'c' 参数看起来像一个单一的数字 RGB 或 RGBA 序列

Question

我的 juypter 笔记本出现以下错误。我已将 mathplotlib 更新为最新版本，但仍然出现错误

'c' 参数看起来像一个单一的数字 RGB 或 RGBA 序列，应该避免这种情况，因为如果其长度与 'x' 和 'y' 匹配，则值映射将具有优先权。如果您真的想为所有点指定相同的 RGB 或 RGBA 值，请使用单行的二维数组。

X=lab3_data
range_n_clusters = [2, 3, 4, 5, 6,7,8]

for n_clusters in range_n_clusters:
# Create a subplot with 1 row and 2 columns
fig, (ax1, ax2) = plt.subplots(1, 2)
fig.set_size_inches(18, 7)

# The 1st subplot is the silhouette plot
# The silhouette coefficient can range from -1, 1 but in this example all
# lie within [-0.1, 1]
ax1.set_xlim([0, 1])
# The (n_clusters+1)*10 is for inserting blank space between silhouette
# plots of individual clusters, to demarcate them clearly.
ax1.set_ylim([0, len(X) + (n_clusters + 1) * 10])

# Initialize the clusterer with n_clusters value and a random generator
# seed of 10 for reproducibility.
clusterer = cluster.KMeans(n_clusters=n_clusters, random_state=10)
cluster_labels = clusterer.fit_predict(X)

# The silhouette_score gives the average value for all the samples.
# This gives a perspective into the density and separation of the formed
# clusters
silhouette_avg = silhouette_score(X, cluster_labels)
print("For n_clusters =", n_clusters,
      "The average silhouette_score is :", silhouette_avg)

# Compute the silhouette scores for each sample
sample_silhouette_values = silhouette_samples(X, cluster_labels)

y_lower = 10
for i in range(n_clusters):
    # Aggregate the silhouette scores for samples belonging to
    # cluster i, and sort them
    ith_cluster_silhouette_values = \
        sample_silhouette_values[cluster_labels == i]

    ith_cluster_silhouette_values.sort()

    size_cluster_i = ith_cluster_silhouette_values.shape[0]
    y_upper = y_lower + size_cluster_i

    color = cm.nipy_spectral(float(i) / n_clusters)
    ax1.fill_betweenx(np.arange(y_lower, y_upper),
                      0, ith_cluster_silhouette_values,
                      facecolor=color, edgecolor=color, alpha=0.7)

    # Label the silhouette plots with their cluster numbers at the middle
    ax1.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i))

    # Compute the new y_lower for next plot
    y_lower = y_upper + 10  # 10 for the 0 samples

ax1.set_title("The silhouette plot for the various clusters.")
ax1.set_xlabel("The silhouette coefficient values")
ax1.set_ylabel("Cluster label")

# The vertical line for average silhouette score of all the values
ax1.axvline(x=silhouette_avg, color="red", linestyle="--")

ax1.set_yticks([])  # Clear the yaxis labels / ticks
ax1.set_xticks([0, 0.2, 0.4, 0.6, 0.8, 1])

# 2nd Plot showing the actual clusters formed
# append the cluster centers to the dataset
lab3_data_and_centers = np.r_[lab3_data,clusterer.cluster_centers_]
# project both th data and the k-Means cluster centers to a 2D space
XYcoordinates = manifold.MDS(n_components=2).fit_transform(lab3_data_and_centers)
# plot the transformed examples and the centers
# use the cluster assignment to colour the examples
# plot the transformed examples and the centers
# use the cluster assignment to colour the examples

clustering_scatterplot(points=XYcoordinates[:-n_clusters,:], 
                       labels=cluster_labels,
                       centers=XYcoordinates[-n_clusters:,:], 
                       title='MDS')

plt.suptitle(("Silhouette analysis for KMeans clustering on sample data "
              "with n_clusters = %d" % n_clusters),
             fontsize=14, fontweight='bold')


plt.show()

Answer 1

您还可以使用以下方法使 c 参数变为 2D：

    c=color.reshape(1,-1)

或者

    c=np.array([color])

或者只是将原始颜色数组更改为 2D：

    color = cm.nipy_spectral(float(i) / n_clusters).reshape(1,-1)

ps：因为我需要 50 个声望才能发表评论，所以我只是打开一个新答案，尽管这应该只是使用内置 numpy.atleast_2D() 的 D Adams 解决方案下方的评论。

Answer 2

作为一种解决方法：

 from matplotlib.axes._axes import _log as matplotlib_axes_logger
 matplotlib_axes_logger.setLevel('ERROR')

Answer 3

首先生成数据并定义颜色：

import numpy
import matplotlib
import matplotlib.pyplot

#Make the color you actually want:
Color = numpy.array([.5, .6, .7])

#Make some data:
Vals = numpy.random.uniform( size = (10, 3) )
PointCount = Vals.shape[0]
Xvals = Vals[:, 0]
Yvals = Vals[:, 1]
Zvals = Vals[:, 2]

第二次重现问题：

#2D: Produce the warning
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111)
matplotlib.pyplot.scatter( Xvals, Yvals, c= Color,   )

'c' argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with 'x' & 'y'.  Please use a 2-D array with a single row if you really want to specify the same RGB or RGBA value for all points.

第一个解决方案是制作所需颜色的副本数组：

#Illustrate how to repeat a numpy array:
ValsCount = Vals.shape[0]
ColorsRepeated = numpy.repeat(numpy.atleast_2d(Color), ValsCount, axis = 0)
print ('ColorsRepeated')
print (ColorsRepeated)

#2D: Make scatter plot without color warning using repeat
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111)
matplotlib.pyplot.scatter( Xvals, Yvals, c= ColorsRepeated, )

#3D: Make scatter plot without color warning using repeat
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111, projection='3d')
matplotlib.pyplot.scatter( Xvals,  Yvals, Zvals, c=ColorsRepeated,  )

ColorsRepeated
[[0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]
 [0.5 0.6 0.7]]

另一个解决方案是使用matplotlib.pyplot.plot它不会抛出相同的警告，并且matplotlib.pyplot.scatter您可以避免使用常规绘图命令的颜色重复问题，并且只是不连接点：

#2D: Make regular plot without using repeat
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111)
matplotlib.pyplot.plot( Xvals, Yvals, c= Color, marker = '.', linestyle = '', )

另一种解决方案是使颜色成为具有单行的二维数组，以解决matplotlib.pyplot.scatter和 的问题，但会引发错误matplotlib.pyplot.plot：

#2D: Use single row in 2D array to avoid warning
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111)
matplotlib.pyplot.scatter( Xvals,  Yvals, c= numpy.atleast_2d(Color), )

使用matplotlib.pyplot.plot带有 2D 颜色单行的常规命令会引发错误：

#2D: Try and fail to use a single row in 2D array in a regular plot
fig = matplotlib.pyplot.figure() 
subplot = fig.add_subplot(111)
matplotlib.pyplot.plot( Xvals, Yvals,  c= numpy.atleast_2d(Color),  marker = '.', linestyle = '', )

ValueError: Invalid RGBA argument: array([[0.5, 0.6, 0.7]])

结论： 在颜色方面表现不同matplotlib.pyplot.plot。需要一维数组。需要一个二维数组。二维数组可以是单行，也可以是重复的，或者每个数据点具有不同的颜色。如果 matplotlib 社区能够添加一个 if 语句来为我们执行重复操作并删除警告，那就太好了。matplotlib.pyplot.scattermatplotlib.pyplot.plotmatplotlib.pyplot.scatter

Answer 4

在最新版本的 matplotlib (3.0.3) 中，参数 'c' 应该是一个二维数组。如果“c”的长度与“x”和“y”的长度匹配，则每个点的颜色对应于“c”的元素。如果你想让每个点显示相同的颜色，'c'应该是一个单行的二维数组，例如c=np.array([0.5, 0.5, 0.5])。最好的祝愿！