initializer update

theislab · Dec 10, 2024 · 1e3a531 · 1e3a531
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commit 1e3a531
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Showing 2 changed files with 14 additions and 8 deletions.
diff --git a/examples/solvers/200_linear_problems_advanced.ipynb b/examples/solvers/200_linear_problems_advanced.ipynb
@@ -34,7 +34,8 @@
    "outputs": [],
    "source": [
     "from moscot import datasets\n",
-    "from moscot.problems.generic import SinkhornProblem"
+    "from moscot.problems.generic import SinkhornProblem\n",
+    "from ott.initializers.linear import initializers_lr as init_lr_lib"
    ]
   },
   {
@@ -105,6 +106,7 @@
      "output_type": "stream",
      "text": [
       "\u001b[34mINFO    \u001b[0m Computing pca with `\u001b[33mn_comps\u001b[0m=\u001b[1;36m30\u001b[0m` for `xy` using `adata.X`                                                  \n",
+      "\u001b[34mINFO    \u001b[0m Solving `\u001b[1;36m1\u001b[0m` problems                                                                                      \n",
       "\u001b[34mINFO    \u001b[0m Solving problem OTProblem\u001b[1m[\u001b[0m\u001b[33mstage\u001b[0m=\u001b[32m'prepared'\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20\u001b[0m, \u001b[1;36m20\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m.                                              \n"
      ]
     }
@@ -114,7 +116,7 @@
     "sp = sp.prepare(key=\"day\")\n",
     "\n",
     "ik = {\"min_iterations\": 5, \"max_iterations\": 200}\n",
-    "sp = sp.solve(epsilon=0, rank=3, initializer=\"k-means\", initializer_kwargs=ik)"
+    "sp = sp.solve(epsilon=0, rank=3, initializer=init_lr_lib.KMeansInitializer(rank=3), initializer_kwargs=ik)"
    ]
   },
   {
@@ -145,6 +147,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "\u001b[34mINFO    \u001b[0m Solving `\u001b[1;36m1\u001b[0m` problems                                                                                      \n",
       "\u001b[34mINFO    \u001b[0m Solving problem OTProblem\u001b[1m[\u001b[0m\u001b[33mstage\u001b[0m=\u001b[32m'solved'\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20\u001b[0m, \u001b[1;36m20\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m.                                                \n",
       "\u001b[31mWARNING \u001b[0m Solver did not converge                                                                                   \n"
      ]
@@ -179,13 +182,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "\u001b[34mINFO    \u001b[0m Solving `\u001b[1;36m1\u001b[0m` problems                                                                                      \n",
       "\u001b[34mINFO    \u001b[0m Solving problem OTProblem\u001b[1m[\u001b[0m\u001b[33mstage\u001b[0m=\u001b[32m'solved'\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20\u001b[0m, \u001b[1;36m20\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m.                                                \n",
       "\u001b[31mWARNING \u001b[0m Solver did not converge                                                                                   \n"
      ]
     }
    ],
    "source": [
-    "sp = sp.solve(epsilon=0, rank=3, initializer=\"random\", max_iterations=30, gamma=1000)"
+    "sp = sp.solve(epsilon=0, rank=3, initializer=init_lr_lib.RandomInitializer(rank=3), max_iterations=30, gamma=1000)"
    ]
   },
   {
@@ -198,12 +202,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[34mINFO    \u001b[0m Solving problem OTProblem\u001b[1m[\u001b[0m\u001b[33mstage\u001b[0m=\u001b[32m'solved'\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20\u001b[0m, \u001b[1;36m20\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m.                                                \n"
+      "\u001b[34mINFO    \u001b[0m Solving `\u001b[1;36m1\u001b[0m` problems                                                                                      \n",
+      "\u001b[34mINFO    \u001b[0m Solving problem OTProblem\u001b[1m[\u001b[0m\u001b[33mstage\u001b[0m=\u001b[32m'solved'\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20\u001b[0m, \u001b[1;36m20\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m.                                                \n",
+      "\u001b[31mWARNING \u001b[0m Solver did not converge                                                                                   \n"
      ]
     }
    ],
    "source": [
-    "sp = sp.solve(epsilon=0, rank=3, initializer=\"random\", max_iterations=30, gamma=10)"
+    "sp = sp.solve(epsilon=0, rank=3, initializer=init_lr_lib.RandomInitializer(rank=3), max_iterations=30, gamma=10)"
    ]
   },
   {
@@ -233,7 +239,7 @@
   "kernelspec": {
    "display_name": "moscot",
    "language": "python",
-   "name": "moscot"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -245,7 +251,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

diff --git a/tutorials/500_spatiotemporal.ipynb b/tutorials/500_spatiotemporal.ipynb
@@ -276,7 +276,7 @@
    "source": [
     "As the data is large, we use low-rank optimal transport to decrease the computational complexity {cite}`scetbon:21a`. \n",
     "\n",
-    "To solve the problem we pass the following arguments, `alpha` (in $(0, 1]$), which  defines the influence of the spatial coordinates as opposed to the single-cell data. `epsilon`, the entropy parameter, and `initializer='rank2'` to improve the speed of convergence.\n",
+    "To solve the problem we pass the following arguments, `alpha` (in $(0, 1]$), which  defines the influence of the spatial coordinates as opposed to the single-cell data and `epsilon`, the entropy parameter to improve the speed of convergence.\n",
     "\n",
     ":::{seealso}\n",
     "- See {doc}`../examples/solvers/200_linear_problems_advanced` on how to modify low-rank parameters. \n",