Dynamics¶
Kuramoto: Heun’s method in Tensorflow¶
References
[1] - Thomas Peron, Bruno Messias, Angélica S. Mata, Francisco A. Rodrigues, and Yamir Moreno. On the onset of synchronization of Kuramoto oscillators in scale-free networks. arXiv:1905.02256 (2019).
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class
stdog.dynamics.kuramoto.heuns.
Heuns
(adjacency, phases, omegas, couplings, total_time, dt, transient=False, frustration=None, precision=32, device='/gpu:0', log=None, use_while=False)[source]¶ This class allow efficiently simulating phase oscillators (the Kuramoto model) on large heterogeneous networks using the Heun’s method implemented in TensorFlow.
Variables: - adjacency (coo matrix) –
- phases (np.ndarray) –
- omegas (np.ndarray) –
- couplings (np.ndarray) –
- total_time (float) –
- dt (float) –
- transient (bool) –
- frustation (bool) –
- device (str) –
- log (bool) –
- use_while (bool) –
- order_parameter_list (np.ndarray) –
Kuramoto: Heun’s method in CUDA¶
allow efficiently simulating phase oscillators (the Kuramoto model) on large heterogeneous networks using the Heun’s method with a “pure” CUDA implementation. Should be faster than tensorflow implementation. .. admonition:: References
[1] - Thomas Peron, Bruno Messias, Angélica S. Mata, Francisco A. Rodrigues, and Yamir Moreno. On the onset of synchronization of Kuramoto oscillators in scale-free networks. arXiv:1905.02256 (2019).
-
class
stdog.dynamics.kuramoto.cuheuns.
CUHeuns
(adjacency, phases, omegas, couplings, total_time, dt, transient=False, block_size=1024)[source]¶ Allow efficiently simulating phase oscillators (the Kuramoto model) on large heterogeneous networks using the Heun’s method. This class uses a pure CUDA implementation of Heun’s method. Therefore, should be faster than TensorFlow implementation also provided by StDoG
Variables: - adjacency (coo matrix) –
- phases (np.ndarray) –
- omegas (np.ndarray) –
- couplings (np.ndarray) –
- total_time (float) –
- dt (float) –
- transient (bool) –
- order_parameter_list (np.ndarray) –