Fix mermaid?

docs/source/how_to/how_to_algorithm_selection.ipynb

@@ -42,21 +42,21 @@
     "This is a practical guide for narrowing down the set of algorithms to experiment with:\n",
     "\n",
     "```{mermaid}\n",
-    "graph LR\n",
+    "graph TD\n",
     "    classDef highlight fill:#FF4500;\n",
     "    A[\"Do you have<br/>nonlinear constraints?\"] -- yes --> B[\"differentiable?\"]\n",
-    "    B[\"Is your objective function differentiable?\"] -- yes --> C[\"ipopt nlopt_slsqp scipy_trust_constr\"]\n",
+    "    B[\"Is your objective function differentiable?\"] -- yes --> C[\"ipopt , nlopt_slsqp , scipy_trust_constr\"]\n",
     "    B[\"differentiable?\"] -- no --> D[\"scipy_cobyla , nlopt_cobyla\"]\n",
     "\n",
     "    A[\"Do you have<br/>nonlinear constraints?\"] -- no --> E[\"Can you exploit<br/>a least-squares<br/>structure?\"]\n",
     "    E[\"Can you exploit<br/>a least-squares<br/>structure?\"] -- yes --> F[\"differentiable?\"]\n",
     "    E[\"Can you exploit<br/>a least-squares<br/>structure?\"] -- no --> G[\"differentiable?\"]\n",
     "\n",
-    "    F[\"differentiable?\"] -- yes --> H[\"scipy_ls_lm; scipy_ls_trf; scipy_ls_dogleg\"]\n",
-    "    F[\"differentiable?\"] -- no --> I[\"nag_dflos/pounders/tao_pounders\"]\n",
+    "    F[\"differentiable?\"] -- yes --> H[\"scipy_ls_lm , scipy_ls_trf , scipy_ls_dogleg\"]\n",
+    "    F[\"differentiable?\"] -- no --> I[\"nag_dflos , pounders , tao_pounders\"]\n",
     "\n",
-    "    G[\"differentiable?\"] -- yes --> J[\"scipy_lbfgsb / nlopt_lbfgsb / fides\"]\n",
-    "    G[\"differentiable?\"] -- no --> K[\"nlopt_bobyqa, nlopt_neldermead, neldermead_parallel\"]\n",
+    "    G[\"differentiable?\"] -- yes --> J[\"scipy_lbfgsb , nlopt_lbfgsb , fides\"]\n",
+    "    G[\"differentiable?\"] -- no --> K[\"nlopt_bobyqa , nlopt_neldermead , neldermead_parallel\"]\n",
     "\n",
     "```\n",
     "\n",