xd again tsvd bugfix

lib/scholar/decomposition/utils.ex

@@ -3,9 +3,14 @@ defmodule Scholar.Decomposition.Utils do
   import Nx.Defn
   require Nx
 
-  defn flip_svd(u, v) do
-    max_abs_cols_idx = u |> Nx.abs() |> Nx.argmax(axis: 0, keep_axis: true)
-    signs = u |> Nx.take_along_axis(max_abs_cols_idx, axis: 0) |> Nx.sign() |> Nx.squeeze()
+  defn flip_svd(u, v, u_based \\ true) do
+    base = if u_based do
+      u
+    else
+      Nx.transpose(v)
+    end
+    max_abs_cols_idx = base |> Nx.abs() |> Nx.argmax(axis: 0, keep_axis: true)
+    signs = base |> Nx.take_along_axis(max_abs_cols_idx, axis: 0) |> Nx.sign() |> Nx.squeeze()
     u = u * signs
     v = v * Nx.new_axis(signs, -1)
     {u, v}

test/scholar/decomposition/truncated_svd_tests.exs

@@ -3,17 +3,27 @@ defmodule Scholar.Decomposition.TruncatedSVDTest do
   alias Scholar.Decomposition.TruncatedSVD
   doctest TruncatedSVD
 
+  defp key do
+    Nx.Random.key(1)
+  end
+
   defp x do
-    Nx.tensor()
+    key = key()
+    {x, _new_key} = Nx.Random.multivariate_normal(key, Nx.tensor([0.0, 0.0, 0.0, 0.0]), Nx.tensor([[3.0, 2.0, 1.0, 9.0], [1.0, 2.0, 3.0, 8.2], [1.3, 1.0, 2.2, 2.4], [1.8, 1.0, 2.0, 2.9]]), shape: {50}, type: :f32)
+    x
   end
+  # key = Nx.Random.key(1)
+  # {x, _new_key} = Nx.Random.multivariate_normal(key, Nx.tensor([0.0, 0.0, 0.0, 0.0]), Nx.tensor([[3.0, 2.0, 1.0, 9.0], [1.0, 2.0, 3.0, 8.2], [1.3, 1.0, 2.2, 2.4], [1.8, 1.0, 2.0, 2.9]]), shape: {50}, type: :f32)
+  # tsvd = Scholar.Decomposition.TruncatedSVD.fit_transform(x, num_components: 2, key: key)
 
 
   test "fit test - all default options" do
-
+    key = key()
+    x = x()
   end
 
   test "fit_transform test - all default options" do
-
+    #tsvd = Scholar.Decomposition.TruncatedSVD.fit_transform(x, num_components: 2, key: key)
   end
 
   test "fit_transform test - :num_components" do