diff --git a/content/data/demo.arg b/content/data/demo.arg
deleted file mode 100644
index 7f80dff..0000000
Binary files a/content/data/demo.arg and /dev/null differ
diff --git a/content/data/demo.py b/content/data/demo.py
new file mode 100644
index 0000000..361b644
--- /dev/null
+++ b/content/data/demo.py
@@ -0,0 +1,48 @@
+# demo.tree file created using the following script
+
+import tskit
+import msprime
+import collections
+
+from matplotlib import pyplot as plt
+
+seq_length = 1e6
+recent_generations = 200
+rho = 1e-7
+tree = "((A:250,B:250):150,(C:210,D:210):190);"
+initial_size = collections.defaultdict(lambda: 500)
+initial_size.update({"A": 500, "B": 500, "C": 300, "D": 1000})
+samples = {"A": 10, "B": 10, "C": 10, "D": 10}
+
+ts_store = []
+for name, Ne in initial_size.items():
+    demography = msprime.Demography()
+    demography.add_population(name=name, initial_size=Ne)
+    # Place a selective sweep in population A
+    if name == "A":
+        p = 1 / (2 * Ne)
+        sweep_model = msprime.SweepGenicSelection(
+            position=seq_length//3,
+            s=0.1,
+            start_frequency=p,
+            end_frequency=1 - p,
+            dt=1 / (40 * Ne),
+        )
+    ts_store.append(msprime.sim_ancestry(
+        samples[name],
+        model=(sweep_model, msprime.StandardCoalescent()) if name == "A" else msprime.StandardCoalescent(),
+        demography=demography,
+        recombination_rate=rho,
+        sequence_length=seq_length,
+        end_time=recent_generations,
+        random_seed=123,
+    ))
+tables = ts_store[0].dump_tables()
+for ts in ts_store[1:]:
+    tables.union(ts.dump_tables(), node_mapping=[tskit.NULL] * ts.num_nodes)
+tables.provenances.clear()
+
+demography = msprime.Demography.from_species_tree(tree, initial_size)
+ts = msprime.sim_ancestry(initial_state=tables.tree_sequence(), recombination_rate=rho, sequence_length=seq_length, demography=demography, random_seed=123).simplify()
+ts = msprime.sim_mutations(ts, rate=5e-8, random_seed=123)
+ts.dump("data/demo.trees")
\ No newline at end of file
diff --git a/content/data/demo.trees b/content/data/demo.trees
index f1a164f..6537e0d 100644
Binary files a/content/data/demo.trees and b/content/data/demo.trees differ
diff --git a/content/tskit.ipynb b/content/tskit.ipynb
index 4382492..a6afd15 100644
--- a/content/tskit.ipynb
+++ b/content/tskit.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "ad71f199",
    "metadata": {},
    "outputs": [],
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "4961282f",
    "metadata": {},
    "outputs": [],
@@ -28,9 +28,17 @@
     "ts = tskit.load(\"data/demo.trees\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "058be451-3ea5-4833-82ce-230d53390585",
+   "metadata": {},
+   "source": [
+    "In a notebook, we can show a tabular summary of the tree sequence file by displaying it to screen. Note that the [provenances](https://tskit.dev/tskit/docs/stable/provenance.html) listed in the second table below record how this ARG was originally generated (in this case, initially simulated by the [msprime](https://tskit.dev/msprime/docs/stable/intro.html) command `sim_ancestry`)."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "1a896cb8",
    "metadata": {},
    "outputs": [
@@ -61,11 +69,11 @@
        "                            </tr>\n",
        "                        </thead>\n",
        "                        <tbody>\n",
-       "                            <tr><td>Trees</td><td>836</td></tr>\n",
+       "                            <tr><td>Trees</td><td>1 811</td></tr>\n",
        "                            <tr><td>Sequence Length</td><td>1 000 000</td></tr>\n",
        "                            <tr><td>Time Units</td><td>generations</td></tr>\n",
-       "                            <tr><td>Sample Nodes</td><td>200</td></tr>\n",
-       "                            <tr><td>Total Size</td><td>273.1 KiB</td></tr>\n",
+       "                            <tr><td>Sample Nodes</td><td>80</td></tr>\n",
+       "                            <tr><td>Total Size</td><td>375.2 KiB</td></tr>\n",
        "                            <tr>\n",
        "                                <td>Metadata</td><td style=\"text-align: left;\">No Metadata</td>\n",
        "                            </tr>\n",
@@ -86,8 +94,8 @@
        "                            \n",
        "            <tr>\n",
        "                <td>Edges</td>\n",
-       "                <td>3 301</td>\n",
-       "                <td>103.2 KiB</td>\n",
+       "                <td>6 979</td>\n",
+       "                <td>218.1 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -95,8 +103,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Individuals</td>\n",
-       "                <td>100</td>\n",
-       "                <td>2.8 KiB</td>\n",
+       "                <td>40</td>\n",
+       "                <td>1.1 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -113,8 +121,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Mutations</td>\n",
-       "                <td>1 816</td>\n",
-       "                <td>65.6 KiB</td>\n",
+       "                <td>989</td>\n",
+       "                <td>35.8 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -122,8 +130,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Nodes</td>\n",
-       "                <td>1 029</td>\n",
-       "                <td>28.1 KiB</td>\n",
+       "                <td>1 337</td>\n",
+       "                <td>36.6 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -131,8 +139,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Populations</td>\n",
-       "                <td>4</td>\n",
-       "                <td>347 Bytes</td>\n",
+       "                <td>7</td>\n",
+       "                <td>454 Bytes</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    ✅\n",
        "                </td>\n",
@@ -140,8 +148,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Provenances</td>\n",
-       "                <td>2</td>\n",
-       "                <td>2.9 KiB</td>\n",
+       "                <td>3</td>\n",
+       "                <td>4.5 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -149,8 +157,8 @@
        "        \n",
        "            <tr>\n",
        "                <td>Sites</td>\n",
-       "                <td>1 814</td>\n",
-       "                <td>44.3 KiB</td>\n",
+       "                <td>989</td>\n",
+       "                <td>24.2 KiB</td>\n",
        "                <td style=\"text-align: center;\">\n",
        "                    \n",
        "                </td>\n",
@@ -173,7 +181,7 @@
        "                        <tbody>\n",
        "                            \n",
        "                <tr>\n",
-       "                    <td>07 January, 2026 at 11:56:13 AM</td>\n",
+       "                    <td>13 January, 2026 at 12:17:04 PM</td>\n",
        "                    <td>msprime</td>\n",
        "                    <td>1.3.3.dev60+g1a86a021.d20250519</td>\n",
        "                    <td>sim_mutations</td>\n",
@@ -206,7 +214,7 @@
        "                    __constant__: __current_ts__<br/>\n",
        "                </details>\n",
        "            </div>\n",
-       "            <br/>rate: 1e-08<br/>model: None<br/>start_time: None<br/>end_time: None<br/>discrete_genome: None<br/>keep: None<br/>random_seed: 123<br/>\n",
+       "            <br/>rate: 5e-08<br/>model: None<br/>start_time: None<br/>end_time: None<br/>discrete_genome: None<br/>keep: None<br/>random_seed: 123<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -219,7 +227,7 @@
        "                <span class=\"tskit-details-label\">os:</span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    system: Darwin<br/>node: A04s-de-<br/>Brebs.ComplexeAscotel.fr<br/>release: 24.6.0<br/>version: Darwin Kernel Version 24.6.0:<br/>Mon Jul 14 11:30:51 PDT 2025; <br/>root:xnu-<br/>11417.140.69~1/RELEASE_ARM64_T<br/>8...<br/>machine: arm64<br/>\n",
+       "                    system: Darwin<br/>node: Yans-M2.local<br/>release: 24.6.0<br/>version: Darwin Kernel Version 24.6.0:<br/>Mon Jul 14 11:30:51 PDT 2025; <br/>root:xnu-<br/>11417.140.69~1/RELEASE_ARM64_T<br/>8...<br/>machine: arm64<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -274,10 +282,10 @@
        "                </tr>\n",
        "            \n",
        "                <tr>\n",
-       "                    <td>07 January, 2026 at 11:56:13 AM</td>\n",
-       "                    <td>msprime</td>\n",
-       "                    <td>1.3.3.dev60+g1a86a021.d20250519</td>\n",
-       "                    <td>sim_ancestry</td>\n",
+       "                    <td>13 January, 2026 at 12:17:04 PM</td>\n",
+       "                    <td>tskit</td>\n",
+       "                    <td>1.0.0</td>\n",
+       "                    <td>simplify</td>\n",
        "                    <td>\n",
        "                        <details>\n",
        "                            <summary>Details</summary>\n",
@@ -291,7 +299,7 @@
        "                <span class=\"tskit-details-label\">software:</span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    name: msprime<br/>version: 1.3.3.dev60+g1a86a021.d2025051<br/>9<br/>\n",
+       "                    name: tskit<br/>version: 1.0.0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -299,15 +307,84 @@
        "                <span class=\"tskit-details-label\">parameters:</span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    command: sim_ancestry<br/>\n",
+       "                    command: simplify<br/>TODO: add simplify parameters<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">environment:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    \n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">os:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    system: Darwin<br/>node: Yans-M2.local<br/>release: 24.6.0<br/>version: Darwin Kernel Version 24.6.0:<br/>Mon Jul 14 11:30:51 PDT 2025; <br/>root:xnu-<br/>11417.140.69~1/RELEASE_ARM64_T<br/>8...<br/>machine: arm64<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">python:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    implementation: CPython<br/>version: 3.12.5<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">libraries:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    \n",
        "            <div>\n",
-       "                <span class=\"tskit-details-label\">samples:</span>\n",
+       "                <span class=\"tskit-details-label\">kastore:</span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    pop_0: 25<br/>pop_1: 25<br/>pop_2: 25<br/>pop_3: 25<br/>\n",
+       "                    version: 2.1.1<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            \n",
+       "                        </details>\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            \n",
+       "                <tr>\n",
+       "                    <td>13 January, 2026 at 12:17:04 PM</td>\n",
+       "                    <td>msprime</td>\n",
+       "                    <td>1.3.3.dev60+g1a86a021.d20250519</td>\n",
+       "                    <td>sim_ancestry</td>\n",
+       "                    <td>\n",
+       "                        <details>\n",
+       "                            <summary>Details</summary>\n",
+       "                            \n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    schema_version: 1.0.0<br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">software:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    name: msprime<br/>version: 1.3.3.dev60+g1a86a021.d2025051<br/>9<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">parameters:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    command: sim_ancestry<br/>samples: None<br/>\n",
        "            <div>\n",
        "                <span class=\"tskit-details-label\">demography:</span>\n",
        "                <details >\n",
@@ -322,7 +399,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    initial_size: 1000.0<br/>growth_rate: 0.0<br/>name: pop_0<br/>description: <br/>\n",
+       "                    initial_size: 500<br/>growth_rate: 0.0<br/>name: A<br/>description: <br/>\n",
        "            <div>\n",
        "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
        "                <details >\n",
@@ -338,7 +415,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    initial_size: 1000.0<br/>growth_rate: 0.0<br/>name: pop_1<br/>description: <br/>\n",
+       "                    initial_size: 500<br/>growth_rate: 0.0<br/>name: B<br/>description: <br/>\n",
        "            <div>\n",
        "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
        "                <details >\n",
@@ -354,7 +431,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    initial_size: 1000.0<br/>growth_rate: 0.0<br/>name: pop_2<br/>description: <br/>\n",
+       "                    initial_size: 300<br/>growth_rate: 0.0<br/>name: C<br/>description: <br/>\n",
        "            <div>\n",
        "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
        "                <details >\n",
@@ -370,7 +447,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    initial_size: 1000.0<br/>growth_rate: 0.0<br/>name: pop_3<br/>description: <br/>\n",
+       "                    initial_size: 1000<br/>growth_rate: 0.0<br/>name: D<br/>description: <br/>\n",
        "            <div>\n",
        "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
        "                <details >\n",
@@ -382,6 +459,54 @@
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    initial_size: 500<br/>growth_rate: 0.0<br/>name: pop_4<br/>description: <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    \n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>default_sampling_time: 250.0<br/>initially_active: False<br/>id: 4<br/>__class__: msprime.demography.Population<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    initial_size: 500<br/>growth_rate: 0.0<br/>name: pop_5<br/>description: <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    \n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>default_sampling_time: 210.0<br/>initially_active: False<br/>id: 5<br/>__class__: msprime.demography.Population<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    initial_size: 500<br/>growth_rate: 0.0<br/>name: pop_6<br/>description: <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">extra_metadata:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    \n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>default_sampling_time: 400.0<br/>initially_active: False<br/>id: 6<br/>__class__: msprime.demography.Population<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -390,6 +515,54 @@
        "                <details >\n",
        "                    <summary>list</summary>\n",
        "                    \n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    time: 210.0<br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">derived:</span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     C<br/> D<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>ancestral: pop_5<br/>__class__: msprime.demography.PopulationS<br/>plit<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    time: 250.0<br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">derived:</span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     A<br/> B<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>ancestral: pop_4<br/>__class__: msprime.demography.PopulationS<br/>plit<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    time: 400.0<br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">derived:</span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     pop_4<br/> pop_5<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>ancestral: pop_6<br/>__class__: msprime.demography.PopulationS<br/>plit<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -402,7 +575,23 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>list</summary>\n",
-       "                     0.0<br/> 2e-05<br/> 2e-05<br/> 2e-05<br/>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -410,7 +599,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>list</summary>\n",
-       "                     2e-05<br/> 0.0<br/> 2e-05<br/> 2e-05<br/>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -418,7 +607,7 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>list</summary>\n",
-       "                     2e-05<br/> 2e-05<br/> 0.0<br/> 2e-05<br/>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -426,7 +615,15 @@
        "                <span class=\"tskit-details-label\"></span>\n",
        "                <details >\n",
        "                    <summary>list</summary>\n",
-       "                     2e-05<br/> 2e-05<br/> 2e-05<br/> 0.0<br/>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\"></span>\n",
+       "                <details >\n",
+       "                    <summary>list</summary>\n",
+       "                     0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/> 0.0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -435,7 +632,15 @@
        "            <br/>__class__: msprime.demography.Demography<br/>\n",
        "                </details>\n",
        "            </div>\n",
-       "            <br/>sequence_length: 1000000.0<br/>discrete_genome: None<br/>recombination_rate: 1e-08<br/>gene_conversion_rate: None<br/>gene_conversion_tract_length: None<br/>population_size: None<br/>ploidy: None<br/>model: None<br/>initial_state: None<br/>start_time: None<br/>end_time: None<br/>record_migrations: None<br/>record_full_arg: None<br/>additional_nodes: None<br/>coalescing_segments_only: None<br/>num_labels: None<br/>random_seed: 123<br/>replicate_index: 0<br/>\n",
+       "            <br/>sequence_length: 1000000.0<br/>discrete_genome: None<br/>recombination_rate: 1e-07<br/>gene_conversion_rate: None<br/>gene_conversion_tract_length: None<br/>population_size: None<br/>ploidy: None<br/>model: None<br/>\n",
+       "            <div>\n",
+       "                <span class=\"tskit-details-label\">initial_state:</span>\n",
+       "                <details >\n",
+       "                    <summary>dict</summary>\n",
+       "                    __constant__: __current_ts__<br/>\n",
+       "                </details>\n",
+       "            </div>\n",
+       "            <br/>start_time: None<br/>end_time: None<br/>record_migrations: None<br/>record_full_arg: None<br/>additional_nodes: None<br/>coalescing_segments_only: None<br/>num_labels: None<br/>random_seed: 123<br/>replicate_index: 0<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -448,7 +653,7 @@
        "                <span class=\"tskit-details-label\">os:</span>\n",
        "                <details >\n",
        "                    <summary>dict</summary>\n",
-       "                    system: Darwin<br/>node: A04s-de-<br/>Brebs.ComplexeAscotel.fr<br/>release: 24.6.0<br/>version: Darwin Kernel Version 24.6.0:<br/>Mon Jul 14 11:30:51 PDT 2025; <br/>root:xnu-<br/>11417.140.69~1/RELEASE_ARM64_T<br/>8...<br/>machine: arm64<br/>\n",
+       "                    system: Darwin<br/>node: Yans-M2.local<br/>release: 24.6.0<br/>version: Darwin Kernel Version 24.6.0:<br/>Mon Jul 14 11:30:51 PDT 2025; <br/>root:xnu-<br/>11417.140.69~1/RELEASE_ARM64_T<br/>8...<br/>machine: arm64<br/>\n",
        "                </details>\n",
        "            </div>\n",
        "            <br/>\n",
@@ -513,10 +718,10 @@
        "    "
       ],
       "text/plain": [
-       "<tskit.trees.TreeSequence at 0x10571d280>"
+       "<tskit.trees.TreeSequence at 0x1082c73b0>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -537,7 +742,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "9c518928-5a62-40d4-866d-0488616b4461",
    "metadata": {},
    "outputs": [
@@ -545,7 +750,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "AFS calculated for 200 genomes of length 1.00 Mb\n"
+      "AFS calculated for 80 genomes of length 1.00 Mb\n"
      ]
     }
    ],
@@ -557,13 +762,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "f1accb0d-cf44-430d-8ae5-534800e72663",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -583,13 +788,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "47dbd599-86f1-4693-88dc-9c8fd457168b",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -600,22 +805,23 @@
    ],
    "source": [
     "# Calculate windowed genetic diversity\n",
-    "windowed_diversity = ts.diversity(windows=\"trees\")\n",
-    "plt.stairs(windowed_diversity, ts.breakpoints(as_array=True))\n",
+    "genome_windows = list(range(0, int(ts.sequence_length+1), 20_000))  # or `np.linspace(0, ts.sequence_length, 51)`\n",
+    "windowed_diversity = ts.diversity(windows=genome_windows)\n",
+    "plt.stairs(windowed_diversity, genome_windows)\n",
     "plt.ylabel(\"Genetic diversity (π)\")\n",
     "plt.xlabel(\"Genome position (bp)\")\n",
-    "plt.title(\"Diversity along the genome\");"
+    "plt.title(\"Diversity along the genome\");\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "981b617f-8de5-4766-81ac-cac0f22a371c",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -625,31 +831,217 @@
     }
    ],
    "source": [
-    "# Calculate the first 2 principle components\n",
-    "pca_output = ts.pca(2, mode=\"branch\", random_seed=42)\n",
+    "# Calculate the first 2 principle components for every haploid genome\n",
+    "# For a more conventional PCA of diploid individuals, use the `individuals` argument)\n",
     "\n",
-    "# Plot the PCA\n",
-    "for population in ts.populations():\n",
-    "    use = ts.samples(population=population.id)\n",
-    "    plt.scatter(*pca_output.factors[use, :].T, label=population.metadata[\"name\"])\n",
+    "pca_output = ts.pca(2, mode=\"branch\", random_seed=42)  # or add `individuals=range(ts.num_individuals)`\n",
     "\n",
+    "# Plot the PCA\n",
+    "for pop in ts.populations():\n",
+    "    use = ts.samples(population=pop.id)  # `use = ts.individual_populations == pop.id` if using individuals\n",
+    "    if use.any():\n",
+    "        plt.scatter(*pca_output.factors[use, :].T, label=f'Population {pop.metadata[\"name\"]}')\n",
     "plt.xlabel(\"PCA 1\")\n",
-    "plt.ylabel(\"PCA 1\")\n",
+    "plt.ylabel(\"PCA 2\")\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e431618b-68be-4142-8af5-c0cc5b5c6593",
+   "metadata": {},
+   "source": [
+    "_Tskit_ has built-in tools for calculating coalescence and cross-coalescence rates. Below you can see that there is no coalescence between populations A and B more recently than 250 generations ago, suggesting populations A and B split around this time, whereas C and D probably split more recently, about 200 generations ago. This could partially explain why points from C and D partially overlapping on the PCA plot above.\n",
+    "\n",
+    "Note that the \"inverse instantaneous coalescence rate\" (IICR) is sometimes known as the effective population size or $N_e$, which is often used in population genetics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d1ee91c9-3eba-41dc-9a74-03b202405c86",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "num_timebins = 20 \n",
+    "time_breaks = np.concatenate(( # NB: first bin must start at sample time & last at infinity\n",
+    "    [0], np.logspace(np.log10(35), np.log10(ts.max_time/2), num_timebins - 2), [np.inf]\n",
+    "))\n",
+    "\n",
+    "all_rates = ts.pair_coalescence_rates(time_windows=time_breaks)\n",
+    "plt.stairs(all_rates[1:-1], time_breaks[1:-1], label=\"All coalescences\")\n",
+    "\n",
+    "# Now calculate some cross coalescences\n",
+    "samples = {pop.metadata[\"name\"]: ts.samples(pop.id) for pop in ts.populations()}\n",
+    "cross_AB_rates = ts.pair_coalescence_rates(sample_sets=[samples[\"A\"], samples[\"B\"]], time_windows=time_breaks)\n",
+    "cross_CD_rates = ts.pair_coalescence_rates(sample_sets=[samples[\"C\"], samples[\"D\"]], time_windows=time_breaks)\n",
+    "plt.stairs(cross_AB_rates[1:-1], time_breaks[1:-1], label=\"A/B cross coalescences\")\n",
+    "plt.stairs(cross_CD_rates[1:-1], time_breaks[1:-1], label=\"C/D cross coalescences\")\n",
+    "\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(f\"Time ({ts.time_units})\")\n",
+    "plt.ylabel(f\"Genome-wide instantaneous coalescence rate\")\n",
     "plt.legend();"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "93a395f2-2fdb-4f2d-b9a0-a763510b79dc",
+   "metadata": {},
+   "source": [
+    "Like all other tskit statistics, we can window coalescence rates along the genome. Below you can see a burst of coalescence (red) at about 170 generations ago around 0.3Mb along the genome, with an absence of coalescence information (grey) within that population at more distant times for that genomic region. This is indicative of a selective sweep at that genomic location (particularly clear because of the cleanliness of simulated data)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "deaa639c-b4d6-460a-a1c0-c8416eb38d50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "time_breaks = np.concatenate(( # NB: first bin must start at sample time & last at infinity\n",
+    "    [0], np.logspace(np.log10(35), np.log10(ts.max_time/10), num_timebins - 2), [np.inf]\n",
+    "))\n",
+    "\n",
+    "popA_rates = ts.pair_coalescence_rates(time_windows=time_breaks, windows=genome_windows, sample_sets=[samples[\"A\"]])\n",
+    "colourmap = plt.get_cmap('jet')\n",
+    "colourmap.set_bad(color='grey')\n",
+    "im = plt.pcolormesh(genome_windows, time_breaks[1:-1], popA_rates[:,1:-1].T, cmap=colourmap)\n",
+    "bar = plt.colorbar(im)\n",
+    "bar.ax.set_ylabel('pairwise coalescent density', labelpad=10, rotation=270)\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(f\"Genome position\")\n",
+    "plt.text(0, 170, \"170\\ngens\", ha=\"right\", va=\"center\", c=\"darkred\")\n",
+    "plt.ylabel(f\"Time ({ts.time_units})\")\n",
+    "plt.title(\"Local coalescence densities for population A\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6de5e1d0-2e10-4a71-a1ae-6c90bed6c103",
+   "metadata": {},
+   "source": [
+    "## Tree plotting\n",
+    "\n",
+    "_Tskit_ records ancestral trees along the genome. These can be easily plotted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "904b74ab-8fd2-4d52-8e18-5371e4ead31a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
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class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab rgt\" transform=\"translate(3 -7)\"/></g><path class=\"edge e5826\" d=\"M 0 0 V -11.7185 H -125.544\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab rgt\" transform=\"translate(3 -7)\"/></g><path class=\"edge e5914\" d=\"M 0 0 V -10.9789 H 169.869\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e6198\" d=\"M 0 0 V -33.3536 H 114.934\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e6204\" d=\"M 0 0 V -1.41758 H 133.639\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab\" transform=\"translate(0 -11)\"/></g></g></g><g class=\"title\" transform=\"translate(500 0)\"><text dominant-baseline=\"hanging\" text-anchor=\"middle\">Tree at genome position 0</text></g></svg>'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "first_tree = ts.first()\n",
+    "first_tree.draw_svg(size=(1000, 250), title=\"Tree at genome position 0\", node_labels={})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ccd74ad8-76dc-4836-b3e0-dd3669cc78ba",
+   "metadata": {},
+   "source": [
+    "_Tskit_ tree plots can be decorated using a variety of styles (see the [viz tutorial](https://tskit.dev/tutorials/viz.html)). Here we plot the tree at position 0.3 Mb, to see population A really does have a cluster of coalescences around 170 generations ago (at the dotted magenta line: it does!)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "b81ab065-37bd-41f7-9ed5-2b9c34d4e54a",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
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transform=\"translate(0 11)\"/></g><g class=\"a87 i28 leaf node n57 p2 sample\" transform=\"translate(5.77 0.865694)\"><path class=\"edge e15\" d=\"M 0 0 V -0.865694 H -5.77\"/><rect class=\"sym\" height=\"6\" width=\"6\" x=\"-3\" y=\"-3\"/><text class=\"lab\" transform=\"translate(0 11)\"/></g><path class=\"edge e233\" d=\"M 0 0 V -3.17964 H 8.655\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e1971\" d=\"M 0 0 V -16.7861 H 17.31\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e2282\" d=\"M 0 0 V -1.94473 H 18.7525\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e4449\" d=\"M 0 0 V -19.8849 H -60.3145\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab rgt\" transform=\"translate(3 -7)\"/></g><path class=\"edge e5831\" d=\"M 0 0 V -44.6709 H 45.3035\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab lft\" transform=\"translate(-3 -7)\"/></g><path class=\"edge e6089\" d=\"M 0 0 V -24.1999 H -122.68\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab rgt\" transform=\"translate(3 -7)\"/></g><path class=\"edge e6505\" d=\"M 0 0 V -63.0683 H -128.695\"/><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab rgt\" transform=\"translate(3 -7)\"/></g><circle class=\"sym\" cx=\"0\" cy=\"0\" r=\"3\"/><text class=\"lab\" transform=\"translate(0 -11)\"/></g></g></g><g class=\"title\" transform=\"translate(500 0)\"><text dominant-baseline=\"hanging\" text-anchor=\"middle\">Tree at genome position 300,000 bp</text></g></svg>'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from matplotlib import colors\n",
+    "styles = [f\".leaf.p{p.id}>.sym\" + \"{fill:\" + colors.to_hex(f\"C{p.id}\") + \"}\" for p in ts.populations()]\n",
+    "\n",
+    "legend = '<rect width=\"100\" height=\"100\" x=\"100\" y=\"10\" fill=\"#EEE\" /><text x=\"140\" y=\"25\">Key</text>'\n",
+    "legend += \"\".join([  # The legend lines, one for each population.\n",
+    "    f'<g transform=\"translate(103, {40 + 18*p.id})\" class=\"leaf p{p.id}\">'  # an SVG group\n",
+    "    f'<rect width=\"6\" height=\"6\" class=\"sym\" />'  # Square symbol\n",
+    "    f'<text x=\"10\" y=\"7\">Population {p.metadata[\"name\"]}</text></g>'  # Label\n",
+    "    for p in ts.populations() if len(ts.samples(p.id)) > 0\n",
+    "])\n",
+    "\n",
+    "ts.at(0.3e6).draw_svg(\n",
+    "    size=(1000, 250),\n",
+    "    node_labels={},    # Remove all node labels for a clearer viz\n",
+    "    mutation_labels={},\n",
+    "    style=\"\".join(styles) + \".y-axis .tick:nth-child(2) .grid {stroke: magenta; stroke-dasharray: 4}\",\n",
+    "    preamble=legend,\n",
+    "    y_axis=True,\n",
+    "    y_gridlines=True,\n",
+    "    y_ticks=[0, 170, 500, 1000, 1500],\n",
+    "    title=\"Tree at genome position 300,000 bp\",\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "39364361-7095-4029-8cc0-f4b825fd307f",
    "metadata": {},
    "source": [
     "## Other analyses\n",
-    "This notebook is fully interactive. Feel free to run other analysis below. Tutorial material is avaiable at https://tskit.dev/tutorials/."
+    "This notebook is fully interactive. Feel free to run other analysis below. Tutorial material is avaiable at https://tskit.dev/tutorials/, and there are also other notebooks in this JupyterLite instance: View -> File Browser will reveal them on the right if they are not shown."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 12,
    "id": "0460fee3-4520-4827-9d63-fafdc491a78b",
    "metadata": {},
    "outputs": [],