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feat(highcharts): implement heatmap-rainflow (#4482)
## Implementation: `heatmap-rainflow` - highcharts Implements the **highcharts** version of `heatmap-rainflow`. **File:** `plots/heatmap-rainflow/implementations/highcharts.py` **Parent Issue:** #4465 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/22595466105)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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‎plots/heatmap-rainflow/implementations/highcharts.py‎

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""" pyplots.ai
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heatmap-rainflow: Rainflow Counting Matrix for Fatigue Analysis
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Library: highcharts unknown | Python 3.14.3
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Quality: 90/100 | Updated: 2026-03-06
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"""
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import tempfile
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import time
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import urllib.request
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from pathlib import Path
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import numpy as np
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from highcharts_core.chart import Chart
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from highcharts_core.options import HighchartsOptions
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from selenium import webdriver
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from selenium.webdriver.chrome.options import Options
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# Data - Simulated rainflow counting matrix from variable-amplitude loading
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np.random.seed(42)
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n_amp_bins = 20
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n_mean_bins = 20
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# Bin centers in MPa
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amplitude_bins = np.linspace(10, 200, n_amp_bins)
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mean_bins = np.linspace(-50, 250, n_mean_bins)
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# Generate realistic rainflow matrix
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# Most cycles at low amplitude, centered around mean ~100 MPa
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amp_grid, mean_grid = np.meshgrid(amplitude_bins, mean_bins, indexing="ij")
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# Exponential decay with amplitude (low amplitude = many cycles)
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amp_factor = np.exp(-0.025 * amp_grid)
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# Gaussian distribution around mean ~100 MPa
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mean_factor = np.exp(-0.5 * ((mean_grid - 100) / 60) ** 2)
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# Combined cycle counts
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raw_counts = amp_factor * mean_factor * 5000
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raw_counts += np.random.exponential(scale=raw_counts * 0.15 + 1)
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cycle_counts = np.round(raw_counts).astype(int)
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cycle_counts = np.clip(cycle_counts, 0, None)
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# Set very low counts to zero for sparsity (realistic for high-amplitude regions)
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cycle_counts[cycle_counts < 3] = 0
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# Amplitude labels (y-axis) and mean labels (x-axis)
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amp_labels = [f"{v:.0f}" for v in amplitude_bins]
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mean_labels = [f"{v:.0f}" for v in mean_bins]
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# Build heatmap data: [x_index (mean), y_index (amplitude), value or None]
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heatmap_data = []
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max_count = 0
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for y_idx in range(n_amp_bins):
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for x_idx in range(n_mean_bins):
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val = int(cycle_counts[y_idx, x_idx])
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if val > max_count:
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max_count = val
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heatmap_data.append([x_idx, y_idx, val if val > 0 else None])
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# Build chart using highcharts-core Python wrapper
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chart = Chart(container="container")
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chart.options = HighchartsOptions.from_dict(
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{
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"chart": {
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"type": "heatmap",
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"width": 4800,
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"height": 2700,
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"backgroundColor": "#fafafa",
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"marginTop": 180,
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"marginBottom": 200,
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"marginRight": 380,
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"marginLeft": 320,
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"style": {"fontFamily": "'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif"},
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},
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"title": {
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"text": "heatmap-rainflow \u00b7 highcharts \u00b7 pyplots.ai",
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"style": {"fontSize": "52px", "fontWeight": "600", "color": "#2c3e50"},
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"y": 30,
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},
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"subtitle": {
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"text": "Rainflow cycle counting matrix \u2014 low-amplitude cycles near 100 MPa mean dominate the fatigue spectrum",
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"style": {"fontSize": "30px", "fontWeight": "normal", "color": "#7f8c8d"},
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"y": 80,
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},
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"xAxis": {
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"categories": mean_labels,
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"title": {
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"text": "Cycle Mean (MPa)",
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"style": {"fontSize": "34px", "fontWeight": "600", "color": "#34495e"},
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"margin": 20,
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},
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"labels": {"style": {"fontSize": "28px", "color": "#34495e"}, "rotation": 315, "y": 30},
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"lineWidth": 0,
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"tickLength": 0,
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},
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"yAxis": {
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"categories": amp_labels,
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"title": {
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"text": "Cycle Amplitude (MPa)",
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"style": {"fontSize": "34px", "fontWeight": "600", "color": "#34495e"},
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"margin": 20,
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},
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"labels": {"style": {"fontSize": "28px", "color": "#34495e"}},
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"reversed": False,
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"lineWidth": 0,
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"gridLineWidth": 0,
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},
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"colorAxis": {
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"min": 1,
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"max": int(max_count),
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"type": "logarithmic",
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"stops": [
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[0, "#440154"],
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[0.12, "#482878"],
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[0.25, "#3e4989"],
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[0.37, "#31688e"],
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[0.50, "#26828e"],
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[0.62, "#1f9e89"],
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[0.75, "#35b779"],
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[0.87, "#6ece58"],
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[1, "#fde725"],
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],
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"labels": {"style": {"fontSize": "28px", "color": "#34495e"}},
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},
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"legend": {
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"title": {"text": "Cycle Count", "style": {"fontSize": "28px", "fontWeight": "600", "color": "#34495e"}},
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"align": "right",
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"layout": "vertical",
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"verticalAlign": "middle",
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"symbolHeight": 900,
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"symbolWidth": 36,
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"itemStyle": {"fontSize": "24px", "color": "#34495e"},
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"x": -40,
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"margin": 40,
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},
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"tooltip": {
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"style": {"fontSize": "30px"},
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"headerFormat": "",
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"pointFormat": (
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"Amplitude: <b>{series.yAxis.categories.(point.y)} MPa</b><br>"
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"Mean: <b>{series.xAxis.categories.(point.x)} MPa</b><br>"
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"Cycles: <b>{point.value}</b>"
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),
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},
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"credits": {"enabled": False},
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"plotOptions": {"heatmap": {"colsize": 1, "rowsize": 1}},
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"series": [
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{
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"type": "heatmap",
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"name": "Cycle Count",
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"data": heatmap_data,
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"borderWidth": 2,
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"borderColor": "#fafafa",
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"nullColor": "#f0f0f0",
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}
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],
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}
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)
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# Generate chart JS literal via highcharts-core wrapper
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js_literal = chart.to_js_literal()
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# Download Highcharts JS and heatmap module with retry
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urls = {
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"highcharts": "https://cdn.jsdelivr.net/npm/highcharts/highcharts.js",
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"heatmap": "https://cdn.jsdelivr.net/npm/highcharts/modules/heatmap.js",
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}
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scripts = {}
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for name, url in urls.items():
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for attempt in range(3):
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try:
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with urllib.request.urlopen(url, timeout=30) as response:
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scripts[name] = response.read().decode("utf-8")
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break
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except urllib.error.HTTPError:
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time.sleep(2 * (attempt + 1))
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else:
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raise RuntimeError(f"Failed to download {url}")
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highcharts_js = scripts["highcharts"]
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heatmap_js = scripts["heatmap"]
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# Generate HTML with inline scripts and renderer annotation for data storytelling
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html_content = f"""<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<script>{highcharts_js}</script>
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<script>{heatmap_js}</script>
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</head>
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<body style="margin:0; padding:0; overflow:hidden; background:#fafafa;">
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<div id="container" style="width:4800px; height:2700px;"></div>
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<script>
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{js_literal}
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</script>
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<script>
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// Add annotation highlighting the dominant fatigue region
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// (separate DOMContentLoaded ensures chart is created first)
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document.addEventListener('DOMContentLoaded', function() {{
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var ch = Highcharts.charts[Highcharts.charts.length - 1];
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if (ch) {{
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ch.renderer.label(
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'\\u25B6 Peak region: low-amplitude cycles near<br>' +
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'\\u2003 100 MPa mean stress dominate fatigue damage',
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ch.plotLeft + ch.plotWidth * 0.55,
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ch.plotTop + ch.plotHeight * 0.78
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).css({{
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fontSize: '28px',
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color: '#333',
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fontStyle: 'italic',
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lineHeight: '40px'
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}}).attr({{
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fill: 'rgba(255, 255, 255, 0.93)',
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stroke: '#888',
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'stroke-width': 1.5,
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padding: 18,
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r: 8,
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zIndex: 5
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}}).add();
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}}
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}});
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</script>
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</body>
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</html>"""
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# Save HTML for interactive version
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with open("plot.html", "w", encoding="utf-8") as f:
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f.write(html_content)
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# Take screenshot using headless Chrome
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with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f:
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f.write(html_content)
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temp_path = f.name
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chrome_options = Options()
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chrome_options.add_argument("--headless=new")
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chrome_options.add_argument("--no-sandbox")
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chrome_options.add_argument("--disable-dev-shm-usage")
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chrome_options.add_argument("--disable-gpu")
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chrome_options.add_argument("--window-size=4800,2840")
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chrome_options.add_argument("--force-device-scale-factor=1")
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chrome_options.add_argument("--hide-scrollbars")
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driver = webdriver.Chrome(options=chrome_options)
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driver.set_window_size(4800, 2840)
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driver.get(f"file://{temp_path}")
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time.sleep(5)
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driver.save_screenshot("plot.png")
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driver.quit()
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Path(temp_path).unlink()

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