matplotlib 入門 (5) nitta@tsuda.ac.jp

5章: グラフエリア内にテキストを描画する

5-1: グラフエリアにテキストをプロットする (pyplot.text)

テキストの描画は Axes.text(x, y, text, ...) を使う。

ボックス付きのテキストは属性を辞書形式で bbox パラメータに渡せばよい。

# sample code 5-1
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

xs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ys = [5.4, 8.5, 12.8, 15.1, 19.5, 23.2, 24.3, 29.1, 24.2, 17.5, 14.0, 7.7] 

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.set_title('Average temperature')
ax.set_ylim(0, 35)

ax.plot(xs, ys)

ax.text(8, 30, 'peak', size=20, ha='center')

dic1={
    'boxstyle': 'round', 
    'facecolor': 'pink', 
    'edgecolor': 'red', 
    'linestyle': 'solid', 
    'linewidth': 2
}
ax.text(2.5, 15, 'warmer and warmer', size=15, rotation=40, bbox=dic1)

dic2={
    'boxstyle': 'circle', 
    'facecolor': 'cyan', 
    'edgecolor': 'blue', 
    'linestyle': 'dashed', 
    'linewidth': 2
}
ax.text(10, 20, 'getting chill', bbox=dic2)

plt.show()

5-2: すべてのデータ点にラベルを表示する (transorms.offset_copy)

マーカをプロットした散布図上に、マーカ毎の値をラベルとして表示する。 Axesオブジェクトのオフセット情報を管理する Transform オブジェクトを利用して、オフセット情報を一括で設定すると便利。

# sample code 5-2
%matplotlib inline

import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import numpy as np

xs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ys = [5.4, 8.5, 12.8, 15.1, 19.5, 23.2, 24.3, 29.1, 24.2, 17.5, 14.0, 7.7] 

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

# get the copy of 'offset' of the current 'Transform'
trans_offset = mtransforms.offset_copy(
    ax.transData,   # Transform of ax
    fig=fig,    # Fugure in which ax is deployed
    x=0.05,    # x offset
    y=0.03,    # y offset
    units='inches'   # unit of offset
)

for x, y in zip(xs, ys):
    ax.plot(x, y, 'ro')   # red circle
    ax.text(
        x, 
        y, 
        f'{y:.1f}',
        transform=trans_offset,   # changed offset
        horizontalalignment='left', # horizontal basepoint
        verticalalignment='bottom'  # vertical basepoint
    )

plt.show()

5-3: グラフに注釈をつける (annotate)

グラフ上の任意の位置に矢印付きのテキストを描画できる。

# sample code 5-3
%matplotlib inline

import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import numpy as np

xs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ys = [5.4, 8.5, 12.8, 15.1, 19.5, 23.2, 24.3, 29.1, 24.2, 17.5, 14.0, 7.7] 

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.plot(xs, ys)

arrow1 = {
    'facecolor': 'red',
    'width': 1,
    'headwidth': 10,
    'headlength': 15,
    'linewidth': 1,
    'edgecolor': 'black',
    'shrink': 0.05
}

ax.annotate('max point', 
            xy=(8, 29.1),
            xytext=(9, 29),
            arrowprops=arrow1,
            fontsize=16)

plt.show()

5-4: 矢印型のボックスを使って注釈を表示する Axes.text()

# sample code 5-4
%matplotlib inline

import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import numpy as np

xs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ys = [5.4, 8.5, 12.8, 15.1, 19.5, 23.2, 24.3, 29.1, 24.2, 17.5, 14.0, 7.7] 

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.plot(xs, ys)

ax.text(
    8.3,   # left point of text
    29.1,  # baseline of text,
    'max point',
    size=12,
    rotation=10,
    horizontalalignment='left',
    verticalalignment='bottom',
    bbox={
        'boxstyle': 'larrow',
        'facecolor': 'pink',
        'edgecolor': 'red',
        'linewidth': 1
    }
)

plt.show()

5-5: 数式を描画する

数式は、文字rに続く文字列中の$のペアの中に数式要素を記述する。

# sample code 5-5-1
# Greek letters
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

cs=[
    # 小文字
    r'$\alpha$',
    r'$\beta$',
    r'$\chi$',
    r'$\delta$',
    r'$\digamma$',
    r'$\epsilon$',
    r'$\eta$',
    r'$\gamma$',
    r'$\iota$',
    r'$\kappa$',
    r'$\lambda$',
    r'$\mu$',
    r'$\nu$',
    r'$\omega$',
    r'$\phi$',
    r'$\pi$',
    r'$\psi$',
    r'$\rho$',
    r'$\sigma$',
    r'$\tau$',
    r'$\theta$',
    r'$\upsilon$',
    r'$\varepsilon$',
    r'$\varkappa$',
    r'$\varphi$',
    r'$\varpi$',
    r'$\varrho$',
    r'$\varsigma$',
    r'$\vartheta$',
    r'$\xi$',
    r'$\zeta$',
# 大文字
    r'$\Delta$',    
    r'$\Gamma$',    
    r'$\Lambda$',    
    r'$\Omega$',    
    r'$\Pi$',    
    r'$\Psi$',    
    r'$\Sigma$'  
]

N = len(cs)
H = 0.5 * N

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = [ 'DejaVu Sans' ]
plt.rcParams['mathtext.fontset'] = 'cm'

fig, ax = plt.subplots(1, 1, figsize=(2, H))
ax.set_xlim(0,2)
ax.set_ylim(0, H)
for i in range(N):
    y = H - 0.5 * (i + 1) + 0.1
    ax.text(0.2, y, cs[i], fontsize=20)

plt.show()

# sample code 5-5-2
# Accent sign
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

cs=[
    r'$\acute{x}$',    
    r'$\bar{x}$',    
    r'$\breve{x}$',    
    r'$\ddot{x}$',    
    r'$\dot{x}$',    
    r'$\grave{x}$',    
    r'$\hat{x}$',    
    r'$\tilde{x}$',    
    r'$\vec{x}$',    
    r'$\overline{xyz}$'  
]

N = len(cs)
H = 0.5 * N

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = [ 'DejaVu Sans' ]
plt.rcParams['mathtext.fontset'] = 'cm'

fig, ax = plt.subplots(1, 1, figsize=(2, 8))
ax.set_xlim(0,2)
ax.set_ylim(0, H)
for i in range(N):
    y = H - 0.5 * (i + 1) + 0.1
    ax.text(0.2, y, cs[i], fontsize=20)

plt.show()

# sample code 5-5-3
# Formula
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

cs=[
    r'$\sqrt{2}$',    
    r'$\sqrt[3]{x}$',    
    r'$\frac{1}{2}-\frac{1}{3}=\frac{1}{6}$',    
    r'$\frac{3}{4} \binom{3}{4}$',  
    r'$\frac{5 - \frac{1}{x}}{4}$',    
    r'$(\frac{5 - \frac{1}{x}}{4})$',    
    r'$\left(\frac{5 - \frac{1}{x}}{4}\right)$',    
    r'$\alpha_i + \beta^i$',    
    r'$\sum_{i=0}^\infty x_i$'
]

N = len(cs)
H = 0.5 * N

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = [ 'DejaVu Sans' ]
plt.rcParams['mathtext.fontset'] = 'cm'

fig, ax = plt.subplots(1, 1, figsize=(2, 8))
ax.set_xlim(0,2)
ax.set_ylim(0, H)
for i in range(N):
    y = H - 0.5 * (i + 1) + 0.2
    ax.text(0.2, y, cs[i], fontsize=20)

plt.show()