|
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib
import matplotlib.axes
from chemreac import ReactionDiffusion
from chemreac.integrate import run
from chemreac.util.plotting import (
coloured_spy, plot_jacobian, plot_per_reaction_contribution,
plot_C_vs_t_in_bin, plot_C_vs_x, plot_C_vs_t_and_x, plot_fields,
plot_solver_linear_error, plot_solver_linear_excess_error,
)
from chemreac.util.testing import slow
matplotlib.use('Agg') # travis-ci has no DISPLAY env var.
def _get_decay_rd(N):
return ReactionDiffusion(2, [[0]], [[1]], [3.14], N, D=[0.0, 0.0])
def _get_decay_Cref(N, y0, tout):
y0 = np.asarray(y0)
tout = tout.reshape((tout.size, 1))
factor = np.exp(-(tout-tout[0])*3.14)
Cref = np.hstack([
np.hstack((y0[i*2]*factor, y0[i*2]*(1 - factor) + y0[i*2+1]))
for i in range(N)])
return Cref.reshape((tout.size, N, 2))
def test_get_decay_Cref():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
Cref = _get_decay_Cref(N, y0, tout)
assert np.allclose(Cref, integr.yout)
def test_plot_jacobian():
# A -> B
rd = _get_decay_rd(1)
y0 = [3.0, 1.0]
tout = np.linspace(0, 3.0, 7)
integr = run(rd, y0, tout)
axes = plot_jacobian(rd, integr.tout, integr.yout, [0, 1])
for ax in axes:
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_per_reaction_contribution():
rd = _get_decay_rd(1)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]
integr = run(rd, y0, tout)
axes = plot_per_reaction_contribution(integr, [0, 1])
for ax in axes:
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_C_vs_t_in_bin():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
ax = plot_C_vs_t_in_bin(rd, tout, integr.yout, 0)
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_C_vs_x():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
ax = plot_C_vs_x(rd, tout, integr.yout, [0, 1], 6)
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_C_vs_t_and_x():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
ax = plot_C_vs_t_and_x(rd, tout, integr.yout, 0)
import mpl_toolkits.mplot3d
assert isinstance(ax, mpl_toolkits.mplot3d.Axes3D)
def test_plot_fields():
# modulation in x means x_center
# A -> B # mod1 (x**2)
# C -> D # mod1 (x**2)
# E -> F # mod2 (sqrt(x))
# G -> H # no modulation
k = np.array([3.0, 7.0, 13.0, 22.0])
N = 5
n = 8
D = np.zeros(n)
x = np.linspace(3, 7, N+1)
xc = x[:-1] + np.diff(x)/2
fields = [
[xc[i]*xc[i] for i in range(N)],
[xc[i]*xc[i] for i in range(N)],
[xc[i]**0.5 for i in range(N)]
]
g_values = [
[-k[0], k[0], 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, -k[1], k[1], 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, -k[2], k[2], 0.0, 0.0],
]
rd = ReactionDiffusion(
n,
[[6]],
[[7]],
k=k[3:], N=N, D=D, x=x, fields=fields,
g_values=g_values
)
ax = plot_fields(rd, indices=[0, 2])
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_solver_linear_error():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
Cref = _get_decay_Cref(N, y0, tout)
ax = plot_solver_linear_error(integr, Cref)
assert isinstance(ax, matplotlib.axes.Axes)
def test_plot_solver_linear_excess_error():
N = 3
rd = _get_decay_rd(N)
tout = np.linspace(0, 3.0, 7)
y0 = [3.0, 1.0]*N
integr = run(rd, y0, tout)
Cref = _get_decay_Cref(N, y0, tout)
ax = plot_solver_linear_excess_error(integr, Cref)
assert isinstance(ax, matplotlib.axes.Axes)
@slow
def test_coloured_spy():
from matplotlib.axes import Axes
A = np.arange(9).reshape((3, 3))
for log in (False, True, -5):
ax_im, ax_cb = coloured_spy(A, log=log)
assert isinstance(ax_im, Axes)
assert isinstance(ax_cb, Axes)
|
