xnx / lineticks Goto Github PK

fig, ax = plt.subplots(constrained_layout=True)

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.tri as mtri
from lineticks import LineTicks

def frame(ax, zlims):
    x = np.linspace(0, 1.0, 20)
    y = x*0.0
    ax.plot(x*0.0, y*0.0, color="blue", zs=np.linspace(zlims[0], zlims[1], 20))
    ax.plot(0.5*(y + 1.0), (y+1.0)*0.5*np.sqrt(3.0), color="blue", zs=np.linspace(zlims[0], zlims[1], 20))
    ax.plot(x*0.0 + 1.0, y*0.0, color="blue", zs=np.linspace(zlims[0], zlims[1], 20))
    # line - 1
    x = np.linspace(0, 0.5, 20)
    y = np.sqrt(3)*x
    line1, = ax.plot(x, y, color="blue")
    ax.plot(x, y, zs=np.max(z), color="blue")
    major_ticks = LineTicks(line1, range(20), 20,lw=1,color='r', direction=-1)

    # line - 2
    x = np.linspace(0.5, 1.0, 20)
    y = -np.sqrt(3)*x + np.sqrt(3)
    ax.plot(x, y, color="blue")
    ax.plot(x, y, zs=np.max(z), color="blue")

    # line - 1
    x = np.linspace(0, 1.0, 20)
    y = x*0.0
    ax.plot(x, y, color="blue")
    ax.plot(x, y, zs=np.max(z), color="blue")
    return ax

x = []
y = []
for x1 in np.arange(0, 1, 0.05).tolist():
    for x2 in np.arange(0, 1.0 - x1, 0.05).tolist():
        x.append(x1 + 0.5*x2)
        y.append(x2*0.5*np.sqrt(3.0))

z = np.array(x)**2 + np.array(y)**2

# Triangulate parameter space to determine the triangles
tri = mtri.Triangulation(x, y)

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')

# The triangles in parameter space determine which x, y, z points are
# connected by an edge
ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral)
ax.set_axis_off()

n = 10
dr = 2.0/n
sqrt3 = np.sqrt(3.0)

ax = frame(ax, [np.min(z), np.max(z)])

plt.show()