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GHA1 num und ana richtig. Tests nach Beispielen aus Panou 2013

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Hendrik Möllersmann
2025-12-10 11:45:41 +01:00
parent 936b7c56f9
commit 946d028fae
6 changed files with 335 additions and 102 deletions
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test_algorithms.py Normal file
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import GHA_triaxial.numeric_examples_panou as nep
import ellipsoide
from GHA_triaxial.panou_2013_2GHA_num import gha2_num
from GHA_triaxial.panou import gha1_ana, gha1_num
import numpy as np
import time
def test():
ell = ellipsoide.EllipsoidTriaxial.init_name("BursaSima1980round")
tables = nep.get_tables()
diffs_gha1_num = []
diffs_gha1_ana = []
diffs_gha2_num = []
times_gha1_num = []
times_gha1_ana = []
times_gha2_num = []
for table in tables:
diffs_gha1_num.append([])
diffs_gha1_ana.append([])
diffs_gha2_num.append([])
times_gha1_num.append([])
times_gha1_ana.append([])
times_gha2_num.append([])
for example in table:
beta0, lamb0, beta1, lamb1, c, alpha0, alpha1, s = example
P0 = ell.ell2cart(beta0, lamb0)
P1 = ell.ell2cart(beta1, lamb1)
start = time.perf_counter()
try:
P1_num = gha1_num(ell, P0, alpha0, s, 10000)
end = time.perf_counter()
diff_P1_num = np.linalg.norm(P1 - P1_num)
except:
end = time.perf_counter()
diff_P1_num = None
time_gha1_num = end - start
start = time.perf_counter()
try:
P1_ana = gha1_ana(ell, P0, alpha0, s, 50)
end = time.perf_counter()
diff_P1_ana = np.linalg.norm(P1 - P1_ana)
except:
end = time.perf_counter()
diff_P1_ana = None
time_gha1_ana = end - start
start = time.perf_counter()
try:
alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=1000)
end = time.perf_counter()
diff_s_num = abs(s - s_num)
except:
end = time.perf_counter()
diff_s_num = None
time_gha2_num = None
time_gha2_num = end - start
diffs_gha1_num[-1].append(diff_P1_num)
diffs_gha1_ana[-1].append(diff_P1_ana)
diffs_gha2_num[-1].append(diff_s_num)
times_gha1_num[-1].append(time_gha1_num)
times_gha1_ana[-1].append(time_gha1_ana)
times_gha2_num[-1].append(time_gha2_num)
print(diffs_gha1_num, diffs_gha1_ana, diffs_gha2_num)
print(times_gha1_num, times_gha1_ana, times_gha2_num)
def display():
diffs = [[{'gha1_num': np.float64(3.410763124264611e-05), 'gha1_ana': np.float64(3.393273802112796e-05), 'gha2_num': np.float64(3.3931806683540344e-05)}, {'gha1_num': np.float64(0.0008736425000530604), 'gha1_ana': np.float64(0.0008736458415010259), 'gha2_num': None}, {'gha1_num': np.float64(0.0007739730058338136), 'gha1_ana': np.float64(0.0007739621469802854), 'gha2_num': np.float64(1.5832483768463135e-07)}, {'gha1_num': np.float64(0.00010554956741100295), 'gha1_ana': np.float64(8.814246009944831), 'gha2_num': np.float64(4.864111542701721e-05)}, {'gha1_num': np.float64(0.0002135908394614854), 'gha1_ana': np.float64(0.0002138610897967267), 'gha2_num': np.float64(5.0179407158866525)}, {'gha1_num': np.float64(0.00032727226891456654), 'gha1_ana': np.float64(0.00032734569198545905), 'gha2_num': np.float64(9.735533967614174e-05)}, {'gha1_num': np.float64(0.0005195973303787956), 'gha1_ana': np.float64(0.0005197766935509641), 'gha2_num': None}], [{'gha1_num': np.float64(1.780250537652368e-05), 'gha1_ana': np.float64(1.996805145339501e-05), 'gha2_num': np.float64(1.8164515495300293e-05)}, {'gha1_num': np.float64(4.8607540473363564e-05), 'gha1_ana': np.float64(2205539.954949392), 'gha2_num': None}, {'gha1_num': np.float64(0.00017376854985685854), 'gha1_ana': np.float64(328124.1513636429), 'gha2_num': np.float64(0.17443156614899635)}, {'gha1_num': np.float64(5.83429352558999e-05), 'gha1_ana': np.float64(0.01891628037258558), 'gha2_num': np.float64(1.4207654744386673)}, {'gha1_num': np.float64(0.0006421087024666934), 'gha1_ana': np.float64(0.0006420400127297228), 'gha2_num': np.float64(0.12751091085374355)}, {'gha1_num': np.float64(0.0004456207867164434), 'gha1_ana': np.float64(0.0004455649707698245), 'gha2_num': np.float64(0.00922046648338437)}, {'gha1_num': np.float64(0.0002340879908275419), 'gha1_ana': np.float64(0.00023422217242111216), 'gha2_num': np.float64(0.001307751052081585)}], [{'gha1_num': np.float64(976.6580096633622), 'gha1_ana': np.float64(976.6580096562798), 'gha2_num': np.float64(6.96033239364624e-05)}, {'gha1_num': np.float64(2825.2936643258527), 'gha1_ana': np.float64(2794.954866417055), 'gha2_num': np.float64(1.3615936040878296e-05)}, {'gha1_num': np.float64(1248.8942058074501), 'gha1_ana': np.float64(538.5550561841195), 'gha2_num': np.float64(3.722589462995529e-05)}, {'gha1_num': np.float64(2201.1793359793814), 'gha1_ana': np.float64(3735.376499414938), 'gha2_num': np.float64(1.4525838196277618e-05)}, {'gha1_num': np.float64(2262.134819997246), 'gha1_ana': np.float64(25549.567793410763), 'gha2_num': np.float64(9.328126907348633e-06)}, {'gha1_num': np.float64(2673.219788119847), 'gha1_ana': np.float64(21760.866677295206), 'gha2_num': np.float64(8.635222911834717e-06)}, {'gha1_num': np.float64(1708.758419275875), 'gha1_ana': np.float64(3792.1128807063437), 'gha2_num': np.float64(2.4085864424705505e-05)}], [{'gha1_num': np.float64(0.7854659044152204), 'gha1_ana': np.float64(0.785466068424286), 'gha2_num': np.float64(0.785466069355607)}, {'gha1_num': np.float64(237.79878717216718), 'gha1_ana': np.float64(1905080.064324282), 'gha2_num': None}, {'gha1_num': np.float64(55204.601699830164), 'gha1_ana': np.float64(55204.60175211949), 'gha2_num': None}, {'gha1_num': np.float64(12766.348063015519), 'gha1_ana': np.float64(12766.376619517901), 'gha2_num': np.float64(12582.786206113175)}, {'gha1_num': np.float64(29703.049988324146), 'gha1_ana': np.float64(29703.056427749252), 'gha2_num': np.float64(28933.668131249025)}, {'gha1_num': np.float64(43912.03007182513), 'gha1_ana': np.float64(43912.03007528712), 'gha2_num': None}, {'gha1_num': np.float64(28522.29828970693), 'gha1_ana': np.float64(28522.29830145182), 'gha2_num': None}, {'gha1_num': np.float64(17769.115549537233), 'gha1_ana': np.float64(17769.115549483362), 'gha2_num': np.float64(17769.121286311187)}]]
arr = []
for table in diffs:
for example in table:
arr.append([example['gha1_num'], example['gha1_ana'], example['gha2_num']])
arr = np.array(arr)
pass
if __name__ == "__main__":
# test()
display()