diff --git a/doc/devlog/2023-07-13.ipynb b/doc/devlog/2023-07-13.ipynb
index 5a148b6f..8aa05eff 100644
--- a/doc/devlog/2023-07-13.ipynb
+++ b/doc/devlog/2023-07-13.ipynb
@@ -22,156 +22,156 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "failed: ('single_pop', 'pei', 'pei') in 69.689 ms\n",
-      "failed: ('single_pop', 'sparsemod', 'pei') in 61.193 ms\n",
-      "succeeded: ('pei', 'icecube', 'pei') in 75.639 ms\n",
-      "succeeded: ('pei', 'no', 'pei') in 77.338 ms\n",
-      "succeeded: ('pei', 'sparsemod', 'pei') in 77.774 ms\n",
-      "succeeded: ('pei', 'centroids', 'pei') in 86.913 ms\n",
-      "failed: ('single_pop', 'centroids', 'pei') in 68.535 ms\n",
-      "succeeded: ('pei', 'no', 'sirs') in 14.799 ms\n",
-      "succeeded: ('pei', 'icecube', 'sirs') in 20.422 ms\n",
-      "succeeded: ('single_pop', 'sparsemod', 'sirs') in 28.933 ms\n",
-      "succeeded: ('pei', 'pei', 'pei') in 91.106 ms\n",
-      "succeeded: ('single_pop', 'pei', 'sirs') in 40.861 ms\n",
-      "succeeded: ('pei', 'centroids', 'sirs') in 25.276 ms\n",
-      "succeeded: ('single_pop', 'centroids', 'sirs') in 25.617 ms\n",
-      "succeeded: ('pei', 'sparsemod', 'sirs') in 42.159 ms\n",
-      "succeeded: ('pei', 'pei', 'sirs') in 45.219 ms\n",
-      "succeeded: ('single_pop', 'sparsemod', 'sirh') in 147.289 ms\n",
-      "succeeded: ('pei', 'icecube', 'sirh') in 161.424 ms\n",
-      "succeeded: ('pei', 'no', 'sirh') in 169.289 ms\n",
-      "succeeded: ('single_pop', 'pei', 'sirh') in 152.119 ms\n",
-      "succeeded: ('pei', 'centroids', 'sirh') in 166.397 ms\n",
-      "succeeded: ('single_pop', 'centroids', 'sirh') in 169.583 ms\n",
-      "succeeded: ('pei', 'sparsemod', 'sirh') in 175.605 ms\n",
-      "succeeded: ('pei', 'pei', 'sirh') in 162.435 ms\n",
-      "succeeded: ('single_pop', 'sparsemod', 'sparsemod') in 113.097 ms\n",
-      "succeeded: ('single_pop', 'sparsemod', 'no') in 14.969 ms\n",
-      "succeeded: ('pei', 'icecube', 'sparsemod') in 121.465 ms\n",
-      "succeeded: ('single_pop', 'pei', 'sparsemod') in 123.608 ms\n",
-      "failed: ('single_pop', 'icecube', 'pei') in 10.372 ms\n",
-      "succeeded: ('pei', 'icecube', 'no') in 11.658 ms\n",
-      "succeeded: ('pei', 'no', 'sparsemod') in 157.503 ms\n",
-      "succeeded: ('single_pop', 'centroids', 'sparsemod') in 116.806 ms\n",
-      "failed: ('single_pop', 'no', 'pei') in 4.213 ms\n",
-      "succeeded: ('single_pop', 'icecube', 'sirs') in 16.158 ms\n",
-      "succeeded: ('pei', 'no', 'no') in 4.139 ms\n",
-      "succeeded: ('single_pop', 'pei', 'no') in 34.712 ms\n",
-      "succeeded: ('pei', 'centroids', 'sparsemod') in 160.009 ms\n",
-      "succeeded: ('pei', 'sparsemod', 'sparsemod') in 124.310 ms\n",
-      "succeeded: ('single_pop', 'no', 'sirs') in 8.027 ms\n",
-      "succeeded: ('single_pop', 'centroids', 'no') in 13.133 ms\n",
-      "failed: ('us_counties_2015', 'sparsemod', 'pei') in 15.559 ms\n",
-      "succeeded: ('pei', 'sparsemod', 'no') in 16.368 ms\n",
-      "succeeded: ('pei', 'centroids', 'no') in 18.224 ms\n",
-      "failed: ('us_counties_2015', 'pei', 'pei') in 27.487 ms\n",
-      "succeeded: ('single_pop', 'no', 'sirh') in 18.911 ms\n",
-      "succeeded: ('single_pop', 'icecube', 'sirh') in 35.189 ms\n",
-      "failed: ('us_counties_2015', 'centroids', 'pei') in 13.775 ms\n",
-      "failed: ('us_counties_2015', 'no', 'pei') in 5.056 ms\n",
-      "failed: ('us_counties_2015', 'icecube', 'pei') in 15.946 ms\n",
-      "succeeded: ('pei', 'pei', 'sparsemod') in 155.409 ms\n",
-      "succeeded: ('single_pop', 'no', 'sparsemod') in 97.401 ms\n",
-      "succeeded: ('single_pop', 'icecube', 'sparsemod') in 102.351 ms\n",
-      "succeeded: ('single_pop', 'no', 'no') in 3.998 ms\n",
-      "succeeded: ('pei', 'pei', 'no') in 48.649 ms\n",
-      "succeeded: ('single_pop', 'icecube', 'no') in 9.799 ms\n",
-      "failed: ('us_states_2015', 'sparsemod', 'pei') in 24.828 ms\n",
-      "failed: ('us_states_2015', 'centroids', 'pei') in 25.182 ms\n",
-      "succeeded: ('us_states_2015', 'sparsemod', 'sirs') in 91.540 ms\n",
-      "succeeded: ('us_states_2015', 'centroids', 'sirs') in 79.740 ms\n",
-      "failed: ('us_states_2015', 'pei', 'pei') in 172.462 ms\n",
-      "succeeded: ('us_states_2015', 'sparsemod', 'sirh') in 109.311 ms\n",
-      "succeeded: ('us_states_2015', 'centroids', 'sirh') in 126.752 ms\n",
-      "succeeded: ('us_states_2015', 'pei', 'sirs') in 165.733 ms\n",
-      "succeeded: ('us_states_2015', 'pei', 'sirh') in 145.946 ms\n",
-      "succeeded: ('us_states_2015', 'sparsemod', 'sparsemod') in 303.398 ms\n",
-      "succeeded: ('us_states_2015', 'sparsemod', 'no') in 35.235 ms\n",
-      "failed: ('us_states_2015', 'icecube', 'pei') in 9.206 ms\n",
-      "succeeded: ('us_states_2015', 'centroids', 'sparsemod') in 353.431 ms\n",
-      "succeeded: ('us_states_2015', 'icecube', 'sirs') in 51.400 ms\n",
-      "succeeded: ('us_states_2015', 'centroids', 'no') in 34.146 ms\n",
-      "failed: ('us_states_2015', 'no', 'pei') in 11.391 ms\n",
-      "succeeded: ('us_states_2015', 'pei', 'sparsemod') in 249.656 ms\n",
-      "succeeded: ('us_states_2015', 'no', 'sirs') in 32.479 ms\n",
-      "succeeded: ('us_states_2015', 'icecube', 'sirh') in 106.337 ms\n",
-      "succeeded: ('us_states_2015', 'no', 'sirh') in 48.802 ms\n",
-      "succeeded: ('us_states_2015', 'pei', 'no') in 102.537 ms\n",
-      "failed: ('us_sw_counties_2015', 'pei', 'pei') in 46.572 ms\n",
-      "succeeded: ('us_states_2015', 'no', 'sparsemod') in 112.321 ms\n",
-      "failed: ('us_sw_counties_2015', 'pei', 'sirs') in 26.161 ms\n",
-      "succeeded: ('us_states_2015', 'no', 'no') in 9.310 ms\n",
-      "succeeded: ('us_states_2015', 'icecube', 'sparsemod') in 210.701 ms\n",
-      "failed: ('us_sw_counties_2015', 'pei', 'sirh') in 51.507 ms\n",
-      "succeeded: ('us_states_2015', 'icecube', 'no') in 20.583 ms\n",
-      "failed: ('us_sw_counties_2015', 'pei', 'sparsemod') in 59.846 ms\n",
-      "failed: ('us_sw_counties_2015', 'pei', 'no') in 24.171 ms\n",
-      "failed: ('us_sw_counties_2015', 'icecube', 'pei') in 809.627 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'icecube', 'sirs') in 149.498 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'icecube', 'sirh') in 193.270 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'icecube', 'sparsemod') in 403.996 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'icecube', 'no') in 54.420 ms\n",
-      "failed: ('us_sw_counties_2015', 'no', 'pei') in 4.119 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'no', 'sirs') in 107.494 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'no', 'sirh') in 155.537 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'no', 'sparsemod') in 250.406 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'no', 'no') in 47.080 ms\n",
-      "failed: ('maricopa_cbg_2019', 'pei', 'pei') in 25.440 ms\n",
-      "failed: ('maricopa_cbg_2019', 'pei', 'sirs') in 32.726 ms\n",
-      "failed: ('maricopa_cbg_2019', 'pei', 'sirh') in 31.464 ms\n",
-      "failed: ('maricopa_cbg_2019', 'pei', 'sparsemod') in 58.167 ms\n",
-      "failed: ('maricopa_cbg_2019', 'pei', 'no') in 72.421 ms\n",
-      "failed: ('maricopa_cbg_2019', 'sparsemod', 'pei') in 31.109 ms\n",
-      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sirs') in 14.571 ms\n",
-      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sirh') in 30.271 ms\n",
-      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sparsemod') in 67.814 ms\n",
-      "failed: ('maricopa_cbg_2019', 'sparsemod', 'no') in 17.723 ms\n",
-      "failed: ('maricopa_cbg_2019', 'centroids', 'pei') in 15.584 ms\n",
-      "succeeded: ('us_counties_2015', 'icecube', 'sirs') in 8795.431 ms\n",
-      "failed: ('us_sw_counties_2015', 'sparsemod', 'pei') in 10721.176 ms\n",
-      "failed: ('us_sw_counties_2015', 'sparsemod', 'sirs') in 17.812 ms\n",
-      "failed: ('us_sw_counties_2015', 'centroids', 'pei') in 10686.765 ms\n",
-      "failed: ('us_sw_counties_2015', 'sparsemod', 'sirh') in 24.423 ms\n",
-      "failed: ('us_sw_counties_2015', 'sparsemod', 'sparsemod') in 50.105 ms\n",
-      "failed: ('us_sw_counties_2015', 'sparsemod', 'no') in 14.715 ms\n",
-      "failed: ('us_sw_counties_2015', 'centroids', 'sirs') in 89.788 ms\n",
-      "failed: ('maricopa_cbg_2019', 'icecube', 'pei') in 11.011 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'centroids', 'sirh') in 1341.993 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'centroids', 'sparsemod') in 642.528 ms\n",
-      "succeeded: ('us_sw_counties_2015', 'centroids', 'no') in 196.366 ms\n",
-      "failed: ('maricopa_cbg_2019', 'no', 'pei') in 4.857 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sirs') in 11865.111 ms\n",
-      "succeeded: ('us_counties_2015', 'no', 'sirs') in 16728.326 ms\n",
-      "succeeded: ('us_counties_2015', 'icecube', 'sirh') in 10646.280 ms\n",
-      "succeeded: ('us_counties_2015', 'pei', 'sirs') in 19964.759 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sirs') in 7991.032 ms\n",
-      "succeeded: ('us_counties_2015', 'centroids', 'sirs') in 20810.002 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'no', 'sirs') in 10700.358 ms\n",
-      "succeeded: ('us_counties_2015', 'sparsemod', 'sirs') in 27150.547 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sirh') in 8675.002 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sirh') in 13449.695 ms\n",
-      "succeeded: ('us_counties_2015', 'icecube', 'sparsemod') in 15950.814 ms\n",
-      "succeeded: ('us_counties_2015', 'no', 'sirh') in 18753.613 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'no', 'sirh') in 11321.057 ms\n",
-      "succeeded: ('us_counties_2015', 'icecube', 'no') in 6471.981 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sparsemod') in 13302.166 ms\n",
-      "succeeded: ('us_counties_2015', 'pei', 'sirh') in 22437.803 ms\n",
-      "succeeded: ('us_counties_2015', 'centroids', 'sirh') in 22250.309 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sparsemod') in 17753.246 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'icecube', 'no') in 5208.520 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'no', 'sparsemod') in 12584.250 ms\n",
-      "succeeded: ('us_counties_2015', 'sparsemod', 'sirh') in 27010.883 ms\n",
-      "succeeded: ('us_counties_2015', 'no', 'sparsemod') in 19812.226 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'centroids', 'no') in 9616.104 ms\n",
-      "succeeded: ('maricopa_cbg_2019', 'no', 'no') in 8404.889 ms\n",
-      "succeeded: ('us_counties_2015', 'pei', 'sparsemod') in 24894.068 ms\n",
-      "succeeded: ('us_counties_2015', 'centroids', 'sparsemod') in 24841.705 ms\n",
-      "succeeded: ('us_counties_2015', 'no', 'no') in 13616.743 ms\n",
-      "succeeded: ('us_counties_2015', 'pei', 'no') in 14099.541 ms\n",
-      "succeeded: ('us_counties_2015', 'sparsemod', 'sparsemod') in 28778.122 ms\n",
-      "succeeded: ('us_counties_2015', 'centroids', 'no') in 16476.987 ms\n",
-      "succeeded: ('us_counties_2015', 'sparsemod', 'no') in 21014.654 ms\n"
+      "failed: ('single_pop', 'sparsemod', 'pei') in 61.920 ms\n",
+      "succeeded: ('pei', 'no', 'pei') in 62.041 ms\n",
+      "succeeded: ('pei', 'icecube', 'pei') in 71.879 ms\n",
+      "failed: ('single_pop', 'centroids', 'pei') in 61.670 ms\n",
+      "failed: ('single_pop', 'pei', 'pei') in 78.340 ms\n",
+      "succeeded: ('pei', 'centroids', 'pei') in 82.929 ms\n",
+      "succeeded: ('pei', 'sparsemod', 'pei') in 88.491 ms\n",
+      "succeeded: ('single_pop', 'sparsemod', 'sirs') in 30.365 ms\n",
+      "succeeded: ('pei', 'no', 'sirs') in 13.165 ms\n",
+      "succeeded: ('pei', 'pei', 'pei') in 111.034 ms\n",
+      "succeeded: ('pei', 'icecube', 'sirs') in 21.796 ms\n",
+      "succeeded: ('single_pop', 'centroids', 'sirs') in 32.210 ms\n",
+      "succeeded: ('pei', 'centroids', 'sirs') in 28.048 ms\n",
+      "succeeded: ('single_pop', 'pei', 'sirs') in 42.019 ms\n",
+      "succeeded: ('pei', 'sparsemod', 'sirs') in 34.933 ms\n",
+      "succeeded: ('pei', 'pei', 'sirs') in 37.486 ms\n",
+      "succeeded: ('single_pop', 'sparsemod', 'sirh') in 147.526 ms\n",
+      "succeeded: ('pei', 'no', 'sirh') in 141.622 ms\n",
+      "succeeded: ('pei', 'icecube', 'sirh') in 143.188 ms\n",
+      "succeeded: ('single_pop', 'pei', 'sirh') in 167.746 ms\n",
+      "succeeded: ('single_pop', 'centroids', 'sirh') in 171.207 ms\n",
+      "succeeded: ('pei', 'centroids', 'sirh') in 191.667 ms\n",
+      "succeeded: ('pei', 'sparsemod', 'sirh') in 170.850 ms\n",
+      "succeeded: ('pei', 'pei', 'sirh') in 159.446 ms\n",
+      "succeeded: ('single_pop', 'sparsemod', 'sparsemod') in 118.546 ms\n",
+      "succeeded: ('pei', 'no', 'sparsemod') in 121.484 ms\n",
+      "succeeded: ('pei', 'icecube', 'sparsemod') in 123.940 ms\n",
+      "succeeded: ('single_pop', 'sparsemod', 'no') in 21.091 ms\n",
+      "succeeded: ('pei', 'no', 'no') in 4.449 ms\n",
+      "succeeded: ('pei', 'icecube', 'no') in 13.323 ms\n",
+      "succeeded: ('single_pop', 'centroids', 'sparsemod') in 127.441 ms\n",
+      "failed: ('single_pop', 'icecube', 'pei') in 9.764 ms\n",
+      "failed: ('single_pop', 'no', 'pei') in 4.452 ms\n",
+      "succeeded: ('single_pop', 'centroids', 'no') in 15.213 ms\n",
+      "succeeded: ('pei', 'centroids', 'sparsemod') in 146.618 ms\n",
+      "succeeded: ('pei', 'sparsemod', 'sparsemod') in 130.333 ms\n",
+      "failed: ('us_counties_2015', 'pei', 'pei') in 25.818 ms\n",
+      "succeeded: ('single_pop', 'no', 'sirs') in 9.419 ms\n",
+      "failed: ('us_counties_2015', 'sparsemod', 'pei') in 21.323 ms\n",
+      "succeeded: ('pei', 'sparsemod', 'no') in 17.913 ms\n",
+      "succeeded: ('pei', 'centroids', 'no') in 23.039 ms\n",
+      "succeeded: ('single_pop', 'pei', 'sparsemod') in 216.704 ms\n",
+      "failed: ('us_counties_2015', 'centroids', 'pei') in 15.410 ms\n",
+      "failed: ('us_counties_2015', 'icecube', 'pei') in 10.890 ms\n",
+      "succeeded: ('single_pop', 'no', 'sirh') in 29.631 ms\n",
+      "succeeded: ('single_pop', 'pei', 'no') in 37.558 ms\n",
+      "failed: ('us_counties_2015', 'no', 'pei') in 10.541 ms\n",
+      "succeeded: ('pei', 'pei', 'sparsemod') in 242.727 ms\n",
+      "succeeded: ('pei', 'pei', 'no') in 29.129 ms\n",
+      "succeeded: ('single_pop', 'icecube', 'sirs') in 182.868 ms\n",
+      "succeeded: ('single_pop', 'no', 'sparsemod') in 97.078 ms\n",
+      "succeeded: ('single_pop', 'no', 'no') in 6.980 ms\n",
+      "failed: ('us_states_2015', 'pei', 'pei') in 56.107 ms\n",
+      "succeeded: ('single_pop', 'icecube', 'sirh') in 30.010 ms\n",
+      "failed: ('us_states_2015', 'sparsemod', 'pei') in 23.749 ms\n",
+      "succeeded: ('single_pop', 'icecube', 'sparsemod') in 117.856 ms\n",
+      "succeeded: ('single_pop', 'icecube', 'no') in 14.580 ms\n",
+      "succeeded: ('us_states_2015', 'pei', 'sirs') in 178.393 ms\n",
+      "failed: ('us_states_2015', 'centroids', 'pei') in 19.069 ms\n",
+      "succeeded: ('us_states_2015', 'sparsemod', 'sirs') in 239.479 ms\n",
+      "succeeded: ('us_states_2015', 'centroids', 'sirs') in 74.068 ms\n",
+      "succeeded: ('us_states_2015', 'pei', 'sirh') in 194.347 ms\n",
+      "succeeded: ('us_states_2015', 'sparsemod', 'sirh') in 96.939 ms\n",
+      "succeeded: ('us_states_2015', 'centroids', 'sirh') in 134.681 ms\n",
+      "succeeded: ('us_states_2015', 'sparsemod', 'sparsemod') in 185.063 ms\n",
+      "succeeded: ('us_states_2015', 'sparsemod', 'no') in 36.132 ms\n",
+      "succeeded: ('us_states_2015', 'pei', 'sparsemod') in 256.530 ms\n",
+      "failed: ('us_states_2015', 'icecube', 'pei') in 9.430 ms\n",
+      "succeeded: ('us_states_2015', 'centroids', 'sparsemod') in 220.862 ms\n",
+      "succeeded: ('us_states_2015', 'centroids', 'no') in 31.563 ms\n",
+      "failed: ('us_states_2015', 'no', 'pei') in 4.271 ms\n",
+      "succeeded: ('us_states_2015', 'icecube', 'sirs') in 63.279 ms\n",
+      "succeeded: ('us_states_2015', 'pei', 'no') in 87.320 ms\n",
+      "succeeded: ('us_states_2015', 'no', 'sirs') in 32.277 ms\n",
+      "succeeded: ('us_states_2015', 'no', 'sirh') in 42.437 ms\n",
+      "succeeded: ('us_states_2015', 'icecube', 'sirh') in 77.759 ms\n",
+      "succeeded: ('us_states_2015', 'no', 'sparsemod') in 115.616 ms\n",
+      "succeeded: ('us_states_2015', 'no', 'no') in 9.437 ms\n",
+      "succeeded: ('us_states_2015', 'icecube', 'sparsemod') in 176.965 ms\n",
+      "succeeded: ('us_states_2015', 'icecube', 'no') in 21.101 ms\n",
+      "succeeded: ('us_counties_2015', 'icecube', 'sirs') in 9418.484 ms\n",
+      "failed: ('us_sw_counties_2015', 'centroids', 'pei') in 12997.205 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'centroids', 'sirs') in 311.861 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'centroids', 'sirh') in 464.451 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'centroids', 'sparsemod') in 725.492 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'centroids', 'no') in 206.879 ms\n",
+      "failed: ('us_sw_counties_2015', 'icecube', 'pei') in 11.376 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'icecube', 'sirs') in 184.281 ms\n",
+      "failed: ('us_sw_counties_2015', 'pei', 'pei') in 15482.803 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'icecube', 'sirh') in 243.570 ms\n",
+      "failed: ('us_sw_counties_2015', 'pei', 'sirs') in 182.560 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'icecube', 'sparsemod') in 520.595 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'icecube', 'no') in 62.105 ms\n",
+      "failed: ('us_sw_counties_2015', 'no', 'pei') in 4.413 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'no', 'sirs') in 95.246 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'no', 'sirh') in 138.987 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'no', 'sparsemod') in 285.687 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'no', 'no') in 48.624 ms\n",
+      "failed: ('maricopa_cbg_2019', 'pei', 'pei') in 29.037 ms\n",
+      "failed: ('maricopa_cbg_2019', 'pei', 'sirs') in 27.812 ms\n",
+      "failed: ('maricopa_cbg_2019', 'pei', 'sirh') in 36.228 ms\n",
+      "failed: ('maricopa_cbg_2019', 'pei', 'sparsemod') in 62.918 ms\n",
+      "failed: ('maricopa_cbg_2019', 'pei', 'no') in 29.656 ms\n",
+      "failed: ('maricopa_cbg_2019', 'sparsemod', 'pei') in 17.967 ms\n",
+      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sirs') in 17.549 ms\n",
+      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sirh') in 28.485 ms\n",
+      "failed: ('maricopa_cbg_2019', 'sparsemod', 'sparsemod') in 68.906 ms\n",
+      "succeeded: ('us_counties_2015', 'no', 'sirs') in 18083.627 ms\n",
+      "failed: ('maricopa_cbg_2019', 'sparsemod', 'no') in 19.430 ms\n",
+      "failed: ('maricopa_cbg_2019', 'centroids', 'pei') in 18.337 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'pei', 'sirh') in 1533.886 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'pei', 'sparsemod') in 695.670 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'pei', 'no') in 468.443 ms\n",
+      "failed: ('maricopa_cbg_2019', 'icecube', 'pei') in 11.912 ms\n",
+      "succeeded: ('us_counties_2015', 'pei', 'sirs') in 21610.587 ms\n",
+      "succeeded: ('us_counties_2015', 'icecube', 'sirh') in 13093.204 ms\n",
+      "succeeded: ('us_counties_2015', 'centroids', 'sirs') in 22523.608 ms\n",
+      "succeeded: ('us_counties_2015', 'sparsemod', 'sirs') in 28058.225 ms\n",
+      "failed: ('us_sw_counties_2015', 'sparsemod', 'pei') in 27433.597 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sirs') in 9201.051 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'sparsemod', 'sirs') in 1819.331 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'sparsemod', 'sirh') in 682.734 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'sparsemod', 'sparsemod') in 728.355 ms\n",
+      "succeeded: ('us_sw_counties_2015', 'sparsemod', 'no') in 338.339 ms\n",
+      "failed: ('maricopa_cbg_2019', 'no', 'pei') in 4.845 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sirs') in 14848.517 ms\n",
+      "succeeded: ('us_counties_2015', 'no', 'sirh') in 20967.992 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sirh') in 10838.965 ms\n",
+      "succeeded: ('us_counties_2015', 'icecube', 'sparsemod') in 20278.106 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'no', 'sirs') in 13922.110 ms\n",
+      "succeeded: ('us_counties_2015', 'centroids', 'sirh') in 25334.168 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sirh') in 15910.061 ms\n",
+      "succeeded: ('us_counties_2015', 'pei', 'sirh') in 27944.012 ms\n",
+      "succeeded: ('us_counties_2015', 'icecube', 'no') in 8079.196 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'icecube', 'sparsemod') in 15149.787 ms\n",
+      "succeeded: ('us_counties_2015', 'sparsemod', 'sirh') in 30462.105 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'no', 'sirh') in 12706.855 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'icecube', 'no') in 5749.188 ms\n",
+      "succeeded: ('us_counties_2015', 'no', 'sparsemod') in 22634.240 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'centroids', 'sparsemod') in 19273.869 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'no', 'sparsemod') in 12725.172 ms\n",
+      "succeeded: ('us_counties_2015', 'no', 'no') in 14936.670 ms\n",
+      "succeeded: ('us_counties_2015', 'centroids', 'sparsemod') in 29830.805 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'centroids', 'no') in 10060.107 ms\n",
+      "succeeded: ('us_counties_2015', 'pei', 'sparsemod') in 29360.442 ms\n",
+      "succeeded: ('maricopa_cbg_2019', 'no', 'no') in 9109.123 ms\n",
+      "succeeded: ('us_counties_2015', 'sparsemod', 'sparsemod') in 31732.416 ms\n",
+      "succeeded: ('us_counties_2015', 'pei', 'no') in 15485.422 ms\n",
+      "succeeded: ('us_counties_2015', 'centroids', 'no') in 17854.806 ms\n",
+      "succeeded: ('us_counties_2015', 'sparsemod', 'no') in 20781.683 ms\n"
      ]
     }
    ],
@@ -293,7 +293,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 800x400 with 2 Axes>"
       ]
@@ -403,25 +403,25 @@
        "      <td>sparsemod</td>\n",
        "      <td>sparsemod</td>\n",
        "      <td>True</td>\n",
-       "      <td>28.778122</td>\n",
+       "      <td>31.732416</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>us_counties_2015</td>\n",
        "      <td>sparsemod</td>\n",
-       "      <td>sirs</td>\n",
+       "      <td>sirh</td>\n",
        "      <td>True</td>\n",
-       "      <td>27.150547</td>\n",
+       "      <td>30.462105</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>us_counties_2015</td>\n",
+       "      <td>centroids</td>\n",
        "      <td>sparsemod</td>\n",
-       "      <td>sirh</td>\n",
        "      <td>True</td>\n",
-       "      <td>27.010883</td>\n",
+       "      <td>29.830805</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -430,16 +430,16 @@
        "      <td>pei</td>\n",
        "      <td>sparsemod</td>\n",
        "      <td>True</td>\n",
-       "      <td>24.894068</td>\n",
+       "      <td>29.360442</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>us_counties_2015</td>\n",
-       "      <td>centroids</td>\n",
        "      <td>sparsemod</td>\n",
+       "      <td>sirs</td>\n",
        "      <td>True</td>\n",
-       "      <td>24.841705</td>\n",
+       "      <td>28.058225</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -452,70 +452,70 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>103</th>\n",
-       "      <td>single_pop</td>\n",
-       "      <td>icecube</td>\n",
+       "      <th>111</th>\n",
+       "      <td>pei</td>\n",
        "      <td>no</td>\n",
+       "      <td>sirs</td>\n",
        "      <td>True</td>\n",
-       "      <td>0.009799</td>\n",
+       "      <td>0.013165</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>104</th>\n",
+       "      <th>112</th>\n",
        "      <td>us_states_2015</td>\n",
        "      <td>no</td>\n",
        "      <td>no</td>\n",
        "      <td>True</td>\n",
-       "      <td>0.009310</td>\n",
+       "      <td>0.009437</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>105</th>\n",
+       "      <th>113</th>\n",
        "      <td>single_pop</td>\n",
        "      <td>no</td>\n",
        "      <td>sirs</td>\n",
        "      <td>True</td>\n",
-       "      <td>0.008027</td>\n",
+       "      <td>0.009419</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>106</th>\n",
-       "      <td>pei</td>\n",
+       "      <th>114</th>\n",
+       "      <td>single_pop</td>\n",
        "      <td>no</td>\n",
        "      <td>no</td>\n",
        "      <td>True</td>\n",
-       "      <td>0.004139</td>\n",
+       "      <td>0.006980</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>107</th>\n",
-       "      <td>single_pop</td>\n",
+       "      <th>115</th>\n",
+       "      <td>pei</td>\n",
        "      <td>no</td>\n",
        "      <td>no</td>\n",
        "      <td>True</td>\n",
-       "      <td>0.003998</td>\n",
+       "      <td>0.004449</td>\n",
        "      <td>None</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>108 rows × 6 columns</p>\n",
+       "<p>116 rows × 6 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "                  geo         mm        ipm  runs    runtime error\n",
-       "0    us_counties_2015  sparsemod  sparsemod  True  28.778122  None\n",
-       "1    us_counties_2015  sparsemod       sirs  True  27.150547  None\n",
-       "2    us_counties_2015  sparsemod       sirh  True  27.010883  None\n",
-       "3    us_counties_2015        pei  sparsemod  True  24.894068  None\n",
-       "4    us_counties_2015  centroids  sparsemod  True  24.841705  None\n",
+       "0    us_counties_2015  sparsemod  sparsemod  True  31.732416  None\n",
+       "1    us_counties_2015  sparsemod       sirh  True  30.462105  None\n",
+       "2    us_counties_2015  centroids  sparsemod  True  29.830805  None\n",
+       "3    us_counties_2015        pei  sparsemod  True  29.360442  None\n",
+       "4    us_counties_2015  sparsemod       sirs  True  28.058225  None\n",
        "..                ...        ...        ...   ...        ...   ...\n",
-       "103        single_pop    icecube         no  True   0.009799  None\n",
-       "104    us_states_2015         no         no  True   0.009310  None\n",
-       "105        single_pop         no       sirs  True   0.008027  None\n",
-       "106               pei         no         no  True   0.004139  None\n",
-       "107        single_pop         no         no  True   0.003998  None\n",
+       "111               pei         no       sirs  True   0.013165  None\n",
+       "112    us_states_2015         no         no  True   0.009437  None\n",
+       "113        single_pop         no       sirs  True   0.009419  None\n",
+       "114        single_pop         no         no  True   0.006980  None\n",
+       "115               pei         no         no  True   0.004449  None\n",
        "\n",
-       "[108 rows x 6 columns]"
+       "[116 rows x 6 columns]"
       ]
      },
      "execution_count": 3,
diff --git a/doc/devlog/2024-03-19.ipynb b/doc/devlog/2024-03-19.ipynb
new file mode 100644
index 00000000..7f864113
--- /dev/null
+++ b/doc/devlog/2024-03-19.ipynb
@@ -0,0 +1,83 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# devlog 2024-03-19\n",
+    "\n",
+    "Canonicalization of the code to create the `us_sw_counties_2015.geo` spec."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from epymorph.data_shape import Shapes\n",
+    "from epymorph.geo.adrio.census.adrio_census import CensusGeography, Granularity\n",
+    "from epymorph.geo.spec import AttribDef, CentroidDType, DynamicGeoSpec, Year\n",
+    "\n",
+    "spec = DynamicGeoSpec(\n",
+    "    attributes=[\n",
+    "        AttribDef('label', dtype=np.str_, shape=Shapes.N),\n",
+    "        AttribDef('population', dtype=np.int64, shape=Shapes.N),\n",
+    "        AttribDef('population_by_age', dtype=np.int64, shape=Shapes.NxA(3)),\n",
+    "        AttribDef('centroid', dtype=CentroidDType, shape=Shapes.N),\n",
+    "        AttribDef('geoid', dtype=np.str_, shape=Shapes.N),\n",
+    "        AttribDef('dissimilarity_index', dtype=np.float64, shape=Shapes.N),\n",
+    "        AttribDef('median_income', dtype=np.int64, shape=Shapes.N),\n",
+    "        AttribDef('pop_density_km2', dtype=np.float64, shape=Shapes.N),\n",
+    "        AttribDef('commuters', dtype=np.int64, shape=Shapes.NxN),\n",
+    "    ],\n",
+    "    time_period=Year(2015),\n",
+    "    geography=CensusGeography(granularity=Granularity.COUNTY, filter={\n",
+    "        'state': ['04', '08', '49', '35', '32'],\n",
+    "        'county': ['*'],\n",
+    "        'tract': ['*'],\n",
+    "        'block group': ['*']\n",
+    "    }),\n",
+    "    source={\n",
+    "        'label': 'Census:name',\n",
+    "        'population': 'Census',\n",
+    "        'population_by_age': 'Census',\n",
+    "        'centroid': 'Census',\n",
+    "        'geoid': 'Census',\n",
+    "        'dissimilarity_index': 'Census',\n",
+    "        'median_income': 'Census',\n",
+    "        'pop_density_km2': 'Census',\n",
+    "        'commuters': 'Census',\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "with open('./epymorph/data/geo/us_sw_counties_2015.geo', mode='w', encoding='utf-8') as f:\n",
+    "    json = spec.serialize()\n",
+    "    f.write(json)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/epymorph/data/geo/us_sw_counties_2015.geo b/epymorph/data/geo/us_sw_counties_2015.geo
index 4bb1970d..1d947ee4 100644
--- a/epymorph/data/geo/us_sw_counties_2015.geo
+++ b/epymorph/data/geo/us_sw_counties_2015.geo
@@ -1 +1 @@
-{"py/object": "epymorph.geo.spec.DynamicGeoSpec", "py/state": {"attributes": [{"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["label", {"py/type": "numpy.str_"}, {"py/object": "epymorph.data_shape.Node"}]}, "py/seq": ["label", {"py/type": "numpy.str_"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["population", {"py/type": "numpy.int64"}, {"py/id": 4}]}, "py/seq": ["population", {"py/type": "numpy.int64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["population_by_age", {"py/type": "numpy.int64"}, {"py/object": "epymorph.data_shape.NodeAndArbitrary", "index": 3}]}, "py/seq": ["population_by_age", {"py/type": "numpy.int64"}, {"py/id": 7}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["centroid", {"py/reduce": [{"py/type": "numpy.dtype"}, {"py/tuple": ["V16", false, true]}, {"py/tuple": [3, "|", null, {"py/tuple": ["longitude", "latitude"]}, {"longitude": {"py/tuple": [{"py/reduce": [{"py/type": "numpy.dtype"}, {"py/tuple": ["f8", false, true]}, {"py/tuple": [3, "<", null, null, null, -1, -1, 0]}]}, 0]}, "latitude": {"py/tuple": [{"py/id": 11}, 8]}}, 16, 1, 16]}]}, {"py/id": 4}]}, "py/seq": ["centroid", {"py/id": 9}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["geoid", {"py/type": "numpy.str_"}, {"py/id": 4}]}, "py/seq": ["geoid", {"py/type": "numpy.int64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["dissimilarity_index", {"py/type": "numpy.float64"}, {"py/id": 4}]}, "py/seq": ["dissimilarity_index", {"py/type": "numpy.float64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["median_income", {"py/type": "numpy.int64"}, {"py/id": 4}]}, "py/seq": ["median_income", {"py/type": "numpy.int64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["pop_density_km2", {"py/type": "numpy.float64"}, {"py/id": 4}]}, "py/seq": ["pop_density_km2", {"py/type": "numpy.float64"}, {"py/id": 4}]}], "time_period": {"py/object": "epymorph.geo.spec.Year", "year": 2015}, "geography": {"py/object": "epymorph.geo.adrio.census.adrio_census.CensusGeography", "granularity": {"py/reduce": [{"py/type": "epymorph.geo.adrio.census.adrio_census.Granularity"}, {"py/tuple": [1]}]}, "filter": {"state": ["04", "08", "49", "35", "32"], "county": ["*"], "tract": ["*"], "block group": ["*"]}}, "source": {"label": "Census:name", "population": "Census", "population_by_age": "Census", "centroid": "Census", "geoid": "Census", "dissimilarity_index": "Census", "median_income": "Census", "pop_density_km2": "Census"}}}
+{"py/object": "epymorph.geo.spec.DynamicGeoSpec", "py/state": {"attributes": [{"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["label", {"py/type": "numpy.str_"}, {"py/object": "epymorph.data_shape.Node"}]}, "py/seq": ["label", {"py/type": "numpy.str_"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["population", {"py/type": "numpy.int64"}, {"py/id": 4}]}, "py/seq": ["population", {"py/type": "numpy.int64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["population_by_age", {"py/type": "numpy.int64"}, {"py/object": "epymorph.data_shape.NodeAndArbitrary", "index": 3}]}, "py/seq": ["population_by_age", {"py/type": "numpy.int64"}, {"py/id": 7}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["centroid", [{"py/tuple": ["longitude", {"py/type": "numpy.float64"}]}, {"py/tuple": ["latitude", {"py/type": "numpy.float64"}]}], {"py/id": 4}]}, "py/seq": ["centroid", {"py/id": 9}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["geoid", {"py/type": "numpy.str_"}, {"py/id": 4}]}, "py/seq": ["geoid", {"py/type": "numpy.str_"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["dissimilarity_index", {"py/type": "numpy.float64"}, {"py/id": 4}]}, "py/seq": ["dissimilarity_index", {"py/type": "numpy.float64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["median_income", {"py/type": "numpy.int64"}, {"py/id": 4}]}, "py/seq": ["median_income", {"py/type": "numpy.int64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["pop_density_km2", {"py/type": "numpy.float64"}, {"py/id": 4}]}, "py/seq": ["pop_density_km2", {"py/type": "numpy.float64"}, {"py/id": 4}]}, {"py/object": "epymorph.geo.spec.AttribDef", "py/newargs": {"py/tuple": ["commuters", {"py/type": "numpy.int64"}, {"py/object": "epymorph.data_shape.NodeAndNode"}]}, "py/seq": ["commuters", {"py/type": "numpy.int64"}, {"py/id": 15}]}], "time_period": {"py/object": "epymorph.geo.spec.Year", "year": 2015}, "geography": {"py/object": "epymorph.geo.adrio.census.adrio_census.CensusGeography", "granularity": {"py/reduce": [{"py/type": "epymorph.geo.adrio.census.adrio_census.Granularity"}, {"py/tuple": [1]}]}, "filter": {"state": ["04", "08", "49", "35", "32"], "county": ["*"], "tract": ["*"], "block group": ["*"]}}, "source": {"label": "Census:name", "population": "Census", "population_by_age": "Census", "centroid": "Census", "geoid": "Census", "dissimilarity_index": "Census", "median_income": "Census", "pop_density_km2": "Census", "commuters": "Census"}}}
\ No newline at end of file