run commit black and isort

Signed-off-by: Nathaniel Starkman (@nstarman) <[email protected]>

Author: nstarman

docs/conf.py

@@ -146,7 +146,9 @@
 
 # Grouping the document tree into LaTeX files. List of tuples
 # (source start file, target name, title, author, documentclass [howto/manual]).
-latex_documents = [("index", project + ".tex", project + u" Documentation", author, "manual")]
+latex_documents = [
+    ("index", project + ".tex", project + u" Documentation", author, "manual"),
+]
 
 
 # -- Options for manual page output -------------------------------------------

pyproject.toml

@@ -15,8 +15,7 @@ force_grid_wrap = 0
 use_parentheses = "True"
 ensure_newline_before_comments = "True"
 sections = ["FUTURE", "STDLIB", "THIRDPARTY", "FIRSTPARTY", "LOCALFOLDER"]
-
-known_third_party = ["astropy", "extension_helpers", "setuptools"]
+known_third_party = ["astropy", "extension_helpers", "galpy", "numpy", "scipy", "setuptools"]
 known_localfolder = "sample_scf"
 
 import_heading_stdlib = "BUILT-IN"

sample_scf/_typing.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # BUILT-IN
 import typing as T

sample_scf/base.py

@@ -109,7 +109,12 @@ def phisampler(self) -> rv_continuous_modrvs:
 
     # /def
 
-    def cdf(self, r: npt.ArrayLike, theta: npt.ArrayLike, phi: npt.ArrayLike) -> NDArray64:
+    def cdf(
+        self,
+        r: npt.ArrayLike,
+        theta: npt.ArrayLike,
+        phi: npt.ArrayLike,
+    ) -> NDArray64:
         """
         Cumulative Distribution Functions in r, theta(r), phi(r, theta)
 
@@ -156,7 +161,9 @@ def rvs(
         phis = self.phisampler.rvs(rs, thetas, size=size, random_state=random_state)
 
         crd = PhysicsSphericalRepresentation(
-            r=rs, theta=(np.pi / 2 - thetas) * u.rad, phi=phis * u.rad
+            r=rs,
+            theta=(np.pi / 2 - thetas) * u.rad,
+            phi=phis * u.rad,
         )
         return crd
 

sample_scf/sample_exact.py

@@ -23,8 +23,6 @@
 
 # LOCAL
 from ._typing import NDArray64, RandomLike
-
-# PROJECT-SPECIFIC
 from .base import SCFSamplerBase, rv_continuous_modrvs
 from .utils import _x_of_theta, difPls, phiRSms, thetaQls, x_of_theta
 
@@ -332,7 +330,7 @@ def _cdf(self, phi: NDArray64, *args: T.Any, **kw: T.Any) -> NDArray64:
         factor = 1 / Rm[0]  # R0
         ms = np.arange(1, Rm.shape[1])
         term1p = np.sum(
-            (Rm[1:] * np.sin(ms * phi) + Sm[1:] * (1 - np.cos(ms * phi))) / (2 * np.pi * ms)
+            (Rm[1:] * np.sin(ms * phi) + Sm[1:] * (1 - np.cos(ms * phi))) / (2 * np.pi * ms),
         )
 
         cdf: NDArray64 = term0 + factor * term1p

sample_scf/sample_intrp.py

@@ -122,7 +122,9 @@ def __init__(
     ) -> None:
         # compute the r-dependent coefficient matrix $\tilde{\rho}$
         nmax, lmax = pot._Acos.shape[:2]
-        rhoTilde = np.array([pot._rhoTilde(r, N=nmax, L=lmax) for r in rgrid])  # (R, N, L)
+        rhoTilde = np.array(
+            [pot._rhoTilde(r, N=nmax, L=lmax) for r in rgrid],
+        )  # (R, N, L)
 
         # ----------
         # theta Qls
@@ -134,7 +136,13 @@ def __init__(
         # phi Rm, Sm
         # radial and inclination sums
 
-        Rm, Sm = _phiRSms(rhoTilde, Acos=pot._Acos, Asin=pot._Asin, r=rgrid, theta=thetagrid)
+        Rm, Sm = _phiRSms(
+            rhoTilde,
+            Acos=pot._Acos,
+            Asin=pot._Asin,
+            r=rgrid,
+            theta=thetagrid,
+        )
 
         # ----------
         # make samplers
@@ -184,8 +192,18 @@ def __init__(self, pot: SCFPotential, rgrid: NDArray64, **kw: T.Any) -> None:
         # work in zeta, not r, since it is more numerically stable
         zeta = zeta_of_r(rgrid)
         # make splines for fast calculation
-        self._spl_cdf = InterpolatedUnivariateSpline(zeta, mgrid, ext="raise", bbox=[-1, 1])
-        self._spl_ppf = InterpolatedUnivariateSpline(mgrid, zeta, ext="raise", bbox=[0, 1])
+        self._spl_cdf = InterpolatedUnivariateSpline(
+            zeta,
+            mgrid,
+            ext="raise",
+            bbox=[-1, 1],
+        )
+        self._spl_ppf = InterpolatedUnivariateSpline(
+            mgrid,
+            zeta,
+            ext="raise",
+            bbox=[0, 1],
+        )
 
         # TODO! make sure
         # # store endpoint values to ensure CDF normalized to [0, 1]
@@ -479,7 +497,9 @@ def __init__(
         # start by supersampling
         Zetas, Xs, Phis = np.meshgrid(zetas, xs, self._phi_interpolant, indexing="ij")
         _cdfs = self._spl_cdf((Zetas.ravel(), Xs.ravel(), Phis.ravel())).reshape(
-            lR, lT, len(self._phi_interpolant)
+            lR,
+            lT,
+            len(self._phi_interpolant),
         )
         # build reverse spline
         ppfs = np.empty((lR, lT, self._ninterpolant), dtype=np.float64)
@@ -488,7 +508,9 @@ def __init__(
             ppfs[i, j, :] = splev(qarr, spl, ext=0)
         # interpolate
         self._spl_ppf = RegularGridInterpolator(
-            (zetas, xs, self._q_interpolant), ppfs, bounds_error=False
+            (zetas, xs, self._q_interpolant),
+            ppfs,
+            bounds_error=False,
         )
 
     # /def
@@ -505,7 +527,12 @@ def _cdf(
 
     # /def
 
-    def cdf(self, phi: npt.ArrayLike, r: npt.ArrayLike, theta: npt.ArrayLike) -> NDArray64:
+    def cdf(
+        self,
+        phi: npt.ArrayLike,
+        r: npt.ArrayLike,
+        theta: npt.ArrayLike,
+    ) -> NDArray64:
         # TODO! make sure r, theta in right domain
         cdf = self._cdf(
             phi,

sample_scf/utils.py

@@ -96,7 +96,8 @@ def zeta_of_r(r: T.Union[u.Quantity, NDArray64]) -> NDArray64:
 
 
 def r_of_zeta(
-    zeta: npt.ArrayLike, unit: T.Optional[u.UnitBase] = None
+    zeta: npt.ArrayLike,
+    unit: T.Optional[u.UnitBase] = None,
 ) -> T.Union[u.Quantity, NDArray64]:
     r""":math:`r = \frac{1 + \zeta}{1 - \zeta}`
 
@@ -258,7 +259,9 @@ def _phiRSms(
 
 
 def phiRSms(
-    pot: SCFPotential, r: npt.ArrayLike, theta: npt.ArrayLike
+    pot: SCFPotential,
+    r: npt.ArrayLike,
+    theta: npt.ArrayLike,
 ) -> T.Tuple[NDArray64, NDArray64]:
     r"""Radial and inclination sums for azimuthal weighting factors.