From: Ben Pfaff Date: Sun, 23 Dec 2018 18:54:01 +0000 (-0800) Subject: tests: Add "categorical" keyword to tests that use categoricals. X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=2e40fba218250a31e244007b15c1fc4b637145d4;p=pspp tests: Add "categorical" keyword to tests that use categoricals. This makes it easier to run tests just for these. --- diff --git a/tests/language/stats/examine.at b/tests/language/stats/examine.at index 6ccfac555a..9d4374d376 100644 --- a/tests/language/stats/examine.at +++ b/tests/language/stats/examine.at @@ -17,6 +17,7 @@ dnl AT_BANNER([EXAMINE]) AT_SETUP([EXAMINE]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [ DATA LIST LIST /QUALITY * W * BRAND * . BEGIN DATA @@ -188,6 +189,7 @@ Breaking Strain,Aspeger,Mean,,2.25,.45 AT_CLEANUP AT_SETUP([EXAMINE -- extremes]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl data list free /V1 W begin data. @@ -249,6 +251,7 @@ AT_CLEANUP AT_SETUP([EXAMINE -- extremes with fractional weights]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([extreme.sps], [dnl set format=F20.3. data list notable list /w * x *. @@ -325,6 +328,7 @@ dnl Test the PERCENTILES subcommand of the EXAMINE command. dnl In particular test that it behaves properly when there are only dnl a few cases. AT_SETUP([EXAMINE -- percentiles]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /X *. BEGIN DATA. @@ -417,6 +421,7 @@ X,Empirical with averaging,2.00,2.00,2.00,5.00,8.00,8.00,8.00 AT_CLEANUP AT_SETUP([EXAMINE -- missing values]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /x * y *. BEGIN DATA. @@ -457,6 +462,7 @@ AT_CLEANUP AT_SETUP([EXAMINE -- user missing values]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-m.sps], [dnl DATA LIST notable LIST /x * y *. BEGIN DATA. @@ -483,6 +489,7 @@ y,2,66.6667%,1,33.3333%,3,100% AT_CLEANUP AT_SETUP([EXAMINE -- missing values and percentiles]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /X *. BEGIN DATA. @@ -503,6 +510,7 @@ AT_CLEANUP dnl Tests the trimmed mean calculation in the case dnl where the data is weighted towards the centre. AT_SETUP([EXAMINE -- trimmed mean]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /X * C *. BEGIN DATA. @@ -550,6 +558,7 @@ X,Mean,,2.02,.03 AT_CLEANUP AT_SETUP([EXAMINE -- crash bug]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl data list list /a * x * y *. begin data. @@ -568,6 +577,7 @@ AT_CLEANUP dnl Test that two consecutive EXAMINE commands don't crash PSPP. AT_SETUP([EXAMINE -- consecutive runs don't crash]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl data list list /y * z *. begin data. @@ -586,6 +596,7 @@ AT_CLEANUP dnl Test that /DESCRIPTIVES does not crash in presence of missing values. AT_SETUP([EXAMINE -- missing values don't crash]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl data list list /x * y *. begin data. @@ -603,6 +614,7 @@ AT_CLEANUP dnl Test that having only a single case doesn't crash. AT_SETUP([EXAMINE -- single case doesn't crash]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /quality * . BEGIN DATA @@ -622,6 +634,7 @@ AT_CLEANUP dnl Test that all-missing data doesn't crash. AT_SETUP([EXAMINE -- all-missing data doesn't crash]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl DATA LIST LIST /x *. BEGIN DATA. @@ -644,6 +657,7 @@ AT_CLEANUP dnl Test that big input doesn't crash (bug 11307). AT_SETUP([EXAMINE -- big input doesn't crash]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine.sps], [dnl INPUT PROGRAM. LOOP #I=1 TO 50000. @@ -664,6 +678,7 @@ AT_CLEANUP dnl Another test that big input doesn't crash. dnl The actual bug that this checks for has been lost. AT_SETUP([EXAMINE -- big input doesn't crash 2]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([make-big-input.pl], [for ($i=0; $i<100000; $i++) { print "AB12\n" }; for ($i=0; $i<100000; $i++) { print "AB04\n" }; @@ -691,6 +706,7 @@ AT_CLEANUP dnl Test that the ID command works with non-numberic variables AT_SETUP([EXAMINE -- non-numeric ID]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-id.sps], [dnl data list notable list /x * y (a12). @@ -743,6 +759,7 @@ AT_CLEANUP dnl Test for a crash which happened on cleanup from a bad input syntax AT_SETUP([EXAMINE -- Bad Input]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-bad.sps], [dnl data list list /h * g *. @@ -773,7 +790,7 @@ AT_CLEANUP dnl Check the MISSING=REPORT option AT_SETUP([EXAMINE -- MISSING=REPORT]) - +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-report.sps], [dnl set format = F22.0. @@ -901,6 +918,7 @@ dnl Run a test of the basic STATISTICS using a "real" dnl dataset and comparing with "real" results kindly dnl provided by Olaf Nöhring AT_SETUP([EXAMINE -- sample unweighted]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([sample.sps], [dnl set format = F22.4. @@ -1044,6 +1062,7 @@ AT_CLEANUP dnl Test for a crash which happened on bad input syntax AT_SETUP([EXAMINE -- Empty Parentheses]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-empty-parens.sps], [dnl DATA LIST notable LIST /X * @@ -1068,6 +1087,7 @@ AT_CLEANUP dnl Test for another crash which happened on bad input syntax AT_SETUP([EXAMINE -- Bad variable]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-bad-variable.sps], [dnl data list list /h * g *. @@ -1091,6 +1111,7 @@ AT_CLEANUP dnl Test for yet another crash. This time for extremes vs. missing weight values. AT_SETUP([EXAMINE -- Extremes vs. Missing Weights]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([examine-missing-weights.sps], [dnl data list notable list /h * g *. diff --git a/tests/language/stats/glm.at b/tests/language/stats/glm.at index bbc343bc50..564c8dee40 100644 --- a/tests/language/stats/glm.at +++ b/tests/language/stats/glm.at @@ -17,6 +17,7 @@ dnl AT_BANNER([GLM procedure]) AT_SETUP([GLM latin square design]) +AT_KEYWORDS([categorical categoricals]) dnl This example comes from : dnl http://ssnds.uwo.ca/statsexamples/spssanova/latinsquareresults.html @@ -88,6 +89,7 @@ Corrected Total,329.62,35,,, AT_CLEANUP AT_SETUP([GLM 2 by 2 factorial design]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([2by2.sps], [dnl set format = F20.3. @@ -140,6 +142,7 @@ AT_CLEANUP AT_SETUP([GLM Type I and II Sums of Squares]) +AT_KEYWORDS([categorical categoricals]) dnl The following example comes from dnl http://www.uvm.edu/~dhowell/StatPages/More_Stuff/Type1-3.pdf @@ -273,6 +276,7 @@ AT_CLEANUP AT_SETUP([GLM excluded intercept]) +AT_KEYWORDS([categorical categoricals]) dnl The following example comes from dnl @@ -344,6 +348,7 @@ AT_CLEANUP AT_SETUP([GLM missing values]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([glm.data], [dnl 1 1 6 3.5 diff --git a/tests/language/stats/logistic.at b/tests/language/stats/logistic.at index 3d7ae76c38..d604c0ad14 100644 --- a/tests/language/stats/logistic.at +++ b/tests/language/stats/logistic.at @@ -95,6 +95,7 @@ dnl Note: In the above data cases 305, 316 318 and 329 have identical values dnl of the 2nd and 3rd variables. We use this for weight testing. AT_SETUP([LOGISTIC REGRESSION basic test]) +AT_KEYWORDS([categorical categoricals]) LOGIT_TEST_DATA @@ -147,6 +148,7 @@ Step 1,survrate,-.081,.019,17.756,1,.000,.922 AT_CLEANUP AT_SETUP([LOGISTIC REGRESSION missing values]) +AT_KEYWORDS([categorical categoricals]) LOGIT_TEST_DATA @@ -195,6 +197,7 @@ dnl Check that a weighted dataset is interpreted correctly dnl To do this, the same data set is used, one weighted, one not. dnl The weighted dataset omits certain cases which are identical AT_SETUP([LOGISTIC REGRESSION weights]) +AT_KEYWORDS([categorical categoricals]) LOGIT_TEST_DATA @@ -256,6 +259,7 @@ dnl Check that the /NOCONST option works as intended. dnl The results this produces are very similar to those dnl at the example in http://www.ats.ucla.edu/stat/SPSS/faq/logregconst.htm AT_SETUP([LOGISTIC REGRESSION without constant]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([non-const.sps], [dnl set format=F20.3. @@ -313,6 +317,7 @@ AT_CLEANUP dnl Check that if somebody passes a dependent variable which is not dichtomous, dnl then an error is raised. AT_SETUP([LOGISTIC REGRESSION non-dichotomous dep var]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([non-dich.sps], [dnl data list notable list /y x1 x2 x3 x4. @@ -338,6 +343,7 @@ dnl An example to check the behaviour of LOGISTIC REGRESSION with a categorical dnl variable. This examṕle was inspired from that at: dnl http://www.ats.ucla.edu/stat/spss/dae/logit.htm AT_SETUP([LOGISTIC REGRESSION with categorical]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([lr-cat.data], [dnl 620 3.07 2 4 @@ -806,6 +812,7 @@ AT_CLEANUP dnl This example is inspired by http://www.ats.ucla.edu/stat/spss/output/logistic.htm AT_SETUP([LOGISTIC REGRESSION with cat var 2]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([lr-cat2.data], [dnl 60.00 1.00 8.00 50.00 @@ -1073,6 +1080,7 @@ AT_CLEANUP dnl Check that it doesn't crash if a categorical variable dnl has only one distinct value AT_SETUP([LOGISTIC REGRESSION identical categories]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash.sps], [dnl data list notable list /y x1 x2*. @@ -1093,6 +1101,7 @@ AT_CLEANUP dnl Test that missing values on the categorical predictors are treated dnl properly. AT_SETUP([LOGISTIC REGRESSION missing categoricals]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([data.txt], [dnl .00 3.69 .00 @@ -1230,6 +1239,7 @@ dnl Use an example with categoricals, because that was buggy at dnl one point. The data in this example comes from: dnl http://people.ysu.edu/~gchang/SPSSE/SPSS_lab2Regression.pdf AT_SETUP([LOGISTIC REGRESSION confidence interval]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([ci.sps], [dnl set FORMAT=F20.3 diff --git a/tests/language/stats/means.at b/tests/language/stats/means.at index aa59242d5c..d4db9ec8af 100644 --- a/tests/language/stats/means.at +++ b/tests/language/stats/means.at @@ -17,6 +17,7 @@ dnl AT_BANNER([MEANS procedure]) AT_SETUP([MEANS simple example]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-simple.sps], [dnl SET FORMAT=F12.5. @@ -78,6 +79,7 @@ AT_CLEANUP AT_SETUP([MEANS very simple example]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-vsimple.sps], [dnl SET FORMAT=F12.5. @@ -112,6 +114,7 @@ AT_CLEANUP AT_SETUP([MEANS default missing]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-dmiss.sps], [dnl SET FORMAT=F12.2. @@ -166,6 +169,7 @@ AT_CLEANUP AT_SETUP([MEANS linear stats]) +AT_KEYWORDS([categorical categoricals]) dnl Slightly more involved example to test the linear statistics AT_DATA([means-linear.sps], [dnl @@ -215,6 +219,7 @@ AT_CLEANUP AT_SETUP([MEANS standard errors]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-stderr.sps], [dnl set format F12.4. @@ -261,6 +266,7 @@ AT_CLEANUP AT_SETUP([MEANS harmonic and geometric means]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-hg.sps], [dnl set format F12.4. @@ -303,6 +309,7 @@ AT_CLEANUP AT_SETUP([MEANS all/none/default]) +AT_KEYWORDS([categorical categoricals]) dnl Make sure that /CELLS = {ALL,NONE,DEFAULT} work properly AT_DATA([means-stat-keywords.sps], [dnl @@ -363,6 +370,7 @@ AT_CLEANUP AT_SETUP([MEANS missing=table ]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-miss-table.sps], [dnl data list notable list /a * b * g1. @@ -473,6 +481,7 @@ AT_CLEANUP AT_SETUP([MEANS user missing values]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-missing.sps], [dnl data list notable list /a * b * g1. @@ -571,6 +580,7 @@ AT_CLEANUP AT_SETUP([MEANS empty factor spec]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([means-bad.sps], [dnl data list list /outcome *. @@ -591,6 +601,7 @@ AT_CLEANUP AT_SETUP([MEANS parser bug]) +AT_KEYWORDS([categorical categoricals]) dnl This bug caused an infinite loop AT_DATA([means-bad.sps], [dnl diff --git a/tests/language/stats/oneway.at b/tests/language/stats/oneway.at index 6cec759749..58fd75e289 100644 --- a/tests/language/stats/oneway.at +++ b/tests/language/stats/oneway.at @@ -17,6 +17,7 @@ dnl AT_BANNER([ONEWAY procedure]) AT_SETUP([ONEWAY basic operation]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway.sps], [DATA LIST NOTABLE LIST /QUALITY * BRAND * . BEGIN DATA @@ -86,6 +87,7 @@ AT_CLEANUP AT_SETUP([ONEWAY with splits]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-splits.sps], [DATA LIST NOTABLE LIST /QUALITY * BRAND * S *. BEGIN DATA @@ -193,6 +195,7 @@ AT_CLEANUP AT_SETUP([ONEWAY with missing values]) +AT_KEYWORDS([categorical categoricals]) dnl Check that missing are treated properly AT_DATA([oneway-missing1.sps], [DATA LIST NOTABLE LIST /v1 * v2 * dep * vn *. @@ -298,6 +301,7 @@ AT_CLEANUP AT_SETUP([ONEWAY descriptives subcommand]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-descriptives.sps], [DATA LIST NOTABLE LIST /QUALITY * BRAND * . @@ -347,6 +351,7 @@ AT_CLEANUP AT_SETUP([ONEWAY homogeneity subcommand]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-homogeneity.sps], [DATA LIST NOTABLE LIST /QUALITY * BRAND * . @@ -392,6 +397,7 @@ AT_CLEANUP AT_SETUP([ONEWAY multiple variables]) +AT_KEYWORDS([categorical categoricals]) dnl check that everything works ok when several different dependent variables are specified. dnl This of course does not mean that we're doing a multivariate analysis. It's just like dnl running several tests at once. @@ -500,6 +506,7 @@ AT_CLEANUP dnl Tests that everything treats weights properly AT_SETUP([ONEWAY vs. weights]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-unweighted.sps], [DATA LIST NOTABLE LIST /QUALITY * BRAND * W *. @@ -571,6 +578,7 @@ AT_CLEANUP AT_SETUP([ONEWAY posthoc LSD and BONFERRONI]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-pig.sps],[dnl SET FORMAT F12.3. data list notable list /pigmentation * family *. @@ -653,6 +661,7 @@ AT_CLEANUP AT_SETUP([ONEWAY posthoc Tukey HSD and Games-Howell]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-tukey.sps],[dnl set format = f11.3. data list notable list /libido * dose *. @@ -709,6 +718,7 @@ Games-Howell,Placebo,1 Dose,-1.000,.887,.479,-3.356,1.356 AT_CLEANUP AT_SETUP([ONEWAY posthoc Sidak]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-sidak.sps],[dnl SET FORMAT F20.4. @@ -769,6 +779,7 @@ Table: Multiple Comparisons (score) AT_CLEANUP AT_SETUP([ONEWAY posthoc Scheffe]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-scheffe.sps],[dnl set format = f11.3. data list notable list /usage * group *. @@ -851,6 +862,7 @@ AT_CLEANUP AT_SETUP([ONEWAY bad contrast count]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([oneway-bad-contrast.sps],[dnl DATA LIST NOTABLE LIST /height * weight * temperature * sex *. @@ -922,6 +934,7 @@ AT_CLEANUP AT_SETUP([ONEWAY crash on single category independent variable]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash.sps],[ input program. loop #i = 1 to 10. @@ -943,6 +956,7 @@ AT_CLEANUP AT_SETUP([ONEWAY crash on missing dependent variable]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash2.sps],[dnl data list notable list /dv1 * dv2 * y * . begin data. @@ -971,6 +985,7 @@ AT_CLEANUP AT_SETUP([ONEWAY Games-Howell test with few cases]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash3.sps],[dnl data list notable list /dv * y * . begin data. @@ -993,6 +1008,7 @@ AT_CLEANUP AT_SETUP([ONEWAY Crash on empty data]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash4.sps],[dnl DATA LIST NOTABLE LIST /height * weight * temperature * sex *. BEGIN DATA. @@ -1015,6 +1031,7 @@ AT_CLEANUP AT_SETUP([ONEWAY Crash on invalid dependent variable]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash5.sps],[dnl data list notable list /a * b *. begin data. @@ -1035,6 +1052,7 @@ AT_CLEANUP AT_SETUP([ONEWAY Crash on unterminated string]) +AT_KEYWORDS([categorical categoricals]) AT_DATA([crash6.sps], [dnl DATA LIST NOTABLE LIST /height * weight * temperature * sex *.