diff --git a/usr.bin/ministat/ministat.1 b/usr.bin/ministat/ministat.1 index f713baef8fca..c7a20c75ce24 100644 --- a/usr.bin/ministat/ministat.1 +++ b/usr.bin/ministat/ministat.1 @@ -1,135 +1,139 @@ .\" .\" Copyright (c) 2007 Poul-Henning Kamp .\" All rights reserved. .\" .\" Redistribution and use in source and binary forms, with or without .\" modification, are permitted provided that the following conditions .\" are met: .\" 1. Redistributions of source code must retain the above copyright .\" notice, this list of conditions and the following disclaimer. .\" 2. Redistributions in binary form must reproduce the above copyright .\" notice, this list of conditions and the following disclaimer in the .\" documentation and/or other materials provided with the distribution. .\" .\" THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND .\" ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE .\" IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE .\" ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE .\" FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL .\" DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS .\" OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) .\" HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT .\" LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY .\" OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF .\" SUCH DAMAGE. .\" .\" $FreeBSD$ .\" .Dd November 10, 2012 .Dt MINISTAT 1 .Os .Sh NAME .Nm ministat .Nd statistics utility .Sh SYNOPSIS .Nm -.Op Fl Ans +.Op Fl Anqs .Op Fl C Ar column .Op Fl c Ar confidence_level .Op Fl d Ar delimiter .Op Fl w Op width .Op Ar .Sh DESCRIPTION The .Nm command calculates fundamental statistical properties of numeric data in the specified files or, if no file is specified, standard input. .Pp The options are as follows: .Bl -tag -width Fl .It Fl A Just report the statistics of the input and relative comparisons, suppress the ASCII-art plot. .It Fl n Just report the raw statistics of the input, suppress the ASCII-art plot and the relative comparisons. +.It Fl q +Suppress printing of summary statistics and data-set names; typically for use +alongside +.Fl n . .It Fl s Print the average/median/stddev bars on separate lines in the ASCII-art plot, to avoid overlap. .It Fl C Ar column Specify which column of data to use. By default the first column in the input file(s) are used. .It Fl c Ar confidence_level Specify desired confidence level for Student's T analysis. Possible values are 80, 90, 95, 98, 99 and 99.5 % .It Fl d Ar delimiter Specifies the column delimiter characters, default is SPACE and TAB. See .Xr strtok 3 for details. .It Fl w Ar width Width of ASCII-art plot in characters. The default is the terminal width, or 74 if standard output is not a terminal. .El .Pp A sample output could look like this: .Bd -literal -offset indent $ ministat -s -w 60 iguana chameleon x iguana + chameleon +------------------------------------------------------------+ |x * x * + + x +| | |________M______A_______________| | | |________________M__A___________________| | +------------------------------------------------------------+ N Min Max Median Avg Stddev x 7 50 750 200 300 238.04761 + 5 150 930 500 540 299.08193 No difference proven at 95.0% confidence .Ed .Pp If .Nm tells you, as in the example above, that there is no difference proven at 95% confidence, the two data sets you gave it are for all statistical purposes identical. .Pp You have the option of lowering your standards by specifying a lower confidence level: .Bd -literal -offset indent $ ministat -s -w 60 -c 80 iguana chameleon x iguana + chameleon +------------------------------------------------------------+ |x * x * + + x +| | |________M______A_______________| | | |________________M__A___________________| | +------------------------------------------------------------+ N Min Max Median Avg Stddev x 7 50 750 200 300 238.04761 + 5 150 930 500 540 299.08193 Difference at 80.0% confidence 240 +/- 212.215 80% +/- 70.7384% (Student's t, pooled s = 264.159) .Ed .Pp But a lower standard does not make your data any better, and the example is only included here to show the format of the output when a statistical difference is proven according to Student's T method. .Sh SEE ALSO Any mathematics text on basic statistics, for instances Larry Gonicks excellent "Cartoon Guide to Statistics" which supplied the above example. .Sh HISTORY The .Nm command was written by Poul-Henning Kamp out of frustration over all the bogus benchmark claims made by people with no understanding of the importance of uncertainty and statistics. .Pp From .Fx 5.2 it has lived in the source tree as a developer tool, graduating to the installed system from .Fx 8.0 . diff --git a/usr.bin/ministat/ministat.c b/usr.bin/ministat/ministat.c index 3134c4b03928..aa6bc27f89ab 100644 --- a/usr.bin/ministat/ministat.c +++ b/usr.bin/ministat/ministat.c @@ -1,686 +1,694 @@ /*- * SPDX-License-Identifier: Beerware * * ---------------------------------------------------------------------------- * "THE BEER-WARE LICENSE" (Revision 42): * wrote this file. As long as you retain this notice you * can do whatever you want with this stuff. If we meet some day, and you think * this stuff is worth it, you can buy me a beer in return. Poul-Henning Kamp * ---------------------------------------------------------------------------- * */ #include __FBSDID("$FreeBSD$"); #include #include #include #include #include #include #include #include #include #include #include #include #include #include #define NSTUDENT 100 #define NCONF 6 static double const studentpct[] = { 80, 90, 95, 98, 99, 99.5 }; static double const student[NSTUDENT + 1][NCONF] = { /* inf */ { 1.282, 1.645, 1.960, 2.326, 2.576, 3.090 }, /* 1. */ { 3.078, 6.314, 12.706, 31.821, 63.657, 318.313 }, /* 2. */ { 1.886, 2.920, 4.303, 6.965, 9.925, 22.327 }, /* 3. */ { 1.638, 2.353, 3.182, 4.541, 5.841, 10.215 }, /* 4. */ { 1.533, 2.132, 2.776, 3.747, 4.604, 7.173 }, /* 5. */ { 1.476, 2.015, 2.571, 3.365, 4.032, 5.893 }, /* 6. */ { 1.440, 1.943, 2.447, 3.143, 3.707, 5.208 }, /* 7. */ { 1.415, 1.895, 2.365, 2.998, 3.499, 4.782 }, /* 8. */ { 1.397, 1.860, 2.306, 2.896, 3.355, 4.499 }, /* 9. */ { 1.383, 1.833, 2.262, 2.821, 3.250, 4.296 }, /* 10. */ { 1.372, 1.812, 2.228, 2.764, 3.169, 4.143 }, /* 11. */ { 1.363, 1.796, 2.201, 2.718, 3.106, 4.024 }, /* 12. */ { 1.356, 1.782, 2.179, 2.681, 3.055, 3.929 }, /* 13. */ { 1.350, 1.771, 2.160, 2.650, 3.012, 3.852 }, /* 14. */ { 1.345, 1.761, 2.145, 2.624, 2.977, 3.787 }, /* 15. */ { 1.341, 1.753, 2.131, 2.602, 2.947, 3.733 }, /* 16. */ { 1.337, 1.746, 2.120, 2.583, 2.921, 3.686 }, /* 17. */ { 1.333, 1.740, 2.110, 2.567, 2.898, 3.646 }, /* 18. */ { 1.330, 1.734, 2.101, 2.552, 2.878, 3.610 }, /* 19. */ { 1.328, 1.729, 2.093, 2.539, 2.861, 3.579 }, /* 20. */ { 1.325, 1.725, 2.086, 2.528, 2.845, 3.552 }, /* 21. */ { 1.323, 1.721, 2.080, 2.518, 2.831, 3.527 }, /* 22. */ { 1.321, 1.717, 2.074, 2.508, 2.819, 3.505 }, /* 23. */ { 1.319, 1.714, 2.069, 2.500, 2.807, 3.485 }, /* 24. */ { 1.318, 1.711, 2.064, 2.492, 2.797, 3.467 }, /* 25. */ { 1.316, 1.708, 2.060, 2.485, 2.787, 3.450 }, /* 26. */ { 1.315, 1.706, 2.056, 2.479, 2.779, 3.435 }, /* 27. */ { 1.314, 1.703, 2.052, 2.473, 2.771, 3.421 }, /* 28. */ { 1.313, 1.701, 2.048, 2.467, 2.763, 3.408 }, /* 29. */ { 1.311, 1.699, 2.045, 2.462, 2.756, 3.396 }, /* 30. */ { 1.310, 1.697, 2.042, 2.457, 2.750, 3.385 }, /* 31. */ { 1.309, 1.696, 2.040, 2.453, 2.744, 3.375 }, /* 32. */ { 1.309, 1.694, 2.037, 2.449, 2.738, 3.365 }, /* 33. */ { 1.308, 1.692, 2.035, 2.445, 2.733, 3.356 }, /* 34. */ { 1.307, 1.691, 2.032, 2.441, 2.728, 3.348 }, /* 35. */ { 1.306, 1.690, 2.030, 2.438, 2.724, 3.340 }, /* 36. */ { 1.306, 1.688, 2.028, 2.434, 2.719, 3.333 }, /* 37. */ { 1.305, 1.687, 2.026, 2.431, 2.715, 3.326 }, /* 38. */ { 1.304, 1.686, 2.024, 2.429, 2.712, 3.319 }, /* 39. */ { 1.304, 1.685, 2.023, 2.426, 2.708, 3.313 }, /* 40. */ { 1.303, 1.684, 2.021, 2.423, 2.704, 3.307 }, /* 41. */ { 1.303, 1.683, 2.020, 2.421, 2.701, 3.301 }, /* 42. */ { 1.302, 1.682, 2.018, 2.418, 2.698, 3.296 }, /* 43. */ { 1.302, 1.681, 2.017, 2.416, 2.695, 3.291 }, /* 44. */ { 1.301, 1.680, 2.015, 2.414, 2.692, 3.286 }, /* 45. */ { 1.301, 1.679, 2.014, 2.412, 2.690, 3.281 }, /* 46. */ { 1.300, 1.679, 2.013, 2.410, 2.687, 3.277 }, /* 47. */ { 1.300, 1.678, 2.012, 2.408, 2.685, 3.273 }, /* 48. */ { 1.299, 1.677, 2.011, 2.407, 2.682, 3.269 }, /* 49. */ { 1.299, 1.677, 2.010, 2.405, 2.680, 3.265 }, /* 50. */ { 1.299, 1.676, 2.009, 2.403, 2.678, 3.261 }, /* 51. */ { 1.298, 1.675, 2.008, 2.402, 2.676, 3.258 }, /* 52. */ { 1.298, 1.675, 2.007, 2.400, 2.674, 3.255 }, /* 53. */ { 1.298, 1.674, 2.006, 2.399, 2.672, 3.251 }, /* 54. */ { 1.297, 1.674, 2.005, 2.397, 2.670, 3.248 }, /* 55. */ { 1.297, 1.673, 2.004, 2.396, 2.668, 3.245 }, /* 56. */ { 1.297, 1.673, 2.003, 2.395, 2.667, 3.242 }, /* 57. */ { 1.297, 1.672, 2.002, 2.394, 2.665, 3.239 }, /* 58. */ { 1.296, 1.672, 2.002, 2.392, 2.663, 3.237 }, /* 59. */ { 1.296, 1.671, 2.001, 2.391, 2.662, 3.234 }, /* 60. */ { 1.296, 1.671, 2.000, 2.390, 2.660, 3.232 }, /* 61. */ { 1.296, 1.670, 2.000, 2.389, 2.659, 3.229 }, /* 62. */ { 1.295, 1.670, 1.999, 2.388, 2.657, 3.227 }, /* 63. */ { 1.295, 1.669, 1.998, 2.387, 2.656, 3.225 }, /* 64. */ { 1.295, 1.669, 1.998, 2.386, 2.655, 3.223 }, /* 65. */ { 1.295, 1.669, 1.997, 2.385, 2.654, 3.220 }, /* 66. */ { 1.295, 1.668, 1.997, 2.384, 2.652, 3.218 }, /* 67. */ { 1.294, 1.668, 1.996, 2.383, 2.651, 3.216 }, /* 68. */ { 1.294, 1.668, 1.995, 2.382, 2.650, 3.214 }, /* 69. */ { 1.294, 1.667, 1.995, 2.382, 2.649, 3.213 }, /* 70. */ { 1.294, 1.667, 1.994, 2.381, 2.648, 3.211 }, /* 71. */ { 1.294, 1.667, 1.994, 2.380, 2.647, 3.209 }, /* 72. */ { 1.293, 1.666, 1.993, 2.379, 2.646, 3.207 }, /* 73. */ { 1.293, 1.666, 1.993, 2.379, 2.645, 3.206 }, /* 74. */ { 1.293, 1.666, 1.993, 2.378, 2.644, 3.204 }, /* 75. */ { 1.293, 1.665, 1.992, 2.377, 2.643, 3.202 }, /* 76. */ { 1.293, 1.665, 1.992, 2.376, 2.642, 3.201 }, /* 77. */ { 1.293, 1.665, 1.991, 2.376, 2.641, 3.199 }, /* 78. */ { 1.292, 1.665, 1.991, 2.375, 2.640, 3.198 }, /* 79. */ { 1.292, 1.664, 1.990, 2.374, 2.640, 3.197 }, /* 80. */ { 1.292, 1.664, 1.990, 2.374, 2.639, 3.195 }, /* 81. */ { 1.292, 1.664, 1.990, 2.373, 2.638, 3.194 }, /* 82. */ { 1.292, 1.664, 1.989, 2.373, 2.637, 3.193 }, /* 83. */ { 1.292, 1.663, 1.989, 2.372, 2.636, 3.191 }, /* 84. */ { 1.292, 1.663, 1.989, 2.372, 2.636, 3.190 }, /* 85. */ { 1.292, 1.663, 1.988, 2.371, 2.635, 3.189 }, /* 86. */ { 1.291, 1.663, 1.988, 2.370, 2.634, 3.188 }, /* 87. */ { 1.291, 1.663, 1.988, 2.370, 2.634, 3.187 }, /* 88. */ { 1.291, 1.662, 1.987, 2.369, 2.633, 3.185 }, /* 89. */ { 1.291, 1.662, 1.987, 2.369, 2.632, 3.184 }, /* 90. */ { 1.291, 1.662, 1.987, 2.368, 2.632, 3.183 }, /* 91. */ { 1.291, 1.662, 1.986, 2.368, 2.631, 3.182 }, /* 92. */ { 1.291, 1.662, 1.986, 2.368, 2.630, 3.181 }, /* 93. */ { 1.291, 1.661, 1.986, 2.367, 2.630, 3.180 }, /* 94. */ { 1.291, 1.661, 1.986, 2.367, 2.629, 3.179 }, /* 95. */ { 1.291, 1.661, 1.985, 2.366, 2.629, 3.178 }, /* 96. */ { 1.290, 1.661, 1.985, 2.366, 2.628, 3.177 }, /* 97. */ { 1.290, 1.661, 1.985, 2.365, 2.627, 3.176 }, /* 98. */ { 1.290, 1.661, 1.984, 2.365, 2.627, 3.175 }, /* 99. */ { 1.290, 1.660, 1.984, 2.365, 2.626, 3.175 }, /* 100. */ { 1.290, 1.660, 1.984, 2.364, 2.626, 3.174 } }; #define MAX_DS 8 static char symbol[MAX_DS] = { ' ', 'x', '+', '*', '%', '#', '@', 'O' }; struct dataset { char *name; double *points; size_t lpoints; double sy, syy; size_t n; }; static struct dataset * NewSet(void) { struct dataset *ds; ds = calloc(1, sizeof *ds); assert(ds != NULL); ds->lpoints = 100000; ds->points = calloc(sizeof *ds->points, ds->lpoints); assert(ds->points != NULL); ds->syy = NAN; return(ds); } static void AddPoint(struct dataset *ds, double a) { double *dp; if (ds->n >= ds->lpoints) { dp = ds->points; ds->lpoints *= 4; ds->points = calloc(sizeof *ds->points, ds->lpoints); assert(ds->points != NULL); memcpy(ds->points, dp, sizeof *dp * ds->n); free(dp); } ds->points[ds->n++] = a; ds->sy += a; } static double Min(const struct dataset *ds) { return (ds->points[0]); } static double Max(const struct dataset *ds) { return (ds->points[ds->n -1]); } static double Avg(const struct dataset *ds) { return(ds->sy / ds->n); } static double Median(const struct dataset *ds) { const size_t m = ds->n / 2; if ((ds->n % 2) == 0) return ((ds->points[m] + (ds->points[m - 1])) / 2); return (ds->points[m]); } static double Var(struct dataset *ds) { size_t z; const double a = Avg(ds); if (isnan(ds->syy)) { ds->syy = 0.0; for (z = 0; z < ds->n; z++) ds->syy += (ds->points[z] - a) * (ds->points[z] - a); } return (ds->syy / (ds->n - 1.0)); } static double Stddev(struct dataset *ds) { return sqrt(Var(ds)); } static void VitalsHead(void) { printf(" N Min Max Median Avg Stddev\n"); } static void Vitals(struct dataset *ds, int flag) { printf("%c %3zu %13.8g %13.8g %13.8g %13.8g %13.8g", symbol[flag], ds->n, Min(ds), Max(ds), Median(ds), Avg(ds), Stddev(ds)); printf("\n"); } static void Relative(struct dataset *ds, struct dataset *rs, int confidx) { double spool, s, d, e, t; double re; size_t z; z = ds->n + rs->n - 2; if (z > NSTUDENT) t = student[0][confidx]; else t = student[z][confidx]; spool = (ds->n - 1) * Var(ds) + (rs->n - 1) * Var(rs); spool /= ds->n + rs->n - 2; spool = sqrt(spool); s = spool * sqrt(1.0 / ds->n + 1.0 / rs->n); d = Avg(ds) - Avg(rs); e = t * s; re = (ds->n - 1) * Var(ds) + (rs->n - 1) * Var(rs) * (Avg(ds) * Avg(ds)) / (Avg(rs) * Avg(rs)); re *= (ds->n + rs->n) / (ds->n * rs->n * (ds->n + rs->n - 2.0)); re = t * sqrt(re); if (fabs(d) > e) { printf("Difference at %.1f%% confidence\n", studentpct[confidx]); printf(" %g +/- %g\n", d, e); printf(" %g%% +/- %g%%\n", d * 100 / Avg(rs), re * 100 / Avg(rs)); printf(" (Student's t, pooled s = %g)\n", spool); } else { printf("No difference proven at %.1f%% confidence\n", studentpct[confidx]); } } struct plot { double min; double max; double span; int width; double x0, dx; size_t height; char *data; char **bar; int separate_bars; int num_datasets; }; static struct plot plot; static void SetupPlot(int width, int separate, int num_datasets) { struct plot *pl; pl = &plot; pl->width = width; pl->height = 0; pl->data = NULL; pl->bar = NULL; pl->separate_bars = separate; pl->num_datasets = num_datasets; pl->min = 999e99; pl->max = -999e99; } static void AdjPlot(double a) { struct plot *pl; pl = &plot; if (a < pl->min) pl->min = a; if (a > pl->max) pl->max = a; pl->span = pl->max - pl->min; pl->dx = pl->span / (pl->width - 1.0); pl->x0 = pl->min - .5 * pl->dx; } static void DimPlot(struct dataset *ds) { AdjPlot(Min(ds)); AdjPlot(Max(ds)); AdjPlot(Avg(ds) - Stddev(ds)); AdjPlot(Avg(ds) + Stddev(ds)); } static void PlotSet(struct dataset *ds, int val) { struct plot *pl; int i, x; size_t m, j, z; size_t n; int bar; double av, sd; pl = &plot; if (pl->span == 0) return; if (pl->separate_bars) bar = val-1; else bar = 0; if (pl->bar == NULL) { pl->bar = calloc(sizeof(char *), pl->num_datasets); assert(pl->bar != NULL); } if (pl->bar[bar] == NULL) { pl->bar[bar] = malloc(pl->width); assert(pl->bar[bar] != NULL); memset(pl->bar[bar], 0, pl->width); } m = 1; i = -1; j = 0; /* Set m to max(j) + 1, to allocate required memory */ for (n = 0; n < ds->n; n++) { x = (ds->points[n] - pl->x0) / pl->dx; if (x == i) { j++; if (j > m) m = j; } else { j = 1; i = x; } } m += 1; if (m > pl->height) { pl->data = realloc(pl->data, pl->width * m); assert(pl->data != NULL); memset(pl->data + pl->height * pl->width, 0, (m - pl->height) * pl->width); } pl->height = m; i = -1; for (n = 0; n < ds->n; n++) { x = (ds->points[n] - pl->x0) / pl->dx; if (x == i) { j++; } else { j = 1; i = x; } pl->data[j * pl->width + x] |= val; } av = Avg(ds); sd = Stddev(ds); if (!isnan(sd)) { x = ((av - sd) - pl->x0) / pl->dx; m = ((av + sd) - pl->x0) / pl->dx; pl->bar[bar][m] = '|'; pl->bar[bar][x] = '|'; for (z = x + 1; z < m; z++) if (pl->bar[bar][z] == 0) pl->bar[bar][z] = '_'; } x = (Median(ds) - pl->x0) / pl->dx; pl->bar[bar][x] = 'M'; x = (av - pl->x0) / pl->dx; pl->bar[bar][x] = 'A'; } static void DumpPlot(void) { struct plot *pl; int i, j, k; size_t z; pl = &plot; if (pl->span == 0) { printf("[no plot, span is zero width]\n"); return; } putchar('+'); for (i = 0; i < pl->width; i++) putchar('-'); putchar('+'); putchar('\n'); for (z = 1; z < pl->height; z++) { putchar('|'); for (j = 0; j < pl->width; j++) { k = pl->data[(pl->height - z) * pl->width + j]; if (k >= 0 && k < MAX_DS) putchar(symbol[k]); else printf("[%02x]", k); } putchar('|'); putchar('\n'); } for (i = 0; i < pl->num_datasets; i++) { if (pl->bar[i] == NULL) continue; putchar('|'); for (j = 0; j < pl->width; j++) { k = pl->bar[i][j]; if (k == 0) k = ' '; putchar(k); } putchar('|'); putchar('\n'); } putchar('+'); for (i = 0; i < pl->width; i++) putchar('-'); putchar('+'); putchar('\n'); } static int dbl_cmp(const void *a, const void *b) { const double *aa = a; const double *bb = b; if (*aa < *bb) return (-1); else if (*aa > *bb) return (1); else return (0); } static struct dataset * ReadSet(FILE *f, const char *n, int column, const char *delim) { char buf[BUFSIZ], *p, *t; struct dataset *s; double d; int line; int i; s = NewSet(); s->name = strdup(n); assert(s->name != NULL); line = 0; while (fgets(buf, sizeof buf, f) != NULL) { line++; i = strlen(buf); while (i > 0 && isspace(buf[i - 1])) buf[--i] = '\0'; for (i = 1, t = strtok(buf, delim); t != NULL && *t != '#'; i++, t = strtok(NULL, delim)) { if (i == column) break; } if (t == NULL || *t == '#') continue; d = strtod(t, &p); if (p != NULL && *p != '\0') errx(2, "Invalid data on line %d in %s", line, n); if (*buf != '\0') AddPoint(s, d); } if (s->n < 3) { fprintf(stderr, "Dataset %s must contain at least 3 data points\n", n); exit (2); } qsort(s->points, s->n, sizeof *s->points, dbl_cmp); return (s); } static void usage(char const *whine) { int i; fprintf(stderr, "%s\n", whine); fprintf(stderr, - "Usage: ministat [-C column] [-c confidence] [-d delimiter(s)] [-Ans] [-w width] [file [file ...]]\n"); + "Usage: ministat [-C column] [-c confidence] [-d delimiter(s)] [-Anqs] [-w width] [file [file ...]]\n"); fprintf(stderr, "\tconfidence = {"); for (i = 0; i < NCONF; i++) { fprintf(stderr, "%s%g%%", i ? ", " : "", studentpct[i]); } fprintf(stderr, "}\n"); fprintf(stderr, "\t-A : print statistics only. suppress the graph.\n"); fprintf(stderr, "\t-C : column number to extract (starts and defaults to 1)\n"); fprintf(stderr, "\t-d : delimiter(s) string, default to \" \\t\"\n"); fprintf(stderr, "\t-n : print summary statistics only, no graph/test\n"); + fprintf(stderr, "\t-q : suppress printing summary-statistics headers and data-set names\n"); fprintf(stderr, "\t-s : print avg/median/stddev bars on separate lines\n"); fprintf(stderr, "\t-w : width of graph/test output (default 74 or terminal width)\n"); exit (2); } int main(int argc, char **argv) { const char *setfilenames[MAX_DS - 1]; struct dataset *ds[MAX_DS - 1]; FILE *setfiles[MAX_DS - 1]; int nds; double a; const char *delim = " \t"; char *p; int c, i, ci; int column = 1; int flag_s = 0; int flag_n = 0; + int flag_q = 0; int termwidth = 74; int suppress_plot = 0; if (isatty(STDOUT_FILENO)) { struct winsize wsz; if ((p = getenv("COLUMNS")) != NULL && *p != '\0') termwidth = atoi(p); else if (ioctl(STDOUT_FILENO, TIOCGWINSZ, &wsz) != -1 && wsz.ws_col > 0) termwidth = wsz.ws_col - 2; } ci = -1; - while ((c = getopt(argc, argv, "AC:c:d:snw:")) != -1) + while ((c = getopt(argc, argv, "AC:c:d:snqw:")) != -1) switch (c) { case 'A': suppress_plot = 1; break; case 'C': column = strtol(optarg, &p, 10); if (p != NULL && *p != '\0') usage("Invalid column number."); if (column <= 0) usage("Column number should be positive."); break; case 'c': a = strtod(optarg, &p); if (p != NULL && *p != '\0') usage("Not a floating point number"); for (i = 0; i < NCONF; i++) if (a == studentpct[i]) ci = i; if (ci == -1) usage("No support for confidence level"); break; case 'd': if (*optarg == '\0') usage("Can't use empty delimiter string"); delim = optarg; break; case 'n': flag_n = 1; break; + case 'q': + flag_q = 1; + break; case 's': flag_s = 1; break; case 'w': termwidth = strtol(optarg, &p, 10); if (p != NULL && *p != '\0') usage("Invalid width, not a number."); if (termwidth < 0) usage("Unable to move beyond left margin."); break; default: usage("Unknown option"); break; } if (ci == -1) ci = 2; argc -= optind; argv += optind; if (argc == 0) { setfilenames[0] = ""; setfiles[0] = stdin; nds = 1; } else { if (argc > (MAX_DS - 1)) usage("Too many datasets."); nds = argc; for (i = 0; i < nds; i++) { setfilenames[i] = argv[i]; if (!strcmp(argv[i], "-")) setfiles[0] = stdin; else setfiles[i] = fopen(argv[i], "r"); if (setfiles[i] == NULL) err(2, "Cannot open %s", argv[i]); } } if (caph_limit_stdio() < 0) err(2, "capsicum"); for (i = 0; i < nds; i++) if (caph_limit_stream(fileno(setfiles[i]), CAPH_READ) < 0) err(2, "unable to limit rights for %s", setfilenames[i]); /* Enter Capsicum sandbox. */ if (caph_enter() < 0) err(2, "unable to enter capability mode"); for (i = 0; i < nds; i++) { ds[i] = ReadSet(setfiles[i], setfilenames[i], column, delim); if (setfiles[i] != stdin) fclose(setfiles[i]); } - for (i = 0; i < nds; i++) - printf("%c %s\n", symbol[i+1], ds[i]->name); + if (!flag_q) { + for (i = 0; i < nds; i++) + printf("%c %s\n", symbol[i+1], ds[i]->name); + } if (!flag_n && !suppress_plot) { SetupPlot(termwidth, flag_s, nds); for (i = 0; i < nds; i++) DimPlot(ds[i]); for (i = 0; i < nds; i++) PlotSet(ds[i], i + 1); DumpPlot(); } - VitalsHead(); + if (!flag_q) + VitalsHead(); Vitals(ds[0], 1); for (i = 1; i < nds; i++) { Vitals(ds[i], i + 1); if (!flag_n) Relative(ds[i], ds[0], ci); } exit(0); }