fix(plotnine): address review feedback for column-stratigraphic

Attempt 3/3 - fixes based on AI review

Author: github-actions[bot]

plots/column-stratigraphic/implementations/plotnine.py

@@ -1,4 +1,4 @@
-""" pyplots.ai
+"""pyplots.ai
 column-stratigraphic: Stratigraphic Column with Lithology Patterns
 Library: plotnine 0.15.3 | Python 3.14.3
 Quality: 86/100 | Created: 2026-03-15
@@ -85,45 +85,50 @@
 col_left = 0.0
 col_right = 4.0
 
-# Lithology colors - improved contrast (Shale lighter gray, Mudstone warm brown)
+# Lithology colors - enhanced contrast, colorblind-friendly palette
 lith_colors = {
-    "Sandstone": "#F5D76E",
-    "Shale": "#A8A8A8",
-    "Limestone": "#6DAEDB",
-    "Siltstone": "#C8DCC0",
+    "Sandstone": "#EEC946",
+    "Shale": "#B0B0B0",
+    "Limestone": "#5A9BD5",
+    "Siltstone": "#7EBF8E",
     "Conglomerate": "#D4785C",
     "Mudstone": "#8B6914",
 }
 
 # Unconformity depth (J/K boundary between Kootenai Fm and Morrison Fm)
 unconformity_depth = 95.0
 
-# Generate pattern overlay data for each lithology
-pattern_rows = []
+# Generate pattern overlay data with helper functions to reduce verbosity
 np.random.seed(42)
+pattern_rows = []
+
+
+def _add_random_points(rows, top_val, bot_val, lith, n, ptype, x_pad=0.3, y_pad=0.5):
+    xs = np.random.uniform(col_left + x_pad, col_right - x_pad, n)
+    ys = np.random.uniform(top_val + y_pad, bot_val - y_pad, n)
+    for px, py in zip(xs, ys, strict=True):
+        rows.append({"x": px, "y": py, "xend": px, "yend": py, "ptype": ptype, "lithology": lith})
+
+
+def _add_horiz_dashes(rows, top_val, bot_val, lith, spacing, ptype, dash_len=0.5, x_step=0.8):
+    y_pos = top_val + spacing * 0.4
+    while y_pos < bot_val - 0.3:
+        for x_start in np.arange(col_left + 0.3, col_right - 0.3, x_step):
+            rows.append(
+                {"x": x_start, "y": y_pos, "xend": x_start + dash_len, "yend": y_pos, "ptype": ptype, "lithology": lith}
+            )
+        y_pos += spacing
+
 
 for _, row in layers.iterrows():
-    top_val = row["top"]
-    bot_val = row["bottom"]
-    lith = row["lithology"]
+    top_val, bot_val, lith = row["top"], row["bottom"], row["lithology"]
     thickness = bot_val - top_val
 
     if lith == "Sandstone":
-        n_dots = int(thickness * 4)
-        for _ in range(n_dots):
-            px = np.random.uniform(col_left + 0.3, col_right - 0.3)
-            py = np.random.uniform(top_val + 0.5, bot_val - 0.5)
-            pattern_rows.append({"x": px, "y": py, "xend": px, "yend": py, "ptype": "dot", "lithology": lith})
+        _add_random_points(pattern_rows, top_val, bot_val, lith, int(thickness * 5), "dot")
 
     elif lith == "Shale":
-        spacing = 2.5
-        y_pos = top_val + 1.0
-        while y_pos < bot_val - 0.5:
-            for x_start in np.arange(col_left + 0.3, col_right - 0.5, 0.8):
-                pattern_rows.append(
-                    {"x": x_start, "y": y_pos, "xend": x_start + 0.5, "yend": y_pos, "ptype": "dash", "lithology": lith}
-                )
-            y_pos += spacing
+        _add_horiz_dashes(pattern_rows, top_val, bot_val, lith, spacing=2.5, ptype="dash", dash_len=0.5, x_step=0.8)
 
     elif lith == "Limestone":
         spacing = 4.0
@@ -150,38 +155,22 @@
             row_idx += 1
 
     elif lith == "Siltstone":
-        n_dashes = int(thickness * 6)
-        for _ in range(n_dashes):
-            px = np.random.uniform(col_left + 0.3, col_right - 0.3)
-            py = np.random.uniform(top_val + 0.5, bot_val - 0.5)
-            dx = np.random.uniform(-0.15, 0.15)
+        n_dashes = int(thickness * 8)
+        xs = np.random.uniform(col_left + 0.3, col_right - 0.3, n_dashes)
+        ys = np.random.uniform(top_val + 0.5, bot_val - 0.5, n_dashes)
+        dxs = np.random.uniform(-0.2, 0.2, n_dashes)
+        for px, py, dx in zip(xs, ys, dxs, strict=True):
             pattern_rows.append(
-                {"x": px, "y": py, "xend": px + dx, "yend": py + 0.2, "ptype": "short_dash", "lithology": lith}
+                {"x": px, "y": py, "xend": px + dx, "yend": py + 0.3, "ptype": "short_dash", "lithology": lith}
             )
 
     elif lith == "Conglomerate":
-        n_circles = int(thickness * 2)
-        for _ in range(n_circles):
-            px = np.random.uniform(col_left + 0.5, col_right - 0.5)
-            py = np.random.uniform(top_val + 1.0, bot_val - 1.0)
-            pattern_rows.append({"x": px, "y": py, "xend": px, "yend": py, "ptype": "circle", "lithology": lith})
+        _add_random_points(pattern_rows, top_val, bot_val, lith, int(thickness * 2.5), "circle", x_pad=0.5, y_pad=1.0)
 
     elif lith == "Mudstone":
-        spacing = 2.0
-        y_pos = top_val + 0.8
-        while y_pos < bot_val - 0.3:
-            for x_start in np.arange(col_left + 0.2, col_right - 0.3, 0.5):
-                pattern_rows.append(
-                    {
-                        "x": x_start,
-                        "y": y_pos,
-                        "xend": x_start + 0.25,
-                        "yend": y_pos,
-                        "ptype": "fine_dash",
-                        "lithology": lith,
-                    }
-                )
-            y_pos += spacing
+        _add_horiz_dashes(
+            pattern_rows, top_val, bot_val, lith, spacing=1.8, ptype="fine_dash", dash_len=0.25, x_step=0.5
+        )
 
 pattern_df = pd.DataFrame(pattern_rows)
 
@@ -210,7 +199,7 @@
 )
 
 # Unconformity wavy line data
-wavy_x = np.linspace(col_left, col_right, 40)
+wavy_x = np.linspace(col_left - 0.15, col_right + 0.15, 45)
 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:]})
 
@@ -221,32 +210,32 @@
     + geom_tile(
         data=layers,
         mapping=aes(x="x_center", y="mid", width=col_right - col_left, height="thickness", fill="lithology"),
-        color="#2C2C2C",
-        size=0.8,
-        alpha=0.6,
+        color="#3A3A3A",
+        size=0.9,
+        alpha=0.7,
     )
-    # Pattern overlays - line segments
+    # Pattern overlays - line segments (thicker for visibility)
     + geom_segment(
-        data=lines_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#2C2C2C", size=0.6, alpha=0.75
+        data=lines_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#2C2C2C", size=0.65, alpha=0.8
     )
     # Pattern overlays - stipple dots (sandstone)
-    + geom_point(data=dots_df, mapping=aes(x="x", y="y"), color="#2C2C2C", size=1.0, alpha=0.65)
+    + geom_point(data=dots_df, mapping=aes(x="x", y="y"), color="#2C2C2C", size=1.2, alpha=0.7)
     # Pattern overlays - open circles (conglomerate)
     + geom_point(
         data=circles_df,
         mapping=aes(x="x", y="y"),
         color="#2C2C2C",
         size=3.5,
-        alpha=0.55,
+        alpha=0.6,
         shape="o",
         fill="none",
         stroke=0.9,
     )
     # Layer boundary lines
-    + geom_segment(data=boundary_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#2C2C2C", size=0.8)
-    # Unconformity wavy line (red - focal point for data storytelling)
+    + geom_segment(data=boundary_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#3A3A3A", size=0.9)
+    # Unconformity wavy line (firebrick red - focal point for data storytelling)
     + geom_segment(
-        data=wavy_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#B22222", size=1.8, alpha=0.9
+        data=wavy_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color="#B22222", size=2.2, alpha=0.95
     )
     # Unconformity annotation
     + annotate(
@@ -255,38 +244,37 @@
         y=unconformity_depth,
         label="~ Unconformity ~",
         ha="left",
-        size=14,
+        size=15,
         color="#B22222",
         fontstyle="italic",
         fontweight="bold",
     )
     # Age bracket lines using geom_linerange (idiomatic plotnine for vertical ranges)
-    + geom_linerange(data=age_groups, mapping=aes(x="bracket_x", ymin="ymin", ymax="ymax"), color="#444444", size=0.8)
+    + geom_linerange(data=age_groups, mapping=aes(x="bracket_x", ymin="ymin", ymax="ymax"), color="#444444", size=0.9)
     # Formation labels using geom_label (plotnine-native styled text with background)
     + geom_label(
         data=form_groups,
         mapping=aes(x="x", y="mid", label="formation"),
         ha="left",
-        size=16,
+        size=17,
         fontstyle="italic",
         color="#1A1A1A",
-        fill="#FFFFFF",
-        alpha=0.7,
+        fill="#FFFFFFCC",
         label_padding=0.3,
-        label_size=0,
+        label_size=0.3,
     )
-    # Age labels (left side)
+    # Age labels (left side) - increased size for legibility
     + geom_text(
         data=age_groups,
         mapping=aes(x="x", y="mid", label="age"),
         ha="right",
-        size=15,
+        size=17,
         fontweight="bold",
-        color="#333333",
+        color="#2A2A2A",
     )
     # Scales - grammar-driven fill mapping with manual color values
     + scale_fill_manual(values=lith_colors, name="Lithology")
-    + scale_x_continuous(limits=(-4.5, 9.0), breaks=[])
+    + scale_x_continuous(limits=(-4.0, 8.5), breaks=[])
     + scale_y_continuous(trans="reverse", name="Depth (m)", breaks=list(range(0, 200, 20)))
     # Clipping for clean edges
     + coord_cartesian(ylim=(185, -5))
@@ -301,22 +289,22 @@
         plot_title=element_text(size=26, face="bold", ha="center"),
         axis_title_y=element_text(size=22),
         axis_title_x=element_blank(),
-        axis_text_y=element_text(size=18),
+        axis_text_y=element_text(size=18, color="#333333"),
         axis_text_x=element_blank(),
         axis_ticks_major_x=element_blank(),
         legend_title=element_text(size=18, face="bold"),
         legend_text=element_text(size=16),
         legend_position="bottom",
         legend_direction="horizontal",
         legend_key_size=22,
-        legend_background=element_rect(fill="#FAFAFA", color="#E0E0E0", size=0.3),
+        legend_background=element_rect(fill="#F5F5F5", color="#CCCCCC", size=0.4),
         legend_margin=10,
         panel_grid_major_x=element_blank(),
         panel_grid_minor_x=element_blank(),
-        panel_grid_major_y=element_line(color="#E0E0E0", size=0.3, alpha=0.4),
+        panel_grid_major_y=element_line(color="#D8D8D8", size=0.3, alpha=0.35),
         panel_grid_minor_y=element_blank(),
         panel_background=element_rect(fill="#FAFAFA", color="none"),
-        plot_background=element_rect(fill="white", color="none"),
+        plot_background=element_rect(fill="#FFFFFF", color="none"),
     )
 )