dcc_quantities.dcc_quantity_type ¶

DccQuantityType(
    si_data: SiDataListType,
    identifier: str | None = None,
    ref_id: list[str] | None = None,
    ref_type: list[str] | None = None,
    name: DccLangName | None = None,
    description: DccLangDescription | None = None,
    relative_uncertainty: str | None = None,
    used_methods: dict | None = None,
    used_software: dict | None = None,
    measuring_equipments: dict | None = None,
    measurement_meta_data: dict | None = None,
    index: str | None = None,
)

from dcc_quantities import DccQuantityType

values: np.ndarray

uncertainties: np.ndarray

dsi_unit: DsiUnit

is_top_level: bool

<dcc:list tableDimension=1>
    <dcc:quantity>
        <dcc:name>"Index0 quantity"</dcc:name>
        ...
    </dcc:quantity>
    <dcc:quantity>
        <dcc:name>"Value0 quantity"</dcc:name>
        ...
    </dcc:quantity>
    <dcc:measurementMetaData>
        <dcc:quantity>
            <dcc:name>"Value1 quantity"</dcc:name>
            ...
        </dcc:quantity>
    </dcc:measurementMetaData>
</dcc:list>

unique_id: str

from_dcc_data(dcc_data: dict) -> DccQuantityType

from_single_quantity_value(
    name: str | DccLangName,
    value: int | float,
    uncertainty: int | float | None,
    unit: str | DsiUnit,
    label: str | None = None,
) -> DccQuantityType

extract_all_quantities(dcc_data: dict | list) -> list[DccQuantityType]

set_label(label: str)

where(condition: Callable) -> np.ndarray[bool]

set_unique_id(new_id: str)

set_name(name: str | dict, language: str | None = None)

export_as_xml_structure() -> str

Built-in Operators¶

Length: len(q)¶

Returns the number of elements (values) contained within the quantity data.

>>> q = DccQuantityType(data=SiRealList([1, 2, 3], ...), ...)
>>> len(q)
3

Math operators¶

Each DccQuantityType instance can perform math operations (through built-in operators like +, *, /, etc.) providing as a result a new DccQuantityType instance. The provided result presents propagated uncertainties, calculated with the help of metas_unclib_python_wrapper, as well as the newly calculated D-SI unit.

Supported Math

• Sum DccQuantityType + other and other + DccQuantityType
• Subtraction DccQuantityType - other and other - DccQuantityType
• Multiplication DccQuantityType * other and other * DccQuantityType
• Division DccQuantityType / other and other / DccQuantityType
• Power DccQuantityType ** other
• Value comparison DccQuantityType == other
• Negation -DccQuantityType

Addition: +¶

Subtraction: -¶

Support for addition quant + other and subtraction quant - other operations. Each operation returns a new DccQuantityType instance with the updated quantity data.

>>> from dcc_quantities import DccQuantityType, SiRealList

>>> q1 = DccQuantityType(si_data=SiRealList(data=[1, 2, 3], unit="\\metre", label="Q1"), name={"en": "First distance"})
>>> q2 = DccQuantityType(si_data=SiRealList(data=[4, 5, 6], unit="\\metre", label="Q2"), name={"en": "Second distance"})

>>> q3 = q1 + q2
>>> q3.set_name("Sum of distances", "en")
>>> q3.set_label("Q3")

>>> print(q3.values)
[5, 7, 9]
>>> print(q3.dsi_unit)
'\metre'

Negation: -q¶

Support for unary negation operator -. This operator allows to obtain -quant, where all the quantity data is negated.

>>> from dcc_quantities import DccQuantityType, SiRealList

>>> q1 = DccQuantityType(SiRealList(data=[1, -2, 3], unit="\\metre", label="Q1"), name={"en": "Distance"})

>>> q2 = -q1
>>> q2.set_name("Negated distance", "en")
>>> q2.set_label("Q2")

>>> print(q2.values)
[-1, 2, -3]
>>> print(q2.dsi_unit)
'\metre'

Multiplication: *¶

Support for multiplications quant * other and other * quant. A quantity can be multiplied by:

• Another quantity, where the resulting quantity is defined by the unit multiplication of both quantities.
• A scalar, where the result quantity has different values at the quantity data but the same original unit.
• Any array like with the same size as the quantity data, applying item per item multiplication at the quantity data.

>>> from dcc_quantities import DccQuantityType, SiRealList

>>> q1 = DccQuantityType(SiRealList(data=[1, 2, 3], unit="\\metre", label="Q1"), name={"en": "First distance"})
>>> q2 = DccQuantityType(SiRealList(data=[4, 5, 6], unit="\\metre", label="Q2"), name={"en": "Second distance"})

>>> # Case: Quantities multiplication
... q3 = q1 * q2
>>> q3.set_label("Q3")
>>> q3.set_name("Multiplied distances", "en")

>>> print(q3.values)
[4, 10, 18]
>>> print(q3.dsi_unit)  
'\metre\tothe{2}'

>>> # Case: Quantity by scalar
... q4 = q1 * 2
>>> q4.set_label("Q4")
>>> q4.set_name("Distance times scalar", "en")

>>> print(q4.values)
[1, 4, 6]
>>> print(q4.dsi_unit)
'\metre'

>>> # Case: Quantity by array
... import numpy as np
>>> q5 = q1 * np.array([4, 5, 6])
>>> q5.set_name("Quantity multiplied by array of same length", "en")
>>> q5.set_label("Q5")

>>> print(q5.values)
[4, 10, 18]
>>> print(q5.dsi_unit)
'\metre'

Division: /¶

Support for dividing a quantity over a target as quant / T and the inverse, a target over a quantity T / quant. The rules that the division follow are the same three as the multiplication, returning then a result quantity with updated quantity data and D-SI unit.

>>> from dcc_quantities import DccQuantityType, SiRealList

>>> q1 = DccQuantityType(SiRealList(data=[2, 4, 6], unit="\\metre", label="d"), name={"en": "Distance"})
>>> q2 = DccQuantityType(SiRealList(data=[2], unit="\\second", label="t"), name={"en", "Time"})

>>> q3 = q1 / q2
>>> q3.set_name("Velocity", "en")
>>> q3.set_label("V")

>>> print(q3.values)
[1, 2, 3]
>>> print(q3.dsi_unit)
'\metre\per\second'

Power: **¶

Support the operation of a quantity powered to a target quant ** exponent. The power operator is supported only for:

• The target being a scalar.
• The target being another quantity with adimensional D-SI units.