Displays the Ichimoku Kinko Hyo ("one glance equilibrium chart") overlay on a candlestick price chart. The indicator plots five lines — Tenkan-sen (conversion), Kijun-sen (base), Senkou Span A, Senkou Span B, and Chikou Span (lagging) — with the area between Senkou Span A and B filled as the "Kumo" (cloud). The cloud color changes depending on which span is on top, providing an at-a-glance view of trend direction, momentum, and support/resistance zones.
""" anyplot.ai
indicator-ichimoku: Ichimoku Cloud Technical Indicator Chart
Library: letsplot 4.10.1 | Python 3.13.13
Quality: 92/100 | Updated: 2026-06-08
"""
import os
import numpy as np
import pandas as pd
from lets_plot import *
LetsPlot.setup_html()
# 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"
# Imprint palette — semantic exception: profit/loss maps to green/red
BULL_COLOR = "#009E73" # Imprint green — bullish candles
BEAR_COLOR = "#AE3030" # Imprint matte red — bearish candles
TENKAN_COLOR = "#C475FD" # Imprint lavender (position 2) — Tenkan-sen
KIJUN_COLOR = "#4467A3" # Imprint blue (position 3) — Kijun-sen
CHIKOU_COLOR = "#BD8233" # Imprint ochre (position 4) — Chikou Span
SIGNAL_COLOR = "#DDCC77" # Imprint amber — TK Crossover signal marker
# Data — 200 trading days of simulated OHLC with Ichimoku components
np.random.seed(42)
n_days = 200
dates = pd.date_range(start="2024-01-02", periods=n_days, freq="B")
# Generate realistic OHLC via random walk
price = 150.0
opens, highs, lows, closes = [], [], [], []
for _ in range(n_days):
open_price = price
change = np.random.randn() * 2.5
close_price = open_price + change
high_price = max(open_price, close_price) + abs(np.random.randn()) * 1.5
low_price = min(open_price, close_price) - abs(np.random.randn()) * 1.5
opens.append(open_price)
closes.append(close_price)
highs.append(high_price)
lows.append(low_price)
price = close_price
df = pd.DataFrame({"date": dates, "open": opens, "high": highs, "low": lows, "close": closes})
# Compute Ichimoku components (standard parameters: 9, 26, 52)
high_s = df["high"]
low_s = df["low"]
tenkan_sen = (high_s.rolling(9).max() + low_s.rolling(9).min()) / 2
kijun_sen = (high_s.rolling(26).max() + low_s.rolling(26).min()) / 2
senkou_span_a = ((tenkan_sen + kijun_sen) / 2).shift(26)
senkou_span_b = ((high_s.rolling(52).max() + low_s.rolling(52).min()) / 2).shift(26)
chikou_span = df["close"].shift(-26)
df["tenkan_sen"] = tenkan_sen
df["kijun_sen"] = kijun_sen
df["senkou_span_a"] = senkou_span_a
df["senkou_span_b"] = senkou_span_b
df["chikou_span"] = chikou_span
# Numeric x-axis for precise candlestick positioning
df["x"] = range(len(df))
# Candlestick geometry columns
df["direction"] = np.where(df["close"] >= df["open"], "Bullish", "Bearish")
df["body_low"] = df[["open", "close"]].min(axis=1)
df["body_high"] = df[["open", "close"]].max(axis=1)
df["xmin"] = df["x"] - 0.35
df["xmax"] = df["x"] + 0.35
# Visible range (skip first 52 rows for full lookback)
visible_start = 52
df_visible = df.iloc[visible_start:].copy()
# Cloud data — split by bullish/bearish polarity for color-coded fill
df_cloud = df_visible.dropna(subset=["senkou_span_a", "senkou_span_b"]).copy()
df_cloud_bull = df_cloud[df_cloud["senkou_span_a"] >= df_cloud["senkou_span_b"]].copy()
df_cloud_bear = df_cloud[df_cloud["senkou_span_a"] < df_cloud["senkou_span_b"]].copy()
# Indicator line data (dropped NaN for clean line rendering)
df_tenkan = df_visible.dropna(subset=["tenkan_sen"]).copy()
df_kijun = df_visible.dropna(subset=["kijun_sen"]).copy()
df_chikou = df_visible.dropna(subset=["chikou_span"]).copy()
# X-axis ticks (every 20 trading days)
tick_pos = list(range(visible_start, len(df), 20))
tick_labels = [dates[i].strftime("%b %d") for i in tick_pos if i < len(dates)]
tick_pos = tick_pos[: len(tick_labels)]
# Tooltip columns
df_visible["date_str"] = df_visible["date"].dt.strftime("%b %d, %Y")
df_visible["change_pct"] = ((df_visible["close"] - df_visible["open"]) / df_visible["open"] * 100).round(2)
# Tenkan/Kijun crossover signal points
df_visible["tk_cross"] = (df_visible["tenkan_sen"] > df_visible["kijun_sen"]) != (
df_visible["tenkan_sen"].shift(1) > df_visible["kijun_sen"].shift(1)
)
df_crossovers = df_visible[df_visible["tk_cross"] & df_visible["tenkan_sen"].notna()].copy()
tip_fmt = (
layer_tooltips()
.title("@date_str")
.line("Open|$@{open}")
.line("High|$@{high}")
.line("Low|$@{low}")
.line("Close|$@{close}")
.line("Change|@{change_pct}%")
.format("open", ".2f")
.format("high", ".2f")
.format("low", ".2f")
.format("close", ".2f")
)
tenkan_tip = (
layer_tooltips()
.title("Tenkan-sen")
.line("Value|$@{tenkan_sen}")
.format("tenkan_sen", ".2f")
)
kijun_tip = (
layer_tooltips()
.title("Kijun-sen")
.line("Value|$@{kijun_sen}")
.format("kijun_sen", ".2f")
)
# Title (51 chars — under 67 baseline, default size=16)
title = "indicator-ichimoku · python · letsplot · anyplot.ai"
subtitle = "Ichimoku Kinko Hyo — Kumo shifts green→red as trend reverses mid-year; amber diamonds mark TK crossovers"
# Plot
plot = (
ggplot()
# Kumo cloud — bullish segment (green)
+ geom_ribbon(
aes(x="x", ymin="senkou_span_b", ymax="senkou_span_a"),
data=df_cloud_bull,
fill=BULL_COLOR,
alpha=0.15,
tooltips="none",
)
# Kumo cloud — bearish segment (red)
+ geom_ribbon(
aes(x="x", ymin="senkou_span_a", ymax="senkou_span_b"),
data=df_cloud_bear,
fill=BEAR_COLOR,
alpha=0.15,
tooltips="none",
)
# Senkou Span A boundary line
+ geom_line(
aes(x="x", y="senkou_span_a"),
data=df_cloud,
color=BULL_COLOR,
size=0.6,
alpha=0.5,
tooltips="none",
)
# Senkou Span B boundary line
+ geom_line(
aes(x="x", y="senkou_span_b"),
data=df_cloud,
color=BEAR_COLOR,
size=0.6,
alpha=0.5,
tooltips="none",
)
# Candlestick wicks
+ geom_segment(
aes(x="x", xend="x", y="low", yend="high", color="direction"),
data=df_visible,
size=0.7,
tooltips=tip_fmt,
)
# Candlestick bodies
+ geom_rect(
aes(xmin="xmin", xmax="xmax", ymin="body_low", ymax="body_high", fill="direction", color="direction"),
data=df_visible,
size=0.4,
tooltips=tip_fmt,
)
# Tenkan-sen (conversion line)
+ geom_line(
aes(x="x", y="tenkan_sen"),
data=df_tenkan,
color=TENKAN_COLOR,
size=1.2,
tooltips=tenkan_tip,
manual_key=layer_key("Tenkan-sen"),
)
# Kijun-sen (base line)
+ geom_line(
aes(x="x", y="kijun_sen"),
data=df_kijun,
color=KIJUN_COLOR,
size=1.2,
tooltips=kijun_tip,
manual_key=layer_key("Kijun-sen"),
)
# Chikou Span (lagging line — shifted 26 bars back)
+ geom_line(
aes(x="x", y="chikou_span"),
data=df_chikou,
color=CHIKOU_COLOR,
size=1.0,
alpha=0.85,
linetype="dashed",
tooltips="none",
manual_key=layer_key("Chikou Span"),
)
# TK Crossover signal markers
+ geom_point(
aes(x="x", y="tenkan_sen"),
data=df_crossovers,
color=SIGNAL_COLOR,
fill=SIGNAL_COLOR,
size=5,
shape=23,
stroke=1.5,
tooltips=layer_tooltips().title("TK Crossover").line("@date_str"),
manual_key=layer_key("TK Crossover"),
)
# Scales
+ scale_fill_manual(values={"Bullish": BULL_COLOR, "Bearish": BEAR_COLOR})
+ scale_color_manual(values={"Bullish": BULL_COLOR, "Bearish": BEAR_COLOR})
+ scale_x_continuous(breaks=tick_pos, labels=tick_labels, expand=[0.02, 0])
+ labs(x="Trading Day (2024)", y="Price ($)", title=title, subtitle=subtitle)
+ guides(fill="none", color="none")
+ theme_minimal()
+ theme(
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
panel_background=element_rect(fill=PAGE_BG),
axis_title=element_text(size=12, color=INK),
axis_text=element_text(size=10, color=INK_SOFT),
plot_title=element_text(size=16, color=INK, face="bold"),
plot_subtitle=element_text(size=11, color=INK_SOFT, face="italic"),
panel_grid_major_x=element_blank(),
panel_grid_major_y=element_line(color=INK, size=0.3),
panel_grid_minor=element_blank(),
axis_ticks=element_blank(),
legend_position=[0.05, 0.95],
legend_justification=[0.0, 1.0],
legend_title=element_text(size=10, face="bold", color=INK),
legend_text=element_text(size=10, color=INK_SOFT),
legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT, size=0.5),
)
+ ggsize(800, 450)
)
# Save
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)
ggsave(plot, f"plot-{THEME}.html", path=".")
Part of Ichimoku Cloud Technical Indicator Chart on anyplot.ai.