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Tests/[Genet,2023]/plot_disp_error_vs_regul_strength-ref/square-translation-tagging-discrete-linear-equilibrated-tractions-normal.dat 0 → 100644
View file @ 16d89f95
# noise_level regul_level disp_err_avg disp_err_std
0.0 0.99 0.00028417829801934103 0.0
0.0 0.8 0.0003457815404307538 0.0
0.0 0.4 0.00048022273764362124 0.0
0.0 0.2 0.0005187809178222003 0.0
0.0 0.1 0.0005727119360465418 0.0
0.0 0.05 0.0006031837067736637 0.0
0.0 0.025 0.0006152841902575706 0.0
0.0 0.0125 0.0006327861685430558 0.0
0.0 0.001 0.00051934522280663 0.0
0.1 0.99 0.010808800056539232 0.0005362249539470191
0.1 0.8 0.010998468754528798 0.000513820171066674
0.1 0.4 0.011445329187696335 0.000499032559731241
0.1 0.2 0.012050804289884066 0.0004919115862185821
0.1 0.1 0.012848654311811569 0.0005231416696091857
0.1 0.05 0.013773600764662258 0.0005722444400992171
0.1 0.025 0.014795863755446309 0.0006029591540843283
0.1 0.0125 0.015961096090562656 0.0006104985419226959
0.1 0.001 0.045490139274622865 0.0012476881321506167
0.2 0.99 0.026694547123949218 0.0018301458601376595
0.2 0.8 0.027197602224481005 0.0017351067479708829
0.2 0.4 0.028112744459432126 0.0017628395543780606
0.2 0.2 0.029358346059759188 0.0017821687207432296
0.2 0.1 0.03101443574992488 0.0017770034262748675
0.2 0.05 0.03295340205044829 0.0016801447023513908
0.2 0.025 0.03511307172840204 0.0016211818594785413
0.2 0.0125 0.037663108582119 0.0015421612224518777
0.2 0.001 0.11150907609292038 0.012440521530165165
0.3 0.99 0.04448140844311659 0.0026469651118007234
0.3 0.8 0.04552478515713853 0.0023049185210227796
0.3 0.4 0.047631497199161266 0.0021862014198355084
0.3 0.2 0.04992015264542798 0.0022558429655571265
0.3 0.1 0.05279810070342519 0.0025947856850757787
0.3 0.05 0.05664129894279596 0.0032576144883590267
0.3 0.025 0.06170224878168764 0.00417203677801766
0.3 0.0125 0.06867557970895152 0.007062262540548239
0.3 0.001 0.3482779609304819 0.05642379778753999
Tests/[Genet,2023]/plot_disp_error_vs_regul_strength-ref/square-translation-tagging-discrete-linear-equilibrated-tractions-tangential.dat 0 → 100644
View file @ 16d89f95
# noise_level regul_level disp_err_avg disp_err_std
0.0 0.99 0.0004939777824945341 0.0
0.0 0.8 0.0004895933401073531 0.0
0.0 0.4 0.00047927496566707535 0.0
0.0 0.2 0.000492425073157513 0.0
0.0 0.1 0.0005249913432411667 0.0
0.0 0.05 0.0005676021212820686 0.0
0.0 0.025 0.0005827204691458032 0.0
0.0 0.0125 0.0006175980727173215 0.0
0.0 0.001 0.00051934522280663 0.0
0.1 0.99 0.010613237991169455 0.0008870640037359933
0.1 0.8 0.01061608591396033 0.0008887130148058874
0.1 0.4 0.010696601938418893 0.0008862295690914342
0.1 0.2 0.010881254201210493 0.0008775412294714439
0.1 0.1 0.011197697976652992 0.0008632619481391089
0.1 0.05 0.011690782342297847 0.0008274495349259126
0.1 0.025 0.012426661742411188 0.0007765157397798059
0.1 0.0125 0.013483391893395095 0.0007080595461771215
0.1 0.001 0.045490139274622865 0.0012476881321506167
0.2 0.99 0.02562151209051621 0.0018314105215969164
0.2 0.8 0.025632476314662776 0.0018154371667222003
0.2 0.4 0.02585983877259581 0.001789177307108364
0.2 0.2 0.026273179953875587 0.0016777537253578286
0.2 0.1 0.0269348453751898 0.0015919311249241867
0.2 0.05 0.027916182205298005 0.001522095104091548
0.2 0.025 0.029346206388701758 0.0015195867614792005
0.2 0.0125 0.031467330912025276 0.001414247394787981
0.2 0.001 0.11150907609292038 0.012440521530165165
0.3 0.99 0.04242314118063274 0.0023897216627500875
0.3 0.8 0.0424498220339548 0.002428189672830974
0.3 0.4 0.04274883364688399 0.002415496643651663
0.3 0.2 0.04353475413042809 0.0022954375211470114
0.3 0.1 0.04498996962241809 0.001978302238239705
0.3 0.05 0.04698834655954552 0.002057910139721028
0.3 0.025 0.049998910060690085 0.0022150083155624742
0.3 0.0125 0.05475595492218235 0.0028456279193838133
0.3 0.001 0.3482779609304819 0.05642379778753999
Tests/[Genet,2023]/plot_disp_error_vs_regul_strength-ref/square-translation-tagging-discrete-linear-equilibrated.dat 0 → 100644
View file @ 16d89f95
# noise_level regul_level disp_err_avg disp_err_std
0.0 0.99 0.000894913670686505 0.0
0.0 0.8 0.0008948327179141007 0.0
0.0 0.4 0.00089290201603703 0.0
0.0 0.2 0.0008862638827011979 0.0
0.0 0.1 0.0008769778732517048 0.0
0.0 0.05 0.0008720787937504464 0.0
0.0 0.025 0.0008721458661482371 0.0
0.0 0.0125 0.0008720579255821412 0.0
0.0 0.001 0.00051934522280663 0.0
0.1 0.99 0.016105411896270468 0.0007258011373982465
0.1 0.8 0.016109243064581977 0.0007311772104687502
0.1 0.4 0.01611884665680863 0.0007287207364561438
0.1 0.2 0.016153000991802082 0.0007210462526533489
0.1 0.1 0.016230004855970682 0.0007082043176172654
0.1 0.05 0.016368822091143095 0.0006847327203703247
0.1 0.025 0.016604795025722083 0.0006625048426703339
0.1 0.0125 0.0169986088823817 0.0006257721154723544
0.1 0.001 0.045490139274622865 0.0012476881321506167
0.2 0.99 0.03853231705879241 0.0023641006823163723
0.2 0.8 0.03854061551737574 0.002369832562862271
0.2 0.4 0.0384773210839831 0.0024015709300898133
0.2 0.2 0.03841481763141202 0.002393691493218177
0.2 0.1 0.03855678428371194 0.0024759738828724876
0.2 0.05 0.03891614350264622 0.002536896350436595
0.2 0.025 0.0393994408405145 0.0025418442830418557
0.2 0.0125 0.04041462131455802 0.0025202659781279895
0.2 0.001 0.11150907609292038 0.012440521530165165
0.3 0.99 0.09165374169581116 0.04289249439570307
0.3 0.8 0.0913182215815278 0.041783107099622595
0.3 0.4 0.09191025152684898 0.041253316677020445
0.3 0.2 0.09179321972673232 0.040810191824664915
0.3 0.1 0.09093594800390138 0.03989890323008269
0.3 0.05 0.09715721408187769 0.043353204628432396
0.3 0.025 0.09635428308632522 0.040053949614048
0.3 0.0125 0.0958144737147211 0.03686015146166034
0.3 0.001 0.3482779609304819 0.05642379778753999
Tests/[Genet,2023]/plot_disp_error_vs_regul_strength-ref/square-translation-tagging-discrete-simple-elastic.dat 0 → 100644
View file @ 16d89f95
# noise_level regul_level disp_err_avg disp_err_std
0.0 0.99 5.334322109343638e-05 0.0
0.0 0.8 5.0768752468158725e-05 0.0
0.0 0.4 0.00011648584764873425 0.0
0.0 0.2 0.00022072287190903758 0.0
0.0 0.1 0.00032829309066352265 0.0
0.0 0.05 0.00042525576218150983 0.0
0.0 0.025 0.0005455545875389306 0.0
0.0 0.0125 0.0006936116847384577 0.0
0.0 0.001 0.00051934522280663 0.0
0.1 0.99 0.0030587897095403953 0.0005450315912807827
0.1 0.8 0.003328476672127558 0.00047496561214216735
0.1 0.4 0.005063220055420892 0.00023749556277365404
0.1 0.2 0.007155359335828481 0.00016354311598568624
0.1 0.1 0.00978370935321516 0.0001399879454544922
0.1 0.05 0.013009855277245602 0.00015009732361750787
0.1 0.025 0.016783569142765627 0.00017171216567023282
0.1 0.0125 0.021152445392149406 0.00020809950386278266
0.1 0.001 0.045490139274622865 0.0012476881321506167
0.2 0.99 0.007836581635251808 0.0015530568647414628
0.2 0.8 0.008416287134760886 0.0014545723857287637
0.2 0.4 0.011948296730618318 0.0011416429677772362
0.2 0.2 0.01637155198318624 0.0011253263218829561
0.2 0.1 0.02190267357880416 0.0010209862479467395
0.2 0.05 0.02884985695202552 0.0008350126792848217
0.2 0.025 0.03738351904901983 0.0006720086143020984
0.2 0.0125 0.0477715160651345 0.0009338555773492819
0.2 0.001 0.11150907609292038 0.012440521530165165
0.3 0.99 0.02280264444506426 0.008968485548405113
0.3 0.8 0.021471246987665428 0.007264514399909607
0.3 0.4 0.0213046658320458 0.0032656852230482647
0.3 0.2 0.027035125405266248 0.002043189697793837
0.3 0.1 0.03606952480495309 0.0015824225277902297
0.3 0.05 0.047306980812514166 0.001434055870590802
0.3 0.025 0.06147573687252247 0.0016673492217698157
0.3 0.0125 0.07918268862780517 0.0019135388789697587
0.3 0.001 0.3482779609304819 0.05642379778753999
Tests/[Genet,2023]/plot_disp_error_vs_regul_strength-ref/square-translation-tagging-discrete-simple-equilibrated.dat 0 → 100644
View file @ 16d89f95
# noise_level regul_level disp_err_avg disp_err_std
0.0 0.99 0.00089491711664884 0.0
0.0 0.8 0.0008948587196891053 0.0
0.0 0.4 0.0008928375052203912 0.0
0.0 0.2 0.0008862684730681632 0.0
0.0 0.1 0.0008770314556670836 0.0
0.0 0.05 0.0008723137556135655 0.0
0.0 0.025 0.0008730238032763445 0.0
0.0 0.0125 0.000874111722227979 0.0
0.0 0.001 0.00051934522280663 0.0
0.1 0.99 0.01610541784764838 0.0007257892661009569
0.1 0.8 0.01610921916594025 0.0007311810092881902
0.1 0.4 0.01611869349482291 0.0007286521342049172
0.1 0.2 0.016152168918725954 0.0007209719760162287
0.1 0.1 0.01622811769811038 0.0007076543001709818
0.1 0.05 0.016363940350526775 0.0006840550036146843
0.1 0.025 0.016596657560431376 0.0006544480487288193
0.1 0.0125 0.01697780854883297 0.0006185083150726038
0.1 0.001 0.045490139274622865 0.0012476881321506167
0.2 0.99 0.038532292126443615 0.0023641083910049404
0.2 0.8 0.03854041890926114 0.0023697950224300175
0.2 0.4 0.03847642957292373 0.00240126034441312
0.2 0.2 0.038415936628001884 0.0023894135701014274
0.2 0.1 0.03855595137253273 0.002470497347057294
0.2 0.05 0.03889993708986826 0.0025353143563041462
0.2 0.025 0.03940092907329074 0.002554026860141877
0.2 0.0125 0.04034834821980717 0.0025189610859531787
0.2 0.001 0.11150907609292038 0.012440521530165165
0.3 0.99 0.09165362691387817 0.042892557902672185
0.3 0.8 0.0913282506964351 0.04177830572254213
0.3 0.4 0.09334974669555635 0.042465481858771734
0.3 0.2 0.09399334630214862 0.04317162624313504
0.3 0.1 0.09028586681441339 0.03865280729375347
0.3 0.05 0.09495793214763824 0.040516138519015164
0.3 0.025 0.09776432242913413 0.04397321836986062
0.3 0.0125 0.09449071066882184 0.03595686308479016
0.3 0.001 0.3482779609304819 0.05642379778753999
Tests/[Genet,2023]/plot_disp_error_vs_regul_strength.py 0 → 100644
View file @ 16d89f95
#coding=utf8
########################################################################
import numpy
import os
import myPythonLibrary as mypy
import dolfin_warp as dwarp
########################################################################
def plot_disp_error_vs_regul_strength(
images_folder : str ,
sol_folder : str ,
structure_type : str ,
deformation_type : str ,
texture_type : str ,
regul_type : str ,
noise_level_lst : list ,
n_runs_for_noisy_images : int ,
regul_level_lst : list ,
mesh_size : float = 0.1 ,
regul_level_for_zero : float = 1e-3 ,
generate_datafile : bool = True ,
generate_datafile_with_limited_precision : bool = False,
generate_plotfile : bool = True ,
generate_plot : bool = True ):
print ("images_folder:" , images_folder )
print ("sol_folder:" , sol_folder )
print ("structure_type:" , structure_type )
print ("deformation_type:", deformation_type)
print ("texture_type:" , texture_type )
print ("regul_type:" , regul_type )
script_basename = "plot_disp_error_vs_regul_strength"
if not os.path.exists(script_basename):
os.mkdir(script_basename)
datafile_basename = script_basename
datafile_basename += "/"+structure_type
datafile_basename += "-"+deformation_type
datafile_basename += "-"+texture_type
datafile_basename += "-"+regul_type
########################################################################
if (generate_datafile) or (generate_datafile_with_limited_precision):
if (generate_datafile): data_printer = mypy.DataPrinter(
names=["noise_level", "regul_level", "disp_err_avg", "disp_err_std"],
filename=datafile_basename+".dat",
limited_precision=False)
if (generate_datafile_with_limited_precision): data_printer2 = mypy.DataPrinter(
names=["noise_level", "regul_level", "disp_err_avg", "disp_err_std"],
filename=datafile_basename+"-limited_precision.dat",
limited_precision="True")
if (generate_datafile): data_printer3 = mypy.DataPrinter(
names=["noise_level", "regul_level", "disp_err"],
filename=datafile_basename+"-all_points.dat",
limited_precision=False)
if (structure_type in ("square", "disc", "ring")):
ref_disp_array_name = "displacement"
elif (structure_type in ("heart")):
ref_disp_array_name = "U"
else: assert (0)
for noise_level in noise_level_lst:
for regul_level in regul_level_lst:
print ("noise_level:", noise_level)
print ("regul_level:", regul_level)
if (regul_level == 0.0):
regul_level_for_write = regul_level_for_zero
else:
regul_level_for_write = regul_level
n_runs = n_runs_for_noisy_images if (noise_level > 0) else 1
disp_err_lst = []
for k_run in range(1, n_runs+1):
print ("k_run:", k_run)
images_basename = structure_type
images_basename += "-"+deformation_type
images_basename += "-"+texture_type
images_basename += "-noise="+str(noise_level)
if (n_runs > 1):
images_basename += "-run="+str(k_run).zfill(2)
sol_basename = images_basename
sol_basename += "-h="+str(mesh_size)
sol_basename += "-"+regul_type
sol_basename += "-regul="+str(regul_level)
disp_err = dwarp.compute_displacement_error(
working_folder=sol_folder,
working_basename=sol_basename,
ref_folder=images_folder,
ref_basename=structure_type+"-"+deformation_type+"-h=0.1",
working_disp_array_name="displacement",
ref_disp_array_name=ref_disp_array_name,
verbose=0)
print ("disp_err:", disp_err)
if (generate_datafile): data_printer3.write_line([noise_level, regul_level_for_write, disp_err])
disp_err_lst.append(disp_err)
disp_err_avg = numpy.mean(disp_err_lst)
disp_err_std = numpy.std(disp_err_lst)
print ("disp_err_avg:", disp_err_avg)
print ("disp_err_std:", disp_err_std)
if (generate_datafile ): data_printer.write_line([noise_level, regul_level_for_write, disp_err_avg, disp_err_std])
if (generate_datafile_with_limited_precision): data_printer2.write_line([noise_level, regul_level_for_write, disp_err_avg, disp_err_std])
if (generate_datafile ): data_printer.write_line(); data_printer.write_line()
if (generate_datafile_with_limited_precision): data_printer2.write_line(); data_printer2.write_line()
if (generate_datafile ): data_printer3.write_line(); data_printer3.write_line()
if (generate_datafile ): data_printer.close()
if (generate_datafile_with_limited_precision): data_printer2.close()
if (generate_datafile ): data_printer3.close()
########################################################################
if (generate_plotfile):
plotfile = open(datafile_basename+".plt", "w")
plotfile.write('''\
set terminal pdf enhanced size 4,3; datafile_ext = "pdf"
load "Set1.plt"
set linestyle 1 pointtype 0
set linestyle 2 pointtype 0
set linestyle 3 pointtype 0
set linestyle 4 pointtype 0
set linestyle 5 pointtype 0
set linestyle 6 pointtype 0
set linestyle 7 pointtype 0
set linestyle 8 pointtype 0
set linestyle 9 pointtype 0
set style fill transparent solid 0.1 noborder
datafile_basename = "'''+datafile_basename+'''"
datafile_name = datafile_basename.".dat"
poinfile_name = datafile_basename."-all_points.dat"
set output datafile_basename.".".datafile_ext
set title "'''+regul_type+'''"
# set title "'''+structure_type+'''-'''+deformation_type+'''-'''+regul_type+'''"
set key right box opaque textcolor variable width -1
set grid
set xlabel "regularization strength"
set xrange ['''+str(regul_level_for_zero)+''':1]
set xtics add ("0" '''+str(regul_level_for_zero)+''')
set xtics add ("0.99" 1e0)
set format x "%g"
set logscale x
set ylabel "normalized displacement error (%)"
set yrange [1e-1:1e+2]
set logscale y
plot ''')
for k_noise_level,noise_level in enumerate(noise_level_lst):
plotfile.write(((''' ''')*(k_noise_level>0))+'''datafile_name index '''+str(k_noise_level)+''' using ($2):(100*$3) with lines linestyle '''+str(k_noise_level+1)+''' linewidth 3 title "noise = '''+str(noise_level)+'''"'''+''',\\\n''')
#plotfile.write( ''' ''' +'''datafile_name index '''+str(k_noise_level)+''' using ($2):(100*$3):(100*$4) with errorbars linestyle '''+str(k_noise_level+1)+''' notitle''' +''',\\\n''')
#plotfile.write( ''' ''' +'''datafile_name index '''+str(k_noise_level)+''' using ($2):(100*$3-100*$4):(100*$3+100*$4) with filledcurves linestyle '''+str(k_noise_level+1)+''' notitle''' +((''',\\
plotfile.write( ''' ''' +'''poinfile_name index '''+str(k_noise_level)+''' using ($2):(100*$3) with points linestyle '''+str(k_noise_level+1)+''' notitle''' +((''',\\
''')*(k_noise_level<len(noise_level_lst)-1)))
plotfile.close()
########################################################################
if (generate_plot):
os.system("gnuplot "+datafile_basename+".plt")
os.system("convert -density 300 "+datafile_basename+".pdf"+" "+datafile_basename+".png")
########################################################################
if (__name__ == "__main__"):
import fire
fire.Fire(plot_disp_error_vs_regul_strength)
Tests/test_compute_regularization_energies.py 0 → 100644
View file @ 16d89f95
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Tests/test_generate_images_from_Model.py 0 → 100644
View file @ 16d89f95
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Tests/test_generate_images_from_Struct.py 0 → 100644
View file @ 16d89f95
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Tests/test_reduced_warp-ref/cube-rotation-all-strains.dat 0 → 100644
View file @ 16d89f95
#k_frame Err_avg Err_std Ecc_avg Ecc_std Ell_avg Ell_std Erc_avg Erc_std Erl_avg Erl_std Ecl_avg Ecl_std
0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 0.004629702772945166 0.0 0.003407413139939308 0.0 0.0016850474057719111 0.0 -0.0012902331072837114 0.0 0.00011935704242205247 0.0 0.0001694990787655115 0.0
2 0.0024934762623161077 0.0 0.0027501643635332584 0.0 0.001840141718275845 0.0 -0.0012133653508499265 0.0 -0.0005730708944611251 0.0 -0.00043151932186447084 0.0
3 0.00337977334856987 0.0 0.0022687693126499653 0.0 0.0017218717839568853 0.0 -0.00039677266613580287 0.0 -0.0002957665710709989 0.0 -0.0010454701259732246 0.0
4 0.0035385838709771633 0.0 0.0028843453619629145 0.0 0.0017311685951426625 0.0 -0.0021433313377201557 0.0 -0.00029201165307313204 0.0 -0.00012462609447538853 0.0
5 0.0015430341009050608 0.0 0.0027987295761704445 0.0 0.0012578798923641443 0.0 -0.0004460901254788041 0.0 -0.00020644141477532685 0.0 -0.0004581794491969049 0.0
6 0.003166780574247241 0.0 0.002939527155831456 0.0 0.0016164116095751524 0.0 -0.0005895877256989479 0.0 3.6184726923238486e-05 0.0 -0.0005750684067606926 0.0
7 0.0026378529146313667 0.0 0.0018884214805439115 0.0 0.0018579739844426513 0.0 -0.0019291063072159886 0.0 -0.00031296093948185444 0.0 -0.0001308170467382297 0.0
8 0.002505834912881255 0.0 0.0020912201143801212 0.0 0.0016387715004384518 0.0 -0.0011261244071647525 0.0 -0.00020224634499754757 0.0 -0.0002808494318742305 0.0
9 0.0020054327324032784 0.0 0.0016470839036628604 0.0 0.0018844997975975275 0.0 -0.0010187539737671614 0.0 -0.00024658828624524176 0.0 -0.0004892792203463614 0.0
10 0.0003206762485206127 0.0 0.000568015209864825 0.0 0.000319346523610875 0.0 -0.0032576974481344223 0.0 -0.0017955085495486856 0.0 -0.0021377485245466232 0.0
Tests/test_reduced_warp-ref/cube-rotation-rotation-strains.dat 0 → 100644
View file @ 16d89f95
#k_frame Err_avg Err_std Ecc_avg Ecc_std Ell_avg Ell_std Erc_avg Erc_std Erl_avg Erl_std Ecl_avg Ecl_std
0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 -1.676215610757481e-08 0.0 8.810070006859405e-09 0.0 1.7777892935555428e-08 0.0 1.0039198361511126e-09 0.0 6.278449982133338e-13 0.0 -2.714760360955637e-10 0.0
2 -1.1134595467865438e-08 0.0 6.602142832434765e-09 0.0 -3.5246507934516558e-09 0.0 4.0946818158360543e-10 0.0 1.0910434777855471e-09 0.0 -1.6101424638037543e-09 0.0
3 -8.635846704407868e-09 0.0 1.790180803595831e-08 0.0 -1.5966572064485263e-08 0.0 1.88267290646138e-09 0.0 4.0906772413862313e-10 0.0 -1.407592264968116e-09 0.0
4 -1.361421753109937e-09 0.0 6.0532676648961115e-09 0.0 -2.563485956841305e-08 0.0 1.2802909843401267e-09 0.0 1.8615646801833918e-09 0.0 6.414080377936671e-10 0.0
5 1.003583971481703e-08 0.0 -2.9389196853912836e-08 0.0 -1.1582512726704408e-08 0.0 -1.4466401410118124e-09 0.0 4.042536583259704e-10 0.0 -3.2454566811779273e-10 0.0
6 -1.8583316219178414e-08 0.0 -1.7025714171836626e-08 0.0 2.6417806608947103e-08 0.0 1.0555503138220956e-09 0.0 -5.09403963455668e-10 0.0 5.013615078652833e-10 0.0
7 -1.2131830651185282e-08 0.0 8.284130714741877e-09 0.0 6.595098689388124e-09 0.0 2.1396515670346616e-09 0.0 -7.439872329317865e-11 0.0 -8.103669818515513e-11 0.0
8 2.2741312832863514e-08 0.0 -2.2131908750111506e-08 0.0 -2.3900601497928164e-09 0.0 1.1001345390226902e-09 0.0 7.472911872641319e-11 0.0 1.6393322810337452e-10 0.0
9 2.4566505274492556e-08 0.0 3.247324853461464e-09 0.0 -1.7395906937167638e-08 0.0 -2.0489480945240501e-10 0.0 -3.189172190221079e-11 0.0 -1.005237212914345e-11 0.0
10 -9.44877731612337e-10 0.0 2.4172916113229803e-08 0.0 2.4693775912965066e-08 0.0 2.4043136925833153e-10 0.0 -4.117866117536728e-11 0.0 1.7973265237225533e-11 0.0
Tests/test_reduced_warp-ref/cube-scaling-all-strains.dat 0 → 100644
View file @ 16d89f95
#k_frame Err_avg Err_std Ecc_avg Ecc_std Ell_avg Ell_std Erc_avg Erc_std Erl_avg Erl_std Ecl_avg Ecl_std
0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 0.024251069873571396 0.0 0.00018869031919166446 0.0 0.0001891673164209351 0.0 0.0003573070571292192 0.0 0.0003571710840333253 0.0 -0.00014842009113635868 0.0
2 0.04381919652223587 0.0 0.0005194715340621769 0.0 0.000520187197253108 0.0 0.00038145744474604726 0.0 0.00038120115641504526 0.0 -0.00012791478366125375 0.0
3 0.054514314979314804 0.0 0.0006071278476156294 0.0 0.0006070085801184177 0.0 0.0004917706246487796 0.0 0.0004917973419651389 0.0 -0.0001064796160790138 0.0
4 0.08838944882154465 0.0 0.0003158355539198965 0.0 0.00031678954837843776 0.0 0.000300459039863199 0.0 0.0003001783916261047 0.0 -2.7250584025750868e-05 0.0
5 0.10377706587314606 0.0 0.00015749224985484034 0.0 0.00015796917432453483 0.0 5.500734914676286e-05 0.0 5.487778253154829e-05 0.0 -2.1641300918417983e-05 0.0
6 0.1221187636256218 0.0 -0.00012282967509236187 0.0 -0.00012247210543137044 0.0 -0.0005718281026929617 0.0 -0.0005719048203900456 0.0 4.901972260995535e-06 0.0
7 0.14686228334903717 0.0 0.00033710733987390995 0.0 0.0003374650259502232 0.0 0.00030292762676253915 0.0 0.0003027931961696595 0.0 -0.00012013605009997264 0.0
8 0.1613456755876541 0.0 0.0005728825926780701 0.0 0.0005727633251808584 0.0 0.00048060022527351975 0.0 0.00048067214083857834 0.0 -0.00016298347327392548 0.0
9 0.1878327578306198 0.0 0.0004683669831138104 0.0 0.00046848627971485257 0.0 -7.232871666928986e-06 0.0 -7.30867805032176e-06 0.0 -5.731832789024338e-05 0.0
10 0.210282564163208 0.0 0.0002953586808871478 0.0 0.0002954779483843595 0.0 0.00016746979963500053 0.0 0.0001674335217103362 0.0 -5.108838377054781e-05 0.0
Tests/test_reduced_warp-ref/cube-scaling-scaling-strains.dat 0 → 100644
View file @ 16d89f95
#k_frame Err_avg Err_std Ecc_avg Ecc_std Ell_avg Ell_std Erc_avg Erc_std Erl_avg Erl_std Ecl_avg Ecl_std
0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 0.0007633498171344399 0.0 8.821526535029989e-06 0.0 8.821526535029989e-06 0.0 -2.4930607585121195e-20 2.3900980262647657e-19 4.1766888830776847e-20 2.8087838493962063e-19 4.548061169980118e-21 7.54314945656091e-21
2 0.0012282513780519366 0.0 1.8835246009984985e-05 0.0 1.8835246009984985e-05 0.0 4.2863053864067426e-19 6.712947696596968e-19 2.7204889734488126e-19 7.381715176751782e-19 5.6717185624379045e-21 1.059095481115188e-20
3 0.0013420038158074021 0.0 2.098105505865533e-05 0.0 2.098105505865533e-05 0.0 1.5960047314896903e-19 5.546033955281438e-19 2.520709879024525e-19 5.315669826709992e-19 4.020475959029307e-21 8.872061809066259e-21
4 0.0013420038158074021 0.0 2.098105505865533e-05 0.0 2.098105505865533e-05 0.0 1.5960047314896903e-19 5.546033955281438e-19 2.520709879024525e-19 5.315669826709992e-19 4.020475959029307e-21 8.872061809066259e-21
5 0.0013322156155481935 0.0 3.707477662828751e-05 0.0 3.707477662828751e-05 0.0 3.5164430116606613e-19 5.770468865191415e-19 4.670181820764171e-19 5.502073870628987e-19 1.695623064704377e-20 1.6999634876379305e-20
6 0.0005363471573218703 0.0 2.217317342001479e-05 0.0 2.217317342001479e-05 0.0 2.16836114484421e-19 2.6046080872283215e-19 2.134289208540239e-19 2.471086960638387e-19 3.769280928940308e-21 1.1303444123342549e-20
7 0.00013471556303557009 0.0 4.482369695324451e-05 0.0 4.482369695324451e-05 0.0 -1.2572272355224675e-20 6.24861679598019e-20 1.5039333685402677e-21 7.025485669864979e-20 1.0666934784894322e-20 3.456392772109667e-20
8 -8.27874246169813e-05 0.0 5.209581649978645e-05 0.0 5.209581649978645e-05 0.0 -5.530862204725572e-20 6.262034037900384e-20 -2.1184225272982796e-20 7.09196751464924e-20 5.759037933653762e-21 1.767562988398584e-20
9 -0.00021646064124070108 0.0 5.281110861687921e-05 0.0 5.281110861687921e-05 0.0 -4.0463259051638594e-20 6.838315958763958e-20 -7.71011922799573e-20 4.655898357410454e-20 4.1802010887274105e-20 2.9316814944802825e-20
10 -0.00022116837499197572 0.0 4.386997898109257e-05 0.0 4.386997898109257e-05 0.0 -6.111967968201756e-20 9.650599757037411e-20 -4.4245010571447675e-20 8.571607835783233e-20 -1.1411705105541053e-20 1.9048673855468837e-20
Tests/test_reduced_warp-ref/cube-shear-all-strains.dat 0 → 100644
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Tests/test_reduced_warp-ref/cube-shear-shear-strains.dat 0 → 100644
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Tests/test_reduced_warp-ref/cube-translation-all-strains.dat 0 → 100644
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