// -*- c -*-
//
// PSPP - a program for statistical analysis.
-// Copyright (C) 2005, 2006, 2009, 2010 Free Software Foundation, Inc.
-//
+// Copyright (C) 2005, 2006, 2009, 2010, 2011, 2012, 2015, 2016 Free Software Foundation, Inc.
+//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
-//
+//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
-//
+//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
boolean operator NE (a, b) = a != b;
// String relational operators.
-boolean operator EQ_STRING (string a, string b) = compare_string (&a, &b) == 0;
-boolean operator GE_STRING (string a, string b) = compare_string (&a, &b) >= 0;
-boolean operator GT_STRING (string a, string b) = compare_string (&a, &b) > 0;
-boolean operator LE_STRING (string a, string b) = compare_string (&a, &b) <= 0;
-boolean operator LT_STRING (string a, string b) = compare_string (&a, &b) < 0;
-boolean operator NE_STRING (string a, string b) = compare_string (&a, &b) != 0;
+boolean operator EQ_STRING (string a, string b) = compare_string_3way (&a, &b) == 0;
+boolean operator GE_STRING (string a, string b) = compare_string_3way (&a, &b) >= 0;
+boolean operator GT_STRING (string a, string b) = compare_string_3way (&a, &b) > 0;
+boolean operator LE_STRING (string a, string b) = compare_string_3way (&a, &b) <= 0;
+boolean operator LT_STRING (string a, string b) = compare_string_3way (&a, &b) < 0;
+boolean operator NE_STRING (string a, string b) = compare_string_3way (&a, &b) != 0;
// Unary functions.
function ABS (x) = fabs (x);
function LN (x) = check_errno (log (x));
function LNGAMMA (x >= 0) = gsl_sf_lngamma (x);
function MOD10 (x) = fmod (x, 10);
-function RND (x) = x >= 0. ? floor (x + .5) : -floor (-x + .5);
+function RND (x) = round_nearest (x, 1, 0);
+function RND (x, mult != 0) = round_nearest (x, mult, 0);
+function RND (x, mult != 0, fuzzbits >= 0) = round_nearest (x, mult, fuzzbits);
function SIN (x) = sin (x);
function SQRT (x >= 0) = sqrt (x);
function TAN (x) = check_errno (tan (x));
-function TRUNC (x) = x >= 0. ? floor (x) : -floor (-x);
+function TRUNC (x) = round_zero (x, 1, 0);
+function TRUNC (x, mult != 0) = round_zero (x, mult, 0);
+function TRUNC (x, mult != 0, fuzzbits >= 0) = round_zero (x, mult, fuzzbits);
absorb_miss function MOD (n, d)
{
size_t i;
for (i = 0; i < n; i++)
- if (!compare_string (&x, &a[i]))
+ if (!compare_string_3way (&x, &a[i]))
return 1.;
return 0.;
}
max = &a[0];
for (i = 1; i < n; i++)
- if (compare_string (&a[i], max) > 0)
+ if (compare_string_3way (&a[i], max) > 0)
max = &a[i];
return *max;
}
return mean;
}
+function MEDIAN.1 (a[n])
+{
+ return median (a, n);
+}
+
function MIN.1 (a[n])
{
double min;
min = &a[0];
for (i = 1; i < n; i++)
- if (compare_string (&a[i], min) < 0)
+ if (compare_string_3way (&a[i], min) < 0)
min = &a[i];
return *min;
}
absorb_miss function NMISS (a[n])
{
- size_t i;
- size_t missing_cnt = 0;
-
- for (i = 0; i < n; i++)
- missing_cnt += a[i] == SYSMIS;
- return missing_cnt;
+ size_t n_missings = 0;
+ for (size_t i = 0; i < n; i++)
+ n_missings += a[i] == SYSMIS;
+ return n_missings;
}
absorb_miss function NVALID (a[n])
{
- size_t i;
- size_t valid_cnt = 0;
-
- for (i = 0; i < n; i++)
- valid_cnt += a[i] != SYSMIS;
- return valid_cnt;
+ size_t n_valids = 0;
+ for (size_t i = 0; i < n; i++)
+ n_valids += a[i] != SYSMIS;
+ return n_valids;
}
absorb_miss boolean function RANGE (x != SYSMIS, a[n*2])
{
struct substring *w = &a[2 * i];
struct substring *y = &a[2 * i + 1];
- if (compare_string (w, &x) <= 0 && compare_string (&x, y) <= 0)
+ if (compare_string_3way (w, &x) <= 0 && compare_string_3way (&x, y) <= 0)
return 1.;
}
return 0.;
}
}
-
function RINDEX (string haystack, string needle)
{
if (needle.length == 0)
function RINDEX (string haystack, string needles, needle_len_d)
{
- if (needle_len_d <= INT_MIN || needle_len_d >= INT_MAX
+ if (needle_len_d <= 0 || needle_len_d >= INT_MAX
|| (int) needle_len_d != needle_len_d
|| needles.length == 0)
return SYSMIS;
}
}
+string function REPLACE (string haystack, string needle, string replacement)
+ expression e;
+ = replace_string (e, haystack, needle, replacement, DBL_MAX);
+
+absorb_miss string function REPLACE (string haystack, string needle,
+ string replacement, n)
+ expression e;
+ = replace_string (e, haystack, needle, replacement, n);
+
absorb_miss string function RPAD (string s, n)
expression e;
{
string function LTRIM (string s)
{
- while (s.length > 0 && s.string[0] == ' ')
+ while (s.length > 0 && s.string[0] == ' ')
{
s.length--;
s.string++;
{
if (c.length == 1)
{
- while (s.length > 0 && s.string[0] == c.string[0])
+ while (s.length > 0 && s.string[0] == c.string[0])
{
s.length--;
s.string++;
function NUMBER (string s, ni_format f)
{
union value out;
- data_in (ss_head (s, f->w), LEGACY_NATIVE, f->type, f->d, 0, 0, NULL, &out, 0);
+ char *error;
+
+ if (s.length > f->w)
+ s.length = f->w;
+ error = data_in (s, C_ENCODING, f->type, settings_get_fmt_settings (),
+ &out, 0, NULL);
+ if (error == NULL)
+ data_in_imply_decimals (s, C_ENCODING, f->type, f->d,
+ settings_get_fmt_settings (), &out);
+ else
+ {
+ msg (SE, "Cannot parse `%.*s' as format %s: %s",
+ (int) s.length, s.string, fmt_name (f->type), error);
+ free (error);
+ }
return out.f;
}
v.f = x;
assert (!fmt_is_string (f->type));
- s = data_out (&v, LEGACY_NATIVE, f);
+ s = data_out (&v, C_ENCODING, f, settings_get_fmt_settings ());
dst = alloc_string (e, strlen (s));
strcpy (dst.string, s);
free (s);
return dst;
}
+absorb_miss string function STRUNC (string s, n)
+{
+ if (n < 1 || n == SYSMIS)
+ return empty_string;
+
+ if (n < s.length)
+ s.length = n;
+ while (s.length > 0 && s.string[s.length - 1] == ' ')
+ s.length--;
+ return s;
+}
+
absorb_miss string function SUBSTR (string s, ofs)
expression e;
{
{
if (x == 0. || x == 1. || x == SYSMIS)
return x;
+
+ if (!ss_is_empty (op_name))
+ msg (SE, _("An operand of the %.*s operator was found to have a value "
+ "other than 0 (false), 1 (true), or the system-missing "
+ "value. The result was forced to 0."),
+ (int) op_name.length, op_name.string);
else
- {
- msg (SE, _("An operand of the %.*s operator was found to have a value "
- "other than 0 (false), 1 (true), or the system-missing "
- "value. The result was forced to 0."),
- (int) op_name.length, op_name.string);
- return 0.;
- }
+ msg (SE, _("A logical expression was found to have a value other than 0 "
+ "(false), 1 (true), or the system-missing value. The result "
+ "was forced to 0."));
+ return 0.;
}
operator BOOLEAN_TO_NUM (boolean x) = x;
function IDF.GAMMA (P >= 0 && P <= 1, a > 0, b > 0)
= gsl_cdf_gamma_Pinv (P, a, 1. / b);
function PDF.GAMMA (x >= 0, a > 0, b > 0) = gsl_ran_gamma_pdf (x, a, 1. / b);
-no_opt function RV.GAMMA (a > 0, b > 0)
+no_opt function RV.GAMMA (a > 0, b > 0)
= gsl_ran_gamma (get_rng (), a, 1. / b);
// Half-normal distribution.
function IDF.LAPLACE (P > 0 && P < 1, a, b > 0)
= a + b * gsl_cdf_laplace_Pinv (P, 1);
function PDF.LAPLACE (x, a, b > 0) = gsl_ran_laplace_pdf ((x - a) / b, 1) / b;
-no_opt function RV.LAPLACE (a, b > 0)
+no_opt function RV.LAPLACE (a, b > 0)
= a + b * gsl_ran_laplace (get_rng (), 1);
// Levy alpha-stable distribution.
-no_opt extension function RV.LEVY (c, alpha > 0 && alpha <= 2)
+no_opt extension function RV.LEVY (c, alpha > 0 && alpha <= 2)
= gsl_ran_levy (get_rng (), c, alpha);
// Levy skew alpha-stable distribution.
no_opt extension function RV.LVSKEW (c, alpha > 0 && alpha <= 2,
- beta >= -1 && beta <= 1)
+ beta >= -1 && beta <= 1)
= gsl_ran_levy_skew (get_rng (), c, alpha, beta);
// Logistic distribution.
= a + b * gsl_cdf_logistic_Pinv (P, 1);
function PDF.LOGISTIC (x, a, b > 0)
= gsl_ran_logistic_pdf ((x - a) / b, 1) / b;
-no_opt function RV.LOGISTIC (a, b > 0)
+no_opt function RV.LOGISTIC (a, b > 0)
= a + b * gsl_ran_logistic (get_rng (), 1);
// Lognormal distribution.
= gsl_cdf_lognormal_Pinv (P, log (m), s);
function PDF.LNORMAL (x >= 0, m > 0, s > 0)
= gsl_ran_lognormal_pdf (x, log (m), s);
-no_opt function RV.LNORMAL (m > 0, s > 0)
+no_opt function RV.LNORMAL (m > 0, s > 0)
= gsl_ran_lognormal (get_rng (), log (m), s);
// Normal distribution.
// Normal tail distribution.
function PDF.NTAIL (x, a > 0, sigma > 0)
= gsl_ran_gaussian_tail_pdf (x, a, sigma);
-no_opt function RV.NTAIL (a > 0, sigma > 0)
+no_opt function RV.NTAIL (a > 0, sigma > 0)
= gsl_ran_gaussian_tail (get_rng (), a, sigma);
// Pareto distribution.
= gsl_cdf_rayleigh_Pinv (P, sigma);
extension function PDF.RAYLEIGH (x, sigma > 0)
= gsl_ran_rayleigh_pdf (x, sigma);
-no_opt extension function RV.RAYLEIGH (sigma > 0)
+no_opt extension function RV.RAYLEIGH (sigma > 0)
= gsl_ran_rayleigh (get_rng (), sigma);
// Rayleigh tail distribution.
extension function PDF.RTAIL (x, a, sigma)
= gsl_ran_rayleigh_tail_pdf (x, a, sigma);
-no_opt extension function RV.RTAIL (a, sigma)
+no_opt extension function RV.RTAIL (a, sigma)
= gsl_ran_rayleigh_tail (get_rng (), a, sigma);
// Studentized maximum modulus distribution.
// Type-1 Gumbel distribution.
extension function CDF.T1G (x, a, b) = gsl_cdf_gumbel1_P (x, a, b);
extension function IDF.T1G (P >= 0 && P <= 1, a, b)
- = gsl_cdf_gumbel1_P (P, a, b);
+ = gsl_cdf_gumbel1_Pinv (P, a, b);
extension function PDF.T1G (x, a, b) = gsl_ran_gumbel1_pdf (x, a, b);
no_opt extension function RV.T1G (a, b) = gsl_ran_gumbel1 (get_rng (), a, b);
// Type-2 Gumbel distribution.
extension function CDF.T2G (x, a, b) = gsl_cdf_gumbel2_P (x, a, b);
extension function IDF.T2G (P >= 0 && P <= 1, a, b)
- = gsl_cdf_gumbel2_P (P, a, b);
+ = gsl_cdf_gumbel2_Pinv (P, a, b);
extension function PDF.T2G (x, a, b) = gsl_ran_gumbel2_pdf (x, a, b);
no_opt extension function RV.T2G (a, b) = gsl_ran_gumbel2 (get_rng (), a, b);
no_opt function RV.WEIBULL (a > 0, b > 0) = gsl_ran_weibull (get_rng (), a, b);
// Bernoulli distribution.
-function CDF.BERNOULLI (k == 0 || k == 1, p >= 0 && p <= 1)
+function CDF.BERNOULLI (k == 0 || k == 1, p >= 0 && p <= 1)
= k ? 1 : 1 - p;
function PDF.BERNOULLI (k == 0 || k == 1, p >= 0 && p <= 1)
= gsl_ran_bernoulli_pdf (k, p);
-no_opt function RV.BERNOULLI (p >= 0 && p <= 1)
+no_opt function RV.BERNOULLI (p >= 0 && p <= 1)
= gsl_ran_bernoulli (get_rng (), p);
// Binomial distribution.
n > 0 && n == floor (n),
p >= 0 && p <= 1)
= gsl_ran_binomial_pdf (k, p, n);
-no_opt function RV.BINOM (p > 0 && p == floor (p), n >= 0 && n <= 1)
+no_opt function RV.BINOM (p > 0 && p == floor (p), n >= 0 && n <= 1)
= gsl_ran_binomial (get_rng (), p, n);
// Geometric distribution.
// Logarithmic distribution.
extension function PDF.LOG (k >= 1, p > 0 && p <= 1)
= gsl_ran_logarithmic_pdf (k, p);
-no_opt extension function RV.LOG (p > 0 && p <= 1)
+no_opt extension function RV.LOG (p > 0 && p <= 1)
= gsl_ran_logarithmic (get_rng (), p);
// Negative binomial distribution.
= gsl_cdf_negative_binomial_P (k, p, n);
function PDF.NEGBIN (k >= 1, n == floor (n), p > 0 && p <= 1)
= gsl_ran_negative_binomial_pdf (k, p, n);
-no_opt function RV.NEGBIN (n == floor (n), p > 0 && p <= 1)
+no_opt function RV.NEGBIN (n == floor (n), p > 0 && p <= 1)
= gsl_ran_negative_binomial (get_rng (), p, n);
// Poisson distribution.
no_opt function RV.POISSON (mu > 0) = gsl_ran_poisson (get_rng (), mu);
// Weirdness.
-absorb_miss boolean function MISSING (x) = x == SYSMIS || !finite (x);
-absorb_miss boolean function SYSMIS (x) = x == SYSMIS || !finite (x);
+absorb_miss boolean function MISSING (x) = x == SYSMIS || !isfinite (x);
+absorb_miss boolean function SYSMIS (x) = x == SYSMIS || !isfinite (x);
no_opt boolean function SYSMIS (num_var v)
case c;
{
vector v;
case c;
{
- if (idx >= 1 && idx <= vector_get_var_cnt (v))
+ if (idx >= 1 && idx <= vector_get_n_vars (v))
{
const struct variable *var = vector_get_var (v, (size_t) idx - 1);
double value = case_num (c, var);
- return !var_is_num_missing (var, value, MV_USER) ? value : SYSMIS;
+ return !var_is_num_missing (var, value, MV_USER) ? value : SYSMIS;
}
else
{
vector v;
case c;
{
- if (idx >= 1 && idx <= vector_get_var_cnt (v))
+ if (idx >= 1 && idx <= vector_get_n_vars (v))
{
struct variable *var = vector_get_var (v, (size_t) idx - 1);
- return copy_string (e, case_str (c, var), var_get_width (var));
+ return copy_string (e, CHAR_CAST_BUG (char *, case_str (c, var)),
+ var_get_width (var));
}
else
{
{
const struct ccase *c = lagged_case (ds, n_before);
if (c != NULL)
- return copy_string (e, case_str (c, v), var_get_width (v));
+ return copy_string (e, CHAR_CAST_BUG (char *, case_str (c, v)),
+ var_get_width (v));
else
return empty_string;
}
{
const struct ccase *c = lagged_case (ds, 1);
if (c != NULL)
- return copy_string (e, case_str (c, v), var_get_width (v));
+ return copy_string (e, CHAR_CAST_BUG (char *, case_str (c, v)),
+ var_get_width (v));
else
return empty_string;
}
projects / pspp / blobdiff