Cleaning up by keeping the old content indexed but otherwise only local

.gitignore

@@ -7,6 +7,7 @@ profiling
 .DS_Store
 **/**.DS_Store
 wheelhouse
+todo
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

docs/src/integration/python_integration.ipynb

@@ -8,15 +8,15 @@
         "title: \"Python Integration\"\n",
         "---"
       ],
-      "id": "52d4a963"
+      "id": "556449dc"
     },
     {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
         "To demonstrate the SLQ method in Python, we start with a simple symmetric matrix $A \\in \\mathbb{R}^{n \\times n}$. \n"
       ],
-      "id": "e481b847"
+      "id": "8a120a38"
     },
     {
       "cell_type": "code",
@@ -26,7 +26,7 @@
         "from primate.random import symmetric\n",
         "A = symmetric(150, psd = True)"
       ],
-      "id": "bdd82c2c",
+      "id": "e7000a74",
       "execution_count": null,
       "outputs": []
     },
@@ -36,7 +36,7 @@
       "source": [
         "This generates a random positive semi-definite matrix with eigenvalues in the interval $[0, 1]$. \n"
       ],
-      "id": "2682a34d"
+      "id": "825ad88c"
     },
     {
       "cell_type": "code",
@@ -47,7 +47,7 @@
         "from bokeh.io import output_notebook\n",
         "output_notebook()"
       ],
-      "id": "22055528",
+      "id": "57f0ef78",
       "execution_count": null,
       "outputs": []
     },
@@ -58,7 +58,7 @@
         "from primate.trace import sl_trace\n",
         "estimates = sl_trace(A, plot=True)"
       ],
-      "id": "a1a51aa5",
+      "id": "0f5e4f2c",
       "execution_count": null,
       "outputs": []
     },
@@ -71,7 +71,7 @@
         "print(f\"Samples std. deviation: {estimates.std(ddof=1)}\")\n",
         "print(f\"Estimator standard error: {estimates.std(ddof=1)/np.sqrt(len(estimates))}\")"
       ],
-      "id": "79f77f58",
+      "id": "207e34ca",
       "execution_count": null,
       "outputs": []
     }