How to draw a set of points using OpenCV Python-CodePudding

I've got a set of points (coordinates X and Y) generated by a mathematical expression and I want to draw the resulting figure in a specific position of the screen (I'd like to determine the position in which to center the drawn figure).

I tried using the following code to test if the formula resulted in the correct figure. But now I need to draw the same contour on a pre-existing image at a specific position.

B = 185
L = 250
W = (L-B)/6
D = (L/2)-L/4

x = np.linspace(-L/2, L/2, 500)
y1 = []
y2 = []

for X in x:
    termo1 = sqrt((L**2 - 4*X**2) / (L**2   8*W*X   4*W**2))
    termo2 = ((sqrt(5.5*L**2   11*L*W   4*W**2) * (sqrt(3)*B*B - 2*D*sqrt(L**2   2*W*L   4*W**2))
               ) / (sqrt(3)*B*L*(sqrt(5.5*L**2   11*L*W   4*W**2) - 2*sqrt(L**2   2*W*L   4*W**2))))
    termo3 = 1 - sqrt((L*(L**2   8*W*X   4*W**2)) / (2*(L - 2*W)*X**2  
                      (L**2   8*L*W - 4*W**2)*X   2*L*W**2   L**2*W   L**2*W   L**3))

    calculo = B/2 * termo1 * (1-termo2 * termo3)
    y1.append(calculo)

    calculo = -B/2 * termo1 * (1-termo2 * termo3)
    y2.append(calculo)



fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.spines['left'].set_position('center')
ax.spines['bottom'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

plt.plot(x, y1, 'r')
plt.plot(x, y2, 'r')


plt.show()

CodePudding user response：

You can do this by creating an onclick event; it will take the mouse cords when click and use them as an offset...I think that's what you are asking for? Though with the current plot x/y limits, it won't show up depending on where you click so I added those in the configuration of the plot.

import numpy as np
from math import sqrt
import matplotlib.pyplot as plt
import os
import matplotlib.image as mpimg


def onclick(event):
    global ix, iy
    ix, iy = event.xdata, event.ydata
    plt.plot(x   ix, y1  iy, 'r')
    plt.plot(x   ix, y2  iy, 'r')
    plt.show()
    fig.canvas.mpl_disconnect(cid)

    return 


B = 185
L = 250
W = (L-B)/6
D = (L/2)-L/4

x = np.linspace(-L/2, L/2, 500)
y1 = []
y2 = []

for X in x:
    termo1 = sqrt((L**2 - 4*X**2) / (L**2   8*W*X   4*W**2))
    termo2 = ((sqrt(5.5*L**2   11*L*W   4*W**2) * (sqrt(3)*B*B - 2*D*sqrt(L**2   2*W*L   4*W**2))
               ) / (sqrt(3)*B*L*(sqrt(5.5*L**2   11*L*W   4*W**2) - 2*sqrt(L**2   2*W*L   4*W**2))))
    termo3 = 1 - sqrt((L*(L**2   8*W*X   4*W**2)) / (2*(L - 2*W)*X**2  
                      (L**2   8*L*W - 4*W**2)*X   2*L*W**2   L**2*W   L**2*W   L**3))

    calculo = B/2 * termo1 * (1-termo2 * termo3)
    y1.append(calculo)

    calculo = -B/2 * termo1 * (1-termo2 * termo3)
    y2.append(calculo)


fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.set_xlim([-500,500])
ax.set_ylim([-500,500])
ax.spines['left'].set_position('center')
ax.spines['bottom'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')


coords = []
cid = fig.canvas.mpl_connect('button_press_event', onclick)
plt.show()