TODO.lisp

   1 ;;; -*- mode: lisp -*-
   2
   3 ;;; Time-stamp: <2008-11-25 18:56:39 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:    demonstrations of how one might use CLS.
   9
  10 ;;; What is this talk of 'release'? Klingons do not make software
  11 ;;; 'releases'.  Our software 'escapes', leaving a bloody trail of
  12 ;;; designers and quality assurance people in its wake.
  13
  14 ;;; This file contains the current challenges to solve, including a
  15 ;;; description of the setup and the work to solve....
  16
  17 ;;; SET UP
  18
  19 (in-package :cl-user)
  20 ;;(asdf:oos 'asdf:compile-op 'lispstat)
  21 ;;(asdf:oos 'asdf:load-op 'lispstat)
  22
  23 (in-package :lisp-stat-unittests)
  24
  25 (describe (run-tests :suite 'lisp-stat-ut))
  26 (run-tests :suite 'lisp-stat-ut)
  27 ;; tests = 68, failures = 12, errors = 5
  28
  29 (in-package :ls-user)
  30
  31 ;;; FIXME: Example: currently not relevant, yet
  32 #|
  33   (describe
  34     (lift::run-test
  35       :test-case  'lisp-stat-unittests::create-proto
  36       :suite 'lisp-stat-unittests::lisp-stat-ut-proto))
  37 |#
  38
  39 :;; FIXME: data frames and structural inheritance
  40 ;;
  41 ;; Serious flaw -- need to consider that we are not really well
  42 ;; working with the data structures, in that Luke created compound as
  43 ;; a base class, which turns out to be slightly backward if we are to
  44 ;; maintain the numerical structures as well as computational
  45 ;; efficiency.
  46
  47
  48
  49 ;;; FIXME: Regression modeling
  50
  51 (defparameter m nil
  52   "holding variable.")
  53 (def m (regression-model (list iron aluminum) absorbtion :print nil))
  54 (send m :compute)
  55 (send m :sweep-matrix)
  56 (format t "~%~A~%" (send m :sweep-matrix))
  57
  58 ;; need to get multiple-linear regression working (simple linear regr
  59 ;; works)... to do this, we need to redo the whole numeric structure,
  60 ;; I'm keeping these in as example of brokenness...
  61
  62 (send m :basis) ;; this should be positive?
  63 (send m :coef-estimates)
  64
  65 ;;; FIXME: Need to clean up data examples, licenses, attributions, etc.
  66
  67 ;; The following breaks because we should use a package to hold
  68 ;; configuration details, and this would be the only package outside
  69 ;; of packages.lisp, as it holds the overall defsystem structure.
  70 (load-data "iris.lsp")  ;; (the above partially fixed).
  71 (variables)
  72 diabetes
  73
  74
  75 ;;; FIXME: Data.Frames probably deserve to be related to lists --
  76 ;;; either lists of cases, or lists of variables.  We probably do not
  77 ;;; want to mix them, but want to be able to convert between such
  78 ;;; structures.
  79
  80 (defparameter *my-case-data*
  81   '((:cases
  82      (:case1 Y Med  3.4 5)
  83      (:case2 N Low  3.2 3)
  84      (:case3 Y High 3.1 4))
  85     (:var-names (list "Response" "Level" "Pressure" "Size"))))
  86
  87 *my-case-data*
  88
  89 (elt *my-case-data* 1)
  90 (elt *my-case-data* 0)
  91 (elt *my-case-data* 2) ;; error
  92 (elt (elt *my-case-data* 0) 1)
  93 (elt (elt *my-case-data* 0) 0)
  94 (elt (elt (elt *my-case-data* 0) 1) 0)
  95 (elt (elt (elt *my-case-data* 0) 1) 1)
  96 (elt (elt (elt *my-case-data* 0) 1) 2)
  97 (elt (elt *my-case-data* 0) 3)
  98
  99
 100 ;;; FIXME: read data from CSV file.  To do.
 101
 102 ;; challenge is to ensure that we get mixed arrays when we want them,
 103 ;; and single-type (simple) arrays in other cases.
 104
 105 (defparameter *csv-num* (read-csv "Data/example-num.csv" :type 'numeric))
 106 (defparameter *csv-mix* (read-csv "Data/example-mixed.csv" :type 'data))
 107
 108 ;; The handling of these types should be compariable to what we do for
 109 ;; matrices, but without the numerical processing.  i.e. mref, bind2,
 110 ;; make-dataframe, and the class structure should be similar.
 111
 112 ;; With numerical data, there should be a straightforward mapping from
 113 ;; the data.frame to a matrix.   With categorical data (including
 114 ;; dense categories such as doc-strings, as well as sparse categories
 115 ;; such as binary data), we need to include metadata about ordering,
 116 ;; coding, and such.  So the structures should probably consider
 117
 118 ;; Using the CSV file:
 119
 120 (asdf:oos 'asdf:compile-op 'csv :force t)
 121 (asdf:oos 'asdf:load-op 'parse-number)
 122 (asdf:oos 'asdf:load-op 'csv)
 123 (fare-csv:read-csv-file "Data/example-numeric.csv")
 124
 125 ;; but I think the cl-csv package is broken, need to use the dsv-style
 126 ;; package.