tunnel = cT.Tunnel()
'Tail Off case'
dir = 'data/'
polar_tailOff = dir + 'raw_tailOff_bal.txt'
polar_tailOff_0 = dir + 'zero_tailOff_bal.txt'
polar_tailOff_raw = source.BAL_class.BAL_data(polar_tailOff, polar_tailOff_0,
5)
raw_data_40 = []
for data_i in polar_tailOff_raw.data:
if np.abs(data_i[polar_tailOff_raw.index.V] - 40) < 2:
raw_data_40.append(data_i[:])
raw_data_40 = np.array(raw_data_40)
polar_tailOff_uncorr = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft)
polar_tailOff_corr = copy.deepcopy(polar_tailOff_uncorr)
fb.correct_notail(polar_tailOff_corr, aircraft, tunnel, 'w')
CLu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CL')
CDu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CD')
CMu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CM')
CLc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CL')
CDc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CD')
CMc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CM')
'Tail On case'
polar_tailOn = dir + 'raw_tailOn_bal.txt'
polar_tailOn_0 = dir + 'zero_tailOn_bal.txt'
polar_tailOn_raw = source.BAL_class.BAL_data(polar_tailOn, polar_tailOn_0, 5)
polar_tailOn_uncorr = cP.Polar(polar_tailOn_raw.data, polar_tailOn_raw.index,
tunnel = cT.Tunnel()
'Tail Off case'
dir = 'data/'
polar_tailOff = dir + 'raw_tailOff_bal.txt'
polar_tailOff_0 = dir + 'zero_tailOff_bal.txt'
polar_tailOff_raw = source.BAL_class.BAL_data(polar_tailOff, polar_tailOff_0,
5)
raw_data_40 = []
for data_i in polar_tailOff_raw.data:
if np.abs(data_i[polar_tailOff_raw.index.V] - 40) < 2:
raw_data_40.append(data_i[:])
raw_data_40 = np.array(raw_data_40)
polar_tailOff_uncorr = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft)
polar_tailOff_corr_block = cP.Polar(raw_data_40, polar_tailOff_raw.index,
aircraft)
fb.correct_blockage(polar_tailOff_corr_block, aircraft, tunnel, 'w')
polar_tailOff_corr = copy.deepcopy(polar_tailOff_corr_block)
fb.correct_streamline(polar_tailOff_corr, aircraft, tunnel, 'w')
df = pd.DataFrame(np.zeros((len(polar_tailOff_corr.points), 11)),
columns=[
'alphau', 'alpha', 'CLu', 'CDu', 'CMu', 'CLc_b', 'CDc_b',
'CMc_b', 'CL', 'CD', 'CM'
])
for i, point in enumerate(polar_tailOff_corr.points):
df.at[i, 'alphau'] = polar_tailOff_uncorr.points[i].alpha
df.at[i, 'alpha'] = polar_tailOff_corr.points[i].alpha
df.at[i, 'CLu'] = polar_tailOff_uncorr.points[i].CFl
tunnel = cT.Tunnel()
'Tail Off case'
dir = 'data/'
polar_tailOff = dir + 'raw_tailOff_bal.txt'
polar_tailOff_0 = dir + 'zero_tailOff_bal.txt'
polar_tailOff_raw = source.BAL_class.BAL_data(polar_tailOff, polar_tailOff_0,
5)
raw_data_40 = []
for data_i in polar_tailOff_raw.data:
if np.abs(data_i[polar_tailOff_raw.index.V] - 40) < 2:
raw_data_40.append(data_i[:])
raw_data_40 = np.array(raw_data_40)
polar_tailOff_uncorr = cP.Polar(raw_data_40, polar_tailOff_raw.index, aircraft)
polar_tailOff_corr = copy.deepcopy(polar_tailOff_uncorr)
fb.correct_notail(polar_tailOff_corr, aircraft, tunnel, 'w')
CLu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CL')
CDu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CD')
CMu_tailOff = fb.get_listfrompolar(polar_tailOff_uncorr, 'CM')
CLc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CL')
CDc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CD')
CMc_tailOff = fb.get_listfrompolar(polar_tailOff_corr, 'CM')
'Tail On case'
polar_tailOn = dir + 'raw_tailOn_bal.txt'
polar_tailOn_0 = dir + 'zero_tailOn_bal.txt'
polar_tailOn_raw = source.BAL_class.BAL_data(polar_tailOn, polar_tailOn_0, 5)
polar_tailOn_uncorr = cP.Polar(polar_tailOn_raw.data, polar_tailOn_raw.index,