Financial Data Classes

Data models for the financial elements of the tool.

NcsPathwayNpv dataclass

NcsPathwayNpv(params, enabled, pathway)

Mapping of the NPV parameters to the corresponding NCS pathway.

base_name property

base_name

Returns a proposed name for the NCS pathway NPV.

An empty string will be return id the pathway attribute is not set.

Returns:

Type	Description
str	Proposed base name for the NCS pathway NPV.

pathway_id property

pathway_id

Gets the identifier of the NCS pathway model.

Returns:

Type	Description
str	The unique identifier of the NCS pathway model else an empty string if no NCS pathway has been set.

NcsPathwayNpvCollection dataclass

NcsPathwayNpvCollection(minimum_value, maximum_value, use_computed=True, remove_existing=False, mappings=list())

Collection for all NcsPathwayNpv configurations that have been specified by the user.

normalize_npvs

normalize_npvs()

Normalize the NPV values of NCS pathway using the specified normalization range.

If the absolute NPV values are less than or greater than the normalization range, then they will be truncated to 0.0 and 1.0 respectively. To avoid such a situation from occurring, it is recommended to make sure that the ranges are synchronized using the latest absolute NPV values by calling update_computed_normalization_range before normalizing the NPVs.

If there is only one NPV mapping, then assign a normalized value of 1.0.

Returns:

Type	Description
bool	True if the NPVs were successfully normalized else False due to various reasons such as if the minimum value is greater than the maximum value, if the min/max values are the same, or if there are no NPV mappings.

Source code in src/cplus_plugin/models/financial.py

def normalize_npvs(self) -> bool:
    """Normalize the NPV values of NCS pathway using the specified
    normalization range.

    If the absolute NPV values are less than or greater than the
    normalization range, then they will be truncated to 0.0 and 1.0
    respectively. To avoid such a situation from occurring, it is recommended
    to make sure that the ranges are synchronized using the latest absolute
    NPV values by calling `update_computed_normalization_range` before
    normalizing the NPVs.

    If there is only one NPV mapping, then assign a normalized value of 1.0.

    :returns: True if the NPVs were successfully normalized else False due
    to various reasons such as if the minimum value is greater than the
    maximum value, if the min/max values are the same, or if there are no NPV
    mappings.
    """
    valid_npv_mappings = self._valid_npv_mappings()
    if len(valid_npv_mappings) == 0:
        return False

    if len(valid_npv_mappings) == 1:
        pathway_npv = self.mappings[0]
        pathway_npv.params.normalized_npv = 1.0
        return True

    if self.minimum_value > self.maximum_value:
        return False

    norm_range = float(self.maximum_value - self.minimum_value)

    if norm_range == 0.0:
        return False

    for pathway_npv in valid_npv_mappings:
        absolute_npv = pathway_npv.params.absolute_npv
        if not absolute_npv:
            continue

        if absolute_npv <= self.minimum_value:
            normalized_npv = 0.0
        elif absolute_npv >= self.maximum_value:
            normalized_npv = 1.0
        else:
            normalized_npv = (absolute_npv - self.minimum_value) / norm_range

        pathway_npv.params.normalized_npv = normalized_npv

    return True

pathway_npv

pathway_npv(pathway_identifier)

Gets the mapping of an NCS pathway's NPV mapping if defined.

Parameters:

Name	Type	Description	Default
pathway_identifier	str	Unique identifier of an NCS pathway whose NPV mapping is to be retrieved.	required

Returns:

Type	Description
NcsPathwayNpv	The NCS pathway's NPV mapping else None if not found.

Source code in src/cplus_plugin/models/financial.py

def pathway_npv(self, pathway_identifier: str) -> typing.Optional[NcsPathwayNpv]:
    """Gets the mapping of an NCS pathway's NPV mapping if defined.

    :param pathway_identifier: Unique identifier of an NCS pathway
    whose NPV mapping is to be retrieved.
    :type pathway_identifier: str

    :returns: The NCS pathway's NPV mapping else None if not found.
    :rtype: NcsPathwayNpv
    """
    matching_mapping = [
        pathway_npv
        for pathway_npv in self.mappings
        if pathway_npv.pathway_id == pathway_identifier
    ]

    return None if len(matching_mapping) == 0 else matching_mapping[0]

update_computed_normalization_range

update_computed_normalization_range()

Update the minimum and maximum normalization values based on the absolute values of the existing NcsPathwayNpv objects.

Values for disabled Ncs pathway NPVs will be excluded from the computation.

Returns:

Type	Description
bool	True if the min/max values were updated else False if there are no mappings or valid absolute NPV values defined.

Source code in src/cplus_plugin/models/financial.py

def update_computed_normalization_range(self) -> bool:
    """Update the minimum and maximum normalization values
    based on the absolute values of the existing NcsPathwayNpv
    objects.

    Values for disabled Ncs pathway NPVs will be excluded from
    the computation.

    :returns: True if the min/max values were updated else False if
    there are no mappings or valid absolute NPV values defined.
    """
    if len(self.mappings) == 0:
        return False

    valid_npv_values = [
        pathway_npv.params.absolute_npv
        for pathway_npv in self._valid_npv_mappings()
    ]

    if len(valid_npv_values) == 0:
        return False

    self.minimum_value = min(valid_npv_values)
    self.maximum_value = max(valid_npv_values)

    return True

NcsPathwayNpvPwl dataclass

NcsPathwayNpvPwl(npv, extent, crs, pixel_size)

Convenience class that contains parameters for creating a PWL raster layer.

NpvParameters dataclass

NpvParameters(years, discount, absolute_npv=0.0, normalized_npv=0.0, yearly_rates=list(), manual_npv=False)

Parameters for computing an NCS pathway's NPV.

__post_init__

__post_init__()

Set empty yearly rates for consistency.

Source code in src/cplus_plugin/models/financial.py

def __post_init__(self):
    """Set empty yearly rates for consistency."""
    for i in range(self.years):
        self.yearly_rates.append((None, None, None))

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Last update: July 11, 2025