Annotating distance of 2D line plot with matplotlib in Python

Question

Does anyone have idea, how to show distance of each point in plot. I am using matplotlib for this purpose. The distance function is already made which is working under for loop to print distance of each line segment. But I would like to have these distances showing on each line segment plot. Any help in this regards will be appreciated.

from math import *

import matplotlib.pyplot as plt

import numpy as np

def DistanceBwPoints(ln1):

    x1 , y1 = ln1[0][0] , ln1[0][1]
    x2 , y2 = ln1[1][0] , ln1[1][1]

    dis = sqrt ((x2 - x1)**2 + (y2 - y1)**2 )

    return dis


def visualization2(a,b):

    x1 = []
    y1 = []
    for pt in a:
        x1 += [pt[0]]
        y1 += [pt[1]]
    plt.plot(x1,y1, 'yo')
    
    m1=[]
    m1 = range(len(x1))
    for i in np.arange(0,len(m1)-1,2):
        plt.plot(x1[i:i+2],y1[i:i+2], color=b)

my_list = [[416689.15984457487, 5961369.921824793], [416463.47437214176, 5961262.376170568], [416784.93559347134, 5961169.622417776], [416662.37786889425, 5961110.342221191], [416882.24253254064, 5960968.447021521], [416861.28136564675, 5960958.308271814]]
for i in range(0,len(my_list)-1,2):
    ln = my_list[i] , my_list[i+1]
    print(round(DistanceBwPoints(ln),2))

visualization2(my_list,'red') 
plt.axis('equal')
plt.show()

Answer 1

Matplotlib has the text and annotate functions to plot text into a graph. In your case, text will suffice. In the original answer (see below), I have tried to keep your structure as much as possible but since the distances have to be calculated for the plot anyhow, I have integrated this into the plot loop to avoid code repetition. But the original simple approach looked weird for slopes other than ascending. So, here is an improved version while keeping your general structure:

from math import sqrt
import matplotlib.pyplot as plt
import numpy as np

my_list = [[1, 2], [10, 20], [30, 80], [70, 50], [110, 120], [180, 190], [130, 20], [180, 20], [10, 120], [10, 150]]
    
def DistanceBwPoints(ln1):
    x1 , y1 = ln1[0][0] , ln1[0][1]
    x2 , y2 = ln1[1][0] , ln1[1][1]    
    dis = sqrt ((x2 - x1)**2 + (y2 - y1)**2 )    
    return dis
  
def visualization2(a,b):    
    x1 = []
    y1 = []
    for pt in a:
        x1 += [pt[0]]
        y1 += [pt[1]]
    plt.plot(x1,y1, 'yo')
    
    m1 = range(len(x1))
    for i in np.arange(0,len(m1)-1,2):
        #plot line
        plt.plot(x1[i:i+2],y1[i:i+2], color=b)
        #calculate distance
        curr_dist = round(DistanceBwPoints([my_list[i], my_list[i+1]]),2)
        print(f"Line number {i//2+1} with distance", curr_dist)
        
        #determine slope direction of line to set text anchors correctly
        ln_slope = 1 + int(np.sign(np.diff(x1[i:i+2]) * np.diff(y1[i:i+2])))
        text_anchor_ha = ["left", "center", "right"][ln_slope]
        text_anchor_va = "bottom"
        #special case vertical line
        if not np.diff(x1[i:i+2]):
            text_anchor_ha, text_anchor_va = "right", "center"
        #annotate line    
        plt.text(x=np.mean(x1[i:i+2]), y=np.mean(y1[i:i+2]), s=curr_dist, ha=text_anchor_ha, va=text_anchor_va)

visualization2(my_list,'red') 
plt.axis('equal')
plt.show()

Sample output:

And one more thing - I have changed from math import *. Please read here why import * is a bad idea.

Original answer

from math import sqrt
import matplotlib.pyplot as plt
import numpy as np

def DistanceBwPoints(ln1):

    x1 , y1 = ln1[0][0] , ln1[0][1]
    x2 , y2 = ln1[1][0] , ln1[1][1]

    dis = sqrt ((x2 - x1)**2 + (y2 - y1)**2 )

    return dis


def visualization2(a,b):

    x1 = []
    y1 = []
    for pt in a:
        x1 += [pt[0]]
        y1 += [pt[1]]
    plt.plot(x1,y1, 'yo')
    
    m1 = range(len(x1))
    for i in np.arange(0,len(m1)-1,2):
        plt.plot(x1[i:i+2],y1[i:i+2], color=b)
        curr_dist = round(DistanceBwPoints([my_list[i], my_list[i+1]]),2)
        print(i, curr_dist)
        plt.text(x=np.mean(x1[i:i+2]), y=np.mean(y1[i:i+2]), s=curr_dist, ha="right", va="bottom")

my_list = [[416689.15984457487, 5961369.921824793], [416463.47437214176, 5961262.376170568], [416784.93559347134, 5961169.622417776], [416662.37786889425, 5961110.342221191], [416882.24253254064, 5960968.447021521], [416861.28136564675, 5960958.308271814]]

visualization2(my_list,'red') 
plt.axis('equal')
plt.show()

Sample output:

Answer 2

You can build a list with distances of data points (let’s say this list is x) and another list y = [i for i in range(0, len(x)]

Then, use plt.plot(x, y)