text_prompt stringlengths 157 13.1k | code_prompt stringlengths 7 19.8k ⌀ |
|---|---|
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def links(self,**args):
'''
Return Gist URL-Link, Clone-Link and Script-Link to embed
'''
if 'name' in args:
self.gist_name = args['name']
self.gist_id = self.getMyID(self.gist_name)
elif 'id' in args:
self.gist_id = args['id']
else:
raise Exception('Gist Name/ID must be provided')
if self.gis... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def load_forecasts(self):
""" Load neighborhood probability forecasts. """ |
run_date_str = self.run_date.strftime("%Y%m%d")
forecast_file = self.forecast_path + "{0}/{1}_{2}_{3}_consensus_{0}.nc".format(run_date_str,
self.ensemble_name,
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def load_coordinates(self):
""" Loads lat-lon coordinates from a netCDF file. """ |
coord_file = Dataset(self.coordinate_file)
if "lon" in coord_file.variables.keys():
self.coordinates["lon"] = coord_file.variables["lon"][:]
self.coordinates["lat"] = coord_file.variables["lat"][:]
else:
self.coordinates["lon"] = coord_file.variables["XLONG"]... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def evaluate_hourly_forecasts(self):
""" Calculates ROC curves and Reliability scores for each forecast hour. Returns: A pandas DataFrame containing forecast met... |
score_columns = ["Run_Date", "Forecast_Hour", "Ensemble Name", "Model_Name", "Forecast_Variable",
"Neighbor_Radius", "Smoothing_Radius", "Size_Threshold", "ROC", "Reliability"]
all_scores = pd.DataFrame(columns=score_columns)
for h, hour in enumerate(range(self.start_ho... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def evaluate_period_forecasts(self):
""" Evaluates ROC and Reliability scores for forecasts over the full period from start hour to end hour Returns: A pandas Da... |
score_columns = ["Run_Date", "Ensemble Name", "Model_Name", "Forecast_Variable", "Neighbor_Radius",
"Smoothing_Radius", "Size_Threshold", "ROC", "Reliability"]
all_scores = pd.DataFrame(columns=score_columns)
if self.coordinate_file is not None:
coord_mask ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def bootstrap_main(args):
""" Main function explicitly called from the C++ code. Return the main application object. """ |
version_info = sys.version_info
if version_info.major != 3 or version_info.minor < 6:
return None, "python36"
main_fn = load_module_as_package("nionui_app.nionswift")
if main_fn:
return main_fn(["nionui_app.nionswift"] + args, {"pyqt": None}), None
return None, "main" |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def _migrate_library(workspace_dir: pathlib.Path, do_logging: bool=True) -> pathlib.Path: """ Migrate library to latest version. """ |
library_path_11 = workspace_dir / "Nion Swift Workspace.nslib"
library_path_12 = workspace_dir / "Nion Swift Library 12.nslib"
library_path_13 = workspace_dir / "Nion Swift Library 13.nslib"
library_paths = (library_path_11, library_path_12)
library_path_latest = library_path_13
if not os.pa... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def merge_input_csv_forecast_json(input_csv_file, forecast_json_path, condition_models, dist_models):
""" Reads forecasts from json files and merges them with th... |
try:
run_date = input_csv_file[:-4].split("_")[-1]
print(run_date)
ens_member = "_".join(input_csv_file.split("/")[-1][:-4].split("_")[3:-1])
ens_name = input_csv_file.split("/")[-1].split("_")[2]
input_data = pd.read_csv(input_csv_file, index_col="Step_ID")
full_jso... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def mark_data_dirty(self):
""" Called from item to indicate its data or metadata has changed.""" |
self.__cache.set_cached_value_dirty(self.__display_item, self.__cache_property_name)
self.__initialize_cache()
self.__cached_value_dirty = True |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def recompute_if_necessary(self, ui):
"""Recompute the data on a thread, if necessary. If the data has recently been computed, this call will be rescheduled for ... |
self.__initialize_cache()
if self.__cached_value_dirty:
with self.__is_recomputing_lock:
is_recomputing = self.__is_recomputing
self.__is_recomputing = True
if is_recomputing:
pass
else:
# the only way t... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def recompute_data(self, ui):
"""Compute the data associated with this processor. This method is thread safe and may take a long time to return. It should not be... |
self.__initialize_cache()
with self.__recompute_lock:
if self.__cached_value_dirty:
try:
calculated_data = self.get_calculated_data(ui)
except Exception as e:
import traceback
traceback.print_exc()
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def thumbnail_source_for_display_item(self, ui, display_item: DisplayItem.DisplayItem) -> ThumbnailSource: """Returned ThumbnailSource must be closed.""" |
with self.__lock:
thumbnail_source = self.__thumbnail_sources.get(display_item)
if not thumbnail_source:
thumbnail_source = ThumbnailSource(ui, display_item)
self.__thumbnail_sources[display_item] = thumbnail_source
def will_delete(thumbn... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def getMyID(self,gist_name):
'''
Getting gistID of a gist in order to make the workflow
easy and uninterrupted.
'''
r = requests.get(
'%s'%BASE_URL+'/users/%s/gists' % self.user,
headers=self.gist.header
)
if (r.status_code == 200):
r_text = json.loads(r.text)
limit = len(r.json())
for g,... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def close(self):
"""Close the document controller. This method must be called to shut down the document controller. There are several paths by which it can be ca... |
assert self.__closed == False
self.__closed = True
self.finish_periodic() # required to finish periodic operations during tests
# dialogs
for weak_dialog in self.__dialogs:
dialog = weak_dialog()
if dialog:
try:
dialog... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def add_periodic(self, interval: float, listener_fn):
"""Add a listener function and return listener token. Token can be closed or deleted to unlisten.""" |
class PeriodicListener:
def __init__(self, interval: float, listener_fn):
self.interval = interval
self.__listener_fn = listener_fn
# the call function is very performance critical; make it fast by using a property
# instead of a logic... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __update_display_items_model(self, display_items_model: ListModel.FilteredListModel, data_group: typing.Optional[DataGroup.DataGroup], filter_id: typing.Optio... |
with display_items_model.changes(): # change filter and sort together
if data_group is not None:
display_items_model.container = data_group
display_items_model.filter = ListModel.Filter(True)
display_items_model.sort_key = None
displ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def focused_data_item(self) -> typing.Optional[DataItem.DataItem]: """Return the data item with keyboard focus.""" |
return self.__focused_display_item.data_item if self.__focused_display_item else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def selected_display_item(self) -> typing.Optional[DisplayItem.DisplayItem]: """Return the selected display item. The selected display is the display ite that has... |
# first check for the [focused] data browser
display_item = self.focused_display_item
if not display_item:
selected_display_panel = self.selected_display_panel
display_item = selected_display_panel.display_item if selected_display_panel else None
return display_i... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def _get_two_data_sources(self):
"""Get two sensible data sources, which may be the same.""" |
selected_display_items = self.selected_display_items
if len(selected_display_items) < 2:
selected_display_items = list()
display_item = self.selected_display_item
if display_item:
selected_display_items.append(display_item)
if len(selected_dis... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def calculate_origin_and_size(canvas_size, data_shape, image_canvas_mode, image_zoom, image_position) -> typing.Tuple[typing.Any, typing.Any]: """Calculate origin... |
if data_shape is None:
return None, None
if image_canvas_mode == "fill":
data_shape = data_shape
scale_h = float(data_shape[1]) / canvas_size[1]
scale_v = float(data_shape[0]) / canvas_size[0]
if scale_v < scale_h:
image_canvas_size = (canvas_size[0], canvas_... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def auto_migrate_storage_system(*, persistent_storage_system=None, new_persistent_storage_system=None, data_item_uuids=None, deletions: typing.List[uuid.UUID] = N... |
storage_handlers = persistent_storage_system.find_data_items()
ReaderInfo = collections.namedtuple("ReaderInfo", ["properties", "changed_ref", "large_format", "storage_handler", "identifier"])
reader_info_list = list()
for storage_handler in storage_handlers:
try:
large_format = isi... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def from_pypirc(pypi_repository):
""" Load configuration from .pypirc file, cached to only run once """ |
ret = {}
pypirc_locations = PYPIRC_LOCATIONS
for pypirc_path in pypirc_locations:
pypirc_path = os.path.expanduser(pypirc_path)
if os.path.isfile(pypirc_path):
parser = configparser.SafeConfigParser()
parser.read(pypirc_path)
if 'distutils' not in parser.... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def pypirc_temp(index_url):
""" Create a temporary pypirc file for interaction with twine """ |
pypirc_file = tempfile.NamedTemporaryFile(suffix='.pypirc', delete=False)
print(pypirc_file.name)
with open(pypirc_file.name, 'w') as fh:
fh.write(PYPIRC_TEMPLATE.format(index_name=PYPIRC_TEMP_INDEX_NAME, index_url=index_url))
return pypirc_file.name |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_api(version: str, ui_version: str=None) -> API_1: """Get a versioned interface matching the given version and ui_version. version is a string in the form ... |
ui_version = ui_version if ui_version else "~1.0"
return _get_api_with_app(version, ui_version, ApplicationModule.app) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def mask_xdata_with_shape(self, shape: DataAndMetadata.ShapeType) -> DataAndMetadata.DataAndMetadata: """Return the mask created by this graphic as extended data.... |
mask = self._graphic.get_mask(shape)
return DataAndMetadata.DataAndMetadata.from_data(mask) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def data(self, data: numpy.ndarray) -> None: """Set the data. :param data: A numpy ndarray. .. versionadded:: 1.0 Scriptable: Yes """ |
self.__data_item.set_data(numpy.copy(data)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def display_xdata(self) -> DataAndMetadata.DataAndMetadata: """Return the extended data of this data item display. Display data will always be 1d or 2d and either... |
display_data_channel = self.__display_item.display_data_channel
return display_data_channel.get_calculated_display_values(True).display_data_and_metadata |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_dimensional_calibrations(self, dimensional_calibrations: typing.List[CalibrationModule.Calibration]) -> None: """Set the dimensional calibrations. :param ... |
self.__data_item.set_dimensional_calibrations(dimensional_calibrations) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def graphics(self) -> typing.List[Graphic]: """Return the graphics attached to this data item. .. versionadded:: 1.0 Scriptable: Yes """ |
return [Graphic(graphic) for graphic in self.__display_item.graphics] |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def add_point_region(self, y: float, x: float) -> Graphic: """Add a point graphic to the data item. :param x: The x coordinate, in relative units [0.0, 1.0] :para... |
graphic = Graphics.PointGraphic()
graphic.position = Geometry.FloatPoint(y, x)
self.__display_item.add_graphic(graphic)
return Graphic(graphic) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def mask_xdata(self) -> DataAndMetadata.DataAndMetadata: """Return the mask by combining any mask graphics on this data item as extended data. .. versionadded:: 1... |
display_data_channel = self.__display_item.display_data_channel
shape = display_data_channel.display_data_shape
mask = numpy.zeros(shape)
for graphic in self.__display_item.graphics:
if isinstance(graphic, (Graphics.SpotGraphic, Graphics.WedgeGraphic, Graphics.RingGraphic, G... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def data_item(self) -> DataItem: """Return the data item associated with this display panel. .. versionadded:: 1.0 Scriptable: Yes """ |
display_panel = self.__display_panel
if not display_panel:
return None
data_item = display_panel.data_item
return DataItem(data_item) if data_item else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_data_item(self, data_item: DataItem) -> None: """Set the data item associated with this display panel. :param data_item: The :py:class:`nion.swift.Facade.... |
display_panel = self.__display_panel
if display_panel:
display_item = data_item._data_item.container.get_display_item_for_data_item(data_item._data_item) if data_item._data_item.container else None
display_panel.set_display_panel_display_item(display_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def add_data_item(self, data_item: DataItem) -> None: """Add a data item to the group. :param data_item: The :py:class:`nion.swift.Facade.DataItem` object to add.... |
display_item = data_item._data_item.container.get_display_item_for_data_item(data_item._data_item) if data_item._data_item.container else None
if display_item:
self.__data_group.append_display_item(display_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def close(self) -> None: """Close the task. .. versionadded:: 1.0 This method must be called when the task is no longer needed. """ |
self.__data_channel_buffer.stop()
self.__data_channel_buffer.close()
self.__data_channel_buffer = None
if not self.__was_playing:
self.__hardware_source.stop_playing() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def record(self, frame_parameters: dict=None, channels_enabled: typing.List[bool]=None, timeout: float=None) -> typing.List[DataAndMetadata.DataAndMetadata]: """R... |
if frame_parameters:
self.__hardware_source.set_record_frame_parameters(self.__hardware_source.get_frame_parameters_from_dict(frame_parameters))
if channels_enabled is not None:
for channel_index, channel_enabled in enumerate(channels_enabled):
self.__hardware_so... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_record_task(self, frame_parameters: dict=None, channels_enabled: typing.List[bool]=None) -> RecordTask: """Create a record task for this hardware sourc... |
return RecordTask(self.__hardware_source, frame_parameters, channels_enabled) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def grab_next_to_finish(self, timeout: float=None) -> typing.List[DataAndMetadata.DataAndMetadata]: """Grabs the next frame to finish and returns it as data and m... |
self.start_playing()
return self.__hardware_source.get_next_xdatas_to_finish(timeout) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_control_output(self, name: str, value: float, *, options: dict=None) -> None: """Set the value of a control asynchronously. :param name: The name of the c... |
self.__instrument.set_control_output(name, value, options) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_property_as_float(self, name: str) -> float: """Return the value of a float property. :return: The property value (float). Raises exception if property wi... |
return float(self.__instrument.get_property(name)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_property_as_float(self, name: str, value: float) -> None: """Set the value of a float property. :param name: The name of the property (string). :param val... |
self.__instrument.set_property(name, float(value)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def data_items(self) -> typing.List[DataItem]: """Return the list of data items. :return: The list of :py:class:`nion.swift.Facade.DataItem` objects. .. versionad... |
return [DataItem(data_item) for data_item in self.__document_model.data_items] |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def display_items(self) -> typing.List[Display]: """Return the list of display items. :return: The list of :py:class:`nion.swift.Facade.Display` objects. .. versi... |
return [Display(display_item) for display_item in self.__document_model.display_items] |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_source_data_items(self, data_item: DataItem) -> typing.List[DataItem]: """Return the list of data items that are data sources for the data item. :return: ... |
return [DataItem(data_item) for data_item in self._document_model.get_source_data_items(data_item._data_item)] if data_item else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_dependent_data_items(self, data_item: DataItem) -> typing.List[DataItem]: """Return the dependent data items the data item argument. :return: The list of ... |
return [DataItem(data_item) for data_item in self._document_model.get_dependent_data_items(data_item._data_item)] if data_item else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_data_item(self, title: str=None) -> DataItem: """Create an empty data item in the library. :param title: The title of the data item (optional). :return... |
data_item = DataItemModule.DataItem()
data_item.ensure_data_source()
if title is not None:
data_item.title = title
self.__document_model.append_data_item(data_item)
return DataItem(data_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_data_item_from_data(self, data: numpy.ndarray, title: str=None) -> DataItem: """Create a data item in the library from an ndarray. The data for the dat... |
return self.create_data_item_from_data_and_metadata(DataAndMetadata.DataAndMetadata.from_data(data), title) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_data_item_from_data_and_metadata(self, data_and_metadata: DataAndMetadata.DataAndMetadata, title: str=None) -> DataItem: """Create a data item in the l... |
data_item = DataItemModule.new_data_item(data_and_metadata)
if title is not None:
data_item.title = title
self.__document_model.append_data_item(data_item)
return DataItem(data_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def copy_data_item(self, data_item: DataItem) -> DataItem: """Copy a data item. .. versionadded:: 1.0 Scriptable: No """ |
data_item = copy.deepcopy(data_item._data_item)
self.__document_model.append_data_item(data_item)
return DataItem(data_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def snapshot_data_item(self, data_item: DataItem) -> DataItem: """Snapshot a data item. Similar to copy but with a data snapshot. .. versionadded:: 1.0 Scriptable... |
data_item = data_item._data_item.snapshot()
self.__document_model.append_data_item(data_item)
return DataItem(data_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_data_item_by_uuid(self, data_item_uuid: uuid_module.UUID) -> DataItem: """Get the data item with the given UUID. .. versionadded:: 1.0 Status: Provisional... |
data_item = self._document_model.get_data_item_by_uuid(data_item_uuid)
return DataItem(data_item) if data_item else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_graphic_by_uuid(self, graphic_uuid: uuid_module.UUID) -> Graphic: """Get the graphic with the given UUID. .. versionadded:: 1.0 Status: Provisional Script... |
for display_item in self._document_model.display_items:
for graphic in display_item.graphics:
if graphic.uuid == graphic_uuid:
return Graphic(graphic)
return None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def has_library_value(self, key: str) -> bool: """Return whether the library value for the given key exists. Please consult the developer documentation for a list... |
desc = Metadata.session_key_map.get(key)
if desc is not None:
field_id = desc['path'][-1]
return bool(getattr(ApplicationData.get_session_metadata_model(), field_id, None))
return False |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_library_value(self, key: str) -> typing.Any: """Get the library value for the given key. Please consult the developer documentation for a list of valid ke... |
desc = Metadata.session_key_map.get(key)
if desc is not None:
field_id = desc['path'][-1]
return getattr(ApplicationData.get_session_metadata_model(), field_id)
raise KeyError() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_library_value(self, key: str, value: typing.Any) -> None: """Set the library value for the given key. Please consult the developer documentation for a lis... |
desc = Metadata.session_key_map.get(key)
if desc is not None:
field_id = desc['path'][-1]
setattr(ApplicationData.get_session_metadata_model(), field_id, value)
return
raise KeyError() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def delete_library_value(self, key: str) -> None: """Delete the library value for the given key. Please consult the developer documentation for a list of valid ke... |
desc = Metadata.session_key_map.get(key)
if desc is not None:
field_id = desc['path'][-1]
setattr(ApplicationData.get_session_metadata_model(), field_id, None)
return
raise KeyError() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def all_display_panels(self) -> typing.List[DisplayPanel]: """Return the list of display panels currently visible. .. versionadded:: 1.0 Scriptable: Yes """ |
return [DisplayPanel(display_panel) for display_panel in self.__document_controller.workspace_controller.display_panels] |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_display_panel_by_id(self, identifier: str) -> DisplayPanel: """Return display panel with the identifier. .. versionadded:: 1.0 Status: Provisional Scripta... |
display_panel = next(
(display_panel for display_panel in self.__document_controller.workspace_controller.display_panels if
display_panel.identifier.lower() == identifier.lower()), None)
return DisplayPanel(display_panel) if display_panel else None |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def display_data_item(self, data_item: DataItem, source_display_panel=None, source_data_item=None):
"""Display a new data item and gives it keyboard focus. Uses ... |
for display_panel in self.__document_controller.workspace_controller.display_panels:
if display_panel.data_item == data_item._data_item:
display_panel.request_focus()
return DisplayPanel(display_panel)
result_display_panel = self.__document_controller.next_re... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_data_item_from_data(self, data: numpy.ndarray, title: str=None) -> DataItem: """Create a data item in the library from data. .. versionadded:: 1.0 .. d... |
return DataItem(self.__document_controller.add_data(data, title)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_data_item_from_data_and_metadata(self, data_and_metadata: DataAndMetadata.DataAndMetadata, title: str=None) -> DataItem: """Create a data item in the l... |
data_item = DataItemModule.new_data_item(data_and_metadata)
if title is not None:
data_item.title = title
self.__document_controller.document_model.append_data_item(data_item)
return DataItem(data_item) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def document_windows(self) -> typing.List[DocumentWindow]: """Return the document windows. .. versionadded:: 1.0 Scriptable: Yes """ |
return [DocumentWindow(document_controller) for document_controller in self.__application.document_controllers] |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def create_panel(self, panel_delegate):
"""Create a utility panel that can be attached to a window. .. versionadded:: 1.0 Scriptable: No The panel_delegate shoul... |
panel_id = panel_delegate.panel_id
panel_name = panel_delegate.panel_name
panel_positions = getattr(panel_delegate, "panel_positions", ["left", "right"])
panel_position = getattr(panel_delegate, "panel_position", "none")
properties = getattr(panel_delegate, "panel_properties", ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_hardware_source_by_id(self, hardware_source_id: str, version: str):
"""Return the hardware source API matching the hardware_source_id and version. .. ver... |
actual_version = "1.0.0"
if Utility.compare_versions(version, actual_version) > 0:
raise NotImplementedError("Hardware API requested version %s is greater than %s." % (version, actual_version))
hardware_source = HardwareSourceModule.HardwareSourceManager().get_hardware_source_for_ha... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def library(self) -> Library: """Return the library object. .. versionadded:: 1.0 Scriptable: Yes """ |
assert self.__app.document_model
return Library(self.__app.document_model) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def pad_matrix(self, matrix, pad_value=0):
""" Pad a possibly non-square matrix to make it square. :Parameters: matrix : list of lists matrix to pad pad_value : ... |
max_columns = 0
total_rows = len(matrix)
for row in matrix:
max_columns = max(max_columns, len(row))
total_rows = max(max_columns, total_rows)
new_matrix = []
for row in matrix:
row_len = len(row)
new_row = row[:]
if tot... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __step1(self):
""" For each row of the matrix, find the smallest element and subtract it from every element in its row. Go to Step 2. """ |
C = self.C
n = self.n
for i in range(n):
minval = min(self.C[i])
# Find the minimum value for this row and subtract that minimum
# from every element in the row.
for j in range(n):
self.C[i][j] -= minval
return 2 |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __step3(self):
""" Cover each column containing a starred zero. If K columns are covered, the starred zeros describe a complete set of unique assignments. In... |
n = self.n
count = 0
for i in range(n):
for j in range(n):
if self.marked[i][j] == 1:
self.col_covered[j] = True
count += 1
if count >= n:
step = 7 # done
else:
step = 4
return ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __step4(self):
""" Find a noncovered zero and prime it. If there is no starred zero in the row containing this primed zero, Go to Step 5. Otherwise, cover th... |
step = 0
done = False
row = -1
col = -1
star_col = -1
while not done:
(row, col) = self.__find_a_zero()
if row < 0:
done = True
step = 6
else:
self.marked[row][col] = 2
st... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __step6(self):
""" Add the value found in Step 4 to every element of each covered row, and subtract it from every element of each uncovered column. Return to... |
minval = self.__find_smallest()
for i in range(self.n):
for j in range(self.n):
if self.row_covered[i]:
self.C[i][j] += minval
if not self.col_covered[j]:
self.C[i][j] -= minval
return 4 |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __find_smallest(self):
"""Find the smallest uncovered value in the matrix.""" |
minval = sys.maxsize
for i in range(self.n):
for j in range(self.n):
if (not self.row_covered[i]) and (not self.col_covered[j]):
if minval > self.C[i][j]:
minval = self.C[i][j]
return minval |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __find_a_zero(self):
"""Find the first uncovered element with value 0""" |
row = -1
col = -1
i = 0
n = self.n
done = False
while not done:
j = 0
while True:
if (self.C[i][j] == 0) and \
(not self.row_covered[i]) and \
(not self.col_covered[j]):
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __find_star_in_row(self, row):
""" Find the first starred element in the specified row. Returns the column index, or -1 if no starred element was found. """ |
col = -1
for j in range(self.n):
if self.marked[row][j] == 1:
col = j
break
return col |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __find_star_in_col(self, col):
""" Find the first starred element in the specified row. Returns the row index, or -1 if no starred element was found. """ |
row = -1
for i in range(self.n):
if self.marked[i][col] == 1:
row = i
break
return row |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __find_prime_in_row(self, row):
""" Find the first prime element in the specified row. Returns the column index, or -1 if no starred element was found. """ |
col = -1
for j in range(self.n):
if self.marked[row][j] == 2:
col = j
break
return col |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __clear_covers(self):
"""Clear all covered matrix cells""" |
for i in range(self.n):
self.row_covered[i] = False
self.col_covered[i] = False |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def __erase_primes(self):
"""Erase all prime markings""" |
for i in range(self.n):
for j in range(self.n):
if self.marked[i][j] == 2:
self.marked[i][j] = 0 |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def update(self, a, b, c, d):
""" Update contingency table with new values without creating a new object. """ |
self.table.ravel()[:] = [a, b, c, d]
self.N = self.table.sum() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def output_tree_ensemble(tree_ensemble_obj, output_filename, attribute_names=None):
""" Write each decision tree in an ensemble to a file. Parameters tree_ensemb... |
for t, tree in enumerate(tree_ensemble_obj.estimators_):
print("Writing Tree {0:d}".format(t))
out_file = open(output_filename + ".{0:d}.tree", "w")
#out_file.write("Tree {0:d}\n".format(t))
tree_str = print_tree_recursive(tree.tree_, 0, attribute_names)
out_file.write(tree_... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def print_tree_recursive(tree_obj, node_index, attribute_names=None):
""" Recursively writes a string representation of a decision tree object. Parameters tree_o... |
tree_str = ""
if node_index == 0:
tree_str += "{0:d}\n".format(tree_obj.node_count)
if tree_obj.feature[node_index] >= 0:
if attribute_names is None:
attr_val = "{0:d}".format(tree_obj.feature[node_index])
else:
attr_val = attribute_names[tree_obj.feature[nod... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def fitness_vs(self, v):
"""Fitness function in the validation set In classification it uses BER and RSE in regression""" |
base = self._base
if base._classifier:
if base._multiple_outputs:
v.fitness_vs = v._error
# if base._fitness_function == 'macro-F1':
# v.fitness_vs = v._error
# elif base._fitness_function == 'BER':
# v.... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def set_fitness(self, v):
"""Set the fitness to a new node. Returns false in case fitness is not finite""" |
base = self._base
self.fitness(v)
if not np.isfinite(v.fitness):
self.del_error(v)
return False
if base._tr_fraction < 1:
self.fitness_vs(v)
if not np.isfinite(v.fitness_vs):
self.del_error(v)
return False
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def output_sector_csv(self,csv_path,file_dict_key,out_path):
""" Segment forecast tracks to only output data contined within a region in the CONUS, as defined by... |
csv_file = csv_path + "{0}_{1}_{2}_{3}.csv".format(
file_dict_key,
self.ensemble_name,
self.member,
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def clean_dict(d0, clean_item_fn=None):
""" Return a json-clean dict. Will log info message for failures. """ |
clean_item_fn = clean_item_fn if clean_item_fn else clean_item
d = dict()
for key in d0:
cleaned_item = clean_item_fn(d0[key])
if cleaned_item is not None:
d[key] = cleaned_item
return d |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def clean_list(l0, clean_item_fn=None):
""" Return a json-clean list. Will log info message for failures. """ |
clean_item_fn = clean_item_fn if clean_item_fn else clean_item
l = list()
for index, item in enumerate(l0):
cleaned_item = clean_item_fn(item)
l.append(cleaned_item)
return l |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def clean_tuple(t0, clean_item_fn=None):
""" Return a json-clean tuple. Will log info message for failures. """ |
clean_item_fn = clean_item_fn if clean_item_fn else clean_item
l = list()
for index, item in enumerate(t0):
cleaned_item = clean_item_fn(item)
l.append(cleaned_item)
return tuple(l) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def sample_stack_all(count=10, interval=0.1):
"""Sample the stack in a thread and print it at regular intervals.""" |
def print_stack_all(l, ll):
l1 = list()
l1.append("*** STACKTRACE - START ***")
code = []
for threadId, stack in sys._current_frames().items():
sub_code = []
sub_code.append("# ThreadID: %s" % threadId)
for filename, lineno, name, line in traceba... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _eval(self):
"Evaluates a individual using recursion and self._pos as pointer"
pos = self._pos
self._pos += 1
node = self._ind[pos]
if isinstance(node, Function):
args = [self._eval() for x in range(node.nargs)]
node.eval(args)
for x in arg... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def create_random_ind_full(self, depth=0):
"Random individual using full method"
lst = []
self._create_random_ind_full(depth=depth, output=lst)
return lst |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def grow_use_function(self, depth=0):
"Select either function or terminal in grow method"
if depth == 0:
return False
if depth == self._depth:
return True
return np.random.random() < 0.5 |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def create_random_ind_grow(self, depth=0):
"Random individual using grow method"
lst = []
self._depth = depth
self._create_random_ind_grow(depth=depth, output=lst)
return lst |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def create_population(self, popsize=1000, min_depth=2,
max_depth=4,
X=None):
"Creates random population using ramped half-and-half method"
import itertools
args = [x for x in itertools.product(range(min_depth,
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def fitness_vs(self):
"Median Fitness in the validation set"
l = [x.fitness_vs for x in self.models]
return np.median(l) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def graphviz(self, directory, **kwargs):
"Directory to store the graphviz models"
import os
if not os.path.isdir(directory):
os.mkdir(directory)
output = os.path.join(directory, 'evodag-%s')
for k, m in enumerate(self.models):
m.graphviz(output % k, **kwar... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def neighborhood_probability(self, threshold, radius):
""" Calculate a probability based on the number of grid points in an area that exceed a threshold. Args: t... |
weights = disk(radius, dtype=np.uint8)
thresh_data = np.zeros(self.data.shape[1:], dtype=np.uint8)
neighbor_prob = np.zeros(self.data.shape, dtype=np.float32)
for t in np.arange(self.data.shape[0]):
thresh_data[self.data[t] >= threshold] = 1
maximized = fftconvol... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def load_data(self):
""" Loads data from each ensemble member. """ |
for m, member in enumerate(self.members):
mo = ModelOutput(self.ensemble_name, member, self.run_date, self.variable,
self.start_date, self.end_date, self.path, self.map_file, self.single_step)
mo.load_data()
if self.data is None:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def point_consensus(self, consensus_type):
""" Calculate grid-point statistics across ensemble members. Args: consensus_type: mean, std, median, max, or percenti... |
if "mean" in consensus_type:
consensus_data = np.mean(self.data, axis=0)
elif "std" in consensus_type:
consensus_data = np.std(self.data, axis=0)
elif "median" in consensus_type:
consensus_data = np.median(self.data, axis=0)
elif "max" in consensus_ty... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def point_probability(self, threshold):
""" Determine the probability of exceeding a threshold at a grid point based on the ensemble forecasts at that point. Arg... |
point_prob = np.zeros(self.data.shape[1:])
for t in range(self.data.shape[1]):
point_prob[t] = np.where(self.data[:, t] >= threshold, 1.0, 0.0).mean(axis=0)
return EnsembleConsensus(point_prob, "point_probability", self.ensemble_name,
self.run_date, ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def neighborhood_probability(self, threshold, radius, sigmas=None):
""" Hourly probability of exceeding a threshold based on model values within a specified radi... |
if sigmas is None:
sigmas = [0]
weights = disk(radius)
filtered_prob = []
for sigma in sigmas:
filtered_prob.append(EnsembleConsensus(np.zeros(self.data.shape[1:], dtype=np.float32),
"neighbor_prob_r_{0:d}_s_{1:d... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def period_max_neighborhood_probability(self, threshold, radius, sigmas=None):
""" Calculates the neighborhood probability of exceeding a threshold at any time o... |
if sigmas is None:
sigmas = [0]
weights = disk(radius)
neighborhood_prob = np.zeros(self.data.shape[2:], dtype=np.float32)
thresh_data = np.zeros(self.data.shape[2:], dtype=np.uint8)
for m in range(self.data.shape[0]):
thresh_data[self.data[m].max(axis=0)... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.