Question

我有一个非常奇怪的bisplrep行为。

在以下示例中重现了该问题。首先是创建样本数据然后在精细网格上选择分散数据，并尝试应用具有不同结节数（tx，ty）的bisplrep。那时，我已经有了问题。有些图表根本没有表示数据。

from scipy.interpolate import bisplrep,bisplev
from numpy import arange
import numpy as np
from matplotlib import pyplot as mpl

#create data
x,y = np.mgrid[slice(0, 100, 0.1),
                slice(0,50,0.1)]

z = cos(x/10)*sin(y/5)**2


# random selection of scattered data
select = np.random.randint(2, size=x.shape)
for i in range(8):
    select *= np.random.randint(2, size=x.shape)
sx = x.flatten().compress(select.flatten() == 1)
sy = y.flatten().compress(select.flatten() == 1)
sz = z.flatten().compress(select.flatten() == 1)
print len(sx)

#plot original data
fig,axs = subplots(nrows = 4,ncols = 3)
axs[0,0].pcolormesh(x,y,z)
axs[0,0].scatter(sx,sy,alpha=0.5)
axs[0,0].set_xlim(0,100)
axs[0,0].set_ylim(0,50)

#try to uncomment/comment this line
#axs[0,0].set_title('original data')


def get_rz(dx,dy,ax):
    print dx,dy
    #ix,iy are the knots for bisplrep
    ix = arange(0, 100, dx)
    iy = arange(0,50,dy)
    #ox,oy are the interpolation points (same as origianl grid)
    ox = arange(0, 100, 0.1)
    oy = arange(0,50,0.1)
    #interpolation with bisplrep
    tck = bisplrep(sx,sy,sz,task = -1, nxest = len(ix) , nyest = len(iy),tx = ix,ty = iy,s=0)
    rz = bisplev(ox,oy,tck)
    c = ax.contourf(x,y,rz,vmin=-1,vmax = 1)

    # scatx and scat y are just for plot
    scatx,scaty = np.mgrid[slice(0, 100, dx),
                           slice(0,50,dy)]

    ax.plot(scatx.flatten(),scaty.flatten(),'+',alpha = 0.5)
    ax.set_title('dx=%s dy=%s'%(dx,dy))
    return rz

get_rz(dx=1,dy=1,ax=axs[1,0])
get_rz(dx=1,dy=2,ax=axs[1,1])
get_rz(dx=1,dy=3,ax=axs[1,2])
get_rz(dx=2,dy=1,ax=axs[2,0])
get_rz(dx=2,dy=2,ax=axs[2,1])
get_rz(dx=2,dy=3,ax=axs[2,2])
get_rz(dx=3,dy=1,ax=axs[3,0])
get_rz(dx=3,dy=2,ax=axs[3,1])
get_rz(dx=3,dy=3,ax=axs[3,2])

#try to uncomment/comment this line
fig.tight_layout(pad = 0.1,h_pad=0.1,w_pad=0.1)

fig.show()

现在，我尝试评论/取消评论一两行，结果不同...... 它看起来像是一个记忆问题。

你能重现这个问题吗？有什么想法来解决这个问题吗？

谢谢

这里有我得到的两个例子（似乎我不允许发布图片）... http://i.stack.imgur.com/gZZc4.png http://i.stack.imgur.com/0344u.png

编辑：我尝试使用LSQBivariateSpline具有相同的结果和fitpack的f2py vertion：dfitpack.surfit_lsq它也是一样的

scipy.interpolate.bisplrep的奇怪行为

0 个答案: