Merge branch 'experimental' into inverse

.gitignore

@@ -9,7 +9,14 @@
 *.py
 mojo
 numojo.mojopkg
-.gitignore
 bench.mojo
 test_ndarray.ipynb
-/venv
+/venv# pixi environments
+.pixi
+*.egg-info
+
+# magic environments
+.magic
+
+.gitattributes
+.gitignore

CONTRIBUTING.md

@@ -10,7 +10,7 @@ Please follow the Mojo standard library style guide for all contributions. Consi
 - Write concise, well-documented code.
 - Adhere to formatting conventions for indentation, spacing, and line breaks.
 
-Additionally refer to `style guide.md` for docstring and nameing conventions.
+Additionally refer to `style guide.md` for docstring and naming conventions.
 
 ## Pull Requests
 
@@ -50,16 +50,20 @@ Following this structure ensures that similar functionalities are grouped togeth
    ```
 
 4. **Make Your Changes**: Implement your changes in your branch.
-5. **Commit Your Changes**: Commit your changes with a clear and descriptive commit message.
+5. **Run Tests**: NuMojo now uses the `Magic` package manager by Modular. To ensure that all unit tests pass, the NuMojo module packages correctly, and the .mojo files are properly formatted, run the following command:
+   ```sh
+   magic run final
+   ```
+6. **Commit Your Changes**: Commit your changes with a clear and descriptive commit message.
 
    ```sh
    git commit -m "Add feature XYZ"
    ```
 
-6. **Push Your Changes**: Push your branch to your fork on GitHub.
+7. **Push Your Changes**: Push your branch to your fork on GitHub.
 
    ```sh
    git push origin feature-name
    ```
 
-7. **Submit a Pull Request**: Open a pull request to the `main` branch of the original repository.
+8. **Submit a Pull Request**: Open a pull request to the `main` branch of the original repository.

mojoproject.toml

@@ -0,0 +1,27 @@
+[project]
+name = "NuMojo"
+version = "0.2.0"
+description = "NuMojo is a library for numerical computing written in Mojo 🔥"
+authors = [
+    "Shivasankar <shivasankar.ka@gmail.com>",
+    "MadAlex1997 <>",
+    "Yuhao Zhu <>",
+    "mmenendezg <>",
+    "sandstromviktor <>",
+]
+channels = ["conda-forge", "https://conda.modular.com/max"]
+platforms = ["osx-arm64", "linux-64"]
+license = "Apache-2.0"
+readme = "README.md"
+
+[tasks]
+# test whether tests pass and the package can be built
+test = " magic run mojo test tests -I ./ && magic run mojo package numojo"
+# runs all final checks before a commit
+final = "magic run mojo test tests -I ./ && magic run mojo format ./ && magic run mojo package numojo"
+# defaults tasks
+package = "magic run mojo package numojo"
+format = "magic run mojo format ./"
+
+[dependencies]
+max = ">=24.4.0,<25"

numojo/core/_array_funcs.mojo

@@ -27,16 +27,16 @@ fn math_func_1_array_in_one_array_out[
         A new NDArray that is the result of applying the function to the NDArray.
     """
     var result_array: NDArray[dtype] = NDArray[dtype](array.shape())
-    alias opt_nelts = simdwidthof[dtype]()
+    alias width = simdwidthof[dtype]()
 
     @parameter
-    fn closure[simdwidth: Int](i: Int):
-        var simd_data = array.load[width=opt_nelts](i)
-        result_array.store[width=opt_nelts](
-            i, func[dtype, opt_nelts](simd_data)
+    fn closure[simd_width: Int](i: Int):
+        var simd_data = array.load[width=simd_width](i)
+        result_array.store[width=simd_width](
+            i, func[dtype, simd_width](simd_data)
         )
 
-    vectorize[closure, opt_nelts](array.num_elements())
+    vectorize[closure, width](array.num_elements())
 
     return result_array
 
@@ -69,17 +69,18 @@ fn math_func_2_array_in_one_array_out[
         raise Error("Shape Mismatch error shapes must match for this function")
 
     var result_array: NDArray[dtype] = NDArray[dtype](array1.shape())
-    alias opt_nelts = simdwidthof[dtype]()
+    alias width = simdwidthof[dtype]()
 
     @parameter
-    fn closure[simdwidth: Int](i: Int):
-        var simd_data1 = array1.load[width=opt_nelts](i)
-        var simd_data2 = array2.load[width=opt_nelts](i)
-        result_array.store[width=opt_nelts](
-            i, func[dtype, opt_nelts](simd_data1, simd_data2)
+    fn closure[simd_width: Int](i: Int):
+        var simd_data1 = array1.load[width=simd_width](i)
+        var simd_data2 = array2.load[width=simd_width](i)
+        result_array.store[width=simd_width](
+            i, func[dtype, simd_width](simd_data1, simd_data2)
         )
 
-    vectorize[closure, opt_nelts](result_array.num_elements())
+    vectorize[closure, width](result_array.num_elements())
+
     return result_array
 
 
@@ -105,14 +106,14 @@ fn math_func_one_array_one_SIMD_in_one_array_out[
     """
 
     var result_array: NDArray[dtype] = NDArray[dtype](array.shape())
-    alias opt_nelts = simdwidthof[dtype]()
+    alias width = simdwidthof[dtype]()
 
     @parameter
-    fn closure[simdwidth: Int](i: Int):
-        var simd_data1 = array.load[width=opt_nelts](i)
-        result_array.store[width=opt_nelts](
-            i, func[dtype, opt_nelts](simd_data1, scalar)
+    fn closure[simd_width: Int](i: Int):
+        var simd_data1 = array.load[width=simd_width](i)
+        result_array.store[width=simd_width](
+            i, func[dtype, simd_width](simd_data1, scalar)
         )
 
-    vectorize[closure, opt_nelts](result_array.num_elements())
+    vectorize[closure, width](result_array.num_elements())
     return result_array