Create Array based on Formula applied to Source Array

Question

I am trying to apply four formulas to a set of coordinates I have in an array, to generate two additional arrays that I can then plot.

The two new arrays called 'internal_edge' and 'external_edge'.

In the code below, I have printed the four equations I need to apply to the X and Y of both 'internal_edge' and 'external_edge'.

import numpy as np
import math as m
from matplotlib import pyplot as plt

track_width = 0.25

centre_line = np.array([
    [5.2838386568469105, 0.5533114231405133],[5.366471208948866, 0.5138588293370626],[5.449968630730311, 0.47627584038467463],[5.534812288152224, 0.4418872118882958],[5.621950766713397, 0.4139674411266211],[5.711536576482786, 0.3955402988007556],[5.80273779150609, 0.38945006681201744],[5.893859166442468, 0.3968403768909704],[5.983006824666859, 0.41711137467093196],
])

x1, y1 = centre_line.T
#Internal X[0] Value:
print(track_width*m.cos(m.radians(m.degrees(m.atan2(y1[1]-y1[0],x1[1]-x1[0]))+90))+x1[1])
#Internal Y[0] Value:
print(track_width*m.sin(m.radians(m.degrees(m.atan2(y1[1]-y1[0],x1[1]-x1[0]))+90))+y1[1])
#External X[0] Value:
print(track_width*m.cos(m.radians(m.degrees(m.atan2(y1[1]-y1[0],x1[1]-x1[0]))-90))+x1[1])
#External Y[0] Value:
print(track_width*m.sin(m.radians(m.degrees(m.atan2(y1[1]-y1[0],x1[1]-x1[0]))-90))+y1[1])

internal_edge = np.array([
])
external_edge = np.array([
])

x2, y2 = internal_edge.T
x3, y3 = external_edge.T

plt.scatter(x1,y1,color='blue')
plt.scatter(x2,y2,color='green')
plt.scatter(x3,y3,color='red')
plt.show()

I now need to work out how to apply these to every single data point in my array to generate my new arrays.

Perfect Output Imperfect Output

Hi, welcome to StackOverflow. Just to clarify, are you trying to work out how to apply the formulas to [[(x1[0], y1[0]), (x1[1], y1[1])], [(x1[1], y1[1]), (x1[2], y1[2])], [(x1[2], y1[2]), (x1[3], y1[3])], ..., [(x1[i], y1[i]), (x1[i+1], y1[i+1])]]? — TrebledJ
– TrebledJ, Commented May 24, 2019 at 8:50

ThatAnnoyingDude · Accepted Answer · 2019-05-24 10:00:42Z

1

Here's how you can do it.

import numpy as np
from matplotlib import pyplot as plt

track_width = 0.25

centre_line = np.array([
    [5.2838386568469105, 0.5533114231405133],[5.366471208948866, 0.5138588293370626],[5.449968630730311, 0.47627584038467463],[5.534812288152224, 0.4418872118882958],[5.621950766713397, 0.4139674411266211],[5.711536576482786, 0.3955402988007556],[5.80273779150609, 0.38945006681201744],[5.893859166442468, 0.3968403768909704],[5.983006824666859, 0.41711137467093196],
])

x1, y1 = centre_line.T

# adjust for full dataset maybe?
x1 = np.append(x1, x1[0])
y1 = np.append(y1, y1[0])

angle = np.arctan2(y1[1:] - y1[:-1], x1[1:] - x1[:-1])


internal_edge = np.array([
    track_width*np.cos(angle + np.deg2rad(90)) + x1[1:],
    track_width*np.sin(angle + np.deg2rad(90)) + y1[1:],
])

external_edge = np.array([
    track_width*np.cos(angle - np.deg2rad(90)) + x1[1:],
    track_width*np.sin(angle - np.deg2rad(90)) + y1[1:],
])

x2, y2 = internal_edge
x3, y3 = external_edge

plt.scatter(x1,y1,color='blue')
plt.scatter(x2,y2,color='green')
plt.scatter(x3,y3,color='red')
plt.show()

edited May 24, 2019 at 10:00

answered May 24, 2019 at 9:14

ThatAnnoyingDude

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5 Comments

Barnee Over a year ago

Thanks! That looks great. Running this with the full dataset is not quite perfect however. I've attached two images to the original post, one of how it should look (generated when I was testing by manually inputting the desired arrays), and the one generated by your code. Would you be able to take a look and let me know what you think? This is frying my brain at this point!

ThatAnnoyingDude Over a year ago

how about now? don't have the dataset to test on

Barnee Over a year ago

That solves the missing datapoint problem, but we still have those two wrong values in the top left.

ThatAnnoyingDude Over a year ago

angle[121] == 0 which coincides with weird anomaly on the graph. Idk how 2 fix it something math related

Barnee Over a year ago

There was a duplicate datapoint that was causing it. I've removed the duplicate (121) and now works fine!

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