Diffusion constraint

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from timeit import default_timer as timer

import matplotlib.pyplot as plt
import numpy as np

import gropt

print(gropt.__file__)

from timeit import default_timer as timer import matplotlib.pyplot as plt import numpy as np import gropt print(gropt.__file__)

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gparams = gropt.GroptParams()
gparams.diff_init()

gparams.add_gmax(.03)
gparams.add_smax(100)
gparams.add_moment(0,0.0)
gparams.add_moment(1,0.0)
gparams.add_moment(2,0.0)
gparams.add_bvalue(106,1)

start_t = timer()
result = gropt.solve(gparams, max_iter=5000)
out = result.X
stop_t = timer()

print(f'Converged: {result.converged}   Solve time: {1000*(stop_t-start_t):.1f} ms')

plt.figure(figsize=(6,3))
tt_ms = np.arange(out.size)*gparams.dt*1e3
plt.plot(tt_ms, out)
plt.show()

gparams = gropt.GroptParams() gparams.diff_init() gparams.add_gmax(.03) gparams.add_smax(100) gparams.add_moment(0,0.0) gparams.add_moment(1,0.0) gparams.add_moment(2,0.0) gparams.add_bvalue(106,1) start_t = timer() result = gropt.solve(gparams, max_iter=5000) out = result.X stop_t = timer() print(f'Converged: {result.converged} Solve time: {1000*(stop_t-start_t):.1f} ms') plt.figure(figsize=(6,3)) tt_ms = np.arange(out.size)*gparams.dt*1e3 plt.plot(tt_ms, out) plt.show()

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