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- import numpy as np
- def create_k_steps(k_span, steps):
- """
- A function that returns a k_span gradient span with odd and even gradient steps
- """
- k_steps = np.array(range(steps + 1))
- if (np.mod(steps, 2) == 0):
- k_steps = (k_steps - steps / 2) / (steps / 2)
- else:
- k_steps = (k_steps - (steps + 1) / 2) / (steps / 2)
- k_steps = np.flip(k_steps, 0)
- k_steps = np.delete(k_steps, -1)
- return k_steps * k_span * 0.5
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