s = (Simulation().
set_pragma_autocompact(True).
add([
ODESystemMass(f_decay_a, [DotMap(attr={ 'sub-a': 'u' }), DotMap(attr={ 'sub-a': 'd' })], dt=0.1),
ODESystemMass(f_decay_b, [DotMap(attr={ 'sub-b': 'u' }), DotMap(attr={ 'sub-b': 'd' })], dt=0.1),
Group(m=1000, attr={ 'sub-a': 'u' }),
Group(m=1000, attr={ 'sub-b': 'u' }),
probe_u,
probe_d
]).
run(1000)
)
# ----------------------------------------------------------------------------------------------------------------------
# (4) Results:
# Time series plot (group mass) -- Undecayed:
# series = [
# { 'var': 'pau', 'lw': 2, 'linestyle': '-', 'marker': '+', 'color': 'red', 'markersize': 0, 'lbl': 'Substance A' },
# { 'var': 'pbu', 'lw': 2, 'linestyle': '--', 'marker': 'o', 'color': 'blue', 'markersize': 0, 'lbl': 'Substance B' }
# ]
# probe_u.plot(series, fpath_fig=None, figsize=(20,4), legend_loc='upper right', dpi=150)
# Time series plot (group mass) -- Decayed:
series = [
{ 'var': 'pad', 'lw': 2, 'linestyle': '-', 'marker': '+', 'color': 'red', 'markersize': 0, 'lbl': 'Substance A' },
{ 'var': 'pbd', 'lw': 2, 'linestyle': '--', 'marker': 'o', 'color': 'blue', 'markersize': 0, 'lbl': 'Substance B' }
]
probe_d.plot(series, fpath_fig=None, figsize=(20,4), legend_loc='lower right', dpi=150)
Group(m=950, attr={ 'flu': 's' }),
Group(m= 50, attr={ 'flu': 'i' }),
probe
]).
run(1000)
)
# ----------------------------------------------------------------------------------------------------------------------
# (4) Results:
# Time series plot (group mass):
cmap = plt.get_cmap('tab20')
series = [
{ 'var': 'ps', 'lw': 2, 'linestyle': '--', 'marker': '+', 'color': cmap(0), 'markersize': 0, 'lbl': 'Susceptible' },
{ 'var': 'pi', 'lw': 2, 'linestyle': '-', 'marker': 'o', 'color': cmap(4), 'markersize': 0, 'lbl': 'Infectious' },
{ 'var': 'pr', 'lw': 2, 'linestyle': ':', 'marker': 'x', 'color': cmap(6), 'markersize': 0, 'lbl': 'Recovered' }
]
probe.plot(series, fpath_fig=None, figsize=(24,8), legend_loc='upper right', dpi=150)
# Time series plot (numeric integrator history):
# h = s.rules[0].get_hist()
# plt.plot(h[0], h[1][0], 'b-', h[0], h[1][1], 'g-', h[0], h[1][2], 'r-') # S-blue, I-green, R-red
# plt.show()
# Phase plot (numeric integrator history):
# h = s.rules[0].get_hist()
# plt.plot(h[1][0], h[1][1], 'k-')
# plt.show()
'lbl': 'Blue @ A'
}, {
'var': 'p1',
'lw': 2,
'linestyle': '-',
'marker': '',
'color': 'red',
'markersize': 0,
'lbl': 'Red @ A'
}, {
'var': 'p2',
'lw': 2,
'linestyle': '-',
'marker': '',
'color': 'navy',
'markersize': 0,
'lbl': 'Blue @ B'
}, {
'var': 'p3',
'lw': 2,
'linestyle': '-',
'marker': '',
'color': 'firebrick',
'markersize': 0,
'lbl': 'Red @ B'
}]
fig = probe_sim.plot(series, figsize=(8, 6))
fig.suptitle(f'Segregation PRAM Model - {runs} iterations', y=0.965)
fig.savefig("Segregation_PRAM_out")