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‎docs/gallery/3d.ipynb‎

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"cell_type": "markdown",
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"id": "cell-0",
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"metadata": {},
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"source": ["# 3D Visualizations\n", "\n", "ggplotly provides geoms for creating interactive 3D plots powered by Plotly's WebGL renderer."]
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"source": [
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"# 3D Visualizations\n",
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"\n",
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"ggplotly provides geoms for creating interactive 3D plots powered by Plotly's WebGL renderer."
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]
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},
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{
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"cell_type": "markdown",
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"id": "cell-1",
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"metadata": {},
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"source": ["## 3D Scatter Plots\n", "\n", "### Basic 3D Scatter"]
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"source": [
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"## 3D Scatter Plots\n",
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"\n",
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"### Basic 3D Scatter"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-2",
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"metadata": {},
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"outputs": [],
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"source": ["import numpy as np\n", "import pandas as pd\n", "from ggplotly import *\n", "\n", "df = pd.DataFrame({\n", " 'x': np.random.randn(200),\n", " 'y': np.random.randn(200),\n", " 'z': np.random.randn(200)\n", "})\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z')) + geom_point_3d()).draw()"]
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"source": "import numpy as np\nimport pandas as pd\nfrom ggplotly import *\n\ndf = pd.DataFrame({\n 'x': np.random.randn(200),\n 'y': np.random.randn(200),\n 'z': np.random.randn(200)\n})\n\n(ggplot(df, aes(x='x', y='y', z='z')) + geom_point_3d())"
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},
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{
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"cell_type": "markdown",
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"id": "cell-3",
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"metadata": {},
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"source": ["### Colored by Group"]
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"source": [
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"### Colored by Group"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-4",
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"metadata": {},
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"outputs": [],
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"source": ["df = pd.DataFrame({\n", " 'x': np.random.randn(200),\n", " 'y': np.random.randn(200),\n", " 'z': np.random.randn(200),\n", " 'group': np.random.choice(['A', 'B', 'C'], 200)\n", "})\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z', color='group')) + geom_point_3d(size=6)).draw()"]
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"source": "df = pd.DataFrame({\n 'x': np.random.randn(200),\n 'y': np.random.randn(200),\n 'z': np.random.randn(200),\n 'group': np.random.choice(['A', 'B', 'C'], 200)\n})\n\n(ggplot(df, aes(x='x', y='y', z='z', color='group')) + geom_point_3d(size=6))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-5",
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"metadata": {},
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"source": ["### Colored by Continuous Variable"]
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"source": [
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"### Colored by Continuous Variable"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-6",
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"metadata": {},
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"outputs": [],
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"source": ["df = pd.DataFrame({\n", " 'x': np.random.randn(200),\n", " 'y': np.random.randn(200),\n", " 'z': np.random.randn(200),\n", " 'value': np.random.rand(200) * 100\n", "})\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z', color='value'))\n", " + geom_point_3d(size=5)\n", " + scale_color_gradient(low='blue', high='red')).draw()"]
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"source": "df = pd.DataFrame({\n 'x': np.random.randn(200),\n 'y': np.random.randn(200),\n 'z': np.random.randn(200),\n 'value': np.random.rand(200) * 100\n})\n\n(ggplot(df, aes(x='x', y='y', z='z', color='value'))\n + geom_point_3d(size=5)\n + scale_color_gradient(low='blue', high='red'))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-7",
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"metadata": {},
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"source": ["## 3D Surfaces\n", "\n", "### Creating Surface Data\n", "\n", "Surfaces require gridded data. Here's a helper function:"]
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"source": [
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"## 3D Surfaces\n",
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"\n",
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"### Creating Surface Data\n",
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"\n",
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"Surfaces require gridded data. Here's a helper function:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-8",
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"metadata": {},
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"outputs": [],
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"source": ["def make_surface(func, x_range=(-5, 5), y_range=(-5, 5), resolution=50):\n", " \"\"\"Generate surface data from a function z = f(x, y).\"\"\"\n", " x = np.linspace(x_range[0], x_range[1], resolution)\n", " y = np.linspace(y_range[0], y_range[1], resolution)\n", " X, Y = np.meshgrid(x, y)\n", " Z = func(X, Y)\n", " return pd.DataFrame({\n", " 'x': X.flatten(),\n", " 'y': Y.flatten(),\n", " 'z': Z.flatten()\n", " })"]
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"source": "def make_surface(func, x_range=(-5, 5), y_range=(-5, 5), resolution=50):\n \"\"\"Generate surface data from a function z = f(x, y).\"\"\"\n x = np.linspace(x_range[0], x_range[1], resolution)\n y = np.linspace(y_range[0], y_range[1], resolution)\n X, Y = np.meshgrid(x, y)\n Z = func(X, Y)\n return pd.DataFrame({\n 'x': X.flatten(),\n 'y': Y.flatten(),\n 'z': Z.flatten()\n })"
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{
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"cell_type": "markdown",
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"id": "cell-9",
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"metadata": {},
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"source": ["### Paraboloid"]
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"source": [
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"### Paraboloid"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-10",
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"metadata": {},
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"outputs": [],
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"source": ["df = make_surface(lambda x, y: x**2 + y**2)\n", "(ggplot(df, aes(x='x', y='y', z='z')) + geom_surface(colorscale='Viridis')).draw()"]
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"source": "df = make_surface(lambda x, y: x**2 + y**2)\n(ggplot(df, aes(x='x', y='y', z='z')) + geom_surface(colorscale='Viridis'))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-11",
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"metadata": {},
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"source": ["### Saddle Surface (Hyperbolic Paraboloid)"]
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"source": [
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"### Saddle Surface (Hyperbolic Paraboloid)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-12",
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"metadata": {},
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"outputs": [],
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"source": ["df = make_surface(lambda x, y: x**2 - y**2)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='RdBu')\n", " + labs(title='Saddle Surface')).draw()"]
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"source": "df = make_surface(lambda x, y: x**2 - y**2)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='RdBu')\n + labs(title='Saddle Surface'))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-13",
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"metadata": {},
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"source": ["### Sinc Function (2D)"]
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"source": [
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"### Sinc Function (2D)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-14",
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"metadata": {},
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"outputs": [],
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"source": ["def sinc_2d(x, y):\n", " r = np.sqrt(x**2 + y**2)\n", " return np.where(r == 0, 1, np.sin(r) / r)\n", "\n", "df = make_surface(sinc_2d, x_range=(-10, 10), y_range=(-10, 10), resolution=80)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='Plasma')\n", " + labs(title='2D Sinc Function')).draw()"]
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"source": "def sinc_2d(x, y):\n r = np.sqrt(x**2 + y**2)\n return np.where(r == 0, 1, np.sin(r) / r)\n\ndf = make_surface(sinc_2d, x_range=(-10, 10), y_range=(-10, 10), resolution=80)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='Plasma')\n + labs(title='2D Sinc Function'))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-15",
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"metadata": {},
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"source": ["### Trigonometric Surface"]
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"source": [
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"### Trigonometric Surface"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-16",
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"metadata": {},
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"outputs": [],
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"source": ["df = make_surface(lambda x, y: np.sin(x) * np.cos(y))\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='Viridis')\n", " + labs(title='sin(x) * cos(y)')).draw()"]
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"source": "df = make_surface(lambda x, y: np.sin(x) * np.cos(y))\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='Viridis')\n + labs(title='sin(x) * cos(y)'))"
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{
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"cell_type": "markdown",
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"id": "cell-17",
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"metadata": {},
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"source": ["### Surface Colorscales\n", "\n", "Available colorscales for `geom_surface`:\n", "\n", "- **Sequential**: `Viridis`, `Plasma`, `Inferno`, `Magma`, `Cividis`, `Blues`, `Greens`, `Reds`, `YlOrRd`, `YlGnBu`\n", "- **Diverging**: `RdBu`, `RdYlBu`, `RdYlGn`, `BrBG`, `PiYG`, `PRGn`, `Spectral`\n", "- **Other**: `Jet`, `Hot`, `Electric`, `Blackbody`, `Earth`, `Picnic`, `Portland`\n", "\n", "## Wireframe Plots\n", "\n", "Wireframes show the surface structure without solid fills:"]
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"source": [
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"### Surface Colorscales\n",
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"\n",
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"Available colorscales for `geom_surface`:\n",
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"\n",
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"- **Sequential**: `Viridis`, `Plasma`, `Inferno`, `Magma`, `Cividis`, `Blues`, `Greens`, `Reds`, `YlOrRd`, `YlGnBu`\n",
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"- **Diverging**: `RdBu`, `RdYlBu`, `RdYlGn`, `BrBG`, `PiYG`, `PRGn`, `Spectral`\n",
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"- **Other**: `Jet`, `Hot`, `Electric`, `Blackbody`, `Earth`, `Picnic`, `Portland`\n",
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"\n",
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"## Wireframe Plots\n",
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"\n",
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"Wireframes show the surface structure without solid fills:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-18",
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"metadata": {},
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"outputs": [],
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"source": ["df = make_surface(lambda x, y: np.sin(x) * np.cos(y), resolution=30)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_wireframe(color='steelblue', linewidth=1)\n", " + labs(title='Wireframe Plot')).draw()"]
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"source": "df = make_surface(lambda x, y: np.sin(x) * np.cos(y), resolution=30)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_wireframe(color='steelblue', linewidth=1)\n + labs(title='Wireframe Plot'))"
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": ["### Wireframe Parameters\n", "\n", "| Parameter | Default | Description |\n", "|-----------|---------|-------------|\n", "| `color` | 'steelblue' | Line color |\n", "| `linewidth` | 1 | Line width |\n", "| `opacity` | 1.0 | Transparency (0-1) |\n", "\n", "## Combining 3D Geoms\n", "\n", "You can layer 3D geoms:"]
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"source": [
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"### Wireframe Parameters\n",
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"\n",
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"| Parameter | Default | Description |\n",
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"|-----------|---------|-------------|\n",
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"| `color` | 'steelblue' | Line color |\n",
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"| `linewidth` | 1 | Line width |\n",
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"| `opacity` | 1.0 | Transparency (0-1) |\n",
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"\n",
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"## Combining 3D Geoms\n",
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"\n",
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"You can layer 3D geoms:"
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]
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-20",
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"metadata": {},
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"outputs": [],
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"source": ["# Surface with scatter points\n", "df_surface = make_surface(lambda x, y: np.sin(x) * np.cos(y))\n", "\n", "# Sample points on the surface\n", "sample_idx = np.random.choice(len(df_surface), 50, replace=False)\n", "df_points = df_surface.iloc[sample_idx].copy()\n", "df_points['z'] = df_points['z'] + 0.1 # Offset slightly above surface\n", "\n", "(ggplot(df_surface, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='Viridis', opacity=0.7)\n", " + geom_point_3d(data=df_points, color='red', size=5)).draw()"]
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"source": "# Surface with scatter points\ndf_surface = make_surface(lambda x, y: np.sin(x) * np.cos(y))\n\n# Sample points on the surface\nsample_idx = np.random.choice(len(df_surface), 50, replace=False)\ndf_points = df_surface.iloc[sample_idx].copy()\ndf_points['z'] = df_points['z'] + 0.1 # Offset slightly above surface\n\n(ggplot(df_surface, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='Viridis', opacity=0.7)\n + geom_point_3d(data=df_points, color='red', size=5))"
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": ["## Mathematical Visualizations\n", "\n", "### Gaussian (Bell Curve) in 3D"]
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"source": [
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"## Mathematical Visualizations\n",
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"\n",
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"### Gaussian (Bell Curve) in 3D"
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]
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{
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"cell_type": "code",
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"id": "cell-22",
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"metadata": {},
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"outputs": [],
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"source": ["def gaussian_2d(x, y, sigma=1):\n", " return np.exp(-(x**2 + y**2) / (2 * sigma**2))\n", "\n", "df = make_surface(gaussian_2d, x_range=(-3, 3), y_range=(-3, 3), resolution=60)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='Viridis')\n", " + labs(title='2D Gaussian Distribution')).draw()"]
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"source": "def gaussian_2d(x, y, sigma=1):\n return np.exp(-(x**2 + y**2) / (2 * sigma**2))\n\ndf = make_surface(gaussian_2d, x_range=(-3, 3), y_range=(-3, 3), resolution=60)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='Viridis')\n + labs(title='2D Gaussian Distribution'))"
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{
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"cell_type": "markdown",
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"id": "cell-23",
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"metadata": {},
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"source": ["### Ripple Effect"]
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"source": [
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"### Ripple Effect"
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]
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},
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{
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"execution_count": null,
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"id": "cell-24",
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"metadata": {},
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"outputs": [],
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"source": ["def ripple(x, y):\n", " r = np.sqrt(x**2 + y**2)\n", " return np.sin(3 * r) * np.exp(-0.3 * r)\n", "\n", "df = make_surface(ripple, x_range=(-5, 5), y_range=(-5, 5), resolution=80)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='RdBu')\n", " + labs(title='Ripple Effect')).draw()"]
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"source": "def ripple(x, y):\n r = np.sqrt(x**2 + y**2)\n return np.sin(3 * r) * np.exp(-0.3 * r)\n\ndf = make_surface(ripple, x_range=(-5, 5), y_range=(-5, 5), resolution=80)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='RdBu')\n + labs(title='Ripple Effect'))"
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},
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{
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"cell_type": "markdown",
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"id": "cell-25",
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"metadata": {},
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"source": ["### Rosenbrock Function (Optimization Test)"]
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"source": [
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"### Rosenbrock Function (Optimization Test)"
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]
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"cell_type": "code",
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"execution_count": null,
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"id": "cell-26",
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"metadata": {},
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"outputs": [],
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"source": ["def rosenbrock(x, y, a=1, b=100):\n", " return (a - x)**2 + b * (y - x**2)**2\n", "\n", "df = make_surface(rosenbrock, x_range=(-2, 2), y_range=(-1, 3), resolution=60)\n", "\n", "(ggplot(df, aes(x='x', y='y', z='z'))\n", " + geom_surface(colorscale='Hot')\n", " + labs(title='Rosenbrock Function')).draw()"]
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"source": "def rosenbrock(x, y, a=1, b=100):\n return (a - x)**2 + b * (y - x**2)**2\n\ndf = make_surface(rosenbrock, x_range=(-2, 2), y_range=(-1, 3), resolution=60)\n\n(ggplot(df, aes(x='x', y='y', z='z'))\n + geom_surface(colorscale='Hot')\n + labs(title='Rosenbrock Function'))"
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{
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"cell_type": "markdown",
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"id": "cell-27",
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"metadata": {},
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"source": ["## Interactivity\n", "\n", "All 3D plots support:\n", "\n", "- **Rotation**: Click and drag to rotate\n", "- **Zoom**: Scroll wheel or pinch\n", "- **Pan**: Shift + drag\n", "- **Reset**: Double-click\n", "\n", "The 3D camera position is automatically saved when you interact, so subsequent renders maintain your viewpoint."]
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"source": [
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"## Interactivity\n",
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"\n",
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"All 3D plots support:\n",
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"\n",
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"- **Rotation**: Click and drag to rotate\n",
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"- **Zoom**: Scroll wheel or pinch\n",
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"- **Pan**: Shift + drag\n",
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"- **Reset**: Double-click\n",
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"\n",
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"The 3D camera position is automatically saved when you interact, so subsequent renders maintain your viewpoint."
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]
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}
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],
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"metadata": {
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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}

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