Python基础绘图教程（二）

import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)
fig = plt.figure()

N = 100
r0 = 0.6
x = 0.9 * np.random.rand(N)
y = 0.9 * np.random.rand(N)
area = (20 * np.random.rand(N))**2  # 0 to 10 point radii
c = np.sqrt(area)
r = np.sqrt(x ** 2 + y ** 2)
area1 = np.ma.masked_where(r < r0, area)
area2 = np.ma.masked_where(r >= r0, area)
plt.scatter(x, y, s=area1, marker='^', c=c)
plt.scatter(x, y, s=area2, marker='o', c=c)
# Show the boundary between the regions:
theta = np.arange(0, np.pi / 2, 0.01)
plt.plot(r0 * np.cos(theta), r0 * np.sin(theta))
plt.show()

fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))

recipe = ["SST",
          "SLP",
          "UWND",
          "VWND",
          "HFLUX",
          "PRECIPITATION"]

data = [0.34, 0.16, 0.22, 0.05, 0.08, 0.15]

wedges, texts = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)

bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
kw = dict(arrowprops=dict(arrowstyle="-"),
          bbox=bbox_props, zorder=0, va="center")

for i, p in enumerate(wedges):
    ang = (p.theta2 - p.theta1)/2. + p.theta1
    y = np.sin(np.deg2rad(ang))
    x = np.cos(np.deg2rad(ang))
    horizontalalignment = {-1: "right", 1: "left"}[int(np.sign(x))]
    connectionstyle = "angle,angleA=0,angleB={}".format(ang)
    kw["arrowprops"].update({"connectionstyle": connectionstyle})
    ax.annotate(recipe[i], xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y),horizontalalignment=horizontalalignment, **kw)

ax.set_title("Weight proportion")
plt.show()

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-5, 5, 5)
X, Y = np.meshgrid(x, x)
U, V = 12 * X, 12 * Y

data = [(-1.5, .5, -6, -6),
        (1, -1, -46, 46),
        (-3, -1, 11, -11),
        (1, 1.5, 80, 80),
        (0.5, 0.25, 25, 15),
        (-1.5, -0.5, -5, 40)]

data = np.array(data, dtype=[('x', np.float32), ('y', np.float32),
                             ('u', np.float32), ('v', np.float32)])

fig1, axs1 = plt.subplots(nrows=2, ncols=2)
# Default parameters, uniform grid
axs1[0, 0].barbs(X, Y, U, V)

# Arbitrary set of vectors, make them longer and change the pivot point
# (point around which they're rotated) to be the middle
axs1[0, 1].barbs(
    data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle')

# Showing colormapping with uniform grid.  Fill the circle for an empty barb,
# don't round the values, and change some of the size parameters
axs1[1, 0].barbs(
    X, Y, U, V, np.sqrt(U ** 2 + V ** 2), fill_empty=True, rounding=False,
    sizes=dict(emptybarb=0.25, spacing=0.2, height=0.3))

# Change colors as well as the increments for parts of the barbs
axs1[1, 1].barbs(data['x'], data['y'], data['u'], data['v'], flagcolor='r',
                 barbcolor=['b', 'g'], flip_barb=True,
                 barb_increments=dict(half=10, full=20, flag=100))

# Masked arrays are also supported
masked_u = np.ma.masked_array(data['u'])
masked_u[4] = 1000  # Bad value that should not be plotted when masked
masked_u[4] = np.ma.masked
fig1.savefig("/Users/chenyue/Downloads/f7.png",dpi=300)
plt.show()

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D

X = np.arange(30*np.pi/180, 89*np.pi/180, np.pi/180)
Y = np.arange(0, 360*np.pi/180, np.pi/180)
X, Y = np.meshgrid(X, Y)
Z = np.sin(Y)/np.tan(X)


fig = plt.figure()
ax = Axes3D(fig)
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='summer')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
ax.set_zlim(-1.5,1.5)
plt.show()