Matplotlib散点图; 颜色作为第三个变量的函数

问题:Matplotlib散点图; 颜色作为第三个变量的函数

我想制作一个散点图(使用matplotlib),其中根据第三个变量对点进行阴影处理。我对此非常了解:

plt.scatter(w, M, c=p, marker='s')

其中w和M是数据点,而p是我要针对其着色的变量。
但是我想用灰度而不是彩色来做。有人可以帮忙吗?

I want to make a scatterplot (using matplotlib) where the points are shaded according to a third variable. I’ve got very close with this:

plt.scatter(w, M, c=p, marker='s')

where w and M are the datapoints and p is the variable I want to shade with respect to.
However I want to do it in greyscale rather than colour. Can anyone help?


回答 0

无需手动设置颜色。相反,请指定灰度颜色图…

import numpy as np
import matplotlib.pyplot as plt

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

# Plot...
plt.scatter(x, y, c=y, s=500)
plt.gray()

plt.show()

或者,如果您希望使用更大范围的颜色图,也可以将cmapkwarg 指定为scatter。要使用其中任何一个的反向版本,只需指定其中_r任何一个的“ ”版本即可。例如,gray_r而不是gray。有几种不同的灰度色彩映射预先制作的(如graygist_yargbinary,等)。

import matplotlib.pyplot as plt
import numpy as np

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

plt.scatter(x, y, c=y, s=500, cmap='gray')
plt.show()

There’s no need to manually set the colors. Instead, specify a grayscale colormap…

import numpy as np
import matplotlib.pyplot as plt

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

# Plot...
plt.scatter(x, y, c=y, s=500)
plt.gray()

plt.show()

Or, if you’d prefer a wider range of colormaps, you can also specify the cmap kwarg to scatter. To use the reversed version of any of these, just specify the “_r” version of any of them. E.g. gray_r instead of gray. There are several different grayscale colormaps pre-made (e.g. gray, gist_yarg, binary, etc).

import matplotlib.pyplot as plt
import numpy as np

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

plt.scatter(x, y, c=y, s=500, cmap='gray')
plt.show()

回答 1

在matplotlib中,可以将灰色表示为介于0-1之间的数字值。
例如c = '0.1'

然后,您可以将第三个变量转换为该范围内的值,并使用它为点着色。
在以下示例中,我将点的y位置用作确定颜色的值:

from matplotlib import pyplot as plt

x = [1, 2, 3, 4, 5, 6, 7, 8, 9]
y = [125, 32, 54, 253, 67, 87, 233, 56, 67]

color = [str(item/255.) for item in y]

plt.scatter(x, y, s=500, c=color)

plt.show()

In matplotlib grey colors can be given as a string of a numerical value between 0-1.
For example c = '0.1'

Then you can convert your third variable in a value inside this range and to use it to color your points.
In the following example I used the y position of the point as the value that determines the color:

from matplotlib import pyplot as plt

x = [1, 2, 3, 4, 5, 6, 7, 8, 9]
y = [125, 32, 54, 253, 67, 87, 233, 56, 67]

color = [str(item/255.) for item in y]

plt.scatter(x, y, s=500, c=color)

plt.show()


回答 2

有时您可能需要根据x值情况精确绘制颜色。例如,您可能有一个包含3种类型的变量和一些数据点的数据框。您想做以下事情,

  • 在RED中绘制对应于物理变量’A’的点。
  • 在BLUE中绘制与物理变量“ B”相对应的点。
  • 在绿色中绘制对应于物理变量“ C”的点。

在这种情况下,您可能必须编写short函数以将x值映射为对应的颜色名称作为列表,然后将该列表传递给plt.scatter命令。

x=['A','B','B','C','A','B']
y=[15,30,25,18,22,13]

# Function to map the colors as a list from the input list of x variables
def pltcolor(lst):
    cols=[]
    for l in lst:
        if l=='A':
            cols.append('red')
        elif l=='B':
            cols.append('blue')
        else:
            cols.append('green')
    return cols
# Create the colors list using the function above
cols=pltcolor(x)

plt.scatter(x=x,y=y,s=500,c=cols) #Pass on the list created by the function here
plt.grid(True)
plt.show()

Sometimes you may need to plot color precisely based on the x-value case. For example, you may have a dataframe with 3 types of variables and some data points. And you want to do following,

  • Plot points corresponding to Physical variable ‘A’ in RED.
  • Plot points corresponding to Physical variable ‘B’ in BLUE.
  • Plot points corresponding to Physical variable ‘C’ in GREEN.

In this case, you may have to write to short function to map the x-values to corresponding color names as a list and then pass on that list to the plt.scatter command.

x=['A','B','B','C','A','B']
y=[15,30,25,18,22,13]

# Function to map the colors as a list from the input list of x variables
def pltcolor(lst):
    cols=[]
    for l in lst:
        if l=='A':
            cols.append('red')
        elif l=='B':
            cols.append('blue')
        else:
            cols.append('green')
    return cols
# Create the colors list using the function above
cols=pltcolor(x)

plt.scatter(x=x,y=y,s=500,c=cols) #Pass on the list created by the function here
plt.grid(True)
plt.show()