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[Maxima-discuss] Testsuite results with ecl 16.1.3
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From: Raymond T. <toy...@gm...> - 2018-09-14 23:27:42
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I notice that when I run the testsuite with ecl 16.1.3, many of the
tests that were marked as failures are now passing. Can we update
these so that they're not failures for ecl anymore?
What is the version of ecl we're testing against these days?
The tests that now pass but are marked as failing:
Running tests in rtest6:
********************** Problem 44 (line 164) ***************
Input:
(string(2.0e-7), (%% = 2.0e-7) or (%% = 2.0E-7) or %%)
Result:
true
Running tests in rtest14:
********************** Problem 201 (line 1292) ***************
Input:
test_bessel(bessel_j(- 2.3, 1.0 + %i),
0.1920598664138632 - 0.5158676904105332 %i, 14)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 233 (line 1416) ***************
Input:
test_bessel(bessel_y(2.3, 1.0 + %i), (- 0.2476879981252862)
+ 0.7595467103431256 %i, 15)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 234 (line 1420) ***************
Input:
test_bessel(bessel_y(- 2.3, 1.0 + %i),
(- 0.1570442638685963) + 0.5821870838327466 %i, 14)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 249 (line 1475) ***************
Input:
test_bessel(bessel_i(- 2.5, - 1.5), (- 0.8015666610717216) %i, 14)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 250 (line 1478) ***************
Input:
test_bessel(bessel_i(- 2.5, 1.5), 0.8015666610717216, 14)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 251 (line 1482) ***************
Input:
test_bessel(bessel_i(- 2.3, - 1.5), 0.373394526583023 - 0.5139334755917659 %i,
15)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 252 (line 1485) ***************
Input:
test_bessel(bessel_i(- 2.3, 1.5), 0.6352567117441515, 15)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 267 (line 1544) ***************
Input:
test_bessel(bessel_i(- 2.3, 1.0 + %i),
(- 0.4053256245784623) - 0.3724481230406298 %i, 14)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 297 (line 1661) ***************
Input:
test_bessel(bessel_k(2.3, 1.0 + %i), (- 0.6635905911278042)
- 1.02588948495693 %i, 15)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 298 (line 1665) ***************
Input:
test_bessel(bessel_k(- 2.3, 1.0 + %i),
(- 0.6635905911278042) - 1.02588948495693 %i, 13)
Result:
true
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 307 (line 1757) ***************
Input:
test_wronskian(lambda([n, z], expand(w_jj(n, %i z))),
(- 2.0) sin(n %pi)
lambda([n, z], ------------------), 1.0e-8, 10)
%i z %pi
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 310 (line 1779) ***************
Input:
2.0
test_wronskian(lambda([n, z], w_jy(n, z %i)), lambda([n, z], --------),
z %i %pi
1.0e-8, 10)
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 312 (line 1795) ***************
Input:
(- 2.0) sin(n %pi)
test_wronskian(w_ii, lambda([n, z], ------------------), 1.0e-10, 5)
z %pi
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 315 (line 1818) ***************
Input:
1
test_wronskian(w_ik, lambda([n, z], -), 1.0e-10, 5)
z
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
********************** Problem 319 (line 1846) ***************
Input:
- 4
test_wronskian(lambda([v, z], w_h1h2(v, z %i)), lambda([v, z], -----),
%pi z
1.0e-13, 5)
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
Running tests in rtest16:
********************** Problem 50 (line 268) ***************
Input:
block([L1 : [[1.2E-10, 1.2E-9, 1.2E-8, 1.2E-7, 1.2E-6, 1.2E-5, 1.2E-4, 0.0012,
0.012, 0.12, 1.2, 1.2E+1, 1.2E+2, 1.2E+3, 1.2E+4, 1.2E+5, 1.2E+6, 1.2E+7,
1.2E+8, 1.2E+9, 1.2E+10], [1.23E-10, 1.23E-9, 1.23E-8, 1.23E-7, 1.23E-6,
1.23E-5, 1.23E-4, 0.00123, 0.0123, 0.123, 1.23, 12.3, 1.23E+2, 1.23E+3,
1.23E+4, 1.23E+5, 1.23E+6, 1.23E+7, 1.23E+8, 1.23E+9, 1.23E+10],
[1.234E-10, 1.234E-9, 1.234E-8, 1.234E-7, 1.234E-6, 1.234E-5, 1.234E-4,
0.001234, 0.01234, 0.1234, 1.234, 12.34, 123.4, 1.234E+3, 1.234E+4, 1.234E+5,
1.234E+6, 1.234E+7, 1.234E+8, 1.234E+9, 1.234E+10],
[1.2344E-10, 1.2344E-9, 1.2344E-8, 1.2344E-7, 1.2344E-6, 1.2344E-5, 1.2344E-4,
0.0012344, 0.012344, 0.12344, 1.2344, 12.344, 123.44, 1234.4, 1.2344E+4,
1.2344E+5, 1.2344E+6, 1.2344E+7, 1.2344E+8, 1.2344E+9, 1.2344E+10],
[1.23443E-10, 1.23443E-9, 1.23443E-8, 1.23443E-7, 1.23443E-6, 1.23443E-5,
1.23443E-4, 0.00123443, 0.0123443, 0.123443, 1.23443, 12.3443, 123.443,
1234.43, 12344.3, 1.23443E+5, 1.23443E+6, 1.23443E+7, 1.23443E+8, 1.23443E+9,
1.23443E+10], [1.234432E-10, 1.234432E-9, 1.234432E-8, 1.234432E-7,
1.234432E-6, 1.234432E-5, 1.234432E-4, 0.001234432, 0.01234432, 0.1234432,
1.234432, 12.34432, 123.4432, 1234.432, 12344.32, 123443.2, 1.234432E+6,
1.234432E+7, 1.234432E+8, 1.234432E+9, 1.234432E+10],
[1.2344321E-10, 1.2344321E-9, 1.2344321E-8, 1.2344321E-7, 1.2344321E-6,
1.2344321E-5, 1.2344321E-4, 0.0012344321, 0.012344321, 0.12344321, 1.2344321,
12.344321, 123.44321, 1234.4321, 12344.321, 123443.21, 1234432.1,
1.2344321E+7, 1.2344321E+8, 1.2344321E+9, 1.2344321E+10],
[1.23443211E-10, 1.23443211E-9, 1.23443211E-8, 1.23443211E-7, 1.23443211E-6,
1.23443211E-5, 1.23443211E-4, 0.00123443211, 0.0123443211, 0.123443211,
1.23443211, 12.3443211, 123.443211, 1234.43211, 12344.3211, 123443.211,
1234432.11, 1.23443211E+7, 1.23443211E+8, 1.23443211E+9, 1.23443211E+10],
[1.234432112E-10, 1.234432112E-9, 1.234432112E-8, 1.234432112E-7,
1.234432112E-6, 1.234432112E-5, 1.234432112E-4, 0.001234432112, 0.01234432112,
0.1234432112, 1.234432112, 12.34432112, 123.4432112, 1234.432112, 12344.32112,
123443.2112, 1234432.112, 1.234432112E+7, 1.234432112E+8, 1.234432112E+9,
1.234432112E+10], [1.2344321123E-10, 1.2344321123E-9, 1.2344321123E-8,
1.2344321123E-7, 1.2344321123E-6, 1.2344321123E-5, 1.2344321123E-4,
0.0012344321123, 0.012344321123, 0.12344321123, 1.2344321123, 12.344321123,
123.44321123, 1234.4321123, 12344.321123, 123443.21123, 1234432.1123,
1.2344321123E+7, 1.2344321123E+8, 1.2344321123E+9, 1.2344321123E+10],
[1.23443211234E-10, 1.23443211234E-9, 1.23443211234E-8, 1.23443211234E-7,
1.23443211234E-6, 1.23443211234E-5, 1.23443211234E-4, 0.00123443211234,
0.0123443211234, 0.123443211234, 1.23443211234, 12.3443211234, 123.443211234,
1234.43211234, 12344.3211234, 123443.211234, 1234432.11234, 1.23443211234E+7,
1.23443211234E+8, 1.23443211234E+9, 1.23443211234E+10],
[1.234432112344E-10, 1.234432112344E-9, 1.234432112344E-8, 1.234432112344E-7,
1.234432112344E-6, 1.234432112344E-5, 1.234432112344E-4, 0.001234432112344,
0.01234432112344, 0.1234432112344, 1.234432112344, 12.34432112344,
123.4432112344, 1234.432112344, 12344.32112344, 123443.2112344,
1234432.112344, 1.234432112344E+7, 1.234432112344E+8, 1.234432112344E+9,
1.234432112344E+10], [1.2344321123443E-10, 1.2344321123443E-9,
1.2344321123443E-8, 1.2344321123443E-7, 1.2344321123443E-6,
1.2344321123443E-5, 1.2344321123443E-4, 0.0012344321123443, 0.012344321123443,
0.12344321123443, 1.2344321123443, 12.344321123443, 123.44321123443,
1234.4321123443, 12344.321123443, 123443.21123443, 1234432.1123443,
1.2344321123443E+7, 1.2344321123443E+8, 1.2344321123443E+9,
1.2344321123443E+10], [1.23443211234432E-10, 1.23443211234432E-9,
1.23443211234432E-8, 1.23443211234432E-7, 1.23443211234432E-6,
1.23443211234432E-5, 1.23443211234432E-4, 0.00123443211234432,
0.0123443211234432, 0.123443211234432, 1.23443211234432, 12.3443211234432,
123.443211234432, 1234.43211234432, 12344.3211234432, 123443.211234432,
1234432.11234432, 1.23443211234432E+7, 1.23443211234432E+8,
1.23443211234432E+9, 1.23443211234432E+10],
[1.234432112344321E-10, 1.234432112344321E-9, 1.234432112344321E-8,
1.234432112344321E-7, 1.234432112344321E-6, 1.234432112344321E-5,
1.234432112344321E-4, 0.001234432112344321, 0.01234432112344321,
0.1234432112344321, 1.234432112344321, 12.34432112344321, 123.4432112344321,
1234.432112344321, 12344.32112344321, 123443.2112344321, 1234432.112344321,
1.234432112344321E+7, 1.234432112344321E+8, 1.234432112344321E+9,
1.234432112344321E+10], [1.234432112344321E-10, 1.234432112344321E-9,
1.234432112344321E-8, 1.234432112344321E-7, 1.234432112344321E-6,
1.234432112344321E-5, 1.234432112344321E-4, 0.001234432112344321,
0.01234432112344321, 0.1234432112344321, 1.234432112344321, 12.34432112344321,
123.4432112344321, 1234.432112344321, 12344.32112344321, 123443.2112344321,
1234432.112344321, 1.234432112344321E+7, 1.234432112344321E+8,
1.234432112344321E+9, 1.234432112344321E+10],
[1.234432112344321E-10, 1.234432112344321E-9, 1.234432112344321E-8,
1.234432112344321E-7, 1.234432112344321E-6, 1.234432112344321E-5,
1.234432112344321E-4, 0.001234432112344321, 0.01234432112344321,
0.1234432112344321, 1.234432112344321, 12.34432112344321, 123.4432112344321,
1234.432112344321, 12344.32112344321, 123443.2112344321, 1234432.112344321,
1.234432112344321E+7, 1.234432112344321E+8, 1.234432112344321E+9,
1.234432112344321E+10], [1.234432112344321E-10, 1.234432112344321E-9,
1.234432112344321E-8, 1.234432112344321E-7, 1.234432112344321E-6,
1.234432112344321E-5, 1.234432112344321E-4, 0.001234432112344321,
0.01234432112344321, 0.1234432112344321, 1.234432112344321, 12.34432112344321,
123.4432112344321, 1234.432112344321, 12344.32112344321, 123443.2112344321,
1234432.112344321, 1.234432112344321E+7, 1.234432112344321E+8,
1.234432112344321E+9, 1.234432112344321E+10],
[1.234432112344321E-10, 1.234432112344321E-9, 1.234432112344321E-8,
1.234432112344321E-7, 1.234432112344321E-6, 1.234432112344321E-5,
1.234432112344321E-4, 0.001234432112344321, 0.01234432112344321,
0.1234432112344321, 1.234432112344321, 12.34432112344321, 123.4432112344321,
1234.432112344321, 12344.32112344321, 123443.2112344321, 1234432.112344321,
1.234432112344321E+7, 1.234432112344321E+8, 1.234432112344321E+9,
1.234432112344321E+10]], L2 : block([foo : 1.234432112344321],
n
makelist(block([fpprintprec : m], makelist(string(foo 10 ), n, - 10, 10)), m,
2, 20))], map(lambda([s1, s2], if sequalignore(s1, s2) then true
else s2 # s1), flatten(L1), flatten(L2)), delete(true, %%))
Result:
[]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
Running tests in rtest8:
********************** Problem 104 (line 399) ***************
Input:
ev(e5, au = 0, omega = 2)
Result:
[0.4000000000000001, 2.216570948815925e-11, 175, 0]
... Which was correct, but was expected to be wrong due to a known bug in
Maxima or in the Lisp it was compiled with.
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