Using matplotlib to draw a path given cartesian coordinates

Question

I'm new to matplotlib and numpy and am trying to plot some array data to something like this:

but it currently looks like this:

My code is extremely basic but basically the image above is what I'd like to be able to do. I'm not too concerned yet with drawing gridlines but the plot should be proportional. I've looked at some examples on the mathplotlib website but can't find something similar enough. I wonder if pyplot is not the correct procedure or if my array is not formatted correctly?

import numpy as np
from matplotlib import pyplot as plt

data = [(2, 2), (3, 2), (4, 1), (4, 0), (3, 0), (3, 1), (4, 2),
        (4, 3), (4, 4), (3, 3), (3, 4), (2, 4), (2, 3), (1, 4),
        (0, 4), (0, 3), (1, 3), (0, 2), (1, 2), (0, 1), (0, 0),
        (1, 0), (1, 1), (2, 0), (2, 1)]

data = np.asarray(data)
print(data)
plt.ylim(0, 4)
plt.xlim(0, 4)
plt.axis([0, 4, 0, 4])
plt.plot(data)
plt.show()

Answer 1

Try

plt.plot(*data.transpose())

instead of

plt.plot(data)

The plt.plot function takes 2 arrays, one with all the x-values and one with all the y-values. You cannot pass it a mixture of x and y values. The transpose method will reorder the values so that all x values are together and all y values are togheter and the star * operator will unpack those arrays into tow separate function arguments.

Answer 2

You need to unpack the x and y components into arrays like this:

plt.plot([p[0] for p in data], [p[1] for p in data], 'o-')

Use format style "o-": "o" for a symbol marker and "-" for a solid line.

To also format the x/y ticks here is the full code:

from matplotlib import pyplot as plt

data = [(2, 2), (3, 2), (4, 1), (4, 0), (3, 0), (3, 1), (4, 2),
        (4, 3), (4, 4), (3, 3), (3, 4), (2, 4), (2, 3), (1, 4),
        (0, 4), (0, 3), (1, 3), (0, 2), (1, 2), (0, 1), (0, 0),
        (1, 0), (1, 1), (2, 0), (2, 1)]

x = [p[0] for p in data]
y = [p[1] for p in data]
_, ax = plt.subplots()
ax.set_xticks(range(5))
ax.set_yticks(range(5))
ax.plot(x, y, 'o-', color='blue')
plt.grid() # add grid lines
plt.show()

Output:

Answer 3

To complete other answers, here is the closest I got in a reasonable amount of time to your desired output :

import numpy as np
from matplotlib import pyplot as plt

data = [(2, 2), (3, 2), (4, 1), (4, 0), (3, 0), (3, 1), (4, 2),
        (4, 3), (4, 4), (3, 3), (3, 4), (2, 4), (2, 3), (1, 4),
        (0, 4), (0, 3), (1, 3), (0, 2), (1, 2), (0, 1), (0, 0),
        (1, 0), (1, 1), (2, 0), (2, 1)]

data = np.asarray(data)
print(data)

# make axis equal and turn them off
plt.axis('equal')
plt.axis('off')

for i in range(5):
    # horizontal and vertical background lines
    plt.plot([i,i], [0,4], linewidth=0.5, color='black')
    plt.plot([0,4], [i,i], linewidth=0.5, color='black')
plt.plot(data[:,0], data[:,1], 'b') # line segments
plt.scatter(data[:,0], data[:,1], c='b') # markers

plt.show()

Output:

---

Edit

From this question, you can add numbers at each marker through plt.annotate. Just add this after plt.scatter :

offset = np.array([0.1, 0.1])
for i in range(data.shape[0]):
    # For each marker
    plt.annotate(str(i+1), data[i]+offset)

Output:

---

Edit #2:

As a bonus, here is my attempt as getting the closest possible to the reference figure:

import numpy as np
from matplotlib import pyplot as plt

data = [(2, 2), (3, 2), (4, 1), (4, 0), (3, 0), (3, 1), (4, 2),
        (4, 3), (4, 4), (3, 3), (3, 4), (2, 4), (2, 3), (1, 4),
        (0, 4), (0, 3), (1, 3), (0, 2), (1, 2), (0, 1), (0, 0),
        (1, 0), (1, 1), (2, 0), (2, 1)]

data = np.asarray(data)
print(data)

# make axis equal and turn them off
plt.axis('equal')
plt.axis('off')

for i in range(5):
    # horizontal and vertical background lines
    plt.plot([i,i], [0,4], linewidth=1.5, color='#b3b3b3', zorder=1)
    plt.plot([0,4], [i,i], linewidth=1.5, color='#b3b3b3', zorder=1)

plt.plot(data[:,0], data[:,1], '#274b8b', linewidth=2.5, zorder=2) # line segments
plt.scatter(data[np.arange(len(data))!=7,0], data[np.arange(len(data))!=7,1], s=60, c='#4472c4', edgecolors='#2e569c', zorder=3) # markers
# marker for point 7 is not plotted in reference figure

# Individual points numbers, not in reference figure so commented
# offset = np.array([0.1, 0.1])
# for i in range(data.shape[0]):
    # # For each marker
    # plt.annotate(str(i+1), data[i]+offset)

for i in range(5):
    plt.annotate(str(i), [i-0.05, -0.25]) # X axis numbers
    plt.annotate(str(i), [-0.2, i-0.07]) # Y axis numbers


plt.show()

Answer 4

You could try something like this:

import numpy as np
from matplotlib import pyplot as plt

data = [(2, 2), (3, 2), (4, 1), (4, 0), (3, 0), (3, 1), (4, 2),
        (4, 3), (4, 4), (3, 3), (3, 4), (2, 4), (2, 3), (1, 4),
        (0, 4), (0, 3), (1, 3), (0, 2), (1, 2), (0, 1), (0, 0),
        (1, 0), (1, 1), (2, 0), (2, 1)]

for i in range(len(data) -1): 
  x1 = data[i][0]
  y1 = data[i][1]
  x2 = data[i+1][0]
  y2 = data[i+1][1]
  plt.plot([x1, x2], [y1, y2], c='blue')
  plt.scatter(x1, y1, c='blue')
plt.show()