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Tests for the ER model implementation.
"""
from pathlib import Path
import numpy as np
import pytest
import yaml
import pandas as pd
from er_model_core.allometry import calculate_biomass
from er_model_core.er_model import ERModel, Species
from er_model_core.metrics import calculate_carbon
@pytest.fixture
def sample_config():
"""Create a minimal test configuration."""
return {
"species": [
{
"name": "Test Species",
"planting_density": 1000,
"m_ref": 0.16,
"DBH_ref": 9.0,
"p": 1.493,
"chapman_richards": {
"dbh": {"a": 30, "b": 0.15, "c": 1.5},
"height": {"a": 10, "b": 0.05, "c": 1.2}
},
"allometry": {
"biomass_equation": "0.2 * (dbh ** 2.4)",
"root_shoot_ratio": 0.4
},
"initial_values": {"dbh": 1.0, "height": 0.5}
}
],
"project": {
"duration_years": 5,
"planting_schedule": {
"year_1": 100
}
},
"carbon": {
"biomass_to_carbon": 0.47,
"carbon_to_co2": 3.67,
"buffer_percentage": 15,
"leakage_percentage": 0,
"baseline_emissions": 0
}
}
@pytest.fixture
def config_file(tmp_path, sample_config):
"""Create a temporary config file."""
config_path = tmp_path / "test_config.yaml"
with open(config_path, "w") as f:
yaml.dump(sample_config, f)
return config_path
def test_model_initialization(config_file):
"""Test that the model initializes correctly from config."""
model = ERModel(config_file)
assert len(model.species) == 1
assert model.species[0].name == "Test Species"
assert model.project.duration_years == 5
assert model.carbon.biomass_to_carbon == 0.47
def test_surviving_trees_calculation(config_file):
"""Test tree survival calculations with DBH-dependent mortality."""
model = ERModel(config_file)
species = model.species[0]
# Test first year mortality (should use DBH-dependent formula)
dbh = 9.0
m = species.m_ref * (species.DBH_ref / dbh) ** species.p
initial_trees = 1000
N_live = initial_trees * (1 - m)
expected = initial_trees * (1 - 0.16)
assert np.isclose(N_live, expected, atol=1e-3)
def test_chapman_richards_growth(config_file):
"""Test DBH calculations using Chapman-Richards equation."""
model = ERModel(config_file)
species = model.species[0]
# Test initial growth
dbh = model.chapman_richards_dbh(0, species.chapman_richards)
assert dbh == 0
# Test asymptotic behavior
dbh = model.chapman_richards_dbh(100, species.chapman_richards)
assert np.isclose(dbh, species.chapman_richards["a"], rtol=0.01)
def test_biomass_calculation():
"""Test biomass calculations from DBH."""
params = {
"biomass_equation": "0.2 * (dbh ** 2.4)",
"root_shoot_ratio": 0.4
}
biomass = calculate_biomass(10, params)
expected_agb = 0.2 * (10 ** 2.4)
expected_total = expected_agb * (1 + 0.4)
assert np.isclose(biomass, expected_total)
def test_carbon_calculation():
"""Test carbon conversion calculations."""
biomass = 1000 # kg
biomass_to_carbon = 0.47
carbon_to_co2 = 3.67
co2 = calculate_carbon(biomass, biomass_to_carbon, carbon_to_co2)
expected = (1000 * 0.47 * 3.67) / 1000 # Convert to metric tons
assert np.isclose(co2, expected)
def test_full_pipeline(config_file):
"""Test the complete model pipeline."""
model = ERModel(config_file)
results = model.run()
assert len(results) == 5 # Duration years
assert "year" in results.columns
assert "gross_carbon" in results.columns
assert "net_carbon" in results.columns
assert all(results["net_carbon"] <= results["gross_carbon"])
def test_dbh_dependent_mortality():
"""Test that DBH-dependent mortality matches expected at DBH=9 and year-5 plateau."""
from er_model_core.er_model import ERModel, Species
# Minimal species config
species = Species(
name="Test Species",
planting_density=1000,
m_ref=0.16,
DBH_ref=9.0,
p=1.493,
chapman_richards={
"dbh": {"a": 9.0, "b": 0.5, "c": 1.0},
"height": {"a": 5.0, "b": 0.2, "c": 1.0}
},
allometry={"equation": "0.2 * (dbh ** 2.4)", "root_shoot_ratio": 0.4},
initial_values={"dbh": 9.0, "height": 5.0}
)
# At DBH = 9, mortality = 0.16
dbh = 9.0
m = species.m_ref * (species.DBH_ref / dbh) ** species.p
assert np.isclose(m, 0.16, atol=1e-3)
# Simulate 5 years, enforce plateau at year 5
initial_trees = 1000
plateau_density = 2000
class DummyModel:
def chapman_richards_growth(self, age, params, initial):
return dbh # Always 9 for this test
model = DummyModel()
N_live = initial_trees
for y in range(1, 6):
m = species.m_ref * (species.DBH_ref / dbh) ** species.p
N_live = N_live * (1 - m)
if y == 5:
N_live = plateau_density
assert N_live == plateau_density
def test_allometric_equation_species_A_B():
"""Test Zanvo et al. 2023 allometric equations for both species."""
from er_model_core.allometry import calculate_biomass
# Test values
dbh = 10.0 # cm
height = 5.0 # m
# species_A (Rhizophora spp.)
expected_A = 2.0738 * (dbh**2 * height)**0.67628
result_A = calculate_biomass(dbh, height, "species_A", {})
assert np.isclose(result_A, expected_A, rtol=1e-6), f"species_A: got {result_A}, expected {expected_A}"
# species_B (Avicennia germinans)
expected_B = 1.5595 * (dbh**2 * height)**0.55864
result_B = calculate_biomass(dbh, height, "species_B", {})
assert np.isclose(result_B, expected_B, rtol=1e-6), f"species_B: got {result_B}, expected {expected_B}"
# --- Parameter sweep/test for plausible survival curves (moved from er_model.py) ---
def test_dbh_mortality_sweep():
import matplotlib.pyplot as plt
import numpy as np
m_refs = [0.01, 0.05, 0.1, 0.16]
ps = [1.0, 1.5, 2.0]
DBH_ref = 9.0
years = np.arange(1, 31)
initial_trees = 1000
results = {}
for m_ref in m_refs:
for p in ps:
N_live = initial_trees
N_lives = []
for year in years:
# This test requires a simplified DBH growth for its internal logic.
# It does not use the main ERModel's growth functions directly.
dbh_test_growth = 1.0 + (year - 1) * 0.5 # simple linear DBH growth for test
dbh = max(dbh_test_growth, 1.0)
# Mortality calculation as per ERModel logic being tested
m = m_ref * (DBH_ref / dbh) ** p
m = min(max(m, 0), 0.99)
N_live = N_live * (1 - m)
N_lives.append(N_live)
results[(m_ref, p)] = N_lives
# This test originally had plotting. For automated tests, assertions are better.
# If visual inspection is needed, this part can be run in a notebook.
# For now, let's assert that the number of trees is non-increasing.
for (m_ref, p), N_lives_curve in results.items():
for i in range(len(N_lives_curve) - 1):
assert N_lives_curve[i+1] <= N_lives_curve[i], f"Mortality sweep {m_ref, p}: Trees increased from {N_lives_curve[i]} to {N_lives_curve[i+1]}"
assert N_lives_curve[-1] < initial_trees, f"Mortality sweep {m_ref, p}: No mortality occurred or trees increased."
# plt.figure(figsize=(10,6))
# for (m_ref, p), N_lives_plot in results.items():
# plt.plot(years, N_lives_plot, label=f"m_ref={m_ref}, p={p}")
# plt.xlabel("Year")
# plt.ylabel("Surviving Trees")
# plt.title("DBH-dependent Mortality Parameter Sweep")
# plt.legend()
# plt.grid(True)
# To save plot instead of showing:
# output_dir = Path(__file__).parent.parent / "outputs" / "test_plots"
# output_dir.mkdir(parents=True, exist_ok=True)
# plt.savefig(output_dir / "dbh_mortality_sweep.png")
# plt.close()
print("test_dbh_mortality_sweep completed basic assertions.")
# If you want to run this specific test and see the plot (e.g., during development):
# if __name__ == "__main__":
# test_dbh_mortality_sweep() # You would need to handle imports for ERModel parts if called directly here |