Below is my code (from here): So "/>
I have a numpy
object in Python ( np
) with which I am plotting a graph in pyplot
. It is a 3D graph with x
, y
and z
being lists containing the values for which the graph is to be plotted. Below is my code (from here ):
data = np.c_[x,y,z]
# regular grid covering the domain of the data
mn = np.min(data, axis=0) - 0.009
mx = np.max(data, axis=0) + 0.009
X,Y = np.meshgrid(np.linspace(mn[0], mx[0]), np.linspace(mn[1], mx[1]))
XX = X.flatten()
YY = Y.flatten()
A = np.c_[np.ones(data.shape[0]), data[:, :2], np.prod(data[:, :2], axis=1), data[:, :2] ** 2]
C, _, _, _ = scipy.linalg.lstsq(A, data[:, 2])
# evaluate it on a grid
Z = np.dot(np.c_[np.ones(XX.shape), XX, YY, XX * YY, XX ** 2, YY ** 2], C).reshape(X.shape)
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, alpha=0.2)
ax.scatter(data[:, 0], data[:, 1], data[:, 2], c='r', s=50)
plt.xlabel('X')
plt.ylabel('Y')
ax.set_zlabel('Z')
ax.axis('equal')
ax.axis('tight')
plt.show()
So here, I want to get the values of x
and y
, where the value of z
is closest to -30
. How do I get those values of x
and y
.
You can try following (see also Find nearest value in numpy array )
value = 30.
zid = (np.abs(Z-value)).argmin()
xval = np.reshape(X, -1)[zid]
yval = np.reshape(Y, -1)[zid]
print xval, yval, np.reshape(Z, -1)[zid]
I've checked it on the example ( https://gist.github.com/amroamroamro/1db8d69b4b65e8bc66a6 ) you referred in the question and it seems to work.
You can use np.where
to get the indices which satisfy the condition -30-eps < z < -30+eps
for some tolerance, eps
, and use these to get the value of x
and y
, eg
eps = 10.
ind = np.where((-30+eps > Z.ravel()) & (Z.ravel() > -30-eps))
print("x=",X.ravel()[ind],"y=",Y.ravel()[ind])
I'm a bit unsure exactly how to do this in your case as your plot differs from the example values from the link (please make code in question a MCVE ). The idea should be fine.
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