线（Line）与标记（Marker）¶

matplotlib.lines.Line2D — Matplotlib 3.10.1 documentation

导入模块与数据准备
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

x = np.arange(1, 51, 1)
"""
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50]
"""

y = np.sin(x)
"""
[ 0.84147098  0.90929743  0.14112001 -0.7568025  -0.95892427 -0.2794155  0.6569866   0.98935825  0.41211849 -0.54402111 -0.99999021 -0.53657292  0.42016704  0.99060736  0.65028784 -0.28790332 -0.96139749 -0.75098725  0.14987721  0.91294525  0.83665564 -0.00885131 -0.8462204  -0.90557836 -0.13235175  0.76255845  0.95637593  0.27090579 -0.66363388 -0.98803162 -0.40403765  0.55142668  0.99991186  0.52908269 -0.42818267 -0.99177885 -0.64353813  0.29636858  0.96379539  0.74511316 -0.15862267 -0.91652155 -0.83177474  0.01770193  0.85090352  0.90178835  0.12357312 -0.76825466 -0.95375265 -0.26237485]
"""

线型（Line Style）¶

Linestyles — Matplotlib 3.10.1 documentation

字符串型¶

linestyle=""

字符串型
from matplotlib.lines import Line2D
Line2D.lineStyles
"""
{'-': '_draw_solid', '--': '_draw_dashed', '-.': '_draw_dash_dot', ':': '_draw_dotted', 
 'None': '_draw_nothing', ' ': '_draw_nothing', '': '_draw_nothing'}
"""

字符串	含义
"solid" / "-"	实线(——)
"dotted" / ":"	点线(·········)	`rcParams["lines.dotted_pattern"]=[1.0, 1.65]`
"dashed" / "--"	虚线(-----)	`rcParams["lines.dashed_pattern"]=[3.7, 1.6]`
"dashdot" / "-."	点划线(·-·-·-·)	`rcParams["lines.dashdot_pattern"]=[6.4, 1.6, 1.0, 1.6]`

linestylecapstylejoinstyle

常规linestyle='solid'linestyle≠'solid'

常规
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        linestyle="dashdot",  # (1)!
        linewidth=4,          # (2)!
        color="green",        # (3)!
        gapcolor="red",       # (4)!
        alpha=0.5             # (5)!
        )

plt.show()

线型(linestyle/ls)
线宽(linewidth/lw)
可见线段填充色(color/c)
不可见线段填充色
透明度

linestyle='solid'
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        linestyle="solid",
        linewidth=10,
        color="green",
        gapcolor="red",
        solid_capstyle="butt",      # (1)!
        solid_joinstyle="miter",    # (2)!
        alpha=0.5
        )

plt.show()

当linestyle="solid"时，两个端点的样式
当linestyle="solid"时，连接点（转折点）的样式

linestyle≠'solid'
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        linestyle="dashdot",
        linewidth=10,
        color="green",
        gapcolor="red",
        dash_capstyle="round",      # (1)!
        dash_joinstyle="miter",     # (2)!
        alpha=0.5
        )

plt.show()

当linestyle≠"solid"时，每个线段端点的样式
当linestyle≠"solid"时，每个线段连接点（转折点）的样式

元组型¶

linestyle=(offset, on_off_seq)dashes=(on_off_seq)

linestyle=(offset, on_off_seq)

offset：在构建的线型上开始的偏移量（以点为单位）
on_off_seq：通过序列构建线型。若序列长度为偶数，则偶数位(0开始)代表可见线段长度（以点为单位），奇数位表示不可见线段的长度（以点为单位）；若序列长度为奇数，则序列扩增为2倍【即(3, 1, 1) 相当于 (3, 1, 1, 3, 1, 1)】

linestyle=(offset, on_off_seq)
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

# 构建5可见1不可见的线型，第一段偏移量为4，所以第一段仅为1可见1不可见
ax.plot(x, y,
        linestyle=(4, (5, 1)),
        linewidth=4,
        color="green",
        gapcolor="red",
        alpha=0.5
        )

plt.show()

dashes=(on_off_seq)

dashes=(on_off_seq)
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

# 构建5可见1不可见的线型
ax.plot(x, y,
        dashes=(5, 1), 
        linewidth=4,
        color="green",
        gapcolor="red",
        alpha=0.5
        )

plt.show()

标记（Marker）¶

matplotlib.markers — Matplotlib 3.7.1 documentation

Marker examples — Matplotlib 3.10.1 documentation

Mapping marker properties to multivariate data — Matplotlib 3.10.1 documentation

标记（Marker）
from matplotlib.lines import Line2D
Line2D.markers
"""
{'.': 'point', ',': 'pixel', 'o': 'circle', 'v': 'triangle_down', '^': 'triangle_up', 
 '<': 'triangle_left', '>': 'triangle_right', '1': 'tri_down', '2': 'tri_up', '3': 'tri_left', 
 '4': 'tri_right', '8': 'octagon', 's': 'square', 'p': 'pentagon', '*': 'star', 
 'h': 'hexagon1', 'H': 'hexagon2', '+': 'plus', 'x': 'x', 'D': 'diamond', 
 'd': 'thin_diamond', '|': 'vline', '_': 'hline', 'P': 'plus_filled', 'X': 'x_filled', 
 0: 'tickleft', 1: 'tickright', 2: 'tickup', 3: 'tickdown', 4: 'caretleft', 
 5: 'caretright', 6: 'caretup', 7: 'caretdown', 8: 'caretleftbase', 9: 'caretrightbase', 
 10: 'caretupbase', 11: 'caretdownbase', 'None': 'nothing', 'none': 'nothing', ' ': 'nothing', '': 'nothing'}
"""

未填充型（Unfilled markers）¶

Marker reference — Matplotlib 3.10.1 documentation

未填充型（Unfilled markers）
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        marker=4,                   # (1)!
        markersize=25,              # (2)!
        markerfacecolor="red",      # (3)!
        markeredgecolor="green",    # (4)!
        markeredgewidth=2,          # (5)!
        markevery=None,             # (6)!
        alpha=1
        )

plt.show()

标记类型
标记大小(markersize/ms)
标记填充色(markerfacecolor/mfc)
标记边缘色(markeredgecolor/mec)
标记边缘宽度(markeredgewidth/mew)
决定每隔几个绘制一个标记点，默认所有

填充型（Filled markers）与填充样式（Fill Style）¶

Marker reference — Matplotlib 3.10.1 documentation

填充型（Filled markers）填充样式（Fill Style）

填充型（Filled markers）
from matplotlib.lines import Line2D
Line2D.filled_markers
"""
('.', 'o', 'v', '^', '<', '>', '8', 's', 'p', '*', 'h', 'H', 'D', 'd', 'P', 'X')
"""

填充样式（Fill Style）
from matplotlib.lines import Line2D
Line2D.fillStyles
"""
('full', 'left', 'right', 'bottom', 'top', 'none')
"""

填充型（Filled markers）与填充样式（Fill Style）
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        marker="*",
        markersize=25,
        fillstyle="left",           # (1)!
        markerfacecolor="red",      # (2)!
        markerfacecoloralt="black", # (3)!
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

指定markerfacecolor填充侧
fillstyle指定侧标记填充色(markerfacecolor/mfc)
非fillstyle指定侧标记填充色(markerfacecoloralt/mfcalt)

TeX符号创建(Markers created from TeX symbols)¶

Marker reference — Matplotlib 3.10.1 documentation

TeX符号创建(Markers created from TeX symbols)
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        marker=r"$\bigotimes$",
        markersize=25,
        markerfacecolor="red",
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

元组型¶

(numsides, 0, angle)(numsides, 1, angle)(numsides, 2, angle)

(numsides, 0, angle)：逆时针旋转angle°的正numsides边形

(numsides, 1, angle)：逆时针旋转angle°的正numsides角形

(numsides, 2, angle)：逆时针旋转angle°的正numsides边星

元组型
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        marker=(5, 0, 90),
        markersize=25,
        markerfacecolor="red",
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

Path创建(Markers created from Paths)¶

Marker reference — Matplotlib 3.10.1 documentation

绘制坐标以原始标记点为原点(0, 0)

mpath.Path(vertices, codes=None, closed=False)
1. vertices：绘制的点坐标序列（如[(x1, y1), (x2, y2), ...]）或者形状(N, 2)的数组（如[[x1 y1] [x2 y2] ...]）。
2. codes：与vertices每个坐标一一对应，表示到该坐标的动作，可选：
  1. mpath.Path.STOP = np.uint8(0) = 0：不绘制该坐标且结束绘制
  2. mpath.Path.MOVETO = np.uint8(1) = 1：不绘制，仅移动到该坐标。第一个必须是该值。
  3. mpath.Path.LINETO = np.uint8(2) = 2：以线段绘制到该坐标
  4. mpath.Path.CURVE3 = np.uint8(3) = 3：绘制曲线到该坐标后一个坐标
  5. mpath.Path.CURVE4 = np.uint8(4) = 4：绘制曲线到该坐标后两个坐标
  6. mpath.Path.CLOSEPOLY = np.uint8(79) = 79：不绘制该坐标，直接前一个坐标绘制线段到第一个坐标以封闭图形
3. closed：是否封闭图形。当codes=None且closed=True时，相当于codes=[1, 2, 2, ..., 79]。
mpath.Path.arc(theta1, theta2, n=None, is_wedge=False)：绘制从 theta1°到 theta2°（>360°时将减去360°）的单位圆弧。n，略。 is_wedge 指是否绘制弧形半径。
mpath.Path.wedge(theta1, theta2, n=None)：相当于mpath.Path.arc中 is_wedge=True
mpath.Path.circle(center=(0.0, 0.0), radius=1.0, readonly=False)：绘制圆心坐标为 center，半径为 radius 的圆。readonly，略。
mpath.Path.unit_circle()：绘制单位圆
mpath.Path.unit_circle_righthalf()：绘制单位圆右侧半
mpath.Path.unit_rectangle()：绘制单位矩形（正方形）
mpath.Path.unit_regular_asterisk(numVertices)：绘制单位正 numVertices 边星
mpath.Path.unit_regular_polygon(numVertices)：绘制单位正 numVertices 边形
mpath.Path.unit_regular_star(numVertices, innerCircle=0.5)：绘制单位正 numVertices 角星。innerCircle，略

基类子类

基类
import matplotlib.path as mpath

fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

vertices = [(-2, 0), (0, 4), (2, 0), (0, -4)]
codes= [1, 2, 2, 79]

ax.plot(x, y,
        marker=mpath.Path(vertices, codes=codes, closed=False),
        markersize=25,
        markerfacecolor="red",
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

子类
import matplotlib.path as mpath

fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        marker=mpath.Path.unit_circle(),
        markersize=25,
        markerfacecolor="red",
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

MarkerStyle创建¶

Marker reference — Matplotlib 3.10.1 documentation

marker capstylemarker joinstyle

MarkerStyle创建
from matplotlib.markers import MarkerStyle

fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

marker = MarkerStyle(marker="1",
                     fillstyle='none',
                     capstyle='round',
                     joinstyle='miter')
marker = marker.rotated(deg=90,      # (1)!
                        rad=None)    # (2)!
marker = marker.scaled(sx=2,         # (3)!
                       sy=4)         # (4)!

ax.plot(x, y,
        marker=marker,
        markersize=25,
        markerfacecolor="red",
        markeredgecolor="green",
        markeredgewidth=2,
        markevery=None,
        alpha=1
        )

plt.show()

逆时针旋转（度数）
逆时针旋转（弧度）
x轴上的缩放。必须指定
y轴上的缩放。若未指定，x轴和y轴均按sx缩放

绘制样式（Draw Style）¶

Step Demo — Matplotlib 3.10.1 documentation

matplotlib.pyplot.step — Matplotlib 3.10.1 documentation

matplotlib.axes.Axes.step — Matplotlib 3.10.1 documentation

step函数是对plot(drawstyle=...)的封装，通过where参数来指定'pre'、'mid'、'post'

绘制样式（Draw Style）
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.plot(x, y,
        linestyle="-",
        marker="*",
        drawstyle="steps-mid"    # (1)!
        )
# ax.step(x, y,
#         linestyle="-",
#         marker="*",
#         where="mid"
#         )

ax.grid()
plt.show()

drawstyle/ds

网格线（Grid）¶

matplotlib.axes.Axes.grid — Matplotlib 3.10.1 documentation

matplotlib.pyplot.grid — Matplotlib 3.10.1 documentation

网格线（Grid）
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)

ax.grid(visible=True,    # (1)!
        which="both",    # (2)!
        axis="both",     # (3)!

        linestyle="--",
        linewidth=2,
        color="red",
        gapcolor="black",
        alpha=0.5,
        )

plt.show()

网格线是否可见
绘制在主刻度还是副刻度, 可选:
1. 'major'
2. 'minor'
3. 'both'
绘制哪个轴的, 可选:
1. 'both'
2. 'x'
3. 'y'

参考线（Line）¶

axhline与axvlinehlines与vlines

matplotlib.axes.Axes.axhline — Matplotlib 3.10.1 documentation

matplotlib.pyplot.axhline — Matplotlib 3.10.1 documentation

matplotlib.axes.Axes.axvline — Matplotlib 3.10.1 documentation

matplotlib.pyplot.axvline — Matplotlib 3.10.1 documentation

axhline与axvline
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)
ax.plot(x, y)

ax.axhline(y=0.5,       # (1)!
           xmin=0.2,    # (2)!
           xmax=0.8,    # (3)!

           linestyle="--",
           linewidth=2,
           color="red",
           gapcolor="black",
           alpha=0.5,
           )

ax.axvline(x=25,        # (4)!
           ymin=0.2,    # (5)!
           ymax=0.8,    # (6)!

           linestyle="--",
           linewidth=2,
           color="red",
           gapcolor="black",
           alpha=0.5,
           )

plt.show()

数据坐标系统
Axes坐标系统
Axes坐标系统
数据坐标系统
Axes坐标系统
Axes坐标系统

matplotlib.axes.Axes.hlines — Matplotlib 3.10.1 documentation

matplotlib.pyplot.hlines — Matplotlib 3.10.1 documentation

matplotlib.axes.Axes.vlines — Matplotlib 3.10.1 documentation

matplotlib.pyplot.vlines — Matplotlib 3.10.1 documentation

hlines与vlines
fig = plt.figure(figsize=(8, 8), dpi=100, layout="constrained")
ax = fig.add_subplot(1, 1, 1)
ax.plot(x, y)

ax.hlines(y=[0.5, 0.6, 0.7, 0.8],    # (1)!
          xmin=[10, 15, 20, 25],     # (2)!
          xmax=[15, 20, 25, 30],     # (3)!

          linestyles="--",
          linewidths=[2, 3, 4, 5],
          colors=["r", "g", "b", "y"],
          gapcolor="b",
          alpha=0.5,
          )

ax.vlines(x=[12.5, 17.5, 22.5, 27.5],    # (4)!
          ymin=[0.4, 0.5, 0.6, 0.7],     # (5)!
          ymax=[0.6, 0.7, 0.8, 0.9],     # (6)!

          linestyles="--",
          linewidths=[2, 3, 4, 5],
          colors=["r", "g", "b", "y"],
          gapcolor="b",
          alpha=0.5,
          )

plt.show()

数据坐标系统
数据坐标系统
数据坐标系统
数据坐标系统
数据坐标系统
数据坐标系统

线（Line）与标记（Marker）¶

线型（Line Style）¶

字符串型¶

元组型¶

标记（Marker）¶

未填充型（Unfilled markers）¶

填充型（Filled markers）与填充样式（Fill Style）¶

TeX符号创建(Markers created from TeX symbols)¶

元组型¶

Path创建(Markers created from Paths)¶

MarkerStyle创建¶

绘制样式（Draw Style）¶

网格线（Grid）¶

参考线（Line）¶

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