A wind barb plot displays wind speed and direction at specific locations using standard meteorological barb notation. Each barb consists of a staff pointing in the direction from which the wind blows, with short barbs (5 knots), long barbs (10 knots), and triangular pennants (50 knots) attached to indicate speed. This internationally recognized symbology enables rapid interpretation of wind patterns across weather maps and atmospheric data visualizations.
""" anyplot.ai
windbarb-basic: Wind Barb Plot for Meteorological Data
Library: altair 6.1.0 | Python 3.13.13
Quality: 86/100 | Updated: 2026-05-19
"""
import os
import altair as alt
import numpy as np
import pandas as pd
# Theme tokens
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"
BRAND = "#009E73" # Okabe-Ito position 1 — used for calm circles
# Data — synthetic wind observations from a 6×5 grid of weather stations
np.random.seed(42)
x_coords = np.linspace(0, 10, 6)
y_coords = np.linspace(0, 8, 5)
xx, yy = np.meshgrid(x_coords, y_coords)
x = xx.flatten()
y = yy.flatten()
u = np.random.uniform(-30, 30, len(x))
v = np.random.uniform(-25, 25, len(x))
# Force calm conditions and high-wind (pennant) cases for feature coverage
u[0], v[0] = 0.5, 0.3
u[5], v[5] = 1.0, -0.8
u[15], v[15] = 45.0, 35.0 # ~57 kt — one pennant + half barb
u[20], v[20] = 55.0, 10.0 # ~56 kt — one pennant + half barb
wind_speed = np.sqrt(u**2 + v**2)
wind_direction = np.degrees(np.arctan2(-u, -v)) % 360 # FROM direction (meteorological)
df = pd.DataFrame({"x": x, "y": y, "u": u, "v": v, "speed": wind_speed, "direction": wind_direction})
calm_df = df[df["speed"] < 2.5].copy()
barbed_df = df[df["speed"] >= 2.5].copy()
# Staff: line from station toward wind source
SCALE = 0.03
barbed_df = barbed_df.copy()
barbed_df["x2"] = barbed_df["x"] - barbed_df["u"] * SCALE
barbed_df["y2"] = barbed_df["y"] - barbed_df["v"] * SCALE
# Build barb segments and pennant markers per station
barb_records = []
pennant_records = []
for _, row in barbed_df.iterrows():
spd = row["speed"]
direction_rad = np.radians(row["direction"])
ux_s = np.sin(direction_rad) # unit vector toward wind source
uy_s = np.cos(direction_rad)
px_s = -uy_s # left-perpendicular (Northern Hemisphere convention)
py_s = ux_s
staff_len = spd * SCALE
remaining = spd
pos_offset = 0.0
num_pennants = int(remaining // 50)
for _ in range(min(num_pennants, 3)):
bpos = 0.85 - pos_offset
bx = row["x"] + ux_s * staff_len * bpos
by = row["y"] + uy_s * staff_len * bpos
pennant_records.append({"x": bx, "y": by, "angle": (row["direction"] + 270) % 360, "speed": spd})
pos_offset += 0.20
remaining -= num_pennants * 50
num_full = int(remaining // 10)
for _ in range(min(num_full, 5)):
bpos = 0.85 - pos_offset
bx = row["x"] + ux_s * staff_len * bpos
by = row["y"] + uy_s * staff_len * bpos
barb_records.append({"x": bx, "y": by, "x2": bx + px_s * 0.35, "y2": by + py_s * 0.35, "speed": spd})
pos_offset += 0.15
remaining -= num_full * 10
if remaining >= 5:
bpos = 0.85 - pos_offset
bx = row["x"] + ux_s * staff_len * bpos
by = row["y"] + uy_s * staff_len * bpos
barb_records.append({"x": bx, "y": by, "x2": bx + px_s * 0.18, "y2": by + py_s * 0.18, "speed": spd})
barb_df = pd.DataFrame(barb_records) if barb_records else pd.DataFrame(columns=["x", "y", "x2", "y2", "speed"])
pennant_df = pd.DataFrame(pennant_records) if pennant_records else pd.DataFrame(columns=["x", "y", "angle", "speed"])
# Continuous speed color encoding — cividis for CVD-safe sequential scale
speed_color = alt.Color(
"speed:Q",
scale=alt.Scale(scheme="cividis", domainMin=0, domainMax=60),
legend=alt.Legend(title="Wind Speed (kt)", orient="bottom-right"),
)
# Layer 1: Staff lines
staff = (
alt.Chart(barbed_df)
.mark_rule(strokeWidth=2.5)
.encode(
x=alt.X("x:Q", title="Longitude (°E)", scale=alt.Scale(domain=[-0.5, 11])),
y=alt.Y("y:Q", title="Latitude (°N)", scale=alt.Scale(domain=[-0.8, 9])),
x2="x2:Q",
y2="y2:Q",
color=speed_color,
tooltip=[
alt.Tooltip("x:Q", title="Longitude", format=".1f"),
alt.Tooltip("y:Q", title="Latitude", format=".1f"),
alt.Tooltip("speed:Q", title="Wind Speed (kt)", format=".1f"),
alt.Tooltip("direction:Q", title="Direction (° from N)", format=".0f"),
],
)
)
# Layer 2: Barb line segments (full and half barbs)
if len(barb_df) > 0:
barbs = (
alt.Chart(barb_df).mark_rule(strokeWidth=2.5).encode(x="x:Q", y="y:Q", x2="x2:Q", y2="y2:Q", color=speed_color)
)
else:
barbs = alt.Chart(pd.DataFrame({"x": []})).mark_point()
# Layer 3: Pennant markers — filled triangles oriented by wind direction
if len(pennant_df) > 0:
pennants = (
alt.Chart(pennant_df)
.mark_point(shape="triangle", filled=True, size=700)
.encode(
x="x:Q",
y="y:Q",
angle=alt.Angle("angle:Q", scale=alt.Scale(domain=[0, 360], range=[0, 360])),
color=speed_color,
)
)
else:
pennants = alt.Chart(pd.DataFrame({"x": []})).mark_point()
# Layer 4: Calm wind indicators — open circles (< 2.5 kt)
calm_circles = (
alt.Chart(calm_df)
.mark_point(shape="circle", filled=False, size=350, stroke=BRAND, strokeWidth=4)
.encode(
x="x:Q",
y="y:Q",
tooltip=[
alt.Tooltip("x:Q", title="Longitude", format=".1f"),
alt.Tooltip("y:Q", title="Latitude", format=".1f"),
alt.Tooltip("speed:Q", title="Wind Speed (kt)", format=".2f"),
],
)
)
# Chart assembly with theme-adaptive chrome
chart = (
alt.layer(staff, barbs, pennants, calm_circles)
.properties(
width=1600,
height=900,
background=PAGE_BG,
title=alt.Title(
text="windbarb-basic · python · altair · anyplot.ai",
subtitle="Half barb = 5 kt | Full barb = 10 kt | ▲ Pennant = 50 kt | ○ Calm < 2.5 kt",
),
)
.configure_view(fill=PAGE_BG, stroke="transparent")
.configure_axis(
domainColor=INK_SOFT,
tickColor=INK_SOFT,
gridColor=INK,
gridOpacity=0.10,
labelColor=INK_SOFT,
titleColor=INK,
labelFontSize=18,
titleFontSize=22,
)
.configure_title(color=INK, subtitleColor=INK_SOFT, fontSize=28, subtitleFontSize=20)
.configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
)
chart.save(f"plot-{THEME}.png", scale_factor=3.0)
chart.save(f"plot-{THEME}.html")
Part of Wind Barb Plot for Meteorological Data on anyplot.ai.