feat(altair): implement column-stratigraphic

Author: github-actions[bot]

plots/column-stratigraphic/implementations/altair.py

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+"""pyplots.ai
+column-stratigraphic: Stratigraphic Column with Lithology Patterns
+Library: altair | Python 3.13
+Quality: pending | Created: 2026-03-15
+"""
+
+import altair as alt
+import pandas as pd
+
+
+# Data: Synthetic sedimentary section with 10 layers
+layers = pd.DataFrame(
+    {
+        "top": [0, 15, 35, 55, 70, 90, 110, 135, 155, 175],
+        "bottom": [15, 35, 55, 70, 90, 110, 135, 155, 175, 200],
+        "lithology": [
+            "Sandstone",
+            "Shale",
+            "Limestone",
+            "Siltstone",
+            "Sandstone",
+            "Conglomerate",
+            "Shale",
+            "Limestone",
+            "Siltstone",
+            "Sandstone",
+        ],
+        "formation": [
+            "Cedar Mesa Fm",
+            "Organ Rock Fm",
+            "White Rim Fm",
+            "De Chelly Fm",
+            "Coconino Fm",
+            "Hermit Fm",
+            "Supai Group",
+            "Redwall Fm",
+            "Temple Butte Fm",
+            "Muav Fm",
+        ],
+        "age": [
+            "Permian",
+            "Permian",
+            "Permian",
+            "Permian",
+            "Permian",
+            "Permian",
+            "Pennsylvanian",
+            "Mississippian",
+            "Devonian",
+            "Cambrian",
+        ],
+    }
+)
+
+layers["thickness"] = layers["bottom"] - layers["top"]
+layers["mid_depth"] = (layers["top"] + layers["bottom"]) / 2
+
+# Lithology color palette (geologically conventional)
+lithology_colors = {
+    "Sandstone": "#F5D76E",
+    "Shale": "#7B8D8E",
+    "Limestone": "#5DADE2",
+    "Siltstone": "#A9CCE3",
+    "Conglomerate": "#E67E22",
+}
+
+lithology_order = ["Sandstone", "Shale", "Limestone", "Siltstone", "Conglomerate"]
+
+# Lithology pattern symbols for overlay
+pattern_map = {
+    "Sandstone": "· · ·",
+    "Shale": "— — —",
+    "Limestone": "▦ ▦ ▦",
+    "Siltstone": "– – –",
+    "Conglomerate": "○ ○ ○",
+}
+layers["pattern_label"] = layers["lithology"].map(pattern_map)
+
+# Identify unique age boundaries for left-side labels
+age_groups = []
+current_age = None
+for _, row in layers.iterrows():
+    if row["age"] != current_age:
+        current_age = row["age"]
+        group_rows = layers[layers["age"] == current_age]
+        age_groups.append(
+            {
+                "age": current_age,
+                "top": group_rows["top"].min(),
+                "bottom": group_rows["bottom"].max(),
+                "mid_depth": (group_rows["top"].min() + group_rows["bottom"].max()) / 2,
+            }
+        )
+age_df = pd.DataFrame(age_groups)
+
+# Layer rectangles
+rects = (
+    alt.Chart(layers)
+    .mark_rect(stroke="#333333", strokeWidth=2)
+    .encode(
+        y=alt.Y(
+            "top:Q",
+            title="Depth (m)",
+            scale=alt.Scale(domain=[0, 200]),
+            axis=alt.Axis(labelFontSize=18, titleFontSize=22),
+        ),
+        y2="bottom:Q",
+        x=alt.X("x:Q", scale=alt.Scale(domain=[0, 14]), axis=None),
+        x2="x2:Q",
+        color=alt.Color(
+            "lithology:N",
+            title="Lithology",
+            scale=alt.Scale(domain=lithology_order, range=[lithology_colors[k] for k in lithology_order]),
+            legend=alt.Legend(
+                titleFontSize=20,
+                labelFontSize=18,
+                symbolSize=400,
+                orient="bottom",
+                titlePadding=10,
+                direction="horizontal",
+                labelLimit=200,
+            ),
+        ),
+        tooltip=[
+            alt.Tooltip("formation:N", title="Formation"),
+            alt.Tooltip("lithology:N", title="Lithology"),
+            alt.Tooltip("age:N", title="Age"),
+            alt.Tooltip("top:Q", title="Top (m)"),
+            alt.Tooltip("bottom:Q", title="Bottom (m)"),
+            alt.Tooltip("thickness:Q", title="Thickness (m)"),
+        ],
+    )
+    .transform_calculate(x="2.5", x2="7.5")
+)
+
+# Pattern texture labels inside each layer
+pattern_text = (
+    alt.Chart(layers)
+    .mark_text(fontSize=16, color="#555555", opacity=0.6)
+    .encode(y=alt.Y("mid_depth:Q"), x=alt.X("x_mid:Q", scale=alt.Scale(domain=[0, 14])), text="pattern_label:N")
+    .transform_calculate(x_mid="5")
+)
+
+# Formation name labels to the right
+formation_labels = (
+    alt.Chart(layers)
+    .mark_text(fontSize=16, fontWeight="bold", align="left", color="#1a1a1a")
+    .encode(y=alt.Y("mid_depth:Q"), x=alt.X("x_pos:Q", scale=alt.Scale(domain=[0, 14])), text="formation:N")
+    .transform_calculate(x_pos="7.8")
+)
+
+# Age labels to the left
+age_labels = (
+    alt.Chart(age_df)
+    .mark_text(fontSize=15, fontStyle="italic", align="right", color="#444444")
+    .encode(y=alt.Y("mid_depth:Q"), x=alt.X("x_pos:Q", scale=alt.Scale(domain=[0, 14])), text="age:N")
+    .transform_calculate(x_pos="1.7")
+)
+
+# Age boundary lines
+age_boundaries = age_df[age_df["top"] > 0][["top"]].copy()
+age_boundaries["x1"] = 2.5
+age_boundaries["x2"] = 7.5
+
+age_rules = (
+    alt.Chart(age_boundaries)
+    .mark_rule(strokeDash=[8, 4], strokeWidth=1.5, color="#666666")
+    .encode(y=alt.Y("top:Q"), x=alt.X("x1:Q", scale=alt.Scale(domain=[0, 14])), x2="x2:Q")
+)
+
+# Combine all layers
+chart = (
+    (rects + pattern_text + formation_labels + age_labels + age_rules)
+    .properties(
+        width=1200,
+        height=900,
+        title=alt.Title(
+            "Stratigraphic Column · column-stratigraphic · altair · pyplots.ai", fontSize=26, anchor="middle", offset=20
+        ),
+    )
+    .configure_view(strokeWidth=0)
+)
+
+# Save
+chart.save("plot.png", scale_factor=3.0)
+chart.save("plot.html")