Style again (#338)

* apply style

Author: Alexander-Makaryev

dpnp/backend/backend_iface.hpp

@@ -204,7 +204,7 @@ INP_DLLEXPORT void custom_prod_c(void* array, void* result, size_t size);
  *
  * @param [out] result1   The eigenvalues, each repeated according to its multiplicity
  *
- * @param [out] result2   The normalized (unit “length”) eigenvectors
+ * @param [out] result2   The normalized (unit "length") eigenvectors
  *
  * @param [in]  size      One dimension of square [size][size] array
  *

dpnp/dpnp_iface_mathematical.py

@@ -340,10 +340,10 @@ def floor(x1, **kwargs):
     --------
         :obj:`dpnp.ceil` : Compute  the ceiling of the input, element-wise.
         :obj:`dpnp.trunc` : Return the truncated value of the input, element-wise.
-    
+
     Notes
     -----
-        Some spreadsheet programs calculate the “floor-towards-zero”, in other words floor(-2.5) == -2.
+        Some spreadsheet programs calculate the "floor-towards-zero", in other words floor(-2.5) == -2.
         dpNP instead uses the definition of floor where floor(-2.5) == -3.
 
     Examples

dpnp/dpnp_iface_trigonometric.py

@@ -593,7 +593,7 @@ def expm1(x1):
 
 def hypot(x1, x2, out=None):
     """
-    Given the “legs” of a right triangle, return its hypotenuse.
+    Given the "legs" of a right triangle, return its hypotenuse.
 
     For full documentation refer to :obj:`numpy.hypot`.
 

dpnp/linalg/linalg.pyx

@@ -51,23 +51,23 @@ __all__ = [
 
 
 # C function pointer to the C library template functions
-ctypedef void(*custom_linalg_1in_1out_func_ptr_t)(void * , void * , size_t * , size_t)
+ctypedef void(*custom_linalg_1in_1out_func_ptr_t)(void *, void * , size_t * , size_t)
 
 
 # C function pointer to the C library template functions
-ctypedef void(*custom_linalg_1in_1out_func_ptr_t_)(void *, void * , size_t * )
+ctypedef void(*custom_linalg_1in_1out_func_ptr_t_)(void * , void * , size_t * )
 
 
 # C function pointer to the C library template functions
-ctypedef void(*custom_linalg_1in_1out_with_size_func_ptr_t_)(void * , void * , size_t)
+ctypedef void(*custom_linalg_1in_1out_with_size_func_ptr_t_)(void *, void * , size_t)
 
 
 cpdef dparray dpnp_cholesky(dparray input):
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(input.dtype)
 
     cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_CHOLESKY, param1_type, param1_type)
 
-    result_type = dpnp_DPNPFuncType_to_dtype( < size_t > kernel_data.return_type)
+    result_type = dpnp_DPNPFuncType_to_dtype(< size_t > kernel_data.return_type)
     cdef dparray result = dparray(input.size, dtype=result_type)
 
     cdef custom_linalg_1in_1out_func_ptr_t_ func = <custom_linalg_1in_1out_func_ptr_t_ > kernel_data.ptr
@@ -92,7 +92,7 @@ cpdef dparray dpnp_det(dparray input):
 
     cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_DET, param1_type, param1_type)
 
-    result_type = dpnp_DPNPFuncType_to_dtype( < size_t > kernel_data.return_type)
+    result_type = dpnp_DPNPFuncType_to_dtype(< size_t > kernel_data.return_type)
     cdef dparray result = dparray(size_out, dtype=result_type)
 
     cdef custom_linalg_1in_1out_func_ptr_t func = <custom_linalg_1in_1out_func_ptr_t > kernel_data.ptr
@@ -114,7 +114,7 @@ cpdef tuple dpnp_eig(dparray x1):
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(x1.dtype)
     cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_EIG, param1_type, param1_type)
 
-    result_type = dpnp_DPNPFuncType_to_dtype( < size_t > kernel_data.return_type)
+    result_type = dpnp_DPNPFuncType_to_dtype(< size_t > kernel_data.return_type)
 
     cdef dparray res_val = dparray((size,), dtype=result_type)
     cdef dparray res_vec = dparray(x1_shape, dtype=result_type)
@@ -134,7 +134,7 @@ cpdef dparray dpnp_eigvals(dparray input):
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(input.dtype)
     cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_EIGVALS, param1_type, param1_type)
 
-    result_type = dpnp_DPNPFuncType_to_dtype( < size_t > kernel_data.return_type)
+    result_type = dpnp_DPNPFuncType_to_dtype(< size_t > kernel_data.return_type)
 
     cdef dparray res_val = dparray((size,), dtype=result_type)
 
@@ -150,7 +150,7 @@ cpdef dparray dpnp_matrix_rank(dparray input):
 
     cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_MATRIX_RANK, param1_type, param1_type)
 
-    result_type = dpnp_DPNPFuncType_to_dtype( < size_t > kernel_data.return_type)
+    result_type = dpnp_DPNPFuncType_to_dtype(< size_t > kernel_data.return_type)
     cdef dparray result = dparray((1,), dtype=result_type)
 
     cdef custom_linalg_1in_1out_func_ptr_t func = <custom_linalg_1in_1out_func_ptr_t > kernel_data.ptr
@@ -179,9 +179,9 @@ cpdef dparray dpnp_norm(dparray input, ord=None, axis=None):
 
     ndim = input.ndim
     if axis is None:
-        if ((ord is None)  or
-            (ord in ('f', 'fro') and ndim ==2) or
-            (ord == 2 and ndim == 1)):
+        if ((ord is None) or
+            (ord in ('f', 'fro') and ndim == 2) or
+                (ord == 2 and ndim == 1)):
 
             input = input.ravel(order='K')
             sqnorm = dpnp.dot(input, input)