pylint and comment out not-working tests

Signed-off-by: nstarman <nstarman@users.noreply.github.com>

noxfile.py

@@ -10,7 +10,7 @@
 
 DIR = Path(__file__).parent.resolve()
 
-nox.options.sessions = ["lint", "tests"]  # "pylint",
+nox.options.sessions = ["lint", "pylint", "tests"]
 
 
 @nox.session

pyproject.toml

@@ -29,16 +29,17 @@ classifiers = [
 ]
 dynamic = ["version"]
 dependencies = [
-  "numpy",
-  "scipy>1.10",
+  "asdf",
+  "dustmaps",
   "astropy",
-  "matplotlib",
+  "astroquery",
   "gala",
   "galstreams",
+  "matplotlib",
+  "numba",
+  "numpy",
   "pyia",
-  "astroquery",
-  "dustmaps",
-  "asdf",
+  "scipy>1.10",
   "ugali",
 ]
 
@@ -81,6 +82,7 @@ addopts = ["-ra", "--showlocals", "--strict-markers", "--strict-config"]
 xfail_strict = true
 filterwarnings = [
   "error",
+  "ignore:numpy.ndarray size changed",
 ]
 log_cli_level = "INFO"
 testpaths = [
@@ -153,6 +155,7 @@ isort.required-imports = ["from __future__ import annotations"]
 
 [tool.ruff.lint.per-file-ignores]
 "docs/conf.py" = ["A001", "D100", "INP001"]
+"scripts/**" = ["INP001"]
 "tests/**" = ["ANN", "D1", "INP", "S101", "T20"]
 "noxfile.py" = ["T20"]
 "__init__.py" = ["F403"]
@@ -168,7 +171,11 @@ similarities.ignore-imports = "yes"
 messages_control.disable = [
   "design",
   "fixme",
-  "line-too-long",
-  "missing-module-docstring",
   "wrong-import-position",
+  # TODO: fix these and remove
+  "attribute-defined-outside-init",
+  "duplicate-code",
+  "invalid-name",
+  "no-member",
+  "unused-variable",
 ]

src/cats/combine_pm_cmd.py → scripts/combine_pm_cmd.py

@@ -8,8 +8,8 @@
 import matplotlib.pyplot as plt
 import pandas as pd
 
-from cats.cmd.CMD import Isochrone
-from cats.pawprint.pawprint import Footprint2D, Pawprint
+from cats.cmd import Isochrone
+from cats.pawprint import Footprint2D, Pawprint
 
 plt.rc("xtick", top=True, direction="in", labelsize=15)
 plt.rc("ytick", right=True, direction="in", labelsize=15)
@@ -50,9 +50,7 @@ def generate_isochrone_vertices(
     return o.simpleSln(0.1, 15, mass_thresh=0.83)[0]
 
 
-def generate_pm_vertices(
-    cat: Any, sky_poly: Any, cmd_poly: Any, config: Any
-) -> list[list[float]]:
+def generate_pm_vertices() -> list[list[float]]:
     """Generate Proper Motion Vertices.
 
     Use the generated class to make a new polygon for the given catalog in PM
@@ -80,7 +78,7 @@ def main() -> int:
     cat = at.Table.read(config.streaminfo.cat_fn)
 
     # load in file with the sky footprint.
-    sky_poly, bg_poly = load_sky_region(config.streaminfo.sky_print)
+    sky_poly, _ = load_sky_region(config.streaminfo.sky_print)
 
     # have an initial selection for the PM region that is very wide
     # this could also be stored in a footprint

src/cats/cmd/_core.py

@@ -2,16 +2,15 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Callable
+from typing import TYPE_CHECKING, Any
 
 import astropy.units as u
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import numpy as np
 import scipy
-from astropy.convolution import Gaussian1DKernel, convolve
 from astropy.coordinates import Distance
-from isochrones.mist import MIST_Isochrone
+from isochrones.mist import MIST_Isochrone  # pylint: disable=import-error
 from matplotlib.patches import PathPatch
 from scipy.interpolate import InterpolatedUnivariateSpline, interp1d
 from scipy.signal import correlate2d
@@ -22,7 +21,6 @@
 
 if TYPE_CHECKING:
     from matplotlib.figure import Figure
-    from numpy.typing import NDArray
 
     from cats.pawprint import Pawprint
 
@@ -271,7 +269,9 @@ def correct_isochrone(self) -> None:
         signal = signal.T
 
         ccor2d = correlate2d(self.CMD_data, signal)
-        y, x = np.unravel_index(np.argmax(ccor2d), ccor2d.shape)
+        y, x = np.unravel_index(
+            np.argmax(ccor2d), ccor2d.shape
+        )  # pylint: disable=W0632
         self.x_shift = (x - len(ccor2d[0]) / 2.0) * (self.x_edges[1] - self.x_edges[0])
         self.y_shift = (y - len(ccor2d) / 2.0) * (self.y_edges[1] - self.y_edges[0])
 
@@ -395,9 +395,6 @@ def simpleSln(
             self.color[ind] + coloff + tol,
             fill_value="extrapolate",
         )
-        # iso_model = interp1d(
-        #     self.mag[ind] + magoff, self.color[ind] + coloff, fill_value="extrapolate"
-        # )
 
         hb_print, self.hb_mask = self.make_hb_print()
 
@@ -413,6 +410,7 @@ def simpleSln(
         return cmd_footprint, self.cmd_mask, hb_print, self.hb_mask, self.pawprint
 
     def make_hb_print(self) -> None:
+        """Make the horizontal branch polygon mask."""
         # probably want to incorporate this into cmdprint and have two
         # discontinuous regions
         if self.phot_survey == "PS1":
@@ -568,68 +566,67 @@ def plot_CMD(self, scale_err: float = 2) -> Figure:
 
         return fig
 
-    def convolve_1d(self, probabilities: NDArray, mag_err: NDArray) -> NDArray:
-        """1D Gaussian convolution.
-
-        Parameters
-        ----------
-        probabilities : NDArray
-            Probability of the magnitudes.
-        mag_err : NDArray
-            Uncertainty in the magnitudes.
-        """
-        self.probabilities = probabilities
-        self.mag_err = mag_err
-
-        sigma = mag_err / self.ybin  # error in pixel units
-        kernel = Gaussian1DKernel(sigma)
-        convolved = convolve(probabilities, kernel)
-
-        self.convolved = convolved
-
-    def convolve_errors(
-        self,
-        g_errors: Callable[[NDArray], NDArray],
-        r_errors: Callable[[NDArray], NDArray],
-        intr_err: float = 0.1,
-    ) -> None:
-        """1D Gaussian convolution of the data with uncertainties.
-
-        Parameters
-        ----------
-        g_errors, r_errors : Callable[[ndarray], ndarray]
-            g, r magnitude uncertainties.
-        intr_err:
-            Free to set. Default is 0.1.
-        """
-        for i in range(len(probabilities)):
-            probabilities[i] = convolve_1d(
-                probabilities[i],
-                np.sqrt(
-                    g_errors(self.x_bins[i]) ** 2
-                    + r_errors(self.y_bins[i]) ** 2
-                    + intr_err**2
-                ),
-                sel.fx_bins[1] - self.x_bins[0],
-            )
-
-        self.probabilities = probabilities
-
-    def errFn(self) -> None:
-        """Generate the errors for the magnitudes."""
-        gerrs = np.zeros(len(self.y_bins))
-        rerrs = np.zeros(len(self.x_bins))
-
-        for i in range(len(self.y_bins)):
-            gerrs[i] = np.nanmedian(
-                self.cat["g0"][abs(self.cat["g0"] - self.y_bins[i]) < self.ybin / 2]
-            )
-            rerrs[i] = np.nanmedian(
-                self.cat["r0"][abs(self.cat["g0"] - self.x_bins[i]) < self.xbin / 2]
-            )
-
-        gerrs = interp1d(self.y_bins, gerrs, fill_value="extrapolate")
-        rerrs = interp1d(self.x_bins, rerrs, fill_value="extrapolate")
-
-        self.gerrs = gerrs
-        self.rerrs = rerrs
+    # def convolve_1d(self, probabilities: NDArray, mag_err: NDArray) -> NDArray:
+    #     """1D Gaussian convolution.
+
+    #     Parameters
+    #     ----------
+    #     probabilities : NDArray
+    #         Probability of the magnitudes.
+    #     mag_err : NDArray
+    #         Uncertainty in the magnitudes.
+    #     """
+    #     self.probabilities = probabilities
+    #     self.mag_err = mag_err
+
+    #     sigma = mag_err / self.ybin  # error in pixel units
+    #     kernel = Gaussian1DKernel(sigma)
+    #     convolved = convolve(probabilities, kernel)
+
+    #     self.convolved = convolved
+
+    # def convolve_errors(
+    #     self,
+    #     probabilities: NDArray,
+    #     g_errors: Callable[[NDArray], NDArray],
+    #     r_errors: Callable[[NDArray], NDArray],
+    #     intr_err: float = 0.1,
+    # ) -> None:
+    #     """1D Gaussian convolution of the data with uncertainties.
+
+    #     Parameters
+    #     ----------
+    #     probabilities : NDArray
+    #         Probability of the magnitudes.
+    #     g_errors, r_errors : Callable[[ndarray], ndarray]
+    #         g, r magnitude uncertainties.
+    #     intr_err:
+    #         Free to set. Default is 0.1.
+    #     """
+    #     for i in range(len(probabilities)):
+    #         probabilities[i] = self.convolve_1d(
+    #             probabilities[i],
+    #             np.sqrt(
+    #                 g_errors(self.x_bins[i]) ** 2
+    #                 + r_errors(self.y_bins[i]) ** 2
+    #                 + intr_err**2
+    #             ),
+    #             self.fx_bins[1] - self.x_bins[0],
+    #         )
+
+    #     self.probabilities = probabilities
+
+    # TODO: remove this function?
+    # def errFn(self) -> None:
+    #     """Generate the errors for the magnitudes."""
+    #     g0 = self.cat["g0"]
+    #     r0 = self.cat["r0"]
+    #     yhb = self.ybin / 2  # half bin size
+    #     xhb = self.xbin / 2
+    #     gerrs = np.array([np.nanmedian(g0[abs(g0 - yb) < yhb]) for yb in self.y_bins])
+    #     rerrs = np.array(  # TODO: are we sure this is right?
+    #         [np.nanmedian(r0[abs(g0 - xb) < xhb]) for xb in self.x_bins]
+    #     )
+
+    #     self.gerrs = interp1d(self.y_bins, gerrs, fill_value="extrapolate")
+    #     self.rerrs = interp1d(self.x_bins, rerrs, fill_value="extrapolate")

src/cats/pawprint/_core.py

@@ -1,3 +1,5 @@
+"""Core classes for pawprint."""
+
 from __future__ import annotations
 
 __all__ = ["Pawprint"]
@@ -12,6 +14,8 @@
 from astropy.coordinates import SkyCoord
 from gala.coordinates import GreatCircleICRSFrame
 
+from cats.pawprint._footprint import Footprint2D
+
 if TYPE_CHECKING:
     from typing_extensions import Self
 
@@ -79,8 +83,9 @@ def __init__(self, data: dict[str, Any]) -> None:
 
     @classmethod
     def from_file(cls: type[Self], fname: str) -> Self:
+        """Create a pawprint from an asdf file."""
         data = {}
-        with asdf.open("fname") as a:
+        with asdf.open(fname) as a:
             # first transfer the stuff that goes directly
             data["stream_name"] = a["stream_name"]
             data["pawprint_ID"] = a["pawprint_ID"]
@@ -115,6 +120,8 @@ def from_file(cls: type[Self], fname: str) -> Self:
     def pawprint_from_galstreams(
         cls: type[Self], stream_name: str, pawprint_ID: Any, width: float
     ) -> Self:
+        """Create a pawprint from galstreams data."""
+
         def _get_stream_frame_from_file(summary_file: str) -> GreatCircleICRSFrame:
             t = apt.QTable.read(summary_file)
 
@@ -162,7 +169,7 @@ def _get_stream_frame_from_file(summary_file: str) -> GreatCircleICRSFrame:
         try:
             # one standard deviation on each side (is this wide enough?)
             data["width"] = 2 * data["track"].track_width["width_phi2"]
-        except Exception:
+        except KeyError:
             data["width"] = width
         data["stream_vertices"] = data["track"].create_sky_polygon_footprint_from_track(
             width=data["width"], phi2_offset=0.0 * u.deg
@@ -183,6 +190,7 @@ def _get_stream_frame_from_file(summary_file: str) -> GreatCircleICRSFrame:
     def add_cmd_footprint(
         self, new_footprint: Any, color: Any, mag: Any, name: str
     ) -> None:
+        """Add a color-magnitude diagram footprint."""
         if self.cmd_filters is None:
             self.cmd_filters = dict((name, [color, mag]))
             self.cmdprint = dict((name, new_footprint))
@@ -191,14 +199,24 @@ def add_cmd_footprint(
             self.cmdprint[name] = new_footprint
 
     def add_pm_footprint(self, new_footprint: Any, name: str) -> None:
+        """Add a proper motion footprint."""
         if self.pmprint is None:
             self.pmprint = dict((name, new_footprint))
         else:
             self.pmprint[name] = new_footprint
 
     def save_pawprint(self) -> None:
-        # WARNING this doesn't save the track yet - need schema
-        # WARNING the stream frame doesn't save right either
+        """Save the pawprint to an asdf file.
+
+        .. warning::
+
+            This doesn't save the track yet.
+
+        .. todo::
+
+            Make an ASDF schema for the track and the frame, and then the
+            pawprint.
+        """
         fname = self.stream_name + self.pawprint_ID + ".asdf"
         tree = {
             "stream_name": self.stream_name,