf_color color = self.stem_color tree = self.tree if len(color) == 3: return color diff = [color[i+3]-color[i] for i in range(3)] per_age = [diff[i]/(tree.age-1) for i in range(3)] return tuple([int(color[i]+per_age[i]*age) for i in range(3)])
Get the fill color depending on age. Args: age (int): The age of the branch/es Returns: tuple: (r, g, b)
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def find_ge(self, dt): i = bisect_left(self.dates, dt) if i != len(self.dates): return i raise RightOutOfBound
Building block of all searches. Find the index corresponding to the leftmost value greater or equal to *dt*. If *dt* is greater than the :func:`dynts.TimeSeries.end` a :class:`dynts.exceptions.RightOutOfBound` exception will raise. *dt* must be a python datetime.date instance.
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def get_refinement_options(self): domain = self.get_domain() for upper_value in self.upper: for suc in domain.successors(upper_value): yield suc
Returns possible specializations for the upper values in the taxonomy
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def data(self): if self.detached: return None bio = Membio() if not libcrypto.CMS_verify(self.ptr, None, None, None, bio.bio, Flags.NO_VERIFY): raise CMSError("extract data") return str(bio)
Returns signed data if present in the message
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def set_cpus(self, cpus=0): from multiprocessing import cpu_count max_cpus = cpu_count() if not 0 < cpus < max_cpus: cpus = max_cpus self.add_option("--cpus", default=cpus, type="int", help="Number of CPUs to use, 0=unlimited [default: %default]")
Add --cpus options to specify how many threads to use.
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def xinfo_help(self): fut = self.execute(b, b) return wait_convert(fut, lambda l: b.join(l))
Retrieve help regarding the ``XINFO`` sub-commands
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def lists(self, uid=0, **kwargs): lists = Lists(self.base_uri, self.auth) return self.get_subresource_instances(uid, instance=lists, resource="lists", params=kwargs)
Returns a list of :class:`List` objects (lists which Contact belongs to) and a pager dict. :Example: lists, pager = client.contacts.lists(uid=1901010) :param int uid: The unique id of the Contact to update. Required. :param int page: Fetch specified results page. Default=1 :param int limit: How many results on page. Default=10
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def device_from_request(request): from yacms.conf import settings try: for (device, _) in settings.DEVICE_USER_AGENTS: if device == request.COOKIES["yacms-device"]: return device except KeyError: try: user_agent = request.META["HTTP_USER_AGENT"].lower() except KeyError: pass else: try: user_agent = user_agent.decode("utf-8") for (device, ua_strings) in settings.DEVICE_USER_AGENTS: for ua_string in ua_strings: if ua_string.lower() in user_agent: return device except (AttributeError, UnicodeDecodeError, UnicodeEncodeError): pass return ""
Determine's the device name from the request by first looking for an overridding cookie, and if not found then matching the user agent. Used at both the template level for choosing the template to load and also at the cache level as a cache key prefix.
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def options_response(env): status_headers = StatusAndHeaders(, [ (, ), (, ), ]) response = WbResponse(status_headers) response.add_access_control_headers(env=env) return response
Construct WbResponse for OPTIONS based on the WSGI env dictionary :param dict env: The WSGI environment dictionary :return: The WBResponse for the options request :rtype: WbResponse
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def _read_mode_acopt(self, size, kind): temp = self._read_unpack(size) algo = chksum_opt.get(temp) data = dict( kind=kind, length=size, ac=algo, ) return data
Read Alternate Checksum Request option. Positional arguments: size - int, length of option kind - int, 14 (Alt-Chksum Request) Returns: * dict -- extracted Alternate Checksum Request (CHKSUM-REQ) option Structure of TCP CHKSUM-REQ [RFC 1146][RFC 6247]: +----------+----------+----------+ | Kind=14 | Length=3 | chksum | +----------+----------+----------+ Octets Bits Name Description 0 0 tcp.chksumreq.kind Kind (14) 1 8 tcp.chksumreq.length Length (3) 2 16 tcp.chksumreq.ac Checksum Algorithm
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def is_known_type(self, type_name): type_name = str(type_name) if type_name in self.known_types: return True return False
Check if type is known to the type system. Returns: bool: True if the type is a known instantiated simple type, False otherwise
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def build_verified_certificate_chain(self, received_certificate_chain: List[Certificate]) -> List[Certificate]: if not self._is_certificate_chain_order_valid(received_certificate_chain): raise InvalidCertificateChainOrderError() verified_certificate_chain = [] anchor_cert = None for cert in received_certificate_chain: anchor_cert = self._get_certificate_with_subject(cert.issuer) verified_certificate_chain.append(cert) if anchor_cert: verified_certificate_chain.append(anchor_cert) break if anchor_cert is None: raise AnchorCertificateNotInTrustStoreError() return verified_certificate_chain
Try to figure out the verified chain by finding the anchor/root CA the received chain chains up to in the trust store. This will not clean the certificate chain if additional/invalid certificates were sent and the signatures and fields (notBefore, etc.) are not verified.
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def _multi_call(function, contentkey, *args, **kwargs): position ret = function(*args, **kwargs) position = ret.get() while position: more = function(*args, position=position, **kwargs) ret[contentkey].extend(more[contentkey]) position = more.get() return ret.get(contentkey)
Retrieve full list of values for the contentkey from a boto3 ApiGateway client function that may be paged via 'position'
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def render_search(self, ctx, data): if self.username is None: return translator = self._getViewerPrivateApplication() searchAggregator = translator.getPageComponents().searchAggregator if searchAggregator is None or not searchAggregator.providers(): return return ctx.tag.fillSlots( , translator.linkTo(searchAggregator.storeID))
Render some UI for performing searches, if we know about a search aggregator.
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def event_transition(self, event_cls, event_type, ion_type=None, value=None, annotations=None, depth=None, whence=None): if annotations is None: annotations = self.annotations if annotations is None: annotations = () if not (event_type is IonEventType.CONTAINER_START) and \ annotations and (self.limit - self.queue.position) != 0: raise IonException() if depth is None: depth = self.depth if whence is None: whence = self.whence return Transition( event_cls(event_type, ion_type, value, self.field_name, annotations, depth), whence )
Returns an ion event event_transition that yields to another co-routine. If ``annotations`` is not specified, then the ``annotations`` are the annotations of this context. If ``depth`` is not specified, then the ``depth`` is depth of this context. If ``whence`` is not specified, then ``whence`` is the whence of this context.
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def p_members(self, p): if len(p) == 1: p[0] = list() else: p[1].append(p[2]) p[0] = p[1]
members : | members member VALUE_SEPARATOR | members member
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def top_charts(self): response = self._call(mc_calls.BrowseTopChart) top_charts = response.body return top_charts
Get a listing of the default top charts.
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def get_db_mutations(mut_db_path, gene_list, res_stop_codons): try: drugfile = open(mut_db_path, "r") except: sys.exit("Wrong path: %s"%(mut_db_path)) known_mutations = dict() drug_genes = dict() known_stop_codon = dict() indelflag = False stopcodonflag = False for line in drugfile: if line.startswith(" if "indel" in line.lower(): indelflag = True elif "stop codon" in line.lower(): stopcodonflag = True else: stopcodonflag = False continue if line.strip() == "": continue mutation = [data.strip() for data in line.strip().split("\t")] assert len(mutation) == 9, "mutation overview file (%s) must have 9 columns, %s"%(mut_db_path, mutation) gene_ID = mutation[0] if gene_ID in gene_list: gene_name = mutation[1] no_of_mut = int(mutation[2]) mut_pos = int(mutation[3]) ref_codon = mutation[4] ref_aa = mutation[5] alt_aa = mutation[6].split(",") res_drug = mutation[7].replace("\t", " ") pmid = mutation[8].split(",") if ("*" in alt_aa and res_stop_codons != ) or (res_stop_codons == and stopcodonflag == True): if gene_ID not in known_stop_codon: known_stop_codon[gene_ID] = {"pos": [], "drug": res_drug} known_stop_codon[gene_ID]["pos"].append(mut_pos) drug_lst = res_drug.split(",") for drug in drug_lst: drug = drug.upper() if drug not in drug_genes: drug_genes[drug] = [] if gene_ID not in drug_genes[drug]: drug_genes[drug].append(gene_ID) mut_info = dict() for i in range(len(alt_aa)): try: mut_info[alt_aa[i]] = {"gene_name": gene_name, "drug": res_drug, "pmid": pmid[i]} except IndexError: mut_info[alt_aa[i]] = {"gene_name": gene_name, "drug": res_drug, "pmid": "-"} if no_of_mut != 1: print("More than one mutation is needed, this is not implemented", mutation) if gene_ID not in known_mutations: known_mutations[gene_ID] = {"sub" : dict(), "ins" : dict(), "del" : dict()} if indelflag == False: mutation_type = "sub" else: mutation_type = ref_aa if mut_pos not in known_mutations[gene_ID][mutation_type]: known_mutations[gene_ID][mutation_type][mut_pos] = dict() for aa in alt_aa: known_mutations[gene_ID][mutation_type][mut_pos][aa] = mut_info[aa] drugfile.close() for gene in gene_list: if gene not in known_mutations: known_mutations[gene] = {"sub" : dict(), "ins" : dict(), "del" : dict()} return known_mutations, drug_genes, known_stop_codon
This function opens the file resistenss-overview.txt, and reads the content into a dict of dicts. The dict will contain information about all known mutations given in the database. This dict is returned.
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def com_google_fonts_check_metadata_canonical_filename(font_metadata, canonical_filename, is_variable_font): if is_variable_font: valid_varfont_suffixes = [ ("Roman-VF", "Regular"), ("Italic-VF", "Italic"), ] for valid_suffix, style in valid_varfont_suffixes: if style in canonical_filename: canonical_filename = valid_suffix.join(canonical_filename.split(style)) if canonical_filename != font_metadata.filename: yield FAIL, ("METADATA.pb: filename field (\"{}\")" " does not match " "canonical name \"{}\".".format(font_metadata.filename, canonical_filename)) else: yield PASS, "Filename in METADATA.pb is set canonically."
METADATA.pb: Filename is set canonically?
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def un_camel_case(text): r revtext = text[::-1] pieces = [] while revtext: match = CAMEL_RE.match(revtext) if match: pieces.append(match.group(1)) revtext = revtext[match.end():] else: pieces.append(revtext) revtext = revstr = .join(piece.strip() for piece in pieces if piece.strip()) return revstr[::-1].replace(, )
r""" Splits apart words that are written in CamelCase. Bugs: - Non-ASCII characters are treated as lowercase letters, even if they are actually capital letters. Examples: >>> un_camel_case('1984ZXSpectrumGames') '1984 ZX Spectrum Games' >>> un_camel_case('aaAa aaAaA 0aA AAAa!AAA') 'aa Aa aa Aa A 0a A AA Aa! AAA' >>> un_camel_case('MotörHead') 'Mot\xf6r Head' >>> un_camel_case('MSWindows3.11ForWorkgroups') 'MS Windows 3.11 For Workgroups' This should not significantly affect text that is not camel-cased: >>> un_camel_case('ACM_Computing_Classification_System') 'ACM Computing Classification System' >>> un_camel_case('Anne_Blunt,_15th_Baroness_Wentworth') 'Anne Blunt, 15th Baroness Wentworth' >>> un_camel_case('Hindi-Urdu') 'Hindi-Urdu'
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def get_gravityspy_triggers(tablename, engine=None, **kwargs): from sqlalchemy.engine import create_engine from sqlalchemy.exc import ProgrammingError if engine is None: conn_kw = {} for key in (, , , ): try: conn_kw[key] = kwargs.pop(key) except KeyError: pass engine = create_engine(get_connection_str(**conn_kw)) try: return GravitySpyTable(fetch(engine, tablename, **kwargs)) except ProgrammingError as exc: if % tablename in str(exc): msg = exc.args[0] msg = msg.replace( , % .join(engine.table_names())) exc.args = (msg,) raise
Fetch data into an `GravitySpyTable` Parameters ---------- table : `str`, The name of table you are attempting to receive triggers from. selection other filters you would like to supply underlying reader method for the given format .. note:: For now it will attempt to automatically connect you to a specific DB. In the future, this may be an input argument. Returns ------- table : `GravitySpyTable`
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def count_genomic_region_plot(self): keys = self.snpeff_section_totals[] sorted_keys = sorted(keys, reverse=True, key=keys.get) pkeys = OrderedDict() for k in sorted_keys: pkeys[k] = {: k.replace(, ).title().replace(, ) } pconfig = { : , : , : , : True } return bargraph.plot(self.snpeff_data, pkeys, pconfig)
Generate the SnpEff Counts by Genomic Region plot
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def sync(remote=, branch=): pull(branch, remote) push(branch, remote) print(cyan("Git Synced!"))
git pull and push commit
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def save_files(self, selections) -> None: try: currentpath = self.currentpath selections = selectiontools.Selections(selections) for selection in selections: if selection.name == : continue path = os.path.join(currentpath, selection.name+) selection.save_networkfile(filepath=path) except BaseException: objecttools.augment_excmessage( % selections)
Save the |Selection| objects contained in the given |Selections| instance to separate network files.
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def get_apps_menu(self): menu = {} for model, model_admin in self.admin_site._registry.items(): if hasattr(model_admin, ): if model_admin.app_config.has_menu_permission(obj=self.user): menu.update({ + model_admin.app_config.name: { : model_admin.app_config.verbose_name, : model_admin.app_config.init_menu(), : model_admin.app_config.icon}}) return menu
Temporal code, will change to apps.get_app_configs() for django 1.7 Generate a initial menu list using the AppsConfig registered
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def network_interfaces_list(resource_group, **kwargs): result = {} netconn = __utils__[](, **kwargs) try: nics = __utils__[]( netconn.network_interfaces.list( resource_group_name=resource_group ) ) for nic in nics: result[nic[]] = nic except CloudError as exc: __utils__[](, str(exc), **kwargs) result = {: str(exc)} return result
.. versionadded:: 2019.2.0 List all network interfaces within a resource group. :param resource_group: The resource group name to list network interfaces within. CLI Example: .. code-block:: bash salt-call azurearm_network.network_interfaces_list testgroup
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def _build_crawlid_info(self, master, dict): master[] = 0 master[] = 0 master[] = dict[] master[] = dict[] master[] = dict[] master[] = {} timeout_key = .format(sid=dict[], aid=dict[], cid=dict[]) if self.redis_conn.exists(timeout_key): master[] = self.redis_conn.get(timeout_key) match_string = .format(sid=dict[]) for key in self.redis_conn.scan_iter(match=match_string): domain = key.split(":")[1] sortedDict = self._get_bin(key) for score in sortedDict: for item in sortedDict[score]: if in item: item = item[] if item[] == dict[] and item[] == dict[]: if domain not in master[]: master[][domain] = {} master[][domain][] = 0 master[][domain][] = -9999 master[][domain][] = 9999 master[] = master[] + 1 master[][domain][] = master[][domain][] + 1 if item[] > master[][domain][]: master[][domain][] = item[] if item[] < master[][domain][]: master[][domain][] = item[] master[] = master[] + 1 return master
Builds the crawlid info object @param master: the master dict @param dict: the dict object received @return: the crawlid info object
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def write_message(self, status=messages.INFO, message=None): if not message: message = u"%s saved" % self.object messages.add_message(self.request, status, message) return message
Writes a message to django's messaging framework and returns the written message. :param status: The message status level. Defaults to \ messages.INFO. :param message: The message to write. If not given, \ defaults to appending 'saved' to the unicode representation \ of `self.object`.
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def bitwise_or(self, t): s = self result_interval = list() for u in s._ssplit(): for v in t._ssplit(): w = u.bits if u.is_integer: s_t = StridedInterval._ntz(v.stride) elif v.is_integer: s_t = StridedInterval._ntz(u.stride) else: s_t = min(StridedInterval._ntz(u.stride), StridedInterval._ntz(v.stride)) if u.is_integer and u.lower_bound == 0: new_stride = v.stride elif v.is_integer and v.lower_bound == 0: new_stride = u.stride else: new_stride = 2 ** s_t mask = (1 << s_t) - 1 r = (u.lower_bound & mask) | (v.lower_bound & mask) m = (2 ** w) - 1 low_bound = WarrenMethods.min_or(u.lower_bound & (~mask & m), u.upper_bound & (~mask & m), v.lower_bound & (~mask & m), v.upper_bound & (~mask & m), w) upper_bound = WarrenMethods.max_or(u.lower_bound & (~mask & m), u.upper_bound & (~mask & m), v.lower_bound & (~mask & m), v.upper_bound & (~mask & m), w) if low_bound == upper_bound: new_stride = 0 new_interval = StridedInterval(lower_bound=((low_bound & (~mask & m)) | r), upper_bound=((upper_bound & (~mask & m)) | r), bits=w, stride=new_stride) result_interval.append(new_interval) return StridedInterval.least_upper_bound(*result_interval).normalize()
Binary operation: logical or :param b: The other operand :return: self | b
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def format_latex(self, strng): escape_re = re.compile(r,re.MULTILINE) cmd_name_re = re.compile(r % ESC_MAGIC, re.MULTILINE) cmd_re = re.compile(r % ESC_MAGIC, re.MULTILINE) par_re = re.compile(r,re.MULTILINE) newline_re = re.compile(r) strng = cmd_name_re.sub(r, strng) strng = cmd_re.sub(r,strng) strng = par_re.sub(r,strng) strng = escape_re.sub(r,strng) strng = newline_re.sub(r,strng) return strng
Format a string for latex inclusion.
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def chain_sub_regexes(phrase, *regex_sub_pairs): test ok _k$ootest_ooo for regex, substitution in regex_sub_pairs: if isinstance(regex, basestring): regex = re.compile(regex) phrase = regex.sub(substitution, phrase) return phrase
Allow for a series of regex substitutions to occur chain_sub_regexes('test ok', (' ', '_'), ('k$', 'oo')) # => 'test_ooo'
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def do_write(self): while True: try: written = 0 if hasattr(self.fd, ): written = self.fd.send(self.buffer) else: written = os.write(self.fd.fileno(), self.buffer) self.buffer = self.buffer[written:] if self.close_requested and len(self.buffer) == 0: self.close() return written except EnvironmentError as e: if e.errno not in Stream.ERRNO_RECOVERABLE: raise e
Flushes as much pending data from the internal write buffer as possible.
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def from_cli(opt, length, delta_f, low_frequency_cutoff, strain=None, dyn_range_factor=1, precision=None): f_low = low_frequency_cutoff sample_rate = int((length -1) * 2 * delta_f) try: psd_estimation = opt.psd_estimation is not None except AttributeError: psd_estimation = False exclusive_opts = [opt.psd_model, opt.psd_file, opt.asd_file, psd_estimation] if sum(map(bool, exclusive_opts)) != 1: err_msg = "You must specify exactly one of , " err_msg += ", , " raise ValueError(err_msg) if (opt.psd_model or opt.psd_file or opt.asd_file): if opt.psd_model: psd = from_string(opt.psd_model, length, delta_f, f_low) elif opt.psd_file or opt.asd_file: if opt.asd_file: psd_file_name = opt.asd_file else: psd_file_name = opt.psd_file if psd_file_name.endswith((, )): is_asd_file = bool(opt.asd_file) psd = from_txt(psd_file_name, length, delta_f, f_low, is_asd_file=is_asd_file) elif opt.asd_file: err_msg = "ASD files are only valid as ASCII files (.dat or " err_msg += ".txt). Supplied {}.".format(psd_file_name) elif psd_file_name.endswith((, )): psd = from_xml(psd_file_name, length, delta_f, f_low, ifo_string=opt.psd_file_xml_ifo_string, root_name=opt.psd_file_xml_root_name) kmin = int(low_frequency_cutoff / psd.delta_f) psd[0:kmin] = psd[kmin] psd *= dyn_range_factor ** 2 elif psd_estimation: psd = welch(strain, avg_method=opt.psd_estimation, seg_len=int(opt.psd_segment_length * sample_rate), seg_stride=int(opt.psd_segment_stride * sample_rate), num_segments=opt.psd_num_segments, require_exact_data_fit=False) if delta_f != psd.delta_f: psd = interpolate(psd, delta_f) else: if opt.psd_inverse_length: psd = inverse_spectrum_truncation(psd, int(opt.psd_inverse_length * sample_rate), low_frequency_cutoff=f_low) if hasattr(opt, ) and opt.psd_output: (psd.astype(float64) / (dyn_range_factor ** 2)).save(opt.psd_output) if precision is None: return psd elif precision == : return psd.astype(float32) elif precision == : return psd.astype(float64) else: err_msg = "If provided the precision kwarg must be either " err_msg += "or . You provided %s." %(precision) raise ValueError(err_msg)
Parses the CLI options related to the noise PSD and returns a FrequencySeries with the corresponding PSD. If necessary, the PSD is linearly interpolated to achieve the resolution specified in the CLI. Parameters ---------- opt : object Result of parsing the CLI with OptionParser, or any object with the required attributes (psd_model, psd_file, asd_file, psd_estimation, psd_segment_length, psd_segment_stride, psd_inverse_length, psd_output). length : int The length in samples of the output PSD. delta_f : float The frequency step of the output PSD. low_frequency_cutoff: float The low frequncy cutoff to use when calculating the PSD. strain : {None, TimeSeries} Time series containing the data from which the PSD should be measured, when psd_estimation is in use. dyn_range_factor : {1, float} For PSDs taken from models or text files, if `dyn_range_factor` is not None, then the PSD is multiplied by `dyn_range_factor` ** 2. precision : str, choices (None,'single','double') If not specified, or specified as None, the precision of the returned PSD will match the precision of the data, if measuring a PSD, or will match the default precision of the model if using an analytical PSD. If 'single' the PSD will be converted to float32, if not already in that precision. If 'double' the PSD will be converted to float64, if not already in that precision. Returns ------- psd : FrequencySeries The frequency series containing the PSD.
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def reboot_adb_server(): _reboot_count = 0 _max_retry = 1 def _reboot(): nonlocal _reboot_count if _reboot_count >= _max_retry: raise RuntimeError(.format(_max_retry)) _reboot_count += 1 return_code = subprocess.call([, ], stdout=subprocess.DEVNULL) if bool(return_code): warnings.warn() raise EnvironmentError() return _reboot
execute 'adb devices' to start adb server
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def _square_batch_bcbio_variation(data, region, bam_files, vrn_files, out_file, todo="square"): ref_file = tz.get_in(("reference", "fasta", "base"), data) cores = tz.get_in(("config", "algorithm", "num_cores"), data, 1) resources = config_utils.get_resources("bcbio-variation-recall", data["config"]) memcores = int(math.ceil(float(cores) / 5.0)) jvm_opts = config_utils.adjust_opts(resources.get("jvm_opts", ["-Xms250m", "-Xmx2g"]), {"algorithm": {"memory_adjust": {"direction": "increase", "magnitude": memcores}}}) input_file = "%s-inputs.txt" % os.path.splitext(out_file)[0] with open(input_file, "w") as out_handle: out_handle.write("\n".join(sorted(list(set(vrn_files)))) + "\n") if todo == "square": out_handle.write("\n".join(sorted(list(set(bam_files)))) + "\n") variantcaller = tz.get_in(("config", "algorithm", "jointcaller"), data).replace("-joint", "") cmd = ["bcbio-variation-recall", todo] + jvm_opts + broad.get_default_jvm_opts() + \ ["-c", cores, "-r", bamprep.region_to_gatk(region)] if todo == "square": cmd += ["--caller", variantcaller] cmd += [out_file, ref_file, input_file] bcbio_env = utils.get_bcbio_env() cmd = " ".join(str(x) for x in cmd) do.run(cmd, "%s in region: %s" % (cmd, bamprep.region_to_gatk(region)), env=bcbio_env) return out_file
Run squaring or merging analysis using bcbio.variation.recall.
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def paste(self): try: t = pygame.scrap.get(SCRAP_TEXT) if t: self.insert(t) return True except: return False
Insert text from the clipboard at the cursor.
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def inall_cmd(argv): envs = lsenvs() errors = False for env in envs: print("\n%s:" % env) try: inve(env, *argv) except CalledProcessError as e: errors = True err(e) sys.exit(errors)
Run a command in each virtualenv.
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def log_error(self, msg, *args): if self._logger is not None: self._logger.error(msg, *args) else: print(msg % args)
Log an error or print in stdout if no logger.
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def program_rtr_nwk_next_hop(self, rout_id, next_hop, cidr): namespace = self.find_rtr_namespace(rout_id) if namespace is None: LOG.error("Unable to find namespace for router %s", rout_id) return False args = [, , , cidr, , next_hop] ret = self.program_rtr(args, rout_id, namespace=namespace) if not ret: LOG.error("Program router returned error for %s", rout_id) return False return True
Program the next hop for all networks of a tenant.
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def to_html(sample, stats_object): n_obs = stats_object[][] value_formatters = formatters.value_formatters row_formatters = formatters.row_formatters if not isinstance(sample, pd.DataFrame): raise TypeError("sample must be of type pandas.DataFrame") if not isinstance(stats_object, dict): raise TypeError("stats_object must be of type dict. Did you generate this using the pandas_profiling.describe() function?") if not set({, , , }).issubset(set(stats_object.keys())): raise TypeError( "stats_object badly formatted. Did you generate this using the pandas_profiling.describe() function?") def fmt(value, name): if pd.isnull(value): return "" if name in value_formatters: return value_formatters[name](value) elif isinstance(value, float): return value_formatters[formatters.DEFAULT_FLOAT_FORMATTER](value) else: try: return unicode(value) except NameError: return str(value) def _format_row(freq, label, max_freq, row_template, n, extra_class=): if max_freq != 0: width = int(freq / max_freq * 99) + 1 else: width = 1 if width > 20: label_in_bar = freq label_after_bar = "" else: label_in_bar = "&nbsp;" label_after_bar = freq return row_template.render(label=label, width=width, count=freq, percentage=.format(freq / n * 100), extra_class=extra_class, label_in_bar=label_in_bar, label_after_bar=label_after_bar) def freq_table(freqtable, n, table_template, row_template, max_number_to_print, nb_col=6): freq_rows_html = u if max_number_to_print > n: max_number_to_print=n if max_number_to_print < len(freqtable): freq_other = sum(freqtable.iloc[max_number_to_print:]) min_freq = freqtable.values[max_number_to_print] else: freq_other = 0 min_freq = 0 freq_missing = n - sum(freqtable) max_freq = max(freqtable.values[0], freq_other, freq_missing) for label, freq in six.iteritems(freqtable.iloc[0:max_number_to_print]): freq_rows_html += _format_row(freq, label, max_freq, row_template, n) if freq_other > min_freq: freq_rows_html += _format_row(freq_other, "Other values (%s)" % (freqtable.count() - max_number_to_print), max_freq, row_template, n, extra_class=) if freq_missing > min_freq: freq_rows_html += _format_row(freq_missing, "(Missing)", max_freq, row_template, n, extra_class=) return table_template.render(rows=freq_rows_html, varid=hash(idx), nb_col=nb_col) def extreme_obs_table(freqtable, table_template, row_template, number_to_print, n, ascending = True):
Generate a HTML report from summary statistics and a given sample. Parameters ---------- sample : DataFrame the sample you want to print stats_object : dict Summary statistics. Should be generated with an appropriate describe() function Returns ------- str containing profile report in HTML format Notes ----- * This function as to be refactored since it's huge and it contains inner functions
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def get_maya_envpath(self): opj = os.path.join ml = self.get_maya_location() mb = self.get_maya_bin() msp = self.get_maya_sitepackage_dir() pyzip = opj(mb, "python27.zip") pydir = opj(ml, "Python") pydll = opj(pydir, "DLLs") pylib = opj(pydir, "lib") pyplat = opj(pylib, "plat-win") pytk = opj(pylib, "lib-tk") path = os.pathsep.join((pyzip, pydll, pylib, pyplat, pytk, mb, pydir, msp)) return path
Return the PYTHONPATH neccessary for running mayapy If you start native mayapy, it will setup these paths. You might want to prepend this to your path if running from an external intepreter. :returns: the PYTHONPATH that is used for running mayapy :rtype: str :raises: None
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def reciprocal_space(space, axes=None, halfcomplex=False, shift=True, **kwargs): if not isinstance(space, DiscreteLp): raise TypeError( .format(space)) if axes is None: axes = tuple(range(space.ndim)) axes = normalized_axes_tuple(axes, space.ndim) if not all(space.is_uniform_byaxis[axis] for axis in axes): raise ValueError( ) if halfcomplex and space.field != RealNumbers(): raise ValueError( ) exponent = kwargs.pop(, None) if exponent is None: exponent = conj_exponent(space.exponent) dtype = kwargs.pop(, None) if dtype is None: dtype = complex_dtype(space.dtype) else: if not is_complex_floating_dtype(dtype): raise ValueError( .format(dtype_repr(dtype))) impl = kwargs.pop(, ) recip_grid = reciprocal_grid(space.grid, shift=shift, halfcomplex=halfcomplex, axes=axes) non_axes = [i for i in range(space.ndim) if i not in axes] min_pt = {i: space.min_pt[i] for i in non_axes} max_pt = {i: space.max_pt[i] for i in non_axes} if halfcomplex: max_pt[axes[-1]] = recip_grid.max_pt[axes[-1]] part = uniform_partition_fromgrid(recip_grid, min_pt, max_pt) axis_labels = list(space.axis_labels) for i in axes: label = axis_labels[i].replace(, ) axis_labels[i] = .format(label) recip_spc = uniform_discr_frompartition(part, exponent=exponent, dtype=dtype, impl=impl, axis_labels=axis_labels) return recip_spc
Return the range of the Fourier transform on ``space``. Parameters ---------- space : `DiscreteLp` Real space whose reciprocal is calculated. It must be uniformly discretized. axes : sequence of ints, optional Dimensions along which the Fourier transform is taken. Default: all axes halfcomplex : bool, optional If ``True``, take only the negative frequency part along the last axis for. For ``False``, use the full frequency space. This option can only be used if ``space`` is a space of real-valued functions. shift : bool or sequence of bools, optional If ``True``, the reciprocal grid is shifted by half a stride in the negative direction. With a boolean sequence, this option is applied separately to each axis. If a sequence is provided, it must have the same length as ``axes`` if supplied. Note that this must be set to ``True`` in the halved axis in half-complex transforms. Default: ``True`` impl : string, optional Implementation back-end for the created space. Default: ``'numpy'`` exponent : float, optional Create a space with this exponent. By default, the conjugate exponent ``q = p / (p - 1)`` of the exponent of ``space`` is used, where ``q = inf`` for ``p = 1`` and vice versa. dtype : optional Complex data type of the created space. By default, the complex counterpart of ``space.dtype`` is used. Returns ------- rspace : `DiscreteLp` Reciprocal of the input ``space``. If ``halfcomplex=True``, the upper end of the domain (where the half space ends) is chosen to coincide with the grid node.
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def handle_get_reseller(self, req): if not self.is_reseller_admin(req): return self.denied_response(req) listing = [] marker = while True: path = % (quote(self.auth_account), quote(marker)) resp = self.make_pre_authed_request( req.environ, , path).get_response(self.app) if resp.status_int // 100 != 2: raise Exception( % (path, resp.status)) sublisting = json.loads(resp.body) if not sublisting: break for container in sublisting: if container[][0] != : listing.append({: container[]}) marker = sublisting[-1][].encode() return Response(body=json.dumps({: listing}), content_type=CONTENT_TYPE_JSON)
Handles the GET v2 call for getting general reseller information (currently just a list of accounts). Can only be called by a .reseller_admin. On success, a JSON dictionary will be returned with a single `accounts` key whose value is list of dicts. Each dict represents an account and currently only contains the single key `name`. For example:: {"accounts": [{"name": "reseller"}, {"name": "test"}, {"name": "test2"}]} :param req: The swob.Request to process. :returns: swob.Response, 2xx on success with a JSON dictionary as explained above.
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def post_load(fn=None, pass_many=False, pass_original=False): return set_hook(fn, (POST_LOAD, pass_many), pass_original=pass_original)
Register a method to invoke after deserializing an object. The method receives the deserialized data and returns the processed data. By default, receives a single datum at a time, transparently handling the ``many`` argument passed to the Schema. If ``pass_many=True``, the raw data (which may be a collection) and the value for ``many`` is passed. If ``pass_original=True``, the original data (before deserializing) will be passed as an additional argument to the method.
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def get_commands(): commands = dict((name, ) for name in find_commands(__path__[0])) if not settings.configured: return commands for app_config in reversed(list(apps.get_app_configs())): path = os.path.join(app_config.path, ) commands.update(dict((name, app_config.name) for name in find_commands(path))) return commands
Returns a dictionary mapping command names to their callback applications. This works by looking for a management.commands package in django.core, and in each installed application -- if a commands package exists, all commands in that package are registered. Core commands are always included. If a settings module has been specified, user-defined commands will also be included. The dictionary is in the format {command_name: app_name}. Key-value pairs from this dictionary can then be used in calls to load_command_class(app_name, command_name) If a specific version of a command must be loaded (e.g., with the startapp command), the instantiated module can be placed in the dictionary in place of the application name. The dictionary is cached on the first call and reused on subsequent calls.
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def read_transport_message(self, origin, message_type, timeout=15): return self.event_handler.wait_for_event((_EventType.Transport, origin, message_type), timeout=timeout)
Blocking read of a transport message that does not indicate a message from the Pebble. Will block until a message is received, or it times out. .. warning:: Avoid calling this method from an endpoint callback; doing so is likely to lead to deadlock. :param origin: The type of :class:`.MessageTarget` that triggers the message. :param message_type: The class of the message to read from the transport. :param timeout: The maximum time to wait before raising :exc:`.TimeoutError`. :return: The object read from the transport; of the same type as passed to ``message_type``.
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def add_dependency(self, depend): try: self._add_child(self.depends, self.depends_set, depend) except TypeError as e: e = e.args[0] if SCons.Util.is_List(e): s = list(map(str, e)) else: s = str(e) raise SCons.Errors.UserError("attempted to add a non-Node dependency to %s:\n\t%s is a %s, not a Node" % (str(self), s, type(e)))
Adds dependencies.
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def detach(self, force=False): instance_id = None if self.attach_data: instance_id = self.attach_data.instance_id device = None if self.attach_data: device = self.attach_data.device return self.connection.detach_volume(self.id, instance_id, device, force)
Detach this EBS volume from an EC2 instance. :type force: bool :param force: Forces detachment if the previous detachment attempt did not occur cleanly. This option can lead to data loss or a corrupted file system. Use this option only as a last resort to detach a volume from a failed instance. The instance will not have an opportunity to flush file system caches nor file system meta data. If you use this option, you must perform file system check and repair procedures. :rtype: bool :return: True if successful