def test_solve_c_lpm():
try:
assert (norm(
ls.solve_c_lpm(
[1, 2, 3, 4, 5], 1, 2, 3, 4, 5, 6, 7, extrap=[1, 2, 3, 4, 5]) -
[0, -3.161, -7.465, -13.3231, -21.298]) < 0.001)
print("solve_c_lpm TEST OK")
except (AssertionError):
print("solve_c_lpm TEST FAIL")
def plot_conc_benchmark(save):
''' Plots the benchmark of the concentration lpm against an analytical solution
Parameters:
----------
save : Bool
If set to true, save figure generated to working directory
Returns:
--------
None
Notes:
This will output a plot to the screen where a plot of the numerical and analytical solution is overlayed on top
dotted broken line is numerical and solid blue line is analytical.
'''
#analytical solution obtained via wolfram, parameters are as follows:
#a = 1, b = 3, P0 = 4, P1 = 5, P = 6, d = 7, Csrc = 1, C(0)=1, M0=3
n = 100
t = np.linspace(0, 5, num=n)
analytical = 3.5 - 2.5 * np.exp(t)
#obtain numerical solution for conc lpm
numerical = ls.solve_c_lpm(t,
1,
3,
4,
5,
7,
3,
1,
testing=[True, t, [1],
np.full(n, 6)])
#plot
f, ax = plt.subplots(1, 1)
ax.plot(t, numerical, 'k-o', label='Numerical')
ax.plot(t, analytical, 'b', label='Analytical')
ax.legend(loc='lower left', prop={'size': 14})
ax.set_title(
'a = 1, b = 3, $P_0$ = 4, $P_1$ = 5, d = 7, $M_0$=3, $C_{src}$ = 1, C(0)=1, and $P$ = 6 [held constant]',
size=10)
f.suptitle(
"Comparison of analytical and numerical solutions to concentration LPM"
)
save_figure = save
if not save_figure:
#Open a new window and display the plot
plt.show()
else:
#Save that plot to a png file
plt.savefig('conc_benchmark.png', dpi=300)
def test_solve_c_lpm():
try:
assert (norm(
ls.solve_c_lpm([0, 1, 2],
2,
3,
4,
5,
6,
7,
8,
testing=[True, [0, 1, 2], [6, 6, 6]]) -
[6, -3.964, -16.293]) < 0.001)
print("solve_c_lpm TEST OK")
except (AssertionError):
print("solve_c_lpm TEST FAIL")