No project description provided
Project description
Install
git clone https://github.com/stdogpkg/cukuramoto/ && cd cukuramoto && python setup.py install
Running
import igraph as ig
import numpy as np
from stdog.utils.misc import ig2sparse
block_size=1024 # gpu parameter
num_couplings = 40
N = 10000
G = ig.Graph.Erdos_Renyi(N, 3/N)
adj = ig2sparse(G)
adj = adj.tocsr()
ptr, indices = adj.indptr, adj.indices
couplings = np.linspace(0, 4, num_couplings).astype("float32")
omegas = np.tan(( np.arange(1,N+1)*np.pi)/N - ((N+1.)*np.pi)/(2.0*N) ).astype("float32")
phases = np.random.uniform(-np.pi, np.pi, int(num_couplings*N)).astype("float32")
import cukuramoto
dt = 0.1
num_temps = 100
simulation = cukuramoto.Heuns(
N, block_size, omegas, phases, couplings,
indices, ptr)
simulation.heuns(num_temps, dt)
order_parameter_list = simulation.get_order_parameter(num_temps, dt)
order_parameter_list = order_parameter_list.reshape(num_couplings, num_temps)
r = np.mean(order_parameter_list, axis=1)
stdr = np.std(order_parameter_list, axis=1)
import matplotlib.pyplot as plt
plt.ion()
fig, ax1 = plt.subplots()
ax1.plot(couplings,r,'.-')
ax2 = ax1.twinx()
ax2.plot(couplings,stdr,'r.-')
plt.show()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cukuramoto-1.0.0.tar.gz
(24.5 kB
view hashes)