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

# ***************************************************************************
# *   Copyright (C) 2011-2013 by Andreas Kührmann [kuean@users.sf.net] and  *
# *   Fabian Schäffer                                                       *
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# *   This program is free software; you can redistribute it and/or modify  *
# *   the Free Software Foundation; either version 3 of the License, or     *
# *   (at your option) any later version.                                   *
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# *   GNU General Public License for more details.                          *
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# *   Free Software Foundation, Inc.,                                       *
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# ***************************************************************************

import numpy as np

[docs]class JoukowskiCamberLine(bcls.AnalyticalCamberLine): """ The Joukowski-Camberline is characterized by the maximum camber. Its geometry results from the Joukowski-Transformation, the camberline is defined for small bulges in the following form: """ def __init__(self): super(JoukowskiCamberLine, self).__init__() # properties (initialized by user) self.__max_camber = fdn.Uninit('max_camber') # add user properties to initialization summary self._properties.append('max_camber') @property def max_camber(self): return self.__max_camber @max_camber.setter @fdn.restrict(new_max_camber=(int, float)) def max_camber(self, new_max_camber): """ Type: int or float """ if self.__max_camber != new_max_camber: self.__max_camber = new_max_camber self.update() @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) return self.max_camber * (1 - 2 * x)
[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) y = self.max_camber * x * (1 - x) return np.reshape(np.append(x, y), (-1, 2), "F")