DOC: save grid fig from tut; rerun tut; Ecoli time

So I was like "why is the E. coli example now taking like ~36 sec
to run, when it was taking ~29 seconds yesterday?" and from testing
it seems to go back down to ~30 sec when I closed all firefox tabs
except the jupyter one & the github one i had open LOLLLLL

so yeah idk. i updated the readme to say ~35 sec, which I think is
fair (erring on the side of being too harsh towards myself), but I
don't wanna slide into doing the stereotypical cs cherry picking
benchmarking jank. you know how it is

README.md

@@ -64,7 +64,7 @@ from matplotlib import pyplot
 # (skipping the part where I loaded the genomes into memory as e1s and e2s...)
 
 # Create the matrix
-# This takes ~30 seconds on a laptop with 8 GB of RAM
+# This takes ~35 seconds on a laptop with 8 GB of RAM
 em = wp.DotPlotMatrix(e1s, e2s, 20, verbose=True)
 
 # Visualize the matrix using matplotlib's spy() function

docs/Tutorial.ipynb

@@ -933,7 +933,8 @@
     "            axes[row, col].axis(\"off\")\n",
     "\n",
     "fig.suptitle(f\"Dot plots ($k$ = {K}) of five random sequences\", fontsize=24, y=0.94)\n",
-    "fig.set_size_inches(15, 15)"
+    "fig.set_size_inches(15, 15)\n",
+    "fig.savefig(os.path.join(\"img\", \"grid.png\"), **savefig_kwargs)"
    ]
   },
   {
@@ -1198,15 +1199,16 @@
      "output_type": "stream",
      "text": [
       "0.00s: Validating inputs...\n",
-      "0.46s: Finding forward matches between s1 and s2...\n",
-      "24.35s: Found 3,357,713 forward match cell(s).\n",
-      "24.35s: Computing ReverseComplement(s2)...\n",
-      "24.37s: Finding reverse-complementary matches between s1 and s2...\n",
-      "33.31s: Found 3,536,693 total (fwd and/or RC) match cell(s).\n",
-      "33.31s: Dot plot matrix density = 0.00%.\n",
-      "33.31s: Converting match information to COO format inputs...\n",
-      "35.11s: Creating sparse matrix from COO format inputs...\n",
-      "36.37s: Done creating the matrix.\n"
+      "0.47s: Will find matches using common_substrings().\n",
+      "0.47s: Finding forward matches between s1 and s2...\n",
+      "20.19s: Found 3,357,713 forward match cell(s).\n",
+      "20.19s: Computing ReverseComplement(s2)...\n",
+      "20.22s: Finding reverse-complementary matches between s1 and s2...\n",
+      "27.36s: Found 3,536,693 total (fwd and/or RC) match cell(s).\n",
+      "27.36s: Dot plot matrix density = 0.00%.\n",
+      "27.37s: Converting match information to COO format inputs...\n",
+      "29.24s: Creating sparse matrix from COO format inputs...\n",
+      "30.38s: Done creating the matrix.\n"
      ]
     }
    ],
@@ -1219,7 +1221,7 @@
    "id": "8902f8f0",
    "metadata": {},
    "source": [
-    "Creating the matrix usually takes about 30 seconds (on my six-year old laptop with 8 GB of RAM). All things considered, not too shabby!"
+    "Creating the matrix usually takes about 30 seconds (on my six-year old laptop with 8 GB of RAM). (... Or closer to 40 seconds when I have a lot of stuff open.) All things considered, not too shabby!"
    ]
   },
   {
@@ -1304,7 +1306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 30,
    "id": "f8bc2e3a",
    "metadata": {},
    "outputs": [
@@ -1314,13 +1316,13 @@
      "text": [
       "0.03s: binary is not True, so we'll draw matches in different colors.\n",
       "0.03s: Visualizing \"1\" cells with spy()...\n",
-      "0.52s: Done visualizing \"1\" cells.\n",
-      "0.52s: Visualizing \"-1\" cells with spy()...\n",
-      "0.75s: Done visualizing \"-1\" cells.\n",
-      "0.75s: Visualizing \"2\" cells with spy()...\n",
-      "0.99s: Done visualizing \"2\" cells.\n",
-      "0.99s: Slightly restyling the visualization...\n",
-      "0.99s: Done.\n"
+      "0.42s: Done visualizing \"1\" cells.\n",
+      "0.42s: Visualizing \"-1\" cells with spy()...\n",
+      "0.66s: Done visualizing \"-1\" cells.\n",
+      "0.66s: Visualizing \"2\" cells with spy()...\n",
+      "0.91s: Done visualizing \"2\" cells.\n",
+      "0.91s: Slightly restyling the visualization...\n",
+      "0.91s: Done.\n"
      ]
     },
     {
@@ -1364,18 +1366,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 31,
    "id": "7bf44264",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.03s: binary is True; visualizing all match cells with spy()...\n",
-      "0.17s: Done visualizing all match cells.\n",
-      "0.18s: Slightly restyling the visualization...\n",
-      "0.18s: Done.\n"
+      "0.05s: binary is True; visualizing all match cells with spy()...\n",
+      "0.24s: Done visualizing all match cells.\n",
+      "0.24s: Slightly restyling the visualization...\n",
+      "0.24s: Done.\n"
      ]
     },
     {
@@ -1398,14 +1400,6 @@
     "ax.set_ylabel(f\"$E. coli$ O157:H7 str. Sakai ({len(e2s)/1e6:.2f} Mbp) \\u2192\")\n",
     "fig.set_size_inches(8, 8)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e9a33a5b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {