Processing Tasks

Plugin tasks related to the scenario analysis

ScenarioAnalysisTask

ScenarioAnalysisTask(analysis_scenario_name, analysis_scenario_description, analysis_activities, analysis_priority_layers_groups, analysis_extent, scenario)

Bases: QgsTask

Prepares and runs the scenario analysis

Source code in src/cplus_plugin/tasks.py

def __init__(
    self,
    analysis_scenario_name,
    analysis_scenario_description,
    analysis_activities,
    analysis_priority_layers_groups,
    analysis_extent,
    scenario,
):
    super().__init__()
    self.analysis_scenario_name = analysis_scenario_name
    self.analysis_scenario_description = analysis_scenario_description

    self.analysis_activities = analysis_activities
    self.analysis_priority_layers_groups = analysis_priority_layers_groups
    self.analysis_extent = analysis_extent
    self.analysis_extent_string = None

    self.analysis_weighted_activities = []
    self.scenario_result = None
    self.scenario_directory = None

    self.success = True
    self.output = None
    self.error = None
    self.status_message = None

    self.info_message = None

    self.processing_cancelled = False
    self.feedback = QgsProcessingFeedback()
    self.processing_context = QgsProcessingContext()

    self.scenario = scenario

align_extent

align_extent(raster_layer, target_extent)

Snaps the passed extent to the activities pathway layer pixel bounds

Parameters:

Name	Type	Description	Default
raster_layer	QgsRasterLayer	The target layer that the passed extent will be aligned with	required
target_extent	QgsRectangle	Spatial extent that will be used a target extent when doing alignment.	required

Source code in src/cplus_plugin/tasks.py

def align_extent(self, raster_layer, target_extent):
    """Snaps the passed extent to the activities pathway layer pixel bounds

    :param raster_layer: The target layer that the passed extent will be
    aligned with
    :type raster_layer: QgsRasterLayer

    :param target_extent: Spatial extent that will be used a target extent when
    doing alignment.
    :type target_extent: QgsRectangle
    """

    try:
        raster_extent = raster_layer.extent()

        x_res = raster_layer.rasterUnitsPerPixelX()
        y_res = raster_layer.rasterUnitsPerPixelY()

        left = raster_extent.xMinimum() + x_res * math.floor(
            (target_extent.xMinimum() - raster_extent.xMinimum()) / x_res
        )
        right = raster_extent.xMinimum() + x_res * math.ceil(
            (target_extent.xMaximum() - raster_extent.xMinimum()) / x_res
        )
        bottom = raster_extent.yMinimum() + y_res * math.floor(
            (target_extent.yMinimum() - raster_extent.yMinimum()) / y_res
        )
        top = raster_extent.yMaximum() - y_res * math.floor(
            (raster_extent.yMaximum() - target_extent.yMaximum()) / y_res
        )

        return QgsRectangle(left, bottom, right, top)

    except Exception as e:
        self.log_message(
            tr(
                f"Problem snapping area of "
                f"interest extent, using the original extent,"
                f"{str(e)}"
            )
        )

    return target_extent

cancel_task

cancel_task(exception=None)

Cancel current task.

Parameters:

Name	Type	Description	Default
exception	Any, optional	Exception if stopped with error, defaults to None	None

Source code in src/cplus_plugin/tasks.py

def cancel_task(self, exception=None):
    """Cancel current task.

    :param exception: Exception if stopped with error, defaults to None
    :type exception: Any, optional
    """
    self.error = exception
    self.cancel()

finished

finished(result)

Calls the handler responsible for doing post analysis workflow.

Parameters:

Name	Type	Description	Default
result	bool	Whether the run() operation finished successfully	required

Source code in src/cplus_plugin/tasks.py

def finished(self, result: bool):
    """Calls the handler responsible for doing post analysis workflow.

    :param result: Whether the run() operation finished successfully
    :type result: bool
    """
    if result:
        self.log_message("Finished from the main task \n")
    else:
        self.log_message(f"Error from task scenario task {self.error}")

get_activity

get_activity(activity_uuid)

Gets an activity object matching the given unique identifier.

Parameters:

Name	Type	Description	Default
activity_uuid	str	Unique identifier of the activity object.	required

Returns:

Type	Description
Activity	Returns the activity object matching the given identifier else None if not found.

Source code in src/cplus_plugin/tasks.py

def get_activity(self, activity_uuid) -> typing.Union[Activity, None]:
    """Gets an activity object matching the given unique
    identifier.

    :param activity_uuid: Unique identifier of the
    activity object.
    :type activity_uuid: str

    :returns: Returns the activity object matching the given
    identifier else None if not found.
    :rtype: Activity
    """
    return settings_manager.get_activity(activity_uuid)

get_masking_layers

get_masking_layers()

Gets all the masking layers.

Returns:

Type	Description
list	List of masking layer paths

Source code in src/cplus_plugin/tasks.py

def get_masking_layers(self) -> typing.List:
    """Gets all the masking layers.

    :return: List of masking layer paths
    :rtype: list
    """
    masking_layers_paths = self.get_settings_value(
        Settings.MASK_LAYERS_PATHS, default=None
    )
    masking_layers = masking_layers_paths.split(",") if masking_layers_paths else []
    masking_layers.remove("") if "" in masking_layers else None
    return masking_layers

get_priority_layer

get_priority_layer(identifier)

Retrieves the priority layer that matches the passed identifier.

Parameters:

Name	Type	Description	Default
identifier	uuid.UUID	Priority layers identifier	required

Returns:

Type	Description
dict	Priority layer dict

Source code in src/cplus_plugin/tasks.py

def get_priority_layer(self, identifier) -> typing.Dict:
    """Retrieves the priority layer that matches the passed identifier.

    :param identifier: Priority layers identifier
    :type identifier: uuid.UUID

    :returns: Priority layer dict
    :rtype: dict
    """
    return settings_manager.get_priority_layer(identifier)

get_priority_layers

get_priority_layers()

Gets all the available priority layers in the plugin.

Returns:

Type	Description
list	Priority layers list

Source code in src/cplus_plugin/tasks.py

def get_priority_layers(self) -> typing.List:
    """Gets all the available priority layers in the plugin.

    :returns: Priority layers list
    :rtype: list
    """
    return settings_manager.get_priority_layers()

get_scenario_directory

get_scenario_directory()

Generate scenario directory for current task.

Returns:

Type	Description
str	Path to scenario directory

Source code in src/cplus_plugin/tasks.py

def get_scenario_directory(self) -> str:
    """Generate scenario directory for current task.

    :return: Path to scenario directory
    :rtype: str
    """
    base_dir = self.get_settings_value(Settings.BASE_DIR)
    return os.path.join(
        f"{base_dir}",
        "scenario_" f'{datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S")}',
    )

get_settings_value

get_settings_value(name, default=None, setting_type=None)

Gets value of the setting with the passed name.

Parameters:

Name	Type	Description	Default
name	str	Name of setting key	required
default	Any	Default value returned when the setting key does not exist	None
setting_type	Any	Type of the store setting	None

Returns:

Type	Description
Any	Value of the setting

Source code in src/cplus_plugin/tasks.py

def get_settings_value(self, name: str, default=None, setting_type=None):
    """Gets value of the setting with the passed name.

    :param name: Name of setting key
    :type name: str

    :param default: Default value returned when the setting key does not exist
    :type default: Any

    :param setting_type: Type of the store setting
    :type setting_type: Any

    :returns: Value of the setting
    :rtype: Any
    """
    return settings_manager.get_value(name, default, setting_type)

layer_extent

layer_extent(extent)

Creates a new vector layer contains has a feature with geometry matching an extent parameter.

Parameters:

Name	Type	Description	Default
extent	str	Extent parameter	required

Returns:

Type	Description
QgsVectorLayer	Vector layer

Source code in src/cplus_plugin/tasks.py

def layer_extent(self, extent):
    """Creates a new vector layer contains has a
    feature with geometry matching an extent parameter.

    :param extent: Extent parameter
    :type extent: str

    :returns: Vector layer
    :rtype: QgsVectorLayer
    """

    alg_params = {
        "INPUT": extent,
        "CRS": None,
        "OUTPUT": QgsProcessing.TEMPORARY_OUTPUT,
    }

    results = processing.run(
        "native:extenttolayer",
        alg_params,
        context=self.processing_context,
        feedback=self.feedback,
    )

    return results["OUTPUT"]

log_message

log_message(message, name='qgis_cplus', info=True, notify=True)

Logs the message into QGIS logs using qgis_cplus as the default log instance. If notify_user is True, user will be notified about the log.

Parameters:

Name	Type	Description	Default
message	str	The log message	required
name	str	Name of te log instance, qgis_cplus is the default	'qgis_cplus'
info	bool	Whether the message is about info or a warning	True
notify	bool	Whether to notify user about the log	True

Source code in src/cplus_plugin/tasks.py

def log_message(
    self,
    message: str,
    name: str = "qgis_cplus",
    info: bool = True,
    notify: bool = True,
):
    """Logs the message into QGIS logs using qgis_cplus as the default
    log instance.
    If notify_user is True, user will be notified about the log.

    :param message: The log message
    :type message: str

    :param name: Name of te log instance, qgis_cplus is the default
    :type message: str

    :param info: Whether the message is about info or a
        warning
    :type info: bool

    :param notify: Whether to notify user about the log
    :type notify: bool
    """
    if not isinstance(message, str):
        if isinstance(message, dict):
            message = json.dumps(message, cls=CustomJsonEncoder)
        else:
            message = json.dumps(todict(message), cls=CustomJsonEncoder)
    log(message, name=name, info=info, notify=notify)

mask_layer_difference

mask_layer_difference(input_layer, overlay_layer)

Creates a new vector layer that contains difference of features between the two passed layers.

Parameters:

Name	Type	Description	Default
input_layer	QgsVectorLayer	Input layer	required
overlay_layer	QgsVectorLayer	Target overlay layer	required

Returns:

Type	Description
QgsVectorLayer	Vector layer

Source code in src/cplus_plugin/tasks.py

def mask_layer_difference(self, input_layer, overlay_layer):
    """Creates a new vector layer that contains
     difference of features between the two passed layers.

    :param input_layer: Input layer
    :type input_layer: QgsVectorLayer

    :param overlay_layer: Target overlay layer
    :type overlay_layer: QgsVectorLayer

    :returns: Vector layer
    :rtype: QgsVectorLayer
    """

    alg_params = {
        "INPUT": input_layer,
        "OVERLAY": overlay_layer,
        "OVERLAY_FIELDS_PREFIX": "",
        "GRID_SIZE": None,
        "OUTPUT": QgsProcessing.TEMPORARY_OUTPUT,
    }

    results = processing.run(
        "native:symmetricaldifference",
        alg_params,
        context=self.processing_context,
        feedback=self.feedback,
    )

    return results["OUTPUT"]

merge_vector_layers

merge_vector_layers(layers)

Merges the passed vector layers into a single layer

Parameters:

Name	Type	Description	Default
layers	typing.List[str]	List of the vector layers paths	required

Returns:

Type	Description
QgsMapLayer	Merged vector layer

Source code in src/cplus_plugin/tasks.py

def merge_vector_layers(self, layers):
    """Merges the passed vector layers into a single layer

    :param layers: List of the vector layers paths
    :type layers: typing.List[str]

    :return: Merged vector layer
    :rtype: QgsMapLayer
    """

    input_map_layers = []

    for layer_path in layers:
        layer = QgsVectorLayer(layer_path, "mask", "ogr")
        if layer.isValid():
            input_map_layers.append(layer)
        else:
            self.log_message(
                f"Skipping invalid mask layer {layer_path} from masking."
            )
    if len(input_map_layers) == 0:
        return None
    if len(input_map_layers) == 1:
        return input_map_layers[0].source()

    self.set_status_message(tr("Merging mask layers"))

    # Actual processing calculation
    alg_params = {
        "LAYERS": input_map_layers,
        "CRS": None,
        "OUTPUT": QgsProcessing.TEMPORARY_OUTPUT,
    }

    self.log_message(f"Used parameters for merging mask layers: {alg_params} \n")

    results = processing.run(
        "native:mergevectorlayers",
        alg_params,
        context=self.processing_context,
        feedback=self.feedback,
    )

    return results["OUTPUT"]

on_terminated

on_terminated(hide=False)

Called when the task is terminated.

Source code in src/cplus_plugin/tasks.py

def on_terminated(self, hide=False):
    """Called when the task is terminated."""
    if hide:
        message = "Processing has been minimized by the user."
    else:
        message = "Processing has been cancelled by the user."
    if self.error:
        message = f"Problem in running scenario analysis: {self.error}"
    self.set_status_message(tr(message))
    self.log_message(message)

replace_nodata

replace_nodata(layer_path, output_path, nodata_value)

Adds nodata value info into the layer available in the passed layer_path and save the layer in the passed output_path path.

The addition will replace any current nodata value available in the input layer.

Parameters:

Name	Type	Description	Default
layer_path	str	Input layer path	required
output_path	str	Output layer path	required
nodata_value		Nodata value to be used	required

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def replace_nodata(self, layer_path, output_path, nodata_value):
    """Adds nodata value info into the layer available
    in the passed layer_path and save the layer in the passed output_path
    path.

    The addition will replace any current nodata value available in
    the input layer.

    :param layer_path: Input layer path
    :type layer_path: str

    :param output_path: Output layer path
    :type output_path: str

    :param nodata_value: Nodata value to be used
    :type output_path: int

    :returns: Whether the task operations was successful
    :rtype: bool

    """
    self.feedback = QgsProcessingFeedback()
    self.feedback.progressChanged.connect(self.update_progress)

    try:
        alg_params = {
            "COPY_SUBDATASETS": False,
            "DATA_TYPE": 6,  # Float32
            "EXTRA": "",
            "INPUT": layer_path,
            "NODATA": None,
            "OPTIONS": "",
            "TARGET_CRS": None,
            "OUTPUT": QgsProcessing.TEMPORARY_OUTPUT,
        }
        translate_output = processing.run(
            "gdal:translate",
            alg_params,
            context=self.processing_context,
            feedback=self.feedback,
            is_child_algorithm=True,
        )

        alg_params = {
            "DATA_TYPE": 0,  # Use Input Layer Data Type
            "EXTRA": "",
            "INPUT": translate_output["OUTPUT"],
            "MULTITHREADING": False,
            "NODATA": -9999,
            "OPTIONS": "",
            "RESAMPLING": 0,  # Nearest Neighbour
            "SOURCE_CRS": None,
            "TARGET_CRS": None,
            "TARGET_EXTENT": None,
            "TARGET_EXTENT_CRS": None,
            "TARGET_RESOLUTION": None,
            "OUTPUT": output_path,
        }
        outputs = processing.run(
            "gdal:warpreproject",
            alg_params,
            context=self.processing_context,
            feedback=self.feedback,
            is_child_algorithm=True,
        )

        return outputs is not None
    except Exception as e:
        log(f"Problem replacing no data value from a snapping output, {e}")

    return False

run

run()

Runs the main scenario analysis task operations

Source code in src/cplus_plugin/tasks.py

def run(self):
    """Runs the main scenario analysis task operations"""

    self.scenario_directory = self.get_scenario_directory()

    FileUtils.create_new_dir(self.scenario_directory)

    selected_pathway = None
    pathway_found = False

    for activity in self.analysis_activities:
        if pathway_found:
            break
        for pathway in activity.pathways:
            if pathway is not None:
                pathway_found = True
                selected_pathway = pathway
                break

    target_layer = QgsRasterLayer(selected_pathway.path, selected_pathway.name)

    dest_crs = (
        target_layer.crs()
        if selected_pathway and selected_pathway.path
        else QgsCoordinateReferenceSystem("EPSG:4326")
    )

    processing_extent = QgsRectangle(
        float(self.analysis_extent.bbox[0]),
        float(self.analysis_extent.bbox[2]),
        float(self.analysis_extent.bbox[1]),
        float(self.analysis_extent.bbox[3]),
    )

    snapped_extent = self.align_extent(target_layer, processing_extent)

    extent_string = (
        f"{snapped_extent.xMinimum()},{snapped_extent.xMaximum()},"
        f"{snapped_extent.yMinimum()},{snapped_extent.yMaximum()}"
        f" [{dest_crs.authid()}]"
    )

    self.log_message(
        "Original area of interest extent: "
        f"{processing_extent.asWktPolygon()} \n"
    )
    self.log_message(
        "Snapped area of interest extent " f"{snapped_extent.asWktPolygon()} \n"
    )
    # Run pathways layers snapping using a specified reference layer

    snapping_enabled = self.get_settings_value(
        Settings.SNAPPING_ENABLED, default=False, setting_type=bool
    )
    reference_layer = self.get_settings_value(Settings.SNAP_LAYER, default="")
    reference_layer_path = Path(reference_layer)
    if (
        snapping_enabled
        and os.path.exists(reference_layer)
        and reference_layer_path.is_file()
    ):
        self.snap_analysis_data(
            self.analysis_activities,
            extent_string,
        )

    # Preparing all the pathways by adding them together with
    # their carbon layers before creating
    # their respective activities.

    save_output = self.get_settings_value(
        Settings.NCS_WITH_CARBON, default=True, setting_type=bool
    )

    self.run_pathways_analysis(
        self.analysis_activities,
        extent_string,
        temporary_output=not save_output,
    )

    # Normalizing all the activities pathways using the carbon coefficient and
    # the pathway suitability index

    self.run_pathways_normalization(
        self.analysis_activities,
        extent_string,
    )

    # Creating activities from the normalized pathways

    save_output = self.get_settings_value(
        Settings.LANDUSE_PROJECT, default=True, setting_type=bool
    )

    self.run_activities_analysis(
        self.analysis_activities,
        extent_string,
        temporary_output=not save_output,
    )

    # Run masking of the activities layers
    masking_layers = self.get_masking_layers()

    if masking_layers:
        self.run_activities_masking(
            self.analysis_activities,
            masking_layers,
            extent_string,
        )

    # TODO enable the sieve functionality
    sieve_enabled = self.get_settings_value(
        Settings.SIEVE_ENABLED, default=False, setting_type=bool
    )

    if sieve_enabled:
        self.run_activities_sieve(
            self.analysis_activities,
        )

    # After creating activities, we normalize them using the same coefficients
    # used in normalizing their respective pathways.

    save_output = self.get_settings_value(
        Settings.LANDUSE_NORMALIZED, default=True, setting_type=bool
    )

    self.run_activities_normalization(
        self.analysis_activities,
        extent_string,
        temporary_output=not save_output,
    )

    # Weighting the activities with their corresponding priority weighting layers
    save_output = self.get_settings_value(
        Settings.LANDUSE_WEIGHTED, default=True, setting_type=bool
    )
    weighted_activities, result = self.run_activities_weighting(
        self.analysis_activities,
        self.analysis_priority_layers_groups,
        extent_string,
        temporary_output=not save_output,
    )

    self.analysis_weighted_activities = weighted_activities
    self.scenario.weighted_activities = weighted_activities

    # Post weighting analysis
    self.run_activities_cleaning(
        weighted_activities, extent_string, temporary_output=not save_output
    )

    # The highest position tool analysis
    save_output = self.get_settings_value(
        Settings.HIGHEST_POSITION, default=True, setting_type=bool
    )
    self.run_highest_position_analysis(temporary_output=not save_output)

    return True

run_activities_analysis

run_activities_analysis(activities, extent, temporary_output=False)

Runs the required activity analysis on the passed activities pathways. The analysis is responsible for creating activities layers from their respective pathways layers.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the selected activities	required
extent	SpatialExtent	selected extent from user	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_analysis(self, activities, extent, temporary_output=False):
    """Runs the required activity analysis on the passed
    activities pathways. The analysis is responsible for creating activities
    layers from their respective pathways layers.

    :param activities: List of the selected activities
    :type activities: typing.List[Activity]

    :param extent: selected extent from user
    :type extent: SpatialExtent

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(tr("Creating activity layers from pathways"))

    try:
        for activity in activities:
            activities_directory = os.path.join(
                self.scenario_directory, "activities"
            )
            FileUtils.create_new_dir(activities_directory)
            file_name = clean_filename(activity.name.replace(" ", "_"))

            layers = []
            if not activity.pathways and (
                activity.path is None or activity.path == ""
            ):
                self.set_info_message(
                    tr(
                        f"No defined activity pathways or a"
                        f" activity layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"No defined activity pathways or an "
                    f"activity layer for the activity {activity.name}"
                )

                return False

            output_file = os.path.join(
                activities_directory, f"{file_name}_{str(uuid.uuid4())[:4]}.tif"
            )

            # Due to the activities base class
            # activity only one of the following blocks will be executed,
            # the activity either contain a path or
            # pathways

            if activity.path is not None and activity.path != "":
                layers = [activity.path]

            for pathway in activity.pathways:
                layers.append(pathway.path)

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation

            alg_params = {
                "IGNORE_NODATA": True,
                "INPUT": layers,
                "EXTENT": extent,
                "OUTPUT_NODATA_VALUE": -9999,
                "REFERENCE_LAYER": layers[0] if len(layers) > 0 else None,
                "STATISTIC": 0,  # Sum
                "OUTPUT": output,
            }

            self.log_message(
                f"Used parameters for " f"activities generation: {alg_params} \n"
            )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "native:cellstatistics",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )
            activity.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem creating activity layers, {e}")
        self.cancel_task(e)
        return False

    return True

run_activities_cleaning

run_activities_cleaning(activities, extent=None, temporary_output=False)

Cleans the weighted activities replacing zero values with no-data as they are not statistical meaningful for the scenario analysis.

Parameters:

Name	Type	Description	Default
extent	str	Selected extent from user	None
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_cleaning(self, activities, extent=None, temporary_output=False):
    """Cleans the weighted activities replacing
    zero values with no-data as they are not statistical meaningful for the
    scenario analysis.

    :param extent: Selected extent from user
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """

    if self.processing_cancelled:
        return False

    self.set_status_message(tr("Updating weighted activity values"))

    try:
        for activity in activities:
            if activity.path is None or activity.path == "":
                self.set_info_message(
                    tr(
                        f"Problem when running activity updates, "
                        f"there is no map layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"Problem when running activity updates, "
                    f"there is no map layer for the activity {activity.name}"
                )

                return False

            layers = [activity.path]

            file_name = clean_filename(activity.name.replace(" ", "_"))

            output_file = os.path.join(
                self.scenario_directory, "weighted_activities"
            )
            output_file = os.path.join(
                output_file, f"{file_name}_{str(uuid.uuid4())[:4]}_cleaned.tif"
            )

            # Actual processing calculation
            # The aim is to convert pixels values to no data, that is why we are
            # using the sum operation with only one layer.

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            alg_params = {
                "IGNORE_NODATA": True,
                "INPUT": layers,
                "EXTENT": extent,
                "OUTPUT_NODATA_VALUE": 0,
                "REFERENCE_LAYER": layers[0] if len(layers) > 0 else None,
                "STATISTIC": 0,  # Sum
                "OUTPUT": output,
            }

            self.log_message(
                f"Used parameters for "
                f"updates on the weighted activities: {alg_params} \n"
            )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "native:cellstatistics",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )
            activity.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem cleaning activities, {e}")
        self.cancel_task(e)
        return False

    return True

run_activities_masking

run_activities_masking(activities, masking_layers, extent, temporary_output=False)

Applies the mask layers into the passed activities

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the selected activities	required
masking_layers	dict	Paths to the mask layers to be used	required
extent	str	selected extent from user	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_masking(
    self, activities, masking_layers, extent, temporary_output=False
):
    """Applies the mask layers into the passed activities

    :param activities: List of the selected activities
    :type activities: typing.List[Activity]

    :param masking_layers: Paths to the mask layers to be used
    :type masking_layers: dict

    :param extent: selected extent from user
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(tr("Masking activities using the saved masked layers"))

    try:
        if len(masking_layers) < 1:
            return False
        if len(masking_layers) > 1:
            initial_mask_layer = self.merge_vector_layers(masking_layers)
        else:
            mask_layer_path = masking_layers[0]
            initial_mask_layer = QgsVectorLayer(mask_layer_path, "mask", "ogr")

        if not initial_mask_layer.isValid():
            self.log_message(
                f"Skipping activities masking "
                f"using layer {mask_layer_path}, not a valid layer."
            )
            return False

        if Qgis.versionInt() < 33000:
            layer_check = initial_mask_layer.geometryType() == QgsWkbTypes.Polygon
        else:
            layer_check = (
                initial_mask_layer.geometryType() == Qgis.GeometryType.Polygon
            )

        if not layer_check:
            self.log_message(
                f"Skipping activities masking "
                f"using layer {mask_layer_path}, not a polygon layer."
            )
            return False

        extent_layer = self.layer_extent(extent)
        mask_layer = self.mask_layer_difference(initial_mask_layer, extent_layer)

        if isinstance(mask_layer, str):
            mask_layer = QgsVectorLayer(mask_layer, "ogr")

        if not mask_layer.isValid():
            self.log_message(
                f"Skipping activities masking "
                f"the created difference mask layer {mask_layer.source()},"
                f" not a valid layer."
            )
            return False

        for activity in activities:
            if activity.path is None or activity.path == "":
                if not self.processing_cancelled:
                    self.set_info_message(
                        tr(
                            f"Problem when masking activities, "
                            f"there is no map layer for the activity {activity.name}"
                        ),
                        level=Qgis.Critical,
                    )
                    self.log_message(
                        f"Problem when masking activities, "
                        f"there is no map layer for the activity {activity.name}"
                    )
                else:
                    # If the user cancelled the processing
                    self.set_info_message(
                        tr(f"Processing has been cancelled by the user."),
                        level=Qgis.Critical,
                    )
                    self.log_message(f"Processing has been cancelled by the user.")

                return False

            masked_activities_directory = os.path.join(
                self.scenario_directory, "masked_activities"
            )
            FileUtils.create_new_dir(masked_activities_directory)
            file_name = clean_filename(activity.name.replace(" ", "_"))

            output_file = os.path.join(
                masked_activities_directory,
                f"{file_name}_{str(uuid.uuid4())[:4]}.tif",
            )

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            activity_layer = QgsRasterLayer(activity.path, "activity_layer")

            # Actual processing calculation
            alg_params = {
                "INPUT": activity.path,
                "MASK": mask_layer,
                "SOURCE_CRS": activity_layer.crs(),
                "DESTINATION_CRS": activity_layer.crs(),
                "TARGET_EXTENT": extent,
                "OUTPUT": output,
                "NO_DATA": -9999,
            }

            self.log_message(
                f"Used parameters for masking the activities: {alg_params} \n"
            )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "gdal:cliprasterbymasklayer",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )
            activity.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem masking activities layers, {e} \n")
        self.cancel_task(e)
        return False

    return True

run_activities_normalization

run_activities_normalization(activities, extent, temporary_output=False)

Runs the normalization analysis on the activities' layers, adjusting band values measured on different scale, the resulting scale is computed using the below formula Normalized_activity = (Carbon coefficient + Suitability index) * ( (Activity layer value) - (Activity band minimum value)) / (Activity band maximum value - Activity band minimum value))

If the carbon coefficient and suitability index are both zero then the computation won't take them into account in the normalization calculation.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the analyzed activities	required
extent	str	Selected area of interest extent	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_normalization(self, activities, extent, temporary_output=False):
    """Runs the normalization analysis on the activities' layers,
    adjusting band values measured on different scale, the resulting scale
    is computed using the below formula
    Normalized_activity = (Carbon coefficient + Suitability index) * (
                        (Activity layer value) - (Activity band minimum value)) /
                        (Activity band maximum value - Activity band minimum value))

    If the carbon coefficient and suitability index are both zero then
    the computation won't take them into account in the normalization
    calculation.

    :param activities: List of the analyzed activities
    :type activities: typing.List[Activity]

    :param extent: Selected area of interest extent
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(tr("Normalization of the activities"))

    try:
        for activity in activities:
            if activity.path is None or activity.path == "":
                if not self.processing_cancelled:
                    self.set_info_message(
                        tr(
                            f"Problem when running activities normalization, "
                            f"there is no map layer for the activity {activity.name}"
                        ),
                        level=Qgis.Critical,
                    )
                    self.log_message(
                        f"Problem when running activities normalization, "
                        f"there is no map layer for the activity {activity.name}"
                    )
                else:
                    # If the user cancelled the processing
                    self.set_info_message(
                        tr(f"Processing has been cancelled by the user."),
                        level=Qgis.Critical,
                    )
                    self.log_message(f"Processing has been cancelled by the user.")

                return False

            layers = []
            normalized_activities_directory = os.path.join(
                self.scenario_directory, "normalized_activities"
            )
            FileUtils.create_new_dir(normalized_activities_directory)
            file_name = clean_filename(activity.name.replace(" ", "_"))

            output_file = os.path.join(
                normalized_activities_directory,
                f"{file_name}_{str(uuid.uuid4())[:4]}.tif",
            )

            activity_layer = QgsRasterLayer(activity.path, activity.name)
            provider = activity_layer.dataProvider()
            band_statistics = provider.bandStatistics(1)

            min_value = band_statistics.minimumValue
            max_value = band_statistics.maximumValue

            self.log_message(
                f"Found minimum {min_value} and "
                f"maximum {max_value} for activity {activity.name} \n"
            )

            layer_name = Path(activity.path).stem

            layers.append(activity.path)

            carbon_coefficient = float(
                self.get_settings_value(Settings.CARBON_COEFFICIENT, default=0.0)
            )

            suitability_index = float(
                self.get_settings_value(
                    Settings.PATHWAY_SUITABILITY_INDEX, default=0
                )
            )

            normalization_index = carbon_coefficient + suitability_index

            if normalization_index > 0:
                expression = (
                    f" {normalization_index} * "
                    f'("{layer_name}@1" - {min_value}) /'
                    f" ({max_value} - {min_value})"
                )

            else:
                expression = (
                    f'("{layer_name}@1" - {min_value}) /'
                    f" ({max_value} - {min_value})"
                )

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation
            alg_params = {
                "CELLSIZE": 0,
                "CRS": None,
                "EXPRESSION": expression,
                "EXTENT": extent,
                "LAYERS": layers,
                "OUTPUT": output,
            }

            self.log_message(
                f"Used parameters for normalization of the activities: {alg_params} \n"
            )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "qgis:rastercalculator",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )
            activity.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem normalizing activity layers, {e} \n")
        self.cancel_task(e)
        return False

    return True

run_activities_sieve

run_activities_sieve(models, temporary_output=False)

Runs the sieve functionality analysis on the passed models layers, removing the models layer polygons that are smaller than the provided threshold size (in pixels) and replaces them with the pixel value of the largest neighbour polygon.

Parameters:

Name	Type	Description	Default
models	typing.List[ImplementationModel]	List of the analyzed activities	required
extent	str	Selected area of interest extent	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_sieve(self, models, temporary_output=False):
    """Runs the sieve functionality analysis on the passed models layers,
    removing the models layer polygons that are smaller than the provided
    threshold size (in pixels) and replaces them with the pixel value of
    the largest neighbour polygon.

    :param models: List of the analyzed activities
    :type models: typing.List[ImplementationModel]

    :param extent: Selected area of interest extent
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(tr("Applying sieve function to the activities"))

    try:
        for model in models:
            if model.path is None or model.path == "":
                if not self.processing_cancelled:
                    self.set_info_message(
                        tr(
                            f"Problem when running sieve function on models, "
                            f"there is no map layer for the model {model.name}"
                        ),
                        level=Qgis.Critical,
                    )
                    self.log_message(
                        f"Problem when running sieve function on models, "
                        f"there is no map layer for the model {model.name}"
                    )
                else:
                    # If the user cancelled the processing
                    self.set_info_message(
                        tr(f"Processing has been cancelled by the user."),
                        level=Qgis.Critical,
                    )
                    self.log_message(f"Processing has been cancelled by the user.")

                return False

            sieved_ims_directory = os.path.join(
                self.scenario_directory, "sieved_ims"
            )
            FileUtils.create_new_dir(sieved_ims_directory)
            file_name = clean_filename(model.name.replace(" ", "_"))

            output_file = os.path.join(
                sieved_ims_directory, f"{file_name}_{str(uuid.uuid4())[:4]}.tif"
            )

            threshold_value = float(
                self.get_settings_value(Settings.SIEVE_THRESHOLD, default=10.0)
            )

            mask_layer = self.get_settings_value(
                Settings.SIEVE_MASK_PATH, default=""
            )

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation
            alg_params = {
                "INPUT": model.path,
                "THRESHOLD": threshold_value,
                "MASK_LAYER": mask_layer,
                "OUTPUT": output,
            }

            self.log_message(f"Used parameters for sieving: {alg_params} \n")

            input_name = os.path.splitext(os.path.basename(model.path))[0]

            # Step 1: Create a binary mask from the original raster
            binary_mask = processing.run(
                "qgis:rastercalculator",
                {
                    "CELLSIZE": 0,
                    "LAYERS": [model.path],
                    "CRS": None,
                    "EXPRESSION": f"{input_name}@1 > 0",
                    "OUTPUT": "TEMPORARY_OUTPUT",
                },
            )["OUTPUT"]

            # feedback.pushInfo(f"binary mask {binary_mask}")

            # binary_mask_layer = QgsRasterLayer(binary_mask, 'binary')

            # QgsProject.instance().addMapLayer(binary_mask_layer)

            # Step 2: Run sieve analysis from on the binary mask
            sieved_mask = processing.run(
                "gdal:sieve",
                {
                    "INPUT": binary_mask,
                    "THRESHOLD": threshold_value,
                    "EIGHT_CONNECTEDNESS": True,
                    "NO_MASK": True,
                    "MASK_LAYER": None,
                    "OUTPUT": "TEMPORARY_OUTPUT",
                },
                context=self.processing_context,
                feedback=self.feedback,
            )["OUTPUT"]

            # feedback.pushInfo(f"sieved mask {sieved_mask}")

            # sieved_mask_layer = QgsRasterLayer(sieved_mask, 'sieved_mask')

            # QgsProject.instance().addMapLayer(sieved_mask_layer)

            expr = f"({os.path.splitext(os.path.basename(sieved_mask))[0]}@1 > 0) * {os.path.splitext(os.path.basename(sieved_mask))[0]}@1"
            # feedback.pushInfo(f"used expression {expr}")

            # Step 3: Remove and convert any no data value to 0
            sieved_mask_clean = processing.run(
                "qgis:rastercalculator",
                {
                    "CELLSIZE": 0,
                    "LAYERS": [sieved_mask],
                    "CRS": None,
                    "EXPRESSION": expr,
                    "OUTPUT": "TEMPORARY_OUTPUT",
                },
                context=self.processing_context,
                feedback=self.feedback,
            )["OUTPUT"]

            # feedback.pushInfo(f"sieved mask clean {sieved_mask_clean}")

            # sieved_mask_clean_layer = QgsRasterLayer(sieved_mask_clean, 'sieved_mask_clean')

            # QgsProject.instance().addMapLayer(sieved_mask_clean_layer)

            expr_2 = f"{input_name}@1 * {os.path.splitext(os.path.basename(sieved_mask_clean))[0]}@1"

            # feedback.pushInfo(f"Used expression 2 {expr_2}")

            # Step 4: Join the sieved mask with the original input layer to filter out the small areas
            sieve_output = processing.run(
                "qgis:rastercalculator",
                {
                    "CELLSIZE": 0,
                    "LAYERS": [model.path, sieved_mask_clean],
                    "CRS": None,
                    "EXPRESSION": expr_2,
                    "OUTPUT": "TEMPORARY_OUTPUT",
                },
                context=self.processing_context,
                feedback=self.feedback,
            )["OUTPUT"]

            # feedback.pushInfo(f"sieved output joined {sieve_output}")

            # sieve_output_layer = QgsRasterLayer(sieve_output, 'sieve_output')

            # QgsProject.instance().addMapLayer(sieve_output_layer)

            # expr_3 = f'if ( {os.path.splitext(os.path.basename(sieve_output))[0]}@1 <= 0, -9999, {os.path.splitext(os.path.basename(sieve_output))[0]}@1 )'

            # feedback.pushInfo(f"used expression 3 {expr_3}")

            # Step 5. Replace all 0 with -9999 using if ("combined@1" <= 0, -9999, "combined@1")
            sieve_output_updated = processing.run(
                "gdal:rastercalculator",
                {
                    "INPUT_A": f"{sieve_output}",
                    "BAND_A": 1,
                    "FORMULA": "9999*(A<=0)*(-1)+A*(A>0)",
                    "NO_DATA": None,
                    "EXTENT_OPT": 0,
                    "PROJWIN": None,
                    "RTYPE": 5,
                    "OPTIONS": "",
                    "EXTRA": "",
                    "OUTPUT": "TEMPORARY_OUTPUT",
                },
                context=self.processing_context,
                feedback=self.feedback,
            )["OUTPUT"]

            # feedback.pushInfo(f"sieved output updated {sieve_output_updated}")

            # sieve_output_updated_layer = QgsRasterLayer(sieve_output_updated, 'sieve_output_updated')

            # QgsProject.instance().addMapLayer(sieve_output_updated_layer)

            # Step 6. Run sum statistics with ignore no data values set to false and no data value of -9999
            results = processing.run(
                "native:cellstatistics",
                {
                    "INPUT": [sieve_output_updated],
                    "STATISTIC": 0,
                    "IGNORE_NODATA": False,
                    "REFERENCE_LAYER": sieve_output_updated,
                    "OUTPUT_NODATA_VALUE": -9999,
                    "OUTPUT": output,
                },
                context=self.processing_context,
                feedback=self.feedback,
            )

            # self.log_message(
            #     f"Used parameters for running sieve function to the models: {alg_params} \n"
            # )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            model.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem running sieve function on models layers, {e} \n")
        self.cancel_task(e)
        return False

    return True

run_activities_weighting

run_activities_weighting(activities, priority_layers_groups, extent, temporary_output=False)

Runs weighting analysis on the passed activities using the corresponding activities weight layers.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the selected activities	required
priority_layers_groups	dict	Used priority layers groups and their values	required
extent	str	selected extent from user	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
typing.Tuple[typing.List, bool]	A tuple with the weighted activities outputs and a value of whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_activities_weighting(
    self, activities, priority_layers_groups, extent, temporary_output=False
):
    """Runs weighting analysis on the passed activities using
    the corresponding activities weight layers.

    :param activities: List of the selected activities
    :type activities: typing.List[Activity]

    :param priority_layers_groups: Used priority layers groups and their values
    :type priority_layers_groups: dict

    :param extent: selected extent from user
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: A tuple with the weighted activities outputs and
    a value of whether the task operations was successful
    :rtype: typing.Tuple[typing.List, bool]
    """

    if self.processing_cancelled:
        return [], False

    self.set_status_message(tr(f"Weighting activities"))

    weighted_activities = []

    try:
        for original_activity in activities:
            activity = clone_activity(original_activity)

            if activity.path is None or activity.path == "":
                self.set_info_message(
                    tr(
                        f"Problem when running activities weighting, "
                        f"there is no map layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"Problem when running activities weighting, "
                    f"there is no map layer for the activity {activity.name}"
                )

                return [], False

            basenames = []
            layers = []

            layers.append(activity.path)
            basenames.append(f'"{Path(activity.path).stem}@1"')

            if not any(priority_layers_groups):
                self.log_message(
                    f"There are no defined priority layers in groups,"
                    f" skipping activities weighting step."
                )
                self.run_activities_cleaning(
                    extent, temporary_output=temporary_output
                )
                return

            if activity.priority_layers is None or activity.priority_layers is []:
                self.log_message(
                    f"There are no associated "
                    f"priority weighting layers for activity {activity.name}"
                )
                continue

            settings_activity = self.get_activity(str(activity.uuid))

            for layer in settings_activity.priority_layers:
                if layer is None:
                    continue

                settings_layer = self.get_priority_layer(layer.get("uuid"))
                if settings_layer is None:
                    continue

                pwl = settings_layer.get("path")

                missing_pwl_message = (
                    f"Path {pwl} for priority "
                    f"weighting layer {layer.get('name')} "
                    f"doesn't exist, skipping the layer "
                    f"from the activity {activity.name} weighting."
                )
                if pwl is None:
                    self.log_message(missing_pwl_message)
                    continue

                pwl_path = Path(pwl)

                if not pwl_path.exists():
                    self.log_message(missing_pwl_message)
                    continue

                path_basename = pwl_path.stem

                for priority_layer in self.get_priority_layers():
                    if priority_layer.get("name") == layer.get("name"):
                        for group in priority_layer.get("groups", []):
                            value = group.get("value")
                            coefficient = float(value)
                            if coefficient > 0:
                                if pwl not in layers:
                                    layers.append(pwl)
                                basenames.append(
                                    f'({coefficient}*"{path_basename}@1")'
                                )

            if basenames is []:
                return [], True

            weighted_activities_directory = os.path.join(
                self.scenario_directory, "weighted_activities"
            )

            FileUtils.create_new_dir(weighted_activities_directory)

            file_name = clean_filename(activity.name.replace(" ", "_"))
            output_file = os.path.join(
                weighted_activities_directory,
                f"{file_name}_{str(uuid.uuid4())[:4]}.tif",
            )
            expression = " + ".join(basenames)

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation
            alg_params = {
                "CELLSIZE": 0,
                "CRS": None,
                "EXPRESSION": expression,
                "EXTENT": extent,
                "LAYERS": layers,
                "OUTPUT": output,
            }

            self.log_message(
                f" Used parameters for calculating weighting activities {alg_params} \n"
            )

            feedback = QgsProcessingFeedback()

            feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return [], False

            results = processing.run(
                "qgis:rastercalculator",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )
            activity.path = results["OUTPUT"]

            weighted_activities.append(activity)

    except Exception as e:
        self.log_message(f"Problem weighting activities, {e}\n")
        self.cancel_task(e)
        return None, False

    return weighted_activities, True

run_highest_position_analysis

run_highest_position_analysis(temporary_output=False)

Runs the highest position analysis which is last step in scenario analysis. Uses the activities set by the current ongoing analysis.

Parameters:

Name	Type	Description	Default
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_highest_position_analysis(self, temporary_output=False):
    """Runs the highest position analysis which is last step
    in scenario analysis. Uses the activities set by the current ongoing
    analysis.

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool

    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    passed_extent_box = self.analysis_extent.bbox
    passed_extent = QgsRectangle(
        passed_extent_box[0],
        passed_extent_box[2],
        passed_extent_box[1],
        passed_extent_box[3],
    )

    self.scenario_result = ScenarioResult(
        scenario=self.scenario, scenario_directory=self.scenario_directory
    )

    try:
        layers = {}

        self.set_status_message(tr("Calculating the highest position"))

        for activity in self.analysis_weighted_activities:
            if activity.path is not None and activity.path != "":
                raster_layer = QgsRasterLayer(activity.path, activity.name)
                layers[activity.name] = (
                    raster_layer if raster_layer is not None else None
                )
            else:
                for pathway in activity.pathways:
                    layers[activity.name] = QgsRasterLayer(pathway.path)

        source_crs = QgsCoordinateReferenceSystem("EPSG:4326")
        dest_crs = list(layers.values())[0].crs() if len(layers) > 0 else source_crs

        extent_string = (
            f"{passed_extent.xMinimum()},{passed_extent.xMaximum()},"
            f"{passed_extent.yMinimum()},{passed_extent.yMaximum()}"
            f" [{dest_crs.authid()}]"
        )

        output_file = os.path.join(
            self.scenario_directory,
            f"{SCENARIO_OUTPUT_FILE_NAME}_{str(self.scenario.uuid)[:4]}.tif",
        )

        # Preparing the input rasters for the highest position
        # analysis in a correct order

        activity_names = [
            activity.name for activity in self.analysis_weighted_activities
        ]
        all_activities = sorted(
            self.analysis_weighted_activities,
            key=lambda activity_instance: activity_instance.style_pixel_value,
        )
        for index, activity in enumerate(all_activities):
            activity.style_pixel_value = index + 1

        all_activity_names = [activity.name for activity in all_activities]
        sources = []

        for activity_name in all_activity_names:
            if activity_name in activity_names:
                sources.append(layers[activity_name].source())

        self.log_message(
            f"Layers sources {[Path(source).stem for source in sources]}"
        )

        output_file = (
            QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
        )

        alg_params = {
            "IGNORE_NODATA": True,
            "INPUT_RASTERS": sources,
            "EXTENT": extent_string,
            "OUTPUT_NODATA_VALUE": -9999,
            "REFERENCE_LAYER": list(layers.values())[0]
            if len(layers) >= 1
            else None,
            "OUTPUT": output_file,
        }

        self.log_message(
            f"Used parameters for highest position analysis {alg_params} \n"
        )

        self.feedback = QgsProcessingFeedback()

        self.feedback.progressChanged.connect(self.update_progress)

        if self.processing_cancelled:
            return False

        self.output = processing.run(
            "native:highestpositioninrasterstack",
            alg_params,
            context=self.processing_context,
            feedback=self.feedback,
        )

    except Exception as err:
        self.log_message(
            tr(
                "An error occurred when running task for "
                'scenario analysis, error message "{}"'.format(str(err))
            )
        )
        self.cancel_task(err)
        return False

    return True

run_pathways_analysis

run_pathways_analysis(activities, extent, temporary_output=False)

Runs the required activity pathways analysis on the passed activities. The analysis involves adding the pathways carbon layers into their respective pathway layers.

If a pathway layer has more than one carbon layer, the resulting weighted pathway will contain the sum of the pathway layer values with the average of the pathway carbon layers values.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the selected activities	required
extent	SpatialExtent	The selected extent from user	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_pathways_analysis(self, activities, extent, temporary_output=False):
    """Runs the required activity pathways analysis on the passed
     activities. The analysis involves adding the pathways
     carbon layers into their respective pathway layers.

     If a pathway layer has more than one carbon layer, the resulting
     weighted pathway will contain the sum of the pathway layer values
     with the average of the pathway carbon layers values.

    :param activities: List of the selected activities
    :type activities: typing.List[Activity]

    :param extent: The selected extent from user
    :type extent: SpatialExtent

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        return False

    self.set_status_message(tr("Adding activity pathways with carbon layers"))

    pathways = []
    activities_paths = []

    try:
        for activity in activities:
            if not activity.pathways and (
                activity.path is None or activity.path == ""
            ):
                self.set_info_message(
                    tr(
                        f"No defined activity pathways or an"
                        f" activity layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"No defined activity pathways or a "
                    f"activity layer for the activity {activity.name}"
                )
                return False

            for pathway in activity.pathways:
                if not (pathway in pathways):
                    pathways.append(pathway)

            if activity.path is not None and activity.path != "":
                activities_paths.append(activity.path)

        if not pathways and len(activities_paths) > 0:
            self.run_pathways_normalization(activities, extent)
            return

        suitability_index = float(
            self.get_settings_value(Settings.PATHWAY_SUITABILITY_INDEX, default=0)
        )

        carbon_coefficient = float(
            self.get_settings_value(Settings.CARBON_COEFFICIENT, default=0.0)
        )

        for pathway in pathways:
            basenames = []
            layers = []
            path_basename = Path(pathway.path).stem
            layers.append(pathway.path)

            file_name = clean_filename(pathway.name.replace(" ", "_"))

            if suitability_index > 0:
                basenames.append(f'{suitability_index} * "{path_basename}@1"')
            else:
                basenames.append(f'"{path_basename}@1"')

            carbon_names = []

            if len(pathway.carbon_paths) <= 0:
                continue

            new_carbon_directory = os.path.join(
                self.scenario_directory, "pathways_carbon_layers"
            )

            FileUtils.create_new_dir(new_carbon_directory)

            output_file = os.path.join(
                new_carbon_directory, f"{file_name}_{str(uuid.uuid4())[:4]}.tif"
            )

            for carbon_path in pathway.carbon_paths:
                carbon_full_path = Path(carbon_path)
                if not carbon_full_path.exists():
                    continue
                layers.append(carbon_path)
                carbon_names.append(f'"{carbon_full_path.stem}@1"')

            if len(carbon_names) == 1 and carbon_coefficient > 0:
                basenames.append(f"{carbon_coefficient} * ({carbon_names[0]})")

            # Setting up calculation to use carbon layers average when
            # a pathway has more than one carbon layer.
            if len(carbon_names) > 1 and carbon_coefficient > 0:
                basenames.append(
                    f"{carbon_coefficient} * ("
                    f'({" + ".join(carbon_names)}) / '
                    f"{len(pathway.carbon_paths)})"
                )
            expression = " + ".join(basenames)

            if carbon_coefficient <= 0 and suitability_index <= 0:
                self.run_pathways_normalization(activities, extent)
                return

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation
            alg_params = {
                "CELLSIZE": 0,
                "CRS": None,
                "EXPRESSION": expression,
                "EXTENT": extent,
                "LAYERS": layers,
                "OUTPUT": output,
            }

            self.log_message(
                f"Used parameters for combining pathways"
                f" and carbon layers generation: {alg_params} \n"
            )

            self.feedback = QgsProcessingFeedback()

            self.feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "qgis:rastercalculator",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )

            pathway.path = results["OUTPUT"]
    except Exception as e:
        self.log_message(f"Problem running pathway analysis,  {e}")
        self.cancel_task(e)

    return True

run_pathways_normalization

run_pathways_normalization(activities, extent, temporary_output=False)

Runs the normalization on the activities pathways layers, adjusting band values measured on different scale, the resulting scale is computed using the below formula Normalized_Pathway = (Carbon coefficient + Suitability index) * ( (activity layer value) - (activity band minimum value)) / (activity band maximum value - activity band minimum value))

If the carbon coefficient and suitability index are both zero then the computation won't take them into account in the normalization calculation.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the analyzed activities	required
extent	str	selected extent from user	required
temporary_output	bool	Whether to save the processing outputs as temporary files	False

Returns:

Type	Description
bool	Whether the task operations was successful

Source code in src/cplus_plugin/tasks.py

def run_pathways_normalization(self, activities, extent, temporary_output=False):
    """Runs the normalization on the activities pathways layers,
    adjusting band values measured on different scale, the resulting scale
    is computed using the below formula
    Normalized_Pathway = (Carbon coefficient + Suitability index) * (
                        (activity layer value) - (activity band minimum value)) /
                        (activity band maximum value - activity band minimum value))

    If the carbon coefficient and suitability index are both zero then
    the computation won't take them into account in the normalization
    calculation.

    :param activities: List of the analyzed activities
    :type activities: typing.List[Activity]

    :param extent: selected extent from user
    :type extent: str

    :param temporary_output: Whether to save the processing outputs as temporary
    files
    :type temporary_output: bool

    :returns: Whether the task operations was successful
    :rtype: bool
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(tr("Normalization of pathways"))

    pathways = []
    activities_paths = []

    try:
        for activity in activities:
            if not activity.pathways and (
                activity.path is None or activity.path == ""
            ):
                self.set_info_message(
                    tr(
                        f"No defined activity pathways or an"
                        f" activity layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"No defined activity pathways or an "
                    f"activity layer for the activity {activity.name}"
                )

                return False

            for pathway in activity.pathways:
                if not (pathway in pathways):
                    pathways.append(pathway)

            if activity.path is not None and activity.path != "":
                activities_paths.append(activity.path)

        if not pathways and len(activities_paths) > 0:
            self.run_activities_analysis(activities, extent)

            return

        carbon_coefficient = float(
            self.get_settings_value(Settings.CARBON_COEFFICIENT, default=0.0)
        )

        suitability_index = float(
            self.get_settings_value(Settings.PATHWAY_SUITABILITY_INDEX, default=0)
        )

        normalization_index = carbon_coefficient + suitability_index

        for pathway in pathways:
            layers = []
            normalized_pathways_directory = os.path.join(
                self.scenario_directory, "normalized_pathways"
            )
            FileUtils.create_new_dir(normalized_pathways_directory)
            file_name = clean_filename(pathway.name.replace(" ", "_"))

            output_file = os.path.join(
                normalized_pathways_directory,
                f"{file_name}_{str(uuid.uuid4())[:4]}.tif",
            )

            pathway_layer = QgsRasterLayer(pathway.path, pathway.name)
            provider = pathway_layer.dataProvider()
            band_statistics = provider.bandStatistics(1)

            min_value = band_statistics.minimumValue
            max_value = band_statistics.maximumValue

            layer_name = Path(pathway.path).stem

            layers.append(pathway.path)

            self.log_message(
                f"Found minimum {min_value} and "
                f"maximum {max_value} for pathway "
                f" \n"
            )

            if max_value < min_value:
                raise Exception(
                    tr(
                        f"Pathway contains "
                        f"invalid minimum and maxmum band values"
                    )
                )

            if normalization_index > 0:
                expression = (
                    f" {normalization_index} * "
                    f'("{layer_name}@1" - {min_value}) /'
                    f" ({max_value} - {min_value})"
                )
            else:
                expression = (
                    f'("{layer_name}@1" - {min_value}) /'
                    f" ({max_value} - {min_value})"
                )

            output = (
                QgsProcessing.TEMPORARY_OUTPUT if temporary_output else output_file
            )

            # Actual processing calculation
            alg_params = {
                "CELLSIZE": 0,
                "CRS": None,
                "EXPRESSION": expression,
                "EXTENT": extent,
                "LAYERS": layers,
                "OUTPUT": output,
            }

            self.log_message(
                f"Used parameters for normalization of the pathways: {alg_params} \n"
            )

            self.feedback = QgsProcessingFeedback()

            self.feedback.progressChanged.connect(self.update_progress)

            if self.processing_cancelled:
                return False

            results = processing.run(
                "qgis:rastercalculator",
                alg_params,
                context=self.processing_context,
                feedback=self.feedback,
            )

            # self.replace_nodata(results["OUTPUT"], output_file, -9999)

            pathway.path = results["OUTPUT"]

    except Exception as e:
        self.log_message(f"Problem normalizing pathways layers, {e} \n")
        self.cancel_task(e)
        return False

    return True

set_custom_progress

set_custom_progress(value)

Set task progress value.

Parameters:

Name	Type	Description	Default
value	float	Value to be set on the progress bar	required

Source code in src/cplus_plugin/tasks.py

def set_custom_progress(self, value: float):
    """Set task progress value.

    :param value: Value to be set on the progress bar
    :type value: float
    """
    self.custom_progress = value
    self.custom_progress_changed.emit(self.custom_progress)

set_info_message

set_info_message(message, level=Qgis.Info)

Set info message.

Parameters:

Name	Type	Description	Default
message	str	Message	required
level	int, optional	log level, defaults to Qgis.Info	Info

Source code in src/cplus_plugin/tasks.py

def set_info_message(self, message: str, level=Qgis.Info):
    """Set info message.

    :param message: Message
    :type message: str
    :param level: log level, defaults to Qgis.Info
    :type level: int, optional
    """
    self.info_message = message
    self.info_message_changed.emit(self.info_message, level)

set_status_message

set_status_message(message)

Set status message in progress dialog

Parameters:

Name	Type	Description	Default
message	str	Message to be displayed	required

Source code in src/cplus_plugin/tasks.py

def set_status_message(self, message: str):
    """Set status message in progress dialog

    :param message: Message to be displayed
    :type message: str
    """
    self.status_message = message
    self.status_message_changed.emit(self.status_message)

snap_analysis_data

snap_analysis_data(activities, extent)

Snaps the passed activities pathways, carbon layers and priority layers to align with the reference layer set on the settings manager.

Parameters:

Name	Type	Description	Default
activities	typing.List[Activity]	List of the selected activities	required
extent	list	The selected extent from user	required

Source code in src/cplus_plugin/tasks.py

def snap_analysis_data(self, activities, extent):
    """Snaps the passed activities pathways, carbon layers and priority layers
     to align with the reference layer set on the settings
    manager.

    :param activities: List of the selected activities
    :type activities: typing.List[Activity]

    :param extent: The selected extent from user
    :type extent: list
    """
    if self.processing_cancelled:
        # Will not proceed if processing has been cancelled by the user
        return False

    self.set_status_message(
        tr(
            "Snapping the selected activity pathways, "
            "carbon layers and priority layers"
        )
    )

    pathways = []

    try:
        for activity in activities:
            if not activity.pathways and (
                activity.path is None or activity.path == ""
            ):
                self.set_info_message(
                    tr(
                        f"No defined activity pathways or a"
                        f" activity layer for the activity {activity.name}"
                    ),
                    level=Qgis.Critical,
                )
                self.log_message(
                    f"No defined activity pathways or a "
                    f"activity layer for the activity {activity.name}"
                )
                return False

            for pathway in activity.pathways:
                if not (pathway in pathways):
                    pathways.append(pathway)

        reference_layer_path = self.get_settings_value(Settings.SNAP_LAYER)
        rescale_values = self.get_settings_value(
            Settings.RESCALE_VALUES, default=False, setting_type=bool
        )

        resampling_method = self.get_settings_value(
            Settings.RESAMPLING_METHOD, default=0
        )

        if pathways is not None and len(pathways) > 0:
            snapped_pathways_directory = os.path.join(
                self.scenario_directory, "pathways"
            )

            FileUtils.create_new_dir(snapped_pathways_directory)

            for pathway in pathways:
                pathway_layer = QgsRasterLayer(pathway.path, pathway.name)
                nodata_value = pathway_layer.dataProvider().sourceNoDataValue(1)

                if self.processing_cancelled:
                    return False

                # carbon layer snapping

                self.log_message(
                    f"Snapping carbon layers from {pathway.name} pathway"
                )

                if (
                    pathway.carbon_paths is not None
                    and len(pathway.carbon_paths) > 0
                ):
                    snapped_carbon_directory = os.path.join(
                        self.scenario_directory, "carbon_layers"
                    )

                    FileUtils.create_new_dir(snapped_carbon_directory)

                    snapped_carbon_paths = []

                    for carbon_path in pathway.carbon_paths:
                        carbon_layer = QgsRasterLayer(
                            carbon_path, f"{str(uuid.uuid4())[:4]}"
                        )
                        nodata_value_carbon = (
                            carbon_layer.dataProvider().sourceNoDataValue(1)
                        )

                        carbon_output_path = self.snap_layer(
                            carbon_path,
                            reference_layer_path,
                            extent,
                            snapped_carbon_directory,
                            rescale_values,
                            resampling_method,
                            nodata_value_carbon,
                        )

                        if carbon_output_path:
                            snapped_carbon_paths.append(carbon_output_path)
                        else:
                            snapped_carbon_paths.append(carbon_path)

                    pathway.carbon_paths = snapped_carbon_paths

                self.log_message(f"Snapping {pathway.name} pathway layer \n")

                # Pathway snapping

                output_path = self.snap_layer(
                    pathway.path,
                    reference_layer_path,
                    extent,
                    snapped_pathways_directory,
                    rescale_values,
                    resampling_method,
                    nodata_value,
                )
                if output_path:
                    pathway.path = output_path

        for activity in activities:
            self.log_message(
                f"Snapping {len(activity.priority_layers)} "
                f"priority weighting layers from activity {activity.name} with layers\n"
            )

            if (
                activity.priority_layers is not None
                and len(activity.priority_layers) > 0
            ):
                snapped_priority_directory = os.path.join(
                    self.scenario_directory, "priority_layers"
                )

                FileUtils.create_new_dir(snapped_priority_directory)

                priority_layers = []
                for priority_layer in activity.priority_layers:
                    if priority_layer is None:
                        continue

                    priority_layer_settings = self.get_priority_layer(
                        priority_layer.get("uuid")
                    )
                    if priority_layer_settings is None:
                        continue

                    priority_layer_path = priority_layer_settings.get("path")

                    if not Path(priority_layer_path).exists():
                        priority_layers.append(priority_layer)
                        continue

                    layer = QgsRasterLayer(
                        priority_layer_path, f"{str(uuid.uuid4())[:4]}"
                    )
                    nodata_value_priority = layer.dataProvider().sourceNoDataValue(
                        1
                    )

                    priority_output_path = self.snap_layer(
                        priority_layer_path,
                        reference_layer_path,
                        extent,
                        snapped_priority_directory,
                        rescale_values,
                        resampling_method,
                        nodata_value_priority,
                    )

                    if priority_output_path:
                        priority_layer["path"] = priority_output_path

                    priority_layers.append(priority_layer)

                activity.priority_layers = priority_layers

    except Exception as e:
        self.log_message(f"Problem snapping layers, {e} \n")
        self.cancel_task(e)
        return False

    return True

snap_layer

snap_layer(input_path, reference_path, extent, directory, rescale_values, resampling_method, nodata_value)

Snaps the passed input layer using the reference layer and updates the snap output no data value to be the same as the original input layer no data value.

Parameters:

Name	Type	Description	Default
input_path	str	Input layer source	required
reference_path	str	Reference layer source	required
extent	list	Clip extent	required
directory	str	Absolute path of the output directory for the snapped layers	required
rescale_values	bool	Whether to rescale pixel values	required
resample_method	QgsAlignRaster.ResampleAlg	Method to use when resampling	required
nodata_value	float	Original no data value of the input layer	required

Source code in src/cplus_plugin/tasks.py

def snap_layer(
    self,
    input_path,
    reference_path,
    extent,
    directory,
    rescale_values,
    resampling_method,
    nodata_value,
):
    """Snaps the passed input layer using the reference layer and updates
    the snap output no data value to be the same as the original input layer
    no data value.

    :param input_path: Input layer source
    :type input_path: str

    :param reference_path: Reference layer source
    :type reference_path: str

    :param extent: Clip extent
    :type extent: list

    :param directory: Absolute path of the output directory for the snapped
    layers
    :type directory: str

    :param rescale_values: Whether to rescale pixel values
    :type rescale_values: bool

    :param resample_method: Method to use when resampling
    :type resample_method: QgsAlignRaster.ResampleAlg

    :param nodata_value: Original no data value of the input layer
    :type nodata_value: float

    """

    input_result_path, reference_result_path = align_rasters(
        input_path,
        reference_path,
        extent,
        directory,
        rescale_values,
        resampling_method,
    )

    if input_result_path is not None:
        result_path = Path(input_result_path)

        directory = result_path.parent
        name = result_path.stem

        output_path = os.path.join(directory, f"{name}_final.tif")

        self.replace_nodata(input_result_path, output_path, nodata_value)

    return output_path

update_progress

update_progress(value)

Sets the value of the task progress

Parameters:

Name	Type	Description	Default
value	float	Value to be set on the progress bar	required

Source code in src/cplus_plugin/tasks.py

def update_progress(self, value):
    """Sets the value of the task progress

    :param value: Value to be set on the progress bar
    :type value: float
    """
    if not self.processing_cancelled:
        self.set_custom_progress(value)
    else:
        self.feedback = QgsProcessingFeedback()
        self.processing_context = QgsProcessingContext()

---

Last update: October 2, 2024