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…into feature-coverage
| # rayleigh | ||
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well that's weird
planes
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Make some changes. Talk to Matthew about one issue
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| cruise | |||
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Idk...why, but the regression/travis works.... @mclarke2 might be able to comment on the use of it.
| actual.takeoff = 99.7 | ||
| actual.side_line = 97.2 | ||
| actual.landing = 105.2 | ||
| actual.takeoff = 99.982372547196633 |
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Hmm, I think these values actually come from Shevell data as a test case. I think what you have done is right. However, we should save the original values in comments somewhere.
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| # constnat_temperature.py | |||
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| # NACA_airfoil_compute.py | |||
| Cm_a_sur[ii,jj] = cm_alpha_surrogate.predict(np.array([AoA_mesh[ii,jj],mach_mesh[ii,jj]])) | ||
| Cn_b_sur[ii,jj] = cn_beta_surrogate.predict(np.array([AoA_mesh[ii,jj],mach_mesh[ii,jj]])) | ||
| NP_sur[ii,jj] = neutral_point_surrogate.predict(np.array([AoA_mesh[ii,jj],mach_mesh[ii,jj]])) | ||
| NP_sur[ii,jj] = neutral_point_surrogate.predict(np.array([AoA_mesh[ii,jj],mach_mesh[ii,jj]])) |
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There wasn't a change...The commented code below allows the sklearn to work on my own machine. I assume my version is more up to date than the SUAVE repo.
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Keep those differences locally...have @mclarke2 comment on it
| g = self.compute_gamma(T,p) | ||
| else: | ||
| g = 1.4*np.ones_like(T) | ||
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nope, I changed It...
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| T = np.resize(T,[n_a,3,3]) | ||
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| return T |
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You should make this a regression
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So this is already being covered...are you sure you want another regression?
Just a general code clean up.
Added regression for Ducted Fan and NACA airfoil geometry for coverage.