はじめに
matplotlibのplt.barで表示する棒グラフの棒の色をグラデーションカラーで表示する方法について説明する。
コード
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%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
plt.rcParams['font.size']=14
plt.rcParams['font.family'] = 'sans-serif'
def gradient_image(ax, extent, direction=0.3, cmap_range=(0, 1), **kwargs):
"""
Draw a gradient image based on a colormap.
Parameters
----------
ax : Axes
The axes to draw on.
extent
The extent of the image as (xmin, xmax, ymin, ymax).
By default, this is in Axes coordinates but may be
changed using the *transform* kwarg.
direction : float
The direction of the gradient. This is a number in
range 0 (=vertical) to 1 (=horizontal).
cmap_range : float, float
The fraction (cmin, cmax) of the colormap that should be
used for the gradient, where the complete colormap is (0, 1).
**kwargs
Other parameters are passed on to `.Axes.imshow()`.
In particular useful is *cmap*.
"""
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range
X = a + (b - a) / X.max() * X
im = ax.imshow(X, extent=extent, interpolation='gaussian',
vmin=0, vmax=1, **kwargs)
return im
def gradient_bar(ax, x, y, width=0.5, bottom=0):
for left, top in zip(x, y):
right = left + width
gradient_image(ax, extent=(left, right, bottom, top),
cmap=plt.cm.Greys, cmap_range=(0., 0.8))
xmin, xmax = xlim = 50, 150
ymin, ymax = ylim = 0, 200
fig, ax = plt.subplots()
ax.set(xlim=xlim, ylim=ylim, autoscale_on=False)
# background image
gradient_image(ax, direction=0, extent=(0, 1, 0, 1), transform=ax.transAxes,
cmap=plt.cm.Greens, cmap_range=(0.6, 0.1))
sample_1 = norm.rvs(loc=100,scale=5,size=1000)
hist_1, bins = np.histogram(sample_1, 50, range=(50,150))
bins = bins[:-1]
x = bins
y = hist_1
gradient_bar(ax, x, y, width=2)
ax.set_aspect('auto')
plt.savefig('gradient_bar.jpg',dpi=130)
plt.show()
解説
モジュールのインポートなど
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%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
plt.rcParams['font.size']=14
plt.rcParams['font.family'] = 'sans-serif'
グラデーションカラー生成関数
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def gradient_image(ax, extent, direction=0.3, cmap_range=(0, 1), **kwargs):
"""
Draw a gradient image based on a colormap.
Parameters
----------
ax : Axes
The axes to draw on.
extent
The extent of the image as (xmin, xmax, ymin, ymax).
By default, this is in Axes coordinates but may be
changed using the *transform* kwarg.
direction : float
The direction of the gradient. This is a number in
range 0 (=vertical) to 1 (=horizontal).
cmap_range : float, float
The fraction (cmin, cmax) of the colormap that should be
used for the gradient, where the complete colormap is (0, 1).
**kwargs
Other parameters are passed on to `.Axes.imshow()`.
In particular useful is *cmap*.
"""
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range
X = a + (b - a) / X.max() * X
im = ax.imshow(X, extent=extent, interpolation='gaussian',
vmin=0, vmax=1, **kwargs)
return im
axではグラデーションカラーを表示する図を指定する。
extentは図中の表示範囲の設定であり、デフォルトはデータ座標なので相対的な座標で設定するには、transform=ax.transAxesなどのようにする。
directionはグラデーションの方向であり、0で垂直方向、1で水平方向となる。
cmap_rangeではカラーマップの範囲を指定する。最低と最高はそれぞれ0と1となる。
phiで角度を指定して、単位ベクトルvでグラデーションの方向を定義する。Xで４隅の座標を得て、a,bの大きさに揃えたXを最終的に得る。これをinterpolation=’gaussian’でimshowすることでグラデーションカラーが得られる。
以下にdirectionを変化させたときの値の変化を示す。
#direction = 0.5
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#direction = 0.5
direction = 0.5
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range = 0.2,0.8
X_ = a + (b - a) / X.max() * X
print(phi)
print(v)
print(X)
print(X_)
'''
0.7853981633974483
[0.70710678 0.70710678]
[[0.70710678 1.41421356]
[0. 0.70710678]]
[[0.5 0.8]
[0.2 0.5]]
'''
#direction = 1
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#direction = 1
direction = 1
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range = 0.2,0.8
X_ = a + (b - a) / X.max() * X
print(phi)
print(v)
print(X)
print(X_)
'''
1.5707963267948966
[6.123234e-17 1.000000e+00]
[[6.123234e-17 1.000000e+00]
[0.000000e+00 1.000000e+00]]
[[0.2 0.8]
[0.2 0.8]]
'''
#direction = 0
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#direction = 0
direction = 0
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range = 0.2,0.8
X_ = a + (b - a) / X.max() * X
print(phi)
print(v)
print(X)
print(X_)
'''
0.0
[1. 0.]
[[1. 1.]
[0. 0.]]
[[0.8 0.8]
[0.2 0.2]]
'''
#direction = 0, a,b =.8,.2
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#direction = 0, a,b =.8,.2
direction = 0
phi = direction * np.pi / 2
v = np.array([np.cos(phi), np.sin(phi)])
X = np.array([[v @ [1, 0], v @ [1, 1]],
[v @ [0, 0], v @ [0, 1]]])
a, b = cmap_range = 0.8,0.2
X_ = a + (b - a) / X.max() * X
print(phi)
print(v)
print(X)
print(X_)
'''
0.0
[1. 0.]
[[1. 1.]
[0. 0.]]
[[0.2 0.2]
[0.8 0.8]]
'''
a, bを降順にすることでグラデーションを逆にすることができる。
グラデーション棒グラフ生成関数
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def gradient_bar(ax, x, y, width=0.5, bottom=0):
for left, top in zip(x, y):
right = left + width
gradient_image(ax, extent=(left, right, bottom, top),
cmap=plt.cm.Greys, cmap_range=(0., 0.8))
棒グラフの角棒のleft, right, bottom, topを取得して、gradient_imageを適用する。
軸範囲の設定
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xmin, xmax = xlim = 50, 150
ymin, ymax = ylim = 0, 200
図の生成
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fig, ax = plt.subplots()
ax.set(xlim=xlim, ylim=ylim, autoscale_on=False)
背景の設定
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# background image
gradient_image(ax, direction=0, extent=(0, 1, 0, 1), transform=ax.transAxes,
cmap=plt.cm.Greens, cmap_range=(0.6, 0.1))
extent=(0, 1, 0, 1), transform=ax.transAxesとすることで図全体にグラデーションカラーを表示できる。
データの生成
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sample_1 = norm.rvs(loc=100,scale=5,size=1000)
hist_1, bins = np.histogram(sample_1, 50, range=(50,150))
bins = bins[:-1]
x = bins
y = hist_1
norm.rvsで正規分布に従うランダムデータを生成する。
棒グラフの表示
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gradient_bar(ax, x, y, width=2)
ax.set_aspect('auto')
gradient_barでグラデーションカラー棒グラフを表示できる。
参考
Bar chart with gradients — Matplotlib 3.1.2 documentation
matplotlib.org
Interpolations for imshow — Matplotlib 3.10.1 documentation
matplotlib.org
matplotlib.pyplot.bar — Matplotlib 3.10.1 documentation
matplotlib.org
コメント
[…] [matplotlib] 58. 棒グラフのbarをグラデーションカラーで表示matplotlibのplt.barで表示する棒グラフの棒の色をグラデーションカラーで表示する方法について説明する。sabopy.com2020.01.29 […]