/
mapseq_test.clj
308 lines (274 loc) · 12.1 KB
/
mapseq_test.clj
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
(ns tech.ml.dataset.mapseq-test
(:require [tech.ml.dataset.pipeline :as ds-pipe]
[tech.ml.dataset :as ds]
[tech.ml.dataset.column :as ds-col]
[tech.ml.dataset.pipeline.column-filters :as cf]
[tech.ml.dataset-test
:refer [mapseq-fruit-dataset]
:as ds-test]
[tech.v2.datatype :as dtype]
[tech.v2.datatype.functional :as dtype-fn]
[tech.v2.tensor :as dtt]
[clojure.set :as c-set]
[clojure.test :refer :all]))
(deftest mapseq-classification-test
(let [src-ds (ds/->dataset (mapseq-fruit-dataset) {})
dataset (-> src-ds
(ds-pipe/remove-columns [:fruit-subtype :fruit-label])
(ds-pipe/string->number)
(ds-pipe/range-scale)
(ds/set-inference-target :fruit-name))
origin-ds (mapseq-fruit-dataset)
src-keys (set (keys (first (mapseq-fruit-dataset))))
result-keys (set (->> (ds/columns dataset)
(map ds-col/column-name)))
non-categorical (cf/not cf/categorical? dataset)]
(is (= #{59}
(->> (ds/columns dataset)
(map dtype/ecount)
set)))
;;Column names can be keywords.
(is (= (set (keys (first (mapseq-fruit-dataset))))
(set (->> (ds/columns src-ds)
(map ds-col/column-name)))))
(is (= (c-set/difference src-keys #{:fruit-subtype :fruit-label})
result-keys))
;; Map back from values to keys for labels. For tablesaw, column values
;; are never keywords.
(is (= (mapv :fruit-name (mapseq-fruit-dataset))
(ds/labels dataset)))
(is (= {:fruit-name :classification}
(ds/model-type dataset)))
(is (= {:fruit-name :classification,
:mass :regression,
:width :regression,
:height :regression,
:color-score :regression}
(ds/model-type dataset (ds/column-names dataset))))
;;Does the post-transformation value of fruit-name map to the
;;pre-transformation value of fruit-name?
(is (= (mapv :fruit-name (mapseq-fruit-dataset))
(->> (ds/->flyweight dataset :number->string? true)
(mapv :fruit-name))))
(is (= (as-> (ds/select dataset :all (range 10)) dataset
(ds/->flyweight dataset)
(group-by :fruit-name dataset))
(->> (ds/select dataset :all (range 10))
(ds/group-by :fruit-name)
(map (fn [[k group-ds]]
[k (vec (ds/->flyweight group-ds))]))
(into {}))))
;;forward map from input value to encoded value.
;;After ETL, column values are all doubles
(let [apple-value (-> (get (ds/inference-target-label-map dataset) :apple)
double)]
(is (= #{:apple}
(->> dataset
(ds/filter #(= apple-value (:fruit-name %)))
;;Use full version of ->flyweight to do reverse mapping of numeric
;;fruit name back to input label.
(#(ds/->flyweight % :number->string? true))
(map :fruit-name)
set))))
;;dataset starts with apple apple apple mandarin mandarin
(let [apple-v (double (get (ds/inference-target-label-map dataset) :apple))
mand-v (double (get (ds/inference-target-label-map dataset) :mandarin))]
(is (= [apple-v apple-v apple-v mand-v mand-v]
;;Order columns
(->> (ds/select dataset [:mass :fruit-name :width] :all)
(take 2)
(drop 1)
(ds/from-prototype dataset "new-table")
(#(ds/select % :all (range 5)))
;;Note the backward conversion failed in this case because we
;;change the column names.
(#(ds/->flyweight % :number->string? true))
(map #(get % :fruit-name))
vec))))
;; Ensure range map works
(is (= (vec (repeat (count non-categorical) [-1 1]))
(->> non-categorical
(mapv (fn [colname]
(let [{col-min :min
col-max :max} (-> (ds/column dataset colname)
(ds-col/stats [:min :max]))]
[(long col-min) (long col-max)]))))))
;;Concatenation should work
(is (= (mapv :fruit-name
(concat (mapseq-fruit-dataset)
(mapseq-fruit-dataset)))
(->> (-> (ds/concat dataset dataset)
(ds/->flyweight :number->string? true))
(mapv :fruit-name))))
(let [new-ds (as-> (ds/->dataset (map hash-map (repeat :mass) (range 20))) dataset
;;The mean should happen in double or floating point space.
(ds-pipe/->datatype dataset)
(ds/new-column dataset :mass-avg
(->> (ds/column dataset :mass)
(dtype-fn/fixed-rolling-window
5 dtype-fn/mean))))]
(is (= [{:mass 0.0, :mass-avg 0.6}
{:mass 1.0, :mass-avg 1.2}
{:mass 2.0, :mass-avg 2.0}
{:mass 3.0, :mass-avg 3.0}
{:mass 4.0, :mass-avg 4.0}
{:mass 5.0, :mass-avg 5.0}
{:mass 6.0, :mass-avg 6.0}
{:mass 7.0, :mass-avg 7.0}
{:mass 8.0, :mass-avg 8.0}
{:mass 9.0, :mass-avg 9.0}]
(-> (ds/select new-ds [:mass :mass-avg] (range 10))
ds/->flyweight)))
(let [sorted-ds (ds/sort-by :mass-avg > new-ds)]
(is (= [{:mass 19.0, :mass-avg 18.4}
{:mass 18.0, :mass-avg 17.8}
{:mass 17.0, :mass-avg 17.0}
{:mass 16.0, :mass-avg 16.0}
{:mass 15.0, :mass-avg 15.0}
{:mass 14.0, :mass-avg 14.0}
{:mass 13.0, :mass-avg 13.0}
{:mass 12.0, :mass-avg 12.0}
{:mass 11.0, :mass-avg 11.0}
{:mass 10.0, :mass-avg 10.0}]
(-> (ds/select sorted-ds [:mass :mass-avg] (range 10))
ds/->flyweight)))))
(let [nth-db (ds/take-nth 5 src-ds)]
(is (= [7 12] (dtype/shape nth-db)))
(is (= [{:mass 192.0, :width 8}
{:mass 80.0, :width 5}
{:mass 166.0, :width 6}
{:mass 156.0, :width 7}
{:mass 160.0, :width 7}
{:mass 356.0, :width 9}
{:mass 158.0, :width 7}
{:mass 150.0, :width 7}
{:mass 154.0, :width 7}
{:mass 186.0, :width 7}]
(->> (-> (ds/select nth-db [:mass :width] (range 10))
ds/->flyweight)
(map #(update % :width int))))))))
(deftest one-hot
(testing "Testing one-hot into multiple column groups"
(let [src-ds (ds/->dataset (mapseq-fruit-dataset))
dataset (-> src-ds
(ds/remove-columns [:fruit-subtype :fruit-label])
(ds-pipe/one-hot :fruit-name
{:main [:apple :mandarin]
:other :rest})
(ds-pipe/string->number)
(ds/set-inference-target :fruit-name))]
(is (= {:fruit-name
{:apple [:fruit-name-main 1],
:mandarin [:fruit-name-main 2],
:orange [:fruit-name-other 1],
:lemon [:fruit-name-other 2]}}
(ds/dataset-label-map dataset)))
(is (= #{:mass :fruit-name-main :fruit-name-other :width :color-score :height}
(->> (ds/columns dataset)
(map ds-col/column-name)
set)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/labels dataset)
(take 20)
vec)))
;;Check that flyweight conversion is correct.
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/->flyweight dataset :number->string? true)
(map :fruit-name)
(take 20)
vec)))
(is (= {:fruit-name :classification
:mass :regression
:width :regression
:height :regression
:color-score :regression}
(ds/model-type dataset (ds/column-names dataset))))))
(testing "one hot-figure it out"
(let [src-ds (ds/->dataset (mapseq-fruit-dataset))
dataset (-> src-ds
(ds-pipe/remove-columns [:fruit-subtype :fruit-label])
(ds-pipe/one-hot :fruit-name)
(ds-pipe/string->number))]
(is (= {:fruit-name
{:apple [:fruit-name-apple 1],
:orange [:fruit-name-orange 1],
:lemon [:fruit-name-lemon 1],
:mandarin [:fruit-name-mandarin 1]}}
(ds/dataset-label-map dataset)))
(is (= #{:mass :fruit-name-mandarin :width :fruit-name-orange :color-score
:fruit-name-lemon :fruit-name-apple :height}
(->> (ds/columns dataset)
(map ds-col/column-name)
set)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/column-values->categorical dataset :fruit-name)
(take 20)
vec)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/->flyweight dataset :number->string? true)
(map :fruit-name)
(take 20)
vec)))
(is (= {:fruit-name :classification
:mass :regression
:width :regression
:height :regression
:color-score :regression}
(ds/model-type dataset (ds/column-names dataset))))))
(testing "one hot - defined values"
(let [src-ds (ds/->dataset (mapseq-fruit-dataset))
dataset (-> src-ds
(ds-pipe/remove-columns [:fruit-subtype :fruit-label])
(ds-pipe/one-hot :fruit-name [:apple :mandarin
:orange :lemon])
(ds-pipe/string->number))]
(is (= {:fruit-name
{:apple [:fruit-name-apple 1],
:orange [:fruit-name-orange 1],
:lemon [:fruit-name-lemon 1],
:mandarin [:fruit-name-mandarin 1]}}
(ds/dataset-label-map dataset)))
(is (= #{:mass :fruit-name-mandarin :width :fruit-name-orange :color-score
:fruit-name-lemon :fruit-name-apple :height}
(->> (ds/columns dataset)
(map ds-col/column-name)
set)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/column-values->categorical dataset :fruit-name)
(take 20)
vec)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv :fruit-name))
(->> (ds/->flyweight dataset :number->string? true)
(map :fruit-name)
(take 20)
vec)))
(is (= {:fruit-name :classification
:mass :regression
:width :regression
:height :regression
:color-score :regression}
(ds/model-type dataset (ds/column-names dataset)))))))
(deftest generalized-mapseq-ds
(let [ds (ds/->dataset [{:a 1 :b {:a 1 :b 2}}
{:a 2}])]
(is (= #{:int64 :object}
(set (map dtype/get-datatype ds))))))
(deftest tensors-in-mapseq
(let [ds (ds/->dataset [{:a (dtt/->tensor (partition 3 (range 9)))
:b "hello"}
{:a (dtt/->tensor (partition 3 (range 9)))
:b "goodbye"}])]
(is (= #{:object :string}
(set (map dtype/get-datatype ds))))))