Source code for openmdao.lib.components.linear_distribution

import numpy as np

from openmdao.main.api import Component
from openmdao.lib.datatypes.api import Float, Array


[docs]class LinearDistribution(Component): """takes two Float inputs, and provides n Float outputs with a linear variation between them. Units can be optionally provided. If use_array is True (default) then the output is an array. Otherwise, the output will be a set of separate variables""" def __init__(self, n=3, units=None, use_array=True): super(LinearDistribution, self).__init__() self._n = n self.add('offset', Float(0.0, iotype="in", desc="offset applied to the linear distribution outputs", units=units)) self.add('start', Float(iotype='in', desc="input closest to the hub", units=units)) self.add('end', Float(iotype='in', desc="input closest to the tip", units=units)) self.add('delta', Float(iotype='out', desc='step size for each of the %d levels'%n, units=units)) if use_array: self.add('output', Array(iotype='out', desc='linearly spaced values from start to end inclusive of the bounds', default_value=np.ones(n), shape=(n,), dtype=Float, units=units)) else: for i in range(0, n): self.add('output_%d'%i, Float(1, iotype="out", desc="linearaly spaced output %d"%i, units=units))
[docs] def execute(self): out = np.linspace(self.start, self.end, self._n) + self.offset self.output = out self.delta = out[1]-out[0]
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