Update README.md (#99)

Fix paths to header files in the documentation.

Author: fbleibel-g

README.md

@@ -174,7 +174,7 @@ array<uint8_t, chunky_image_shape<3>> my_chunky_image({1920, 1080, {}});
 ```
 
 `strided_dim<>` is another alias for `dim<>` where the min and extent are unknown, and the stride may be a compile-time constant.
-[`image.h`](image.h) is a small helper library of typical image shape and object types defined using arrays, including `chunky_image_shape`.
+[`image.h`](include/array/image.h) is a small helper library of typical image shape and object types defined using arrays, including `chunky_image_shape`.
 
 Another common example is matrices indexed `(row, column)` with the column dimension stored densely:
 ```c++
@@ -203,7 +203,7 @@ small_matrix<float, 4, 4> my_small_matrix;
 // happen. sizeof(small_matrix) = sizeof(float) * 4 * 4 + (overhead)
 ```
 
-[`matrix.h`](matrix.h) is a small helper library of typical matrix shape and object types defined using arrays, including the examples above.
+[`matrix.h`](include/array/matrix.h) is a small helper library of typical matrix shape and object types defined using arrays, including the examples above.
 
 ### Slicing, cropping, and splitting
 
@@ -250,7 +250,7 @@ This allows potentially significant optimizations to be expressed relatively eas
 
 ### Einstein reductions
 
-The [`ein_reduce.h`](ein_reduce.h) header provides [Einstein notation](https://en.wikipedia.org/wiki/Einstein_notation) reductions and summation helpers, similar to [np.einsum](https://numpy.org/doc/stable/reference/generated/numpy.einsum.html) or [tf.einsum](https://www.tensorflow.org/api_docs/python/tf/einsum).
+The [`ein_reduce.h`](include/array/ein_reduce.h) header provides [Einstein notation](https://en.wikipedia.org/wiki/Einstein_notation) reductions and summation helpers, similar to [np.einsum](https://numpy.org/doc/stable/reference/generated/numpy.einsum.html) or [tf.einsum](https://www.tensorflow.org/api_docs/python/tf/einsum).
 These are zero-cost abstractions for describing loops that allow expressing a wide variety of array operations.
 Einstein notation expression operands are constructed using the `ein<i, j, ...>(x)` helper function, where `x` can be any callable object, including an `array<>` or `array_ref<>`.
 `i, j, ...` are `constexpr` integers indicating which dimensions of the reduction operation are used to evaluate `x`.