site_params

Site-level parameters: latitude, altitude, atmosphere, sowing calendar.

Ports the constant site-level inputs of the SIMPLACE Lintul5 component family — primarily PotentialEvapoTranspiration.java (atmosphere) and the sowing/emergence-calendar constants of Phenology.java — to a PyTorch-friendly dataclass.

Note

Latitude is normally consumed by the AstronomicParametersTransformer upstream of Lintul5; we keep it here so torchcrop can compute astronomy and irradiation internally.

SiteParameters dataclass

Geographical, atmospheric, and calendar parameters for a site.

Scalar fields have shape [] or [B] (broadcastable). Defaults correspond to a temperate Western-European site (≈ Wageningen).

Source code in torchcrop/parameters/site_params.py

@dataclass
class SiteParameters:
    """Geographical, atmospheric, and calendar parameters for a site.

    Scalar fields have shape ``[]`` or ``[B]`` (broadcastable). Defaults
    correspond to a temperate Western-European site (≈ Wageningen).
    """

    # ------------------------------------------------------------------ #
    # 1. Geography
    # ------------------------------------------------------------------ #

    latitude: torch.Tensor = field(default_factory=lambda: _t(52.0))
    """Decimal latitude [°] (positive northward). Drives the
    astronomical day-length and solar-declination calculations."""

    altitude: torch.Tensor = field(default_factory=lambda: _t(10.0))
    """``cALTI``. Site / weather-station altitude [m a.s.l.]. Used in the
    psychrometric-constant calculation of the Penman ET₀ routine."""

    # ------------------------------------------------------------------ #
    # 2. Atmosphere
    # ------------------------------------------------------------------ #

    co2: torch.Tensor = field(default_factory=lambda: _t(370.0))
    """``cCO``. Atmospheric CO₂ concentration [ppm]. Mirrors
    `CropParameters.co2`; provided here so a site-level CO₂ scenario
    can be set independently of the crop default. The Lintul5 ET routine
    uses 370 ppm as its reference."""

    cfet: torch.Tensor = field(default_factory=lambda: _t(1.0))
    """``cCFET``. Empirical correction factor [-] applied to the Penman
    transpiration rate (canopy-resistance proxy)."""

    fpenmtb: torch.Tensor = field(
        default_factory=lambda: _table(
            [(40.0, 1.05), (360.0, 1.00), (720.0, 0.95), (1000.0, 0.92), (2000.0, 0.92)]
        )
    )
    """``cFPENMTB`` (= ``cET0CorrectionTableCo2`` × ``cET0CorrectionTableFactor``).
    Multiplicative correction factor [-] for the Penman ET₀ as a function
    of atmospheric CO₂ concentration [ppm] (C3 crops)."""

    # ------------------------------------------------------------------ #
    # 3. Solar-radiation reconstruction (when only sunshine duration is
    #    available — Ångström–Prescott formula).
    # ------------------------------------------------------------------ #

    angstrom_a: torch.Tensor = field(default_factory=lambda: _t(0.25))
    """Ångström–Prescott coefficient ``a`` [-]: fraction of extra-
    terrestrial radiation reaching the surface on overcast days."""

    angstrom_b: torch.Tensor = field(default_factory=lambda: _t(0.50))
    """Ångström–Prescott coefficient ``b`` [-]: additional fraction
    reaching the surface on cloudless days, multiplied by relative
    sunshine duration."""

    # ------------------------------------------------------------------ #
    # 4. Sowing / emergence calendar (from Phenology.java)
    # ------------------------------------------------------------------ #

    plant_at_sowing: torch.Tensor = field(default_factory=lambda: _t(1.0))
    """``cPL``. Boolean flag (0/1) — if 1, the simulation starts at
    **planting** (uses `idpl`); if 0, it starts at **emergence**
    (uses `idem`)."""

    idpl: torch.Tensor = field(default_factory=lambda: _t(0.0))
    """``cIDPL``. Day of planting [day-of-year, 0–366]. Used when
    `plant_at_sowing` = 1."""

    idem: torch.Tensor = field(default_factory=lambda: _t(0.0))
    """``cIDEM``. Day of emergence [day-of-year, 0–366]. Used when
    `plant_at_sowing` = 0 to bypass the temperature-sum-driven
    emergence calculation."""

    # ------------------------------------------------------------------ #
    # Helpers
    # ------------------------------------------------------------------ #

    def to(
        self,
        dtype: torch.dtype | None = None,
        device: torch.device | str | None = None,
    ) -> "SiteParameters":
        """Cast and/or move all tensor fields to a new dtype/device.

        Args:
            dtype: Target tensor dtype, or ``None`` to leave unchanged.
            device: Target torch device, or ``None`` to leave unchanged.

        Returns:
            A new `SiteParameters` with every tensor field moved/cast.
        """
        kwargs: dict[str, Any] = {}
        for f in fields(self):
            t = getattr(self, f.name)
            if isinstance(t, torch.Tensor):
                kwargs[f.name] = t.to(dtype=dtype, device=device)
            else:
                kwargs[f.name] = t
        return SiteParameters(**kwargs)

altitude: Tensor dataclass-field

cALTI. Site / weather-station altitude [m a.s.l.]. Used in the psychrometric-constant calculation of the Penman ET₀ routine.

angstrom_a: Tensor dataclass-field

Ångström–Prescott coefficient a [-]: fraction of extra- terrestrial radiation reaching the surface on overcast days.

angstrom_b: Tensor dataclass-field

Ångström–Prescott coefficient b [-]: additional fraction reaching the surface on cloudless days, multiplied by relative sunshine duration.

cfet: Tensor dataclass-field

cCFET. Empirical correction factor [-] applied to the Penman transpiration rate (canopy-resistance proxy).

co2: Tensor dataclass-field

cCO. Atmospheric CO₂ concentration [ppm]. Mirrors CropParameters.co2; provided here so a site-level CO₂ scenario can be set independently of the crop default. The Lintul5 ET routine uses 370 ppm as its reference.

fpenmtb: Tensor dataclass-field

cFPENMTB (= cET0CorrectionTableCo2 × cET0CorrectionTableFactor). Multiplicative correction factor [-] for the Penman ET₀ as a function of atmospheric CO₂ concentration [ppm] (C3 crops).

idem: Tensor dataclass-field

cIDEM. Day of emergence [day-of-year, 0–366]. Used when plant_at_sowing = 0 to bypass the temperature-sum-driven emergence calculation.

idpl: Tensor dataclass-field

cIDPL. Day of planting [day-of-year, 0–366]. Used when plant_at_sowing = 1.

latitude: Tensor dataclass-field

Decimal latitude [°] (positive northward). Drives the astronomical day-length and solar-declination calculations.

plant_at_sowing: Tensor dataclass-field

cPL. Boolean flag (0/1) — if 1, the simulation starts at planting (uses idpl); if 0, it starts at emergence (uses idem).

to(self, dtype=None, device=None)

Cast and/or move all tensor fields to a new dtype/device.

Parameters:

Name	Type	Description	Default
dtype	torch.dtype | None	Target tensor dtype, or None to leave unchanged.	None
device	torch.device | str | None	Target torch device, or None to leave unchanged.	None

Returns:

Type	Description
'SiteParameters'	A new SiteParameters with every tensor field moved/cast.

Source code in torchcrop/parameters/site_params.py

def to(
    self,
    dtype: torch.dtype | None = None,
    device: torch.device | str | None = None,
) -> "SiteParameters":
    """Cast and/or move all tensor fields to a new dtype/device.

    Args:
        dtype: Target tensor dtype, or ``None`` to leave unchanged.
        device: Target torch device, or ``None`` to leave unchanged.

    Returns:
        A new `SiteParameters` with every tensor field moved/cast.
    """
    kwargs: dict[str, Any] = {}
    for f in fields(self):
        t = getattr(self, f.name)
        if isinstance(t, torch.Tensor):
            kwargs[f.name] = t.to(dtype=dtype, device=device)
        else:
            kwargs[f.name] = t
    return SiteParameters(**kwargs)