/
mapseq_test.clj
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/
mapseq_test.clj
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(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]
[clojure.set :as c-set]
[clojure.test :refer :all]))
;;A sequence of maps is actually hard because keywords aren't represented
;;in tablesaw so we have to do a lot of work. Classification also imposes
;;the necessity of mapping back from the label column to a sequence of
;;keyword labels.
(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 (comp name :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 (comp name :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/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/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)
(ds/ds-column-map #(ds-col/set-metadata
%
{:name (name (ds-col/column-name %))}))
(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 (comp name :fruit-name)
(concat (mapseq-fruit-dataset)
(mapseq-fruit-dataset)))
(->> (-> (ds/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/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/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 (comp name :fruit-name)))
(->> (ds/labels dataset)
(take 20)
vec)))
;;Check that flyweight conversion is correct.
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv (comp name :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 (comp name :fruit-name)))
(->> (ds/column-values->categorical dataset :fruit-name)
(take 20)
vec)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv (comp name :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 (comp name :fruit-name)))
(->> (ds/column-values->categorical dataset :fruit-name)
(take 20)
vec)))
(is (= (->> (mapseq-fruit-dataset)
(take 20)
(mapv (comp name :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)))))))