如何使一维阵列成为散点图中两个二维阵列的颜色
如何使一维阵列成为散点图中两个二维阵列的颜色
提问于 2021-11-15 17:50:27
这个问题不是最清楚的，但当我尝试在散点图上绘制不同的颜色vi颜色图时，基本上得到了这个错误。我有两个二维数组(x和y)，它们的大小都是42,100。我想要绘制颜色，但基于一维阵列和大小为42。然而，我得到了一个重复出现的错误：
请注意，这只是一个可重复性的例子！
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
# test
x = np.random.rand(42,100)
y = np.random.rand(42,100)
color = np.arange(0,42,1)
# scatter plot of x and y with no colormap!
plt.scatter(x,y,s=5)
plt.show()
# error occurs when trying to plot the 1D array as the color
plt.scatter(x,y,s=5,c=color,cmap='jet')
plt.show()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/axes/_axes.py in _parse_scatter_color_args(c, edgecolors, kwargs, xsize, get_next_color_func)
4349 try: # Is 'c' acceptable as PathCollection facecolors?
-> 4350 colors = mcolors.to_rgba_array(c)
4351 except (TypeError, ValueError) as err:
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/colors.py in to_rgba_array(c, alpha)
384 else:
--> 385 rgba = np.array([to_rgba(cc) for cc in c])
386
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/colors.py in <listcomp>(.0)
384 else:
--> 385 rgba = np.array([to_rgba(cc) for cc in c])
386
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/colors.py in to_rgba(c, alpha)
205 if rgba is None: # Suppress exception chaining of cache lookup failure.
--> 206 rgba = _to_rgba_no_colorcycle(c, alpha)
207 try:
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/colors.py in _to_rgba_no_colorcycle(c, alpha)
283 if not np.iterable(c):
--> 284 raise ValueError(f"Invalid RGBA argument: {orig_c!r}")
285 if len(c) not in [3, 4]:
ValueError: Invalid RGBA argument: 0.0
The above exception was the direct cause of the following exception:
ValueError Traceback (most recent call last)
/tmp/ipykernel_2811997/1837670260.py in <module>
----> 1 plt.scatter(x,y,s=5,c=color,cmap='jet')
2 plt.show()
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/pyplot.py in scatter(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, edgecolors, plotnonfinite, data, **kwargs)
3066 vmin=None, vmax=None, alpha=None, linewidths=None, *,
3067 edgecolors=None, plotnonfinite=False, data=None, **kwargs):
-> 3068 __ret = gca().scatter(
3069 x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
3070 vmin=vmin, vmax=vmax, alpha=alpha, linewidths=linewidths,
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/__init__.py in inner(ax, data, *args, **kwargs)
1359 def inner(ax, *args, data=None, **kwargs):
1360 if data is None:
-> 1361 return func(ax, *map(sanitize_sequence, args), **kwargs)
1362
1363 bound = new_sig.bind(ax, *args, **kwargs)
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/axes/_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, edgecolors, plotnonfinite, **kwargs)
4514 orig_edgecolor = kwargs.get('edgecolor', None)
4515 c, colors, edgecolors = \
-> 4516 self._parse_scatter_color_args(
4517 c, edgecolors, kwargs, x.size,
4518 get_next_color_func=self._get_patches_for_fill.get_next_color)
~/miniconda3/envs/py3_std_maps/lib/python3.9/site-packages/matplotlib/axes/_axes.py in _parse_scatter_color_args(c, edgecolors, kwargs, xsize, get_next_color_func)
4354 else:
4355 if not valid_shape:
-> 4356 raise invalid_shape_exception(c.size, xsize) from err
4357 # Both the mapping *and* the RGBA conversion failed: pretty
4358 # severe failure => one may appreciate a verbose feedback.
ValueError: 'c' argument has 42 elements, which is inconsistent with 'x' and 'y' with size 4200.看起来这个错误与2d数组的形状有关(已将其重塑为4200...)。
如果将颜色数组更改为与4200的形状相匹配，则该错误将消失：
color_but_not_accurate = np.linspace(0,42,4200)
plt.scatter(x,y,s=5,c=color_but_not_accurate,cmap='jet')
plt.show()但在我的实际程序中，我需要将颜色数组保留为42的形状，以便颜色栏有意义。是否有解决此问题的方法？目标是绘制x和y的散点图(大小为42，100的二维数组)，然后根据大小为42？谢谢！
Stack Overflow用户
回答已采纳
发布于 2021-11-15 18:24:47
您可以使用color = np.repeat(np.arange(42), 100)，将每个颜色值重复数据中的列数。
下面是一个例子。为方便调试，行数减为4，列数减为10：
import matplotlib.pyplot as plt
import numpy as np
x = np.tile(np.arange(10), 4).reshape(4, 10)
y = (np.random.randn(4, 10) + 0.1).cumsum(axis=1) + np.arange(0, 40, 10)[:, np.newaxis]
color = np.repeat(np.arange(x.shape[0]), x.shape[1])
plt.scatter(x, y, s=50, c=color, cmap='plasma')
plt.colorbar(ticks=np.arange(x.shape[0]))
plt.show()
使用数据的原始大小，示例将如下所示：
import matplotlib.pyplot as plt
import numpy as np
x = np.tile(np.arange(100), 42).reshape(42, 100)
y = (np.random.randn(42, 100) + 0.01).cumsum(axis=1) + np.arange(0, 420, 10)[:, np.newaxis]
color = np.repeat(np.arange(x.shape[0]), x.shape[1])
plt.scatter(x, y, s=5, c=color, cmap='plasma')
plt.colorbar(ticks=np.arange(x.shape[0]))
plt.show()
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/69978702
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