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 conjugate realpart imagpart phase
21 min max logand logior logxor lognot ffloor fceiling
22 ftruncate fround signum cis
)
23 (:export run-lisp-stat-tests run-lisp-stat-test scoreboard
))
25 (in-package :lisp-stat-unittests
)
29 (defun run-lisp-stat-tests ()
30 (run-tests :suite
'lisp-stat
))
32 (defun run-lisp-stat-test (&rest x
)
36 (deftestsuite lisp-stat
() ())
37 (deftestsuite lisp-stat-lin-alg
(lisp-stat) ())
38 (deftestsuite lisp-stat-spec-fns
(lisp-stat) ())
39 (deftestsuite lisp-stat-probdistn
(lisp-stat) ())
42 (defun almost= (a b
&key
(tol 0.000001))
43 "Numerically compares 2 values to a tolerance."
44 (< (abs (- a b
)) tol
))
46 (defun almost=lists
(a b
&key
(tol 0.000001))
47 "Numerically compare 2 lists using almost=."
48 (if (and (null a
) (null b
))
50 (and (almost= (car a
) (car b
) :tol tol
)
51 (almost=lists
(cdr a
) (cdr b
) :tol tol
))))
55 ;; Need to consider a CLOSy approach for almost= to cover the range of
56 ;; possible data structures that we would like to be equal to a
57 ;; particular tolerance range. For example, fill in a shell like:
59 (defgeneric numerical
= (a b
&key tol
))
61 (defmethod numerical= ((a real
) (b real
) &key
(tol 0.00001)) ;; real))
62 (print (format nil
" equality pred for real a=%l real b=%l" a b
))
63 (< (abs (- a b
)) tol
))
65 (defmethod numerical= ((a integer
) (b integer
) &key
(tol 0.1)) ;; real))
66 (print (format nil
" equality pred for int a=~l int b=~l" (list a b
)))
67 (< (abs (- a b
)) tol
))
69 (defmethod numerical= ((a complex
) (b complex
) &key
(tol 0.00001)) ;; real))
70 (< (abs (- a b
)) tol
))
72 ;; can we use sequence for both array and list? I think so.
73 (defmethod numerical= ((a sequence
) (b sequence
) &key
(tol 0.00001))
74 (print (format nil
"checking equality for list a %l list b=%l" a b
))
75 (if (and (= (length a
) (length b
))
77 (numerical= (car a
) (car b
) :tol tol
))
79 (numerical= (cdr a
) (cdr b
) :tol tol
))
81 ;; FIXME++++ This is too slow, a few too many comparisons.
83 (numerical= (list 2.0 2.0 2.2) (list 2.1 2.0 2.2))
84 (numerical= (list 2.1 2.0 2.2) (list 2.1 2.0 2.2))
86 (numerical= (list 2.1 2.0 2.2 4.2) (list 2.1 2.0 2.2 4.2))
87 (numerical= (list 2.1 2.0 2.3 4.0) (list 2.1 2.0 2.2 4.0))
89 (let ((a (list 2.1 2.0 2.2 4.2))
90 (b (list 2.0 2.1 2.2 4.2)))
91 (and (= (length a
) (length b
))
92 (numerical= (car a
) (car b
))))
95 ;; (defmethod numerical= ((complex a) (complex b) &key (tol 0.00001))
96 ;; (defmethod numerical= ((list a) (list b) &key (tol 0.00001))
97 ;; (defmethod numerical= ((array a) (array b) &key (tol 0.00001))
101 (deftestsuite lisp-stat-testsupport
(lisp-stat)
104 (almost=1 (ensure (almost= 3 3.001 :tol
0.01)))
105 (almost=2 (ensure (almost= 3 3.01 :tol
0.01)))
106 (almost=3 (ensure (not (almost= 3 3.1 :tol
0.01))))
107 (almost=lists1
(ensure (almost=lists nil nil
:tol
0.01)))
108 (almost=lists2
(ensure (almost=lists
(list ) (list ) :tol
0.01)))
109 (almost=lists3
(ensure (almost=lists
(list 1.0) (list 1.0) :tol
0.01)))
110 (almost=lists4
(ensure (almost=lists
(list 1.0 1.0) (list 1.0 1.0) :tol
0.01)))
111 (almost=lists5
(ensure (not (almost=lists
(list 1.0 1.0)
112 (list 1.0 1.1) :tol
0.01))))))
114 (deftestsuite lisp-stat-testsupport2
(lisp-stat)
117 (numerical=1 (ensure (numerical= 3 3.001 :tol
0.01)))
118 (numerical=2 (ensure (numerical= 3 3.01 :tol
0.01)))
119 (numerical=3 (ensure (not (numerical= 3 3.1 :tol
0.01))))
120 (numerical=4 (ensure (numerical= nil nil
:tol
0.01)))
121 (numerical=5 (ensure (numerical= (list ) (list ) :tol
0.01)))
122 (numerical=6 (ensure (numerical= (list 1.0) (list 1.0) :tol
0.01)))
123 (numerical=7 (ensure (numerical= (list 1.0 1.0) (list 1.0 1.0) :tol
0.01)))
124 (numerical=8 (ensure (not (numerical= (list 1.0 1.0)
125 (list 1.0 1.1) :tol
0.01))))))
130 (numerical= 2.0 2.1 :tol
0.5)
133 (numerical= 2.0 (list 2.1 2.0 2.2))
138 (addtest (lisp-stat-lin-alg) cholesky-decomposition-1
140 (chol-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
141 (list #2A
((1.7888543819998317
0.0 0.0)
142 (1.6770509831248424
0.11180339887498929 0.0)
143 (2.23606797749979
2.23606797749979 3.332000937312528e-8))
145 :test
'almost
=lists
))
147 (addtest (lisp-stat-lin-alg) lu-decomposition
149 (lu-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
150 (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
)))
152 (addtest (lisp-stat-lin-alg) rcondest
154 (ensure-error ;; it barfs, FIXME!!
155 (rcondest #2A
((2 3 4) (1 2 4) (2 4 5)))
159 (addtest (lisp-stat-lin-alg) lu-solve
163 #2A
((2 3 4) (1 2 4) (2 4 5)))
165 #(-2.333333333333333
1.3333333333333335 0.6666666666666666)))
167 (addtest (lisp-stat-lin-alg) inverse
169 (inverse #2A
((2 3 4) (1 2 4) (2 4 5)))
170 #2A
((2.0 -
0.33333333333333326 -
1.3333333333333335)
171 (-1.0 -
0.6666666666666666 1.3333333333333333)
172 (0.0
0.6666666666666666 -
0.3333333333333333))))
174 (addtest (lisp-stat-lin-alg) sv-decomp
176 (sv-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
177 (list #2A
((-0.5536537653489974
0.34181191712789266 -
0.7593629708013371)
178 (-0.4653437312661058 -
0.8832095891230851 -
0.05827549615722014)
179 (-0.6905959164998124
0.3211003503429828 0.6480523475178517))
180 #(9.699290438141343
0.8971681569301373 0.3447525123483081)
181 #2A
((-0.30454218417339873
0.49334669582252344 -
0.8147779426198863)
182 (-0.5520024849987308
0.6057035911404464 0.5730762743603965)
183 (-0.7762392122368734 -
0.6242853493399995 -
0.08786630745236332))
185 :test
'almost
=lists
))
187 (addtest (lisp-stat-lin-alg) qr-decomp
189 (qr-decomp #2A
((2 3 4) (1 2 4) (2 4 5)))
190 (list #2A
((-0.6666666666666665
0.7453559924999298 5.551115123125783e-17)
191 (-0.3333333333333333 -
0.2981423969999719 -
0.894427190999916)
192 (-0.6666666666666666 -
0.5962847939999439 0.44721359549995787))
193 #2A
((-3.0 -
5.333333333333334 -
7.333333333333332)
194 (0.0 -
0.7453559924999292 -
1.1925695879998877)
195 (0.0
0.0 -
1.3416407864998738)))
196 :test
'almost
=lists
))
198 (addtest (lisp-stat-lin-alg) eigen
200 (eigen #2A
((2 3 4) (1 2 4) (2 4 5)))
201 (list #(10.656854249492381 -
0.6568542494923802 -
0.9999999999999996)
202 (list #(0.4999999999999998
0.4999999999999997 0.7071067811865475)
203 #(-0.49999999999999856 -
0.5000000000000011 0.7071067811865474)
204 #(0.7071067811865483 -
0.7071067811865466 -
1.2560739669470215e-15))
207 (addtest (lisp-stat-lin-alg) spline
209 (spline #(1.0
1.2 1.3 1.8 2.1 2.5)
210 #(1.2
2.0 2.1 2.0 1.1 2.8)
212 (list (list 1.0 1.3 1.6 1.9 2.2 2.5)
213 (list 1.2 2.1 2.2750696543866313 1.6465231041904045 1.2186576148879609 2.8))
214 :test
'almost
=lists
))
216 (addtest (lisp-stat-lin-alg) kernel-smooth
218 ;; using KERNEL-SMOOTH-FRONT, not KERNEL-SMOOTH-CPORT
220 #(1.0
1.2 1.3 1.8 2.1 2.5)
221 #(1.2
2.0 2.1 2.0 1.1 2.8)
223 (list (list 1.0 1.375 1.75 2.125 2.5)
224 (list 1.6603277642110226 1.9471748095239771 1.7938127405752287
225 1.5871511322219498 2.518194783156392))
226 :test
'almost
=lists
))
228 (addtest (lisp-stat-lin-alg) kernel-dens
231 #(1.0
1.2 2.5 2.1 1.8 1.2)
233 (list (list 1.0 1.375 1.75 2.125 2.5)
234 (list 0.7224150453621405 0.5820045548233707 0.38216411702854214
235 0.4829822708587095 0.3485939156929503))))
238 (addtest (lisp-stat-lin-alg) fft
240 (fft #(1.0
1.2 2.5 2.1 1.8))
241 (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)))
242 :test
'almost
=lists
))
245 (addtest (lisp-stat-lin-alg) lowess
247 (lowess #(1.0
1.2 2.5 2.1 1.8 1.2)
248 #(1.2
2.0 2.1 2.0 1.1 2.8))
249 #(1.0
1.2 1.2 1.8 2.1 2.5)
250 :test
'almost
=lists
)) ;; result isn't a list!
254 ;;;; Log-gamma function
256 (addtest (lisp-stat-spec-fns) log-gamma-fn
263 ;;; Probability distributions
265 ;; This macro should be generalized, but it's a good start now.
266 ;;(defmacro ProbDistnTests (prefixName
267 ;; quant-params quant-answer
268 ;; cdf-params cdf-answer
269 ;; pmf-params pmf-answer
270 ;; rand-params rand-answer)
271 ;; (deftestsuite lisp-stat-probdist-,prefixName (lisp-stat-probdistn)
273 ;; (:documentation "testing for ,testName distribution results")
274 ;; (:test (ensure-same
275 ;; (lisp-stat-basics:,testName-quant ,quant-params) ,quant-answer))
276 ;; (:test (ensure-same
277 ;; (lisp-stat-basics:,testName-cdf ,cdf-params) ,cdf-answer))
278 ;; (:test (ensure-same
279 ;; (lisp-stat-basics:,testName-pmf ,pmf-params) ,pmf-answer))
283 ;; (lisp-stat-basics:,testName-rand ,rand-params) ,rand-answer)))))
285 ;;; Normal distribution
287 (deftestsuite lisp-stat-probdist-f
(lisp-stat-probdistn)
289 (:documentation
"testing for Gaussian distn results")
298 0.17136859204780736))
301 (list -
0.40502015f0 -
0.8091404f0
)))
303 (bivnorm-cdf 0.2 0.4 0.6)
304 0.4736873734160288)))
306 ;;;; Cauchy distribution
308 (deftestsuite lisp-stat-probdist-cauchy
(lisp-stat-probdistn)
310 (:documentation
"testing for Cachy-distn results")
319 0.1183308127104695 ))
322 (list -
1.06224644160405 -
0.4524695943939537))))
324 ;;;; Gamma distribution
326 (deftestsuite lisp-stat-probdist-gamma
(lisp-stat-probdistn)
328 (:documentation
"testing for gamma distn results")
330 (gamma-quant 0.95 4.3)
334 0.028895150986674906))
340 (list 2.454918912880936 4.081365384357454))))
342 ;;;; Chi-square distribution
344 (deftestsuite lisp-stat-probdist-chisq
(lisp-stat-probdistn)
346 (:documentation
"testing for Chi-square distn results")
352 0.03743422675631789))
355 0.08065690818083521))
360 (list 1.968535826180572 2.9988646156942997)))))
362 ;;;; Beta distribution
364 (deftestsuite lisp-stat-probdist-beta
(lisp-stat-probdistn)
366 (:documentation
"testing for beta distn results")
368 (beta-quant 0.95 3 2)
372 0.4247997418541529 ))
374 (beta-dens 0.4 2 2.4)
375 1.5964741858913518 ))
378 (list 0.8014897077282279 0.6516371997922659))))
382 (deftestsuite lisp-stat-probdist-t
(lisp-stat-probdistn)
384 (:documentation
"testing for t-distn results")
396 (list -
0.34303672776089306 -
1.142505872436518))))
400 (deftestsuite lisp-stat-probdist-f
(lisp-stat-probdistn)
402 (:documentation
"testing for f-distn results")
404 (f-quant 0.95 3 5) 5.409451318117459))
410 0.37551128864591415))
415 (list 0.7939093442091963 0.07442694152491144)))))
417 ;;;; Poisson distribution
419 (deftestsuite lisp-stat-probdist-poisson
(lisp-stat-probdistn)
421 (:documentation
"testing for poisson distribution results")
423 (poisson-quant 0.95 3.2) 6))
426 0.17120125672252395))
429 0.13043905274097067))
436 ;; Binomial distribution
438 (deftestsuite lisp-stat-probdist-binomial
(lisp-stat-probdistn)
440 (:documentation
"testing for binomial distribution results")
443 (binomial-quant 0.95 3 0.4) ;;; DOESN'T RETURN
446 (binomial-quant 0 3 0.4)
450 (binomial-cdf 1 3 0.4)
454 (binomial-pmf 1 3 0.4)
459 (binomial-rand 5 3 0.4)