Add initializer_list-based constructors

Author: SylvainCorlay

.appveyor.yml

@@ -24,7 +24,7 @@ install:
   - conda info -a
   - conda install pytest -c conda-forge
   - cd test
-  - conda install xtensor==0.5.0 pytest numpy pybind11==2.0.1 -c conda-forge
+  - conda install xtensor==0.6.0 pytest numpy pybind11==2.0.1 -c conda-forge
   - xcopy /S %APPVEYOR_BUILD_FOLDER%\include %MINICONDA%\include
 
 build_script:

.travis.yml

@@ -59,7 +59,7 @@ install:
     # Useful for debugging any issues with conda
     - conda info -a
     - cd test
-    - conda install xtensor==0.5.0 pytest numpy pybind11==2.0.1 -c conda-forge
+    - conda install xtensor==0.6.0 pytest numpy pybind11==2.0.1 -c conda-forge
     - cp -r $TRAVIS_BUILD_DIR/include/* $HOME/miniconda/include/
 
 script:

README.md

@@ -29,7 +29,8 @@ conda install -c conda-forge xtensor-python
 
 | `xtensor-python`  | `xtensor`  |  `pybind11` |
 |-------------------|------------|-------------|
-| master            |   0.5.0    | ^2.0.0      |
+| master            |   0.6.0    | ^2.0.0      |
+| 0.5.0             |   0.5.0    | ^2.0.0      |
 | 0.4.0             |   0.5.0    | ^2.0.0      |
 | 0.3.0             |  ^0.4.1    | ^2.0.0      |
 | 0.2.0             |  ^0.2.1    | ^1.8.1      |

include/xtensor-python/pyarray.hpp

@@ -108,6 +108,7 @@ namespace xt
         using semantic_base = xcontainer_semantic<self_type>;
         using base_type = pycontainer<self_type>;
         using container_type = typename base_type::container_type;
+        using value_type = typename base_type::value_type; 
         using pointer = typename base_type::pointer;
         using size_type = typename base_type::size_type;
         using shape_type = typename base_type::shape_type;
@@ -117,6 +118,12 @@ namespace xt
         using inner_strides_type = typename base_type::inner_strides_type;
 
         pyarray() = default;
+        pyarray(const value_type& t);
+        pyarray(nested_initializer_list_t<T, 1> t);
+        pyarray(nested_initializer_list_t<T, 2> t);
+        pyarray(nested_initializer_list_t<T, 3> t);
+        pyarray(nested_initializer_list_t<T, 4> t);
+        pyarray(nested_initializer_list_t<T, 5> t);
 
         pyarray(pybind11::handle h, pybind11::object::borrowed_t);
         pyarray(pybind11::handle h, pybind11::object::stolen_t);
@@ -179,6 +186,48 @@ namespace xt
      * pyarray implementation *
      **************************/
 
+    template <class T>
+    inline pyarray<T>::pyarray(const value_type& t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
+    template <class T>
+    inline pyarray<T>::pyarray(nested_initializer_list_t<T, 1> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
+    template <class T>
+    inline pyarray<T>::pyarray(nested_initializer_list_t<T, 2> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
+    template <class T>
+    inline pyarray<T>::pyarray(nested_initializer_list_t<T, 3> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
+    template <class T>
+    inline pyarray<T>::pyarray(nested_initializer_list_t<T, 4> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
+    template <class T>
+    inline pyarray<T>::pyarray(nested_initializer_list_t<T, 5> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
     template <class T>
     inline pyarray<T>::pyarray(pybind11::handle h, pybind11::object::borrowed_t)
         : base_type(h, pybind11::object::borrowed)

include/xtensor-python/pytensor.hpp

@@ -12,6 +12,7 @@
 #include <cstddef>
 #include <array>
 #include <algorithm>
+#include "xtensor/xutils.hpp"
 #include "xtensor/xsemantic.hpp"
 #include "xtensor/xiterator.hpp"
 
@@ -83,6 +84,7 @@ namespace xt
         using semantic_base = xcontainer_semantic<self_type>;
         using base_type = pycontainer<self_type>;
         using container_type = typename base_type::container_type;
+        using value_type = typename base_type::value_type; 
         using pointer = typename base_type::pointer;
         using size_type = typename base_type::size_type;
         using shape_type = typename base_type::shape_type;
@@ -92,7 +94,7 @@ namespace xt
         using inner_strides_type = typename base_type::inner_strides_type;
 
         pytensor() = default;
-
+        pytensor(nested_initializer_list_t<T, N> t);
         pytensor(pybind11::handle h, pybind11::object::borrowed_t);
         pytensor(pybind11::handle h, pybind11::object::stolen_t);
         pytensor(const pybind11::object &o);
@@ -137,6 +139,13 @@ namespace xt
      * pytensor implementation *
      ***************************/
 
+    template <class T, std::size_t N>
+    inline pytensor<T, N>::pytensor(nested_initializer_list_t<T, N> t)
+    {
+        base_type::reshape(xt::shape<shape_type>(t), layout::row_major);
+        nested_copy(m_data.begin(), t);
+    }
+
     template <class T, std::size_t N>
     inline pytensor<T, N>::pytensor(pybind11::handle h, pybind11::object::borrowed_t)
         : base_type(h, pybind11::object::borrowed)

test/main.cpp

@@ -11,19 +11,19 @@ using complex_t = std::complex<double>;
 
 // Examples
 
-double example1(xt::pyarray<double> &m)
+double example1(xt::pyarray<double>& m)
 {
     return m(0);
 }
 
-xt::pyarray<double> example2(xt::pyarray<double> &m)
+xt::pyarray<double> example2(xt::pyarray<double>& m)
 {
     return m + 2;
 }
 
 // Readme Examples
 
-double readme_example1(xt::pyarray<double> &m)
+double readme_example1(xt::pyarray<double>& m)
 {
     auto sines = xt::sin(m);
     return std::accumulate(sines.begin(), sines.end(), 0.0);

test/test_pyarray.py

@@ -16,32 +16,27 @@
 class ExampleTest(TestCase):
 
     def test_example1(self):
-        print("test1")
         self.assertEqual(4, xt.example1([4, 5, 6]))
 
     def test_example2(self):
-        print("test2")
         x = np.array([[0., 1.], [2., 3.]])
         res = np.array([[2., 3.], [4., 5.]])
         y = xt.example2(x)
         np.testing.assert_allclose(y, res, 1e-12)
 
     def test_vectorize(self):
-        print("test3")
         x1 = np.array([[0, 1], [2, 3]])
         x2 = np.array([0, 1])
         res = np.array([[0, 2], [2, 4]])
         y = xt.vectorize_example1(x1, x2)
         np.testing.assert_array_equal(y, res)
 
     def test_readme_example1(self):
-        print("test4")
         v = np.arange(15).reshape(3, 5)
         y = xt.readme_example1(v)
         np.testing.assert_allclose(y, 1.2853996391883833, 1e-12)
 
     def test_readme_example2(self):
-        print("test5")
         x = np.arange(15).reshape(3, 5)
         y = [1, 2, 3, 4, 5]
         z = xt.readme_example2(x, y)
@@ -51,7 +46,6 @@ def test_readme_example2(self):
              [-1.084323, -0.583843,  0.45342 ,  1.073811,  0.706945]], 1e-5)
 
     def test_rect_to_polar(self):
-        print("test6")
         x = np.ones(10, dtype=complex)
         z = xt.rect_to_polar(x[::2]);
         np.testing.assert_allclose(z, (np.ones(5, dtype=float), np.zeros(5, dtype=float)), 1e-5)