feat(plotnine): implement point-and-figure-basic (#7473)

## Implementation: `point-and-figure-basic` - python/plotnine

Implements the **python/plotnine** version of `point-and-figure-basic`.

**File:**
`plots/point-and-figure-basic/implementations/python/plotnine.py`

**Parent Issue:** #3755

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/26139439654)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>

Author: 3 people

plots/point-and-figure-basic/implementations/python/plotnine.py

@@ -1,18 +1,30 @@
-""" pyplots.ai
+""" anyplot.ai
 point-and-figure-basic: Point and Figure Chart
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 91/100 | Created: 2026-01-15
+Library: plotnine 0.15.4 | Python 3.13.13
+Quality: 83/100 | Updated: 2026-05-20
 """
 
+import os
+import sys
+
+
+# Work around filename shadowing the plotnine library
+sys.path.pop(0)
 import numpy as np
 import pandas as pd
 from plotnine import (
     aes,
+    coord_fixed,
     element_blank,
     element_line,
+    element_rect,
     element_text,
+    geom_point,
+    geom_segment,
     geom_text,
     ggplot,
+    guide_legend,
+    guides,
     labs,
     scale_color_manual,
     scale_y_continuous,
@@ -21,30 +33,35 @@
 )
 
 
-# Generate synthetic stock price data
+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"
+
+X_COLOR = "#009E73"  # Okabe-Ito position 1 - rising columns
+O_COLOR = "#D55E00"  # Okabe-Ito position 2 - falling columns (colorblind-safe vs pure red)
+
+# Data
 np.random.seed(42)
 n_days = 300
 
-# Create trending price movement with volatility
 returns = np.random.normal(0.001, 0.02, n_days)
-# Add some trend periods
-returns[50:100] += 0.005  # Uptrend
-returns[120:160] -= 0.008  # Downtrend
-returns[180:250] += 0.004  # Uptrend
+returns[50:100] += 0.005
+returns[120:160] -= 0.008
+returns[180:250] += 0.004
 
 price = 100 * np.cumprod(1 + returns)
 close = price
 
-# Point and Figure parameters
-box_size = 2.0  # Each box represents $2 price movement
-reversal = 3  # 3-box reversal
+box_size = 2.0
+reversal = 3
 
 # Build Point and Figure data
-pf_data = []  # List of (column_index, price_level, direction)
-current_direction = None  # 'X' (up) or 'O' (down)
+pf_data = []
+current_direction = None
 current_column = 0
 
-# Initialize with first price (quantize to box level)
 start_box = int(np.floor(close[0] / box_size))
 current_high_box = start_box
 current_low_box = start_box
@@ -53,7 +70,6 @@
     current_box = int(np.floor(close[i] / box_size))
 
     if current_direction is None:
-        # Determine initial direction
         if current_box > current_high_box:
             current_direction = "X"
             for b in range(current_low_box, current_box + 1):
@@ -66,73 +82,94 @@
             current_low_box = current_box
 
     elif current_direction == "X":
-        # Currently in an X (up) column
         if current_box > current_high_box:
-            # Continue up
             for b in range(current_high_box + 1, current_box + 1):
                 pf_data.append((current_column, b * box_size, "X"))
             current_high_box = current_box
         elif current_box <= current_high_box - reversal:
-            # Reversal - start O column
             current_column += 1
             current_direction = "O"
             current_low_box = current_box
             for b in range(current_box, current_high_box):
                 pf_data.append((current_column, b * box_size, "O"))
 
     elif current_direction == "O":
-        # Currently in an O (down) column
         if current_box < current_low_box:
-            # Continue down
             for b in range(current_box, current_low_box):
                 pf_data.append((current_column, b * box_size, "O"))
             current_low_box = current_box
         elif current_box >= current_low_box + reversal:
-            # Reversal - start X column
             current_column += 1
             current_direction = "X"
             current_high_box = current_box
             for b in range(current_low_box + 1, current_box + 1):
                 pf_data.append((current_column, b * box_size, "X"))
 
-# Create DataFrame for plotting
 df = pd.DataFrame(pf_data, columns=["column", "price", "symbol"])
+# Use full label text as the color aesthetic value to avoid plotnine legend prefix bug
+df["direction"] = pd.Categorical(
+    df["symbol"].map({"X": "Rising (X)", "O": "Falling (O)"}), categories=["Rising (X)", "Falling (O)"]
+)
 
-# Map symbols to display characters
-df["display"] = df["symbol"].map({"X": "X", "O": "O"})
+# 45-degree support and resistance trend lines (one box per column)
+min_idx = df["price"].idxmin()
+max_idx = df["price"].idxmax()
+max_col = float(df["column"].max())
+support_col = float(df.loc[min_idx, "column"])
+support_price = float(df.loc[min_idx, "price"])
+resist_col = float(df.loc[max_idx, "column"])
+resist_price = float(df.loc[max_idx, "price"])
+
+trend_lines = pd.DataFrame(
+    {
+        "x": [support_col, resist_col],
+        "y": [support_price, resist_price],
+        "xend": [max_col, max_col],
+        "yend": [support_price + (max_col - support_col) * box_size, resist_price - (max_col - resist_col) * box_size],
+    }
+)
 
-# Create plot
+# Plot
 plot = (
-    ggplot(df, aes(x="column", y="price", color="symbol", label="display"))
-    + geom_text(size=12, fontweight="bold")
-    + scale_color_manual(
-        values={"X": "#2E8B57", "O": "#DC143C"},  # Green for X, Red for O
-        labels={"X": "Rising (X)", "O": "Falling (O)"},
+    ggplot(df, aes(x="column", y="price"))
+    + geom_segment(
+        data=trend_lines,
+        mapping=aes(x="x", y="y", xend="xend", yend="yend"),
+        color=INK_SOFT,
+        size=0.6,
+        linetype="dashed",
+        alpha=0.7,
+        inherit_aes=False,
     )
+    + geom_text(mapping=aes(color="direction", label="symbol"), size=8, fontweight="bold", show_legend=False)
+    + geom_point(mapping=aes(color="direction"), size=0.01, alpha=0.01)
+    + coord_fixed(ratio=box_size)
+    + scale_color_manual(values={"Rising (X)": X_COLOR, "Falling (O)": O_COLOR}, name="Direction")
+    + guides(color=guide_legend(override_aes={"size": 3, "alpha": 1}))
     + scale_y_continuous(
         breaks=np.arange(
             int(df["price"].min() / box_size) * box_size, int(df["price"].max() / box_size + 2) * box_size, box_size * 2
         )
     )
-    + labs(
-        x="Column (Reversals)",
-        y="Price Level ($)",
-        title="point-and-figure-basic · plotnine · pyplots.ai",
-        color="Direction",
-    )
+    + labs(x="Column (Reversals)", y="Price Level ($)", title="point-and-figure-basic · python · plotnine · anyplot.ai")
     + theme_minimal()
     + theme(
-        figure_size=(16, 9),
-        text=element_text(size=14),
-        axis_title=element_text(size=20),
-        axis_text=element_text(size=16),
-        plot_title=element_text(size=24),
-        legend_text=element_text(size=16),
-        legend_title=element_text(size=18),
+        figure_size=(6, 6),
+        text=element_text(size=7, color=INK),
+        axis_title=element_text(size=10, color=INK),
+        axis_text=element_text(size=8, color=INK_SOFT),
+        plot_title=element_text(size=12, color=INK),
+        legend_text=element_text(size=8, color=INK_SOFT),
+        legend_title=element_text(size=9, color=INK),
+        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
+        panel_background=element_rect(fill=PAGE_BG),
+        legend_background=element_rect(fill=ELEVATED_BG, size=0),
+        panel_border=element_blank(),
+        axis_line=element_line(color=INK_SOFT, size=0.5),
         panel_grid_major_x=element_blank(),
         panel_grid_minor=element_blank(),
-        panel_grid_major_y=element_line(color="#cccccc", size=0.5, alpha=0.5),
+        panel_grid_major_y=element_line(color=INK, size=0.3, alpha=0.10),
     )
 )
 
-plot.save("plot.png", dpi=300)
+plot.save(f"plot-{THEME}.png", dpi=400, width=6, height=6, units="in")