@@ -41,7 +41,7 @@ consideration: by default, numpy matrices and eigen matrices are *not* storage
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compatible.
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If the numpy matrix cannot be used as is (either because its types differ, e.g.
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- passing an array of integers to an Eigen paramater requiring doubles, or
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+ passing an array of integers to an Eigen parameter requiring doubles, or
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because the storage is incompatible), pybind11 makes a temporary copy and
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passes the copy instead.
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@@ -89,7 +89,7 @@ as dictated by the binding function's return value policy (see the
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documentation on :ref: `return_value_policies ` for full details). That means,
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without an explicit return value policy, lvalue references will be copied and
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pointers will be managed by pybind11. In order to avoid copying, you should
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- explictly specify an appropriate return value policy, as in the following
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+ explicitly specify an appropriate return value policy, as in the following
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example:
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.. code-block :: cpp
@@ -287,7 +287,7 @@ On the other hand, pybind11 allows you to pass 1-dimensional arrays of length N
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as Eigen parameters. If the Eigen type can hold a column vector of length N it
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will be passed as such a column vector. If not, but the Eigen type constraints
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will accept a row vector, it will be passed as a row vector. (The column
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- vector takes precendence when both are supported, for example, when passing a
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+ vector takes precedence when both are supported, for example, when passing a
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1D numpy array to a MatrixXd argument). Note that the type need not be
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expicitly a vector: it is permitted to pass a 1D numpy array of size 5 to an
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Eigen ``Matrix<double, Dynamic, 5> ``: you would end up with a 1x5 Eigen matrix.
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