如何在 matplotlib 中绘制渐变色线？

Question

为了以一般形式陈述它，我正在寻找一种使用 matplotlib 将几个点与 渐变色线 连接起来的方法，但我没有在任何地方找到它。更具体地说，我正在绘制一个带有单色线的二维随机游走。但是，由于这些点具有相关顺序，我想查看绘图并查看数据移动的位置。渐变色的线条可以解决问题。或者透明度逐渐变化的线条。

我只是想改进我的数据的可视化。看看这张由 R 的 ggplot2 包生成的美丽图像。我正在 matplotlib 中寻找相同的图像。谢谢。

原文由 PDRX 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

我最近用类似的请求回答了一个问题（ 使用 matplotlib 创建超过 20 种独特的图例颜色）。我在那里展示了您可以将绘制线条所需的颜色循环映射到颜色图。您可以使用相同的过程为每对点获取特定颜色。

您应该仔细选择颜色贴图，因为如果颜色贴图是彩色的，则沿着您的线条的颜色过渡可能会显得剧烈。

或者，您可以更改每条线段的 alpha，范围从 0 到 1。

下面的代码示例中包含一个例程 ( highResPoints )，用于扩展随机游走的点数，因为如果点太少，转换可能看起来很激烈。这段代码的灵感来自于我最近提供的另一个答案： https ://stackoverflow.com/a/8253729/717357

 import numpy as np
import matplotlib.pyplot as plt

def highResPoints(x,y,factor=10):
    '''
    Take points listed in two vectors and return them at a higher
    resultion. Create at least factor*len(x) new points that include the
    original points and those spaced in between.

    Returns new x and y arrays as a tuple (x,y).
    '''

    # r is the distance spanned between pairs of points
    r = [0]
    for i in range(1,len(x)):
        dx = x[i]-x[i-1]
        dy = y[i]-y[i-1]
        r.append(np.sqrt(dx*dx+dy*dy))
    r = np.array(r)

    # rtot is a cumulative sum of r, it's used to save time
    rtot = []
    for i in range(len(r)):
        rtot.append(r[0:i].sum())
    rtot.append(r.sum())

    dr = rtot[-1]/(NPOINTS*RESFACT-1)
    xmod=[x[0]]
    ymod=[y[0]]
    rPos = 0 # current point on walk along data
    rcount = 1
    while rPos < r.sum():
        x1,x2 = x[rcount-1],x[rcount]
        y1,y2 = y[rcount-1],y[rcount]
        dpos = rPos-rtot[rcount]
        theta = np.arctan2((x2-x1),(y2-y1))
        rx = np.sin(theta)*dpos+x1
        ry = np.cos(theta)*dpos+y1
        xmod.append(rx)
        ymod.append(ry)
        rPos+=dr
        while rPos > rtot[rcount+1]:
            rPos = rtot[rcount+1]
            rcount+=1
            if rcount>rtot[-1]:
                break

    return xmod,ymod

#CONSTANTS
NPOINTS = 10
COLOR='blue'
RESFACT=10
MAP='winter' # choose carefully, or color transitions will not appear smoooth

# create random data
np.random.seed(101)
x = np.random.rand(NPOINTS)
y = np.random.rand(NPOINTS)

fig = plt.figure()
ax1 = fig.add_subplot(221) # regular resolution color map
ax2 = fig.add_subplot(222) # regular resolution alpha
ax3 = fig.add_subplot(223) # high resolution color map
ax4 = fig.add_subplot(224) # high resolution alpha

# Choose a color map, loop through the colors, and assign them to the color
# cycle. You need NPOINTS-1 colors, because you'll plot that many lines
# between pairs. In other words, your line is not cyclic, so there's
# no line from end to beginning
cm = plt.get_cmap(MAP)
ax1.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])
for i in range(NPOINTS-1):
    ax1.plot(x[i:i+2],y[i:i+2])

ax1.text(.05,1.05,'Reg. Res - Color Map')
ax1.set_ylim(0,1.2)

# same approach, but fixed color and
# alpha is scale from 0 to 1 in NPOINTS steps
for i in range(NPOINTS-1):
    ax2.plot(x[i:i+2],y[i:i+2],alpha=float(i)/(NPOINTS-1),color=COLOR)

ax2.text(.05,1.05,'Reg. Res - alpha')
ax2.set_ylim(0,1.2)

# get higher resolution data
xHiRes,yHiRes = highResPoints(x,y,RESFACT)
npointsHiRes = len(xHiRes)

cm = plt.get_cmap(MAP)

ax3.set_color_cycle([cm(1.*i/(npointsHiRes-1))
                     for i in range(npointsHiRes-1)])

for i in range(npointsHiRes-1):
    ax3.plot(xHiRes[i:i+2],yHiRes[i:i+2])

ax3.text(.05,1.05,'Hi Res - Color Map')
ax3.set_ylim(0,1.2)

for i in range(npointsHiRes-1):
    ax4.plot(xHiRes[i:i+2],yHiRes[i:i+2],
             alpha=float(i)/(npointsHiRes-1),
             color=COLOR)
ax4.text(.05,1.05,'High Res - alpha')
ax4.set_ylim(0,1.2)

fig.savefig('gradColorLine.png')
plt.show()

此图显示了四种情况：

原文由 Yann 发布，翻译遵循 CC BY-SA 3.0 许可协议

Answer 2

请注意，如果您有很多点，则为每个线段调用 plt.plot 可能会非常慢。使用 LineCollection 对象效率更高。

使用 colorline 配方，您可以执行以下操作：

 import matplotlib.pyplot as plt
import numpy as np
import matplotlib.collections as mcoll
import matplotlib.path as mpath

def colorline(
    x, y, z=None, cmap=plt.get_cmap('copper'), norm=plt.Normalize(0.0, 1.0),
        linewidth=3, alpha=1.0):
    """
    http://nbviewer.ipython.org/github/dpsanders/matplotlib-examples/blob/master/colorline.ipynb
    http://matplotlib.org/examples/pylab_examples/multicolored_line.html
    Plot a colored line with coordinates x and y
    Optionally specify colors in the array z
    Optionally specify a colormap, a norm function and a line width
    """

    # Default colors equally spaced on [0,1]:
    if z is None:
        z = np.linspace(0.0, 1.0, len(x))

    # Special case if a single number:
    if not hasattr(z, "__iter__"):  # to check for numerical input -- this is a hack
        z = np.array([z])

    z = np.asarray(z)

    segments = make_segments(x, y)
    lc = mcoll.LineCollection(segments, array=z, cmap=cmap, norm=norm,
                              linewidth=linewidth, alpha=alpha)

    ax = plt.gca()
    ax.add_collection(lc)

    return lc

def make_segments(x, y):
    """
    Create list of line segments from x and y coordinates, in the correct format
    for LineCollection: an array of the form numlines x (points per line) x 2 (x
    and y) array
    """

    points = np.array([x, y]).T.reshape(-1, 1, 2)
    segments = np.concatenate([points[:-1], points[1:]], axis=1)
    return segments

N = 10
np.random.seed(101)
x = np.random.rand(N)
y = np.random.rand(N)
fig, ax = plt.subplots()

path = mpath.Path(np.column_stack([x, y]))
verts = path.interpolated(steps=3).vertices
x, y = verts[:, 0], verts[:, 1]
z = np.linspace(0, 1, len(x))
colorline(x, y, z, cmap=plt.get_cmap('jet'), linewidth=2)

plt.show()

原文由 unutbu 发布，翻译遵循 CC BY-SA 3.0 许可协议