Is there any way to express changing color from Matplotlib, Python?

Question

Before you reading, I apologize about broken English. I have a data array of moving mass, and want to show them by time area. Like:

import matplotlib.pyplot as plt
import numpy as np

x = np.array([0, 1, 2, 3])
y = np.array([3, 4, 5, 6])

plt.plot(x,y)

In this code, I just want to see them with different color each rows. For example, point (0,3) is white dot, point (3,5) is black dot, and (1,4) , (2,5) are gray dot but different brightness.

I just started python, so I searched pyplot lib but didn't find examples.

I tried with Seaborn library, and Pyplot 3d examples. But didn't find solution to express what want to do.

Does this answer your question? [matplotlib scatter plot with different markers and colors](https://stackoverflow.com/questions/26490817/matplotlib-scatter-plot-with-different-markers-and-colors) — Derek O, Dec 22 '22 at 04:43

score 0 · Answer 1 · answered Dec 22 '22 at 06:04

Pass a color argument into a scatter function that displays given points and any defined features.

#array declaration
#...

for x1, y1 in zip(x, y):
    if x1 == 0:
        color = "white"
    elif x1 == 1 or x1 == 2:
        color = "gray"
    elif x1 == 3:
        color = "black"
        
    plt.scatter(x1, y1, c=color)

# plot linear line from arrays

We use the zip class to iterate through both arrays at once, allowing us to plot each point from the given arrays. We use the x-coordinates from the x array to determine what color to label the dot. The scatter function puts this point on the graph, giving us options to change features of the given dot(s).

--

The final code would look something like this:

import matplotlib.pyplot as plt
import numpy as np

x = np.array([0, 1, 2, 3])
y = np.array([3, 4, 5, 6])

for x1, y1 in zip(x, y):
    if x1 == 0:
        color = "white"
    elif x1 == 1 or x1 == 2:
        color = "gray"
    elif x1 == 3:
        color = "black"
        
    plt.scatter(x1, y1, c=color)

plt.plot(x, y)
plt.show()

Documentation on matplotlib's scatter function can be found here

I believe there is a more efficient method of setting each point's colors. I'm not too sure on how it can be implemented. — poiboi, Dec 22 '22 at 06:06
Thank you for answering! But I still wondering to coloring datas by orders (row / column number) not by values. I'll try to find another way. — Alfed, Dec 22 '22 at 07:01

score 0 · Answer 2 · answered Dec 22 '22 at 06:58

poiboi was on the right track. Here's an example which automatically sets a linear gradient for the colours of the dots.

import matplotlib.pyplot as plt
import numpy as np
x = [0, 1, 2, 3]
y = [3, 4, 5, 6]
plt.scatter(x, y, c=x[:: -1], cmap='gray', vmin=min(x), vmax=max(x))
plt.show()

The c keyword argument tells Matplotlib which colour to use for which point using a grey colourmap. By default, said colourmap goes from black to white, so we pass x reversed. vmin and vmax are the least and greatest values to be assigned colours. Note that the first point is white (hence invisible).

gboffi · Accepted Answer · 2022-12-24T13:22:43.717

If your aim is to identify the order of your points, you can use a colormap, specifying that the vector that determines the coloring is simply the sequence of the indices of the points.

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(20201222)
x = np.random.randint(5, 20, 20)
y = np.random.randint(5, 20, 20)

r = range(len(x))
plt.scatter(x, y, s=80, c=r, cmap='plasma')
plt.grid()
cb = plt.colorbar()
cb.set_ticks(r)
cb.set_ticklabels(("%d"%(order+1) for order in r))

and eventually the very awaited overworked implementation

import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate

np.random.seed(20201222)
x = np.random.rand(20)*5+np.arange(20)/3
y = np.random.rand(20)*5+np.arange(20)/3
tck, u = interpolate.splprep([x,y] ,s=0.05)
x1, y1 = interpolate.splev(np.linspace(0, 1, 3333), tck)

r = range(len(x))
plt.plot(x1, y1, color='k', lw=0.4, alpha=0.4)
plt.scatter(x, y, s=60, c=r, cmap='Greys', ec='grey', zorder=4)
plt.xlim((0,12)), plt.ylim((0,12))
plt.grid(1)
plt.gca().set_aspect(1)
cb = plt.colorbar()
cb.set_ticks((0, len(x)-1))
cb.set_ticklabels(('First', 'Last'))

Maybe this one is I'm looking for. I'm not sure about cmap variable(function?), so gonna try this one. — Alfed, Dec 23 '22 at 04:23

Is there any way to express changing color from Matplotlib, Python?

3 Answers3

and eventually the very awaited overworked implementation