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Merge branch 'master' into cleanup_geometry

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This commit is contained in:
Christopher Lackner 2019-11-02 19:39:00 +01:00
commit c1ede2a89f
3 changed files with 189 additions and 188 deletions
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11
libsrc/core/exception.cpp
View File

@ -14,6 +14,7 @@
#include <memory> #include <memory>
#include <cxxabi.h> #include <cxxabi.h>
#include <signal.h> #include <signal.h>
#include <vector>
namespace ngcore namespace ngcore
{ {
@ -104,11 +105,11 @@ namespace ngcore
if(!funcname.empty()) if(!funcname.empty())
{ {
std::array<char, 256> buffer; std::vector<char> buffer(10240);
int status; int status;
size_t size = buffer.size(); size_t size = buffer.size();
abi::__cxa_demangle(funcname.c_str(), buffer.data(), &size, &status); abi::__cxa_demangle(funcname.c_str(), &buffer[0], &size, &status);
out << "in " << yellow << buffer.data() << reset_shell << '\n'; out << "in " << yellow << &buffer[0] << reset_shell << '\n';
std::string nm_command = "nm " + libname + " | grep " + funcname + " | cut -f 1 -d ' '"; std::string nm_command = "nm " + libname + " | grep " + funcname + " | cut -f 1 -d ' '";
std::string output; std::string output;
@ -145,12 +146,12 @@ namespace ngcore
{ {
std::cerr << "Collecting backtrace..." << std::endl; std::cerr << "Collecting backtrace..." << std::endl;
std::stringstream result; std::stringstream result;
void *bt[1024]; void *bt[100];
int bt_size; int bt_size;
char **bt_syms; char **bt_syms;
int i; int i;
bt_size = backtrace(bt, 1024); bt_size = backtrace(bt, 100);
bt_syms = backtrace_symbols(bt, bt_size); bt_syms = backtrace_symbols(bt, bt_size);
Dl_info info; Dl_info info;
for (i = 1; i < bt_size-1; i++) for (i = 1; i < bt_size-1; i++)

362
tests/pytest/results.json
View File

@ -293,33 +293,33 @@
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@ -516,9 +516,9 @@
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@ -941,14 +941,14 @@
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@ -1014,18 +1014,18 @@
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@ -1074,18 +1074,18 @@
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@ -1162,7 +1162,7 @@
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@ -1367,18 +1367,18 @@
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"ne2d": 3110, "ne2d": 3110,
"ne3d": 8379, "ne3d": 8379,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 3, 27, 91, 210, 452, 680, 983, 1089, 1149, 1165, 1083, 812, 518, 117]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 3, 27, 91, 210, 453, 679, 983, 1088, 1150, 1165, 1083, 812, 518, 117]",
"total_badness": 11964.310541 "total_badness": 11964.310211
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -2229,18 +2229,18 @@
}, },
{ {
"angles_tet": [ "angles_tet": [
15.455, 15.408,
145.04 145.04
], ],
"angles_trig": [ "angles_trig": [
14.648, 14.362,
134.93 134.93
], ],
"ne1d": 240, "ne1d": 240,
"ne2d": 1830, "ne2d": 1830,
"ne3d": 3862, "ne3d": 3864,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 2, 32, 67, 154, 280, 412, 508, 495, 499, 430, 398, 332, 213, 40]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 3, 31, 69, 157, 283, 417, 507, 494, 513, 422, 403, 319, 206, 40]",
"total_badness": 5742.111994 "total_badness": 5758.3866216
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -2255,7 +2255,7 @@
"ne2d": 3110, "ne2d": 3110,
"ne3d": 8253, "ne3d": 8253,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 2, 13, 47, 138, 333, 624, 839, 1047, 1151, 1187, 1166, 945, 608, 153]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 2, 13, 47, 138, 333, 624, 839, 1047, 1151, 1187, 1166, 945, 608, 153]",
"total_badness": 11468.849016 "total_badness": 11468.848993
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -2430,63 +2430,63 @@
"shaft.geo": [ "shaft.geo": [
{ {
"angles_tet": [ "angles_tet": [
11.861, 11.152,
162.65 164.8
], ],
"angles_trig": [ "angles_trig": [
11.536, 13.065,
151.09 153.81
], ],
"ne1d": 708, "ne1d": 708,
"ne2d": 1722, "ne2d": 1722,
"ne3d": 2888, "ne3d": 2786,
"quality_histogram": "[0, 0, 0, 5, 22, 31, 50, 68, 109, 164, 278, 418, 327, 290, 256, 301, 246, 188, 106, 29]", "quality_histogram": "[0, 0, 1, 6, 23, 42, 45, 55, 94, 140, 280, 392, 314, 282, 250, 301, 240, 180, 105, 36]",
"total_badness": 4780.7450312 "total_badness": 4609.6986746
}, },
{ {
"angles_tet": [ "angles_tet": [
14.99, 14.566,
157.83 156.38
], ],
"angles_trig": [ "angles_trig": [
17.101, 17.101,
121.63 120.3
], ],
"ne1d": 410, "ne1d": 410,
"ne2d": 606, "ne2d": 606,
"ne3d": 837, "ne3d": 870,
"quality_histogram": "[0, 0, 0, 0, 0, 3, 0, 5, 21, 42, 43, 54, 83, 94, 118, 110, 89, 78, 51, 46]", "quality_histogram": "[0, 0, 0, 0, 0, 3, 2, 5, 22, 36, 42, 53, 91, 101, 127, 131, 94, 85, 47, 31]",
"total_badness": 1215.3787027 "total_badness": 1263.6238885
}, },
{ {
"angles_tet": [ "angles_tet": [
8.4343, 9.5449,
167.31 167.3
], ],
"angles_trig": [ "angles_trig": [
10.596, 10.216,
155.64 148.27
], ],
"ne1d": 510, "ne1d": 510,
"ne2d": 1004, "ne2d": 1004,
"ne3d": 2038, "ne3d": 2013,
"quality_histogram": "[0, 0, 4, 28, 43, 77, 101, 140, 143, 120, 135, 161, 142, 194, 216, 184, 195, 85, 56, 14]", "quality_histogram": "[0, 0, 2, 11, 38, 79, 90, 131, 106, 114, 113, 172, 155, 218, 217, 207, 190, 98, 58, 14]",
"total_badness": 3926.3340848 "total_badness": 3713.7502435
}, },
{ {
"angles_tet": [ "angles_tet": [
14.303, 14.302,
162.65 162.65
], ],
"angles_trig": [ "angles_trig": [
15.347, 17.889,
147.74 130.85
], ],
"ne1d": 708, "ne1d": 708,
"ne2d": 1722, "ne2d": 1722,
"ne3d": 2795, "ne3d": 2748,
"quality_histogram": "[0, 0, 0, 1, 2, 2, 18, 29, 64, 128, 269, 412, 331, 316, 289, 307, 277, 209, 109, 32]", "quality_histogram": "[0, 0, 0, 0, 5, 3, 17, 26, 54, 118, 266, 416, 341, 298, 267, 329, 256, 205, 110, 37]",
"total_badness": 4321.8306337 "total_badness": 4242.1246898
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -2982,7 +2982,7 @@
"torus.geo": [ "torus.geo": [
{ {
"angles_tet": [ "angles_tet": [
16.896, 16.805,
152.81 152.81
], ],
"angles_trig": [ "angles_trig": [
@ -2991,24 +2991,24 @@
], ],
"ne1d": 0, "ne1d": 0,
"ne2d": 2534, "ne2d": 2534,
"ne3d": 5725, "ne3d": 5726,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 3, 26, 89, 206, 394, 548, 658, 774, 820, 719, 629, 496, 275, 88]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 3, 26, 89, 209, 392, 549, 656, 774, 819, 718, 633, 497, 273, 88]",
"total_badness": 8397.4026608 "total_badness": 8399.0875048
}, },
{ {
"angles_tet": [ "angles_tet": [
1.6289, 1.8454,
174.98 174.07
], ],
"angles_trig": [ "angles_trig": [
4.715, 3.7635,
167.36 166.86
], ],
"ne1d": 0, "ne1d": 0,
"ne2d": 692, "ne2d": 692,
"ne3d": 3327, "ne3d": 3289,
"quality_histogram": "[18, 376, 565, 458, 423, 303, 290, 219, 148, 131, 120, 79, 58, 39, 36, 20, 15, 21, 4, 4]", "quality_histogram": "[22, 357, 521, 490, 397, 337, 276, 212, 158, 125, 86, 85, 59, 35, 37, 25, 30, 23, 11, 3]",
"total_badness": 18184.120092 "total_badness": 17806.714921
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -3036,9 +3036,9 @@
], ],
"ne1d": 0, "ne1d": 0,
"ne2d": 2534, "ne2d": 2534,
"ne3d": 5622, "ne3d": 5613,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 1, 7, 30, 146, 290, 432, 650, 749, 830, 788, 702, 543, 347, 107]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 1, 7, 32, 146, 287, 439, 640, 748, 826, 786, 707, 539, 349, 106]",
"total_badness": 7969.2642686 "total_badness": 7957.8333725
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -3051,9 +3051,9 @@
], ],
"ne1d": 0, "ne1d": 0,
"ne2d": 5894, "ne2d": 5894,
"ne3d": 25266, "ne3d": 25261,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 11, 45, 117, 415, 859, 1688, 2866, 4124, 4942, 5200, 3815, 1184]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 11, 44, 119, 414, 855, 1696, 2860, 4123, 4940, 5200, 3813, 1186]",
"total_badness": 31475.174764 "total_badness": 31467.735079
}, },
{ {
"angles_tet": [ "angles_tet": [
@ -3160,7 +3160,7 @@
"ne2d": 10042, "ne2d": 10042,
"ne3d": 84837, "ne3d": 84837,
"quality_histogram": "[0, 0, 0, 0, 0, 3, 55, 1435, 719, 373, 691, 1186, 2492, 5459, 8935, 13171, 16437, 16966, 12825, 4090]", "quality_histogram": "[0, 0, 0, 0, 0, 3, 55, 1435, 719, 373, 691, 1186, 2492, 5459, 8935, 13171, 16437, 16966, 12825, 4090]",
"total_badness": 108583.90758 "total_badness": 108583.90765
} }
], ],
"twobricks.geo": [ "twobricks.geo": [
@ -3252,7 +3252,7 @@
"ne2d": 346, "ne2d": 346,
"ne3d": 595, "ne3d": 595,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 23, 40, 55, 95, 101, 105, 99, 60, 8]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 23, 40, 55, 95, 101, 105, 99, 60, 8]",
"total_badness": 777.63273621 "total_badness": 777.63275563
} }
], ],
"twocubes.geo": [ "twocubes.geo": [
@ -3344,7 +3344,7 @@
"ne2d": 346, "ne2d": 346,
"ne3d": 595, "ne3d": 595,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 23, 40, 55, 95, 101, 105, 99, 60, 8]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 23, 40, 55, 95, 101, 105, 99, 60, 8]",
"total_badness": 777.63273621 "total_badness": 777.63275563
} }
], ],
"twocyl.geo": [ "twocyl.geo": [
@ -3365,33 +3365,33 @@
}, },
{ {
"angles_tet": [ "angles_tet": [
18.424, 18.404,
153.38 153.38
], ],
"angles_trig": [ "angles_trig": [
27.664, 26.007,
121.51 121.51
], ],
"ne1d": 68, "ne1d": 68,
"ne2d": 100, "ne2d": 100,
"ne3d": 152, "ne3d": 150,
"quality_histogram": "[0, 0, 0, 0, 0, 0, 2, 2, 5, 6, 12, 11, 10, 14, 22, 19, 18, 23, 4, 4]", "quality_histogram": "[0, 0, 0, 0, 0, 0, 2, 2, 4, 6, 12, 12, 8, 13, 24, 18, 18, 23, 4, 4]",
"total_badness": 226.47203657 "total_badness": 222.6797729
}, },
{ {
"angles_tet": [ "angles_tet": [
10.647, 12.34,
163.92 161.32
], ],
"angles_trig": [ "angles_trig": [
11.415, 12.084,
146.97 152.05
], ],
"ne1d": 102, "ne1d": 102,
"ne2d": 238, "ne2d": 238,
"ne3d": 548, "ne3d": 497,
"quality_histogram": "[0, 0, 0, 5, 10, 19, 40, 65, 83, 49, 39, 31, 25, 38, 34, 37, 44, 20, 7, 2]", "quality_histogram": "[0, 0, 0, 2, 11, 31, 40, 56, 65, 43, 34, 21, 26, 25, 30, 31, 43, 28, 8, 3]",
"total_badness": 1137.6676071 "total_badness": 1042.5778658
}, },
{ {
"angles_tet": [ "angles_tet": [

4
tests/pytest/test_tutorials.py
View File

@ -41,8 +41,8 @@ def checkData(mesh, mp, ref):
assert ref['ne3d'] == data['ne3d'] assert ref['ne3d'] == data['ne3d']
assert json.loads(ref['quality_histogram']) == pytest.approx(json.loads(data['quality_histogram']), abs=1, rel=0.4) assert json.loads(ref['quality_histogram']) == pytest.approx(json.loads(data['quality_histogram']), abs=1, rel=0.4)
assert ref['total_badness'] == pytest.approx(data['total_badness'], rel=1e-5) assert ref['total_badness'] == pytest.approx(data['total_badness'], rel=1e-5)
assert ref['angles_trig'] == pytest.approx(data['angles_trig'], rel=1e-5) assert ref['angles_trig'] == pytest.approx(data['angles_trig'], rel=1e-4)
assert ref['angles_tet'] == pytest.approx(data['angles_tet'], rel=1e-5) assert ref['angles_tet'] == pytest.approx(data['angles_tet'], rel=1e-4)
# get tutorials # get tutorials
def getFiles(fileEnding): def getFiles(fileEnding):