sort r-c-vs

scicloj · Oct 15, 2024 · 87d6243 · 87d6243
1 parent 898f92c
commit 87d6243
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Showing 3 changed files with 117 additions and 9 deletions.
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
@@ -6,11 +6,11 @@
 		"dockerfile": "Dockerfile",
 		"args": {
 			"BASE_IMAGE": "temurin-21-tools-deps-jammy",
-			"USERNAME": "${localEnv:USER}"
+			"USERNAME": "${localEnv:USER:vscode}"
 		}
 	},
-	"remoteUser": "${localEnv:USER}",
-	"containerUser": "${localEnv:USER}",
+	"remoteUser": "${localEnv:USER:vscode}",
+	"containerUser": "${localEnv:USER:vscode}",
 	"features": {
 		"ghcr.io/devcontainers/features/git:1": {}
 	},

diff --git a/src/scicloj/ml/xgboost/csr.clj b/src/scicloj/ml/xgboost/csr.clj
@@ -1,3 +1,5 @@
+;; re-implements https://blog.newtum.com/sparse-matrix-in-java/
+;; maybe se here, nmot sure teh same: https://github.com/scipy/scipy/blob/v1.14.1/scipy/sparse/_csr.py
 (ns scicloj.ml.xgboost.csr
   (:require
             [ tech.v3.datatype :as dt]
@@ -17,15 +19,18 @@
        :row-pointers new-row-pointers})))
 
 (defn ->csr [r-c-vs]
+  ;; data gets sorted by r and c
+  ;; not sure, if good idea for performace ?
+
   (->
    (reduce
-
     (fn [csr [row col value]]
       (add-to-csr csr row col value))
     {:values (dt/make-list :float)
      :column-indices (dt/make-list :int)
-     :row-pointers (dt/make-list :long [0])}
-    r-c-vs)
+     :row-pointers (dt/make-list :long [0])} 
+    (sort-by (juxt first second) 
+             r-c-vs))
 
    (#(assoc % :row-pointers (conj (:row-pointers %)
                                   (count (:values %)))))))

diff --git a/test/scicloj/ml/xgboost/csr_test.clj b/test/scicloj/ml/xgboost/csr_test.clj
@@ -4,14 +4,91 @@
              [tech.v3.tensor :as t]))
 
 
+;; scipy
+;;1 0 2 0
+;;4 0 0 3
+;;3 1 2 0
+;;csr=csr_matrix (np.array ([[1,0,2,0],[4,0,0,3],[3,1,2,0]]))
+
+;;>>> csr.data    , same as dmatrix.data
+;;array ([1, 2, 4, 3, 3, 1, 2])
+
+;; >>> csr.indices, same as dmatrix.colIndex
+;;array ([0, 2, 0, 3, 0, 1, 2], dtype=int32)
+
+;;>>> csr.indptr, same as dmatrix.rowHeaders
+;;array ([0, 2, 4, 7], dtype=int32)
+
+
 (deftest ->csr
+;;                       3.        1.       2.  
+;;>>> csr=coo_array (([5,8,3,6],([0,1,2,3],[0,1,2,1])),shape= (4,4)) .tocsr ()
+;;>>> csr.data
+;;array ([5, 8, 3, 6])
+;;>>> csr.indices
+;;array ([0, 1, 2, 1])
+;;>>> csr.indptr
+;;array ([0, 1, 2, 3, 4])  
+
   (is (=
        {:values [5.0 8.0 3.0 6.0], :column-indices [0 1 2 1], :row-pointers [0 1 2 3 4]}
        (csr/->csr
+        ;; row,col,value
         [[0 0 5]
          [1 1 8]
          [2 2 3]
-         [4 1 6]]))))
+         [3 1 6]]))))
+
+
+(deftest ->csr-2
+;; matches wikipedia https://en.wikipedia.org/wiki/Sparse_matrix
+;;in python
+;; coo_array (([10,20,30,40,50,60,70,80],([0,0,1,1,2,2,2,3],[0,1,1,3,2,3,4,5])),shape=(4,6)).todense()
+;; array ([[10, 20,  0,  0,  0,  0],
+;;         [0, 30,  0, 40,  0,  0],
+;;         [0,  0, 50, 60, 70,  0],
+;;         [0,  0,  0,  0,  0, 80]])
+;;
+;;                             3.                       1.                2.
+;; >>> csr=coo_array (([10,20,30,40,50,60,70,80],([0,0,1,1,2,2,2,3],[0,1,1,3,2,3,4,5])),shape= (4,6)) .tocsr ()
+;; >>> csr.data
+;; array ([10, 20, 30, 40, 50, 60, 70, 80])
+;; >>> csr.indices
+;; array ([0, 1, 1, 3, 2, 3, 4, 5])
+;; >>> csr.indptr
+;; array ([0, 2, 4, 7, 8])
+  (is (= {:values [10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0] 
+          :column-indices [0 1 1 3 2 3 4 5] 
+          :row-pointers [0 2 4 7 8]}
+         (csr/->csr
+          [
+           [0 0 10.0]
+           [0 1 20.0]
+           [1 1 30.0]
+           [1 3 40.0]
+           [2 2 50.0]
+           [2 3 60.0]
+           [2 4 70.]
+           [3 5 80.0]]))))
+;;=> 
+
+
+(deftest unsorted []
+  (is (= {:values [10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0]
+          :column-indices [0 1 1 3 2 3 4 5]
+          :row-pointers [0 2 4 7 8]}
+         (csr/->csr
+          (shuffle
+           [[0 0 10.0]
+            [0 1 20.0]
+            [1 1 30.0]
+            [1 3 40.0]
+            [2 2 50.0]
+            [2 3 60.0]
+            [2 4 70.0]
+            [3 5 80.0]]))
+         )))
+
 
 (deftest ->dense
   (is (=
@@ -51,6 +128,32 @@
          4 4)))))
 
 
+(t/->tensor
+ (csr/->dense
+  (csr/->csr
+   [[0 0 5]
+    [1 1 8]
+    [2 2 3]
+    [4 1 6]])
+  4 4))
+;;=> #tech.v3.tensor<object>[4 4]
+;;   [[5.000     0     0 0]
+;;    [    0 8.000     0 0]
+;;    [    0     0 3.000 0]
+;;    [    0 6.000     0 0]]
+
 
-(comment
-  )
+(t/->tensor
+ (csr/->dense
+  (csr/->csr
+   [[1 1 8]
+    [2 2 3]
+    [4 1 6]
+    [0 0 5]]
+   )
+  4 4))
+;;=> #tech.v3.tensor<object>[4 4]
+;;   [[    0     0     0 0]
+;;    [    0 8.000     0 0]
+;;    [    0     0 3.000 0]
+;;    [5.000 6.000     0 0]]