Renamed reg_export_comments.h regression_export.h

diff --git a/src/reg_export_comments.h b/src/reg_export_comments.h
deleted file mode 100644 (file)
index 396f390..0000000
--- a/src/reg_export_comments.h
+++ /dev/null
@@ -1,102 +0,0 @@
-/* PSPP - Comments for C files generated by REGRESSION's EXPORT subcommand.
-   Copyright (C) 2005 Free Software Foundation, Inc.
-   Written by Jason H Stover <jason@sakla.net>.
-
-   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 2 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, write to the Free Software
-   Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
-   02110-1301, USA. */
-
-/*
-  Exported C code for a regression model. The EXPORT subcommand causes PSPP
-  to save a model as a small C program. This file contains some of the code
-  of that saved program.
- */
-#ifndef REG_EXPORT_COMMENTS_H
-#define REG_EXPORT_COMMENTS_H
-const char reg_preamble[] =  "/*\n   This program contains functions which return estimates\n"
-"   and confidence intervals for a linear model. The EXPORT subcommand\n"
-"   of the REGRESSION procedure of GNU PSPP generated this program.\n*/\n\n";
-
-const char reg_mean_cmt[] =  "/*\n   Estimate the mean of Y, the dependent variable for\n"
-"   the linear model of the form \n\n"
-"      Y = b0 + b1 * X1 + b2 * X2 + ... + bk * Xk + error\n\n"
-"   where X1, ..., Xk are the independent variables\n"
-"   whose values are stored in var_vals and whose names, \n"
-"   as known by PSPP, are stored in var_names. The estimated \n"
-"   regression coefficients (i.e., the estimates of b0,...,bk) \n"
-"   are stored in model_coeffs.\n*/\n";
-
-const char reg_getvar[] = "{\n\t\tj = pspp_reg_getvar (var_names[i]);\n"
-"\t\testimate += var_vals[j] * model_coeffs[j];\n"
-"\t}\n\t\n\treturn estimate;\n}\n\n"
-"/*\n    Variance of an estimated mean of this form:\n\t"
-"Y = b0 + b1 * X1 + ... + bk * Xk\n    where X1,...Xk are the dependent variables,"
-" stored in\n    var_vals and b0,...,bk are the estimated regression coefficients.\n*/\n"
-"double\npspp_reg_variance (const double *var_vals, "
-"const char *var_names[])\n{\n\t";
-
-const char reg_export_t_quantiles_1[] = "/*\n    Quantiles for the T distribution.\n*/\n"
-"static int\npspp_reg_t_quantile "
-"(double prob)\n{\n\n\tint i;\n\tdouble quantiles[] = {\n\t\t";
-
-const char reg_export_t_quantiles_2[] = "i = (int) 100.0 * prob;\n\treturn quantiles[i];\n}\n";
-
-const char reg_variance[] = "double result = 0.0;\n\n\tfor(i = 0; i < n_vars; i++)\n\t"
-"{\n\t\tj = pspp_reg_getvar (var_names[i]);\n\t\t"
-"unshuffled_vals[j] = var_vals[i];\n\t}\n\t"
-"for (i = 0; i < n_vars; i++)\n\t"
-"{\n\t\tresult += cov[i][i] * unshuffled_vals[i] * unshuffled_vals[i];\n\t\t"
-"for (j = i + 1; j < n_vars; j++)\n\t\t{\n\t\t\t"
-"result += 2.0 * cov[i][j] * unshuffled_vals[i] * unshuffled_vals[j];"
-"\n\t\t}\n\t}\n\treturn result;\n}\n";
-
-const char reg_export_confidence_interval[] = "/*\n    Upper confidence limit for an "
-"estimated mean b0 + b1 * X1 + ... + bk * Xk.\n    The confidence interval is a "
-"100 * p percent confidence interval.\n*/\n"
-"double pspp_reg_confidence_interval_U "
-"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
-"double result;\n\t"
-"result = sqrt (pspp_reg_variance (var_vals, var_names);\n\treturn result;\n\t"
-"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
-"result += pspp_reg_estimate (var_vals, var_names);\n}\n"
-"/*\n    Lower confidence limit for an "
-"estimated mean b0 + b1 * X1 + ... + bk * Xk.\n    The confidence interval is a "
-"100 * p percent confidence interval.\n*/\n"
-"double pspp_reg_confidence_interval_L "
-"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
-"double result;\n\t"
-"result = -sqrt (pspp_reg_variance (var_vals, var_names);\n\treturn result;\n\t"
-"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
-"result += pspp_reg_estimate (var_vals, var_names);\n}\n";
-
-const char reg_export_prediction_interval[] = "/*\n    Upper prediction limit for a "
-"predicted value b0 + b1 * X1 + ... + bk * Xk.\n    The prediction interval is a "
-"100 * p percent prediction interval.\n*/\n"
-"double pspp_reg_prediction_interval_U "
-"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
-"double result;\n\t"
-"result = 1 + sqrt (pspp_reg_variance (var_vals, var_names);\n\treturn result;\n\t"
-"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
-"result += pspp_reg_estimate (var_vals, var_names);\n}\n"
-"/*\n    Lower prediction limit for a "
-"predicted value b0 + b1 * X1 + ... + bk * Xk.\n    The prediction interval is a "
-"100 * p percent prediction interval.\n*/\n"
-"double pspp_reg_prediction_interval_L "
-"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
-"double result;\n\t"
-"result = -1.0 - sqrt (pspp_reg_variance (var_vals, var_names);\n\treturn result;\n\t"
-"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
-"result += pspp_reg_estimate (var_vals, var_names);\n}\n";
-
-#endif

diff --git a/src/regression_export.h b/src/regression_export.h
new file mode 100644 (file)
index 0000000..e7f880e
--- /dev/null
+++ b/src/regression_export.h
@@ -0,0 +1,118 @@
+/* PSPP - Comments for C files generated by REGRESSION's EXPORT subcommand.
+   Copyright (C) 2005 Free Software Foundation, Inc.
+   Written by Jason H Stover <jason@sakla.net>.
+
+   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 2 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, write to the Free Software
+   Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
+   02110-1301, USA. */
+
+/*
+  Exported C code for a regression model. The EXPORT subcommand causes PSPP
+  to save a model as a small C program. This file contains some of the code
+  of that saved program.
+ */
+#ifndef REG_EXPORT_COMMENTS_H
+#define REG_EXPORT_COMMENTS_H
+const char reg_header[] = "#ifndef REG_EXPORT_COMMENTS_H\n#define REG_EXPORT_COMMENTS_H\n"
+"double pspp_reg_estimate (const double *, const char *[]);\n\n"
+"double pspp_reg_variance (const double *var_vals, const char *[]);\n\n"
+"double pspp_reg_confidence_interval_U "
+"(const double *var_vals, const char *var_names[], double p);\n\n"
+"double pspp_reg_confidence_interval_L "
+"(const double *var_vals, const char *var_names[], double p);\n\n"
+"double pspp_reg_prediction_interval_U "
+"(const double *var_vals, const char *var_names[], double p);\n\n"
+"double pspp_reg_prediction_interval_L "
+"(const double *var_vals, const char *var_names[], double p);\n"
+"#endif\n";
+
+const char reg_preamble[] =  "/*\n   This program contains functions which return estimates\n"
+"   and confidence intervals for a linear model. The EXPORT subcommand\n"
+"   of the REGRESSION procedure of GNU PSPP generated this program.\n*/\n\n";
+
+const char reg_mean_cmt[] =  "/*\n   Estimate the mean of Y, the dependent variable for\n"
+"   the linear model of the form \n\n"
+"      Y = b0 + b1 * X1 + b2 * X2 + ... + bk * Xk + error\n\n"
+"   where X1, ..., Xk are the independent variables\n"
+"   whose values are stored in var_vals and whose names, \n"
+"   as known by PSPP, are stored in var_names. The estimated \n"
+"   regression coefficients (i.e., the estimates of b0,...,bk) \n"
+"   are stored in model_coeffs.\n*/\n";
+
+const char reg_getvar[] = "{\n\t\tj = pspp_reg_getvar (var_names[i]);\n"
+"\t\testimate += var_vals[j] * model_coeffs[j];\n"
+"\t}\n\t\n\treturn estimate;\n}\n\n"
+"/*\n    Variance of an estimated mean of this form:\n\t"
+"Y = b0 + b1 * X1 + ... + bk * Xk\n    where X1,...Xk are the dependent variables,"
+" stored in\n    var_vals and b0,...,bk are the estimated regression coefficients.\n*/\n"
+"double\npspp_reg_variance (const double *var_vals, "
+"const char *var_names[])\n{\n\t";
+
+const char reg_export_t_quantiles_1[] = "/*\n    Quantiles for the T distribution.\n*/\n"
+"static int\npspp_reg_t_quantile "
+"(double prob)\n{\n\n\tint i;\n\tdouble quantiles[] = {\n\t\t";
+
+const char reg_export_t_quantiles_2[] = "i = (int) 100.0 * prob;\n\treturn quantiles[i];\n}\n";
+
+const char reg_variance[] = "double result = 0.0;\n\n\tfor(i = 0; i < n_vars; i++)\n\t"
+"{\n\t\tj = pspp_reg_getvar (var_names[i]);\n\t\t"
+"unshuffled_vals[j] = var_vals[i];\n\t}\n\t"
+"for (i = 0; i < n_vars; i++)\n\t"
+"{\n\t\tresult += cov[i][i] * unshuffled_vals[i] * unshuffled_vals[i];\n\t\t"
+"for (j = i + 1; j < n_vars; j++)\n\t\t{\n\t\t\t"
+"result += 2.0 * cov[i][j] * unshuffled_vals[i] * unshuffled_vals[j];"
+"\n\t\t}\n\t}\n\treturn result;\n}\n";
+
+const char reg_export_confidence_interval[] = "/*\n    Upper confidence limit for an "
+"estimated mean b0 + b1 * X1 + ... + bk * Xk.\n    The confidence interval is a "
+"100 * p percent confidence interval.\n*/\n"
+"double pspp_reg_confidence_interval_U "
+"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
+"double result;\n\t"
+"result = sqrt (pspp_reg_variance (var_vals, var_names));\n\t"
+"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
+"result += pspp_reg_estimate (var_vals, var_names);\n\treturn result;\n}\n"
+"/*\n    Lower confidence limit for an "
+"estimated mean b0 + b1 * X1 + ... + bk * Xk.\n    The confidence interval is a "
+"100 * p percent confidence interval.\n*/\n"
+"double pspp_reg_confidence_interval_L "
+"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
+"double result;\n\t"
+"result = -sqrt (pspp_reg_variance (var_vals, var_names));\n\t"
+"result *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
+"result += pspp_reg_estimate (var_vals, var_names);\n\treturn result;\n}\n";
+
+const char reg_export_prediction_interval_1[] = "/*\n    Upper prediction limit for a "
+"predicted value b0 + b1 * X1 + ... + bk * Xk.\n    The prediction interval is a "
+"100 * p percent prediction interval.\n*/\n"
+"double pspp_reg_prediction_interval_U "
+"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
+"double result;\n\tresult = sqrt (";
+
+const char reg_export_prediction_interval_2[] = " + pspp_reg_variance (var_vals, var_names));\n"
+"\tresult *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
+"result += pspp_reg_estimate (var_vals, var_names);\n\treturn result;\n}\n"
+"/*\n    Lower prediction limit for a "
+"predicted value b0 + b1 * X1 + ... + bk * Xk.\n    The prediction interval is a "
+"100 * p percent prediction interval.\n*/\n"
+"double pspp_reg_prediction_interval_L "
+"(const double *var_vals, const char *var_names[], double p)\n{\n\t"
+"double result;\n\t"
+"result = -sqrt (";
+
+const char reg_export_prediction_interval_3[] = " + pspp_reg_variance (var_vals, var_names));"
+"\n\tresult *= pspp_reg_t_quantile ((1.0 + p) / 2.0);\n\t"
+"result += pspp_reg_estimate (var_vals, var_names);\n\treturn result;\n}\n";
+
+#endif