Source code for openmdao.utils.spline_distributions

"""Helper function to create non uniform distributions for SplineComp."""

import numpy as np


[docs]def cell_centered(num_cells, start=0.0, end=1.0): """ Cell centered distribution of control points. Parameters ---------- num_cells : int Number of cells. start : int or float Minimum value to interpolate at. end : int or float Maximum value to interpolate at. Returns ------- ndarray Values to interpolate at. """ interp_grid = np.linspace(start, end, num=num_cells + 1) return np.array(0.5 * (interp_grid[1:] + interp_grid[:-1]))
[docs]def sine_distribution(num_points, start=0.0, end=1.0, phase=np.pi): """ Sine distribution of control points. Parameters ---------- num_points : int Number of points to predict at. start : int or float Minimum value to interpolate at. end : int or float Maximum value to interpolate at. phase : float Phase of the sine wave Returns ------- ndarray Values to interpolate at. """ t_vec = np.linspace(start, end, num_points) return np.array(0.5 * (1.0 + np.sin(-0.5 * phase + t_vec * phase)))
[docs]def node_centered(num_points, start=0.0, end=1.0): """ Distribute control points. Parameters ---------- num_points : int Number of points to predict. start : int or float Minimum value to interpolate at. end : int or float Maximum value to interpolate at. Returns ------- ndarray Values to interpolate at. """ return np.linspace(start, end, num_points + 1)