TODO.lisp

   1 ;;; -*- mode: lisp -*-
   2
   3 ;;; Time-stamp: <2010-03-19 08:17:46 tony>
   4 ;;; Creation:   <2008-09-08 08:06:30 tony>
   5 ;;; File:       TODO.lisp
   6 ;;; Author:     AJ Rossini <blindglobe@gmail.com>
   7 ;;; Copyright:  (c) 2007-2008, AJ Rossini <blindglobe@gmail.com>.  BSD.
   8 ;;; Purpose: Stuff that needs to be made working sits inside the
   9 ;;;          progns... This file contains the current challenges to
  10 ;;;          solve, including a description of the setup and the work
  11 ;;;          to solve....
  12
  13 ;;; What is this talk of 'release'? Klingons do not make software
  14 ;;; 'releases'.  Our software 'escapes', leaving a bloody trail of
  15 ;;; designers and quality assurance people in its wake.
  16
  17 ;;; SET UP
  18
  19 (in-package :cl-user)
  20
  21 (progn
  22   (defun init-CLS ()
  23
  24     ;; core system
  25     ;;(asdf:oos 'asdf:load-op 'lisp-matrix)
  26     ;;(asdf:oos 'asdf:compile-op 'cls :force t)
  27     (asdf:oos 'asdf:load-op 'cls)
  28
  29     ;; visualization
  30     (asdf:oos 'asdf:load-op 'cl-cairo2-x11)
  31     (asdf:oos 'asdf:load-op 'cl-2d)
  32
  33     ;; doc reporting
  34     (asdf:oos 'asdf:load-op 'cl-pdf)
  35     (asdf:oos 'asdf:load-op 'cl-typesetting))
  36
  37   ;;INFRA
  38   ;; (asdf:oos 'asdf:compile-op 'asdf-system-connections :force t)\x01
  39   ;; (asdf:oos 'asdf:compile-op 'lisp-matrix)
  40   ;; (asdf:oos 'asdf:load-op 'xarray)
  41
  42   ;;DOCS
  43   ;;; (asdf:oos 'asdf:compile-op 'metatilities-base :force t)
  44   ;;; (asdf:oos 'asdf:load-op 'metatilities-base)
  45   ;;; (asdf:oos 'asdf:load-op 'anaphora)
  46   ;;; (asdf:oos 'asdf:load-op 'tinaa)
  47   ;;; (asdf:oos 'asdf:load-op 'cl-ppcre)
  48   ;; (asdf:oos 'asdf:load-op 'cl-markdown) ;; just need this and the next...
  49   ;; (asdf:oos 'asdf:load-op 'docudown)
  50
  51   ;;use of extension packages supporting versioning and validation of
  52   ;;CLOS objects?
  53   ;; (asdf:oos 'asdf:compile-op 'versioned-objects :force t)
  54   ;; (asdf:oos 'asdf:load-op 'versioned-objects)
  55   ;; (asdf:oos 'asdf:compile-op 'validations :force t)
  56   ;; (asdf:oos 'asdf:load-op 'validations)
  57
  58   ;;VIZ
  59   ;; (asdf:oos 'asdf:compile-op 'cffi :force t)
  60   ;; (asdf:oos 'asdf:load-op 'cl-opengl)
  61   ;; (asdf:oos 'asdf:load-op 'cl-glu)
  62   ;; (asdf:oos 'asdf:load-op 'cl-glut)
  63   ;; (asdf:oos 'asdf:load-op 'cl-glut-examples)
  64
  65   ;; (asdf:oos 'asdf:load-op 'cells)
  66   (asdf:oos 'asdf:load-op 'bordeaux-threads)
  67   ;; (asdf:oos 'asdf:load-op 'cells-gtk)
  68
  69   (init-CLS))
  70
  71 (in-package :lisp-stat-unittests)
  72
  73 ;; tests = 78, failures = 7, errors = 20
  74 (run-tests :suite 'lisp-stat-ut)
  75
  76 (asdf:oos 'asdf:test-op 'cls)
  77 ;; which runs (describe (run-tests :suite 'lisp-stat-ut))
  78
  79 (describe 'lisp-stat-ut)
  80 (documentation 'lisp-stat-ut 'type)
  81
  82 ;; FIXME: Example: currently not relevant, yet
  83 ;;   (describe (lift::run-test :test-case  'lisp-stat-unittests::create-proto
  84 ;;                             :suite 'lisp-stat-unittests::lisp-stat-ut-proto))
  85
  86 (describe (lift::run-tests :suite 'lisp-stat-ut-dataframe))
  87 (lift::run-tests :suite 'lisp-stat-ut-dataframe)
  88
  89 (describe (lift::run-test
  90            :test-case  'lisp-stat-unittests::create-proto
  91            :suite 'lisp-stat-unittests::lisp-stat-ut-proto))
  92
  93 (in-package :ls-user)
  94
  95 ;;; Tasks working on...
  96
  97 #+nil
  98 (progn )
  99
 100 #+nil
 101 (progn
 102   ;; Syntax examples using lexical scope, closures, and bindings to
 103   ;; ensure a clean communication of results
 104   (with-data dataset ((dsvarname1 [usevarname1])
 105                       (dsvarname2 [usevarname2]))
 106       @body))
 107
 108 (defparameter *df-test*
 109   (make-instance 'dataframe-array
 110                  :storage #2A (('a "test0" 0 0d0)
 111                                ('b "test1" 1 1d0)
 112                                ('c "test2" 2 2d0)
 113                                ('d "test3" 3 3d0)
 114                                ('e "test4" 4 4d0))
 115                  :doc "test reality"
 116                  :case-labels (list "0" "1" 2 "3" "4")
 117                  :var-labels (list "symbol" "string" "integer" "double-float")
 118                  :var-types (list 'symbol 'string 'integer 'double-float)))
 119
 120 *df-test* ; but with SBCL, ints become floats?
 121
 122 (defun check-var (df colnum)
 123   (let ((nobs (xdim (dataset df) 0)))
 124     (dotimes (i nobs)
 125       (check-type (xref df i colnum) (elt (var-types df) i)))))
 126
 127 (xdim (dataset *df-test*) 1)
 128 (xdim (dataset *df-test*) 0)
 129
 130 (check-var *df-test* 0)
 131
 132 (check-type (xref *df-test* 1 1) simple-character-string)
 133 (xref *df-test* 1 2)
 134
 135 (class-of
 136   (xref *df-test* 1 1) )
 137
 138 (check-type)
 139
 140
 141
 142 (integerp (xref *df-test* 1 2))
 143 (floatp (xref *df-test* 1 2))
 144 (integerp (xref *df-test* 1 3))
 145 (type-of (xref *df-test* 1 3))
 146 (floatp (xref *df-test* 1 3))
 147
 148 (type-of (vector 1 1d0))
 149
 150
 151
 152 (loop )
 153
 154 (xref *df-test* 2 1)
 155 (xref *df-test* 0 0)
 156 (xref *df-test* 1 0)
 157 (xref *df-test* 1 '*)
 158
 159 ;;; Experiments with cl-variates
 160
 161 ;; (asdf:oos 'asdf:compile-op 'cl-variates :force t)
 162 ;; (asdf:oos 'asdf:compile-op 'cl-variates-test :force t)
 163 ;; (asdf:oos 'asdf:load-op 'lift)
 164 ;; (asdf:oos 'asdf:load-op 'cl-variates)
 165 (asdf:oos 'asdf:load-op 'cl-variates-test)
 166
 167 (in-package :cl-variates-test)
 168 ;; check tests
 169 (run-tests :suite 'cl-variates-test)
 170 (describe (run-tests :suite 'cl-variates-test))
 171
 172 (in-package :cl-variates-user)
 173 ;; example usage
 174 (defparameter state (make-random-number-generator))
 175 (setf (random-seed state) 44)
 176 (random-seed state)
 177 (loop for i from 1 to 10 collect
 178                   (random-range state 0 10))
 179 ;; => (1 5 1 0 7 1 2 2 8 10)
 180 (setf (random-seed state) 44)
 181 (loop for i from 1 to 10 collect
 182                   (random-range state 0 10))
 183 ;; => (1 5 1 0 7 1 2 2 8 10)
 184
 185 (setf (random-seed state) 44)
 186 (random-seed state)
 187 (loop for i from 1 to 10 collect
 188                   (normal-random state 0 1))
 189 ;; =>
 190 ;; (-1.2968656102820426 0.40746363934173213 -0.8594712469518473 0.8795681301148328
 191 ;;  1.0731526250004264 -0.8161629082481728 0.7001813608754809 0.1078045427044097
 192 ;;  0.20750134211656893 -0.14501914108452274)
 193
 194 (setf (random-seed state) 44)
 195 (loop for i from 1 to 10 collect
 196                   (normal-random state 0 1))
 197 ;; =>
 198 ;; (-1.2968656102820426 0.40746363934173213 -0.8594712469518473 0.8795681301148328
 199 ;;  1.0731526250004264 -0.8161629082481728 0.7001813608754809 0.1078045427044097
 200 ;;  0.20750134211656893 -0.14501914108452274)
 201
 202
 203 ;;; experiments with LLA
 204 (in-package :cl-user)
 205 (asdf:oos 'asdf:load-op 'lla)
 206 (in-package :lla-user)
 207
 208
 209
 210 (in-package :cls-user)
 211 ;;;; PFIM notes
 212
 213 ;; PFIM 3.2
 214
 215 ;; population design eval and opt
 216 #|
 217 issues:
 218 - # individuals
 219 - # sampling times
 220 - sampling times?
 221
 222 constraints:
 223 number of samples/cost of lab analysis and collection
 224 expt constraints
 225 |#
 226
 227 (defun pfim (&key model ( constraints ( summary-function )
 228
 229   (list num-subjects num-times list-times))))
 230
 231 #|
 232 N individuals i
 233 Each individal has a deisgn psi_i
 234    nubmer of samples n_i and sampling times t_{i{1}} t_{i{n_1}}
 235    individuals can differ
 236
 237 Model:
 238
 239 individual-level model
 240 |#
 241
 242 (=model y_i (+ (f \theta_i \psi_i) epsilion_i ))
 243 (=var \epsilion_i \sigma_between \sigma_within  )
 244
 245 ;; Information Matrix for pop deisgn
 246
 247 (defparameter IM (sum  (i 1 N) (MF \psi_i \phi_i)))
 248
 249 #|
 250 For nonlinear structureal models, expand around RE=0
 251
 252 Cramer-Rao : MF^{-1} is lower bound for estimation variance.
 253
 254 Design comparisons:
 255
 256 - smallest SE, but is a matrix, so
 257 - criteria for matrix comparison
 258 -- D-opt, (power (determinant MF) (/ 1 P))
 259
 260
 261 find design maxing D opt, (power (determinant MF) (/ 1 P))
 262 Design varialables
 263  -- contin vars for smapling times within interval or set
 264  -- number of groups for cat vars
 265
 266 Stat in Med 2009, expansion around post-hoc RE est, not necessarily zero.
 267
 268 Example binary covariate C
 269 |#
 270
 271 (if (= i reference-class)
 272     (setf (aref C i) 0)
 273     (setf (aref C i) 1))
 274
 275 ;; Exponential RE,
 276 (=model (log \theta) (  ))
 277
 278 ;; extensions
 279
 280 ;; outputs
 281
 282 #|
 283 PFIM provides for a given design and values of \beta:
 284  compute extended FIM
 285  SE/RSE for \beta of each class of each covar
 286  eval influence of design on SE(\beta)
 287
 288 inter-occassion variability (IOV)
 289 - patients sampled more than once, H occassions
 290 - RE for IOV
 291 - additional vars to estimate
 292
 293 |#
 294
 295 ;;; comparison criteria
 296
 297 functional of conc/time curve which is used for comparison, i.e.
 298 (AUC conc/time-curve)
 299 (Cmax conc/time-curve)
 300 (Tmax conc/time-curve)
 301
 302 where
 303
 304 (defun conc/time-curve (t)
 305   ;; computation
 306 #|
 307   (let ((conc (exp (* t \beta1))))
 308      conc)
 309 |#
 310   )
 311
 312 ;;See
 313 (url-get "www.pfim.biostat.fr")
 314
 315 ;;; Thinking of generics...
 316 (information-matrix model parameters)
 317 (information-matrix variance-matrix)
 318 (information-matrix model data)
 319 (information-matrix list-of-individual-IMs)
 320
 321
 322 (defun IM (loglikelihood parameters times)
 323   "Does double work.  Sum up the resulting IMs to form a full IM."
 324   (let ((IM (make-matrix (length parameters)
 325                          (length parameters)
 326                          :initial-value 0.0d0)))
 327     (dolist (parameterI parameters)
 328       (dolist (parameterJ parameters)
 329         (setf (aref IM I J)
 330               (differentiate (differentiate loglikelihood parameterI) parameterJ))))))
 331
 332
 333
 334 ;; difference between empirical, fisherian, and ...? information.
 335
 336 ;;; Docudown...