I’m having a curve (parabol) from 0 to 1 on both axes as follows:
I generate another curve by moving the original curve along the x-axis and combine both to get the following graph:
How can I remove the intersected section to have only the double bottoms pattern like this:
The code I use for the graph:
import numpy as np import matplotlib.pyplot as plt def get_parabol(start=-1, end=1, steps=100, normalized=True): x = np.linspace(start, end, steps) y = x**2 if normalized: x = np.array(x) x = (x - x.min())/(x.max() - x.min()) y = np.array(y) y = (y - y.min())/(y.max() - y.min()) return x, y def curve_after(x, y, x_ratio=1/3, y_ratio=1/2, normalized=False): x = x*x_ratio + x.max() - x[0]*x_ratio y = y*y_ratio + y.max() - y.max()*y_ratio if normalized: x = np.array(x) x = (x - x.min())/(x.max() - x.min()) y = np.array(y) y = (y - y.min())/(y.max() - y.min()) return x, y def concat_arrays(*arr, axis=0, normalized=True): arr = np.concatenate([*arr], axis=axis).tolist() if normalized: arr = np.array(arr) arr = (arr - arr.min())/(arr.max() - arr.min()) return arr x, y = get_parabol() new_x, new_y = curve_after(x, y, x_ratio=1, y_ratio=1, normalized=False) new_x = np.add(x, 0.5) # new_y = np.add(y, 0.2) xx = concat_arrays(x, new_x, normalized=True) yy = concat_arrays(y, new_y, normalized=True) # plt.plot(x, y, '-') plt.plot(xx, yy, '--')
I’m doing a research on pattern analysis that requires me to generate patterns with mathematical functions.
Could you show me a way to achieve this? Thank you!
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Answer
First off, I would have two different parabola functions such that:
import numpy as np import matplotlib.pyplot as plt x = np.linspace(-1, 1, 100) y1 = np.add(x, 0.3)**2 # Parabola centered at -0.3 y2 = np.add(x, -0.3)**2 # Parabola centered at 0.3
You can choose your own offsets for y1 and y2 depending on your needs.
And then it’s simply take the min of the two arrays
y_final = np.minimum(y1, y2) plt.plot(x, y_final, '--')