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map_coordinates does not seem to work with order unspecified

See original GitHub issue

I’m trying to use cupyx.scipy.ndimage.map_coordinates to convert images to polar coordinates. In the documentation it says the default order is 1 when left unspecified. I was trying to use this function for polar transforming images but kept getting 0 arrays returned. Only when I explicitly set order=1 did it work:

Minimal example:

import cupy as cp
import matplotlib.pyplot as plt
import numpy as np

image = np.arange(100).reshape((10,10))
im_gpu = cp.asarray(image)
plt.imshow(image)

from cupyx.scipy.ndimage import map_coordinates

cor = cp.array([[0, 5, 9],[0, 5, 9]], dtype=cp.float32)
map_coordinates(im_gpu, cor) # returns [0 0 0] 
map_coordinates(im_gpu, cor, order=1) # returns [0 55 99]

I tried this with various dtypes of both the image and coordinate arrays with the same behavior.

Conditions

OS                           : Linux-4.12.14-197.56-default-x86_64-with-glibc2.10
CuPy Version                 : 8.5.0
NumPy Version                : 1.20.1
SciPy Version                : 1.6.0
Cython Build Version         : 0.29.22
CUDA Root                    : /u/ncautaerts/conda-envs/nielsenv
CUDA Build Version           : 11000
CUDA Driver Version          : 11000
CUDA Runtime Version         : 11000
cuBLAS Version               : 11200
cuFFT Version                : 10201
cuRAND Version               : 10201
cuSOLVER Version             : (10, 6, 0)
cuSPARSE Version             : 11101
NVRTC Version                : (11, 0)
Thrust Version               : 100909
CUB Build Version            : 100909
cuDNN Build Version          : 8100
cuDNN Version                : 8100
NCCL Build Version           : 2804
NCCL Runtime Version         : 2804
cuTENSOR Version             : 10202
Device 0 Name                : Tesla V100-PCIE-32GB
Device 0 Compute Capability  : 70
Device 1 Name                : Tesla V100-PCIE-32GB
Device 1 Compute Capability  : 70