formatted and fixed typos

Author: shivasankarka

numojo/core/array_creation_routines.mojo

@@ -51,15 +51,18 @@ fn arange[
         is_inttype[in_dtype]() and is_inttype[out_dtype]()
     ):
         raise Error(
-            "Both input and output datatypes cannot be integers. If the input is a float, the output must also be a float."
+            "Both input and output datatypes cannot be integers. If the input"
+            " is a float, the output must also be a float."
         )
 
     var num: Int = ((stop - start) / step).__int__()
     var result: NDArray[out_dtype] = NDArray[out_dtype](
         NDArrayShape(num, size=num)
     )
     for idx in range(num):
-        result.data[idx] = start.cast[out_dtype]() + step.cast[out_dtype]() * idx
+        result.data[idx] = (
+            start.cast[out_dtype]() + step.cast[out_dtype]() * idx
+        )
 
     return result
 
@@ -104,7 +107,8 @@ fn linspace[
         is_floattype[in_dtype]() and is_inttype[out_dtype]()
     ):
         raise Error(
-            "Both input and output datatypes cannot be integers. If the input is a float, the output must also be a float."
+            "Both input and output datatypes cannot be integers. If the input"
+            " is a float, the output must also be a float."
         )
 
     if parallel:
@@ -237,7 +241,8 @@ fn logspace[
         is_floattype[in_dtype]() and is_inttype[out_dtype]()
     ):
         raise Error(
-            "Both input and output datatypes cannot be integers. If the input is a float, the output must also be a float."
+            "Both input and output datatypes cannot be integers. If the input"
+            " is a float, the output must also be a float."
         )
     if parallel:
         return _logspace_parallel[out_dtype](
@@ -376,7 +381,8 @@ fn geomspace[
         is_floattype[in_dtype]() and is_inttype[out_dtype]()
     ):
         raise Error(
-            "Both input and output datatypes cannot be integers. If the input is a float, the output must also be a float."
+            "Both input and output datatypes cannot be integers. If the input"
+            " is a float, the output must also be a float."
         )
 
     var a: Scalar[out_dtype] = start.cast[out_dtype]()

numojo/core/array_manipulation_routines.mojo

@@ -1,14 +1,15 @@
 """
 # ===----------------------------------------------------------------------=== #
 # ARRAY MANIPULATION ROUTINES
-# Last updated: 2024-07-21
+# Last updated: 2024-08-03
 # ===----------------------------------------------------------------------=== #
 """
 
 
 fn copyto():
     pass
 
+
 fn ndim[dtype: DType](array: NDArray[dtype]) -> Int:
     """
     Returns the number of dimensions of the NDArray.
@@ -34,6 +35,7 @@ fn shape[dtype: DType](array: NDArray[dtype]) -> NDArrayShape:
     """
     return array.ndshape
 
+
 fn size[dtype: DType](array: NDArray[dtype], axis: Int) raises -> Int:
     """
     Returns the size of the NDArray.
@@ -47,7 +49,12 @@ fn size[dtype: DType](array: NDArray[dtype], axis: Int) raises -> Int:
     """
     return array.ndshape[axis]
 
-fn reshape[dtype: DType](inout array: NDArray[dtype], shape: VariadicList[Int], order: String = "C") raises:
+
+fn reshape[
+    dtype: DType
+](
+    inout array: NDArray[dtype], shape: VariadicList[Int], order: String = "C"
+) raises:
     """
         Reshapes the NDArray to given Shape.
 
@@ -58,7 +65,7 @@ fn reshape[dtype: DType](inout array: NDArray[dtype], shape: VariadicList[Int],
         array: A NDArray.
         shape: Variadic integers of shape.
         order: Order of the array - Row major `C` or Column major `F`.
-    
+
     """
     var num_elements_new: Int = 1
     var ndim_new: Int = 0
@@ -81,26 +88,32 @@ fn reshape[dtype: DType](inout array: NDArray[dtype], shape: VariadicList[Int],
     array.stride = NDArrayStride(shape=shape_new, order=order)
     array.order = order
 
+
 fn ravel[dtype: DType](inout array: NDArray[dtype], order: String = "C") raises:
     """
     Returns the raveled version of the NDArray.
     """
     if array.ndim == 1:
         print("Array is already 1D")
-        return 
+        return
     else:
         if order == "C":
             reshape[dtype](array, array.ndshape._size, order="C")
         else:
             reshape[dtype](array, array.ndshape._size, order="F")
 
-fn where[dtype: DType](inout x: NDArray[dtype], scalar: SIMD[dtype, 1], mask:NDArray[DType.bool]) raises:
+
+fn where[
+    dtype: DType
+](
+    inout x: NDArray[dtype], scalar: SIMD[dtype, 1], mask: NDArray[DType.bool]
+) raises:
     """
     Replaces elements in `x` with `scalar` where `mask` is True.
 
     Parameters:
         dtype: DType.
-    
+
     Args:
         x: A NDArray.
         scalar: A SIMD value.
@@ -111,8 +124,11 @@ fn where[dtype: DType](inout x: NDArray[dtype], scalar: SIMD[dtype, 1], mask:NDA
         if mask.data[i] == True:
             x.data.store(i, scalar)
 
+
 # TODO: do it with vectorization
-fn where[dtype: DType](inout x: NDArray[dtype], y: NDArray[dtype], mask:NDArray[DType.bool]) raises:
+fn where[
+    dtype: DType
+](inout x: NDArray[dtype], y: NDArray[dtype], mask: NDArray[DType.bool]) raises:
     """
     Replaces elements in `x` with elements from `y` where `mask` is True.
 
@@ -121,7 +137,7 @@ fn where[dtype: DType](inout x: NDArray[dtype], y: NDArray[dtype], mask:NDArray[
 
     Parameters:
         dtype: DType.
-    
+
     Args:
         x: NDArray[dtype].
         y: NDArray[dtype].
@@ -135,13 +151,13 @@ fn where[dtype: DType](inout x: NDArray[dtype], y: NDArray[dtype], mask:NDArray[
             x.data.store(i, y.data[i])
 
 
-fn flip[dtype: DType](inout array: NDArray[dtype]) raises -> NDArray[dtype]:
+fn flip[dtype: DType](array: NDArray[dtype]) raises -> NDArray[dtype]:
     """
     Flips the NDArray along the given axis.
 
     Parameters:
         dtype: DType.
-    
+
     Args:
         array: A NDArray.
 
@@ -151,8 +167,9 @@ fn flip[dtype: DType](inout array: NDArray[dtype]) raises -> NDArray[dtype]:
     if array.ndim != 1:
         raise Error("Flip is only supported for 1D arrays")
 
-    var result: NDArray[dtype] = NDArray[dtype](shape=array.ndshape, order=array.order)
+    var result: NDArray[dtype] = NDArray[dtype](
+        shape=array.ndshape, order=array.order
+    )
     for i in range(array.ndshape._size):
         result.data.store(i, array.data[array.ndshape._size - i - 1])
-
     return result

numojo/core/ndarray.mojo

@@ -49,7 +49,7 @@ from .ndarray_utils import (
 from ..math.math_funcs import Vectorized
 from .utility_funcs import is_inttype
 from ..math.linalg.matmul import matmul_parallelized
-from .array_manipulation_routines import reshape 
+from .array_manipulation_routines import reshape
 
 
 @register_passable("trivial")
@@ -968,7 +968,7 @@ struct NDArray[dtype: DType = DType.float32](
         if self.ndim == 1:
             narr.ndim = 0
             narr.ndshape._shape[0] = 0
-            
+
         return narr
 
     fn _adjust_slice_(self, inout span: Slice, dim: Int):
@@ -2435,7 +2435,6 @@ struct NDArray[dtype: DType = DType.float32](
         var s: VariadicList[Int] = shape
         reshape[dtype](self, s, order=order)
 
-
     fn unsafe_ptr(self) -> DTypePointer[dtype, 0]:
         return self.data
 

numojo/core/ndarray_utils.mojo

@@ -10,6 +10,7 @@ from .ndarray import NDArray, NDArrayShape, NDArrayStride
 
 # TODO: there's some problem with using narr[idx] in traverse function, Make sure to correct this before v0.1
 
+
 fn _get_index(indices: List[Int], weights: NDArrayShape) raises -> Int:
     """
     Get the index of a multi-dimensional array from a list of indices and weights.
@@ -192,10 +193,10 @@ fn to_numpy[dtype: DType](array: NDArray[dtype]) raises -> PythonObject:
     Convert a NDArray to a numpy array.
 
     Example:
-    ```console 
+    ```console
     var arr = NDArray[DType.float32](3, 3, 3)
-    var np_arr = to_numpy(arr) 
-    var np_arr1 = arr.to_numpy() 
+    var np_arr = to_numpy(arr)
+    var np_arr1 = arr.to_numpy()
     ```
 
     Parameters:

numojo/core/sort.mojo

@@ -224,11 +224,11 @@ fn _argsort_partition(
     """
 
     var pivot_value = ndarray.get_scalar(pivot_index)
-    
+
     var _value_at_pivot = ndarray.get_scalar(pivot_index)
     ndarray.__setitem__(pivot_index, ndarray.get_scalar(right))
     ndarray.__setitem__(right, _value_at_pivot)
-    
+
     var _value_at_pivot_index = idx_array.get_scalar(pivot_index)
     idx_array.__setitem__(pivot_index, idx_array.get_scalar(right))
     idx_array.__setitem__(right, _value_at_pivot_index)
@@ -240,7 +240,7 @@ fn _argsort_partition(
             var _value_at_store = ndarray.get_scalar(store_index)
             ndarray.__setitem__(store_index, ndarray.get_scalar(i))
             ndarray.__setitem__(i, _value_at_store)
-            
+
             var _value_at_store_index = idx_array.get_scalar(store_index)
             idx_array.__setitem__(store_index, idx_array.get_scalar(i))
             idx_array.__setitem__(i, _value_at_store_index)

numojo/core/utility_funcs.mojo

@@ -64,6 +64,7 @@ fn is_floattype[dtype: DType]() -> Bool:
         return True
     return False
 
+
 fn is_floattype(dtype: DType) -> Bool:
     """
     Check if the given dtype is a floating point type at run time.
@@ -80,4 +81,4 @@ fn is_floattype(dtype: DType) -> Bool:
         or dtype == DType.float64
     ):
         return True
-    return False
+    return False

numojo/math/__init__.mojo

@@ -12,4 +12,4 @@ from .math_funcs import (
     VectorizedVerbose,
     VectorizedParallelizedNWorkers,
 )
-from .interpolate import *
+from .interpolate import *