{"spec_id":"contour-map-geographic","library":"plotly","language":"python","code":"\"\"\" anyplot.ai\ncontour-map-geographic: Contour Lines on Geographic Map\nLibrary: plotly 6.7.0 | Python 3.13.13\nQuality: 84/100 | Updated: 2026-05-20\n\"\"\"\n\nimport os\nimport sys\n\n\n# Remove the script's own directory from sys.path so the sibling matplotlib.py\n# implementation file does not shadow the system matplotlib package.\n_here = os.path.dirname(os.path.abspath(__file__))\nsys.path = [p for p in sys.path if p and os.path.abspath(p) != _here]\n\nimport matplotlib\n\n\nmatplotlib.use(\"Agg\")\nimport matplotlib.colors as mcolors\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport plotly.graph_objects as go\n\n\n# Theme tokens\nTHEME = os.getenv(\"ANYPLOT_THEME\", \"light\")\nPAGE_BG = \"#FAF8F1\" if THEME == \"light\" else \"#1A1A17\"\nELEVATED_BG = \"#FFFDF6\" if THEME == \"light\" else \"#242420\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_SOFT = \"#4A4A44\" if THEME == \"light\" else \"#B8B7B0\"\nLAND_COLOR = \"#D8D3BB\" if THEME == \"light\" else \"#2A2A25\"\nOCEAN_BG = \"#C5D8E8\" if THEME == \"light\" else \"#19242E\"\nCOAST_COLOR = \"#888880\" if THEME == \"light\" else \"#666660\"\n\n# Data - Simulated North Atlantic SST\nnp.random.seed(42)\nlat_range = np.linspace(30, 60, 60)\nlon_range = np.linspace(-60, 0, 60)\nlon_grid, lat_grid = np.meshgrid(lon_range, lat_range)\n\nbase_temp = 20 - 0.5 * (lat_grid - 30)\ngulf_stream = 3 * np.exp(-((lon_grid + 30) ** 2) / 400)\nvariation = 2 * np.sin(lat_grid / 5) * np.cos(lon_grid / 8)\ntemperature = base_temp + gulf_stream + variation\n\nT_MIN, T_MAX = 4, 24\nlevels = np.arange(T_MIN, T_MAX + 1, 2)\n\n# Viridis colormap — perceptually-uniform, spec-compliant for sequential temperature data\nnorm = mcolors.Normalize(vmin=T_MIN, vmax=T_MAX)\ncmap = plt.get_cmap(\"viridis\")\n\n# Compute contour paths using matplotlib off-screen (allsegs API, matplotlib 3.8+)\n_fig, _ax = plt.subplots()\ncs_fill = _ax.contourf(lon_range, lat_range, temperature, levels=levels, cmap=cmap, norm=norm)\ncs_line = _ax.contour(lon_range, lat_range, temperature, levels=levels)\nplt.close(\"all\")\n\nfig = go.Figure()\n\n# Filled contour patches on the geographic map.\n# Plotly's fill='toself' fills the interior for polygons whose top edge touches\n# lat=60 (the data domain top), but fills the exterior for all other polygons.\n# Reversing the vertex order for non-top-touching polygons corrects the winding.\nfor i, segs in enumerate(cs_fill.allsegs):\n mid_val = (levels[i] + levels[i + 1]) / 2\n r, g, b, _ = cmap(norm(mid_val))\n fill_color = f\"rgba({int(r * 255)},{int(g * 255)},{int(b * 255)},0.85)\"\n for seg in segs:\n if len(seg) < 3:\n continue\n seg = seg[::-1] if seg[:, 1].max() < 59.9 else seg\n fig.add_trace(\n go.Scattergeo(\n lon=seg[:, 0].tolist(),\n lat=seg[:, 1].tolist(),\n mode=\"lines\",\n fill=\"toself\",\n fillcolor=fill_color,\n line=dict(width=0),\n showlegend=False,\n hoverinfo=\"skip\",\n )\n )\n\n# Contour isolines as Scattergeo line traces\nfor i, segs in enumerate(cs_line.allsegs):\n level_val = float(cs_line.levels[i])\n for seg in segs:\n if len(seg) < 2:\n continue\n fig.add_trace(\n go.Scattergeo(\n lon=seg[:, 0].tolist(),\n lat=seg[:, 1].tolist(),\n mode=\"lines\",\n line=dict(width=1, color=INK_SOFT),\n showlegend=False,\n hovertemplate=f\"{level_val:.0f}°C\",\n )\n )\n\n# Isoline value labels at midpoints of selected levels (every 4°C)\nlabel_levels = {8.0, 12.0, 16.0, 20.0}\nfor i, segs in enumerate(cs_line.allsegs):\n level_val = float(cs_line.levels[i])\n if level_val not in label_levels:\n continue\n for seg in segs:\n if len(seg) < 10:\n continue\n mid = len(seg) // 2\n fig.add_trace(\n go.Scattergeo(\n lon=[float(seg[mid, 0])],\n lat=[float(seg[mid, 1])],\n mode=\"text\",\n text=[f\"{level_val:.0f}°C\"],\n textfont=dict(size=9, color=INK),\n showlegend=False,\n hoverinfo=\"skip\",\n )\n )\n\n# Dummy trace for standalone colorbar\nfig.add_trace(\n go.Scattergeo(\n lon=[None],\n lat=[None],\n mode=\"markers\",\n marker=dict(\n color=[0],\n colorscale=\"viridis\",\n cmin=T_MIN,\n cmax=T_MAX,\n showscale=True,\n colorbar=dict(\n title=dict(text=\"Temperature (°C)\", font=dict(size=12, color=INK)),\n tickfont=dict(size=10, color=INK_SOFT),\n len=0.75,\n thickness=20,\n bgcolor=ELEVATED_BG,\n bordercolor=INK_SOFT,\n borderwidth=1,\n x=1.0,\n ),\n ),\n showlegend=False,\n )\n)\n\n# Native Plotly geographic basemap with Natural Earth coastlines and borders\nfig.update_geos(\n projection_type=\"mercator\",\n lataxis_range=[27, 63],\n lonaxis_range=[-64, 4],\n showcoastlines=True,\n coastlinecolor=COAST_COLOR,\n coastlinewidth=1.5,\n showland=True,\n landcolor=LAND_COLOR,\n showocean=True,\n oceancolor=OCEAN_BG,\n showlakes=True,\n lakecolor=OCEAN_BG,\n showcountries=True,\n countrycolor=COAST_COLOR,\n countrywidth=0.5,\n bgcolor=OCEAN_BG,\n showframe=True,\n framecolor=INK_SOFT,\n framewidth=1,\n)\n\nfig.update_layout(\n autosize=False,\n paper_bgcolor=PAGE_BG,\n title=dict(\n text=\"North Atlantic SST · contour-map-geographic · python · plotly · anyplot.ai\",\n font=dict(size=16, color=INK),\n x=0.5,\n xanchor=\"center\",\n ),\n font=dict(color=INK),\n margin=dict(l=40, r=120, t=80, b=40),\n annotations=[\n dict(\n x=0.12,\n y=0.72,\n text=\"Newfoundland\",\n showarrow=False,\n font=dict(size=10, color=INK_SOFT),\n xref=\"paper\",\n yref=\"paper\",\n ),\n dict(\n x=0.85,\n y=0.68,\n text=\"Ireland\",\n showarrow=False,\n font=dict(size=10, color=INK_SOFT),\n xref=\"paper\",\n yref=\"paper\",\n ),\n dict(\n x=0.60,\n y=0.20,\n text=\"Azores\",\n showarrow=False,\n font=dict(size=10, color=INK_SOFT),\n xref=\"paper\",\n yref=\"paper\",\n ),\n ],\n)\n\nfig.write_image(f\"plot-{THEME}.png\", width=800, height=450, scale=4)\nfig.write_html(f\"plot-{THEME}.html\", include_plotlyjs=\"cdn\")\n"}