Adds some ruff unsafe-fixes

aerosandbox/aerodynamics/aero_2D/airfoil_inviscid.py

@@ -219,7 +219,7 @@ def draw_streamlines(self, res=200, show=True):
             V[contains] = np.nan
 
         speed = (U**2 + V**2) ** 0.5
-        Cp = 1 - speed**2
+        # Cp = 1 - speed**2
 
         ### Draw the airfoils
         for airfoil in self.airfoils:

aerosandbox/aerodynamics/aero_3D/aero_buildup.py

@@ -445,7 +445,6 @@ def run_with_stability_derivatives(
             "r": (2 * self.op_point.velocity) / self.airplane.b_ref,
         }
 
-        original_op_point = self.op_point
 
         # Compute the point analysis, which returns a dictionary that we will later add key:value pairs to.
         run_base = self.run()

aerosandbox/aerodynamics/aero_3D/lifting_line.py

@@ -448,7 +448,6 @@ def run_with_stability_derivatives(
             "r": (2 * self.op_point.velocity) / self.airplane.b_ref,
         }
 
-        original_op_point = self.op_point
 
         # Compute the point analysis, which returns a dictionary that we will later add key:value pairs to.
         run_base = self.run()

aerosandbox/atmosphere/thermodynamics/gas.py

@@ -51,7 +51,8 @@ def __init__(
         self.effective_collision_diameter = effective_collision_diameter
 
     def __repr__(self) -> str:
-        f = lambda s, u: eng_string(s, unit=u, format="%.6g")
+        def f(val, unit):
+            return eng_string(val, unit=unit, format="%.6g")
 
         return f"Gas (P = {f(self.pressure, 'Pa')}, T = {self.temperature:.6g} K, ρ = {self.density:.6g} kg/m^3, Pv^gamma = {self.pressure * self.specific_volume ** self.ratio_of_specific_heats: .6g})"
 

aerosandbox/geometry/polygon.py

@@ -255,9 +255,9 @@ def J(self):
 
         A = 0.5 * np.sum(a)  # area
 
+        # Centroid location
         x_c = 1 / (6 * A) * np.sum(a * (x + x_n))
         y_c = 1 / (6 * A) * np.sum(a * (y + y_n))
-        centroid = np.array([x_c, y_c])
 
         Ixx = 1 / 12 * np.sum(a * (y**2 + y * y_n + y_n**2))
 

aerosandbox/geometry/test_geometry/test_airfoil.py

@@ -44,7 +44,7 @@ def test_repanel(naca4412):
 
 
 def test_containts_points(naca4412):
-    assert naca4412.contains_points(x=0.5, y=0) == True
+    assert naca4412.contains_points(x=0.5, y=0)
     assert np.all(
         naca4412.contains_points(x=np.array([0.5, 0.5]), y=np.array([0, -0.1]))
         == np.array([True, False])

aerosandbox/geometry/test_geometry/test_polygon.py

@@ -13,14 +13,14 @@ def test_polygon_creation():
 def test_contains_points():
     p = Polygon(coordinates=np.array([[0, 0], [1, 0], [1, 1], [0, 1]]))
 
-    assert p.contains_points(0.5, 0.5) == True
-    assert p.contains_points(-0.1, 0.5) == False
-    assert p.contains_points(0.5, -0.1) == False
-    assert p.contains_points(-0.1, -0.1) == False
-    assert p.contains_points(1.1, 1.1) == False
-    assert p.contains_points(1.0, 1.0) == True
-    assert p.contains_points(0.5, 1.0) == True
-    assert p.contains_points(0.5, 1.1) == False
+    assert p.contains_points(0.5, 0.5)
+    assert not p.contains_points(-0.1, 0.5)
+    assert not p.contains_points(0.5, -0.1)
+    assert not p.contains_points(-0.1, -0.1)
+    assert not p.contains_points(1.1, 1.1)
+    assert p.contains_points(1.0, 1.0)
+    assert p.contains_points(0.5, 1.0)
+    assert not p.contains_points(0.5, 1.1)
 
     assert np.all(
         p.contains_points(

aerosandbox/geometry/test_geometry/test_wingxsec.py

@@ -3,7 +3,7 @@
 
 
 def test_init():  # TODO actually test this
-    xsec = WingXSec(
+    WingXSec(
         xyz_le=np.array([0, 0, 0]),
         chord=1.0,
         twist=0,

aerosandbox/library/aerodynamics/transonic.py

@@ -177,11 +177,8 @@ def approximate_CD_wave(
 
 if __name__ == "__main__":
     mc = 0.6
-    drag = lambda mach: approximate_CD_wave(
-        mach,
-        mach_crit=mc,
-        CD_wave_at_fully_supersonic=1,
-    )
+    def drag(mach):
+        return approximate_CD_wave(mach, mach_crit=mc, CD_wave_at_fully_supersonic=1)
 
     import matplotlib.pyplot as plt
     import aerosandbox.tools.pretty_plots as p

aerosandbox/library/power_nuclear_rtg.py

@@ -38,11 +38,11 @@
 def po210_specific_power(
     days_after_formation=0,
 ):
-    half_life = 138.376  # days
     # Source: https://en.wikipedia.org/wiki/Polonium-210
-    pure_specific_energy = (
+    (
         (po_210_mass_amu - alpha_particle_mass_amu - pb_206_mass_amu)
         * c**2
         / po_210_mass_amu
     )  # J/kg
     # TODO finish
+    raise NotImplementedError()

aerosandbox/library/weights/torenbeek_weights.py

@@ -420,15 +420,17 @@ def mass_fuselage(
     # Torenbeek Eq. D-3
     fuselage.fineness_ratio()
 
-    fuselage_quasi_slenderness_ratio = fuselage.fineness_ratio(
+    fuselage.fineness_ratio(
         assumed_shape="sears_haack"
     )
 
     k_lambda = np.softmin(0.56 * fuselage.fineness_ratio(assumed_shape="sears_haack"))
 
     W_sk = 0.05428 * k_lambda * S_g**1.07 * never_exceed_airspeed**0.743
 
-    W_g = W_sk + W_str + W_fr
+    W_sk + W_str + W_fr
+
+    raise NotImplementedError()
 
 
 def mass_propeller(

aerosandbox/library/winds.py

@@ -223,10 +223,10 @@ def plot_winds_at_altitude(altitude=18000):
 
         levels = np.arange(0, 80.1, 5)
         CS = plt.contour(*args, levels=levels, linewidths=0.5, colors="k", alpha=0.7)
-        CF = plt.contourf(
+        plt.contourf(
             *args, levels=levels, cmap="viridis_r", alpha=0.7, extend="max"
         )
-        cbar = plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
+        plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
         ax.clabel(CS, inline=1, fontsize=9, fmt="%.0f m/s")
 
         plt.xticks(
@@ -280,10 +280,10 @@ def plot_winds_at_day(day_of_year=0):
 
         levels = np.arange(0, 80.1, 5)
         CS = plt.contour(*args, levels=levels, linewidths=0.5, colors="k", alpha=0.7)
-        CF = plt.contourf(
+        plt.contourf(
             *args, levels=levels, cmap="viridis_r", alpha=0.7, extend="max"
         )
-        cbar = plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
+        plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
         ax.clabel(CS, inline=1, fontsize=9, fmt="%.0f m/s")
 
         lat_label_vals = np.arange(-80, 80.1, 20)
@@ -316,10 +316,10 @@ def plot_tropopause_altitude():
 
         levels = np.arange(10, 20.1, 1)
         CS = plt.contour(*args, levels=levels, linewidths=0.5, colors="k", alpha=0.7)
-        CF = plt.contourf(
+        plt.contourf(
             *args, levels=levels, cmap="viridis_r", alpha=0.7, extend="both"
         )
-        cbar = plt.colorbar(label="Tropopause Altitude [km]", extendrect=True)
+        plt.colorbar(label="Tropopause Altitude [km]", extendrect=True)
         ax.clabel(CS, inline=1, fontsize=9, fmt="%.0f km")
 
         plt.xticks(
@@ -373,10 +373,10 @@ def plot_winds_at_tropopause_altitude():
 
         levels = np.arange(0, 80.1, 5)
         CS = plt.contour(*args, levels=levels, linewidths=0.5, colors="k", alpha=0.7)
-        CF = plt.contourf(
+        plt.contourf(
             *args, levels=levels, cmap="viridis_r", alpha=0.7, extend="max"
         )
-        cbar = plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
+        plt.colorbar(label="Wind Speed [m/s]", extendrect=True)
         ax.clabel(CS, inline=1, fontsize=9, fmt="%.0f m/s")
 
         plt.xticks(

aerosandbox/modeling/fitting.py

@@ -143,13 +143,11 @@ def flatten(input):
             return np.array(input).flatten()
 
         try:
-            x_data = {k: flatten(v) for k, v in x_data.items()}
-            x_data_is_dict = True
+            x_data = {k: flatten(v) for k, v in x_data.items()}  # type: dict
         except (
             AttributeError
         ):  # If it's not a dict or dict-like, assume it's a 1D ndarray dataset
-            x_data = flatten(x_data)
-            x_data_is_dict = False
+            x_data = flatten(x_data)  # type: np.ndarray
         y_data = flatten(y_data)
         n_datapoints = np.length(y_data)
 

aerosandbox/modeling/surrogate_model.py

@@ -137,7 +137,7 @@ def axis_range(x_data_axis: np.ndarray) -> Tuple[float, float]:
                 y_fit = self(x_fit)
 
             ### Plot the 2D figure
-            fig = plt.figure(dpi=200)
+            plt.figure(dpi=200)
             plt.plot(
                 x_data,
                 self.y_data,

aerosandbox/numpy/surrogate_model_tools.py

@@ -280,7 +280,8 @@ def blend(
         on the value of the 'switch' parameter.
 
     """
-    blend_function = lambda x: sigmoid(x, normalization_range=(0, 1))
+    def blend_function(x):
+        return sigmoid(x, normalization_range=(0, 1))
     weight_to_value_switch_high = blend_function(switch)
 
     blend_value = value_switch_high * weight_to_value_switch_high + value_switch_low * (

aerosandbox/numpy/test_numpy/test_determine_type.py

@@ -5,60 +5,59 @@
 
 
 def test_int():
-    assert is_casadi_type(5, recursive=True) == False
-    assert is_casadi_type(5, recursive=False) == False
+    assert not is_casadi_type(5, recursive=True)
+    assert not is_casadi_type(5, recursive=False)
 
 
 def test_float():
-    assert is_casadi_type(5.0, recursive=True) == False
-    assert is_casadi_type(5.0, recursive=False) == False
+    assert not is_casadi_type(5.0, recursive=True)
+    assert not is_casadi_type(5.0, recursive=False)
 
 
 def test_numpy():
-    assert is_casadi_type(np.array([1, 2, 3]), recursive=True) == False
-    assert is_casadi_type(np.array([1, 2, 3]), recursive=False) == False
+    assert not is_casadi_type(np.array([1, 2, 3]), recursive=True)
+    assert not is_casadi_type(np.array([1, 2, 3]), recursive=False)
 
 
 def test_casadi():
-    assert is_casadi_type(cas.MX(np.ones(5)), recursive=False) == True
-    assert is_casadi_type(cas.MX(np.ones(5)), recursive=True) == True
+    assert is_casadi_type(cas.MX(np.ones(5)), recursive=False)
+    assert is_casadi_type(cas.MX(np.ones(5)), recursive=True)
 
 
 def test_numpy_list():
-    assert is_casadi_type([np.array(5), np.array(7)], recursive=False) == False
-    assert is_casadi_type([np.array(5), np.array(7)], recursive=True) == False
+    assert not is_casadi_type([np.array(5), np.array(7)], recursive=False)
+    assert not is_casadi_type([np.array(5), np.array(7)], recursive=True)
 
 
 def test_casadi_list():
-    assert (
+    assert not (
         is_casadi_type([cas.MX(np.ones(5)), cas.MX(np.ones(5))], recursive=False)
-        == False
     )
     assert (
-        is_casadi_type([cas.MX(np.ones(5)), cas.MX(np.ones(5))], recursive=True) == True
+        is_casadi_type([cas.MX(np.ones(5)), cas.MX(np.ones(5))], recursive=True)
     )
 
 
 def test_mixed_list():
-    assert is_casadi_type([np.array(5), cas.MX(np.ones(5))], recursive=False) == False
-    assert is_casadi_type([np.array(5), cas.MX(np.ones(5))], recursive=True) == True
+    assert not is_casadi_type([np.array(5), cas.MX(np.ones(5))], recursive=False)
+    assert is_casadi_type([np.array(5), cas.MX(np.ones(5))], recursive=True)
 
 
 def test_multi_level_contaminated_list():
     a = [[1 for _ in range(10)] for _ in range(10)]
 
-    assert is_casadi_type(a, recursive=False) == False
-    assert is_casadi_type(a, recursive=True) == False
+    assert not is_casadi_type(a, recursive=False)
+    assert not is_casadi_type(a, recursive=True)
 
     a[5][5] = cas.MX(1)
 
-    assert is_casadi_type(a, recursive=False) == False
-    assert is_casadi_type(a, recursive=True) == True
+    assert not is_casadi_type(a, recursive=False)
+    assert is_casadi_type(a, recursive=True)
 
     a[5][5] = np.array(cas.DM(1), dtype="O")
 
-    assert is_casadi_type(a, recursive=False) == False
-    assert is_casadi_type(a, recursive=True) == False
+    assert not is_casadi_type(a, recursive=False)
+    assert not is_casadi_type(a, recursive=True)
 
 
 if __name__ == "__main__":

aerosandbox/numpy/test_numpy/test_interpolate.py

@@ -105,12 +105,12 @@ def value_func_3d(x, y, z):
 
     point = np.array([5.21, 3.12, 1.15])
     with pytest.raises(ValueError):
-        value = np.interpn(points, values, point)
+        np.interpn(points, values, point)
 
     ### CasADi test
     point = cas.DM(point)
     with pytest.raises(ValueError):
-        value = np.interpn(points, values, point)
+        np.interpn(points, values, point)
 
 
 def test_interpn_bounds_error_multiple_samples():
@@ -125,12 +125,12 @@ def value_func_3d(x, y, z):
 
     point = np.array([[2.21, 3.12, 1.15], [3.42, 5.81, 2.43]])
     with pytest.raises(ValueError):
-        value = np.interpn(points, values, point)
+        np.interpn(points, values, point)
 
     ### CasADi test
     point = cas.DM(point)
     with pytest.raises(ValueError):
-        value = np.interpn(points, values, point)
+        np.interpn(points, values, point)
 
 
 def test_interpn_fill_value():

aerosandbox/optimization/test_optimization/test_opti_analytical_wing_drag_minimization.py

@@ -62,7 +62,7 @@ def test_log_transformed_negativity_error():
     opti = asb.Opti()
 
     with pytest.raises(ValueError):
-        myvar = opti.variable(log_transform=True, init_guess=-1)
+        opti.variable(log_transform=True, init_guess=-1)
 
 
 def test_fixed_variable():

aerosandbox/structures/buckling.py

@@ -114,7 +114,7 @@ def thin_walled_tube_crippling_buckling_critical_load(
         # Following the Air Force Stress Manual, Section 2.3.2.1, Eq. 2-20.
         # The above value assumes mu = 0.3, which is a good assumption for most metals.
 
-    crippling_stress = 0.3 * (elastic_modulus * wall_thickness / radius)
+    crippling_stress = crippling_stress_constant * (elastic_modulus * wall_thickness / radius)
 
     tube_xsec_area = 2 * np.pi * radius * wall_thickness
 

aerosandbox/tools/statistics/time_series_uncertainty_quantification.py

@@ -51,7 +51,8 @@ def estimate_noise_standard_deviation(
     ##### Noise Variance Reconstruction #####
     from scipy.special import gammaln
 
-    ln_factorial = lambda x: gammaln(x + 1)
+    def ln_factorial(x):
+        return gammaln(x + 1)
 
     ### For speed, pre-compute the log-factorial of integers from 1 to estimator_order
     # ln_f = ln_factorial(np.arange(estimator_order + 1))
@@ -166,21 +167,26 @@ def bootstrap_fits(
     y_rng = y_max - y_min
 
     if normalize:
-        x_normalize = lambda x: (x - x_min) / x_rng
-        y_normalize = lambda y: (y - y_min) / y_rng
+        def x_normalize(x):
+            return (x - x_min) / x_rng
+        def y_normalize(y):
+            return (y - y_min) / y_rng
         # x_unnormalize = lambda x_n: x_n * x_rng + x_min
-        y_unnormalize = lambda y_n: y_n * y_rng + y_min
+        def y_unnormalize(y_n):
+            return y_n * y_rng + y_min
 
-        x_stdev_normalized = x_noise_stdev / x_rng
+        x_noise_stdev / x_rng
         y_stdev_normalized = y_noise_stdev / y_rng
 
     else:
-        x_normalize = lambda x: x
-        y_normalize = lambda y: y
+        def x_normalize(x):
+            return x
+        def y_normalize(y):
+            return y
         # x_unnormalize = lambda x_n: x_n
-        y_unnormalize = lambda y_n: y_n
+        def y_unnormalize(y_n):
+            return y_n
 
-        x_stdev_normalized = x_noise_stdev
         y_stdev_normalized = y_noise_stdev
 
     with tqdm(