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authorMiodrag Milanovic <mmicko@gmail.com>2021-01-02 10:15:39 +0100
committerMiodrag Milanovic <mmicko@gmail.com>2021-01-02 10:15:39 +0100
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parentc6cdf30501dcb2da01361229dd66a05dad73a132 (diff)
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Update pybind11 to version 2.6.1
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-rw-r--r--3rdparty/pybind11/docs/advanced/cast/eigen.rst2
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diff --git a/3rdparty/pybind11/docs/advanced/cast/eigen.rst b/3rdparty/pybind11/docs/advanced/cast/eigen.rst
index 59ba08c3..e01472d5 100644
--- a/3rdparty/pybind11/docs/advanced/cast/eigen.rst
+++ b/3rdparty/pybind11/docs/advanced/cast/eigen.rst
@@ -274,7 +274,7 @@ Vectors versus column/row matrices
Eigen and numpy have fundamentally different notions of a vector. In Eigen, a
vector is simply a matrix with the number of columns or rows set to 1 at
-compile time (for a column vector or row vector, respectively). Numpy, in
+compile time (for a column vector or row vector, respectively). NumPy, in
contrast, has comparable 2-dimensional 1xN and Nx1 arrays, but *also* has
1-dimensional arrays of size N.