import matplotlib.pyplot as plt
import numpy as np
# 1. 首先是導(dǎo)入包，創(chuàng)建數(shù)據(jù)
n = 10
x = np.random.rand(n) * 2# 隨機(jī)產(chǎn)生10個(gè)0~2之間的x坐標(biāo)
y = np.random.rand(n) * 2# 隨機(jī)產(chǎn)生10個(gè)0~2之間的y坐標(biāo)
# 2.創(chuàng)建一張figure
fig = plt.figure(1)
# 3. 設(shè)置顏色 color 值【可選參數(shù)，即可填可不填】，方式有幾種
# colors = np.random.rand(n) # 隨機(jī)產(chǎn)生10個(gè)0~1之間的顏色值，或者
colors = ['r', 'g', 'y', 'b', 'r', 'c', 'g', 'b', 'k', 'm']  # 可設(shè)置隨機(jī)數(shù)取
# 4. 設(shè)置點(diǎn)的面積大小 area 值 【可選參數(shù)】
area = 20*np.arange(1, n+1)
# 5. 設(shè)置點(diǎn)的邊界線寬度 【可選參數(shù)】
widths = np.arange(n)# 0-9的數(shù)字
# 6. 正式繪制散點(diǎn)圖：scatter
plt.scatter(x, y, s=area, c=colors, linewidths=widths, alpha=0.5, marker='o')
# 7. 設(shè)置軸標(biāo)簽：xlabel、ylabel
#設(shè)置X軸標(biāo)簽
plt.xlabel('X坐標(biāo)')
#設(shè)置Y軸標(biāo)簽
plt.ylabel('Y坐標(biāo)')
# 8. 設(shè)置圖標(biāo)題：title
plt.title('test繪圖函數(shù)')
# 9. 設(shè)置軸的上下限顯示值：xlim、ylim
# 設(shè)置橫軸的上下限值
plt.xlim(-0.5, 2.5)
# 設(shè)置縱軸的上下限值
plt.ylim(-0.5, 2.5)
# 10. 設(shè)置軸的刻度值：xticks、yticks
# 設(shè)置橫軸精準(zhǔn)刻度
plt.xticks(np.arange(np.min(x)-0.2, np.max(x)+0.2, step=0.3))
# 設(shè)置縱軸精準(zhǔn)刻度
plt.yticks(np.arange(np.min(y)-0.2, np.max(y)+0.2, step=0.3))
# 也可按照xlim和ylim來設(shè)置
# 設(shè)置橫軸精準(zhǔn)刻度
plt.xticks(np.arange(-0.5, 2.5, step=0.5))
# 設(shè)置縱軸精準(zhǔn)刻度
plt.yticks(np.arange(-0.5, 2.5, step=0.5))
 
# 11. 在圖中某些點(diǎn)上（位置）顯示標(biāo)簽：annotate
# plt.annotate("(" + str(round(x[2], 2)) + ", " + str(round(y[2], 2)) + ")", xy=(x[2], y[2]), fontsize=10, xycoords='data')# 或者
plt.annotate("({0},{1})".format(round(x[2],2), round(y[2],2)), xy=(x[2], y[2]), fontsize=10, xycoords='data')
# xycoords='data' 以data值為基準(zhǔn)
# 設(shè)置字體大小為 10
# 12. 在圖中某些位置顯示文本：text
plt.text(round(x[6],2), round(y[6],2), "good point", fontdict={'size': 10, 'color': 'red'})  # fontdict設(shè)置文本字體
# Add text to the axes.
# 13. 設(shè)置顯示中文
plt.rcParams['font.sans-serif']=['SimHei'] #用來正常顯示中文標(biāo)簽
plt.rcParams['axes.unicode_minus']=False #用來正常顯示負(fù)號
# 14. 設(shè)置legend，【注意，'繪圖測試'：一定要是可迭代格式，例如元組或者列表，要不然只會(huì)顯示第一個(gè)字符，也就是legend會(huì)顯示不全】
plt.legend(['繪圖測試'], loc=2, fontsize=10)
# plt.legend(['繪圖測試'], loc='upper left', markerscale = 0.5, fontsize = 10) #這個(gè)也可
# markerscale：The relative size of legend markers compared with the originally drawn ones.
# 15. 保存圖片 savefig
plt.savefig('test_xx.png', dpi=200, bbox_inches='tight', transparent=False)
# dpi: The resolution in dots per inch，設(shè)置分辨率，用于改變清晰度
# If *True*, the axes patches will all be transparent
# 16. 顯示圖片 show
plt.show()

def scatter(self, x, y, s=None, c=None, marker=None, cmap=None, norm=None,
                vmin=None, vmax=None, alpha=None, linewidths=None,
                verts=None, edgecolors=None,
                **kwargs):
        """
        A scatter plot of *y* vs *x* with varying marker size and/or color.
        Parameters
        ----------
        x, y : array_like, shape (n, )
            The data positions.
        s : scalar or array_like, shape (n, ), optional
            The marker size in points**2.
            Default is ``rcParams['lines.markersize'] ** 2``.
        c : color, sequence, or sequence of color, optional, default: 'b'
            The marker color. Possible values:
            - A single color format string.
            - A sequence of color specifications of length n.
            - A sequence of n numbers to be mapped to colors using *cmap* and
              *norm*.
            - A 2-D array in which the rows are RGB or RGBA.
            Note that *c* should not be a single numeric RGB or RGBA sequence
            because that is indistinguishable from an array of values to be
            colormapped. If you want to specify the same RGB or RGBA value for
            all points, use a 2-D array with a single row.
        marker : `~matplotlib.markers.MarkerStyle`, optional, default: 'o'
            The marker style. *marker* can be either an instance of the class
            or the text shorthand for a particular marker.
            See `~matplotlib.markers` for more information marker styles.
        cmap : `~matplotlib.colors.Colormap`, optional, default: None
            A `.Colormap` instance or registered colormap name. *cmap* is only
            used if *c* is an array of floats. If ``None``, defaults to rc
            ``image.cmap``.
        alpha : scalar, optional, default: None
            The alpha blending value, between 0 (transparent) and 1 (opaque).
        linewidths : scalar or array_like, optional, default: None
            The linewidth of the marker edges. Note: The default *edgecolors*
            is 'face'. You may want to change this as well.
            If *None*, defaults to rcParams ``lines.linewidth``.

plt.legend(['繪圖測試'], loc=2, fontsize = 10)
# plt.legend(['繪圖測試'], loc='upper left', markerscale = 0.5, fontsize = 10) #這個(gè)也可
#  markerscale：The relative size of legend markers compared with the originally drawn ones.

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
 
# 隨機(jī)種子
np.random.seed(1)
 
 
def randrange(n, vmin, vmax):
    '''
    使數(shù)據(jù)分布均勻(vmin, vmax).
    '''
    return (vmax - vmin)*np.random.rand(n) + vmin
 
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')  # 可進(jìn)行多圖繪制
 
n = 500
 
# 對于每一組樣式和范圍設(shè)置，在由x在[23，32]、y在[0，100]、
# z在[zlow，zhigh]中定義的框中繪制n個(gè)隨機(jī)點(diǎn)
for m, zlow, zhigh in [('o', -50, -25), ('^', -30, -5)]:
    xs = randrange(n, 23, 32)
    ys = randrange(n, 0, 100)
    zs = randrange(n, zlow, zhigh)
    ax.scatter(xs, ys, zs, marker=m)  # 繪圖
 
# X、Y、Z的標(biāo)簽
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
 
plt.show()