[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

galpy/actionAngle/actionAngleSpherical.py

@@ -807,9 +807,7 @@ def _calc_anglez(
 
 def _JrSphericalIntegrand(r, E, L, pot):
     """The J_r integrand"""
-    return numpy.sqrt(
-        2.0 * (E - _evaluateplanarPotentials(pot, r)) - L**2.0 / r**2.0
-    )
+    return numpy.sqrt(2.0 * (E - _evaluateplanarPotentials(pot, r)) - L**2.0 / r**2.0)
 
 
 def _TrSphericalIntegrandSmall(t, E, L, pot, rperi):

galpy/actionAngle/actionAngleStaeckel.py

@@ -1237,10 +1237,7 @@ def calcELStaeckel(R, vR, vT, z, vz, pot, vc=1.0, ro=1.0):
 
     """
     return (
-        _evaluatePotentials(pot, R, z)
-        + vR**2.0 / 2.0
-        + vT**2.0 / 2.0
-        + vz**2.0 / 2.0,
+        _evaluatePotentials(pot, R, z) + vR**2.0 / 2.0 + vT**2.0 / 2.0 + vz**2.0 / 2.0,
         R * vT,
     )
 
@@ -1552,9 +1549,7 @@ def estimateDeltaStaeckel(pot, R, z, no_median=False, delta0=1e-6):
                 for ii in range(len(R))
             ]
         )
-        indx = (delta2 < delta0**2.0) * (
-            (delta2 > -(10.0**-10.0)) + pot_includes_scf
-        )
+        indx = (delta2 < delta0**2.0) * ((delta2 > -(10.0**-10.0)) + pot_includes_scf)
         delta2[indx] = delta0**2.0
         if not no_median:
             delta2 = numpy.median(delta2[True ^ numpy.isnan(delta2)])

galpy/actionAngle/actionAngleTorus.py

@@ -18,9 +18,9 @@
 from .actionAngleTorus_c import _ext_loaded as ext_loaded
 
 _autofit_errvals = {}
-_autofit_errvals[
-    -1
-] = "something wrong with input, usually bad starting values for the parameters"
+_autofit_errvals[-1] = (
+    "something wrong with input, usually bad starting values for the parameters"
+)
 _autofit_errvals[-2] = "Fit failed the goal by a factor <= 2"
 _autofit_errvals[-3] = "Fit failed the goal by more than 2"
 _autofit_errvals[-4] = "Fit aborted: serious problems occurred"

galpy/df/constantbetadf.py

@@ -384,9 +384,9 @@ def _fEintegrand_raw(r, pot, E, dmp1nudrmp1, alpha):
     out = numpy.zeros_like(r)  # Avoid JAX item assignment issues
     # print("r",r,dmp1nudrmp1(r),(_evaluatePotentials(pot,r,0)-E))
     out[:] = dmp1nudrmp1(r) / (_evaluatePotentials(pot, r, 0) - E) ** alpha
-    out[
-        True ^ numpy.isfinite(out)
-    ] = 0.0  # assume these are where denom is slightly neg.
+    out[True ^ numpy.isfinite(out)] = (
+        0.0  # assume these are where denom is slightly neg.
+    )
     return out
 
 

galpy/df/diskdf.py

@@ -1782,9 +1782,7 @@ def _estimateSigmaT2(self, R, phi=0.0, log=False):
                 self._gamma
             )
         else:
-            return (
-                self.targetSigma2(R, log=log, use_physical=False) / self._gamma**2.0
-            )
+            return self.targetSigma2(R, log=log, use_physical=False) / self._gamma**2.0
 
 
 class dehnendf(diskdf):

galpy/df/evolveddiskdf.py

@@ -2910,9 +2910,9 @@ def _buildvgrid(
                         deriv=deriv,
                         use_physical=False,
                     )
-                    out.df[
-                        ii, jj, numpy.isnan(out.df[ii, jj, :])
-                    ] = 0.0  # BOVY: for now
+                    out.df[ii, jj, numpy.isnan(out.df[ii, jj, :])] = (
+                        0.0  # BOVY: for now
+                    )
             if print_progress:
                 sys.stdout.write("\n")  # pragma: no cover
         else:
@@ -3278,9 +3278,9 @@ def __init__(
                     self.df[ii, jj, :] = edf(
                         thiso, numpy.array(t).flatten(), deriv=deriv
                     )
-                    self.df[
-                        ii, jj, numpy.isnan(self.df[ii, jj, :])
-                    ] = 0.0  # BOVY: for now
+                    self.df[ii, jj, numpy.isnan(self.df[ii, jj, :])] = (
+                        0.0  # BOVY: for now
+                    )
                     # Multiply in area, somewhat tricky for edge objects
                     if upperdxdy is None or (
                         ii != 0
@@ -3401,9 +3401,7 @@ def __call__(self, n, m):
                 return numpy.array(out) + self.subgrid(n, m)
         else:
             # We already multiplied in the area
-            thislevel = numpy.dot(
-                self.vRgrid**n, numpy.dot(self.df, self.vTgrid**m)
-            )
+            thislevel = numpy.dot(self.vRgrid**n, numpy.dot(self.df, self.vTgrid**m))
             if self.subgrid is None:
                 return thislevel
             else:

galpy/df/isotropicPlummerdf.py

@@ -40,12 +40,7 @@ def __init__(self, pot=None, ro=None, vo=None):
         self._Etildemax = pot._amp / pot._b
         # /amp^4 instead of /amp^5 to make the DF that of mass density
         self._fEnorm = (
-            24.0
-            * numpy.sqrt(2.0)
-            / 7.0
-            / numpy.pi**3.0
-            * pot._b**2.0
-            / pot._amp**4.0
+            24.0 * numpy.sqrt(2.0) / 7.0 / numpy.pi**3.0 * pot._b**2.0 / pot._amp**4.0
         )
 
     def fE(self, E):

galpy/df/osipkovmerrittNFWdf.py

@@ -59,9 +59,7 @@ def __init__(self, pot=None, ra=1.4, rmax=1e4, ro=None, vo=None):
         self._Qtildemax = pot._amp / pot.a
         self._Qtildemin = -pot(self._rmax, 0, use_physical=False) / self._Qtildemax
         self._a2overra2 = self._pot.a**2.0 / self._ra2
-        self._fQnorm = (
-            self._a2overra2 / (4.0 * numpy.pi) / pot.a**1.5 / pot._amp**0.5
-        )
+        self._fQnorm = self._a2overra2 / (4.0 * numpy.pi) / pot.a**1.5 / pot._amp**0.5
         # Initialize isotropic version to use as part of fQ
         self._idf = isotropicNFWdf(pot=pot, rmax=rmax, ro=ro, vo=vo)
 

galpy/df/osipkovmerrittdf.py

@@ -160,8 +160,7 @@ def _p_v_at_r(self, v, r):
             )
         else:
             return (
-                self.fQ(-_evaluatePotentials(self._pot, r, 0) - 0.5 * v**2.0)
-                * v**2.0
+                self.fQ(-_evaluatePotentials(self._pot, r, 0) - 0.5 * v**2.0) * v**2.0
             )
 
     def _sample_v(self, r, eta, n=1):

galpy/df/sphericaldf.py

@@ -732,10 +732,7 @@ def _p_v_at_r(self, v, r):
                 * v**2.0
             )
         else:
-            return (
-                self.fE(_evaluatePotentials(self._pot, r, 0) + 0.5 * v**2.0)
-                * v**2.0
-            )
+            return self.fE(_evaluatePotentials(self._pot, r, 0) + 0.5 * v**2.0) * v**2.0
 
 
 class anisotropicsphericaldf(sphericaldf):

galpy/df/streamdf.py

@@ -2650,9 +2650,7 @@ def sigangledAngle(self, dangle, assumeZeroMean=True, smallest=False, simple=Fal
             eigIndx = 1
         if simple:
             dt = self.meantdAngle(dangle, use_physical=False)
-            return numpy.sqrt(
-                self._sigangle2 + self._sortedSigOEig[eigIndx] * dt**2.0
-            )
+            return numpy.sqrt(self._sigangle2 + self._sortedSigOEig[eigIndx] * dt**2.0)
         aplow = numpy.amax(
             [
                 numpy.sqrt(self._sortedSigOEig[eigIndx]) * self._tdisrupt * 5.0,

galpy/df/streamgapdf.py

@@ -382,9 +382,7 @@ def _densMoments_approx_higherorder_gaussxpolyInts(self, ll, ul, maxj):
         in the higher-order terms, recursively"""
         gaussxpolyInt = numpy.zeros((maxj, len(ul)))
         gaussxpolyInt[-1] = (
-            1.0
-            / numpy.sqrt(numpy.pi)
-            * (numpy.exp(-(ll**2.0)) - numpy.exp(-(ul**2.0)))
+            1.0 / numpy.sqrt(numpy.pi) * (numpy.exp(-(ll**2.0)) - numpy.exp(-(ul**2.0)))
         )
         gaussxpolyInt[-2] = 1.0 / numpy.sqrt(numpy.pi) * (
             numpy.exp(-(ll**2.0)) * ll - numpy.exp(-(ul**2.0)) * ul

galpy/orbit/Orbits.py

@@ -219,9 +219,9 @@ def _update_keys_named_objects():
         # Format the keys of the known objects dictionary, first collections
         old_keys = list(_known_objects["_collections"].keys())
         for old_key in old_keys:
-            _known_objects["_collections"][
-                _named_objects_key_formatting(old_key)
-            ] = _known_objects["_collections"].pop(old_key)
+            _known_objects["_collections"][_named_objects_key_formatting(old_key)] = (
+                _known_objects["_collections"].pop(old_key)
+            )
         # Then the objects themselves
         old_keys = list(_known_objects.keys())
         old_keys.remove("_collections")
@@ -488,9 +488,7 @@ def _setup_parse_coordtransform(self, vxvv, ro, vo, zo, solarmotion, radec, lb):
             elif (
                 not vxvv.galcen_distance is None
                 and numpy.fabs(
-                    ro**2.0
-                    + zo**2.0
-                    - vxvv.galcen_distance.to(units.kpc).value ** 2.0
+                    ro**2.0 + zo**2.0 - vxvv.galcen_distance.to(units.kpc).value ** 2.0
                 )
                 > 1e-10
             ):
@@ -643,8 +641,7 @@ def _setup_parse_vxvv(self, vxvv, radec, lb, uvw):
                 / units.s
             )
             gc_frame = coordinates.Galactocentric(
-                galcen_distance=numpy.sqrt(self._ro**2.0 + self._zo**2.0)
-                * units.kpc,
+                galcen_distance=numpy.sqrt(self._ro**2.0 + self._zo**2.0) * units.kpc,
                 z_sun=self._zo * units.kpc,
                 galcen_v_sun=galcen_v_sun,
             )
@@ -2148,9 +2145,7 @@ def E(self, *args, **kwargs):
                             for jj in range(self.size)
                         ]
                     )
-                    + (
-                        thiso[1] ** 2.0 / 2.0 + thiso[2] ** 2.0 / 2.0 + vz**2.0 / 2.0
-                    ).T
+                    + (thiso[1] ** 2.0 / 2.0 + thiso[2] ** 2.0 / 2.0 + vz**2.0 / 2.0).T
                 )
         elif self.phasedim() == 6:
             z = kwargs.get("_z", 1.0) * thiso[3]  # For ER and Ez
@@ -2187,9 +2182,7 @@ def E(self, *args, **kwargs):
                             for jj in range(self.size)
                         ]
                     )
-                    + (
-                        thiso[1] ** 2.0 / 2.0 + thiso[2] ** 2.0 / 2.0 + vz**2.0 / 2.0
-                    ).T
+                    + (thiso[1] ** 2.0 / 2.0 + thiso[2] ** 2.0 / 2.0 + vz**2.0 / 2.0).T
                 )
         if onet:
             return out[:, 0]
@@ -8056,9 +8049,11 @@ def _parse_radec_kwargs(orb, kwargs, vel=False, dontpop=False, thiso=None):
     if isinstance(obs, list) and not thiso is None and thiso.shape[1] > orb.size:
         nt = thiso.shape[1] // orb.size
         obs = [
-            numpy.tile(obs[ii], nt)
-            if isinstance(obs[ii], numpy.ndarray) and obs[ii].ndim > 0
-            else obs[ii]
+            (
+                numpy.tile(obs[ii], nt)
+                if isinstance(obs[ii], numpy.ndarray) and obs[ii].ndim > 0
+                else obs[ii]
+            )
             for ii in range(len(obs))
         ]
         ro = numpy.tile(ro, nt) if isinstance(ro, numpy.ndarray) and ro.ndim > 0 else ro

galpy/potential/BurkertPotential.py

@@ -65,8 +65,7 @@ def _revaluate(self, r, t=0.0):
             * (
                 -numpy.pi / x
                 + 2.0 * (1.0 / x + 1) * numpy.arctan(1 / x)
-                + (1.0 / x + 1)
-                * numpy.log((1.0 + 1.0 / x) ** 2.0 / (1.0 + 1 / x**2.0))
+                + (1.0 / x + 1) * numpy.log((1.0 + 1.0 / x) ** 2.0 / (1.0 + 1 / x**2.0))
                 + special.xlogy(2.0 / x, 1.0 + x**2.0)
             )
         )

galpy/potential/DehnenBarPotential.py

@@ -163,10 +163,7 @@ def _smooth(self, t):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # bar is fully on
                 smooth = 1.0

galpy/potential/DehnenSmoothWrapperPotential.py

@@ -72,9 +72,7 @@ def _smooth(self, t):
         elif t < self._tsteady:
             deltat = t - self._tform
             xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
-            smooth = (
-                3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
-            )
+            smooth = 3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
         else:  # bar is fully on
             smooth = 1.0
         return smooth if self._grow else 1.0 - smooth

galpy/potential/DiskSCFPotential.py

@@ -392,10 +392,7 @@ def _Rzderiv(self, R, z, phi=0.0, t=0.0):
                 4.0
                 * numpy.pi
                 * a
-                * (
-                    H(z) * R * z / r**2.0 * (d2s(r) - ds(r) / r)
-                    + ds(r) * dH(z) * R / r
-                )
+                * (H(z) * R * z / r**2.0 * (d2s(r) - ds(r) / r) + ds(r) * dH(z) * R / r)
             )
         return out
 

galpy/potential/EllipsoidalPotential.py

@@ -430,11 +430,7 @@ def _forceInt(x, y, z, dens, b2, c2, i, glx=None, glw=None):
     def integrand(s):
         t = 1 / s**2.0 - 1.0
         return (
-            dens(
-                numpy.sqrt(
-                    x**2.0 / (1.0 + t) + y**2.0 / (b2 + t) + z**2.0 / (c2 + t)
-                )
-            )
+            dens(numpy.sqrt(x**2.0 / (1.0 + t) + y**2.0 / (b2 + t) + z**2.0 / (c2 + t)))
             * (
                 x / (1.0 + t) * (i == 0)
                 + y / (b2 + t) * (i == 1)

galpy/potential/EllipticalDiskPotential.py

@@ -109,10 +109,7 @@ def _evaluate(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # fully on
                 smooth = 1.0
@@ -135,10 +132,7 @@ def _Rforce(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # fully on
                 smooth = 1.0
@@ -162,18 +156,13 @@ def _phitorque(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # fully on
                 smooth = 1.0
         else:
             smooth = 1.0
-        return (
-            smooth * self._twophio * R**self._p * numpy.sin(2.0 * (phi - self._phib))
-        )
+        return smooth * self._twophio * R**self._p * numpy.sin(2.0 * (phi - self._phib))
 
     def _R2deriv(self, R, phi=0.0, t=0.0):
         # Calculate relevant time
@@ -184,10 +173,7 @@ def _R2deriv(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # fully on
                 smooth = 1.0
@@ -212,10 +198,7 @@ def _phi2deriv(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # perturbation is fully on
                 smooth = 1.0
@@ -238,10 +221,7 @@ def _Rphideriv(self, R, phi=0.0, t=0.0):
                 deltat = t - self._tform
                 xi = 2.0 * deltat / (self._tsteady - self._tform) - 1.0
                 smooth = (
-                    3.0 / 16.0 * xi**5.0
-                    - 5.0 / 8 * xi**3.0
-                    + 15.0 / 16.0 * xi
-                    + 0.5
+                    3.0 / 16.0 * xi**5.0 - 5.0 / 8 * xi**3.0 + 15.0 / 16.0 * xi + 0.5
                 )
             else:  # perturbation is fully on
                 smooth = 1.0

galpy/potential/FerrersPotential.py

@@ -439,9 +439,7 @@ def _FracInt(x, y, z, a, b, c, tau, n):
     sqrt(tau+a)(tau+b)(tau+c))       tau+a     tau+b     tau+c
     """
     denom = numpy.sqrt((a + tau) * (b + tau) * (c + tau))
-    return (
-        1.0 - x**2 / (a + tau) - y**2 / (b + tau) - z**2 / (c + tau)
-    ) ** n / denom
+    return (1.0 - x**2 / (a + tau) - y**2 / (b + tau) - z**2 / (c + tau)) ** n / denom
 
 
 def lowerlim(x, y, z, a, b, c):