Published May 14, 2025 | Version v1
Dataset Open

CODES Dataset: lv_parametric_no_params

Authors/Creators

  • 1. EDMO icon University of Heidelberg

Description

Dataset for the CODES benchmark (https://github.com/robin-janssen/CODES-Benchmark). This dataset was designed to test variations of the architectures that can take additional ODE parameters as inputs. It is related to lv_parametric, which contains the same trajectories, and additionally the parameter alpha used to generate them. This enables comparison between providing the architecture with the additional information that is the value of the parameter, and leaving out this additional information (as is the case in this dataset).

Lotka-Volterra predator-prey model with three predators (p1, p2, p3) and three prey (q1, q2, q3), as well as a parameter alpha, which modifies reproduction and predation coefficients.

The system is defined by its gradients as follows:

# --- reproduction rates (prey) ---
# baseline: 0.5, 0.6, 0.4
rep_p1 = 0.5 * (1.0 - alpha) * p1
rep_p2 = 0.6 * (1.0 - alpha) * p2
rep_p3 = 0.4 * (1.0 - alpha) * p3

# --- predation terms ---
# baseline coefficients: 0.02, 0.01, 0.03, 0.015, 0.01, 0.025
pred1 = (0.02 * (1.0 + alpha)) * p1 * q1 + (0.01 * (1.0 + alpha)) * p1 * q2

pred2 = (0.03 * (1.0 + alpha)) * p2 * q1 + (0.015 * (1.0 + alpha)) * p2 * q3

pred3 = (0.01 * (1.0 + alpha)) * p3 * q2 + (0.025 * (1.0 + alpha)) * p3 * q3

# --- predator death rates (unchanged) ---
death_q1 = 0.1 * q1
death_q2 = 0.08 * q2
death_q3 = 0.12 * q3

# --- predator gains (unchanged) ---
gain_q1 = 0.005 * p1 * q1 + 0.007 * p2 * q1
gain_q2 = 0.006 * p1 * q2 + 0.009 * p3 * q2
gain_q3 = 0.008 * p2 * q3 + 0.01 * p3 * q3

# --- derivatives ---
dp1_dt = rep_p1 - pred1
dp2_dt = rep_p2 - pred2
dp3_dt = rep_p3 - pred3

dq1_dt = -death_q1 + gain_q1
dq2_dt = -death_q2 + gain_q2
dq3_dt = -death_q3 + gain_q3

return np.array([dp1_dt, dp2_dt, dp3_dt, dq1_dt, dq2_dt, dq3_dt])
101 timesteps in the interval [0, 100], solved with scipy.integrate.solve_ivp with the DOP853 method (atol = rtol = 1e-8).
Initial conditions for each species sampled in log-space between 1 and 10, while alpha was sampled linearly between 0 and 1. Initial conditions and the parameter were jointly Sobol-sampled (note that alpha is not included in the dataset).
 
350/50/100 train/test/val samples.

Files

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Additional details

Software

Repository URL
https://github.com/robin-janssen/CODES-Benchmark
Programming language
Python
Development Status
Active