问题描述
我想对数据(120 * 120)进行插值以获得输出数据(1200 * 1200).
I want to interpolate data (120*120) in order to get output data (1200*1200).
通过这种方式,我正在使用 scipy.interpolate.interp2d
.
In this way I'm using scipy.interpolate.interp2d
.
下面是我的输入数据,其中255对应于填充值,我在插值之前屏蔽了这些值.
Below is my input data, where 255 corresponds to fill values, I mask these values before the interpolation.
我正在使用以下代码:
tck = interp2d(np.linspace(0, 1200, data.shape[1]),
np.linspace(0, 1200, data.shape[0]),
data,
fill_value=255)
data = tck(range(1200), range(1200))
data = np.ma.MaskedArray(data, data == 255)
我得到以下结果:
填充值已内插.
如何在不插入填充值的情况下插入数据?
How can I interpolate my data without interpolate fill values ?
推荐答案
我找到了 scipy.interpolate.griddata ,但我不确定那是最好的.
I found a solution with scipy.interpolate.griddata but I'm not sure that's the best one.
我使用nearest
方法参数对数据进行插值,该参数返回最接近插值点的数据点处的值.
I interpolate data with the nearest
method parameter which returns the value at the data point closest to the point of interpolation.
points = np.meshgrid(np.linspace(0, 1200, data.shape[1]),
np.linspace(0, 1200, data.shape[0]))
points = zip(points[0].flatten(), points[1].flatten())
xi = np.meshgrid(np.arange(1200), np.arange(1200))
xi = zip(xi[0].flatten(), xi[1].flatten())
tck = griddata(np.array(points), data.flatten(), np.array(xi), method='nearest')
data = tck.reshape((1200, 1200))
这篇关于Scipy interp2d内插蒙版填充值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!