Fix mermaid?

docs/source/how_to/how_to_algorithm_selection.ipynb

@@ -45,18 +45,18 @@
     "graph LR\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[\"differentiable?\"] -- no --> D[\"'scipy_cobyla', 'nlopt_cobyla'\"]\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",