3 ;;; Time-stamp: <2009-01-03 19:36:11 tony>
4 ;;; Creation: <2008-09-08 08:06:30 tony>
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 progns...
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.
14 ;;; This file contains the current challenges to solve, including a
15 ;;; description of the setup and the work to solve....
20 ;;(asdf:oos 'asdf:compile-op 'lispstat)
21 ;;(asdf:oos 'asdf:load-op 'lispstat)
24 (in-package :lisp-stat-unittests
)
26 (describe (run-tests :suite
'lisp-stat-ut
))
27 (run-tests :suite
'lisp-stat-ut
)
29 ;; tests = 54, failures = 7, errors = 3
33 ;;; FIXME: Example: currently not relevant, yet
37 :test-case
'lisp-stat-unittests
::create-proto
38 :suite
'lisp-stat-unittests
::lisp-stat-ut-proto
))
41 :;; FIXME: data frames and structural inheritance
43 ;; Serious flaw -- need to consider that we are not really well
44 ;; working with the data structures, in that Luke created compound as
45 ;; a base class, which turns out to be slightly backward if we are to
46 ;; maintain the numerical structures as well as computational
51 (progn ;; FIXME: Regression modeling
55 ;; need to make vectors and matrices from the lists...
57 (def m
(regression-model (list->vector-like iron
)
58 (list->vector-like absorbtion
) :print nil
)) ;;Good
59 (def m
(regression-model (list->vector-like iron
)
60 (list->vector-like absorbtion
)))
62 (def m
(regression-model (listoflists->matrix-like
(list iron aluminum
))
63 (list->vector-like absorbtion
) :print nil
))
65 (defparameter *indep-vars-1-matrix
*
66 (make-matrix 1 (length iron
)
68 (list (mapcar #'(lambda (x) (coerce x
'double-float
))
70 ;; *indep-vars-1-matrix*
72 (defparameter *indep-vars-2-matrix
*
73 (make-matrix 2 (length iron
)
76 (mapcar #'(lambda (x) (coerce x
'double-float
))
78 (mapcar #'(lambda (x) (coerce x
'double-float
))
80 ;; *indep-vars-2-matrix*
83 ;; FAILS due to coercion issues; it just isn't lispy, it's R'y.
84 ;; (defparameter *dep-var* (make-vector (length absorbtion)
85 ;; :initial-contents (list absorbtion)))
86 ;; BUT this should be the right type.
87 (defparameter *dep-var
*
88 (make-vector (length absorbtion
)
92 (mapcar #'(lambda (x) (coerce x
'double-float
))
97 (defparameter *dep-var-int
*
98 (make-vector (length absorbtion
)
100 :element-type
'integer
101 :initial-contents
(list absorbtion
)))
103 (typep *dep-var
* 'matrix-like
) ; => T
104 (typep *dep-var
* 'vector-like
) ; => T
106 (typep *indep-vars-1-matrix
* 'matrix-like
) ; => T
107 (typep *indep-vars-1-matrix
* 'vector-like
) ; => T
108 (typep *indep-vars-2-matrix
* 'matrix-like
) ; => T
109 (typep *indep-vars-2-matrix
* 'vector-like
) ; => F
111 (def m1
(regression-model-new *indep-vars-1-matrix
* *dep-var
* ))
112 (def m2
(regression-model-new *indep-vars-2-matrix
* *dep-var
* ))
115 ;; following fails, need to ensure that we work on list elts, not just
116 ;; elts within a list:
117 ;; (coerce iron 'real)
119 ;; the following is a general list-conversion coercion approach -- is
120 ;; there a more efficient way?
121 (mapcar #'(lambda (x) (coerce x
'double-float
)) iron
)
126 (send m
:sweep-matrix
)
127 (format t
"~%~A~%" (send m
:sweep-matrix
))
129 ;; need to get multiple-linear regression working (simple linear regr
130 ;; works)... to do this, we need to redo the whole numeric structure,
131 ;; I'm keeping these in as example of brokenness...
133 (send m
:basis
) ;; this should be positive?
134 (send m
:coef-estimates
) )
137 (progn ;; FIXME: Need to clean up data examples, licenses, attributions, etc.
138 ;; The following breaks because we should use a package to hold
139 ;; configuration details, and this would be the only package outside
140 ;; of packages.lisp, as it holds the overall defsystem structure.
141 (load-data "iris.lsp") ;; (the above partially fixed).
146 (progn ;; FIXME: Data.Frames probably deserve to be related to lists --
147 ;; either lists of cases, or lists of variables. We probably do not
148 ;; want to mix them, but want to be able to convert between such
151 (defparameter *my-case-data
*
155 (:case3 Y High
3.1 4))
156 (:var-names
(list "Response" "Level" "Pressure" "Size"))))
160 (elt *my-case-data
* 1)
161 (elt *my-case-data
* 0)
162 (elt *my-case-data
* 2) ;; error
163 (elt (elt *my-case-data
* 0) 1)
164 (elt (elt *my-case-data
* 0) 0)
165 (elt (elt (elt *my-case-data
* 0) 1) 0)
166 (elt (elt (elt *my-case-data
* 0) 1) 1)
167 (elt (elt (elt *my-case-data
* 0) 1) 2)
168 (elt (elt *my-case-data
* 0) 3))
171 (progn ;; FIXME: read data from CSV file. To do.
173 ;; challenge is to ensure that we get mixed arrays when we want them,
174 ;; and single-type (simple) arrays in other cases.
176 (defparameter *csv-num
* (read-csv "Data/example-num.csv" :type
'numeric
))
177 (defparameter *csv-mix
* (read-csv "Data/example-mixed.csv" :type
'data
))
179 ;; The handling of these types should be compariable to what we do for
180 ;; matrices, but without the numerical processing. i.e. mref, bind2,
181 ;; make-dataframe, and the class structure should be similar.
183 ;; With numerical data, there should be a straightforward mapping from
184 ;; the data.frame to a matrix. With categorical data (including
185 ;; dense categories such as doc-strings, as well as sparse categories
186 ;; such as binary data), we need to include metadata about ordering,
187 ;; coding, and such. So the structures should probably consider
189 ;; Using the CSV file:
191 (asdf:oos
'asdf
:compile-op
'csv
:force t
)
192 (asdf:oos
'asdf
:load-op
'parse-number
)
193 (asdf:oos
'asdf
:load-op
'csv
)
194 (fare-csv:read-csv-file
"Data/example-numeric.csv")
196 ;; but I think the cl-csv package is broken, need to use the dsv-style