2 ;;; Copyright (c) 2007, by A.J. Rossini <blindglobe@gmail.com>
3 ;;; See COPYRIGHT file for any additional restrictions (BSD license).
4 ;;; Since 1991, ANSI was finally finished. Edited for ANSI Common Lisp.
6 ;;; This is semi-external to lispstat core packages. The dependency
7 ;;; should be that lispstat packages are dependencies for the unit
8 ;;; tests. However, where they will end up is still to be
13 (defpackage :lisp-stat-unittests
14 (:use
:common-lisp
:lift
:lisp-stat
)
15 (:shadowing-import-from
:lisp-stat
16 slot-value call-method call-next-method
;; objects
17 expt
+ -
* / ** mod rem abs
1+ 1- log exp sqrt sin cos tan
;; lsmath
18 asin acos atan sinh cosh tanh asinh acosh atanh float random
19 truncate floor ceiling round minusp zerop plusp evenp oddp
20 < <= = /= >= > ;; complex
21 conjugate realpart imagpart phase
22 min max logand logior logxor lognot ffloor fceiling
23 ftruncate fround signum cis
)
24 (:export run-lisp-stat-tests run-lisp-stat-test scoreboard
))
26 (in-package :lisp-stat-unittests
)
30 (defun run-lisp-stat-tests ()
31 (run-tests :suite
'lisp-stat
))
33 (defun run-lisp-stat-test (&rest x
)
37 (deftestsuite lisp-stat
() ())
38 (deftestsuite lisp-stat-lin-alg
(lisp-stat) ())
39 (deftestsuite lisp-stat-spec-fns
(lisp-stat) ())
40 (deftestsuite lisp-stat-probdistn
(lisp-stat) ())
43 (defun almost= (a b
&key
(tol 0.000001))
44 "Numerically compares 2 values to a tolerance."
45 (< (abs (- a b
)) tol
))
47 (defun almost=lists
(a b
&key
(tol 0.000001))
48 "Numerically compare 2 lists using almost=."
49 (if (and (null a
) (null b
))
51 (and (almost= (car a
) (car b
) :tol tol
)
52 (almost=lists
(cdr a
) (cdr b
) :tol tol
))))
56 ;; Need to consider a CLOSy approach for almost= to cover the range of
57 ;; possible data structures that we would like to be equal to a
58 ;; particular tolerance range. For example, fill in a shell like:
60 (defgeneric numerical
= (a b
&key tol
))
62 (defmethod numerical= ((a real
) (b real
) &key
(tol 0.00001)) ;; real))
63 ;;(print (format nil " equality pred for real a=~w real b=~w" a b))
64 (< (abs (- a b
)) tol
))
66 ;; can we just worry about reals if integers are a subclass?
67 (defmethod numerical= ((a integer
) (b integer
) &key
(tol 0.1)) ;; real))
68 ;;(print (format nil " equality pred for int a=~w int b=~w" a b))
69 (< (abs (- a b
)) tol
))
71 (defmethod numerical= ((a complex
) (b complex
) &key
(tol 0.00001))
72 ;;(print (format nil " equality pred for cmplx a=~w cmplx b=~w" a b))
73 (< (abs (- a b
)) tol
))
75 (defmethod numerical= ((a sequence
) (b sequence
) &key
(tol 0.00001))
76 ;; (print (format nil "checking equality for list a ~w list b=~w" a b))
77 ;; using sequence for lists and vectors, but not arrays.
78 ;; FIXME++++ This is too slow, too many comparisons!
79 (if (and (null a
) (null b
))
81 (if (and (= (length a
) (length b
))
83 (numerical= (car a
) (car b
) :tol tol
))
85 (if (= (length (cdr a
)) 0)
87 (numerical= (cdr a
) (cdr b
) :tol tol
)))
92 (defmethod numerical= ((a array
) (b array
) &key
(tol 0.00001))
93 (print (format nil
"checking equality for array a ~w and array b=~w" a b
))
94 ;;; FIXME Warning! Need to generalize past 2-d array!!
95 (if (/= (array-dimensions a
) (array-dimensions b
))
97 (let* ((a-dim (array-dimensions a
))
98 (a-b-elt-eq (loop for i from
0 to
(nth 0 a-dim
)
99 for j from
0 to
(nth 1 a-dim
)
100 collect
(numerical= (apply #'aref a
(list i j
))
101 (apply #'aref b
(list i j
))
103 (every #'(lambda (x) x
) a-b-elt-eq
))))
105 (deftestsuite lisp-stat-testsupport
(lisp-stat)
108 (almost=1 (ensure (almost= 3 3.001 :tol
0.01)))
109 (almost=2 (ensure (almost= 3 3.01 :tol
0.01)))
110 (almost=3 (ensure (not (almost= 3 3.1 :tol
0.01))))
111 (almost=lists1
(ensure (almost=lists nil nil
:tol
0.01)))
112 (almost=lists2
(ensure (almost=lists
(list ) (list ) :tol
0.01)))
113 (almost=lists3
(ensure (almost=lists
(list 1.0) (list 1.0) :tol
0.01)))
114 (almost=lists4
(ensure (almost=lists
(list 1.0 1.0) (list 1.0 1.0) :tol
0.01)))
115 (almost=lists5
(ensure (not (almost=lists
(list 1.0 1.0)
116 (list 1.0 1.1) :tol
0.01))))))
118 (deftestsuite lisp-stat-testsupport2
(lisp-stat)
121 (numerical=1 (ensure (numerical= 3 3.001 :tol
0.01)))
122 (numerical=1.1 (ensure (numerical= 2 2)))
123 (numerical=1.2 (ensure (not (numerical= 2 3))))
124 (numerical=2 (ensure (numerical= 3 3.01 :tol
0.01)))
125 (numerical=3 (ensure (not (numerical= 3 3.1 :tol
0.01))))
126 (numerical=4 (ensure (numerical= nil nil
:tol
0.01)))
127 (numerical=5 (ensure (numerical= (list ) (list ) :tol
0.01)))
128 (numerical=6 (ensure (numerical= (list 1.0) (list 1.0) :tol
0.01)))
129 (numerical=7 (ensure (numerical= (list 1.0 1.0) (list 1.0 1.0) :tol
0.01)))
130 (numerical=7.5 (ensure-error (numerical= 1.0 (list 1.0 1.0) :tol
0.01)))
131 (numerical=8 (ensure (not (numerical= (list 2.0 2.0 2.2) (list 2.1 2.0 2.2)))))
132 (numerical=9 (ensure (numerical= (list 2.1 2.0 2.2) (list 2.1 2.0 2.2)) ))
133 (numerical=10 (ensure (numerical= (list 2.1 2.0 2.2 4.2) (list 2.1 2.0 2.2 4.2))))
134 (numerical=11 (ensure (not (numerical= (list 2.1 2.0 2.3 4.0) (list 2.1 2.0 2.2 4.0)))))
135 (numerical=12 (ensure (not (numerical= (list 1.0 1.0)
136 (list 1.0 1.1) :tol
0.01))))
137 (numerical=C1
(ensure (numerical= #C
(2 3) #C
(2 3))))
138 (numerical=C2
(ensure (not(numerical= #C
(2 3) #C
(2 4)))))
139 (numerical=C3
(ensure (numerical= #C
(2 3) #C
(3 4) :tol
2)))
140 (numerical=C4
(ensure (not(numerical= #C
(2 3) #C
(3 4) :tol
1))))
144 (numerical=A1
(ensure (numerical= #1A
(2 3 4)
147 (numerical=A2
(ensure (numerical= #2A
((2 3 4) (1 2 4) (2 4 5))
148 #2A
((2 3 4) (1 2 4) (2 4 5)))))
150 (numerical=A3
(ensure (not (numerical= #2A
((2 3 4) (1 2 4) (2 5 4))
151 #2A
((2 3 4) (1 2 4) (2 4 5))))))
153 (numerical=A4
(ensure (not (numerical= #1A
(2 2 4)
158 ;; (describe (run-tests :suite 'lisp-stat-testsupport2))
162 (addtest (lisp-stat-lin-alg) cholesky-decomposition-1
164 (chol-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
165 (list #2A
((1.7888543819998317
0.0 0.0)
166 (1.6770509831248424
0.11180339887498929 0.0)
167 (2.23606797749979
2.23606797749979 3.332000937312528e-8))
169 :test
'almost
=lists
))
171 ;(addtest (lisp-stat-lin-alg) cholesky-decomposition-1a
173 ; (chol-decomp #2A((2 3 4) (1 2 4) (2 4 5)))
174 ; (list #2A((1.7888543819998317 0.0 0.0)
175 ; (1.6770509831248424 0.11180339887498929 0.0)
176 ; (2.23606797749979 2.23606797749979 3.332000937312528e-8))
178 ; :test 'numerical=))
180 (addtest (lisp-stat-lin-alg) lu-decomposition
182 (lu-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
183 (list #2A
((2.0
3.0 4.0) (1.0
1.0 1.0) (0.5
0.5 1.5)) #(0 2 2) -
1.0 NIL
)))
185 (addtest (lisp-stat-lin-alg) rcondest
187 (ensure-error ;; it barfs, FIXME!!
188 (rcondest #2A
((2 3 4) (1 2 4) (2 4 5)))
192 (addtest (lisp-stat-lin-alg) lu-solve
196 #2A
((2 3 4) (1 2 4) (2 4 5)))
198 #(-2.333333333333333
1.3333333333333335 0.6666666666666666)))
200 (addtest (lisp-stat-lin-alg) inverse
202 (inverse #2A
((2 3 4) (1 2 4) (2 4 5)))
203 #2A
((2.0 -
0.33333333333333326 -
1.3333333333333335)
204 (-1.0 -
0.6666666666666666 1.3333333333333333)
205 (0.0
0.6666666666666666 -
0.3333333333333333))))
207 (addtest (lisp-stat-lin-alg) sv-decomp
209 (sv-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
210 (list #2A
((-0.5536537653489974
0.34181191712789266 -
0.7593629708013371)
211 (-0.4653437312661058 -
0.8832095891230851 -
0.05827549615722014)
212 (-0.6905959164998124
0.3211003503429828 0.6480523475178517))
213 #(9.699290438141343
0.8971681569301373 0.3447525123483081)
214 #2A
((-0.30454218417339873
0.49334669582252344 -
0.8147779426198863)
215 (-0.5520024849987308
0.6057035911404464 0.5730762743603965)
216 (-0.7762392122368734 -
0.6242853493399995 -
0.08786630745236332))
218 :test
'almost
=lists
))
220 (addtest (lisp-stat-lin-alg) qr-decomp
222 (qr-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
223 (list #2A
((-0.6666666666666665
0.7453559924999298 5.551115123125783e-17)
224 (-0.3333333333333333 -
0.2981423969999719 -
0.894427190999916)
225 (-0.6666666666666666 -
0.5962847939999439 0.44721359549995787))
226 #2A
((-3.0 -
5.333333333333334 -
7.333333333333332)
227 (0.0 -
0.7453559924999292 -
1.1925695879998877)
228 (0.0
0.0 -
1.3416407864998738)))
229 :test
'almost
=lists
))
231 (addtest (lisp-stat-lin-alg) eigen
233 (eigen #2A
((2 3 4) (1 2 4) (2 4 5)))
234 (list #(10.656854249492381 -
0.6568542494923802 -
0.9999999999999996)
235 (list #(0.4999999999999998
0.4999999999999997 0.7071067811865475)
236 #(-0.49999999999999856 -
0.5000000000000011 0.7071067811865474)
237 #(0.7071067811865483 -
0.7071067811865466 -
1.2560739669470215e-15))
240 (addtest (lisp-stat-lin-alg) spline
242 (spline #(1.0
1.2 1.3 1.8 2.1 2.5)
243 #(1.2
2.0 2.1 2.0 1.1 2.8)
245 (list (list 1.0 1.3 1.6 1.9 2.2 2.5)
246 (list 1.2 2.1 2.2750696543866313 1.6465231041904045 1.2186576148879609 2.8))
247 :test
'almost
=lists
))
249 (addtest (lisp-stat-lin-alg) kernel-smooth
251 ;; using KERNEL-SMOOTH-FRONT, not KERNEL-SMOOTH-CPORT
253 #(1.0
1.2 1.3 1.8 2.1 2.5)
254 #(1.2
2.0 2.1 2.0 1.1 2.8)
256 (list (list 1.0 1.375 1.75 2.125 2.5)
257 (list 1.6603277642110226 1.9471748095239771 1.7938127405752287
258 1.5871511322219498 2.518194783156392))
259 :test
'almost
=lists
))
261 (addtest (lisp-stat-lin-alg) kernel-dens
264 #(1.0
1.2 2.5 2.1 1.8 1.2)
266 (list (list 1.0 1.375 1.75 2.125 2.5)
267 (list 0.7224150453621405 0.5820045548233707 0.38216411702854214
268 0.4829822708587095 0.3485939156929503))))
271 (addtest (lisp-stat-lin-alg) fft
273 (fft #(1.0
1.2 2.5 2.1 1.8))
274 (list #(#C
(1.0
0.0) #C
(1.2
0.0) #C
(2.5
0.0) #C
(2.1
0.0) #C
(1.8
0.0)))
275 :test
'almost
=lists
))
278 (addtest (lisp-stat-lin-alg) lowess
280 (lowess #(1.0
1.2 2.5 2.1 1.8 1.2)
281 #(1.2
2.0 2.1 2.0 1.1 2.8))
282 #(1.0
1.2 1.2 1.8 2.1 2.5)
283 :test
'almost
=lists
)) ;; result isn't a list!
287 ;;;; Log-gamma function
289 (addtest (lisp-stat-spec-fns) log-gamma-fn
296 ;;; Probability distributions
298 ;; This macro should be generalized, but it's a good start now.
299 ;;(defmacro ProbDistnTests (prefixName
300 ;; quant-params quant-answer
301 ;; cdf-params cdf-answer
302 ;; pmf-params pmf-answer
303 ;; rand-params rand-answer)
304 ;; (deftestsuite lisp-stat-probdist-,prefixName (lisp-stat-probdistn)
306 ;; (:documentation "testing for ,testName distribution results")
307 ;; (:test (ensure-same
308 ;; (lisp-stat-basics:,testName-quant ,quant-params) ,quant-answer))
309 ;; (:test (ensure-same
310 ;; (lisp-stat-basics:,testName-cdf ,cdf-params) ,cdf-answer))
311 ;; (:test (ensure-same
312 ;; (lisp-stat-basics:,testName-pmf ,pmf-params) ,pmf-answer))
316 ;; (lisp-stat-basics:,testName-rand ,rand-params) ,rand-answer)))))
318 ;;; Normal distribution
320 (deftestsuite lisp-stat-probdist-f
(lisp-stat-probdistn)
322 (:documentation
"testing for Gaussian distn results")
331 0.17136859204780736))
334 (list -
0.40502015f0 -
0.8091404f0
)))
336 (bivnorm-cdf 0.2 0.4 0.6)
337 0.4736873734160288)))
339 ;;;; Cauchy distribution
341 (deftestsuite lisp-stat-probdist-cauchy
(lisp-stat-probdistn)
343 (:documentation
"testing for Cachy-distn results")
352 0.1183308127104695 ))
355 (list -
1.06224644160405 -
0.4524695943939537))))
357 ;;;; Gamma distribution
359 (deftestsuite lisp-stat-probdist-gamma
(lisp-stat-probdistn)
361 (:documentation
"testing for gamma distn results")
363 (gamma-quant 0.95 4.3)
367 0.028895150986674906))
373 (list 2.454918912880936 4.081365384357454))))
375 ;;;; Chi-square distribution
377 (deftestsuite lisp-stat-probdist-chisq
(lisp-stat-probdistn)
379 (:documentation
"testing for Chi-square distn results")
385 0.03743422675631789))
388 0.08065690818083521))
393 (list 1.968535826180572 2.9988646156942997)))))
395 ;;;; Beta distribution
397 (deftestsuite lisp-stat-probdist-beta
(lisp-stat-probdistn)
399 (:documentation
"testing for beta distn results")
401 (beta-quant 0.95 3 2)
405 0.4247997418541529 ))
407 (beta-dens 0.4 2 2.4)
408 1.5964741858913518 ))
411 (list 0.8014897077282279 0.6516371997922659))))
415 (deftestsuite lisp-stat-probdist-t
(lisp-stat-probdistn)
417 (:documentation
"testing for t-distn results")
429 (list -
0.34303672776089306 -
1.142505872436518))))
433 (deftestsuite lisp-stat-probdist-f
(lisp-stat-probdistn)
435 (:documentation
"testing for f-distn results")
437 (f-quant 0.95 3 5) 5.409451318117459))
443 0.37551128864591415))
448 (list 0.7939093442091963 0.07442694152491144)))))
450 ;;;; Poisson distribution
452 (deftestsuite lisp-stat-probdist-poisson
(lisp-stat-probdistn)
454 (:documentation
"testing for poisson distribution results")
456 (poisson-quant 0.95 3.2) 6))
459 0.17120125672252395))
462 0.13043905274097067))
469 ;; Binomial distribution
471 (deftestsuite lisp-stat-probdist-binomial
(lisp-stat-probdistn)
473 (:documentation
"testing for binomial distribution results")
476 (binomial-quant 0.95 3 0.4) ;;; DOESN'T RETURN
479 (binomial-quant 0 3 0.4)
483 (binomial-cdf 1 3 0.4)
487 (binomial-pmf 1 3 0.4)
492 (binomial-rand 5 3 0.4)
497 ;;;; Object System tests
499 ;;(deftestsuite lisp-stat-proto-objects (lisp-stat)
501 ;; (:documentation "Make sure the proto object system is valid.")
503 ;; (create-proto (ensure (object-proto-p (defproto test-me))))
504 ;; (create-proto2 (ensure (object-proto-p (defproto2 test-me2))))
505 ;; (instance1 (ensure (send test-me :isnew)))
506 ;; (instance1-2 (ensure (send test-me2 :isnew)))
507 ;; (instance2 (ensure (send test-me :has-slot 'new)))
508 ;; (instance2-2 (ensure (send test-me2 :has-slot 'new)))
510 ;; (instance5 (ensure (send test-me :has-slot 'new)))
511 ;; (instance5-2 (ensure (send test-me2 :has-slot 'new)))
512 ;; (instance5 (ensure (send test-me :own-slots 'new)))
513 ;; (instance5-2 (ensure (send test-me2 :own-slots 'new)))
514 ;; (instance5 (ensure (send test-me :has-slot 'new)))
515 ;; (instance5-2 (ensure (send test-me2 :has-slot 'new)))
516 ;; (instance5 (ensure (send test-me :has-slot 'new)))
517 ;; (instance5-2 (ensure (send test-me2 :has-slot 'new)))