From 5c987582f0dbefa05aa7aa0eb6a22928a5c99946 Mon Sep 17 00:00:00 2001 From: Akshay Agrawal Date: Fri, 3 Apr 2026 09:28:01 -0700 Subject: [PATCH 1/3] Add linear algebra example notebooks Add four interactive marimo notebooks exploring linear algebra concepts through graph theory and matrix decomposition: - graph_laplacian.py: Spectral clustering with graph Laplacian eigenvectors - spectral_graph_drawing.py: Graph drawing using Laplacian eigenvectors - graph_signal_denoising.py: Signal denoising via Laplacian spectral projection - low_rank_approximation.py: Image compression with low-rank SVD --- README.md | 4 + .../session/graph_laplacian.py.json | 295 ++++++++++++++ .../session/graph_signal_denoising.py.json | 178 +++++++++ .../session/low_rank_approximation.py.json | 100 +++++ .../session/spectral_graph_drawing.py.json | 139 +++++++ notebooks/math/graph_laplacian.py | 280 ++++++++++++++ notebooks/math/graph_signal_denoising.py | 366 ++++++++++++++++++ notebooks/math/low_rank_approximation.py | 91 +++++ notebooks/math/spectral_graph_drawing.py | 287 ++++++++++++++ 9 files changed, 1740 insertions(+) create mode 100644 notebooks/math/__marimo__/session/graph_laplacian.py.json create mode 100644 notebooks/math/__marimo__/session/graph_signal_denoising.py.json create mode 100644 notebooks/math/__marimo__/session/low_rank_approximation.py.json create mode 100644 notebooks/math/__marimo__/session/spectral_graph_drawing.py.json create mode 100644 notebooks/math/graph_laplacian.py create mode 100644 notebooks/math/graph_signal_denoising.py create mode 100644 notebooks/math/low_rank_approximation.py create mode 100644 notebooks/math/spectral_graph_drawing.py diff --git a/README.md b/README.md index 5d53a28..06a2b86 100644 --- a/README.md +++ b/README.md @@ -114,6 +114,10 @@ uvx marimo edit --sandbox | RPSLS Math | Explore balanced tournament graphs for Rock-Paper-Scissors variants. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/rpsls-math/notebook.py) | | ChartPuck Circle | Explore how complex functions transform circles interactively. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/chartpuck-circle.py) | | Droste Zoom | Simulate the Droste zoom effect with log-polar transforms. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/zooming.py) | +| Graph Laplacian | Spectral clustering with graph Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_laplacian.py) | +| Spectral Graph Drawing | Draw graphs using Laplacian eigenvectors as node coordinates. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/spectral_graph_drawing.py) | +| Graph Signal Denoising | Denoise graph signals by projecting onto smooth Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_signal_denoising.py) | +| Low-Rank Approximation | Interactive image compression with low-rank SVD. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/low_rank_approximation.py) | ## Custom UI elements with Anywidget diff --git a/notebooks/math/__marimo__/session/graph_laplacian.py.json b/notebooks/math/__marimo__/session/graph_laplacian.py.json new file mode 100644 index 0000000..ecc79df --- /dev/null +++ b/notebooks/math/__marimo__/session/graph_laplacian.py.json @@ -0,0 +1,295 @@ +{ + "version": "1", + "metadata": { + "marimo_version": "0.21.1", + "script_metadata_hash": null + }, + "cells": [ + { + "id": "setup", + "code_hash": "15353d90ec32ed5bd56bc17f376c7800", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "Hbol", + "code_hash": "17a117a50c3daedb924fd54571af8cc6", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Graph Laplacian

\nThis notebook shows a special way to represent graphs as matrices, capturing\nimportant characteristics of the graph's connectivity.\nThe Laplacian matrix of an undirected graph with degree matrix ||(D||) and adjacency matrix ||(A||)\nis the symmetric postive semidefinite matrix\n||[\nL = D - A.\n||]Here, ||(D||) is a diagonal matrix in ||(\\mathbf{R}^{n \\times n}||) with ||(D_{i,i}||) equal\nto the degree of node ||(i||), and\n||[\nA_{ij} \\in \\mathbf{R}^{n \\times n} =\n\\begin{cases}\n1, & \\mbox{$i$ is connected to $j$} \\\\\n0, & \\mbox{otherwise}.\n\\end{cases}\n||]This Laplacian matrix tells us\nhow scalar potentials associated with nodes encoded in a vector ||(x||) vary across the graph, satisfying\n||[\nx^T L x = \\sum_{i, j} (x_i - x_j)^2.\n||]Spectral properties. ||(L||) has many interesting spectral properties. For example, an\neigenvector with small eigenvalue means that connected nodes will have similar\nvalues (or \"potentials\") in that eigenvector, a property we can exploit for\napplications such as clustering and embedding.
" + } + } + ], + "console": [] + }, + { + "id": "MJUe", + "code_hash": "a218781cac95f0bc0708258c293d5a2f", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Spectral clustering

\nIn this notebook we show how the eigenvectors of a graph Laplacian can be used to cluster\ndata points in settings where a naive application of ||(k||)-means fails.
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" + } + } + ], + "console": [] + }, + { + "id": "PKri", + "code_hash": "ee4cd425853dd799da6ecc920ac01548", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Neighborhood graph

\nWe can discover the natural clusters if we cluster the second eigenvector of a particular Laplacian matrix, interpreting the original data as a graph with two points connected if one is a nearest neighbor of the other. The number of neighbors is a parameter we can vary.\n

Adjacency matrix

\nFirst, we form the graph's adjacency matrix. Adjust the number of neighbors to see how it affects the matrix. In the visualization below, a black patch at index ||((i, j)||) indicates that ||(A_{ij} = 1||), meaning nodes ||(i||) and ||(j||) are connected in the graph.
" + } + } + ], + "console": [] + }, + { + "id": "Xref", + "code_hash": "ecf4053cd2e2c51c8972409ec596635f", + "outputs": [ + { + "type": "data", + "data": { + "text/html": "" + } + } + ], + "console": [] + }, + { + "id": "SFPL", + "code_hash": "c6d6f95b904a8ff840b0eb0e52dc945a", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "BYtC", + "code_hash": "183b92d7b88485e500c83f54c5cddeb3", + "outputs": [ + { + "type": "data", + "data": { + "text/html": "
" + } + } + ], + "console": [] + }, + { + "id": "RGSE", + "code_hash": "4119185b8335c556ff35b77447e72209", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Laplacian matrix

\nNext, we form the associated Laplacian matrix and compute its eigenvectors.
" + } + } + ], + "console": [] + }, + { + "id": "Kclp", + "code_hash": "c3e721587d7c3e942ab251e0e07fd799", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "emfo", + "code_hash": "ac29898ec602f38f4f30685a1a25977c", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "Hstk", + "code_hash": "6bc21f6b1cd81ab617d0027fb976a9bc", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "The bottom eigenvector of ||(L||) is the all-ones eigenvector with eigenvalue ||(0||). The next eigenvector, however, also has a small eigenvalue, meaning its associated eigenvector has connected nodes placed near each other. This second eigenvector is known as the Fiedler eigenvector." + } + } + ], + "console": [] + }, + { + "id": "nWHF", + "code_hash": "ab1b4d899f59c169866f86b601f647eb", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "iLit", + "code_hash": "3fec49f89e9612d522d3a67e56aa189c", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "We can plot the entries of the Fiedler eigenvector. Notice how they sharply\nseparate into two groups, suggesting that it may be useful in clustering the\noriginal data. The number of neighbors affects the structure of the graph\nand the distribution of values of the Fiedler eigenvalue.\n" + } + } + ], + "console": [] + }, + { + "id": "ZHCJ", + "code_hash": "97d1c86a78b2dab02d6e15c325271fa0", + "outputs": [ + { + "type": "data", + "data": { + "application/vnd.marimo+mimebundle": "{\"image/png\": 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"marimo_version": "0.21.1", + "script_metadata_hash": null + }, + "cells": [ + { + "id": "Hbol", + "code_hash": "0baa14faf57f217eca9547d9f9aade01", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "MJUe", + "code_hash": "4e04c1cb906dfa0cbb55893c3d40f69f", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Graph Signal Denoising

\nA graph signal is a function that assigns a scalar value to each node\nof a graph. In practice, measured signals are often corrupted by noise. The\ngoal of this notebook is to recover a clean signal from a noisy measurement,\nusing the structure of the graph.\nThe key idea is that meaningful signals tend to vary smoothly across edges:\nif two nodes are connected, their values are likely similar. Noise, on the\nother hand, has no such structure. The eigenvectors of the graph Laplacian\n||[\nL = D - A\n||](where ||(A||) is the adjacency matrix and ||(D = \\mathrm{diag}(A\\mathbf{1})||) is\nthe degree matrix) provide an orthonormal basis that separates smooth\nvariation from rough. Eigenvectors with small eigenvalues vary smoothly\nacross edges; eigenvectors with large eigenvalues oscillate sharply between\nneighbors.\nTo denoise, we decompose the noisy signal in this basis, discard the\nhigh-eigenvalue components (where the noise lives), and reconstruct from\nthe rest.
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Graph construction

\nWe build a nearest-neighbor graph from points sampled on the unit circle.\nTwo nodes are connected if one is among the other's ||(k||) nearest neighbors.
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Parameters

\n\n\n\n
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Denoising by orthogonal projection

\nTo denoise the signal, we project it onto the subspace spanned by the\nfirst ||(k||) Laplacian eigenvectors:\n||[\n\\hat{f} = \\sum_{i=1}^{k} (v_i^T f)\\, v_i.\n||]The effect is to keep the components of ||(f||) that vary smoothly across\nedges and discard the rest. Since noise has no reason to align with the\nsmooth eigenvectors, it is largely removed.
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\"__metadata__\": {\"image/png\": {\"width\": 990, \"height\": 340}}}" + } + } + ], + "console": [] + }, + { + "id": "Kclp", + "code_hash": "06246a11f5d2b7ec4cf286c4e633bf68", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "Why is this the closest vector to ||(f||) in ||(\\mathrm{span}\\{v_1, \\ldots, v_k\\}||)?\nLet ||(S = \\mathrm{span}\\{v_1, \\ldots, v_k\\}||). For any other vector ||(g \\in S||),\n||[\n\\|f - g\\|^2 = \\|f - \\hat{f} + \\hat{f} - g\\|^2 = \\|f - \\hat{f}\\|^2 + \\|\\hat{f} - g\\|^2\n||]where the cross term vanishes because ||((f - \\hat{f})||) is orthogonal to\n||((\\hat{f} - g)||), which lies in ||(S||). Since ||(\\|\\hat{f} - g\\|^2 \\geq 0||),\nthe minimum is achieved when ||(g = \\hat{f}||).\nIt remains to check that ||(f - \\hat{f}||) is indeed orthogonal to ||(S||).\nWriting ||(\\hat{f} = \\alpha_1 v_1 + \\cdots + \\alpha_k v_k||) and requiring\n||(v_j^T(f - \\hat{f}) = 0||) for each ||(j||) gives\n||[\nv_j^T f = v_j^T \\hat{f} = \\alpha_j\n||]where the last step uses orthonormality (||(v_j^T v_i = 0||) for ||(i \\neq j||),\nand ||(1||) for ||(i = j||)). So the coefficients are exactly the dot products\n||(v_i^T f||), and we recover the formula above." + } + } + ], + "console": [] + }, + { + "id": "emfo", + "code_hash": "a76de866225de74f323e675473f4b338", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Spectral coefficients

\nThe bar chart below shows the signal's coefficients in the Laplacian\neigenbasis. The dashed line marks the cutoff: coefficients to the left are\nkept, coefficients to the right are zeroed out. Noise tends to spread\nenergy across all coefficients, while the underlying signal concentrates\nin the first few.
" + } + } + ], + "console": [] + }, + { + "id": "Hstk", + "code_hash": "49f2ad85b95eebd0ee3a92b0ef75b72a", + "outputs": [ + { + "type": "data", + "data": { + "application/vnd.marimo+mimebundle": "{\"image/png\": 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jTfON2Nt7ty5jW7b0Gw2bZhquvTSSwvtd+ONN27wO8X999+fW2yxxbJtlllmmdwnn3wy3/3aMG3ll7/8ZTaae8aMGdn/p06d2uLRu+Vqn+eee27huX/4wx8udH88Lj/bfs0111zofULH1No2PHny5Nwuu+ySe/zxxxvd5sorr8x16tQp2+caa6zR6Ey3X/ziF4Xnjv6Lhp4r/14ZNWpUi14n9akc5+AFxfeM4cOHZ/v41a9+lc2cKGUGhfZLNQhQUFPuvffewkn4Bz/4QYPbxHTgtddeu/DDranOCaik+EJRnJqhIQcccEBhm7vvvrvBbeLvTf0og3J46aWXCtPYb7311izg21yAQvulmuLzP58qYb311lukDiltmGr6yU9+UjjPRjrTxuy8886F7R555JH57tOGqZRF6RwrV/vM/9ZbbrnlsqBGQ4477rjCfi655JIWvDI6inJ08Dbkm9/8ZmG/DzzwwEL3R/9Er169svujLTeWziz6O/L7mTJlStnKR30oR/s98cQTs8evtdZa2cCdUgIU2i/VIsUTNeXKK68s3I5FAhsS0yrHjh2b3X7vvffSLbfcUrHyQVO23HLLwu3nn39+ofsjKPzvf/87ux2Lo335y19ucD/x91goM8T2/y8lJZTXgQcemE1jHzduXBo1alSz22u/VFukwMmnSoiF3bt27dqix2vD1MLi2HmxWGVjYhHghh6jDVPLytU+I5Xvk08+md3eZZdd0hJLLNHgfopTql5xxRVlex3Q2t980T8xc+bM7HZ8z24s5aQ2TFuKRdgjdWT461//mrp161bS47RfqkWAgppy5513ZteRf3f48OGNblfcmTZ58uSKlA2aE7lw87p06bLQ/VOnTi2sZdFch3D+/ldffTW9+OKLKp+yuuSSS9LVV1+dlltuuXTCCSeU9Bjtl2q79NJLs+tOnTqlHXbYofD3d955JwtcxHVTtGGqLd8pG1544YVGt8t3eEVbHzRoUOHv2jC1rFztM/97sLn99OnTJ1uHKPg9SC395iu1DW+44YaFAJw2TLn98Ic/zNZr+973vpe22GKLkh+n/VItAhTUlPxomTXXXLPJkZExKmfBx0C13XbbbYXba6+99kL3P/HEEw224YZo47SVmHkWC72HWIC1d+/eJT1O+6Xa7rnnnux6tdVWyxb5u/DCC9OwYcPS8ssvn3VSxXV0AEfQrbjzIE8bptp22223tPTSSxfOv7EQcEOLWV5zzTXZ7d13372wfdCGqWXlap+Lsp9XXnkl64iD9vSbL/o7ot8j6NOgnC6++OL0n//8Jy277LLpxBNPbNFjtV+qRYCCmvHRRx+lt956K7vdv3//JreNE23Mssh/IYVq++yzz9Lvf//7wv9jSvqCpk2bVrjdXBsfMGBA4bY2TjkdfvjhacaMGWnTTTdNe++9d8mP036p9jn2qaeeym5HUC2CbN/97nfTY489tlBqkMMOOyxttdVWWTCumDZMtUXb/dvf/paNmI3RsiNGjEgXXHBBFny78cYb07HHHpuNto20ThtssMFCnQraMLWsXO1zUfYTaaKKHwdt5X//+18hiByDJBoKUOTbYvRXLLPMMiW14TfffLPBwRXQUu+++2768Y9/nN2O/okVVlihRY/XfqkWAQpqxqxZswq3e/bs2ez2+QBF5FCHajvppJPSlClTsttjxoxpMEVZS9p4vn0HbZxyueOOO9I555yTjdiKXKSRPqRU2i/VFLmcI0gRHn300XTqqaemvn37pr///e9Zaqc5c+ZkIxrzOc/vuuuu9P3vf3++fWjD1IKddtopPfDAA2mfffZJDz/8cJaffOONN07bbrttOuaYY7Lgxcknn5ydr1daaaX5HqsNU8vK1T61c2pVBBDi3J2f/fbb3/62we3ybbglfRrBbz7KIQbqvP7669l3i3333bfFj9d+qRYBCmpqBkVeKQv4dO/ePbv+8MMP27Rc0JzoFPu///u/7PaKK66YzjjjjFa38Xz7Dto45RAjcvfbb79slOFPfvKT9IUvfKFFj9d+qabi1B3RFqMTNxbxi1kUMaty8cUXT5tvvnm6+eab03rrrVdYNPXee++d73F5zsFU81wcsyYaWhw4RKdCBN5iRsWCtGFqWbnap3ZOrTrooIPS/fffn92O4PKOO+7Y4Hb5NtySPo3gNx+tdfvtt6fzzjtvkQaj5Wm/VIsABTWjR48e8/14a05+CmR0SkC1PP7442nnnXdO8+bNy9pwLOIaQYrWtvHiKb7aOOXwu9/9LkuRs8oqq6Tx48e3+PHaL9VU3P5CjGAsXnC4+HxZPKLxn//8Z4P7cA6mWoG2bbbZJh133HHZzJ9IuRd5x+MzP2YJXX/99WmzzTbLOsC+8Y1vpD/96U/zPV4bppaVq31q59SiOG/HLOQQ6fn+8pe/NLptvg23pE8j+M1Ha0Rbyg9Gi1So66677iLtR/ulWgQoqBmx4GVLpjfmR1OWMnUS2sLUqVPT6NGjszyPXbp0yRajihG85WjjxaOFtXFaKwIT8cMqnHbaafNNJy+V9ks1Fbe/EOfexmy99dbZyLFw3333NbgP52CqIVI4ReqmcO6552YLZccCqjHKNhbDjjRPMTNoyy23zDoYIk1D5DvP04apZeVqn9o5tebMM89MP//5z7Pbcc6OxYeb+i6db8Mt6dMIfvPRGjFA5+mnn87WNYk1rRaV9ku1/L9fb1ADIlK7/PLLp7fffrvZRc6iQzj/YV68yBpUymuvvZaNgozrmDoZUym//vWvN/mY4oX+mmvjxQsGauOUY42UGMW1+uqrZ7n6I5i2oOLFhiNNTiykHWL6evwI036ppkiBEIv8xSKSzZ0X4/tELEYcbTi/fdCGqaYIOMR3hTB48OAsPUhDIrj261//OptJEeuuTJw4MTuHB22YWlau9rngfuJ83tx+4rt4cwtqw6K46KKL0g9/+MPs9qqrrppuuOGGJttkiLYYKSajv+K9995rcqHsfBuO7zjF6Z6gpWLQQ4g+ikmTJjW4Tb4PLa7zvwcj+8NWW22l/VJ1AhTUlKFDh2Yjy5577rksZU5+BGRDo4Hz1l577QqWEFJ66623slGOL7zwQmFE+tixY0tq3w214YZo45RTfvp4tNnddtut2e2jc6x4plAEKLRfqm2dddZJt956a3Y7v0BlY/L3F3+P0IapplhbItI6hfXXX7/JbYcPH97g9wFtmFpWrva54H6++MUvNrufCHIsyuxQaMpVV12V/caLYHHfvn3TTTfdVFIgLNrwv/71r0Ib/fKXv9zgdtHf8fzzz2e39WnQWvmUYhMmTMguzfVn5H8Tjho1ar4AhfZLtUjxRE2J0WL5iO4DDzzQ5KLEeZtuumlFygYhckRvt9126Yknnsj+//vf/z4deOCBJVXOwIED08orr7xQG25sgavQr1+/tNpqq6l8qk77pdqKU+jlA8QNef/997MfXvlzaJ42TDUVB8uiU6opn3zySYOP04apZeVqn/nfg83tJ2bJPfPMM9ltvwcptwhG7LLLLtn5OrI8xMyJNdZYo6THltqGY72h/Ih2bZhaof1SLQIU1JRYEDCvsahvjGC44IILstsxXTLy9EIlRGqc7bffPj344IPZ/4866qh0xBFHlPz4mH6eTwMVo2nuueeeBreLv+dHhMX28ThojUgREulFmroUL5wdOdDzf893HGi/VNs3v/nNwu0rrrii0e3ivmi7YeTIkYW/a8NU03LLLZetMxHuvvvuJoMUxR1a0embpw1Ty8rVPiMFWn40+SWXXJJ9/27su03ezjvvXLbXAXfddVfWNmMGcq9evdJ1112XzeIs1RZbbJE9Lpx//vmF7yQL0oYpp+Z+68Ul0pSFuM7/LT87Wful6nJQY0aOHBmf4LmuXbvm7rrrroXu/+Mf/5jdH5fx48dXpYx0PB9//HFu9OjRhbZ3yCGHLNJ+nn766VyXLl2yfWy44Ya5OXPmzHd//D/+nn8PPPPMM2V6BdC0OJ/m2/ctt9zS4DbaL9X21a9+NWujnTt3zt14440L3T99+vRc//79s226deuWmzZt2nz3a8NU02677VY4zx5zzDENbvPOO+/khg4dWtjuuuuum+9+bZhKmTp1aqEdjhs3rqTHlKt9nnvuuYXnPvDAAxe6/7nnnsstvfTS2f1rrrlm7pNPPlnEV0k9W5Q2/NBDD+WWWWaZ7DFLLrlk7s4771yk5/7FL35ReO7ov1hQ9HPEeyDuHzVq1CI9B/VtUdpvc1ZdddVsf3HdFO2XaugU/1Q7SALFHnrooWyK44cffph69uyZfv7zn2ezJOL/sZDPWWedVRhdE9Mil1pqKRVIRUbuXn755dntyNF48sknNzmzoVu3blkbbciRRx6ZpYbK56GOWRgxZThykMbiVvEeyG/3u9/9rk1eDyzomGOOSccee2xhBkWM/tJ+qTWRzuNLX/pStuhkLIb94x//OH3ta19Liy++eJoyZUo67rjjCouzxvn08MMPX2gfzsFUS4waj/Ul8iPCd9xxx2yx7NVXXz199NFH2cjy+H7x8ssvZ/dvvfXW6cYbb1xoP9owbeHOO+/M1gHMi1R5hx12WHY7fpvts88+822/5557NrifcrTPWEco8qJPnjy58D183333Tcsuu2x2ro+1st54443UuXPndPXVV6evfvWrZaoFOnIbjja6ySabZG0rnHTSSdmCw02JBYbjsqBZs2alDTfcsJCGbL/99ku77rpr9n0lvmdH2589e3b2/5ix0dRaK3QM5ToHNyVmxr/00kvZDIoXX3yx0e20X6qiKmERaMZVV11VGBXT0GXw4MG5Z599Vj1SMY21xcYuTY1K+PTTT3Pf//73m3z83nvvnW0HtTSDQvulFtxxxx25lVZaqdHzZ6dOnXJHH310o493Dqaabrjhhlzv3r2b/R6x1VZbZbMpGqIN0xZihG5Lvus2plzt880338yNGDGi0X107949d/bZZ7dBTdBR2/CECRNa/JuvqYwO0V8x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\"__metadata__\": {\"image/png\": {\"width\": 788, \"height\": 289}}}" + } + } + ], + "console": [] + } + ] +} \ No newline at end of file diff --git a/notebooks/math/__marimo__/session/low_rank_approximation.py.json b/notebooks/math/__marimo__/session/low_rank_approximation.py.json new file mode 100644 index 0000000..8ea0bc4 --- /dev/null +++ b/notebooks/math/__marimo__/session/low_rank_approximation.py.json @@ -0,0 +1,100 @@ +{ + "version": "1", + "metadata": { + "marimo_version": "0.21.1", + "script_metadata_hash": null + }, + "cells": [ + { + "id": "Hbol", + "code_hash": "d9494b49949dae3c2fbd40b46f722650", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "MJUe", + "code_hash": "0db750110ba73f956c50187987940e12", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "vblA", + "code_hash": "774e27b23927ed4a54ea34dbae7bda7e", + "outputs": [ + { + "type": "data", + "data": { + "text/html": "" + } + } + ], + "console": [] + }, + { + "id": "bkHC", + "code_hash": "f1b5f8bccfa57c6d40e7661f5221f64d", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "Take a photo to get started." + } + } + ], + "console": [] + }, + { + "id": "lEQa", + "code_hash": "ebf42973c9588235f74b16b905036c9b", + "outputs": [ + { + "type": "error", + "ename": "ancestor-stopped", + "evalue": "This cell wasn't run because an ancestor was stopped with `mo.stop`: ", + "traceback": [] + } + ], + "console": [] + }, + { + "id": "PKri", + "code_hash": "c1dbc288b32d7aec24fe4be140694f56", + "outputs": [ + { + "type": "data", + "data": { + "text/html": "" + } + } + ], + "console": [] + }, + { + "id": "Xref", + "code_hash": "43af141a7cb70f893f2dac8d5c8ef897", + "outputs": [ + { + "type": "error", + "ename": "ancestor-stopped", + "evalue": "This cell wasn't run because an ancestor was stopped with `mo.stop`: ", + "traceback": [] + } + ], + "console": [] + } + ] +} \ No newline at end of file diff --git a/notebooks/math/__marimo__/session/spectral_graph_drawing.py.json b/notebooks/math/__marimo__/session/spectral_graph_drawing.py.json new file mode 100644 index 0000000..68a1716 --- /dev/null +++ b/notebooks/math/__marimo__/session/spectral_graph_drawing.py.json @@ -0,0 +1,139 @@ +{ + "version": "1", + "metadata": { + "marimo_version": "0.21.1", + "script_metadata_hash": null + }, + "cells": [ + { + "id": "Hbol", + "code_hash": "a69aabe2d4176a1e48c8927c74ea7786", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "MJUe", + "code_hash": "4d2a05841078dab915de20e11cf4187d", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Spectral Graph Drawing

\nThis notebook shows how eigenvectors of the graph Laplacian can be used\nto draw graphs, positioning nodes in two dimensions so that the layout\nreflects the graph's connectivity.\nGiven an undirected graph with adjacency matrix ||(A \\in \\mathbf{R}^{n imes n}||)\nand degree matrix ||(D = \\mathrm{diag}(A \\mathbf{1})||), the Laplacian matrix is\n||[\nL = D - A.\n||]The eigenvectors of ||(L||) minimize the sum of squared distances between\nconnected nodes. Specifically, if we assign each node ||(i||) a position\n||(x_i \\in \\mathbf{R}||), the Laplacian satisfies\n||[\nx^T L x = \\sum_{(i,j) \\in E} (x_i - x_j)^2,\n||]so an eigenvector with a small eigenvalue places connected nodes close\ntogether.\nTo draw a graph in two dimensions, we use the second and third smallest\neigenvectors as ||((x, y)||) coordinates for each node. The first eigenvector\n(constant, eigenvalue ||(0||)) is discarded because it would place every node\nat the same point.
" + } + } + ], + "console": [] + }, + { + "id": "vblA", + "code_hash": "63793352c0c6ea114935ac46245b2fab", + "outputs": [ + { + "type": "data", + "data": { + "text/html": "" + } + } + ], + "console": [] + }, + { + "id": "bkHC", + "code_hash": "4a7e48d79f2860eed695376895126b2c", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Parameters

\n
" + } + } + ], + "console": [] + }, + { + "id": "lEQa", + "code_hash": "883c91471bdb7ae993b6a9fb37281dcb", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "PKri", + "code_hash": "353b62c328092461f449583b3b4fa5c1", + "outputs": [ + { + "type": "data", + "data": { + "text/plain": "" + } + } + ], + "console": [] + }, + { + "id": "Xref", + "code_hash": "0bd7c0be17c7ecd115dc3be4abec5924", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Eigenvector pair

\nChoose which eigenvectors to use as coordinates. The default (second and\nthird) gives the classical spectral drawing. Eigenvectors with larger\neigenvalues vary more rapidly across the graph, so using them as\ncoordinates emphasizes local differences between nearby nodes rather than\nglobal shape.\n\n\nNodes are colored by the eigenvector you've selected below. For low\neigenvectors the color varies smoothly across the graph; for higher ones\nit oscillates between neighbors.\n
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\"__metadata__\": {\"image/png\": {\"width\": 984, \"height\": 506}}}" + } + } + ], + "console": [] + }, + { + "id": "BYtC", + "code_hash": "b9b59ede8665df7bede40c27ab1886ef", + "outputs": [ + { + "type": "data", + "data": { + "text/markdown": "

Eigenvalue spectrum

\nEach eigenvalue of ||(L||) measures how much the corresponding eigenvector\nvaries across edges. An eigenvector with a small eigenvalue assigns similar\nvalues to connected nodes; one with a large eigenvalue changes sharply\nbetween neighbors. The plot below shows the spectrum, with the selected\neigenvectors highlighted.
" + } + } + ], + "console": [] + }, + { + "id": "RGSE", + "code_hash": "8bb6b38e74982fe9544df8f4ae421ef4", + "outputs": [ + { + "type": "data", + "data": { + "application/vnd.marimo+mimebundle": "{\"image/png\": 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\", \"__metadata__\": {\"image/png\": {\"width\": 588, \"height\": 289}}}" + } + } + ], + "console": [] + } + ] +} \ No newline at end of file diff --git a/notebooks/math/graph_laplacian.py b/notebooks/math/graph_laplacian.py new file mode 100644 index 0000000..477e1b7 --- /dev/null +++ b/notebooks/math/graph_laplacian.py @@ -0,0 +1,280 @@ +# /// script +# dependencies = [ +# "marimo", +# "matplotlib==3.10.8", +# "numpy==2.4.3", +# "scikit-learn==1.8.0", +# "scipy==1.17.1", +# ] +# requires-python = ">=3.14" +# /// + +import marimo + +__generated_with = "0.21.1" +app = marimo.App() + +with app.setup(hide_code=True): + import marimo as mo + import numpy as np + import matplotlib.pyplot as plt + from numpy.linalg import eigh + import sklearn + from sklearn.neighbors import NearestNeighbors + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + # Graph Laplacian + + This notebook shows a special way to represent graphs as matrices, capturing + important characteristics of the graph's connectivity. + + The Laplacian matrix of an undirected graph with degree matrix $D$ and adjacency matrix $A$ + is the symmetric postive semidefinite matrix + + $$ + L = D - A. + $$ + + Here, $D$ is a diagonal matrix in $\mathbf{R}^{n \times n}$ with $D_{i,i}$ equal + to the degree of node $i$, and + + $$ + A_{ij} \in \mathbf{R}^{n \times n} = + \begin{cases} + 1, & \mbox{$i$ is connected to $j$} \\ + 0, & \mbox{otherwise}. + \end{cases} + $$ + + This _Laplacian matrix_ tells us + how scalar potentials associated with nodes encoded in a vector $x$ vary across the graph, satisfying + + $$ + x^T L x = \sum_{i, j} (x_i - x_j)^2. + $$ + + **Spectral properties.** $L$ has many interesting spectral properties. For example, an + eigenvector with small eigenvalue means that connected nodes will have similar + values (or "potentials") in that eigenvector, a property we can exploit for + applications such as clustering and embedding. + """) + return + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + ## Spectral clustering + + In this notebook we show how the eigenvectors of a graph Laplacian can be used to cluster + data points in settings where a naive application of $k$-means fails. + """) + return + + +@app.cell(hide_code=True) +def _(): + dataset_picker = mo.ui.dropdown( + options={"Two Moons": "moons", "Concentric Circles": "circles"}, + value="Two Moons", + label="Dataset", + ) + + dataset_picker + return (dataset_picker,) + + +@app.cell +def _(dataset_picker): + if dataset_picker.value == "moons": + data, _ = sklearn.datasets.make_moons(n_samples=200, noise=0.06, random_state=0) + else: + data, _ = sklearn.datasets.make_circles( + n_samples=200, noise=0.05, factor=0.4, random_state=0 + ) + return (data,) + + +@app.cell(hide_code=True) +def _(data): + mo.hstack( + [ + scatter(data, title="raw data"), + color_by_clusters( + data, compute_clusters(data), title="k-means on raw data" + ), + ] + ) + return + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + ## Neighborhood graph + + We can discover the natural clusters if we cluster the second eigenvector of a particular Laplacian matrix, interpreting the original data as a graph with two points connected if one is a nearest neighbor of the other. The number of neighbors is a parameter we can vary. + + ### Adjacency matrix + + First, we form the graph's **adjacency matrix.** Adjust the number of neighbors to see how it affects the matrix. In the visualization below, a black patch at index $(i, j)$ indicates that $A_{ij} = 1$, meaning nodes $i$ and $j$ are connected in the graph. + """) + return + + +@app.cell +def _(): + n_neighbors = mo.ui.slider( + value=11, start=3, stop=20, step=1, label="Number of neighbors $k$", show_value=True + ) + n_neighbors + return (n_neighbors,) + + +@app.cell +def _(data, n_neighbors): + neighbors = NearestNeighbors(n_neighbors=n_neighbors.value).fit(data) + _A = neighbors.kneighbors_graph(data).toarray() + adjacency_matrix = np.maximum(_A, _A.T) + return (adjacency_matrix,) + + +@app.cell(hide_code=True) +def _(adjacency_matrix, data): + plt.imshow(adjacency_matrix, cmap="gray_r") + plt.gca() + plt.xlabel("node index") + plt.ylabel("node index") + plt.title(f"Adjacency matrix A") + _adjacency_ax = plt.gca() + + plt.figure() + _ax = scatter(data, title="Neighbor graph") + _n = adjacency_matrix.shape[0] + for _i in range(_n): + for _j in range(_i + 1, _n): + if adjacency_matrix[_i, _j] > 0: + _ax.plot( + [data[_i, 0], data[_j, 0]], + [data[_i, 1], data[_j, 1]], + color="gray", + linewidth=0.4, + alpha=0.5, + ) + # Re-scatter on top so points aren't hidden behind edges + _ax.scatter(data[:, 0], data[:, 1], s=10, color="royalblue", zorder=3) + + mo.hstack([_adjacency_ax, _ax]) + return + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + ### Laplacian matrix + + Next, we form the associated **Laplacian matrix** and compute its eigenvectors. + """) + return + + +@app.function +def laplacian_matrix(adjacency_matrix): + degree_matrix = np.diag(np.sum(adjacency_matrix, axis=1)) + L = degree_matrix - adjacency_matrix + return L + + +@app.cell +def _(adjacency_matrix): + L = laplacian_matrix(adjacency_matrix) + return (L,) + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + The bottom eigenvector of $L$ is the all-ones eigenvector with eigenvalue $0$. The next eigenvector, however, also has a small eigenvalue, meaning its associated eigenvector has connected nodes placed near each other. This second eigenvector is known as the **Fiedler eigenvector.** + """) + return + + +@app.cell +def _(L): + eigenvalues, eigenvectors = eigh(L) + fiedler_eigenvector = eigenvectors[:, 0].reshape(-1, 1) + return (fiedler_eigenvector,) + + +@app.cell(hide_code=True) +def _(n_neighbors): + mo.md(rf""" + We can plot the entries of the Fiedler eigenvector. Notice how they sharply + separate into two groups, suggesting that it may be useful in clustering the + original data. The number of neighbors affects the structure of the graph + and the distribution of values of the Fiedler eigenvalue. + + {n_neighbors} + """) + return + + +@app.cell(hide_code=True) +def _(fiedler_eigenvector): + plt.scatter( + range(len(fiedler_eigenvector)), + fiedler_eigenvector, + c=compute_clusters(fiedler_eigenvector), + cmap="coolwarm", + s=10, + ) + plt.xlabel("indices") + plt.ylabel("value") + plt.gca() + return + + +@app.cell(hide_code=True) +def _(): + mo.md(r""" + Indeed, if we assign clusters based on a $k$-means clustering of the Fiedler eigenvector, we obtain the natural clustering on the moons dataset. + """) + return + + +@app.cell +def _(data, fiedler_eigenvector): + color_by_clusters(data, compute_clusters(fiedler_eigenvector)) + return + + +@app.function +def color_by_clusters(X, cluster_labels, title=""): + plt.figure() + plt.scatter(X[:, 0], X[:, 1], s=2, c=cluster_labels, cmap='coolwarm') + plt.axis("equal") + plt.title(title) + return plt.gca() + + +@app.function +def compute_clusters(X): + from sklearn.cluster import KMeans + kmeans = KMeans(n_clusters=2, random_state=0) + return kmeans.fit_predict(X) + + +@app.function +def scatter(X, title=""): + plt.figure() + plt.scatter(X[:, 0], X[:, 1], s=10) + plt.axis("equal") + plt.title(title) + return plt.gca() + + +if __name__ == "__main__": + app.run() diff --git a/notebooks/math/graph_signal_denoising.py b/notebooks/math/graph_signal_denoising.py new file mode 100644 index 0000000..78cb1da --- /dev/null +++ b/notebooks/math/graph_signal_denoising.py @@ -0,0 +1,366 @@ +# /// script +# dependencies = [ +# "marimo", +# "matplotlib==3.10.8", +# "numpy==2.4.3", +# "scikit-learn==1.8.0", +# ] +# requires-python = ">=3.14" +# /// + +import marimo + +__generated_with = "0.22.0" +app = marimo.App() + + +@app.cell(hide_code=True) +def _(): + import marimo as mo + import numpy as np + import matplotlib.pyplot as plt + from numpy.linalg import eigh + from sklearn.neighbors import NearestNeighbors + + return NearestNeighbors, eigh, mo, np, plt + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + # Graph Signal Denoising + + A **graph signal** is a function that assigns a scalar value to each node + of a graph. In practice, measured signals are often corrupted by noise. The + goal of this notebook is to recover a clean signal from a noisy measurement, + using the structure of the graph. + + The key idea is that meaningful signals tend to vary smoothly across edges: + if two nodes are connected, their values are likely similar. Noise, on the + other hand, has no such structure. The eigenvectors of the graph Laplacian + + $$ + L = D - A + $$ + + (where $A$ is the adjacency matrix and $D = \mathrm{diag}(A\mathbf{1})$ is + the degree matrix) provide an orthonormal basis that separates smooth + variation from rough. Eigenvectors with small eigenvalues vary smoothly + across edges; eigenvectors with large eigenvalues oscillate sharply between + neighbors. + + To denoise, we decompose the noisy signal in this basis, discard the + high-eigenvalue components (where the noise lives), and reconstruct from + the rest. + """) + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + ## Graph construction + + We build a nearest-neighbor graph from points sampled on the unit circle. + Two nodes are connected if one is among the other's $k$ nearest neighbors. + """) + return + + +@app.cell(hide_code=True) +def _(mo): + signal_type = mo.ui.dropdown( + options={ + "Sine wave": "sine", + "Step function": "step", + "Gaussian bump": "bump", + }, + value="Sine wave", + label="Signal", + ) + signal_type + return (signal_type,) + + +@app.cell(hide_code=True) +def _(mo): + n_nodes = mo.ui.slider( + start=50, + stop=300, + step=10, + value=150, + label="Number of nodes $n$", + show_value=True, + ) + n_neighbors = mo.ui.slider( + start=3, + stop=20, + step=1, + value=7, + label="Number of neighbors $k$", + show_value=True, + ) + noise_level = mo.ui.slider( + start=0.0, + stop=1.0, + step=0.05, + value=0.3, + label=r"Noise level $\sigma$", + show_value=True, + ) + n_components = mo.ui.slider( + start=1, + stop=30, + step=1, + value=5, + label="Components to keep", + show_value=True, + ) + mo.md(f""" + ### Parameters + + {n_nodes} + + {n_neighbors} + + {noise_level} + + {n_components} + """) + return n_components, n_neighbors, n_nodes, noise_level + + +@app.cell(hide_code=True) +def _( + NearestNeighbors, + eigh, + n_neighbors, + n_nodes, + noise_level, + np, + signal_type, +): + _rng = np.random.default_rng(42) + _t = np.sort(_rng.uniform(0, 2 * np.pi, n_nodes.value)) + positions = np.column_stack([np.cos(_t), np.sin(_t)]) + + neighbors = NearestNeighbors(n_neighbors=n_neighbors.value).fit(positions) + _A = neighbors.kneighbors_graph(positions).toarray() + adjacency_matrix = np.maximum(_A, _A.T) + + degree_matrix = np.diag(adjacency_matrix.sum(axis=1)) + L = degree_matrix - adjacency_matrix + eigenvalues, eigenvectors = eigh(L) + + if signal_type.value == "sine": + clean_signal = np.sin(2 * _t) + elif signal_type.value == "step": + clean_signal = np.sign(np.sin(_t)) + else: + clean_signal = np.exp(-4 * (_t - np.pi) ** 2) + + noisy_signal = clean_signal + noise_level.value * _rng.standard_normal( + len(clean_signal) + ) + return ( + adjacency_matrix, + clean_signal, + eigenvectors, + noisy_signal, + positions, + ) + + +@app.cell(hide_code=True) +def _(eigenvectors, n_components, noisy_signal): + coefficients = eigenvectors.T @ noisy_signal + filtered_coefficients = coefficients.copy() + filtered_coefficients[n_components.value :] = 0 + denoised_signal = eigenvectors @ filtered_coefficients + return coefficients, denoised_signal + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + ## Denoising by orthogonal projection + + To denoise the signal, we project it onto the subspace spanned by the + first $k$ Laplacian eigenvectors: + + $$ + \hat{f} = \sum_{i=1}^{k} (v_i^T f)\, v_i. + $$ + + The effect is to keep the components of $f$ that vary smoothly across + edges and discard the rest. Since noise has no reason to align with the + smooth eigenvectors, it is largely removed. + """) + return + + +@app.cell(hide_code=True) +def _( + adjacency_matrix, + clean_signal, + denoised_signal, + n_components, + noise_level, + noisy_signal, + plt, + positions, +): + _fig, _axes = plt.subplots(1, 3, figsize=(14, 4.5)) + _vmin = min(noisy_signal.min(), denoised_signal.min(), clean_signal.min()) + _vmax = max(noisy_signal.max(), denoised_signal.max(), clean_signal.max()) + _n = adjacency_matrix.shape[0] + + for _ax, _sig, _title in [ + (_axes[0], clean_signal, "Ground truth"), + ( + _axes[1], + noisy_signal, + rf"Noisy signal ($\sigma$ = {noise_level.value:.2f})", + ), + (_axes[2], denoised_signal, f"Denoised ({n_components.value} components)"), + ]: + for _i in range(_n): + for _j in range(_i + 1, _n): + if adjacency_matrix[_i, _j] > 0: + _ax.plot( + [positions[_i, 0], positions[_j, 0]], + [positions[_i, 1], positions[_j, 1]], + color="gray", + linewidth=0.3, + alpha=0.2, + ) + _sc = _ax.scatter( + positions[:, 0], + positions[:, 1], + c=_sig, + cmap="coolwarm", + s=20, + vmin=_vmin, + vmax=_vmax, + zorder=3, + ) + _ax.set_title(_title) + _ax.set_aspect("equal") + _ax.axis("off") + + plt.tight_layout() + plt.gca() + return + + +@app.cell(hide_code=True) +def _( + clean_signal, + denoised_signal, + n_components, + noise_level, + noisy_signal, + np, + plt, +): + _fig, _ax = plt.subplots(figsize=(10, 3.5)) + _idx = np.arange(len(clean_signal)) + _ax.plot( + _idx, clean_signal, color="black", linewidth=1.5, label="Ground truth" + ) + _ax.scatter( + _idx, + noisy_signal, + color="gray", + s=5, + alpha=0.5, + label=rf"Noisy ($\sigma$ = {noise_level.value:.2f})", + ) + _ax.plot( + _idx, + denoised_signal, + color="royalblue", + linewidth=1.5, + label=f"Denoised ({n_components.value} components)", + ) + _ax.set_xlabel("node index") + _ax.set_ylabel("signal value") + _ax.legend(frameon=False) + plt.tight_layout() + plt.gca() + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + **Why is this the closest vector to $f$ in $\mathrm{span}\{v_1, \ldots, v_k\}$?** + Let $S = \mathrm{span}\{v_1, \ldots, v_k\}$. For any other vector $g \in S$, + + $$ + \|f - g\|^2 = \|f - \hat{f} + \hat{f} - g\|^2 = \|f - \hat{f}\|^2 + \|\hat{f} - g\|^2 + $$ + + where the cross term vanishes because $(f - \hat{f})$ is orthogonal to + $(\hat{f} - g)$, which lies in $S$. Since $\|\hat{f} - g\|^2 \geq 0$, + the minimum is achieved when $g = \hat{f}$. + + It remains to check that $f - \hat{f}$ is indeed orthogonal to $S$. + Writing $\hat{f} = \alpha_1 v_1 + \cdots + \alpha_k v_k$ and requiring + $v_j^T(f - \hat{f}) = 0$ for each $j$ gives + + $$ + v_j^T f = v_j^T \hat{f} = \alpha_j + $$ + + where the last step uses orthonormality ($v_j^T v_i = 0$ for $i \neq j$, + and $1$ for $i = j$). So the coefficients are exactly the dot products + $v_i^T f$, and we recover the formula above. + """) + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + ## Spectral coefficients + + The bar chart below shows the signal's coefficients in the Laplacian + eigenbasis. The dashed line marks the cutoff: coefficients to the left are + kept, coefficients to the right are zeroed out. Noise tends to spread + energy across all coefficients, while the underlying signal concentrates + in the first few. + """) + return + + +@app.cell(hide_code=True) +def _(coefficients, n_components, np, plt): + _fig, _ax = plt.subplots(figsize=(8, 3)) + _ax.bar( + range(len(coefficients)), + np.abs(coefficients), + color="lightgray", + edgecolor="gray", + linewidth=0.5, + ) + _ax.bar( + range(n_components.value), + np.abs(coefficients[: n_components.value]), + color="royalblue", + edgecolor="gray", + linewidth=0.5, + ) + _ax.axvline( + n_components.value - 0.5, color="black", linestyle="--", linewidth=1 + ) + _ax.set_xlabel("eigenvector index") + _ax.set_ylabel("$|$coefficient$|$") + _ax.set_title("Spectral coefficients of noisy signal") + plt.tight_layout() + plt.gca() + return + + +if __name__ == "__main__": + app.run() diff --git a/notebooks/math/low_rank_approximation.py b/notebooks/math/low_rank_approximation.py new file mode 100644 index 0000000..32272f9 --- /dev/null +++ b/notebooks/math/low_rank_approximation.py @@ -0,0 +1,91 @@ +# /// script +# requires-python = ">=3.14" +# dependencies = [ +# "marimo", +# "matplotlib==3.10.8", +# "numpy==2.4.3", +# "scikit-image==0.26.0", +# "wigglystuff==0.3.1", +# ] +# /// + +import marimo + +__generated_with = "0.22.0" +app = marimo.App() + + +@app.cell(hide_code=True) +def _(): + import marimo as mo + import numpy as np + import matplotlib.pyplot as plt + from skimage import data + from skimage.util import img_as_float + from wigglystuff import WebcamCapture + + return WebcamCapture, mo, np, plt + + +@app.cell +def _(np): + def low_rank_rgb(img, rank): + height, width, channels = img.shape + assert channels == 3, "Expected RGB image with shape (H, W, 3)" + + out = np.empty_like(img, dtype=np.float64) + for c in range(3): + channel = img[:, :, c].astype(np.float64) + U, S, Vt = np.linalg.svd(channel, full_matrices=False) + out[:, :, c] = U[:, :rank] @ np.diag(S[:rank]) @ Vt[:rank, :] + + return out + + return (low_rank_rgb,) + + +@app.cell(hide_code=True) +def _(WebcamCapture, mo): + camera = mo.ui.anywidget(WebcamCapture()) + camera + return (camera,) + + +@app.cell +def _(camera, mo, np): + mo.stop(not camera.image_base64, mo.md("**Take a photo to get started.**")) + + pil_image = camera.get_pil() + image = np.array(pil_image)[:, :, :3] / 255.0 + return (image,) + + +@app.cell +def _(image, low_rank_rgb, rank_slider): + approx_image = low_rank_rgb(image, rank_slider.value) + return (approx_image,) + + +@app.cell(hide_code=True) +def _(mo): + rank_slider = mo.ui.slider(1, 128, value=20, label="Rank of approximation") + rank_slider + return (rank_slider,) + + +@app.cell(hide_code=True) +def _(approx_image, image, plt, rank_slider): + fig, axes = plt.subplots(1, 2, figsize=(8, 4)) + axes[0].imshow(image) + axes[0].set_title("Original") + axes[0].axis("off") + axes[1].imshow(approx_image) + axes[1].set_title(f"Rank {rank_slider.value} Approximation") + axes[1].axis("off") + plt.tight_layout() + plt.gca() + return + + +if __name__ == "__main__": + app.run() diff --git a/notebooks/math/spectral_graph_drawing.py b/notebooks/math/spectral_graph_drawing.py new file mode 100644 index 0000000..cbf087c --- /dev/null +++ b/notebooks/math/spectral_graph_drawing.py @@ -0,0 +1,287 @@ +# /// script +# dependencies = [ +# "marimo", +# "matplotlib==3.10.8", +# "numpy==2.4.3", +# ] +# requires-python = ">=3.14" +# /// + +import marimo + +__generated_with = "0.22.0" +app = marimo.App() + + +@app.cell(hide_code=True) +def _(): + import marimo as mo + import numpy as np + import matplotlib.pyplot as plt + from numpy.linalg import eigh + + return eigh, mo, np, plt + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + # Spectral Graph Drawing + + This notebook shows how eigenvectors of the graph Laplacian can be used + to draw graphs, positioning nodes in two dimensions so that the layout + reflects the graph's connectivity. + + Given an undirected graph with adjacency matrix $A \in \mathbf{R}^{n imes n}$ + and degree matrix $D = \mathrm{diag}(A \mathbf{1})$, the **Laplacian matrix** is + + $$ + L = D - A. + $$ + + The eigenvectors of $L$ minimize the sum of squared distances between + connected nodes. Specifically, if we assign each node $i$ a position + $x_i \in \mathbf{R}$, the Laplacian satisfies + + $$ + x^T L x = \sum_{(i,j) \in E} (x_i - x_j)^2, + $$ + + so an eigenvector with a small eigenvalue places connected nodes close + together. + + To draw a graph in two dimensions, we use the second and third smallest + eigenvectors as $(x, y)$ coordinates for each node. The first eigenvector + (constant, eigenvalue $0$) is discarded because it would place every node + at the same point. + """) + return + + +@app.cell(hide_code=True) +def _(mo): + graph_type = mo.ui.dropdown( + options={ + "Path": "path", + "Cycle": "cycle", + "Grid": "grid", + "Petersen": "petersen", + "Random (Erdős–Rényi)": "random", + }, + value="Path", + label="Graph", + ) + graph_type + return (graph_type,) + + +@app.cell(hide_code=True) +def _(graph_type, mo): + n_nodes = mo.ui.slider( + start=10, + stop=100, + step=1, + value=30, + label="Number of nodes $n$", + show_value=True, + ) + edge_prob = mo.ui.slider( + start=0.02, + stop=0.4, + step=0.02, + value=0.1, + label="Edge probability $p$", + show_value=True, + ) + mo.md(f""" + ### Parameters + + {n_nodes} + + {edge_prob if graph_type.value == "random" else ""} + """) + return edge_prob, n_nodes + + +@app.cell(hide_code=True) +def _(edge_prob, graph_type, n_nodes, np): + def build_adjacency(kind, n, p): + if kind == "path": + A = np.zeros((n, n)) + for i in range(n - 1): + A[i, i + 1] = A[i + 1, i] = 1 + return A + elif kind == "cycle": + A = np.zeros((n, n)) + for i in range(n): + A[i, (i + 1) % n] = A[(i + 1) % n, i] = 1 + return A + elif kind == "grid": + side = int(np.ceil(np.sqrt(n))) + actual = side * side + A = np.zeros((actual, actual)) + for i in range(actual): + r, c = divmod(i, side) + if c + 1 < side: + A[i, i + 1] = A[i + 1, i] = 1 + if r + 1 < side: + A[i, i + side] = A[i + side, i] = 1 + return A + elif kind == "petersen": + A = np.zeros((10, 10)) + for i in range(5): + A[i, (i + 1) % 5] = A[(i + 1) % 5, i] = 1 + A[i, i + 5] = A[i + 5, i] = 1 + for i in range(5): + A[5 + i, 5 + (i + 2) % 5] = A[5 + (i + 2) % 5, 5 + i] = 1 + return A + else: + rng = np.random.default_rng(42) + A = (rng.random((n, n)) < p).astype(float) + A = np.triu(A, 1) + A = A + A.T + return A + + + adjacency_matrix = build_adjacency( + graph_type.value, n_nodes.value, edge_prob.value + ) + return (adjacency_matrix,) + + +@app.cell(hide_code=True) +def _(adjacency_matrix, eigh, np): + degree_matrix = np.diag(np.sum(adjacency_matrix, axis=1)) + L = degree_matrix - adjacency_matrix + eigenvalues, eigenvectors = eigh(L) + return eigenvalues, eigenvectors + + +@app.cell(hide_code=True) +def _(adjacency_matrix, mo): + _max_idx = min(adjacency_matrix.shape[0], 10) + + evec_x = mo.ui.slider( + start=1, + stop=_max_idx - 1, + value=1, + label="Eigenvector for $x$-axis", + show_value=True, + ) + evec_y = mo.ui.slider( + start=1, + stop=_max_idx - 1, + value=2, + label="Eigenvector for $y$-axis", + show_value=True, + ) + color_by = mo.ui.radio( + options={"x-axis eigenvector": "x", "y-axis eigenvector": "y"}, + value="x-axis eigenvector", + label="Color nodes by", + ) + + mo.md(f""" + ### Eigenvector pair + + Choose which eigenvectors to use as coordinates. The default (second and + third) gives the classical spectral drawing. Eigenvectors with larger + eigenvalues vary more rapidly across the graph, so using them as + coordinates emphasizes local differences between nearby nodes rather than + global shape. + + {evec_x} + + {evec_y} + + Nodes are colored by the eigenvector you've selected below. For low + eigenvectors the color varies smoothly across the graph; for higher ones + it oscillates between neighbors. + + {color_by} + """) + return color_by, evec_x, evec_y + + +@app.cell(hide_code=True) +def _(adjacency_matrix, color_by, eigenvectors, evec_x, evec_y, np, plt): + _x = eigenvectors[:, evec_x.value] + _y = eigenvectors[:, evec_y.value] + _n = adjacency_matrix.shape[0] + _color = _x if color_by.value == "x" else _y + + _fig, _axes = plt.subplots(1, 2, figsize=(10, 5)) + + _rng = np.random.default_rng(0) + _rx, _ry = _rng.normal(size=_n), _rng.normal(size=_n) + + for _ax, (_px, _py), _title in [ + (_axes[0], (_rx, _ry), "Random layout"), + ( + _axes[1], + (_x, _y), + f"Spectral layout (eigenvectors {evec_x.value}, {evec_y.value})", + ), + ]: + for _i in range(_n): + for _j in range(_i + 1, _n): + if adjacency_matrix[_i, _j] > 0: + _ax.plot( + [_px[_i], _px[_j]], + [_py[_i], _py[_j]], + color="gray", + linewidth=0.5, + alpha=0.3, + ) + _ax.scatter(_px, _py, s=30, c=_color, cmap="coolwarm", zorder=3) + _ax.set_title(_title) + _ax.set_aspect("equal") + _ax.axis("off") + + plt.tight_layout() + plt.gca() + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + ### Eigenvalue spectrum + + Each eigenvalue of $L$ measures how much the corresponding eigenvector + varies across edges. An eigenvector with a small eigenvalue assigns similar + values to connected nodes; one with a large eigenvalue changes sharply + between neighbors. The plot below shows the spectrum, with the selected + eigenvectors highlighted. + """) + return + + +@app.cell(hide_code=True) +def _(eigenvalues, evec_x, evec_y, plt): + _fig, _ax = plt.subplots(figsize=(6, 3)) + _ax.bar( + range(len(eigenvalues)), + eigenvalues, + color="lightgray", + edgecolor="gray", + linewidth=0.5, + ) + for _idx in [evec_x.value, evec_y.value]: + _ax.bar( + _idx, + eigenvalues[_idx], + color="royalblue", + edgecolor="gray", + linewidth=0.5, + ) + _ax.set_xlabel("index") + _ax.set_ylabel(r"eigenvalue $\lambda_i$") + _ax.set_title("Laplacian spectrum") + plt.tight_layout() + plt.gca() + return + + +if __name__ == "__main__": + app.run() From 15602ec1839669c38b1ae325001978454ef9de3a Mon Sep 17 00:00:00 2001 From: Akshay Agrawal Date: Fri, 3 Apr 2026 09:28:43 -0700 Subject: [PATCH 2/3] Use /wasm links for graph notebooks in README --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 06a2b86..ee028af 100644 --- a/README.md +++ b/README.md @@ -114,9 +114,9 @@ uvx marimo edit --sandbox | RPSLS Math | Explore balanced tournament graphs for Rock-Paper-Scissors variants. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/rpsls-math/notebook.py) | | ChartPuck Circle | Explore how complex functions transform circles interactively. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/chartpuck-circle.py) | | Droste Zoom | Simulate the Droste zoom effect with log-polar transforms. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/zooming.py) | -| Graph Laplacian | Spectral clustering with graph Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_laplacian.py) | -| Spectral Graph Drawing | Draw graphs using Laplacian eigenvectors as node coordinates. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/spectral_graph_drawing.py) | -| Graph Signal Denoising | Denoise graph signals by projecting onto smooth Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_signal_denoising.py) | +| Graph Laplacian | Spectral clustering with graph Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_laplacian.py/wasm) | +| Spectral Graph Drawing | Draw graphs using Laplacian eigenvectors as node coordinates. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/spectral_graph_drawing.py/wasm) | +| Graph Signal Denoising | Denoise graph signals by projecting onto smooth Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_signal_denoising.py/wasm) | | Low-Rank Approximation | Interactive image compression with low-rank SVD. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/low_rank_approximation.py) | ## Custom UI elements with Anywidget From d37f5928191d75058daec31505d71b96d0989cfe Mon Sep 17 00:00:00 2001 From: Akshay Agrawal Date: Fri, 3 Apr 2026 09:30:08 -0700 Subject: [PATCH 3/3] Fix graph signal denoising description in README --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ee028af..bf14053 100644 --- a/README.md +++ b/README.md @@ -116,7 +116,7 @@ uvx marimo edit --sandbox | Droste Zoom | Simulate the Droste zoom effect with log-polar transforms. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/zooming.py) | | Graph Laplacian | Spectral clustering with graph Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_laplacian.py/wasm) | | Spectral Graph Drawing | Draw graphs using Laplacian eigenvectors as node coordinates. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/spectral_graph_drawing.py/wasm) | -| Graph Signal Denoising | Denoise graph signals by projecting onto smooth Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_signal_denoising.py/wasm) | +| Graph Signal Denoising | Denoise graph signals by projecting onto Laplacian eigenvectors. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/graph_signal_denoising.py/wasm) | | Low-Rank Approximation | Interactive image compression with low-rank SVD. | [![Open in molab](https://marimo.io/molab-shield.svg)](https://molab.marimo.io/github/marimo-team/gallery-examples/blob/main/notebooks/math/low_rank_approximation.py) | ## Custom UI elements with Anywidget