A vertical column visualization showing geological rock layers with standardized lithology patterns, formation names, ages, and thickness scales. Each layer is represented as a stacked rectangular block filled with a distinctive pattern (e.g., brick pattern for limestone, dots for sandstone, dashes for shale) following FGDC/USGS conventions. This plot is essential for communicating subsurface geology and sedimentary sequences in a compact, standardized format.
""" anyplot.ai
column-stratigraphic: Stratigraphic Column with Lithology Patterns
Library: plotnine 0.15.7 | Python 3.13.13
Quality: 94/100 | Updated: 2026-06-17
"""
import os
import numpy as np
import pandas as pd
from plotnine import (
aes,
annotate,
coord_cartesian,
element_blank,
element_line,
element_rect,
element_text,
geom_label,
geom_linerange,
geom_point,
geom_segment,
geom_text,
geom_tile,
ggplot,
guide_legend,
guides,
labs,
scale_fill_manual,
scale_x_continuous,
scale_y_continuous,
theme,
theme_minimal,
)
# Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome")
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
# Data - synthetic sedimentary borehole section (Western US)
layers = pd.DataFrame(
{
"top": [0, 12, 28, 45, 58, 72, 95, 115, 138, 160],
"bottom": [12, 28, 45, 58, 72, 95, 115, 138, 160, 180],
"lithology": [
"Sandstone",
"Shale",
"Limestone",
"Siltstone",
"Sandstone",
"Conglomerate",
"Shale",
"Limestone",
"Mudstone",
"Sandstone",
],
"formation": [
"Frontier Fm",
"Frontier Fm",
"Madison Fm",
"Madison Fm",
"Kootenai Fm",
"Kootenai Fm",
"Morrison Fm",
"Morrison Fm",
"Sundance Fm",
"Sundance Fm",
],
"age": [
"Late Cretaceous",
"Late Cretaceous",
"Early Cretaceous",
"Early Cretaceous",
"Late Jurassic",
"Late Jurassic",
"Middle Jurassic",
"Middle Jurassic",
"Triassic",
"Triassic",
],
}
)
# Derived columns for grammar-of-graphics mapping
layers["mid"] = (layers["top"] + layers["bottom"]) / 2
layers["thickness"] = layers["bottom"] - layers["top"]
# Column geometry
col_left = 0.0
col_right = 3.5
layers["x_center"] = (col_left + col_right) / 2
# Lithology fills - Imprint palette (Sandstone = brand green, position 1).
# Position 5 (matte red #AE3030) is reserved for the unconformity focal point.
lith_colors = {
"Sandstone": "#009E73",
"Shale": "#C475FD",
"Limestone": "#4467A3",
"Siltstone": "#BD8233",
"Conglomerate": "#2ABCCD",
"Mudstone": "#954477",
}
# Unconformity depth (J/K boundary between Kootenai Fm and Morrison Fm)
unconformity_depth = 95.0
# Generate FGDC/USGS-style pattern overlays inline (flat KISS structure)
np.random.seed(42)
dot_rows = []
circle_rows = []
seg_rows = []
for _, row in layers.iterrows():
top_val, bot_val, lith = row["top"], row["bottom"], row["lithology"]
thickness = bot_val - top_val
if lith == "Sandstone": # stipple dots
n = int(thickness * 5)
xs = np.random.uniform(col_left + 0.3, col_right - 0.3, n)
ys = np.random.uniform(top_val + 0.5, bot_val - 0.5, n)
for px, py in zip(xs, ys, strict=True):
dot_rows.append({"x": px, "y": py})
elif lith == "Shale": # horizontal dashes
y_pos = top_val + 1.0
while y_pos < bot_val - 0.3:
for x_start in np.arange(col_left + 0.3, col_right - 0.3, 0.8):
seg_rows.append({"x": x_start, "y": y_pos, "xend": x_start + 0.45, "yend": y_pos})
y_pos += 2.5
elif lith == "Limestone": # brick (staggered horizontal + vertical lines)
y_pos = top_val + 2.0
ridx = 0
while y_pos < bot_val - 1.0:
seg_rows.append({"x": col_left + 0.2, "y": y_pos, "xend": col_right - 0.2, "yend": y_pos})
offset = 0.8 if ridx % 2 == 0 else 0.0
for vx in np.arange(col_left + 0.4 + offset, col_right - 0.3, 1.6):
seg_rows.append({"x": vx, "y": max(y_pos - 4.0, top_val + 0.2), "xend": vx, "yend": y_pos})
y_pos += 4.0
ridx += 1
elif lith == "Siltstone": # short random dashes
n = int(thickness * 8)
xs = np.random.uniform(col_left + 0.3, col_right - 0.3, n)
ys = np.random.uniform(top_val + 0.5, bot_val - 0.5, n)
dxs = np.random.uniform(-0.18, 0.18, n)
for px, py, dx in zip(xs, ys, dxs, strict=True):
seg_rows.append({"x": px, "y": py, "xend": px + dx, "yend": py + 0.3})
elif lith == "Conglomerate": # open clasts
n = int(thickness * 2.5)
xs = np.random.uniform(col_left + 0.5, col_right - 0.5, n)
ys = np.random.uniform(top_val + 1.0, bot_val - 1.0, n)
for px, py in zip(xs, ys, strict=True):
circle_rows.append({"x": px, "y": py})
elif lith == "Mudstone": # fine horizontal dashes
y_pos = top_val + 0.7
while y_pos < bot_val - 0.3:
for x_start in np.arange(col_left + 0.3, col_right - 0.3, 0.5):
seg_rows.append({"x": x_start, "y": y_pos, "xend": x_start + 0.22, "yend": y_pos})
y_pos += 1.8
dots_df = pd.DataFrame(dot_rows)
circles_df = pd.DataFrame(circle_rows)
lines_df = pd.DataFrame(seg_rows)
# Formation labels (one per formation, at its midpoint) on the right flank
form_groups = layers.groupby("formation", sort=False).agg({"top": "min", "bottom": "max"}).reset_index()
form_groups["mid"] = (form_groups["top"] + form_groups["bottom"]) / 2
form_groups["x"] = col_right + 0.3
# Age labels (one per age, at its midpoint) on the left flank with bracket lines
age_groups = layers.groupby("age", sort=False).agg({"top": "min", "bottom": "max"}).reset_index()
age_groups["mid"] = (age_groups["top"] + age_groups["bottom"]) / 2
age_groups["x"] = col_left - 0.55
age_groups["ymin"] = age_groups["top"] + 0.6
age_groups["ymax"] = age_groups["bottom"] - 0.6
age_groups["bracket_x"] = col_left - 0.25
# Layer boundary lines
boundaries = sorted(set(layers["top"].tolist() + layers["bottom"].tolist()))
boundary_df = pd.DataFrame(
{"x": [col_left] * len(boundaries), "xend": [col_right] * len(boundaries), "y": boundaries, "yend": boundaries}
)
# Unconformity wavy line
wavy_x = np.linspace(col_left - 0.15, col_right + 0.15, 60)
wavy_y = unconformity_depth + np.sin(wavy_x * 8) * 0.8
wavy_df = pd.DataFrame({"x": wavy_x[:-1], "y": wavy_y[:-1], "xend": wavy_x[1:], "yend": wavy_y[1:]})
# Build plot using plotnine grammar of graphics
plot = (
ggplot()
# Layer fills - grammar-driven aesthetic mapping
+ geom_tile(
data=layers,
mapping=aes(x="x_center", y="mid", width=col_right - col_left, height="thickness", fill="lithology"),
color=INK,
size=0.7,
alpha=0.62,
)
# Pattern overlays - line segments (dashes, brick, siltstone, mudstone)
+ geom_segment(data=lines_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color=INK, size=0.45, alpha=0.85)
# Pattern overlays - stipple dots (sandstone)
+ geom_point(data=dots_df, mapping=aes(x="x", y="y"), color=INK, size=0.9, alpha=0.8)
# Pattern overlays - open clasts (conglomerate)
+ geom_point(
data=circles_df, mapping=aes(x="x", y="y"), color=INK, size=2.6, alpha=0.7, shape="o", fill="none", stroke=0.8
)
# Layer boundary lines
+ geom_segment(data=boundary_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color=INK, size=0.7)
# Unconformity wavy line - Imprint matte red (#AE3030), the storytelling focal point
+ geom_segment(
data=wavy_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#AE3030", size=1.8, alpha=0.95
)
+ annotate(
"text",
x=col_right + 0.3,
y=unconformity_depth,
label="Unconformity",
ha="left",
size=4.2,
color="#AE3030",
fontstyle="italic",
fontweight="bold",
)
# Age bracket lines (idiomatic plotnine vertical ranges)
+ geom_linerange(data=age_groups, mapping=aes(x="bracket_x", ymin="ymin", ymax="ymax"), color=INK_SOFT, size=0.8)
# Formation labels (plotnine-native styled text with elevated background)
+ geom_label(
data=form_groups,
mapping=aes(x="x", y="mid", label="formation"),
ha="left",
size=3.7,
fontstyle="italic",
color=INK,
fill=ELEVATED_BG,
label_padding=0.28,
label_size=0.3,
)
# Age labels on the left flank
+ geom_text(
data=age_groups,
mapping=aes(x="x", y="mid", label="age"),
ha="right",
size=3.6,
fontweight="bold",
color=INK_SOFT,
)
# Scales - grammar-driven fill mapping
+ scale_fill_manual(values=lith_colors, name="Lithology")
+ scale_x_continuous(limits=(-3.6, 7.2), breaks=[])
+ scale_y_continuous(trans="reverse", name="Depth (m)", breaks=list(range(0, 200, 20)))
+ coord_cartesian(xlim=(-3.6, 7.2), ylim=(185, -5))
+ labs(title="column-stratigraphic · python · plotnine · anyplot.ai", x="")
+ guides(fill=guide_legend(nrow=2))
# Theme - theme-adaptive chrome over a 2400×2400 square canvas
+ theme_minimal()
+ theme(
figure_size=(6, 6),
plot_title=element_text(size=12, face="bold", ha="center", color=INK),
axis_title_y=element_text(size=11, color=INK),
axis_title_x=element_blank(),
axis_text_y=element_text(size=9, color=INK_SOFT),
axis_text_x=element_blank(),
axis_ticks_major_x=element_blank(),
legend_title=element_text(size=11, face="bold", color=INK),
legend_text=element_text(size=9, color=INK_SOFT),
legend_position="bottom",
legend_direction="horizontal",
legend_key_size=16,
legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT, size=0.4),
legend_margin=8,
panel_grid_major_x=element_blank(),
panel_grid_minor_x=element_blank(),
panel_grid_major_y=element_line(color=INK, size=0.3, alpha=0.12),
panel_grid_minor_y=element_blank(),
panel_background=element_rect(fill=PAGE_BG, color="none"),
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
)
)
# Save (square 2400×2400)
plot.save(f"plot-{THEME}.png", dpi=400, width=6, height=6, units="in")
Part of Stratigraphic Column with Lithology Patterns on anyplot.ai.