From b9d4045fef32fc6045b58708a4cab39ed79df530 Mon Sep 17 00:00:00 2001 From: Philipenko Vladimir Date: Mon, 25 Dec 2023 15:54:42 +0300 Subject: [PATCH] Update readme --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 3fb2dad2..fad53efd 100644 --- a/README.md +++ b/README.md @@ -72,9 +72,9 @@ points = np.unique(points, axis=0) x_points = points[: n // 2] values = np.random.uniform(low=0.0, high=1.0, size=(len(x_points),)) interp_points = points[n // 2:] -n_jobs = -1 # will be equal to num of CPU cores +num_threads = -1 # will be equal to num of CPU cores # You can optionally pass your own triangulation as an np.array of shape [num_triangles, 3], element at (i, j) position is an index of a point from x_points -interpolator = Linear2DInterpolator(x_points, values, n_jobs=n_jobs, triangles=None) +interpolator = Linear2DInterpolator(x_points, values, num_threads=num_threads, triangles=None) # Also you can pass values to __call__ and rewrite the ones that were passed to __init__ interp_values = interpolator(interp_points, values + 1.0, fill_value=0.0) ```