With reference to issue dask#3663

exit()

exit
logout
exit()
exit

dask/array/slicing.py

@@ -1242,14 +1242,36 @@ def cached_cumsum(seq, initial_zero=False):
         result = result[1:]
     return result
 
-
-def take_along_axis(arr,indices,axis):
-    if axis is None:
-      arr=arr.flat
-      arr_shape=(len(arr),)
-      axis=0
-    arr=np.array(arr)
-    indices=np.array()
-    if np.shape(arr)!=np.shape(indices):
-      raise ValueError('Dimensions of arr and indices does not match ')
-
+def take_along_axis(arr,indices,axis=None):
+ out_d=np.array([]) #creating a new empty array to store the value of result
+ arr=np.array(arr)
+ indices=np.array(indices)
+ if arr.shape != indices.ndim:
+        raise ValueError(
+            "`indices` and `arr` must have the same number of dimensions")
+
+ for integer in indices:
+  if not isinstance(integer,int):
+    raiseIndexError('indices must be an integer array')
+ if axis is None:
+    arr=arr.flatten
+    arr_shape=(np.prod((arr.shape),)
+    axis = 0
+ Ni, M, Nk=arr.shape[:axis], arr.shape[axis], arr.shape[axis+1:]
+ j=indices.shape[axis]
+ out=np.empty(Ni+ (j,)+Nk)
+ for i in np.ndindex(Ni):
+  for k in np.ndindex(Nk):
+   a_1d = a[i+np.s_[:,]+ k]
+   indices_1d=indices[i+np.s_[:,]+k]
+   out_1d= out[i+np.s_[:,]+k]
+   out_1d[:]=a_1d[indices_1d]
+   out_d=np.append(out_d,out_1d,axis=0)
+ out_d=np.reshape(out_d,arr.shape)   
+ return(da.from_array(out_d))
+"""    
+a =np.array([[10, 30, 20], [60, 40, 50]])
+ai=np.array([[0, 2, 1],[1, 2, 0]])      
+y=take_along_axis(a,ai,axis=0)
+print(y.compute())
+"""