3dMATLABplot
I know I can create a 3D surface plot in MATLAB by doing:
x = linspace(1,10,100);
y = linspace(10,20,100);
[X Y] = meshgrid(x,y);
Z = X * Y;
surf(X,Y,Z);
But this requires that all the nodes for the height map generated line up. I have a set of data which has arbitrary points (x,y) and a height (z). Is there a simple way to plot a graph which will generate a surface between the points in a similar fashion to surf?
figure tells you the call signature:
from matplotlib.pyplot import figure
figure(figsize=(8, 6), dpi=80)
figure(figsize=(1,1)) would create an inch-by-inch image, which would be 80-by-80 pixels unless you also give a different dpi argument.
You could use scipy.interpolate.spline to smooth out your data yourself:
from scipy.interpolate import spline
# 300 represents number of points to make between T.min and T.max
xnew = np.linspace(T.min(), T.max(), 300)
power_smooth = spline(T, power, xnew)
plt.plot(xnew,power_smooth)
plt.show()
spline is deprecated in scipy 0.19.0, use BSpline class instead.
Switching from spline to BSpline isn't a straightforward copy/paste and requires a little tweaking:
from scipy.interpolate import make_interp_spline, BSpline
# 300 represents number of points to make between T.min and T.max
xnew = np.linspace(T.min(), T.max(), 300)
spl = make_interp_spline(T, power, k=3) # type: BSpline
power_smooth = spl(xnew)
plt.plot(xnew, power_smooth)
plt.show()
Before:
After:
Best Answer
Appologies, after some hunting I managed to answer my own question:
You can use the
trisurffunction:If you have dense data you will want to do
shading interp(or another value, checkdoc shading) so you don't get a black blob due to the grid.