Reputation: 33
I have 4 known points that I am trying to run a smooth curve through.
gg_xy=np.array([[-2.612,0],[0,1.6969999999999996],[0.5870000000000001,0],[0,-2.605]])
plt.plot(gg_xy[:,0],gg_xy[:,1],'ro')
ggx,ggy=splprep(gg_xy.T,u=None,s=0.0,per=1)
gg_xspline=np.linspace(ggy.min(),ggy.max(),300)
ggxnew,ggynew=splev(gg_xspline,ggx,der=0)
plt.plot(ggxnew,ggynew)
plt.show()
It is missing a point when interpolating. Could someone help me force it through this point? Is there a better way to do this other than using spline interpolation? Edit: the curve must be a single connected loop. Thanks!
Upvotes: 0
Views: 497
Reputation: 16876
from scipy.interpolate import splprep, splev
import matplotlib.pyplot as plt
import numpy as np
gg_xy=np.array([[-2.612,0],[0,1.6969999999999996],
[0.5870000000000001,0],[0,-2.605], [0,-2.605]])
plt.plot(gg_xy[:,0],gg_xy[:,1],'ro')
ggx,ggy=splprep(gg_xy.T,u=None,s=0.0,per=1)
gg_xspline=np.linspace(ggy.min(),ggy.max(),300)
ggxnew,ggynew=splev(gg_xspline,ggx,der=0)
plt.plot(ggxnew,ggynew)
plt.show()
Docs:
per: int, optional
If non-zero, data points are considered periodic with period x[m-1] - x[0] and a smooth periodic spline approximation is returned. Values of y[m-1] and w[m-1] are not used.
Looks like it ignores the last point, so I just repeated the last point.
Upvotes: 1