问题描述
使用 scipy时. ndimage.interpolation.shift 使用周期性边界处理(mode = 'wrap'
)沿一个轴移动numpy数据数组,我得到了意外的行为.该例程尝试强制第一个像素(index 0
)与最后一个像素(index N-1
)相同,而不是最后一个加一个(index N
)".
When using scipy.ndimage.interpolation.shift to shift a numpy data array along one axis with periodic boundary treatment (mode = 'wrap'
), I get an unexpected behavior. The routine tries to force the first pixel (index 0
) to be identical to the last one (index N-1
) instead of the "last plus one (index N
)".
最小示例:
# module import
import numpy as np
from scipy.ndimage.interpolation import shift
import matplotlib.pyplot as plt
# print scipy.__version__
# 0.18.1
a = range(10)
plt.figure(figsize=(16,12))
for i, shift_pix in enumerate(range(10)):
# shift the data via spline interpolation
b = shift(a, shift=shift_pix, mode='wrap')
# plotting the data
plt.subplot(5,2,i+1)
plt.plot(a, marker='o', label='data')
plt.plot(np.roll(a, shift_pix), marker='o', label='data, roll')
plt.plot(b, marker='o',label='shifted data')
if i == 0:
plt.legend(loc=4,fontsize=12)
plt.ylim(-1,10)
ax = plt.gca()
ax.text(0.10,0.80,'shift %d pix' % i, transform=ax.transAxes)
蓝线:移位前的数据
绿线:预期的换档行为
红线: scipy.ndimage.interpolation.shift
Blue line: data before the shift
Green line: expected shift behavior
Red line: actual shift output of scipy.ndimage.interpolation.shift
在调用函数或使用mode = 'wrap'
理解函数时是否存在一些错误?当前结果与相关 scipy教程页面,并从另一个.代码中是否存在一个错误提示?
Is there some error in how I call the function or how I understand its behavior with mode = 'wrap'
? The current results are in contrast to the mode parameter description from the related scipy tutorial page and from another StackOverflow post. Is there an off-by-one-error in the code?
使用的Scipy版本为0.18.1,分布在anaconda-2.2.0中
Scipy version used is 0.18.1, distributed in anaconda-2.2.0
推荐答案
值得注意的是,此行为似乎是一个错误,如本SciPy问题中所述: https://github.com/scipy/scipy/issues/2640
It is worth noting that this behavior appears to be a bug, as noted in this SciPy issue:https://github.com/scipy/scipy/issues/2640
该问题似乎会影响除mode='mirror'
之外的scipy.ndimage
中的所有mode
外推.
The issue appears to effect every extrapolation mode
in scipy.ndimage
other than mode='mirror'
.
这篇关于移位插值未提供预期的行为的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!