yay truediv

docs/source/examples/beam.py

@@ -74,14 +74,14 @@ def setup(self, N=4):
 L, EI, q = sol("L"), sol("EI"), sol("q")
 x = np.linspace(0, mag(L), len(q))*ureg.m  # position along beam
 q = q[0]  # assume uniform loading for the check below
-w_exact = q/(24.*EI) * x**2 * (x**2 - 4*L*x + 6*L**2)  # analytic soln
+w_exact = q/(24*EI) * x**2 * (x**2 - 4*L*x + 6*L**2)  # analytic soln
 assert max(abs(w_gp - w_exact)) <= 1.1*ureg.cm
 
 PLOT = False
 if PLOT:
     import matplotlib.pyplot as plt
     x_exact = np.linspace(0, L, 1000)
-    w_exact = q/(24.*EI) * x_exact**2 * (x_exact**2 - 4*L*x_exact + 6*L**2)
+    w_exact = q/(24*EI) * x_exact**2 * (x_exact**2 - 4*L*x_exact + 6*L**2)
     plt.plot(x, w_gp, color='red', linestyle='solid', marker='^',
              markersize=8)
     plt.plot(x_exact, w_exact, color='blue', linestyle='dashed')

docs/source/examples/external_sp.py

@@ -9,8 +9,8 @@
 objective = y
 
 constraints = [ExternalConstraint(x, y),
-               x <= np.pi/2.,
-               x >= np.pi/4.,
+               x <= np.pi/2,
+               x >= np.pi/4,
               ]
 
 m = Model(objective, constraints)

docs/source/examples/sin_approx_example.py

@@ -9,8 +9,8 @@
 objective = y
 
 constraints = [y >= x,
-               x <= np.pi/2.,
-               x >= np.pi/4.,
+               x <= np.pi/2,
+               x >= np.pi/4,
               ]
 
 m = Model(objective, constraints)

docs/source/examples/sp_to_gp_sweep.py

@@ -22,7 +22,7 @@ def SimPleAC():
     tau = Variable("\\tau", 0.12, "-", "airfoil thickness to chord ratio")
     W_W_coeff1 = Variable("W_{W_{coeff1}}", 2e-5, "1/m",
                           "wing weight coefficent 1")  # 12e-5 originally
-    W_W_coeff2 = Variable("W_{W_{coeff2}}", 60., "Pa",
+    W_W_coeff2 = Variable("W_{W_{coeff2}}", 60, "Pa",
                           "wing weight coefficent 2")
 
     # Dimensional constants
@@ -91,7 +91,7 @@ def SimPleAC():
     # Wing weight model
     constraints += [
         W_w_surf >= W_W_coeff2 * S,
-        W_w_strc**2. >= W_W_coeff1**2/tau**2 * N_ult**2*A**3*(V_f_fuse*g*rho_f
+        W_w_strc**2 >= W_W_coeff1**2/tau**2 * N_ult**2*A**3*(V_f_fuse*g*rho_f
                                                               + W_0)*W*S,
         W_w >= W_w_surf + W_w_strc]
 

docs/source/ipynb/BEMT.ipynb

@@ -389,7 +389,7 @@
         " r: array([[ 0.21773709,  0.58869686,  0.74669362,  0.87573369,  1.        ]]),\n",
         " dC_T: array([[ 0.00373315,  0.00373315,  0.00373315,  0.00373315,  0.00373315]]),\n",
         " dC_P: array([[ 0.00037037,  0.00035362,  0.00035362,  0.00035362,  0.00031661]]),\n",
-        " \\xi: array([[ 2000.,  2000.,  2000.,  2000.,  2000.]]),\n",
+        " \\xi: array([[ 2000,  2000,  2000,  2000,  2000]]),\n",
         " P: array([ 43582.46513974]),\n",
         " \\Omega: array([ 55.55730973]),\n",
         " A: array([ 201.06192911]),\n",

docs/source/ipynb/Fuel/Fuel.ipynb

@@ -231,7 +231,7 @@
     "                         p >= 2.2,\n",
     "                         tau <= 0.25,\n",
     "                         M_rbar >= W_tw*A*p/(24*gpkit.units.N),\n",
-    "                         .92**2/2.*w*tau**2*t_cap >= I_cap * wunits + .92*w*tau*t_cap**2,\n",
+    "                         .92**2/2*w*tau**2*t_cap >= I_cap * wunits + .92*w*tau*t_cap**2,\n",
     "                         8 >= N_lift*M_rbar*A*q**2*tau/S/I_cap/sigma_max * munits,\n",
     "                         12 >= A*W_tw*N_lift*q**2/tau/S/t_web/sigma_maxshear,\n",
     "                         nu**3.94 >= .86*p**-2.38 + .14*p**0.56,\n",

docs/source/ipynb/Fuel/Fuel.rst

@@ -161,7 +161,7 @@ return and sprint flights.
                              p >= 1.9,
                              tau <= 0.15,
                              M_rbar >= W_tw*A*p/(24*gpkit.units.N),
-                             .92**2/2.*w*tau**2*t_cap >= I_cap * gpkit.units.m**-4 + .92*w*tau*t_cap**2,
+                             .92**2/2*w*tau**2*t_cap >= I_cap * gpkit.units.m**-4 + .92*w*tau*t_cap**2,
                              8 >= N_lift*M_rbar*A*q**2*tau/S/I_cap/sigma_max * gpkit.units.parse_expression('Pa*m**6'),
                              12 >= A*W_tw*N_lift*q**2/tau/S/t_web/sigma_maxshear,
                              nu**3.94 >= .86*p**-2.38 + .14*p**0.56,

gpkit/build.py

@@ -86,7 +86,7 @@ class MosekCLI(SolverBackend):
     name = "mosek_cli"
 
     def look(self):  # pylint: disable=too-many-return-statements
-        "Looks in default install locations for a mosek before 9."
+        "Looks in default install locations for a mosek before version 9."
         already_in_path = self.run()
         if already_in_path:
             return already_in_path
@@ -156,7 +156,7 @@ class MosekConif(SolverBackend):
     name = "mosek_conif"
 
     def look(self):
-        "Attempts to import mosek, version >= 9."
+        "Attempts to import a mosek supporting exponential cones."
         try:
             log("#   Trying to import mosek...")
             import mosek

gpkit/constraints/gp.py

@@ -401,19 +401,17 @@ def _almost_equal(num1, num2):
         for mi in self.m_idxs[1:]:
             if primal_exp_vals[mi].sum() > 1 + tol:
                 raise Infeasible("Primal solution violates constraint: %s is "
-                                 "greater than 1." % primal_exp_vals[mi].sum())
+                                 "greater than 1" % primal_exp_vals[mi].sum())
 
         # check dual sol #
         # note: follows dual formulation in section 3.1 of
         # http://web.mit.edu/~whoburg/www/papers/hoburg_phd_thesis.pdf
-        if not _almost_equal(self.nu_by_posy[0].sum(), 1.):
+        if not _almost_equal(self.nu_by_posy[0].sum(), 1):
             raise Infeasible("Dual variables associated with objective sum"
-                             " to %s, not 1." % self.nu_by_posy[0].sum())
+                             " to %s, not 1" % self.nu_by_posy[0].sum())
         if any(nu < 0):
             minnu = min(nu)
-            if minnu > -tol/1000.:  # HACK, see issue 528
-                print("Allowing negative dual variables up to %s." % minnu)
-            else:
+            if minnu < -tol/1000:
                 raise Infeasible("Dual solution has negative entries as"
                                  " large as %s." % minnu)
         if any(np.abs(A.T.dot(nu)) > tol):

gpkit/tests/t_constraints.py

@@ -130,7 +130,7 @@ def test_sub_tol(self):
         y = Variable('y')
         z = Variable('z')
         PosynomialInequality.feastol = 1e-5
-        m = Model(z, [x == z, x >= y], {x: 1., y: 1.0001})
+        m = Model(z, [x == z, x >= y], {x: 1, y: 1.0001})
         self.assertRaises(PrimalInfeasible, m.solve, verbosity=0)
         PosynomialInequality.feastol = 1e-3
         self.assertEqual(m.substitutions('x'), m.solve(verbosity=0)('x'))

gpkit/tests/t_nomials.py

@@ -42,7 +42,7 @@ def test_init(self):
 
         # non-positive c raises
         self.assertRaises(InvalidPosynomial, Monomial, -2)
-        self.assertRaises(InvalidPosynomial, Monomial, -1.)
+        self.assertRaises(InvalidPosynomial, Monomial, -1)
         self.assertRaises(InvalidPosynomial, Monomial, 0)
         self.assertRaises(InvalidPosynomial, Monomial, 0.0)
 
@@ -191,9 +191,9 @@ def test_pow(self):
 
     def test_numerical_precision(self):
         "not sure what to test here, placeholder for now"
-        c1, c2 = 1/700., 123e8
+        c1, c2 = 1/700, 123e8
         m1 = Monomial({"x": 2, "y": 1}, c1)
-        m2 = Monomial({"y": -1, "z": 3/2.}, c2)
+        m2 = Monomial({"y": -1, "z": 3/2}, c2)
         self.assertEqual(math.log((m1**4 * m2**3).c),  # pylint: disable=no-member
                          4*math.log(c1) + 3*math.log(c2))
 
@@ -239,7 +239,7 @@ def test_chop(self):
         x = Variable("x")
         y = Variable("y")
         with SignomialsEnabled():
-            c = x + 5.*y**2 - 0.2*x*y**0.78
+            c = x + 5*y**2 - 0.2*x*y**0.78
             monomials = c.chop()
         with self.assertRaises(InvalidPosynomial):
             c.chop()
@@ -373,9 +373,9 @@ def test_integer_division(self):
         x = Variable("x")
         y = Variable("y")
         p = 4*x + y
-        self.assertEqual(p/3, p/3.)
-        equiv1 = all((p/3).cs == [1./3., 4./3.])
-        equiv2 = all((p/3).cs == [4./3., 1./3.])
+        self.assertEqual(p/3, p/3)
+        equiv1 = all((p/3).cs == [1/3, 4/3])
+        equiv2 = all((p/3).cs == [4/3, 1/3])
         self.assertTrue(equiv1 or equiv2)
 
     def test_diff(self):

gpkit/tests/t_solution_array.py

@@ -100,7 +100,7 @@ class TestResultsTable(unittest.TestCase):
     def test_nan_printing(self):
         """Test that solution prints when it contains nans"""
         x = VarKey(name='x')
-        data = {x: np.array([np.nan, 1., 1., 1., 1.])}
+        data = {x: np.array([np.nan, 1, 1, 1, 1])}
         title = "Free variables"
         printstr = "\n".join(var_table(data, title))
         self.assertTrue(" - " in printstr)  # nan is printed as " - "

gpkit/tests/t_sub.py

@@ -223,7 +223,7 @@ def test_calcconst(self):
         m.substitutions.update({t_day: ("sweep", [6, 8, 9, 13])})
         sol = m.solve(verbosity=0)
         npt.assert_allclose(sol["sensitivities"]["constants"][t_day],
-                            [-1./3, -0.5, -0.6, +1], 1e-5)
+                            [-1/3, -0.5, -0.6, +1], 1e-5)
         self.assertEqual(len(sol["cost"]), 4)
         npt.assert_allclose([float(l) for l in
                              (sol(t_day) + sol(t_night))/gpkit.ureg.hours], 24)

gpkit/tests/t_tools.py

@@ -89,7 +89,7 @@ def test_dual_objective(self):
         eqns = [L >= 1, W >= 1,
                 L*W == 10]
         N = 4
-        ws = Variable("w_{CO}", ("sweep", np.linspace(1./N, 1-1./N, N)), "-")
+        ws = Variable("w_{CO}", ("sweep", np.linspace(1/N, 1-1/N, N)), "-")
         w_s = Variable("v_{CO}", lambda c: 1-c[ws], "-")
         obj = ws*(L+W) + w_s*(W**-1 * L**-3)
         m = Model(obj, eqns)
@@ -102,24 +102,24 @@ def test_te_exp_minus1(self):
         """Test Taylor expansion of e^x - 1"""
         x = Variable('x')
         self.assertEqual(te_exp_minus1(x, 1), x)
-        self.assertEqual(te_exp_minus1(x, 3), x + x**2/2. + x**3/6.)
+        self.assertEqual(te_exp_minus1(x, 3), x + x**2/2 + x**3/6)
         self.assertEqual(te_exp_minus1(x, 0), 0)
         # make sure x was not modified
         self.assertEqual(x, Variable('x'))
         # try for VectorVariable too
         y = VectorVariable(3, 'y')
         self.assertEqual(te_exp_minus1(y, 1), y)
-        self.assertEqual(te_exp_minus1(y, 3), y + y**2/2. + y**3/6.)
+        self.assertEqual(te_exp_minus1(y, 3), y + y**2/2 + y**3/6)
         self.assertEqual(te_exp_minus1(y, 0), 0)
         # make sure y was not modified
         self.assertEqual(y, VectorVariable(3, 'y'))
 
     def test_te_secant(self):
         "Test Taylor expansion of secant(var)"
         x = Variable('x')
-        self.assertEqual(te_secant(x, 1), 1 + x**2/2.)
+        self.assertEqual(te_secant(x, 1), 1 + x**2/2)
         a = te_secant(x, 2)
-        b = 1 + x**2/2. + 5*x**4/24.
+        b = 1 + x**2/2 + 5*x**4/24
         self.assertTrue(all([abs(val) <= 1e-10
                              for val in (a.hmap - b.hmap).values()]))  # pylint:disable=no-member
         self.assertEqual(te_secant(x, 0), 1)
@@ -128,23 +128,23 @@ def test_te_secant(self):
         # try for VectorVariable too
         y = VectorVariable(3, 'y')
         self.assertTrue(te_secant(y, 0) == 1)  # truthy bc monomial constraint
-        self.assertTrue(all(te_secant(y, 1) == 1 + y**2/2.))
-        self.assertTrue(all(te_secant(y, 2) == 1 + y**2/2. + 5*y**4/24.))
+        self.assertTrue(all(te_secant(y, 1) == 1 + y**2/2))
+        self.assertTrue(all(te_secant(y, 2) == 1 + y**2/2 + 5*y**4/24))
         # make sure y was not modified
         self.assertEqual(y, VectorVariable(3, 'y'))
 
     def test_te_tangent(self):
         "Test Taylor expansion of tangent(var)"
         x = Variable('x')
         self.assertEqual(te_tangent(x, 1), x)
-        self.assertEqual(te_tangent(x, 3), x + x**3/3. + 2*x**5/15.)
+        self.assertEqual(te_tangent(x, 3), x + x**3/3 + 2*x**5/15)
         self.assertEqual(te_tangent(x, 0), 0)
         # make sure x was not modified
         self.assertEqual(x, Variable('x'))
         # try for VectorVariable too
         y = VectorVariable(3, 'y')
         self.assertEqual(te_tangent(y, 1), y)
-        self.assertEqual(te_tangent(y, 3), y + y**3/3. + 2*y**5/15.)
+        self.assertEqual(te_tangent(y, 3), y + y**3/3 + 2*y**5/15)
         self.assertEqual(te_tangent(y, 0), 0)
         # make sure y was not modified
         self.assertEqual(y, VectorVariable(3, 'y'))

gpkit/tests/t_vars.py

@@ -52,7 +52,7 @@ def test_ast(self): # pylint: disable=too-many-statements
         # print(w >= x)  # TODO: this always prints the vector on the left
         self.assertEqual(str(3*(x + y)*z), "3·(x[:] + y[:])·z[:]")
         nni = 3
-        ii = np.tile(np.arange(1., nni+1.), a.shape[1:]+(1,)).T
+        ii = np.tile(np.arange(1, nni+1), a.shape[1:]+(1,)).T
         self.assertEqual(str(w*NomialArray(ii)/nni)[:4], "w·[[")
         self.assertEqual(str(w*NomialArray(ii)/nni)[-4:], "]]/3")
         self.assertEqual(str(NomialArray(ii)*w/nni)[:2], "[[")
@@ -221,7 +221,7 @@ def test_init(self):
 
         # test inspired by issue 137
         N = 20
-        x_arr = np.arange(0, 5., 5./N) + 1e-6
+        x_arr = np.arange(0, 5, 5/N) + 1e-6
         x = VectorVariable(N, 'x', x_arr, 'm', "Beam Location")
 
     def test_constraint_creation_units(self):

gpkit/tools/autosweep.py

@@ -37,7 +37,7 @@ class BinarySweepTree:  # pylint: disable=too-many-instance-attributes
 
     def __init__(self, bounds, sols, sweptvar, costposy):
         if len(bounds) != 2:
-            raise ValueError("bounds must be of length 2.")
+            raise ValueError("bounds must be of length 2")
         if bounds[1] <= bounds[0]:
             raise ValueError("bounds[0] must be smaller than bounds[1].")
         self.bounds = bounds

gpkit/tools/tools.py

@@ -60,7 +60,7 @@ def te_secant(var, nterm):
         E2n = np.append(E2n, E2n_add)
 
     res = 1
-    factorial_denom = 1.
+    factorial_denom = 1
     for i in range(1, nterm + 1):
         factorial_denom *= ((2*i)*(2*i-1))
         res = res + var**(2*i) * E2n[i-1] / factorial_denom
@@ -87,21 +87,21 @@ def te_tangent(var, nterm):
                                   " 15 terms")
 
     # The first 15 Bernoulli Numbers
-    B2n = np.asarray([1/6.,
-                      -1/30.,
-                      1/42.,
-                      -1/30.,
-                      5/66.,
-                      -691/2730.,
-                      7/6.,
-                      -3617/510.,
-                      43867/798.,
-                      -174611/330.,
-                      854513/138.,
-                      -236364091/2730.,
-                      8553103/6.,
-                      -23749461029/870.,
-                      8615841276005/14322.])
+    B2n = np.asarray([1/6,
+                      -1/30,
+                      1/42,
+                      -1/30,
+                      5/66,
+                      -691/2730,
+                      7/6,
+                      -3617/510,
+                      43867/798,
+                      -174611/330,
+                      854513/138,
+                      -236364091/2730,
+                      8553103/6,
+                      -23749461029/870,
+                      8615841276005/14322])
 
     res = 0
     factorial_denom = 1