feat(letsplot): implement column-stratigraphic (#4917)

## Implementation: `column-stratigraphic` - letsplot

Implements the **letsplot** version of `column-stratigraphic`.

**File:** `plots/column-stratigraphic/implementations/letsplot.py`

**Parent Issue:** #4573

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23121198898)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/column-stratigraphic/implementations/letsplot.py

@@ -0,0 +1,303 @@
+""" pyplots.ai
+column-stratigraphic: Stratigraphic Column with Lithology Patterns
+Library: letsplot 4.9.0 | Python 3.14.3
+Quality: 88/100 | Created: 2026-03-15
+"""
+# ruff: noqa: F405
+
+import os
+import shutil
+
+import pandas as pd
+from lets_plot import *  # noqa: F403
+
+
+LetsPlot.setup_html()
+
+# Data - synthetic sedimentary section with 10 layers (depth increasing downward)
+layers = pd.DataFrame(
+    {
+        "top": [0, 15, 35, 55, 80, 110, 135, 165, 195, 230],
+        "bottom": [15, 35, 55, 80, 110, 135, 165, 195, 230, 260],
+        "lithology": [
+            "Sandstone",
+            "Shale",
+            "Limestone",
+            "Siltstone",
+            "Sandstone",
+            "Conglomerate",
+            "Shale",
+            "Limestone",
+            "Siltstone",
+            "Sandstone",
+        ],
+        "formation": [
+            "Basal Sand Fm",
+            "Dark Shale Mbr",
+            "Reef Limestone Fm",
+            "Gray Silt Mbr",
+            "Channel Sand Fm",
+            "Gravel Bed Fm",
+            "Marine Shale Fm",
+            "Platform Carb Fm",
+            "Tidal Flat Mbr",
+            "Upper Sand Fm",
+        ],
+        "age": [
+            "Triassic",
+            "Triassic",
+            "Jurassic",
+            "Jurassic",
+            "Jurassic",
+            "Cretaceous",
+            "Cretaceous",
+            "Cretaceous",
+            "Paleogene",
+            "Paleogene",
+        ],
+    }
+)
+
+layers["thickness"] = layers["bottom"] - layers["top"]
+layers["xmin"] = 0.0
+layers["xmax"] = 1.0
+
+# Lithology color palette (refined earth tones for geological context)
+lithology_colors = {
+    "Sandstone": "#F2D16B",
+    "Shale": "#8C8C8C",
+    "Limestone": "#6AAED6",
+    "Siltstone": "#C08C5A",
+    "Conglomerate": "#D06A62",
+}
+lithology_order = ["Sandstone", "Shale", "Limestone", "Siltstone", "Conglomerate"]
+
+# Generate lithology pattern overlay data
+pattern_segments = []  # For line-based patterns (shale dashes, limestone bricks)
+pattern_points = []  # For dot-based patterns (sandstone stipple, conglomerate circles)
+
+for _, row in layers.iterrows():
+    top, bottom, lith = row["top"], row["bottom"], row["lithology"]
+    thickness = bottom - top
+    margin = 0.03
+
+    if lith == "Shale":
+        # Horizontal dashes - denser pattern
+        spacing = 2.5
+        n_lines = max(1, int(thickness / spacing))
+        for i in range(n_lines):
+            y = top + (i + 0.5) * thickness / n_lines
+            for x_start in [0.04, 0.20, 0.36, 0.52, 0.68, 0.84]:
+                pattern_segments.append({"x": x_start, "y": y, "xend": x_start + 0.12, "yend": y})
+
+    elif lith == "Limestone":
+        # Brick pattern: horizontal lines + offset vertical lines - denser
+        spacing = 3.5
+        n_rows = max(1, int(thickness / spacing))
+        for i in range(n_rows + 1):
+            y = top + margin + i * (thickness - 2 * margin) / max(n_rows, 1)
+            if top + margin <= y <= bottom - margin:
+                pattern_segments.append({"x": 0.02, "y": y, "xend": 0.98, "yend": y})
+        for i in range(n_rows):
+            y_top = top + margin + i * (thickness - 2 * margin) / max(n_rows, 1)
+            y_bot = top + margin + (i + 1) * (thickness - 2 * margin) / max(n_rows, 1)
+            offset = 0.2 if i % 2 == 0 else 0.0
+            for vx in [0.2 + offset, 0.4 + offset, 0.6 + offset, 0.8 + offset]:
+                if 0.02 < vx < 0.98:
+                    pattern_segments.append({"x": vx, "y": y_top, "xend": vx, "yend": y_bot})
+
+    elif lith == "Sandstone":
+        # Stipple dots - denser grid
+        spacing_y = 2.8
+        spacing_x = 0.08
+        n_rows = max(1, int(thickness / spacing_y))
+        for i in range(n_rows):
+            y = top + (i + 0.5) * thickness / n_rows
+            offset = 0.04 if i % 2 == 0 else 0.0
+            x = 0.06 + offset
+            while x < 0.96:
+                pattern_points.append({"x": x, "y": y, "shape": "dot"})
+                x += spacing_x
+
+    elif lith == "Siltstone":
+        # Short tilted dashes - denser
+        spacing_y = 3.5
+        n_rows = max(1, int(thickness / spacing_y))
+        for i in range(n_rows):
+            y = top + (i + 0.5) * thickness / n_rows
+            offset = 0.06 if i % 2 == 0 else 0.0
+            for x in [0.08 + offset, 0.22 + offset, 0.36 + offset, 0.50 + offset, 0.64 + offset, 0.78 + offset]:
+                if x < 0.95:
+                    pattern_segments.append({"x": x, "y": y - 0.8, "xend": x + 0.06, "yend": y + 0.8})
+
+    elif lith == "Conglomerate":
+        # Circles (larger dots) - denser
+        spacing_y = 4.5
+        n_rows = max(1, int(thickness / spacing_y))
+        for i in range(n_rows):
+            y = top + (i + 0.5) * thickness / n_rows
+            offset = 0.08 if i % 2 == 0 else 0.0
+            for x in [0.12 + offset, 0.32 + offset, 0.52 + offset, 0.72 + offset]:
+                if x < 0.95:
+                    pattern_points.append({"x": x, "y": y, "shape": "circle"})
+
+pattern_seg_df = pd.DataFrame(pattern_segments) if pattern_segments else None
+pattern_dot_df = pd.DataFrame([p for p in pattern_points if p["shape"] == "dot"]) if pattern_points else None
+pattern_circle_df = pd.DataFrame([p for p in pattern_points if p["shape"] == "circle"]) if pattern_points else None
+
+# Formation labels (right side)
+form_labels = []
+for _, row in layers.iterrows():
+    mid_depth = (row["top"] + row["bottom"]) / 2
+    form_labels.append({"x": 1.08, "y": mid_depth, "label": row["formation"]})
+form_df = pd.DataFrame(form_labels)
+
+# Age labels (left side) with bracket indicators
+age_spans = {"Triassic": (0, 35), "Jurassic": (35, 110), "Cretaceous": (110, 195), "Paleogene": (195, 260)}
+age_labels = []
+age_brackets = []
+for age_name, (age_top, age_bottom) in age_spans.items():
+    age_labels.append({"x": -0.18, "y": (age_top + age_bottom) / 2, "label": age_name})
+    # Bracket lines on left
+    age_brackets.append({"x": -0.06, "y": age_top + 1, "xend": -0.06, "yend": age_bottom - 1})
+    age_brackets.append({"x": -0.06, "y": age_top + 1, "xend": -0.03, "yend": age_top + 1})
+    age_brackets.append({"x": -0.06, "y": age_bottom - 1, "xend": -0.03, "yend": age_bottom - 1})
+age_df = pd.DataFrame(age_labels)
+bracket_df = pd.DataFrame(age_brackets)
+
+# Unconformity wavy line at Jurassic/Cretaceous boundary (110m)
+wavy_x = []
+wavy_y = []
+n_waves = 20
+for i in range(n_waves + 1):
+    xi = i / n_waves
+    yi = 110 + 1.5 * (1 if (i % 2 == 0) else -1)
+    wavy_x.append(xi)
+    wavy_y.append(yi)
+wavy_df = pd.DataFrame({"x": wavy_x, "y": wavy_y})
+
+# Plot assembly
+plot = (
+    ggplot()
+    # Layer rectangles with interactive tooltips
+    + geom_rect(
+        aes(xmin="xmin", xmax="xmax", ymin="top", ymax="bottom", fill="lithology"),
+        data=layers,
+        color="#2C2C2C",
+        size=1.0,
+        alpha=0.8,
+        tooltips=layer_tooltips()
+        .format("@top", ".0f")
+        .format("@bottom", ".0f")
+        .format("@thickness", ".0f")
+        .title("@formation")
+        .line("@lithology | @age")
+        .line("Depth: @top\u2013@bottom m")
+        .line("Thickness: @thickness m"),
+    )
+)
+
+# Add pattern overlays
+if pattern_seg_df is not None and len(pattern_seg_df) > 0:
+    plot = plot + geom_segment(
+        aes(x="x", y="y", xend="xend", yend="yend"),
+        data=pattern_seg_df,
+        color="#2A2A2A",
+        size=0.6,
+        alpha=0.75,
+        show_legend=False,
+    )
+
+if pattern_dot_df is not None and len(pattern_dot_df) > 0:
+    plot = plot + geom_point(
+        aes(x="x", y="y"), data=pattern_dot_df, color="#4A3A10", size=1.8, alpha=0.7, shape=16, show_legend=False
+    )
+
+if pattern_circle_df is not None and len(pattern_circle_df) > 0:
+    plot = plot + geom_point(
+        aes(x="x", y="y"), data=pattern_circle_df, color="#5A2A2A", size=5.0, alpha=0.7, shape=1, show_legend=False
+    )
+
+# Unconformity wavy line at 110m with label
+plot = plot + geom_line(aes(x="x", y="y"), data=wavy_df, color="#C0392B", size=2.0, show_legend=False)
+unconformity_label = pd.DataFrame({"x": [1.08], "y": [110], "label": ["Unconformity"]})
+plot = plot + geom_text(
+    aes(x="x", y="y", label="label"),
+    data=unconformity_label,
+    color="#C0392B",
+    size=13,
+    fontface="bold",
+    hjust=0,
+    show_legend=False,
+)
+
+# Age boundary dashed lines (non-unconformity)
+non_unconformity_boundaries = pd.DataFrame(
+    {"x": [-0.02, -0.02], "y": [35, 195], "xend": [1.02, 1.02], "yend": [35, 195]}
+)
+plot = plot + geom_segment(
+    aes(x="x", y="y", xend="xend", yend="yend"),
+    data=non_unconformity_boundaries,
+    linetype="dashed",
+    color="#666666",
+    size=0.6,
+    show_legend=False,
+)
+
+# Age brackets (left side)
+plot = plot + geom_segment(
+    aes(x="x", y="y", xend="xend", yend="yend"), data=bracket_df, color="#444444", size=0.6, show_legend=False
+)
+
+# Formation labels (right side)
+plot = plot + geom_text(aes(x="x", y="y", label="label"), data=form_df, size=15, color="#2C2C2C", hjust=0)
+
+# Age labels (left side)
+plot = plot + geom_text(aes(x="x", y="y", label="label"), data=age_df, size=15, color="#2C2C2C", fontface="italic")
+
+# Scales and theme
+plot = (
+    plot
+    + scale_fill_manual(values=lithology_colors, name="Lithology", limits=lithology_order)
+    + scale_y_reverse()
+    + labs(
+        title="column-stratigraphic \u00b7 letsplot \u00b7 pyplots.ai",
+        subtitle="Synthetic Mesozoic\u2013Cenozoic sedimentary section \u00b7 Triassic to Paleogene",
+        y="Depth (m)",
+        x="",
+    )
+    + scale_x_continuous(limits=[-0.28, 1.52])
+    + flavor_high_contrast_light()
+    + theme(
+        plot_title=element_text(size=26, face="bold", color="#1A1A1A", margin=[0, 0, 12, 0]),
+        plot_subtitle=element_text(size=16, color="#666666", face="italic"),
+        axis_title_y=element_text(size=20, color="#333333", margin=[0, 8, 0, 0]),
+        axis_title_x=element_blank(),
+        axis_text_y=element_text(size=16, color="#444444"),
+        axis_text_x=element_blank(),
+        axis_ticks_x=element_blank(),
+        axis_line_y=element_line(size=0.8, color="#333333"),
+        legend_title=element_text(size=16, face="bold"),
+        legend_text=element_text(size=14),
+        legend_position="bottom",
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor_x=element_blank(),
+        panel_grid_major_y=element_line(size=0.2, color="#D8D8D8"),
+        panel_grid_minor_y=element_blank(),
+        plot_background=element_rect(color="white", fill="white"),
+        plot_margin=[16, 16, 16, 16],
+    )
+    + ggsize(1600, 900)
+)
+
+# Save
+ggsave(plot, "plot.png", scale=3)
+ggsave(plot, "plot.html")
+
+# Move files from lets-plot-images to current directory
+if os.path.exists("lets-plot-images/plot.png"):
+    shutil.move("lets-plot-images/plot.png", "plot.png")
+if os.path.exists("lets-plot-images/plot.html"):
+    shutil.move("lets-plot-images/plot.html", "plot.html")
+if os.path.exists("lets-plot-images") and not os.listdir("lets-plot-images"):
+    os.rmdir("lets-plot-images")