chore(deps): update pre-commit hook astral-sh/ruff-pre-commit to v0.7.1

.pre-commit-config.yaml

@@ -33,7 +33,7 @@ repos:
     #       - id: yamlfmt
 
     - repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.7.0
+      rev: v0.7.1
       hooks:
         # Run the linter.
           - id: ruff

artistools/deposition.py

@@ -72,7 +72,7 @@ def main_analytical(args: argparse.Namespace | None = None, argsraw: list[str] |
     # define T52MN   (0.0211395*DAY)
 
     t_now = args.timedays * u.day
-    print(f't_now = {t_now.to("d")}')
+    print(f"t_now = {t_now.to('d')}")
     print("The following assumes that all 56Ni has decayed to 56Co and all energy comes from emitted positrons")
 
     # adata = at.atomic.get_levels(args.modelpath, get_photoionisations=True)
@@ -118,7 +118,7 @@ def main_analytical(args: argparse.Namespace | None = None, argsraw: list[str] |
         #     width = ((v_outer - v_inner) * t_now).to('cm').value
         #     tau = width * phixs * nnlevel
         #     print(f'width: {width:.3e} cm, phixs: {phixs:.3e} cm^2, nnlevel: {nnlevel:.3e} cm^-3, tau: {tau:.3e}')
-    print(f'Global posdep: {global_posdep.to("solLum"):.3e}')
+    print(f"Global posdep: {global_posdep.to('solLum'):.3e}")
 
 
 def main(args: argparse.Namespace | None = None, argsraw: list[str] | None = None, **kwargs: t.Any) -> None:

artistools/estimators/plot3destimators_classic.py

@@ -54,7 +54,7 @@ def plot_Te_vs_time_lineofsight_3d_model(modelpath, modeldata, estimators, reado
         associated_modeldata_row_for_mgi = modeldata.loc[modeldata["inputcellid"] == assoc_cells[mgi][0]]
 
         Te = [estimators[timestep, mgi]["Te"] for timestep, _ in enumerate(times)]
-        plt.scatter(times, Te, label=f'vel={associated_modeldata_row_for_mgi["vel_y_mid"].to_numpy()[0] / CLIGHT}')
+        plt.scatter(times, Te, label=f"vel={associated_modeldata_row_for_mgi['vel_y_mid'].to_numpy()[0] / CLIGHT}")
 
     plt.xlabel("time [days]")
     plt.ylabel("Te [K]")

artistools/inputmodel/describeinputmodel.py

@@ -146,17 +146,17 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
     if "cellYe" in dfmodel.collect_schema().names():
         electronfrac = dfmodel.select(pl.col("cellYe").dot(pl.col("mass_g")) / pl.col("mass_g").sum()).collect().item()
         assert electronfrac is not None
-        print(f'  {"electron frac Ye":19s} {electronfrac:.3f}')
+        print(f"  {'electron frac Ye':19s} {electronfrac:.3f}")
         if args.isotopes:
             # currently assumes that all isotopes are specified (i.e. not for Type Ia models)
             calcelectronfrac = calculate_model_electron_frac(dfmodel)
             assert calcelectronfrac is not None
-            print(f'  {"snapshot Ye":19s} {calcelectronfrac:.3f}')
+            print(f"  {'snapshot Ye':19s} {calcelectronfrac:.3f}")
 
     if "q" in dfmodel.collect_schema().names():
         initial_energy = dfmodel.select(pl.col("q").dot(pl.col("mass_g"))).collect().item()
         assert initial_energy is not None
-        print(f'  {"initial energy":19s} {initial_energy:.3e} erg')
+        print(f"  {'initial energy':19s} {initial_energy:.3e} erg")
     else:
         initial_energy = 0.0
 
@@ -176,7 +176,7 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
             .item()
         ) * 1e7
 
-    print(f'  {"kinetic energy":19s} {ejecta_ke_erg:.2e} [erg]')
+    print(f"  {'kinetic energy':19s} {ejecta_ke_erg:.2e} [erg]")
 
     mass_msun_rho = dfmodel.select(pl.col("mass_g").sum() / msun_g).collect().item()
 
@@ -203,18 +203,18 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
                 )
 
                 print(
-                    f'  {"initial energy":19s} {initial_energy_mapped:.3e} erg (when mapped to'
+                    f"  {'initial energy':19s} {initial_energy_mapped:.3e} erg (when mapped to"
                     f" {ncoordgridx}^3 cubic grid, error"
                     f" {100 * (initial_energy_mapped / initial_energy - 1):.2f}%)"
                 )
 
             mtot_mapped_msun = sum(cellmass_mapped) / msun_g
             print(
-                f'  {"M_tot_rho_map":19s} {mtot_mapped_msun:7.5f} MSun (density * volume when mapped to {ncoordgridx}^3'
+                f"  {'M_tot_rho_map':19s} {mtot_mapped_msun:7.5f} MSun (density * volume when mapped to {ncoordgridx}^3"
                 f" cubic grid, error {100 * (mtot_mapped_msun / mass_msun_rho - 1):.2f}%)"
             )
 
-    print(f'  {"M_tot_rho":19s} {mass_msun_rho:7.5f} MSun (density * volume)')
+    print(f"  {'M_tot_rho':19s} {mass_msun_rho:7.5f} MSun (density * volume)")
 
     if modelmeta["dimensions"] > 1:
         corner_mass = (
@@ -225,7 +225,7 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
             .item()
         ) / msun_g
         print(
-            f'  {"M_corners":19s} {corner_mass:7.5f} MSun ('
+            f"  {'M_corners':19s} {corner_mass:7.5f} MSun ("
             f" {100 * corner_mass / mass_msun_rho:.2f}% of M_tot in cells with v_r_mid > vmax)"
         )
 
@@ -273,28 +273,28 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
                 mass_msun_actinides += species_mass_msun
 
     print(
-        f'  {"M_tot_elem":19s} {mass_msun_elem:7.5f} MSun ({mass_msun_elem / mass_msun_rho * 100:6.2f}% of M_tot_rho)'
+        f"  {'M_tot_elem':19s} {mass_msun_elem:7.5f} MSun ({mass_msun_elem / mass_msun_rho * 100:6.2f}% of M_tot_rho)"
     )
 
     if args.isotopes:
         print(
-            f'  {"M_tot_iso":19s} {mass_msun_isotopes:7.5f} MSun ({mass_msun_isotopes / mass_msun_rho * 100:6.2f}% '
+            f"  {'M_tot_iso':19s} {mass_msun_isotopes:7.5f} MSun ({mass_msun_isotopes / mass_msun_rho * 100:6.2f}% "
             "of M_tot_rho, but can be < 100% if stable isotopes not tracked)"
         )
 
     mass_msun_fegroup = dfmodel.select(pl.col("X_Fegroup").dot(pl.col("mass_g"))).collect().item() / msun_g
     print(
-        f'  {"M_Fegroup":19s} {mass_msun_fegroup:7.5f} MSun'
+        f"  {'M_Fegroup':19s} {mass_msun_fegroup:7.5f} MSun"
         f" ({mass_msun_fegroup / mass_msun_rho * 100:6.2f}% of M_tot_rho)"
     )
 
     print(
-        f'  {"M_lanthanide_isosum":19s} {mass_msun_lanthanides:7.5f} MSun'
+        f"  {'M_lanthanide_isosum':19s} {mass_msun_lanthanides:7.5f} MSun"
         f" ({mass_msun_lanthanides / mass_msun_rho * 100:6.2f}% of M_tot_rho)"
     )
 
     print(
-        f'  {"M_actinide_isosum":19s} {mass_msun_actinides:7.5f} MSun'
+        f"  {'M_actinide_isosum':19s} {mass_msun_actinides:7.5f} MSun"
         f" ({mass_msun_actinides / mass_msun_rho * 100:6.2f}% of M_tot_rho)"
     )
 

artistools/inputmodel/energyinputfiles.py

@@ -16,14 +16,14 @@
 def write_energydistribution_file(energydistdata, outputfilepath="."):
     print("Writing energydistribution.txt")
     with Path(outputfilepath, "energydistribution.txt").open("w", encoding="utf-8") as fmodel:
-        fmodel.write(f'{len(energydistdata["cell_energy"])}\n')  # write number of points
+        fmodel.write(f"{len(energydistdata['cell_energy'])}\n")  # write number of points
         energydistdata.to_csv(fmodel, header=False, sep="\t", index=False, float_format="%g")
 
 
 def write_energyrate_file(energy_rate_data, outputfilepath="."):
     print("Writing energyrate.txt")
     with Path(outputfilepath, "energyrate.txt").open("w", encoding="utf-8") as fmodel:
-        fmodel.write(f'{len(energy_rate_data["times"])}\n')  # write number of points
+        fmodel.write(f"{len(energy_rate_data['times'])}\n")  # write number of points
         energy_rate_data.to_csv(fmodel, sep="\t", index=False, header=False, float_format="%.10f")
 
 

artistools/inputmodel/inputmodel_misc.py

@@ -311,9 +311,9 @@ def vectormatch(vec1: list[float], vec2: list[float]) -> bool:
                 if not vectormatch(pos3_in, [pos_z_mid, pos_y_mid, pos_x_mid]):
                     matched_pos_zyx_mid = False
 
-            assert (
-                sum((matched_pos_xyz_min, matched_pos_zyx_min, matched_pos_xyz_mid, matched_pos_zyx_mid)) == 1
-            ), "one option must match uniquely"
+            assert sum((matched_pos_xyz_min, matched_pos_zyx_min, matched_pos_xyz_mid, matched_pos_zyx_mid)) == 1, (
+                "one option must match uniquely"
+            )
 
             colrenames = {}
             if matched_pos_xyz_min:
@@ -934,7 +934,7 @@ def save_modeldata(
             fmodel.write(f"{vmax:.4e}\n")
 
         if customcols:
-            fmodel.write(f'#{" ".join(standardcols)} {" ".join(customcols)}\n')
+            fmodel.write(f"#{' '.join(standardcols)} {' '.join(customcols)}\n")
 
         abundandcustomcols = [*[col for col in standardcols if col.startswith("X_")], *customcols]
 

artistools/inputmodel/maptogrid.py

@@ -212,7 +212,7 @@ def maptogrid(
     assert isinstance(rmax, float)
     with Path(outputfolderpath, "ejectapartanalysis.dat").open(mode="w", encoding="utf-8") as fpartanalysis:
         fpartanalysis.writelines(
-            f'{part["dis"]} {part["h"]} {part["h"] / part["dis"]} {part["vrad"]} {part["vperp"]} {part["vtot"]}\n'
+            f"{part['dis']} {part['h']} {part['h'] / part['dis']} {part['vrad']} {part['vperp']} {part['vtot']}\n"
             for part in dfsnapshot.select(["dis", "h", "vrad", "vperp", "vtot"]).iter_rows(named=True)
         )
 

artistools/inputmodel/modelfromhydro.py

@@ -401,7 +401,7 @@ def makemodelfromgriddata(
         )
 
     if dfelabundances is not None:
-        print(f'Writing to {Path(outputpath) / "abundances.txt"}...')
+        print(f"Writing to {Path(outputpath) / 'abundances.txt'}...")
         at.inputmodel.save_initelemabundances(
             dfelabundances=dfelabundances, outpath=outputpath, headercommentlines=modelmeta["headercommentlines"]
         )
@@ -411,7 +411,7 @@ def makemodelfromgriddata(
     if "tracercount" in dfmodel:
         dfmodel = dfmodel.with_columns(pl.col("tracercount").cast(pl.Int32))
 
-    print(f'Writing to {Path(outputpath) / "model.txt"}...')
+    print(f"Writing to {Path(outputpath) / 'model.txt'}...")
     at.inputmodel.save_modeldata(outpath=outputpath, dfmodel=dfmodel, modelmeta=modelmeta)
 
 

artistools/inputmodel/opacityinputfile.py

@@ -43,7 +43,7 @@ def opacity_by_Ye(outputfilepath, griddata):
     griddata["opacity"] = cell_opacities
 
     with Path(outputfilepath, "opacity.txt").open("w", encoding="utf-8") as fopacity:
-        fopacity.write(f'{len(griddata["inputcellid"])}\n')
+        fopacity.write(f"{len(griddata['inputcellid'])}\n")
         griddata[["inputcellid", "opacity"]].to_csv(fopacity, sep="\t", index=False, header=False, float_format="%.10f")
 
 
@@ -59,7 +59,7 @@ def write_Ye_file(outputfilepath: Path | str, griddata: pd.DataFrame | pl.DataFr
     assert griddata.schema["inputcellid"].is_integer()
 
     with Path(outputfilepath, "Ye.txt").open("w", encoding="utf-8") as fYe:
-        fYe.write(f'{len(griddata["inputcellid"])}\n')
+        fYe.write(f"{len(griddata['inputcellid'])}\n")
         griddata.to_pandas(use_pyarrow_extension_array=True)[["inputcellid", "cellYe"]].to_csv(
             fYe, sep="\t", index=False, header=False, float_format="%.10f", na_rep="0.0"
         )

artistools/inputmodel/shen2018.py

@@ -90,8 +90,8 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
         v_inner = v_outer
         m_enc_inner = m_enc_outer
 
-    print(f'M_tot  = {m_enc_outer / u.solMass.to("g"):.3f} solMass')
-    print(f'M_Ni56 = {tot_ni56mass / u.solMass.to("g"):.3f} solMass')
+    print(f"M_tot  = {m_enc_outer / u.solMass.to('g'):.3f} solMass")
+    print(f"M_Ni56 = {tot_ni56mass / u.solMass.to('g'):.3f} solMass")
 
     at.save_modeldata(dfmodel=dfmodel, t_model_init_days=t_model_init_days, outpath=args.outputpath)
     at.inputmodel.save_initelemabundances(dfelabundances, outpath=args.outputpath)

artistools/inputmodel/test_inputmodel.py

@@ -99,9 +99,9 @@ def verify_file_checksums(checksums_expected: dict, digest: str = "sha256", fold
 
     for filename, checksum_expected in checksums_expected.items():
         fullpath = Path(folder) / filename
-        assert (
-            checksums_actual[fullpath] == checksum_expected
-        ), f"{folder}/{filename} checksum mismatch. Expecting {checksum_expected} but calculated {checksums_actual[fullpath]}"
+        assert checksums_actual[fullpath] == checksum_expected, (
+            f"{folder}/{filename} checksum mismatch. Expecting {checksum_expected} but calculated {checksums_actual[fullpath]}"
+        )
 
 
 def test_makeartismodelfrom_sph_particles() -> None:

artistools/inputmodel/to_tardis.py

@@ -96,9 +96,9 @@ def main(args: argparse.Namespace | None = None, argsraw: t.Sequence[str] | None
         # fileout.write(f'{0.},{0.:.4e},{0.},{0.},{",".join([f"{0.:.4e}" for _ in listspecies])}\n')
 
         for cell in dfmodel.itertuples(index=False):
-            abundlist = [f'{getattr(cell, f"X_{strnuc}"):.4e}' for strnuc in listspecies]
+            abundlist = [f"{getattr(cell, f'X_{strnuc}'):.4e}" for strnuc in listspecies]
             fileout.write(
-                f'{cell.vel_r_max_kmps},{cell.rho:.4e},{temperature},{dilution_factor},{",".join(abundlist)}\n'
+                f"{cell.vel_r_max_kmps},{cell.rho:.4e},{temperature},{dilution_factor},{','.join(abundlist)}\n"
             )
 
     print(f"Saved {outputfilepath}")

artistools/linefluxes.py

@@ -766,7 +766,7 @@ def make_emitting_regions_plot(args: argparse.Namespace) -> None:
                         emdata = emdata_all[modelindex][tmid, feature.colname]
 
                         if not bars:
-                            print(f'   {len(emdata["em_log10nne"])} points plotted for {feature.featurelabel}')
+                            print(f"   {len(emdata['em_log10nne'])} points plotted for {feature.featurelabel}")
 
                         serieslabel = (
                             (modellabel + " " + feature.featurelabel)

artistools/misc.py

@@ -1012,7 +1012,7 @@ def merge_pdf_files(pdf_files: list[str]) -> None:
             merger.append(pdffile)  # type: ignore[attr-defined]
         Path(pdfpath).unlink()
 
-    resultfilename = f'{pdf_files[0].replace(".pdf", "")}-{pdf_files[-1].replace(".pdf", "")}'
+    resultfilename = f"{pdf_files[0].replace('.pdf', '')}-{pdf_files[-1].replace('.pdf', '')}"
     with Path(f"{resultfilename}.pdf").open("wb") as resultfile:
         merger.write(resultfile)  # type: ignore[attr-defined]
 

artistools/nltepops/nltepops.py

@@ -53,7 +53,7 @@ def texifyconfiguration(levelname: str) -> str:
         strout = strout.replace(strorbitalocc, strorbitalocctex)
 
     for parentterm in re.findall(r"\([0-9][A-Z][^)]?\)", strout):
-        parentermtex = f'({texifyterm(parentterm.strip("()"))})'
+        parentermtex = f"({texifyterm(parentterm.strip('()'))})"
         strout = strout.replace(parentterm, parentermtex)
     strterm = levelname.split("_")[-1]
     strout += " " + texifyterm(strterm)

artistools/packets/packets.py

@@ -819,7 +819,7 @@ def make_3d_histogram_from_packets(
         # print(dfpackets[['emission_velocity', 'em_velx', 'em_vely', 'em_velz']])
         # select only type escape and type r-pkt (don't include gamma-rays)
         dfpackets = dfpackets.query(
-            f'type_id == {type_ids["TYPE_ESCAPE"]} and escape_type_id == {type_ids["TYPE_RPKT"]}'
+            f"type_id == {type_ids['TYPE_ESCAPE']} and escape_type_id == {type_ids['TYPE_RPKT']}"
         )
         if em_time:
             dfpackets = dfpackets.query("@timeminarray[@timestep_min] < em_time/@DAY < @timemaxarray[@timestep_max]")

artistools/plotspherical.py

@@ -176,7 +176,7 @@ def plot_spherical(
         .sort(["costhetabin", "phibin"])
     ).collect()
 
-    print(f'packets plotted: {alldirbins.select("count").sum().item(0, 0):.1e}')
+    print(f"packets plotted: {alldirbins.select('count').sum().item(0, 0):.1e}")
 
     # these phi and theta angle ranges are defined differently to artis
     phigrid = np.linspace(-np.pi, np.pi, nphibins + 1, endpoint=True, dtype=np.float64)

artistools/spectra/sampleblackbodyfrompacket_tr.py

@@ -94,7 +94,7 @@ def planck(nu, temperature):
 for npacketfile in range(nprocs):
     dfpackets = at.packets.readfile(packetsfiles[npacketfile])  # , type='TYPE_ESCAPE', escape_type='TYPE_RPKT')
     dfpackets = at.packets.bin_packet_directions(modelpath, dfpackets)
-    dfpackets = dfpackets.query(f'type_id == {type_ids["TYPE_ESCAPE"]} and escape_type_id == {type_ids["TYPE_RPKT"]}')
+    dfpackets = dfpackets.query(f"type_id == {type_ids['TYPE_ESCAPE']} and escape_type_id == {type_ids['TYPE_RPKT']}")
 
     # print(max(dfpackets['t_arrive_d']))
     # print(dfpackets)

artistools/spectra/spectra.py

@@ -1258,7 +1258,7 @@ def print_integrated_flux(
     lambda_max = arr_lambda_angstroms.max()
     assert isinstance(lambda_min, int | float)
     assert isinstance(lambda_max, int | float)
-    print(f" integrated flux ({lambda_min:.1f} to " f"{lambda_max:.1f} A): {integrated_flux:.3e} erg/s/cm2")
+    print(f" integrated flux ({lambda_min:.1f} to {lambda_max:.1f} A): {integrated_flux:.3e} erg/s/cm2")
     assert isinstance(integrated_flux, float)
     return integrated_flux
 

artistools/writecomparisondata.py

@@ -37,7 +37,7 @@ def write_spectra(modelpath: str | Path, model_id: str, selected_timesteps: t.Se
     with outfilepath.open("w", encoding="utf-8") as outfile:
         outfile.write(f"#NTIMES: {len(selected_timesteps)}\n")
         outfile.write(f"#NWAVE: {len(lambdas)}\n")
-        outfile.write(f'#TIMES[d]: {" ".join([f"{times[ts]:.2f}" for ts in selected_timesteps])}\n')
+        outfile.write(f"#TIMES[d]: {' '.join([f'{times[ts]:.2f}' for ts in selected_timesteps])}\n")
         outfile.write("#wavelength[Ang] flux_t0[erg/s/Ang] flux_t1[erg/s/Ang] ... flux_tn[erg/s/Ang]\n")
 
         for n in reversed(range(len(lambdas))):
@@ -53,7 +53,7 @@ def write_ntimes_nvel(outfile: TextIOWrapper, selected_timesteps: t.Sequence[int
     _, modelmeta = at.inputmodel.get_modeldata(modelpath, getheadersonly=True)
     outfile.write(f"#NTIMES: {len(selected_timesteps)}\n")
     outfile.write(f"#NVEL: {modelmeta['npts_model']}\n")
-    outfile.write(f'#TIMES[d]: {" ".join([f"{times[ts]:.2f}" for ts in selected_timesteps])}\n')
+    outfile.write(f"#TIMES[d]: {' '.join([f'{times[ts]:.2f}' for ts in selected_timesteps])}\n")
 
 
 def write_single_estimator(modelpath, selected_timesteps, estimators, allnonemptymgilist, outfile, keyname) -> None:
@@ -103,12 +103,12 @@ def write_ionfracts(
         with pathfileout.open("w", encoding="utf-8") as f:
             f.write(f"#NTIMES: {len(selected_timesteps)}\n")
             f.write(f"#NSTAGES: {nions}\n")
-            f.write(f'#TIMES[d]: {" ".join([f"{times[ts]:.2f}" for ts in selected_timesteps])}\n')
+            f.write(f"#TIMES[d]: {' '.join([f'{times[ts]:.2f}' for ts in selected_timesteps])}\n")
             f.write("#\n")
             for timestep in selected_timesteps:
                 f.write(f"#TIME: {times[timestep]:.2f}\n")
                 f.write(f"#NVEL: {len(allnonemptymgilist)}\n")
-                f.write(f'#vel_mid[km/s] {" ".join([f"{elsymb.lower()}{ion}" for ion in range(nions)])}\n')
+                f.write(f"#vel_mid[km/s] {' '.join([f'{elsymb.lower()}{ion}' for ion in range(nions)])}\n")
                 for modelgridindex, cell in modeldata.iterrows():
                     if modelgridindex not in allnonemptymgilist:
                         continue
@@ -134,7 +134,7 @@ def write_phys(modelpath, model_id, selected_timesteps, estimators, allnonemptym
     modeldata, modelmeta = at.inputmodel.get_modeldata(modelpath, derived_cols=["vel_r_min_kmps"])
     with Path(outputpath, f"phys_{model_id}_artisnebular.txt").open("w", encoding="utf-8") as f:
         f.write(f"#NTIMES: {len(selected_timesteps)}\n")
-        f.write(f'#TIMES[d]: {" ".join([f"{times[ts]:.2f}" for ts in selected_timesteps])}\n')
+        f.write(f"#TIMES[d]: {' '.join([f'{times[ts]:.2f}' for ts in selected_timesteps])}\n")
         f.write("#\n")
         for timestep in selected_timesteps:
             f.write(f"#TIME: {times[timestep]:.2f}\n")

conftest.py

@@ -12,9 +12,9 @@ def pytest_configure(config):
     assert isinstance(repopath, Path)
     if outputpath.exists():
         is_descendant = repopath.resolve() in outputpath.resolve().parents
-        assert (
-            is_descendant
-        ), f"Refusing to delete {outputpath.resolve()} as it is not a descendant of the repository {repopath.resolve()}"
+        assert is_descendant, (
+            f"Refusing to delete {outputpath.resolve()} as it is not a descendant of the repository {repopath.resolve()}"
+        )
         shutil.rmtree(outputpath, ignore_errors=True)
     outputpath.mkdir(exist_ok=True)
 

requirements.txt

@@ -21,7 +21,7 @@ pytest-codspeed>=2.2.1
 pytest-cov>=5.0.0
 pytest-xdist[psutil]>=3.6.1
 PyYAML>=6.0.2
-ruff>=0.7.0
+ruff>=0.7.1
 scipy>=1.14.1
 setuptools_scm[toml]>=8.1.0
 tabulate>=0.9