Source code for bladedesigner.camberlines.d3pcamberline

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# ***************************************************************************
# *   Copyright (C) 2011-2012 by Andreas K├╝hrmann [kuean@users.sf.net]      *
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import numpy as np

import bladedesigner.foundation as fdn

from d2pcamberline import D2PCamberLine


__all__ = ['D3PCamberLine']


[docs]class D3PCamberLine(D2PCamberLine): """ some documentation """ def __init__(self): super(D3PCamberLine, self).__init__() # properties (initialized by user) self.__angle_of_outflow = fdn.Uninit('angle_of_outflow') # add user properties to initialization summary self._properties.append('angle_of_outflow') @property def angle_of_outflow(self): r""" Type: ``int or float`` - values between (exclusive) 0 and :math:`\pi` only """ return self.__angle_of_outflow @angle_of_outflow.setter @fdn.restrict(new_angle_of_outflow=fdn.OpenInterval(0, np.pi))
[docs] def angle_of_outflow(self, new_angle_of_outflow): if self.__angle_of_outflow != new_angle_of_outflow: self.__angle_of_outflow = new_angle_of_outflow self.update()
def __get_coefficients(self): self._check_initialization('angle_of_inflow', 'angle_of_outflow') slop_inlet = np.tan(self.angle_of_inflow - np.pi / 2.) slop_outlet = np.tan(np.pi / 2. - self.angle_of_outflow) a_3 = slop_inlet - np.tan(slop_outlet) a_2 = -slop_inlet - a_3 a_1 = slop_inlet return a_1, a_2, a_3 @fdn.memoize
[docs] def get_derivations(self): """ get_derivations() Returns: ``ndarray`` Calculates camber line derivations and returns them in an array. .. note:: **Note** The return value will be cached. Recalling this method returns the cached value, if the attribues are unchanged. """ self._check_initialization() self._cached = True x = self.distribution(self.sample_rate) a_1, a_2, a_3 = self.__get_coefficients() return x * (x * 3 * a_3 + 2 * a_2) + a_1
@fdn.memoize
[docs] def as_array(self): """ as_array() Returns: ``ndarray`` Calculates camber line coordinates and returns them in an array. .. note:: **Note** The return value will be cached. Recalling this method returns the cached value, if the attribues are unchanged. """ self._check_initialization() self._cached = True x = self.distribution(self.sample_rate) a_1, a_2, a_3 = self.__get_coefficients() y = x * (x * (x * a_3 + a_2) + a_1) return np.reshape(np.append(x, y), (-1, 2), "F")