def runtests(p, problem, parallel=False, tol=None):
from nodepy import rk, ivp, conv
import numpy as np
from nodepy import loadmethod
if tol is None:
tol = [10.**(-m) for m in range(2, 11)]
# Load methods
print 'constructing Ex-Euler'
ex = rk.extrap_pair(p)
print 'constructing Ex-midpoint'
exm = rk.extrap_pair(p / 2, 'midpoint')
print 'constructing DC-Euler'
dc = rk.DC_pair(p - 1)
if p == 6:
ork = rk.loadRKM('CMR6')
elif p == 8:
ork = rk.loadRKM('DP8')
elif p == 10:
ork = loadmethod.load_rkpair_from_file('rk108curtis.txt')
elif p == 12:
ork = loadmethod.load_rkpair_from_file('rk129hiroshi.txt')
if problem == 'suite':
myivp = ivp.detest_suite_minus()
else:
myivp = ivp.detest(problem)
methods = [ork, ex, exm, dc]
[work, err] = conv.ptest(methods,
myivp,
tol,
verbosity=1,
parallel=parallel)
plot_efficiency(methods, err, work)
fname = 'eff_' + problem + '_' + str(p)
if parallel:
fname = fname + '_par'
plt.ylabel('Sequential derivative evaluations')
plt.savefig(fname + '.pdf')
def run_tolerances(tols, p=8):
from nodepy import rk
from nodepy import loadmethod
err = np.zeros((4, len(tols)))
work = np.zeros((4, len(tols)))
rkm = rk.loadRKM("BS5").__num__()
q_ref, dx, iwork = stegoton(rkm, tol=1.0e-13)
rkm = rk.extrap_pair(p / 2, "midpoint").__num__()
rke = rk.extrap_pair(p).__num__()
rkd = rk.DC_pair(p - 1, grid="cheb").__num__()
if p == 6:
ork = rk.loadRKM("CMR6")
elif p == 8:
ork = rk.loadRKM("DP8")
elif p == 10:
ork = loadmethod.load_rkpair_from_file("rk108curtis.txt")
elif p == 12:
ork = loadmethod.load_rkpair_from_file("rk129hiroshi.txt")
for i, tol in enumerate(tols):
q, dx, iwork = stegoton(ork, tol)
err[0, i] = np.linalg.norm(q - q_ref, 1) * dx
work[0, i] = iwork * len(rkm)
q, dx, iwork = stegoton(rke, tol)
err[2, i] = np.linalg.norm(q - q_ref, 1) * dx
work[2, i] = iwork * len(rke)
q, dx, iwork = stegoton(rkm, tol)
err[1, i] = np.linalg.norm(q - q_ref, 1) * dx
work[1, i] = iwork * len(rkm)
q, dx, iwork = stegoton(rkd, tol)
err[3, i] = np.linalg.norm(q - q_ref, 1) * dx
work[3, i] = iwork * len(rkd)
return err, work, ork
def run_tolerances(tols, p=8):
from nodepy import rk
from nodepy import loadmethod
err = np.zeros((4, len(tols)))
work = np.zeros((4, len(tols)))
rkm = rk.loadRKM('BS5').__num__()
q_ref, dx, iwork = stegoton(rkm, tol=1.e-13)
rkm = rk.extrap_pair(p / 2, 'midpoint').__num__()
rke = rk.extrap_pair(p).__num__()
rkd = rk.DC_pair(p - 1, grid='cheb').__num__()
if p == 6:
ork = rk.loadRKM('CMR6')
elif p == 8:
ork = rk.loadRKM('DP8')
elif p == 10:
ork = loadmethod.load_rkpair_from_file('rk108curtis.txt')
elif p == 12:
ork = loadmethod.load_rkpair_from_file('rk129hiroshi.txt')
for i, tol in enumerate(tols):
q, dx, iwork = stegoton(ork, tol)
err[0, i] = np.linalg.norm(q - q_ref, 1) * dx
work[0, i] = iwork * len(rkm)
q, dx, iwork = stegoton(rke, tol)
err[2, i] = np.linalg.norm(q - q_ref, 1) * dx
work[2, i] = iwork * len(rke)
q, dx, iwork = stegoton(rkm, tol)
err[1, i] = np.linalg.norm(q - q_ref, 1) * dx
work[1, i] = iwork * len(rkm)
q, dx, iwork = stegoton(rkd, tol)
err[3, i] = np.linalg.norm(q - q_ref, 1) * dx
work[3, i] = iwork * len(rkd)
return err, work, ork
def runtests(p,problem,parallel=False,tol=None):
from nodepy import rk, ivp, conv
import numpy as np
from nodepy import loadmethod
if tol is None:
tol = [10.**(-m) for m in range(2,11)]
# Load methods
print 'constructing Ex-Euler'
ex = rk.extrap_pair(p);
print 'constructing Ex-midpoint'
exm = rk.extrap_pair(p/2,'midpoint');
print 'constructing DC-Euler'
dc = rk.DC_pair(p-1);
if p == 6:
ork = rk.loadRKM('CMR6')
elif p == 8:
ork = rk.loadRKM('DP8')
elif p == 10:
ork = loadmethod.load_rkpair_from_file('rk108curtis.txt')
elif p == 12:
ork = loadmethod.load_rkpair_from_file('rk129hiroshi.txt')
if problem == 'suite':
myivp = ivp.detest_suite_minus()
else:
myivp = ivp.detest(problem);
methods = [ork,ex,exm,dc]
[work,err] = conv.ptest(methods,myivp,tol,verbosity=1,parallel=parallel);
plot_efficiency(methods, err, work)
fname = 'eff_'+problem+'_'+str(p)
if parallel:
fname = fname + '_par'
plt.ylabel('Sequential derivative evaluations')
plt.savefig(fname+'.pdf')
def erk(u0, f, t_eval, method="RK44", args=()):
rkbt = rk.loadRKM(method).__num__()
u = np.zeros((t_eval.size, *u0.shape), dtype=u0.dtype)
u[0, ...] = u0
t_step = len(t_eval) - 1
rate = 20
for k, t1 in enumerate(t_eval[1:], start=1):
t_percent = np.int(np.around(k / t_step * rate))
print("\r[{}{}]({}/{})".format("#" * t_percent,
"+" * (rate - t_percent), k, t_step),
end="")
t0 = t_eval[k - 1]
dt = t1 - t0
u[k, ...] = erk_step(t0, u[k - 1, ...], dt, f, rkbt, args)
print()
return u
def write_numipedia():
"""
Main function to write the whole numipedia site.
Loops over all methods in rk.loadRKM('All') and writes a page for each.
TODO:
- Add parameterized method families
- Add more methods
"""
from nodepy import rk
methods = rk.loadRKM('All')
for key,method in methods.iteritems():
fname = method.shortname+'.html'
print fname
#write_page(method, fname=fname)
write_method_page(method, fname=fname)
write_index_page(methods)
import numpy as np
ivpoptim = IVPOPTIM()
if testkey == '2OD': #system of differential equations
ivpoptim.u0 = u0 #initial parameters
ivpoptim.T = 3.0 #Final time of integration
ivpoptim.rhs = lambda t, u: (s0[0] * u - s0[1] * u
) #right side of ODE system
ivpoptim.dt0 = 0.01 #time step
else:
raise Exception('Unknown Detest problem')
ivpoptim.name = testkey
ivpoptim.description = 'Problem ' + testkey + ' of the non-stiff DETEST suite.'
return ivpoptim
rk44 = rk.loadRKM('RK44') #load runge-kutta
ivp = detest('2OD')
myivp = ivp #load initial parameters from problem
t, u = rk44(myivp) #approximate soluton of problem
u4 = np.array([u[1667], u[3334], u[5001]])
t4 = np.array([t[1667], t[3334], t[5001]])
pogr1 = ([(u4[0] - u1), (u4[1] - u2), (u4[2] - u3)]
) #difference between model and fact values when time is 1,2,3
norma1 = round(
ln.norm(pogr1[0]), 4
) #the distance between the points of the model and fact values when time is 1
norma2 = round(
ln.norm(pogr1[1]), 4
) #the distance between the points of the model and fact values when time is 2
norma3 = round(
ln.norm(pogr1[2]), 4
if testkey == 'Differential equation for exact solution': #differential equation
#with parameter which is (-1), i.e. we think, that a0=-1,
# it is necessary to find "experimental" solution which is identically to exact solution
ivpoptim.u0 = u0 #initial value
ivpoptim.T = 3.0 #Final time of integration
ivpoptim.rhs = lambda t, z: -2 * t * (z**2) #right side of ODE
ivpoptim.dt0 = 0.01 #time step
else:
raise Exception('Unknown Detest problem')
ivpoptim.name = testkey
ivpoptim.description = 'Problem ' + testkey + ' of the non-stiff DETEST suite.'
return ivpoptim
rk44 = rk.loadRKM('RK44') #load runge-kutta
ivp = detest('Differential equation for exact solution')
myivp = ivp #load initial parameters from problem
t, z = rk44(myivp) #approximate soluton of problem
z1 = np.array([z[1667], z[3334],
z[5001]]) #"experimental" solutions in moment of time 1,2,3
def detest(testkey): #Description of problem
import numpy as np
ivpoptim = IVPOPTIM()
if testkey == 'Differential equation': #differential equation with parameter a0 which is not (-1)
#print('\nDifferential equation -----')
ivpoptim.u0 = u0 #initial value
ivpoptim.T = 3.0 #Final time of integration
ivpoptim.rhs = lambda t, u: a0 * t * (u**2) #right side of ODE
s_start=4
s_end=12
order = range(s_start,s_end+1)
I_R = np.zeros((4,len(order)))
I_I = np.zeros((4,len(order)))
I_R_scaled = np.zeros((4,len(order)))
I_I_scaled = np.zeros((4,len(order)))
for i,p in enumerate(order):
print p
if p == 4:
ork = rk.loadRKM('Merson43')
if p == 6:
ork = rk.loadRKM('CMR6')
elif p == 8:
ork = rk.loadRKM('DP8')
elif p == 10:
ork = loadmethod.load_rkpair_from_file('rk108curtis.txt')
elif p == 12:
ork = loadmethod.load_rkpair_from_file('rk129hiroshi.txt')
pp,q = ork.stability_function()
I_R[0,i] = stability_function.real_stability_interval(pp,q)
I_I[0,i] = stability_function.imaginary_stability_interval(pp,q)
I_R_scaled[0,i] = I_R[0,i]/len(ork)
I_I_scaled[0,i] = I_I[0,i]/len(ork)
