diff --git a/src/core_pmatrix.c b/src/core_pmatrix.c index 77aedb5..0a5d6bd 100644 --- a/src/core_pmatrix.c +++ b/src/core_pmatrix.c @@ -179,38 +179,44 @@ PLL_EXPORT int pll_core_update_pmatrix(double ** pmatrix, } else { + /* NOTE: in order to deal with numerical issues in cases when Qt -> 0, we + * use a trick suggested by Ben Redelings and explained here: + * https://github.com/xflouris/libpll/issues/129#issuecomment-304004005 + * In short, we use expm1() to compute (exp(Qt) - I), and then correct + * for this by adding an identity matrix I in the very end */ + /* exponentiate eigenvalues */ if (pinvar > PLL_MISC_EPSILON) { for (j = 0; j < states; ++j) - expd[j] = exp(evals[j] * rates[n] * branch_lengths[i] + expd[j] = expm1(evals[j] * rates[n] * branch_lengths[i] / (1.0 - pinvar)); } else { for (j = 0; j < states; ++j) - expd[j] = exp(evals[j] * rates[n] * branch_lengths[i]); + expd[j] = expm1(evals[j] * rates[n] * branch_lengths[i]); } - /* check if all values of expd are approximately one */ - for (k=0, j=0; j < states; ++j) - if ((expd[j] > PLL_ONE_MIN) && (expd[j] < PLL_ONE_MAX)) - ++k; - - /* if yes, it means we are multiplying the inverse eigenvectors matrix - by the eigenvectors matrix, and essentially the resulting pmatrix is - the identity matrix. This is done to prevent having numerical issues - (negative entries in the pmatrix) which can occur due to the - different floating point representations of one in expd */ - if (k == states) - { - /* set identity matrix */ - for (j = 0; j < states; ++j) - for (k = 0; k < states; ++k) - pmat[j*states_padded + k] = (j == k) ? 1 : 0; - - continue; - } +// /* check if all values of expd are approximately one */ +// for (k=0, j=0; j < states; ++j) +// if ((expd[j] > PLL_ONE_MIN) && (expd[j] < PLL_ONE_MAX)) +// ++k; +// +// /* if yes, it means we are multiplying the inverse eigenvectors matrix +// by the eigenvectors matrix, and essentially the resulting pmatrix is +// the identity matrix. This is done to prevent having numerical issues +// (negative entries in the pmatrix) which can occur due to the +// different floating point representations of one in expd */ +// if (k == states && 0) +// { +// /* set identity matrix */ +// for (j = 0; j < states; ++j) +// for (k = 0; k < states; ++k) +// pmat[j*states_padded + k] = (j == k) ? 1 : 0; +// +// continue; +// } for (j = 0; j < states; ++j) for (k = 0; k < states; ++k) @@ -220,7 +226,8 @@ PLL_EXPORT int pll_core_update_pmatrix(double ** pmatrix, { for (k = 0; k < states; ++k) { - pmat[j*states_padded+k] = 0; +// pmat[j*states_padded+k] = 0; + pmat[j*states_padded+k] = (j==k) ? 1.0 : 0; for (m = 0; m < states; ++m) { pmat[j*states_padded+k] += diff --git a/src/core_pmatrix_avx.c b/src/core_pmatrix_avx.c index 439b10e..b1e93ac 100644 --- a/src/core_pmatrix_avx.c +++ b/src/core_pmatrix_avx.c @@ -78,6 +78,11 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, ymm8 = _mm256_set1_pd(PLL_ONE_MIN); ymm9 = _mm256_set1_pd(PLL_ONE_MAX); + __m256d idm_row0 = _mm256_set_pd(0., 0., 0., 1.0); + __m256d idm_row1 = _mm256_set_pd(0., 0., 1.0, 0.); + __m256d idm_row2 = _mm256_set_pd(0., 1.0, 0., 0.); + __m256d idm_row3 = _mm256_set_pd(1.0, 0., 0., 0.); + for (i = 0; i < count; ++i) { assert(branch_lengths[i] >= 0); @@ -129,10 +134,17 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, /* for now exponentiate non-vectorized */ _mm256_store_pd(expd,xmm2); - xmm1 = _mm256_set_pd(exp(expd[3]), - exp(expd[2]), - exp(expd[1]), - exp(expd[0])); + + /* NOTE: in order to deal with numerical issues in cases when Qt -> 0, we + * use a trick suggested by Ben Redelings and explained here: + * https://github.com/xflouris/libpll/issues/129#issuecomment-304004005 + * In short, we use expm1() to compute (exp(Qt) - I), and then correct + * for this by adding an identity matrix I in the very end */ + + xmm1 = _mm256_set_pd(expm1(expd[3]), + expm1(expd[2]), + expm1(expd[1]), + expm1(expd[0])); /* check if all values of expd are approximately one */ @@ -147,7 +159,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, (negative entries in the pmatrix) which can occur due to the different floating point representations of one in expd. Otherwise, proceed as normal and multiply eigenvector matrices with expd */ - if (_mm256_movemask_pd(xmm5) == 0xF) + if (_mm256_movemask_pd(xmm5) == 0xF && 0) { _mm256_store_pd(pmat+0,xmm0); _mm256_store_pd(pmat+4,xmm0); @@ -207,6 +219,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, ymm3 = _mm256_blend_pd(ymm0,ymm1,12); ymm0 = _mm256_add_pd(ymm2,ymm3); + ymm0 = _mm256_add_pd(ymm0,idm_row0); _mm256_store_pd(pmat+0,ymm0); /* pmat row 1 */ @@ -230,6 +243,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, ymm3 = _mm256_blend_pd(ymm0,ymm1,12); ymm0 = _mm256_add_pd(ymm2,ymm3); + ymm0 = _mm256_add_pd(ymm0,idm_row1); _mm256_store_pd(pmat+4,ymm0); /* pmat row 2 */ @@ -253,6 +267,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, ymm3 = _mm256_blend_pd(ymm0,ymm1,12); ymm0 = _mm256_add_pd(ymm2,ymm3); + ymm0 = _mm256_add_pd(ymm0,idm_row2); _mm256_store_pd(pmat+8,ymm0); /* pmat row 3 */ @@ -276,6 +291,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_avx(double ** pmatrix, ymm3 = _mm256_blend_pd(ymm0,ymm1,12); ymm0 = _mm256_add_pd(ymm2,ymm3); + ymm0 = _mm256_add_pd(ymm0,idm_row3); _mm256_store_pd(pmat+12,ymm0); } } @@ -382,8 +398,8 @@ PLL_EXPORT int pll_core_update_pmatrix_20x20_avx(double ** pmatrix, __m256d ymm0,ymm1,ymm2,ymm3,ymm4,ymm5,ymm6,ymm7,ymm8,ymm9; __m256d zmm0,zmm1,zmm2,zmm3; - ymm8 = _mm256_set1_pd(PLL_ONE_MIN); - ymm9 = _mm256_set1_pd(PLL_ONE_MAX); +// ymm8 = _mm256_set1_pd(PLL_ONE_MIN); +// ymm9 = _mm256_set1_pd(PLL_ONE_MAX); double * tran = NULL; for (i = 0; i < count; ++i) @@ -446,8 +462,14 @@ PLL_EXPORT int pll_core_update_pmatrix_20x20_avx(double ** pmatrix, _mm256_store_pd(expd+k*4,xmm5); } + /* NOTE: in order to deal with numerical issues in cases when Qt -> 0, we + * use a trick suggested by Ben Redelings and explained here: + * https://github.com/xflouris/libpll/issues/129#issuecomment-304004005 + * In short, we use expm1() to compute (exp(Qt) - I), and then correct + * for this by adding an identity matrix I in the very end */ + for (k = 0; k < 20; ++k) - expd[k] = exp(expd[k]); + expd[k] = expm1(expd[k]); /* load expd */ xmm4 = _mm256_load_pd(expd+0); @@ -456,50 +478,50 @@ PLL_EXPORT int pll_core_update_pmatrix_20x20_avx(double ** pmatrix, xmm7 = _mm256_load_pd(expd+12); xmm8 = _mm256_load_pd(expd+16); - /* check if all values of expd are approximately one */ - ymm0 = _mm256_cmp_pd(xmm4, ymm8, _CMP_GT_OS); - ymm1 = _mm256_cmp_pd(xmm4, ymm9, _CMP_LT_OS); - ymm2 = _mm256_and_pd(ymm0,ymm1); /* expd[0..3] */ - ymm0 = _mm256_cmp_pd(xmm5, ymm8, _CMP_GT_OS); - ymm1 = _mm256_cmp_pd(xmm5, ymm9, _CMP_LT_OS); - ymm3 = _mm256_and_pd(ymm0,ymm1); /* expd[4..7] */ - ymm0 = _mm256_cmp_pd(xmm6, ymm8, _CMP_GT_OS); - ymm1 = _mm256_cmp_pd(xmm6, ymm9, _CMP_LT_OS); - ymm4 = _mm256_and_pd(ymm0,ymm1); /* expd[8..11] */ - ymm0 = _mm256_cmp_pd(xmm7, ymm8, _CMP_GT_OS); - ymm1 = _mm256_cmp_pd(xmm7, ymm9, _CMP_LT_OS); - ymm5 = _mm256_and_pd(ymm0,ymm1); /* expd[12..15] */ - ymm0 = _mm256_cmp_pd(xmm8, ymm8, _CMP_GT_OS); - ymm1 = _mm256_cmp_pd(xmm8, ymm9, _CMP_LT_OS); - ymm6 = _mm256_and_pd(ymm0,ymm1); /* expd[12..15] */ - - /* AND the results of comnparisons and check the mask to see if all - values of expd are approximately one. If they are, it means we are - multiplying the inverse eigenvectors matrix by the eigenvectors - matrix, and essentially the resulting pmatrix is the identity matrix. - This is done to prevent having numerical issues (negative entries in - the pmatrix) which can occur due to the different floating point - representations of one in expd. Otherwise, proceed as normal and - multiply eigenvector matrices with expd */ - ymm0 = _mm256_and_pd(ymm2,ymm3); - ymm1 = _mm256_and_pd(ymm0,ymm4); - ymm0 = _mm256_and_pd(ymm1,ymm5); - ymm1 = _mm256_and_pd(ymm0,ymm6); - if (_mm256_movemask_pd(ymm1) == 0xF) - { - xmm0 = _mm256_setzero_pd(); - for (j = 0; j < 20; ++j) - { - _mm256_store_pd(pmat+0,xmm0); - _mm256_store_pd(pmat+4,xmm0); - _mm256_store_pd(pmat+8,xmm0); - _mm256_store_pd(pmat+12,xmm0); - _mm256_store_pd(pmat+16,xmm0); - pmat[j] = 1; - pmat += 20; - } - continue; - } +// /* check if all values of expd are approximately one */ +// ymm0 = _mm256_cmp_pd(xmm4, ymm8, _CMP_GT_OS); +// ymm1 = _mm256_cmp_pd(xmm4, ymm9, _CMP_LT_OS); +// ymm2 = _mm256_and_pd(ymm0,ymm1); /* expd[0..3] */ +// ymm0 = _mm256_cmp_pd(xmm5, ymm8, _CMP_GT_OS); +// ymm1 = _mm256_cmp_pd(xmm5, ymm9, _CMP_LT_OS); +// ymm3 = _mm256_and_pd(ymm0,ymm1); /* expd[4..7] */ +// ymm0 = _mm256_cmp_pd(xmm6, ymm8, _CMP_GT_OS); +// ymm1 = _mm256_cmp_pd(xmm6, ymm9, _CMP_LT_OS); +// ymm4 = _mm256_and_pd(ymm0,ymm1); /* expd[8..11] */ +// ymm0 = _mm256_cmp_pd(xmm7, ymm8, _CMP_GT_OS); +// ymm1 = _mm256_cmp_pd(xmm7, ymm9, _CMP_LT_OS); +// ymm5 = _mm256_and_pd(ymm0,ymm1); /* expd[12..15] */ +// ymm0 = _mm256_cmp_pd(xmm8, ymm8, _CMP_GT_OS); +// ymm1 = _mm256_cmp_pd(xmm8, ymm9, _CMP_LT_OS); +// ymm6 = _mm256_and_pd(ymm0,ymm1); /* expd[12..15] */ +// +// /* AND the results of comnparisons and check the mask to see if all +// values of expd are approximately one. If they are, it means we are +// multiplying the inverse eigenvectors matrix by the eigenvectors +// matrix, and essentially the resulting pmatrix is the identity matrix. +// This is done to prevent having numerical issues (negative entries in +// the pmatrix) which can occur due to the different floating point +// representations of one in expd. Otherwise, proceed as normal and +// multiply eigenvector matrices with expd */ +// ymm0 = _mm256_and_pd(ymm2,ymm3); +// ymm1 = _mm256_and_pd(ymm0,ymm4); +// ymm0 = _mm256_and_pd(ymm1,ymm5); +// ymm1 = _mm256_and_pd(ymm0,ymm6); +// if (_mm256_movemask_pd(ymm1) == 0xF) +// { +// xmm0 = _mm256_setzero_pd(); +// for (j = 0; j < 20; ++j) +// { +// _mm256_store_pd(pmat+0,xmm0); +// _mm256_store_pd(pmat+4,xmm0); +// _mm256_store_pd(pmat+8,xmm0); +// _mm256_store_pd(pmat+12,xmm0); +// _mm256_store_pd(pmat+16,xmm0); +// pmat[j] = 1; +// pmat += 20; +// } +// continue; +// } /* compute temp matrix */ for (k = 0; k < 400; k += 20) @@ -565,6 +587,15 @@ PLL_EXPORT int pll_core_update_pmatrix_20x20_avx(double ** pmatrix, pmat += 4; } } + + /* add identity matrix */ + pmat -= 400; + for (j = 0; j < 20; ++j) + { + pmat[j] += 1.0; + pmat += 20; + } + #ifdef DEBUG for (j = 0; j < 20; ++j) for (k = 0; k < 20; ++k) diff --git a/src/core_pmatrix_avx2.c b/src/core_pmatrix_avx2.c index b67bcdd..6f062df 100644 --- a/src/core_pmatrix_avx2.c +++ b/src/core_pmatrix_avx2.c @@ -181,8 +181,14 @@ int pll_core_update_pmatrix_20x20_avx2(double ** pmatrix, _mm256_store_pd(expd+k*4,xmm5); } + /* NOTE: in order to deal with numerical issues in cases when Qt -> 0, we + * use a trick suggested by Ben Redelings and explained here: + * https://github.com/xflouris/libpll/issues/129#issuecomment-304004005 + * In short, we use expm1() to compute (exp(Qt) - I), and then correct + * for this by adding an identity matrix I in the very end */ + for (k = 0; k < 20; ++k) - expd[k] = exp(expd[k]); + expd[k] = expm1(expd[k]); /* load expd */ xmm4 = _mm256_load_pd(expd+0); @@ -255,6 +261,15 @@ int pll_core_update_pmatrix_20x20_avx2(double ** pmatrix, pmat += 4; } } + + /* add identity matrix */ + pmat -= 400; + for (j = 0; j < 20; ++j) + { + pmat[j] += 1.0; + pmat += 20; + } + } } diff --git a/src/core_pmatrix_sse.c b/src/core_pmatrix_sse.c index 1aa1564..ff8aab1 100644 --- a/src/core_pmatrix_sse.c +++ b/src/core_pmatrix_sse.c @@ -67,7 +67,7 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_sse(double ** pmatrix, double * const * inv_eigenvecs, unsigned int count) { - unsigned int i,n; + unsigned int i,j,n; double * expd; double pinvar; @@ -89,11 +89,12 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_sse(double ** pmatrix, __m128d xmm0, xmm1, xmm2, xmm3, xmm4, xmm5, xmm6, xmm7, xmm8, xmm9; __m128d xmm10, xmm11, xmm12, xmm13, xmm14, xmm15, xmm16; - __m128d v_onemin, v_onemax; xmm0 = _mm_setzero_pd(); - v_onemin = _mm_set1_pd(PLL_ONE_MIN); - v_onemax = _mm_set1_pd(PLL_ONE_MAX); + +// __m128d v_onemin, v_onemax; +// v_onemin = _mm_set1_pd(PLL_ONE_MIN); +// v_onemax = _mm_set1_pd(PLL_ONE_MAX); for (i = 0; i < count; ++i) { @@ -156,30 +157,36 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_sse(double ** pmatrix, _mm_store_pd(expd+0,xmm7); _mm_store_pd(expd+2,xmm8); - /* check if all values of expd are approximately one */ - xmm12 = _mm_set_pd(exp(expd[1]), exp(expd[0])); - xmm13 = _mm_set_pd(exp(expd[3]), exp(expd[2])); - - /* */ - xmm1 = _mm_cmpgt_pd(xmm12,v_onemin); - xmm2 = _mm_cmplt_pd(xmm13,v_onemax); - xmm4 = _mm_and_pd(xmm1,xmm2); + /* NOTE: in order to deal with numerical issues in cases when Qt -> 0, we + * use a trick suggested by Ben Redelings and explained here: + * https://github.com/xflouris/libpll/issues/129#issuecomment-304004005 + * In short, we use expm1() to compute (exp(Qt) - I), and then correct + * for this by adding an identity matrix I in the very end */ - if (_mm_movemask_pd(xmm4) == 0x3) - { - _mm_store_pd(pmat+0, xmm0); - _mm_store_pd(pmat+2, xmm0); - _mm_store_pd(pmat+4, xmm0); - _mm_store_pd(pmat+6, xmm0); - _mm_store_pd(pmat+8, xmm0); - _mm_store_pd(pmat+10,xmm0); - _mm_store_pd(pmat+12,xmm0); - _mm_store_pd(pmat+14,xmm0); - - pmat[0] = pmat[5] = pmat[10] = pmat[15] = 1; - } - else - { + /* check if all values of expd are approximately one */ + xmm12 = _mm_set_pd(expm1(expd[1]), expm1(expd[0])); + xmm13 = _mm_set_pd(expm1(expd[3]), expm1(expd[2])); + +// /* */ +// xmm1 = _mm_cmpgt_pd(xmm12,v_onemin); +// xmm2 = _mm_cmplt_pd(xmm13,v_onemax); +// xmm4 = _mm_and_pd(xmm1,xmm2); + +// if (_mm_movemask_pd(xmm4) == 0x3 && 0) +// { +// _mm_store_pd(pmat+0, xmm0); +// _mm_store_pd(pmat+2, xmm0); +// _mm_store_pd(pmat+4, xmm0); +// _mm_store_pd(pmat+6, xmm0); +// _mm_store_pd(pmat+8, xmm0); +// _mm_store_pd(pmat+10,xmm0); +// _mm_store_pd(pmat+12,xmm0); +// _mm_store_pd(pmat+14,xmm0); +// +// pmat[0] = pmat[5] = pmat[10] = pmat[15] = 1; +// } +// else +// { /* transpose eigenvector */ xmm1 = _mm_load_pd(evecs+0); @@ -217,7 +224,15 @@ PLL_EXPORT int pll_core_update_pmatrix_4x4_sse(double ** pmatrix, ONESTEP(4); ONESTEP(8); ONESTEP(12); +// } + + /* add identity matrix */ + for (j = 0; j < 4; ++j) + { + pmat[j] += 1.0; + pmat += 4; } + pmat -= 16; } #ifdef DEBUG unsigned int j,k; diff --git a/test/out/00010_NMDU_lkcalc.out b/test/out/00010_NMDU_lkcalc.out index 1a5094c..02b6a8e 100644 --- a/test/out/00010_NMDU_lkcalc.out +++ b/test/out/00010_NMDU_lkcalc.out @@ -91,8 +91,8 @@ [7] CLV 7: [ {(0.00001,0.98843,0.00001,0.00004),(0.00036,0.91716,0.00036,0.00216),(0.00347,0.76334,0.00347,0.01818),(0.02958,0.44435,0.02958,0.10423)} {(0.00129,0.00001,0.00001,0.00192),(0.00916,0.00033,0.00033,0.01338),(0.02584,0.00298,0.00302,0.03561),(0.05660,0.02082,0.02161,0.06516)} {(0.00001,0.98843,0.00001,0.00004),(0.00036,0.91716,0.00036,0.00216),(0.00347,0.76334,0.00347,0.01818),(0.02958,0.44435,0.02958,0.10423)} {(0.00129,0.00322,0.00129,0.99098),(0.00955,0.02322,0.00955,0.93447),(0.02945,0.06741,0.02945,0.80629),(0.08599,0.16142,0.08599,0.50517)} {(0.00000,0.00001,0.00000,0.98204),(0.00009,0.00054,0.00009,0.87323),(0.00087,0.00454,0.00087,0.65010),(0.00739,0.02606,0.00739,0.25520)} {(0.00257,0.00193,0.00001,0.00001),(0.01833,0.01372,0.00067,0.00067),(0.05168,0.03859,0.00603,0.00596),(0.11320,0.08598,0.04323,0.04164)} {(0.98905,0.00000,0.00002,0.00000),(0.92102,0.00021,0.00122,0.00021),(0.77001,0.00195,0.01050,0.00195),(0.43328,0.01664,0.06318,0.01664)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.98905,0.00000,0.00002,0.00000),(0.92102,0.00021,0.00122,0.00021),(0.77001,0.00195,0.01050,0.00195),(0.43328,0.01664,0.06318,0.01664)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.00000,0.00320,0.00000,0.00638),(0.00018,0.02224,0.00018,0.04339),(0.00173,0.05890,0.00173,0.10870),(0.01479,0.10761,0.01479,0.16309)} {(0.00000,0.00000,0.98266,0.00000),(0.00014,0.00002,0.87680,0.00002),(0.00117,0.00022,0.65480,0.00022),(0.00702,0.00185,0.24075,0.00185)} ] inner-inner logL: -58.887310 -persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 -0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 +persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 checksum logL: -58.887310 tip-inner logL: -58.887310 -persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 -0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 +persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 checksum logL: -58.887310 diff --git a/test/out/00020_NMDR_lkcalc.out b/test/out/00020_NMDR_lkcalc.out index 48a796a..8252c5c 100644 --- a/test/out/00020_NMDR_lkcalc.out +++ b/test/out/00020_NMDR_lkcalc.out @@ -91,8 +91,8 @@ [7] CLV 7: [ {(0.00004,0.97142,0.00004,0.00025),(0.00212,0.81035,0.00212,0.01156),(0.01726,0.54096,0.01726,0.07088),(0.09112,0.23865,0.09112,0.17576)} {(0.00317,0.00004,0.00004,0.00472),(0.02081,0.00186,0.00188,0.02923),(0.04824,0.01312,0.01350,0.05936),(0.06593,0.04746,0.04999,0.06314)} {(0.00004,0.97142,0.00004,0.00025),(0.00212,0.81035,0.00212,0.01156),(0.01726,0.54096,0.01726,0.07088),(0.09112,0.23865,0.09112,0.17576)} {(0.00322,0.00796,0.00322,0.97764),(0.02302,0.05376,0.02302,0.84643),(0.06569,0.13311,0.06569,0.60239),(0.15093,0.20962,0.15093,0.27890)} {(0.00001,0.00006,0.00001,0.95578),(0.00053,0.00289,0.00053,0.71645),(0.00432,0.01772,0.00432,0.36287),(0.02278,0.04394,0.02278,0.07778)} {(0.00634,0.00475,0.00008,0.00008),(0.04161,0.03109,0.00375,0.00371),(0.09649,0.07248,0.02701,0.02623),(0.13185,0.11060,0.09998,0.09491)} {(0.97292,0.00002,0.00014,0.00002),(0.81681,0.00119,0.00664,0.00119),(0.53934,0.00971,0.04226,0.00971),(0.19080,0.05125,0.10970,0.05125)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.97292,0.00002,0.00014,0.00002),(0.81681,0.00119,0.00664,0.00119),(0.53934,0.00971,0.04226,0.00971),(0.19080,0.05125,0.10970,0.05125)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.00002,0.00785,0.00002,0.01557),(0.00106,0.04840,0.00106,0.09101),(0.00863,0.09790,0.00863,0.16037),(0.04556,0.10240,0.04556,0.11693)} {(0.00002,0.00000,0.95725,0.00000),(0.00074,0.00013,0.72157,0.00013),(0.00470,0.00108,0.35682,0.00108),(0.01219,0.00569,0.04666,0.00569)} ] inner-inner logL: -56.794804 -persite logL: -5.4918656 -6.1108011 -1.8692434 -1.6094379 -5.5400058 -7.3473984 -5.8428678 -0.0000000 -5.2305290 -2.5066511 -7.5044254 -7.7415788 +persite logL: -5.4918656 -6.1108011 -1.8692434 -1.6094379 -5.5400058 -7.3473984 -5.8428678 0.0000000 -5.2305290 -2.5066511 -7.5044254 -7.7415788 checksum logL: -56.794804 tip-inner logL: -56.794804 -persite logL: -5.4918656 -6.1108011 -1.8692434 -1.6094379 -5.5400058 -7.3473984 -5.8428678 -0.0000000 -5.2305290 -2.5066511 -7.5044254 -7.7415788 +persite logL: -5.4918656 -6.1108011 -1.8692434 -1.6094379 -5.5400058 -7.3473984 -5.8428678 0.0000000 -5.2305290 -2.5066511 -7.5044254 -7.7415788 checksum logL: -56.794804 diff --git a/test/out/00030_NMDU_gamma.out b/test/out/00030_NMDU_gamma.out index c127167..f659220 100644 --- a/test/out/00030_NMDU_gamma.out +++ b/test/out/00030_NMDU_gamma.out @@ -94,10 +94,10 @@ [MEAN][7] CLV 7: [ {(0.00001,0.98843,0.00001,0.00004),(0.00036,0.91716,0.00036,0.00216),(0.00347,0.76334,0.00347,0.01818),(0.02958,0.44435,0.02958,0.10423)} {(0.00129,0.00001,0.00001,0.00192),(0.00916,0.00033,0.00033,0.01338),(0.02584,0.00298,0.00302,0.03561),(0.05660,0.02082,0.02161,0.06516)} {(0.00001,0.98843,0.00001,0.00004),(0.00036,0.91716,0.00036,0.00216),(0.00347,0.76334,0.00347,0.01818),(0.02958,0.44435,0.02958,0.10423)} {(0.00129,0.00322,0.00129,0.99098),(0.00955,0.02322,0.00955,0.93447),(0.02945,0.06741,0.02945,0.80629),(0.08599,0.16142,0.08599,0.50517)} {(0.00000,0.00001,0.00000,0.98204),(0.00009,0.00054,0.00009,0.87323),(0.00087,0.00454,0.00087,0.65010),(0.00739,0.02606,0.00739,0.25520)} {(0.00257,0.00193,0.00001,0.00001),(0.01833,0.01372,0.00067,0.00067),(0.05168,0.03859,0.00603,0.00596),(0.11320,0.08598,0.04323,0.04164)} {(0.98905,0.00000,0.00002,0.00000),(0.92102,0.00021,0.00122,0.00021),(0.77001,0.00195,0.01050,0.00195),(0.43328,0.01664,0.06318,0.01664)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.98905,0.00000,0.00002,0.00000),(0.92102,0.00021,0.00122,0.00021),(0.77001,0.00195,0.01050,0.00195),(0.43328,0.01664,0.06318,0.01664)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.00000,0.00320,0.00000,0.00638),(0.00018,0.02224,0.00018,0.04339),(0.00173,0.05890,0.00173,0.10870),(0.01479,0.10761,0.01479,0.16309)} {(0.00000,0.00000,0.98266,0.00000),(0.00014,0.00002,0.87680,0.00002),(0.00117,0.00022,0.65480,0.00022),(0.00702,0.00185,0.24075,0.00185)} ] [MEAN] inner-inner logL: -58.887310 -[MEAN] persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 -0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 +[MEAN] persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 [MEAN] checksum logL: -58.887310 [MEAN] tip-inner logL: -58.887310 -[MEAN] persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 -0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 +[MEAN] persite logL: -6.1622140 -6.9407523 -1.4797267 -1.6094379 -5.2773906 -8.1327377 -5.7500211 0.0000000 -5.1947970 -2.1438344 -8.0304760 -8.1659221 [MEAN] checksum logL: -58.887310 [MEDIAN] Discrete GAMMA rates: 0.029078 0.280715 0.924773 2.765435 @@ -196,10 +196,10 @@ [MEDIAN][7] CLV 7: [ {(0.00001,0.98991,0.00001,0.00003),(0.00045,0.90832,0.00045,0.00265),(0.00432,0.73928,0.00432,0.02217),(0.02762,0.45703,0.02762,0.09956)} {(0.00112,0.00000,0.00000,0.00168),(0.01013,0.00041,0.00041,0.01476),(0.02839,0.00367,0.00373,0.03873),(0.05558,0.01967,0.02039,0.06460)} {(0.00001,0.98991,0.00001,0.00003),(0.00045,0.90832,0.00045,0.00265),(0.00432,0.73928,0.00432,0.02217),(0.02762,0.45703,0.02762,0.09956)} {(0.00113,0.00281,0.00113,0.99214),(0.01061,0.02572,0.01061,0.92734),(0.03287,0.07444,0.03287,0.78537),(0.08310,0.15777,0.08310,0.51827)} {(0.00000,0.00001,0.00000,0.98433),(0.00011,0.00066,0.00011,0.85996),(0.00108,0.00554,0.00108,0.61681),(0.00691,0.02489,0.00691,0.26860)} {(0.00224,0.00168,0.00001,0.00001),(0.02027,0.01517,0.00082,0.00082),(0.05678,0.04240,0.00745,0.00734),(0.11117,0.08427,0.04078,0.03933)} {(0.99046,0.00000,0.00002,0.00000),(0.91250,0.00025,0.00150,0.00025),(0.74581,0.00243,0.01284,0.00243),(0.44744,0.01554,0.06022,0.01554)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.99046,0.00000,0.00002,0.00000),(0.91250,0.00025,0.00150,0.00025),(0.74581,0.00243,0.01284,0.00243),(0.44744,0.01554,0.06022,0.01554)} {(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000),(1.00000,1.00000,1.00000,1.00000)} {(0.00000,0.00279,0.00000,0.00557),(0.00023,0.02451,0.00023,0.04770),(0.00216,0.06400,0.00216,0.11693),(0.01381,0.10666,0.01381,0.16353)} {(0.00000,0.00000,0.98488,0.00000),(0.00017,0.00003,0.86379,0.00003),(0.00143,0.00027,0.62103,0.00027),(0.00669,0.00173,0.25534,0.00173)} ] [MEDIAN] inner-inner logL: -58.770643 -[MEDIAN] persite logL: -6.1427884 -6.9489336 -1.5024934 -1.6094379 -5.2628707 -8.1164519 -5.7110281 -0.0000000 -5.1565451 -2.1652071 -8.0078758 -8.1470110 +[MEDIAN] persite logL: -6.1427884 -6.9489336 -1.5024934 -1.6094379 -5.2628707 -8.1164519 -5.7110281 0.0000000 -5.1565451 -2.1652071 -8.0078758 -8.1470110 [MEDIAN] checksum logL: -58.770643 [MEDIAN] tip-inner logL: -58.770643 -[MEDIAN] persite logL: -6.1427884 -6.9489336 -1.5024934 -1.6094379 -5.2628707 -8.1164519 -5.7110281 -0.0000000 -5.1565451 -2.1652071 -8.0078758 -8.1470110 +[MEDIAN] persite logL: -6.1427884 -6.9489336 -1.5024934 -1.6094379 -5.2628707 -8.1164519 -5.7110281 0.0000000 -5.1565451 -2.1652071 -8.0078758 -8.1470110 [MEDIAN] checksum logL: -58.770643 logL MEAN: -58.887310, logL MEDIAN: -58.770643 diff --git a/test/out/alpha-cats.out b/test/out/alpha-cats.out index 561d62b..5afccbd 100644 --- a/test/out/alpha-cats.out +++ b/test/out/alpha-cats.out @@ -6556,10 +6556,10 @@ 0.000000 0.000000 0.000000 0.000002 0.000022 0.000166 0.000882 0.003692 0.012917 0.039363 0.107650 0.270699 0.640794 1.470721 3.453341 9.999749 [0] P-matrix for branch length 0.100000 -+1.0000 +0.0000 +0.0000 -0.0000 ++1.0000 +0.0000 +0.0000 +0.0000 +0.0000 +1.0000 +0.0000 +0.0000 +0.0000 +0.0000 +1.0000 +0.0000 --0.0000 +0.0000 +0.0000 +1.0000 ++0.0000 +0.0000 +0.0000 +1.0000 +1.0000 +0.0000 +0.0000 +0.0000 +0.0000 +1.0000 +0.0000 +0.0000 @@ -6884,7 +6884,7 @@ [0] CLV 5: [ {(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00001,0.00003,0.00000,0.00003),(0.00007,0.00014,0.00000,0.00017),(0.00029,0.00057,0.00000,0.00072),(0.00100,0.00200,0.00000,0.00249),(0.00303,0.00603,0.00002,0.00752),(0.00816,0.01612,0.00016,0.01998),(0.01981,0.03839,0.00098,0.04698),(0.04332,0.08059,0.00497,0.09597),(0.08409,0.14374,0.02116,0.16230),(0.13941,0.20244,0.07257,0.21038),(0.18743,0.20890,0.17210,0.20774)} {(1.00000,0.00000,0.00000,0.00000),(1.00000,0.00000,0.00000,0.00000),(1.00000,0.00000,0.00000,0.00000),(1.00000,0.00000,0.00000,0.00000),(0.99999,0.00000,0.00000,0.00000),(0.99995,0.00000,0.00000,0.00000),(0.99971,0.00000,0.00000,0.00000),(0.99878,0.00000,0.00000,0.00000),(0.99575,0.00000,0.00000,0.00000),(0.98711,0.00001,0.00003,0.00001),(0.96524,0.00004,0.00024,0.00004),(0.91545,0.00024,0.00140,0.00024),(0.81401,0.00123,0.00685,0.00123),(0.63444,0.00555,0.02666,0.00555),(0.37902,0.02148,0.07487,0.02148),(0.14118,0.06603,0.10956,0.06603)} {(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00001,0.00001,0.00000,0.00000),(0.00007,0.00005,0.00000,0.00000),(0.00029,0.00021,0.00000,0.00000),(0.00100,0.00075,0.00000,0.00000),(0.00303,0.00227,0.00002,0.00002),(0.00813,0.00609,0.00013,0.00013),(0.01960,0.01467,0.00077,0.00076),(0.04222,0.03154,0.00387,0.00383),(0.07915,0.05919,0.01623,0.01587),(0.12032,0.09228,0.05347,0.05129),(0.12874,0.11476,0.11340,0.10833)} {(0.00000,1.00000,0.00000,0.00000),(0.00000,1.00000,0.00000,0.00000),(0.00000,1.00000,0.00000,0.00000),(0.00000,1.00000,0.00000,0.00000),(0.00000,0.99999,0.00000,0.00000),(0.00000,0.99994,0.00000,0.00000),(0.00000,0.99969,0.00000,0.00000),(0.00000,0.99871,0.00000,0.00000),(0.00000,0.99550,0.00000,0.00001),(0.00001,0.98637,0.00001,0.00006),(0.00007,0.96335,0.00007,0.00042),(0.00042,0.91138,0.00042,0.00247),(0.00219,0.80752,0.00219,0.01192),(0.00987,0.63070,0.00987,0.04534),(0.03819,0.39641,0.03819,0.12244),(0.11739,0.19944,0.11739,0.17774)} {(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00000,0.00000,0.00000,0.00000),(0.00001,0.00000,0.00000,0.00001),(0.00003,0.00000,0.00000,0.00005),(0.00014,0.00000,0.00000,0.00021),(0.00050,0.00000,0.00000,0.00075),(0.00151,0.00001,0.00001,0.00226),(0.00406,0.00006,0.00006,0.00603),(0.00980,0.00038,0.00038,0.01428),(0.02111,0.00192,0.00194,0.02962),(0.03957,0.00793,0.00811,0.05125),(0.06016,0.02564,0.02674,0.06664),(0.06437,0.05417,0.05670,0.06059)} 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{(0.00000,0.00000,1.00000,0.00000),(0.00000,0.00000,1.00000,0.00000),(0.00000,0.00000,1.00000,0.00000),(0.00000,0.00000,1.00000,0.00000),(0.00000,0.00000,0.99999,0.00000),(0.00000,0.00000,0.99991,0.00000),(0.00000,0.00000,0.99954,0.00000),(0.00000,0.00000,0.99807,0.00000),(0.00000,0.00000,0.99325,0.00000),(0.00000,0.00000,0.97959,0.00000),(0.00003,0.00000,0.94523,0.00000),(0.00016,0.00003,0.86829,0.00003),(0.00076,0.00014,0.71752,0.00014),(0.00296,0.00062,0.47287,0.00062),(0.00832,0.00239,0.18769,0.00239),(0.01217,0.00734,0.02405,0.00734)} 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1.000000 1.000000 1.000000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999000 +0.000000333 +0.000000333 +0.000000333 ++0.000000333 +0.999999000 +0.000000333 +0.000000333 ++0.000000333 +0.000000333 +0.999999000 +0.000000333 ++0.000000333 +0.000000333 +0.000000333 +0.999999000 + ++0.999900007 +0.000033331 +0.000033331 +0.000033331 ++0.000033331 +0.999900007 +0.000033331 +0.000033331 ++0.000033331 +0.000033331 +0.999900007 +0.000033331 ++0.000033331 +0.000033331 +0.000033331 +0.999900007 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 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+0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998756 +0.000000610 +0.000000024 +0.000000610 ++0.000000610 +0.999998756 +0.000000024 +0.000000610 ++0.000000024 +0.000000024 +0.999999829 +0.000000122 ++0.000000610 +0.000000610 +0.000000122 +0.999998659 + ++0.999875621 +0.000060970 +0.000002439 +0.000060970 ++0.000060970 +0.999875621 +0.000002439 +0.000060970 ++0.000002439 +0.000002439 +0.999982927 +0.000012194 ++0.000060970 +0.000060970 +0.000012194 +0.999865866 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999988 +0.000000006 +0.000000000 +0.000000006 ++0.000000006 +0.999999988 +0.000000000 +0.000000006 ++0.000000000 +0.000000000 +0.999999998 +0.000000001 ++0.000000006 +0.000000006 +0.000000001 +0.999999987 + ++0.987674840 +0.006040680 +0.000246618 +0.006037862 ++0.006040680 +0.987674840 +0.000246618 +0.006037862 ++0.000246618 +0.000246618 +0.998294940 +0.001211825 ++0.006037862 +0.006037862 +0.001211825 +0.986712451 + ++0.427874834 +0.271211875 +0.037872391 +0.263040900 ++0.271211875 +0.427874834 +0.037872391 +0.263040900 ++0.037872391 +0.037872391 +0.848854741 +0.075400476 ++0.263040900 +0.263040900 +0.075400476 +0.398517725 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999751 +0.000000122 +0.000000005 +0.000000122 ++0.000000122 +0.999999751 +0.000000005 +0.000000122 ++0.000000005 +0.000000005 +0.999999966 +0.000000024 ++0.000000122 +0.000000122 +0.000000024 +0.999999732 + ++0.791839387 +0.101610287 +0.005817610 +0.100732716 ++0.101610287 +0.791839387 +0.005817610 +0.100732716 ++0.005817610 +0.005817610 +0.966727985 +0.021636795 ++0.100732716 +0.100732716 +0.021636795 +0.776897773 + ++0.251121459 +0.251121459 +0.246875280 +0.250881803 ++0.251121459 +0.251121459 +0.246875280 +0.250881803 ++0.246875280 +0.246875280 +0.258706406 +0.247543034 ++0.250881803 +0.250881803 +0.247543034 +0.250693361 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998756 +0.000000610 +0.000000024 +0.000000610 ++0.000000610 +0.999998756 +0.000000024 +0.000000610 ++0.000000024 +0.000000024 +0.999999829 +0.000000122 ++0.000000610 +0.000000610 +0.000000122 +0.999998659 + ++0.427874834 +0.271211875 +0.037872391 +0.263040900 ++0.271211875 +0.427874834 +0.037872391 +0.263040900 ++0.037872391 +0.037872391 +0.848854741 +0.075400476 ++0.263040900 +0.263040900 +0.075400476 +0.398517725 + ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999875621 +0.000060970 +0.000002439 +0.000060970 ++0.000060970 +0.999875621 +0.000002439 +0.000060970 ++0.000002439 +0.000002439 +0.999982927 +0.000012194 ++0.000060970 +0.000060970 +0.000012194 +0.999865866 + ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 + ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 ++0.250000000 +0.250000000 +0.250000000 +0.250000000 + +datatype = DNA +base freqs: [0.250000 0.250000 0.250000 0.250000 ] +subst rates: [0.001000 1000.000000 0.001000 1000.000000 0.001000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999001 +0.000000000 +0.000000999 +0.000000000 ++0.000000000 +0.999999001 +0.000000999 +0.000000000 ++0.000000999 +0.000000999 +0.999998000 +0.000000001 ++0.000000000 +0.000000000 +0.000000001 +0.999999999 + ++0.999900060 +0.000000005 +0.000099935 +0.000000000 ++0.000000005 +0.999900060 +0.000099935 +0.000000000 ++0.000099935 +0.000099935 +0.999800030 +0.000000100 ++0.000000000 +0.000000000 +0.000000100 +0.999999900 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999990 +0.000000000 +0.000000010 +0.000000000 ++0.000000000 +0.999999990 +0.000000010 +0.000000000 ++0.000000010 +0.000000010 +0.999999980 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.990104066 +0.000049299 +0.009846575 +0.000000059 ++0.000049299 +0.990104066 +0.009846575 +0.000000059 ++0.009846575 +0.009846575 +0.980296953 +0.000009896 ++0.000000059 +0.000000059 +0.000009896 +0.999989985 + ++0.525628575 +0.157565792 +0.316577419 +0.000228215 ++0.157565792 +0.525628575 +0.316577419 +0.000228215 ++0.316577419 +0.316577419 +0.366300915 +0.000544248 ++0.000228215 +0.000228215 +0.000544248 +0.998999322 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999800 +0.000000000 +0.000000200 +0.000000000 ++0.000000000 +0.999999800 +0.000000200 +0.000000000 ++0.000000200 +0.000000200 +0.999999600 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.834234545 +0.015422202 +0.150326552 +0.000016701 ++0.015422202 +0.834234545 +0.150326552 +0.000016701 ++0.150326552 +0.150326552 +0.699180035 +0.000166860 ++0.000016701 +0.000016701 +0.000166860 +0.999799738 + ++0.331209794 +0.331209791 +0.331101645 +0.006478770 ++0.331209791 +0.331209794 +0.331101645 +0.006478770 ++0.331101645 +0.331101645 +0.330993641 +0.006803069 ++0.006478770 +0.006478770 +0.006803069 +0.980239391 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999001 +0.000000000 +0.000000999 +0.000000000 ++0.000000000 +0.999999001 +0.000000999 +0.000000000 ++0.000000999 +0.000000999 +0.999998000 +0.000000001 ++0.000000000 +0.000000000 +0.000000001 +0.999999999 + ++0.525628575 +0.157565792 +0.316577419 +0.000228215 ++0.157565792 +0.525628575 +0.316577419 +0.000228215 ++0.316577419 +0.316577419 +0.366300915 +0.000544248 ++0.000228215 +0.000228215 +0.000544248 +0.998999322 + ++0.322983476 +0.322983476 +0.322886284 +0.031146764 ++0.322983476 +0.322983476 +0.322886284 +0.031146764 ++0.322886284 +0.322886284 +0.322789221 +0.031438212 ++0.031146764 +0.031146764 +0.031438212 +0.906268259 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999900060 +0.000000005 +0.000099935 +0.000000000 ++0.000000005 +0.999900060 +0.000099935 +0.000000000 ++0.000099935 +0.000099935 +0.999800030 +0.000000100 ++0.000000000 +0.000000000 +0.000000100 +0.999999900 + ++0.322983476 +0.322983476 +0.322886284 +0.031146764 ++0.322983476 +0.322983476 +0.322886284 +0.031146764 ++0.322886284 +0.322886284 +0.322789221 +0.031438212 ++0.031146764 +0.031146764 +0.031438212 +0.906268259 + ++0.250000133 +0.250000133 +0.250000133 +0.249999602 ++0.250000133 +0.250000133 +0.250000133 +0.249999602 ++0.250000133 +0.250000133 +0.250000132 +0.249999602 ++0.249999602 +0.249999602 +0.249999602 +0.250001194 + +datatype = DNA +base freqs: [0.333333 0.166667 0.333333 0.250000 ] +subst rates: [1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999129 +0.000000194 +0.000000387 +0.000000290 ++0.000000387 +0.999998935 +0.000000387 +0.000000290 ++0.000000387 +0.000000194 +0.999999129 +0.000000290 ++0.000000387 +0.000000194 +0.000000387 +0.999999032 + ++0.999912909 +0.000019354 +0.000038707 +0.000029030 ++0.000038707 +0.999893555 +0.000038707 +0.000029030 ++0.000038707 +0.000019354 +0.999912909 +0.000029030 ++0.000038707 +0.000019354 +0.000038707 +0.999903232 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999991 +0.000000002 +0.000000004 +0.000000003 ++0.000000004 +0.999999989 +0.000000004 +0.000000003 ++0.000000004 +0.000000002 +0.999999991 +0.000000003 ++0.000000004 +0.000000002 +0.000000004 +0.999999990 + ++0.991344880 +0.001923360 +0.003846720 +0.002885040 ++0.003846720 +0.989421520 +0.003846720 +0.002885040 ++0.003846720 +0.001923360 +0.991344880 +0.002885040 ++0.003846720 +0.001923360 +0.003846720 +0.990383200 + ++0.504448623 +0.110122528 +0.220245057 +0.165183792 ++0.220245057 +0.394326094 +0.220245057 +0.165183792 ++0.220245057 +0.110122528 +0.504448623 +0.165183792 ++0.220245057 +0.110122528 +0.220245057 +0.449387358 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999826 +0.000000039 +0.000000077 +0.000000058 ++0.000000077 +0.999999787 +0.000000077 +0.000000058 ++0.000000077 +0.000000039 +0.999999826 +0.000000058 ++0.000000077 +0.000000039 +0.000000077 +0.999999806 + ++0.845993153 +0.034223744 +0.068447488 +0.051335616 ++0.068447488 +0.811769409 +0.068447488 +0.051335616 ++0.068447488 +0.034223744 +0.845993153 +0.051335616 ++0.068447488 +0.034223744 +0.068447488 +0.828881281 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999129 +0.000000194 +0.000000387 +0.000000290 ++0.000000387 +0.999998935 +0.000000387 +0.000000290 ++0.000000387 +0.000000194 +0.999999129 +0.000000290 ++0.000000387 +0.000000194 +0.000000387 +0.999999032 + ++0.504448623 +0.110122528 +0.220245057 +0.165183792 ++0.220245057 +0.394326094 +0.220245057 +0.165183792 ++0.220245057 +0.110122528 +0.504448623 +0.165183792 ++0.220245057 +0.110122528 +0.220245057 +0.449387358 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999912909 +0.000019354 +0.000038707 +0.000029030 ++0.000038707 +0.999893555 +0.000038707 +0.000029030 ++0.000038707 +0.000019354 +0.999912909 +0.000029030 ++0.000038707 +0.000019354 +0.000038707 +0.999903232 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + +datatype = DNA +base freqs: [0.333333 0.166667 0.333333 0.250000 ] +subst rates: [5.000000 0.200000 5.000000 0.200000 5.000000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998946 +0.000000409 +0.000000033 +0.000000613 ++0.000000817 +0.999998537 +0.000000033 +0.000000613 ++0.000000033 +0.000000016 +0.999999828 +0.000000123 ++0.000000817 +0.000000409 +0.000000163 +0.999998610 + ++0.999894560 +0.000040868 +0.000003270 +0.000061302 ++0.000081736 +0.999853692 +0.000003270 +0.000061302 ++0.000003270 +0.000001635 +0.999982834 +0.000012261 ++0.000081736 +0.000040868 +0.000016348 +0.999861049 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999989 +0.000000004 +0.000000000 +0.000000006 ++0.000000008 +0.999999985 +0.000000000 +0.000000006 ++0.000000000 +0.000000000 +0.999999998 +0.000000001 ++0.000000008 +0.000000004 +0.000000002 +0.999999986 + ++0.989551841 +0.004048534 +0.000330621 +0.006069004 ++0.008097068 +0.985503307 +0.000330621 +0.006069004 ++0.000330621 +0.000165311 +0.998285929 +0.001218139 ++0.008092005 +0.004046003 +0.001624185 +0.986237807 + ++0.512302123 +0.179238171 +0.050343937 +0.258115769 ++0.358476342 +0.333063952 +0.050343937 +0.258115769 ++0.050343937 +0.025171969 +0.849999839 +0.074484256 ++0.344154358 +0.172077179 +0.099312341 +0.384456122 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999789 +0.000000082 +0.000000007 +0.000000123 ++0.000000163 +0.999999707 +0.000000007 +0.000000123 ++0.000000007 +0.000000003 +0.999999966 +0.000000025 ++0.000000163 +0.000000082 +0.000000033 +0.999999722 + ++0.823564668 +0.067926949 +0.007794686 +0.100713697 ++0.135853898 +0.755637719 +0.007794686 +0.100713697 ++0.007794686 +0.003897343 +0.966650676 +0.021657295 ++0.134284930 +0.067142465 +0.028876393 +0.769696213 + ++0.308985514 +0.154492757 +0.305004241 +0.231517488 ++0.308985514 +0.154492757 +0.305004241 +0.231517488 ++0.305004241 +0.152502121 +0.313279740 +0.229213899 ++0.308689984 +0.154344992 +0.305618532 +0.231346492 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998946 +0.000000409 +0.000000033 +0.000000613 ++0.000000817 +0.999998537 +0.000000033 +0.000000613 ++0.000000033 +0.000000016 +0.999999828 +0.000000123 ++0.000000817 +0.000000409 +0.000000163 +0.999998610 + ++0.512302123 +0.179238171 +0.050343937 +0.258115769 ++0.358476342 +0.333063952 +0.050343937 +0.258115769 ++0.050343937 +0.025171969 +0.849999839 +0.074484256 ++0.344154358 +0.172077179 +0.099312341 +0.384456122 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999894560 +0.000040868 +0.000003270 +0.000061302 ++0.000081736 +0.999853692 +0.000003270 +0.000061302 ++0.000003270 +0.000001635 +0.999982834 +0.000012261 ++0.000081736 +0.000040868 +0.000016348 +0.999861049 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 ++0.307692308 +0.153846154 +0.307692308 +0.230769231 + +datatype = DNA +base freqs: [0.333333 0.166667 0.333333 0.250000 ] +subst rates: [0.001000 1000.000000 0.001000 1000.000000 0.001000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999001 +0.000000000 +0.000000999 +0.000000000 ++0.000000000 +0.999999000 +0.000000999 +0.000000000 ++0.000000999 +0.000000500 +0.999998500 +0.000000001 ++0.000000000 +0.000000000 +0.000000001 +0.999999999 + ++0.999900060 +0.000000003 +0.000099937 +0.000000000 ++0.000000005 +0.999900057 +0.000099937 +0.000000000 ++0.000099937 +0.000049969 +0.999850019 +0.000000075 ++0.000000000 +0.000000000 +0.000000100 +0.999999900 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999990 +0.000000000 +0.000000010 +0.000000000 ++0.000000000 +0.999999990 +0.000000010 +0.000000000 ++0.000000010 +0.000000005 +0.999999985 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.990104151 +0.000024691 +0.009871113 +0.000000045 ++0.000049381 +0.990079461 +0.009871113 +0.000000045 ++0.009871113 +0.004935557 +0.985185889 +0.000007441 ++0.000000059 +0.000000030 +0.000009921 +0.999989990 + ++0.544562451 +0.088249773 +0.366997620 +0.000190157 ++0.176499545 +0.456312678 +0.366997620 +0.000190157 ++0.366997620 +0.183498810 +0.449038630 +0.000464940 ++0.000253542 +0.000126771 +0.000619920 +0.998999766 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999800 +0.000000000 +0.000000200 +0.000000000 ++0.000000000 +0.999999800 +0.000000200 +0.000000000 ++0.000000200 +0.000000100 +0.999999700 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.834718617 +0.007953109 +0.157315366 +0.000012907 ++0.015906219 +0.826765508 +0.157315366 +0.000012907 ++0.157315366 +0.078657683 +0.763896188 +0.000130763 ++0.000017210 +0.000008605 +0.000174351 +0.999799834 + ++0.397722506 +0.198861252 +0.397605604 +0.005810639 ++0.397722504 +0.198861254 +0.397605604 +0.005810639 ++0.397605604 +0.198802802 +0.397488854 +0.006102740 ++0.007747518 +0.003873759 +0.008136987 +0.980241736 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999001 +0.000000000 +0.000000999 +0.000000000 ++0.000000000 +0.999999000 +0.000000999 +0.000000000 ++0.000000999 +0.000000500 +0.999998500 +0.000000001 ++0.000000000 +0.000000000 +0.000000001 +0.999999999 + ++0.544562451 +0.088249773 +0.366997620 +0.000190157 ++0.176499545 +0.456312678 +0.366997620 +0.000190157 ++0.366997620 +0.183498810 +0.449038630 +0.000464940 ++0.000253542 +0.000126771 +0.000619920 +0.998999766 + ++0.388822890 +0.194411445 +0.388717545 +0.028048120 ++0.388822890 +0.194411445 +0.388717545 +0.028048120 ++0.388717545 +0.194358772 +0.388612336 +0.028311347 ++0.037397494 +0.018698747 +0.037748463 +0.906155296 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999900060 +0.000000003 +0.000099937 +0.000000000 ++0.000000005 +0.999900057 +0.000099937 +0.000000000 ++0.000099937 +0.000049969 +0.999850019 +0.000000075 ++0.000000000 +0.000000000 +0.000000100 +0.999999900 + ++0.388822890 +0.194411445 +0.388717545 +0.028048120 ++0.388822890 +0.194411445 +0.388717545 +0.028048120 ++0.388717545 +0.194358772 +0.388612336 +0.028311347 ++0.037397494 +0.018698747 +0.037748463 +0.906155296 + ++0.307692514 +0.153846257 +0.307692514 +0.230768714 ++0.307692514 +0.153846257 +0.307692514 +0.230768714 ++0.307692514 +0.153846257 +0.307692514 +0.230768715 ++0.307691619 +0.153845810 +0.307691620 +0.230770951 + +datatype = DNA +base freqs: [0.001000 0.499000 0.001000 0.499000 ] +subst rates: [1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998010 +0.000000994 +0.000000002 +0.000000994 ++0.000000002 +0.999999002 +0.000000002 +0.000000994 ++0.000000002 +0.000000994 +0.999998010 +0.000000994 ++0.000000002 +0.000000994 +0.000000002 +0.999999002 + ++0.999801014 +0.000099393 +0.000000199 +0.000099393 ++0.000000199 +0.999900208 +0.000000199 +0.000099393 ++0.000000199 +0.000099393 +0.999801014 +0.000099393 ++0.000000199 +0.000099393 +0.000000199 +0.999900208 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999980 +0.000000010 +0.000000000 +0.000000010 ++0.000000000 +0.999999990 +0.000000000 +0.000000010 ++0.000000000 +0.000000010 +0.999999980 +0.000000010 ++0.000000000 +0.000000010 +0.000000000 +0.999999990 + ++0.980296348 +0.009841964 +0.000019723 +0.009841964 ++0.000019723 +0.990118589 +0.000019723 +0.009841964 ++0.000019723 +0.009841964 +0.980296348 +0.009841964 ++0.000019723 +0.009841964 +0.000019723 +0.990118589 + ++0.137279379 +0.430928519 +0.000863584 +0.430928519 ++0.000863584 +0.567344313 +0.000863584 +0.430928519 ++0.000863584 +0.430928519 +0.137279379 +0.430928519 ++0.000863584 +0.430928519 +0.000863584 +0.567344313 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999602 +0.000000199 +0.000000000 +0.000000199 ++0.000000000 +0.999999800 +0.000000000 +0.000000199 ++0.000000000 +0.000000199 +0.999999602 +0.000000199 ++0.000000000 +0.000000199 +0.000000000 +0.999999800 + ++0.671715618 +0.163977884 +0.000328613 +0.163977884 ++0.000328613 +0.835364890 +0.000328613 +0.163977884 ++0.000328613 +0.163977884 +0.671715618 +0.163977884 ++0.000328613 +0.163977884 +0.000328613 +0.835364890 + ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998010 +0.000000994 +0.000000002 +0.000000994 ++0.000000002 +0.999999002 +0.000000002 +0.000000994 ++0.000000002 +0.000000994 +0.999998010 +0.000000994 ++0.000000002 +0.000000994 +0.000000002 +0.999999002 + ++0.137279379 +0.430928519 +0.000863584 +0.430928519 ++0.000863584 +0.567344313 +0.000863584 +0.430928519 ++0.000863584 +0.430928519 +0.137279379 +0.430928519 ++0.000863584 +0.430928519 +0.000863584 +0.567344313 + ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999801014 +0.000099393 +0.000000199 +0.000099393 ++0.000000199 +0.999900208 +0.000000199 +0.000099393 ++0.000000199 +0.000099393 +0.999801014 +0.000099393 ++0.000000199 +0.000099393 +0.000000199 +0.999900208 + ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 + ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 + +datatype = DNA +base freqs: [0.001000 0.499000 0.001000 0.499000 ] +subst rates: [5.000000 0.200000 5.000000 0.200000 5.000000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998005 +0.000000998 +0.000000000 +0.000000998 ++0.000000002 +0.999999000 +0.000000000 +0.000000998 ++0.000000000 +0.000000040 +0.999999761 +0.000000200 ++0.000000002 +0.000000998 +0.000000000 +0.999999000 + ++0.999800507 +0.000099743 +0.000000008 +0.000099743 ++0.000000200 +0.999900049 +0.000000008 +0.000099743 ++0.000000008 +0.000003991 +0.999976052 +0.000019949 ++0.000000200 +0.000099743 +0.000000040 +0.999900018 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999980 +0.000000010 +0.000000000 +0.000000010 ++0.000000000 +0.999999990 +0.000000000 +0.000000010 ++0.000000000 +0.000000000 +0.999999998 +0.000000002 ++0.000000000 +0.000000010 +0.000000000 +0.999999990 + ++0.980246588 +0.009876306 +0.000000814 +0.009876291 ++0.000019792 +0.990103102 +0.000000814 +0.009876291 ++0.000000814 +0.000406434 +0.997608008 +0.001984744 ++0.000019792 +0.009876291 +0.000003977 +0.990099939 + ++0.136589151 +0.431648903 +0.000153961 +0.431607986 ++0.000865028 +0.567373025 +0.000153961 +0.431607986 ++0.000153961 +0.076826551 +0.787062697 +0.135956790 ++0.000864946 +0.431607986 +0.000272458 +0.567254610 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999601 +0.000000200 +0.000000000 +0.000000200 ++0.000000000 +0.999999800 +0.000000000 +0.000000200 ++0.000000000 +0.000000008 +0.999999952 +0.000000040 ++0.000000000 +0.000000200 +0.000000000 +0.999999800 + ++0.671034399 +0.164474551 +0.000021134 +0.164469916 ++0.000329608 +0.835179342 +0.000021134 +0.164469916 ++0.000021134 +0.010545780 +0.953233284 +0.036199803 ++0.000329599 +0.164469916 +0.000072545 +0.835127941 + ++0.001000010 +0.499004920 +0.000990970 +0.499004100 ++0.001000010 +0.499004920 +0.000990970 +0.499004100 ++0.000990970 +0.494494164 +0.009269046 +0.495245820 ++0.001000008 +0.499004100 +0.000992477 +0.499003416 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999998005 +0.000000998 +0.000000000 +0.000000998 ++0.000000002 +0.999999000 +0.000000000 +0.000000998 ++0.000000000 +0.000000040 +0.999999761 +0.000000200 ++0.000000002 +0.000000998 +0.000000000 +0.999999000 + ++0.136589151 +0.431648903 +0.000153961 +0.431607986 ++0.000865028 +0.567373025 +0.000153961 +0.431607986 ++0.000153961 +0.076826551 +0.787062697 +0.135956790 ++0.000864946 +0.431607986 +0.000272458 +0.567254610 + ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 ++0.001000000 +0.499000000 +0.001000000 +0.499000000 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 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+0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999505 +0.000000247 +0.000000000 +0.000000247 +0.000000000 ++0.000000001 +0.999999988 +0.000000001 +0.000000010 +0.000000001 ++0.000000000 +0.000000247 +0.999999742 +0.000000010 +0.000000001 ++0.000000001 +0.000000010 +0.000000000 +0.999999989 +0.000000000 ++0.000000000 +0.000000247 +0.000000001 +0.000000049 +0.999999702 + ++0.609662000 +0.195035345 +0.000079476 +0.195135388 +0.000087791 ++0.000488810 +0.988561530 +0.000543703 +0.009871997 +0.000533961 ++0.000079476 +0.216937390 +0.772631935 +0.009817104 +0.000534095 ++0.000489061 +0.009871997 +0.000024604 +0.989504839 +0.000109498 ++0.000087791 +0.213050273 +0.000534095 +0.043689893 +0.742637948 + ++0.001248440 +0.497991399 +0.001248098 +0.498263867 +0.001248195 ++0.001248099 +0.561220715 +0.001406965 +0.434762521 +0.001361701 ++0.001248098 +0.561378900 +0.001407362 +0.434603655 +0.001361985 ++0.001248782 +0.434762521 +0.001089232 +0.561764775 +0.001134691 ++0.001248195 +0.543318649 +0.001361985 +0.452741607 +0.001329564 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999990099 +0.000004950 +0.000000000 +0.000004950 +0.000000000 ++0.000000012 +0.999999765 +0.000000012 +0.000000198 +0.000000012 ++0.000000000 +0.000004950 +0.999994839 +0.000000198 +0.000000012 ++0.000000012 +0.000000198 +0.000000000 +0.999999787 +0.000000002 ++0.000000000 +0.000004950 +0.000000012 +0.000000990 +0.999994047 + ++0.001297961 +0.497414695 +0.001232535 +0.498815273 +0.001239535 ++0.001246653 +0.827013402 +0.002060579 +0.167846059 +0.001833306 ++0.001232535 +0.822171137 +0.007729406 +0.167032133 +0.001834789 ++0.001250164 +0.167846059 +0.000418627 +0.829830514 +0.000654636 ++0.001239535 +0.731488923 +0.001834789 +0.261199884 +0.004236870 + ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999950498 +0.000024749 +0.000000002 +0.000024749 +0.000000002 ++0.000000062 +0.999998824 +0.000000062 +0.000000990 +0.000000062 ++0.000000002 +0.000024749 +0.999974197 +0.000000990 +0.000000062 ++0.000000062 +0.000000990 +0.000000002 +0.999998933 +0.000000012 ++0.000000002 +0.000024749 +0.000000062 +0.000004950 +0.999970237 + ++0.001248440 +0.497991399 +0.001248098 +0.498263867 +0.001248195 ++0.001248099 +0.561220715 +0.001406965 +0.434762521 +0.001361701 ++0.001248098 +0.561378900 +0.001407362 +0.434603655 +0.001361985 ++0.001248782 +0.434762521 +0.001089232 +0.561764775 +0.001134691 ++0.001248195 +0.543318649 +0.001361985 +0.452741607 +0.001329564 + ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.995061920 +0.002468778 +0.000000255 +0.002468791 +0.000000256 ++0.000006187 +0.999882430 +0.000006194 +0.000098995 +0.000006193 ++0.000000255 +0.002471593 +0.997422971 +0.000098988 +0.000006193 ++0.000006187 +0.000098995 +0.000000248 +0.999893330 +0.000001239 ++0.000000256 +0.002471124 +0.000006193 +0.000494344 +0.997028083 + ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 + ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 + +datatype = ODD +base freqs: [0.001000 0.399000 0.001000 0.399000 0.001000 ] +subst rates: [0.001000 1000.000000 0.001000 1000.000000 0.001000 1000.000000 0.001000 1000.000000 0.001000 1.000000 ] +P-matrix: 0, brlen = 0.000001 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999994 +0.000000000 +0.000000003 +0.000000000 +0.000000003 ++0.000000000 +0.999998750 +0.000000000 +0.000001250 +0.000000000 ++0.000000003 +0.000000000 +0.999998747 +0.000001250 +0.000000000 ++0.000000000 +0.000001250 +0.000000003 +0.999998747 +0.000000000 ++0.000000003 +0.000000000 +0.000000000 +0.000000001 +0.999999996 + ++0.999999373 +0.000000000 +0.000000313 +0.000000000 +0.000000313 ++0.000000000 +0.999875018 +0.000000000 +0.000124982 +0.000000000 ++0.000000313 +0.000000008 +0.999874696 +0.000124982 +0.000000000 ++0.000000000 +0.000124982 +0.000000313 +0.999874704 +0.000000000 ++0.000000313 +0.000000000 +0.000000000 +0.000000125 +0.999999562 + +P-matrix: 1, brlen = 0.010000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.999999988 +0.000000000 +0.000000012 +0.000000000 ++0.000000000 +0.000000000 +0.999999987 +0.000000012 +0.000000000 ++0.000000000 +0.000000012 +0.000000000 +0.999999987 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999937322 +0.000000013 +0.000031131 +0.000000207 +0.000031326 ++0.000000000 +0.987655138 +0.000000193 +0.012344668 +0.000000000 ++0.000031131 +0.000077164 +0.987547229 +0.012344474 +0.000000001 ++0.000000001 +0.012344668 +0.000030939 +0.987624362 +0.000000031 ++0.000031326 +0.000000090 +0.000000001 +0.000012422 +0.999956161 + ++0.993759766 +0.000353955 +0.001780134 +0.000989991 +0.003116155 ++0.000000887 +0.540852460 +0.000636818 +0.458508843 +0.000000992 ++0.001780134 +0.254090546 +0.286252064 +0.457872911 +0.000004345 ++0.000002481 +0.458508843 +0.001147551 +0.540338987 +0.000002139 ++0.003116155 +0.000395745 +0.000004345 +0.000853295 +0.995630461 + +P-matrix: 2, brlen = 0.200000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999999 +0.000000000 +0.000000001 +0.000000000 +0.000000001 ++0.000000000 +0.999999750 +0.000000000 +0.000000250 +0.000000000 ++0.000000001 +0.000000000 +0.999999749 +0.000000250 +0.000000000 ++0.000000000 +0.000000250 +0.000000001 +0.999999749 +0.000000000 ++0.000000001 +0.000000000 +0.000000000 +0.000000000 +0.999999999 + ++0.998747548 +0.000005686 +0.000553862 +0.000067013 +0.000625890 ++0.000000014 +0.803262809 +0.000061289 +0.196675821 +0.000000067 ++0.000553862 +0.024454197 +0.778377146 +0.196614546 +0.000000248 ++0.000000168 +0.196675821 +0.000492768 +0.802830684 +0.000000560 ++0.000625890 +0.000026843 +0.000000248 +0.000223242 +0.999123777 + ++0.884067682 +0.028066020 +0.002291092 +0.029205284 +0.056369921 ++0.000070341 +0.499325901 +0.001248483 +0.499323812 +0.000031463 ++0.002291092 +0.498144894 +0.001251110 +0.498145669 +0.000167235 ++0.000073196 +0.499323812 +0.001248485 +0.499321727 +0.000032779 ++0.056369921 +0.012553633 +0.000167235 +0.013078795 +0.917830415 + +P-matrix: 3, brlen = 1.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999994 +0.000000000 +0.000000003 +0.000000000 +0.000000003 ++0.000000000 +0.999998750 +0.000000000 +0.000001250 +0.000000000 ++0.000000003 +0.000000000 +0.999998747 +0.000001250 +0.000000000 ++0.000000000 +0.000001250 +0.000000003 +0.999998747 +0.000000000 ++0.000000003 +0.000000000 +0.000000000 +0.000000001 +0.999999996 + ++0.993759766 +0.000353955 +0.001780134 +0.000989991 +0.003116155 ++0.000000887 +0.540852460 +0.000636818 +0.458508843 +0.000000992 ++0.001780134 +0.254090546 +0.286252064 +0.457872911 +0.000004345 ++0.000002481 +0.458508843 +0.001147551 +0.540338987 +0.000002139 ++0.003116155 +0.000395745 +0.000004345 +0.000853295 +0.995630461 + ++0.562948729 +0.123610367 +0.001722292 +0.124410307 +0.187308305 ++0.000309800 +0.499136189 +0.001248610 +0.499134471 +0.000170930 ++0.001722292 +0.498195368 +0.001249804 +0.498195661 +0.000636874 ++0.000311805 +0.499134471 +0.001248611 +0.499132756 +0.000172357 ++0.187308305 +0.068201177 +0.000636874 +0.068770550 +0.675083093 + +P-matrix: 4, brlen = 100.000000 ++1.000000000 +0.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +1.000000000 +0.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +1.000000000 +0.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +1.000000000 +0.000000000 ++0.000000000 +0.000000000 +0.000000000 +0.000000000 +1.000000000 + ++0.999999373 +0.000000000 +0.000000313 +0.000000000 +0.000000313 ++0.000000000 +0.999875018 +0.000000000 +0.000124982 +0.000000000 ++0.000000313 +0.000000008 +0.999874696 +0.000124982 +0.000000000 ++0.000000000 +0.000124982 +0.000000313 +0.999874704 +0.000000000 ++0.000000313 +0.000000000 +0.000000000 +0.000000125 +0.999999562 + ++0.562948729 +0.123610367 +0.001722292 +0.124410307 +0.187308305 ++0.000309800 +0.499136189 +0.001248610 +0.499134471 +0.000170930 ++0.001722292 +0.498195368 +0.001249804 +0.498195661 +0.000636874 ++0.000311805 +0.499134471 +0.001248611 +0.499132756 +0.000172357 ++0.187308305 +0.068201177 +0.000636874 +0.068770550 +0.675083093 + ++0.001248440 +0.498127340 +0.001248439 +0.498127340 +0.001248440 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248439 +0.498127341 +0.001248439 +0.498127341 +0.001248439 ++0.001248440 +0.498127340 +0.001248439 +0.498127340 +0.001248440 + diff --git a/test/out/scaling.out b/test/out/scaling.out index aa5e947..dacbc92 100644 --- a/test/out/scaling.out +++ b/test/out/scaling.out @@ -9,10 +9,10 @@ logLH TIP-INNER at edge (3997-1999): -inf, LH derivatives: -nan, -nan datatype = DNA, scaling = per-rate, alpha = 0.050000, rates = [ 0.000000 0.000001 0.005299 3.994700 ] recompute P-matrices: 3997 recompute CLVs: 1998 -scaler 1995: [ 8+(50 22 7 0) 6+(50 25 9 0) 15+(48 16 0 5) 15+(47 16 0 5) 4+(50 27 11 0) ] -per-site logLH: [ -1565.4625 -1079.1468 -2838.4636 -2813.7556 -812.9101 ] -logLH INNER-INNER at edge (3997-3995): -9109.7386, LH derivatives: -2.7826, 2.9738 -logLH TIP-INNER at edge (3997-1999): -9109.7386, LH derivatives: -1.5936, 1.2950 +scaler 1995: [ 8+(47 22 7 0) 6+(50 25 9 0) 15+(42 16 0 5) 15+(41 16 0 5) 4+(50 27 11 0) ] +per-site logLH: [ -1565.4625 -1079.1468 -2838.4637 -2813.7557 -812.9101 ] +logLH INNER-INNER at edge (3997-3995): -9109.7387, LH derivatives: -2.7826, 2.9738 +logLH TIP-INNER at edge (3997-1999): -9109.7387, LH derivatives: -1.5936, 1.2950 datatype = PROT, scaling = per-site, alpha = 0.050000, rates = [ 0.000000 0.000001 0.005299 3.994700 ] recompute P-matrices: 3997 @@ -26,9 +26,9 @@ datatype = PROT, scaling = per-rate, alpha = 0.050000, rates = [ 0.000000 0.0000 recompute P-matrices: 3997 recompute CLVs: 1998 scaler 1995: [ 22+(50 26 2 0) 24+(50 24 0 4) 22+(50 26 2 0) 24+(50 23 0 12) 24+(50 24 0 2) ] -per-site logLH: [ -4082.7793 -4417.3800 -4041.0983 -4356.9538 -4396.2292 ] -logLH INNER-INNER at edge (3997-3995): -21294.4406, LH derivatives: -3.4943, 4.6390 -logLH TIP-INNER at edge (3997-1999): -21294.4406, LH derivatives: -2.2599, 1.7979 +per-site logLH: [ -4082.7793 -4417.3800 -4041.0983 -4356.9538 -4396.2291 ] +logLH INNER-INNER at edge (3997-3995): -21294.4407, LH derivatives: -3.4943, 4.6390 +logLH TIP-INNER at edge (3997-1999): -21294.4407, LH derivatives: -2.2599, 1.7979 datatype = ODD, scaling = per-site, alpha = 0.050000, rates = [ 0.000000 0.000001 0.005299 3.994700 ] recompute P-matrices: 3997 @@ -41,7 +41,7 @@ logLH TIP-INNER at edge (3997-1999): -inf, LH derivatives: -nan, -nan datatype = ODD, scaling = per-rate, alpha = 0.050000, rates = [ 0.000000 0.000001 0.005299 3.994700 ] recompute P-matrices: 3997 recompute CLVs: 1998 -scaler 1995: [ 14+(50 18 1 0) 14+(50 18 0 1) 14+(50 17 0 9) 14+(50 17 0 3) 14+(50 16 0 0) ] +scaler 1995: [ 14+(44 18 1 0) 14+(44 18 0 1) 14+(43 17 0 9) 14+(43 17 0 3) 14+(42 16 0 0) ] per-site logLH: [ -2532.1251 -2613.2293 -2665.1969 -2613.1833 -2529.7137 ] logLH INNER-INNER at edge (3997-3995): -12953.4482, LH derivatives: -2.8949, 2.6829 logLH TIP-INNER at edge (3997-1999): -12953.4482, LH derivatives: -1.9224, 1.2544 diff --git a/test/src/pmatrix.c b/test/src/pmatrix.c index d61a2f4..ea70bad 100644 --- a/test/src/pmatrix.c +++ b/test/src/pmatrix.c @@ -220,11 +220,13 @@ int main(int argc, char * argv[]) { unsigned int i, j, k; -// skip_test(); - /* check attributes */ unsigned int attributes = get_attributes(argc, argv); + /* pattern tip is not relevant for pmatrix computation */ + if (attributes & PLL_ATTRIB_PATTERN_TIP) + skip_test(); + init(attributes); pll_partition_t * parts[] = {part_nt, part_aa, part_odd};