feat(pygal): implement quiver-basic (#5564)

## Implementation: `quiver-basic` - python/pygal

Implements the **python/pygal** version of `quiver-basic`.

**File:** `plots/quiver-basic/implementations/python/pygal.py`

**Parent Issue:** #1014

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/25137241599)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[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/quiver-basic/implementations/python/pygal.py

@@ -1,109 +1,118 @@
-""" pyplots.ai
+""" anyplot.ai
 quiver-basic: Basic Quiver Plot
-Library: pygal 3.1.0 | Python 3.13.11
-Quality: 82/100 | Created: 2025-12-23
+Library: pygal 3.1.0 | Python 3.13.13
+Quality: 77/100 | Updated: 2026-04-29
 """
 
+import importlib
+import os
+import sys
+
 import numpy as np
-import pygal
-from pygal.style import Style
 
 
-# Data - Wind flow pattern over a geographic area
-# Simulating wind vectors that flow around a central low-pressure system
+# Remove script dir so 'pygal' resolves to the installed package, not this file
+_d = os.path.abspath(os.path.dirname(__file__))
+sys.path = [p for p in sys.path if os.path.abspath(p) != _d]
+os.chdir(_d)
+
+pygal = importlib.import_module("pygal")
+Style = importlib.import_module("pygal.style").Style
+
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
+
+OKABE_ITO = ("#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#F0E442")
+
+# Data — counterclockwise wind rotation around a low-pressure centre (u=-y, v=x)
 np.random.seed(42)
-grid_size = 12
-x_range = np.linspace(-3, 3, grid_size)  # Longitude-like coordinates
-y_range = np.linspace(-3, 3, grid_size)  # Latitude-like coordinates
+grid_size = 8  # 8×8 = 64 arrows, well-spaced for discrete legibility
+x_range = np.linspace(-3, 3, grid_size)
+y_range = np.linspace(-3, 3, grid_size)
 X, Y = np.meshgrid(x_range, y_range)
 x_flat = X.flatten()
 y_flat = Y.flatten()
 
-# Circular rotation field simulating counterclockwise wind around low pressure
-# u = -y, v = x creates the rotation pattern
 U = -y_flat
 V = x_flat
-
-# Calculate magnitude - represents wind speed (stronger further from center)
 magnitude = np.sqrt(U**2 + V**2)
 max_mag = magnitude.max()
-
-# Normalize magnitude to 0-1 range for color mapping
 norm_mag = magnitude / max_mag
 
-# Scale vectors for visual clarity
-arrow_scale = 0.12
+arrow_scale = 0.22
 U_scaled = U * arrow_scale
 V_scaled = V * arrow_scale
 
-# Arrowhead parameters
-head_ratio = 0.4
+head_ratio = 0.40
 head_angle = 0.55
 
-# Color palette for magnitude bins (blue to orange to red, colorblind-friendly)
-# Low magnitude = blue/cyan, High magnitude = orange/red
-num_bins = 5
-bin_colors = ["#2269a4", "#32b9b0", "#e6a020", "#e65020", "#ff3232"]
-wind_labels = ["Calm", "Light", "Moderate", "Fresh", "Strong"]
-
-# Group arrows by magnitude ranges for color encoding
-arrow_groups = {i: [] for i in range(num_bins)}
+num_bins = 3
+wind_labels = ["Calm / Light", "Moderate", "Fresh / Strong"]
+bin_colors = OKABE_ITO[:num_bins]
 
+# Build each arrow as an isolated 9-item segment group, collected per bin
+arrow_bins = [[] for _ in range(num_bins)]
 for i in range(len(x_flat)):
-    # Skip very weak vectors (near center)
-    if magnitude[i] < 0.05:
+    if magnitude[i] < 0.01:
         continue
-
     x1, y1 = x_flat[i], y_flat[i]
     x2, y2 = x1 + U_scaled[i], y1 + V_scaled[i]
-
-    # Calculate arrowhead size based on arrow length
     arrow_len = np.sqrt(U_scaled[i] ** 2 + V_scaled[i] ** 2)
     head_size = arrow_len * head_ratio
-
-    # Calculate arrowhead points
     angle = np.arctan2(V_scaled[i], U_scaled[i])
-    x_left = x2 - head_size * np.cos(angle - head_angle)
-    y_left = y2 - head_size * np.sin(angle - head_angle)
-    x_right = x2 - head_size * np.cos(angle + head_angle)
-    y_right = y2 - head_size * np.sin(angle + head_angle)
-
-    # Determine which bin this arrow belongs to
+    xl = x2 - head_size * np.cos(angle - head_angle)
+    yl = y2 - head_size * np.sin(angle - head_angle)
+    xr = x2 - head_size * np.cos(angle + head_angle)
+    yr = y2 - head_size * np.sin(angle + head_angle)
     bin_idx = min(int(norm_mag[i] * num_bins), num_bins - 1)
+    # Each arrow = shaft + two barb segments, each terminated with None
+    arrow_bins[bin_idx].append([(x1, y1), (x2, y2), None, (x2, y2), (xl, yl), None, (x2, y2), (xr, yr), None])
 
-    # Build arrow segments (shaft + arrowhead)
-    arrow_groups[bin_idx].extend([(x1, y1), (x2, y2), None])
-    arrow_groups[bin_idx].extend([(x2, y2), (x_left, y_left), None])
-    arrow_groups[bin_idx].extend([(x2, y2), (x_right, y_right), None])
-
-# Custom style with larger fonts for readability
+# Shuffle arrow order within each bin to break the spatial row-order band patterns
+# that make consecutive arrows appear visually connected even with None breaks
+rng = np.random.RandomState(42)
+arrow_series = []
+for i in range(num_bins):
+    arrows = arrow_bins[i][:]
+    rng.shuffle(arrows)
+    flat = []
+    for arrow in arrows:
+        flat.extend(arrow)
+    arrow_series.append(flat)
+
+# Style
 custom_style = Style(
-    background="white",
-    plot_background="white",
-    foreground="#333333",
-    foreground_strong="#333333",
-    foreground_subtle="#555555",
-    colors=tuple(bin_colors),
-    title_font_size=72,
-    label_font_size=48,
-    major_label_font_size=40,
-    legend_font_size=56,
-    value_font_size=32,
-    guide_stroke_color="#dddddd",
+    background=PAGE_BG,
+    plot_background=PAGE_BG,
+    foreground=INK,
+    foreground_strong=INK,
+    foreground_subtle=INK_MUTED,
+    colors=bin_colors,
+    title_font_size=28,
+    label_font_size=22,
+    major_label_font_size=18,
+    legend_font_size=16,
+    value_font_size=14,
+    stroke_width=3,
 )
 
-# Create chart
+# Plot — thinner strokes (10 vs 20) + dot markers at each segment endpoint
+# clearly distinguish 64 discrete arrow positions rather than sweeping bands
 chart = pygal.XY(
     style=custom_style,
     width=4800,
     height=2700,
     stroke=True,
-    stroke_style={"width": 20},
-    show_dots=False,
+    stroke_style={"width": 10},
+    show_dots=True,
+    dot_size=4,
     show_legend=True,
     legend_at_bottom=True,
-    legend_at_bottom_columns=5,
-    title="quiver-basic · pygal · pyplots.ai",
+    legend_at_bottom_columns=3,
+    title="quiver-basic · pygal · anyplot.ai",
     x_title="Longitude (degrees)",
     y_title="Latitude (degrees)",
     show_x_guides=True,
@@ -112,11 +121,11 @@
     xrange=(-3.8, 3.8),
 )
 
-# Add each magnitude group as a separate series with its color
 for i in range(num_bins):
-    if arrow_groups[i]:
-        chart.add(wind_labels[i], arrow_groups[i])
+    if arrow_series[i]:
+        chart.add(wind_labels[i], arrow_series[i], allow_interruptions=True)
 
-# Save outputs
-chart.render_to_png("plot.png")
-chart.render_to_file("plot.html")
+# Save
+chart.render_to_png(f"plot-{THEME}.png")
+with open(f"plot-{THEME}.html", "wb") as f:
+    f.write(chart.render())