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.

Asked By: Alfed

||

Source

Answer 1

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

Answered By: poiboi

Answer 2

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).

Answered By: tfpf

Answer 3

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'))

Answered By: gboffi

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

Question:

Answers:

and eventually the very awaited overworked implementation