I'm trying to plot a Spirograph™ curve

In [65]: from matplotlib.pyplot import gca, subplots
    ...: from numpy import exp, lcm, linspace, pi
    ...: 
    ...: def prepare_for_sg():
    ...:     fig, ax = subplots()
    ...:     ax.set_aspect(1)
    ...:     ax.axis(False)
    ...:     return fig, ax
    ...: 
    ...: def plot_sg(R, r, d, Φ=0.0, φ=0.0, ax=None):
    ...:     if ax is None : ax = gca()
    ...:     Ω = 2*pi ;  ω = -Ω*R/r
    ...:     n = lcm(r, R)
    ...:     t = linspace(0, n, n*360 1)
    ...:     xy = (R-r)*np.exp(1j*Ω*(t-Φ))   d*np.exp(1j*ω*(t-φ))
    ...:     line, = ax.plot(xy.real, xy.imag)
    ...:     line.set_antialiased(True)
    ...: 
    ...: prepare_for_sg() ; plot_sg(56, 42, 13)

In [66]: !xmag

and below it's what I get, plus an xmag window zooming on a detail of the curve — there is no excess of antialiasing.

What should I do to remove the jaggedness?

PS the PNG image that I inserted in my question IS ANTIALIASED, because of the conversion and scaling operated by SO.

CodePudding user response：

matplotlib renders the graph for your screen, so in the end, this is like a bitmap. There will always be some form aliasing in this case.

I assume you want a graph without aliasing to process it further, maybe printing it with high detail? Then you could plt.savefig("output.pdf"), which would save it as PDF with vector graphics.

CodePudding user response：

try to modify figure size and linewidth

    line, = ax.plot(xy.real, xy.imag,linewidth=5.0) #line width
    fig = plt.gcf()
    fig.set_size_inches(30, 30) #set figure size

example