From d7d1357369be0f71bcfe172df5568382d624c060 Mon Sep 17 00:00:00 2001 From: Niru Maheswaranathan Date: Sat, 17 May 2025 11:10:51 -0700 Subject: [PATCH] Fix typos in comments --- jetplot/plots.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/jetplot/plots.py b/jetplot/plots.py index 9a37a78..1061e66 100644 --- a/jetplot/plots.py +++ b/jetplot/plots.py @@ -340,7 +340,7 @@ def ellipse(x, y, n_std=3.0, facecolor="none", estimator="empirical", **kwargs): pearson = cov[0, 1] / np.sqrt(cov[0, 0] * cov[1, 1]) # Using a special case to obtain the eigenvalues of this - # two-dimensionl dataset. + # two-dimensional dataset. ell_radius_x = np.sqrt(1 + pearson) ell_radius_y = np.sqrt(1 - pearson) ellipse = Ellipse( @@ -351,13 +351,13 @@ def ellipse(x, y, n_std=3.0, facecolor="none", estimator="empirical", **kwargs): **kwargs, ) - # Calculating the stdandard deviation of x from - # the squareroot of the variance and multiplying + # Calculating the standard deviation of x from + # the square root of the variance and multiplying # with the given number of standard deviations. scale_x = np.sqrt(cov[0, 0]) * n_std mean_x = np.mean(x) - # calculating the stdandard deviation of y ... + # calculating the standard deviation of y ... scale_y = np.sqrt(cov[1, 1]) * n_std mean_y = np.mean(y)