Expose metabolic constants in Animal model

.github/workflows/ci.yml

@@ -81,7 +81,7 @@ jobs:
       - name: Build docs using sphinx
         run: |
           cd docs
-          poetry run sphinx-build --jobs auto -W --keep-going source build
+          poetry run sphinx-build -W --keep-going source build
 
       - name: Archive built docs for error checking on failure
         if: failure()

virtual_ecosystem/core/model_config.py

@@ -61,6 +61,9 @@ class CoreConstants(Configuration):
     gravity: float = constants.gravitational_constant
     """Newtonian constant of gravitation, [m s-1]."""
 
+    boltzmann_constant: float = constants.Boltzmann
+    """The Boltzmann constant, [J K-1]"""
+
     stefan_boltzmann_constant: float = constants.Stefan_Boltzmann
     """Stefan-Boltzmann constant, [W m-2 K-4].
 

virtual_ecosystem/models/animal/animal_cohorts.py

@@ -13,6 +13,7 @@
 import virtual_ecosystem.models.animal.scaling_functions as sf
 from virtual_ecosystem.core.grid import Grid
 from virtual_ecosystem.core.logger import LOGGER
+from virtual_ecosystem.core.model_config import CoreConstants
 from virtual_ecosystem.models.animal.animal_traits import VerticalOccupancy
 from virtual_ecosystem.models.animal.cnp import CNP
 from virtual_ecosystem.models.animal.decay import (
@@ -42,6 +43,7 @@ def __init__(
         centroid_key: int,
         grid: Grid,
         constants: AnimalConstants = AnimalConstants(),
+        core_constants: CoreConstants = CoreConstants(),
     ) -> None:
         if age < 0:
             raise ValueError("Age must be a positive number.")
@@ -63,6 +65,8 @@ def __init__(
         """The the grid structure of the simulation."""
         self.constants = constants
         """Animal constants."""
+        self.core_constants = core_constants
+        """Core constants."""
         self.location_status: Literal["active", "migrated", "aquatic"] = "active"
         """Location status of the cohort, active means present and participating."""
         self.remaining_time_away: float = 0.0
@@ -255,10 +259,12 @@ def metabolize(self, temperature: float, dt: timedelta64) -> dict[str, float]:
 
         # Calculate potential carbon metabolized (kg/day * number of days)
         potential_carbon_metabolized = sf.metabolic_rate(
-            self.mass_current,
-            temperature,
-            self.functional_group.metabolic_rate_terms,
-            self.functional_group.metabolic_type,
+            mass=self.mass_current,
+            temperature=temperature,
+            terms=self.functional_group.metabolic_rate_terms,
+            metabolic_type=self.functional_group.metabolic_type,
+            metabolic_scaling_coefficients=self.constants.metabolic_scaling_coefficients,
+            boltzmann_constant=self.core_constants.boltzmann_constant,
         ) * float(dt / timedelta64(1, "D"))
 
         # Ensure metabolized carbon does not exceed available carbon

virtual_ecosystem/models/animal/animal_model.py

@@ -1818,6 +1818,7 @@ def create_new_cohort(
             centroid_key=centroid_key,
             grid=self.data.grid,
             constants=self.model_constants,
+            core_constants=self.core_constants,
         )
 
         self.assign_prey_groups(cohort)

virtual_ecosystem/models/animal/model_config.py

@@ -124,6 +124,22 @@ def get_population_density_terms(
     madingley_biomass_scaling_terms: tuple[float, float] = (0.6, 300000.0)
     """Biomass scaling terms from the Madingley model."""
 
+    metabolic_scaling_coefficients: tuple[float, float, float] = (
+        0.037,  # Es
+        0.5,  # sig
+        0.69,  # Ea
+    )
+    """Metabolic rate scaling coefficients.
+
+    These are the coefficients of Madingley style scaling of metabolic rate with  mass
+    and temperature, assuming a power-law relationship with mass and an exponential
+    relationship with temperature. The three values are:
+
+    * $E_s$ - energy to mass conversion constant (g/kJ)
+    * $\sigma$ - proportion of time-step with temp in active range (toy default value)
+    * $E_a$ - aggregate activation energy of metabolic reactions
+    """
+
     metabolic_rate_terms: dict[MetabolicType, dict[str, tuple[float, float]]] = Field(
         default_factory=lambda: {
             MetabolicType.ENDOTHERMIC: {

virtual_ecosystem/models/animal/scaling_functions.py

@@ -12,10 +12,10 @@
 
 import numpy as np
 
+from virtual_ecosystem.core.model_config import CoreConstants
 from virtual_ecosystem.models.animal.animal_traits import DietType, MetabolicType
-
-# from virtual_ecosystem.models.animal.constants import BOLTZMANN_CONSTANT
 from virtual_ecosystem.models.animal.functional_group import FunctionalGroup
+from virtual_ecosystem.models.animal.model_config import AnimalConstants
 
 
 def damuths_law(mass: float, terms: tuple) -> float:
@@ -75,29 +75,34 @@ def metabolic_rate(
     temperature: float,
     terms: dict,
     metabolic_type: MetabolicType,
+    metabolic_scaling_coefficients: tuple[
+        float, float, float
+    ] = AnimalConstants().metabolic_scaling_coefficients,
+    boltzmann_constant: float = CoreConstants().boltzmann_constant,
 ) -> float:
-    """Calculates metabolic rate in grams of body mass per day.
+    r"""Calculates metabolic rate in grams of body mass per day.
 
     This follows the Madingley implementation, assuming a power-law relationship with
     mass and an exponential relationship with temperature.
 
     TODO: Implement activity windows to properly parameterize sigma.
-    TODO: Move constants to constants file.
 
     Args:
         mass: The body-mass [kg] of an AnimalCohort.
         temperature: The temperature [Celsius] of the environment.
         terms: The tuple of metabolic rate terms used.
         metabolic_type: The metabolic type of the animal [ENDOTHERMIC or ECTOTHERMIC].
+        metabolic_scaling_coefficients: A tuple providing the $E_s, \sigma, E_a$
+            coefficients of the Madingley metabolic rate model (see
+            :attr:`~virtual_ecosystem.models.animal.model_config.AnimalConstants.metabolic_scaling_coefficients`)
+        boltzmann_constant: The Boltzmann constant ($k_B$)
 
     Returns:
         The metabolic rate of an individual of the given cohort in [g/d].
     """
 
-    Es = 3.7 * 10 ** (-2)  # energy to mass conversion constant (g/kJ)
-    sig = 0.5  # proportion of time-step with temp in active range (toy)
-    Ea = 0.69  # aggregate activation energy of metabolic reactions
-    kB = 1.380649e-23
+    Es, sig, Ea = metabolic_scaling_coefficients
+    kB = boltzmann_constant
     mass_g = mass * 1000  # convert mass to grams
 
     if metabolic_type == MetabolicType.ENDOTHERMIC: