unique plot marker for each plot

Question

I have a loop where i create some plots and I need unique marker for each plot. I think about creating function, which returns random symbol, and use it in my program in this way:

for i in xrange(len(y)):
    plt.plot(x, y [i], randomMarker())

but I think this way is not good one. I need this just to distinguish plots on legend, because plots must be not connected with lines, they must be just sets of dots.

Answer 1

itertools.cycle will iterate over a list or tuple indefinitely. This is preferable to a function which randomly picks markers for you.

Python 2.x

import itertools
marker = itertools.cycle((',', '+', '.', 'o', '*')) 
for n in y:
    plt.plot(x,n, marker = marker.next(), linestyle='')

Python 3.x

import itertools
marker = itertools.cycle((',', '+', '.', 'o', '*')) 
for n in y:
    plt.plot(x,n, marker = next(marker), linestyle='')

You can use that to produce a plot like this (Python 2.x):

import numpy as np
import matplotlib.pyplot as plt
import itertools

x = np.linspace(0,2,10)
y = np.sin(x)

marker = itertools.cycle((',', '+', '.', 'o', '*')) 

fig = plt.figure()
ax = fig.add_subplot(111)

for q,p in zip(x,y):
    ax.plot(q,p, linestyle = '', marker=marker.next())
    
plt.show()

Answer 2

Just manually create an array that contains marker characters and use that, e.g.:

 markers=[',', '+', '-', '.', 'o', '*']

Answer 3

import matplotlib.pyplot as plt
fig = plt.figure()
markers=['^', 's', 'p', 'h', '8']
for i in range(5):
    plt.plot(x[i], y[i], c='green', marker=markers[i])
    plt.xlabel('X Label')
    plt.ylabel('Y Label') 
plt.show()

Answer 4

You can also use marker generation by tuple e.g. as

import matplotlib.pyplot as plt
markers = [(i,j,0) for i in range(2,10) for j in range(1, 3)]
[plt.plot(i, 0, marker = markers[i], ms=10) for i in range(16)]

See Matplotlib markers doc site for details.

In addition, this can be combined with itertools.cycle looping mentioned above

Answer 5

It appears that nobody has mentioned the built-in pyplot method for cycling properties yet. So here it is:

import numpy as np
import matplotlib.pyplot as plt
from cycler import cycler

x = np.linspace(0,3,20)
y = np.sin(x)

fig = plt.figure()
plt.gca().set_prop_cycle(marker=['o', '+', 'x', '*', '.', 'X']) # gca()=current axis

for q,p in zip(x,y):
    plt.plot(q,p, linestyle = '')

plt.show()

However, this way you lose the color cycle. You can add back color by multiplying or adding a color cycler and a marker cycler object, like this:

fig = plt.figure()

markercycle = cycler(marker=['o', '+', 'x', '*', '.', 'X'])
colorcycle = cycler(color=['blue', 'orange', 'green', 'magenta'])
# Or use the default color cycle:
# colorcycle = cycler(color=plt.rcParams['axes.prop_cycle'].by_key()['color'])

plt.gca().set_prop_cycle(colorcycle * markercycle) # gca()=current axis

for q,p in zip(x,y):
    plt.plot(q,p, linestyle = '')

plt.show()

When adding cycles, they need to have the same length, so we only use the first four elements of markercycle in that case:

plt.gca().set_prop_cycle(colorcycle + markercycle[:4]) # gca()=current axis