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March 19, 2026 12:07
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KaTeX mathml's position problem
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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>KaTeX Scroll Issue Demo</title> | |
| <link rel="stylesheet" href="dist/katex.min.css"> | |
| <script defer src="dist/katex.min.js"></script> | |
| <script defer src="dist/contrib/auto-render.min.js" | |
| onload="renderMathInElement(document.body)"></script> | |
| <style> | |
| body { | |
| font-family: Arial, sans-serif; | |
| margin: 0; | |
| padding: 20px; | |
| } | |
| h1 { font-size: 1.4rem; margin-bottom: 16px; } | |
| h2 { font-size: 1.1rem; margin: 0 0 8px; } | |
| .container { | |
| display: flex; | |
| gap: 24px; | |
| } | |
| .panel { | |
| flex: 1; | |
| background: #fff; | |
| border: 1px solid #ccc; | |
| border-radius: 4px; | |
| overflow: hidden; | |
| } | |
| .panel-header { | |
| padding: 8px 12px; | |
| font-weight: bold; | |
| border-bottom: 1px solid #ccc; | |
| } | |
| .scroll-area { | |
| max-height: 50vh; | |
| overflow: auto; | |
| padding: 12px; | |
| } | |
| .content-block { | |
| margin-bottom: 12px; | |
| line-height: 1.8; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <h1>KaTeX Scroll Issue Demo</h1> | |
| <div class="container"> | |
| <div class="panel"> | |
| <div class="scroll-area"> | |
| <div class="content-block"> | |
| <h2>Probability Distributions</h2> | |
| <p>Probability mass function of the binomial distribution: $$P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}$$</p> | |
| <p>The expected value is $$E[X] = np$$ and the variance is $$\text{Var}(X) = np(1-p)$$.</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Fundamental Equations of Physics</h2> | |
| <p>Einstein's mass-energy equivalence: $$E = mc^2$$</p> | |
| <p>Schrödinger equation: $$i\hbar\frac{\partial}{\partial t}\Psi = \hat{H}\Psi$$</p> | |
| <p>Maxwell's equation: $$\nabla \cdot \mathbf{E} = \frac{\rho}{\varepsilon_0}$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Integrals</h2> | |
| <p>Gaussian integral: $$\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}$$</p> | |
| <p>Euler's formula: $$e^{i\theta} = \cos\theta + i\sin\theta$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Probability Distributions</h2> | |
| <p>Probability mass function of the binomial distribution: $$P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}$$</p> | |
| <p>The expected value is $$E[X] = np$$ and the variance is $$\text{Var}(X) = np(1-p)$$.</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Fundamental Equations of Physics</h2> | |
| <p>Einstein's mass-energy equivalence: $$E = mc^2$$</p> | |
| <p>Schrödinger equation: $$i\hbar\frac{\partial}{\partial t}\Psi = \hat{H}\Psi$$</p> | |
| <p>Maxwell's equation: $$\nabla \cdot \mathbf{E} = \frac{\rho}{\varepsilon_0}$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Integrals</h2> | |
| <p>Gaussian integral: $$\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}$$</p> | |
| <p>Euler's formula: $$e^{i\theta} = \cos\theta + i\sin\theta$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Probability Distributions</h2> | |
| <p>Probability mass function of the binomial distribution: $$P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}$$</p> | |
| <p>The expected value is $$E[X] = np$$ and the variance is $$\text{Var}(X) = np(1-p)$$.</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Fundamental Equations of Physics</h2> | |
| <p>Einstein's mass-energy equivalence: $$E = mc^2$$</p> | |
| <p>Schrödinger equation: $$i\hbar\frac{\partial}{\partial t}\Psi = \hat{H}\Psi$$</p> | |
| <p>Maxwell's equation: $$\nabla \cdot \mathbf{E} = \frac{\rho}{\varepsilon_0}$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Integrals</h2> | |
| <p>Gaussian integral: $$\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}$$</p> | |
| <p>Euler's formula: $$e^{i\theta} = \cos\theta + i\sin\theta$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Probability Distributions</h2> | |
| <p>Probability mass function of the binomial distribution: $$P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}$$</p> | |
| <p>The expected value is $$E[X] = np$$ and the variance is $$\text{Var}(X) = np(1-p)$$.</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Fundamental Equations of Physics</h2> | |
| <p>Einstein's mass-energy equivalence: $$E = mc^2$$</p> | |
| <p>Schrödinger equation: $$i\hbar\frac{\partial}{\partial t}\Psi = \hat{H}\Psi$$</p> | |
| <p>Maxwell's equation: $$\nabla \cdot \mathbf{E} = \frac{\rho}{\varepsilon_0}$$</p> | |
| </div> | |
| <div class="content-block"> | |
| <h2>Integrals</h2> | |
| <p>Gaussian integral: $$\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}$$</p> | |
| <p>Euler's formula: $$e^{i\theta} = \cos\theta + i\sin\theta$$</p> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </body> | |
| </html> |
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