diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index ed31d85f6..6f3894bea 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -18,14 +18,15 @@ jobs:
   pre-commit:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v6
-    - uses: actions/setup-python@v6
-      with:
-        python-version: "3.14"
-    - name: Run pre-commit
-      run: |
-        pip install pre-commit
-        pre-commit run --files src/**/*.py
+      - uses: actions/checkout@main
+      - uses: actions/setup-python@main
+        with:
+          python-version: "3.14"
+          cache: pip
+      - name: Run pre-commit
+        run: |
+          pip install pre-commit
+          pre-commit run --files $(git ls-files "*.py")
 
   no_object_checks:
     needs: pre-commit
@@ -33,30 +34,73 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version:
-          - "3.11"
-          - "3.12"
-          - "3.13"
-          - "3.14"
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
         group: [1, 2, 3]
 
     steps:
-    - uses: actions/checkout@v6
+    - uses: actions/checkout@main
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v6
+      uses: actions/setup-python@main
       with:
         python-version: ${{ matrix.python-version }}
         cache: pip
+
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
         pip install --editable . --group dev
-    - name: Test with pytest
+
+    - name: Test with pytest + coverage
+      if: matrix.python-version == '3.14'
       run: |
-        coverage run --source src -m pytest tests/pre_3_10 --splits 3 --group ${{ matrix.group }}
-        coverage xml
-    - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v6
+        coverage run --source src --parallel-mode -m pytest tests/pre_3_10 --splits 3 --group ${{ matrix.group }}
+
+    - name: Test with pytest
+      if: matrix.python-version != '3.14'
+      run: pytest tests/pre_3_10 --splits 3 --group ${{ matrix.group }}
+
+    # upload each coverage shard file for combining later
+    - name: Upload coverage shard
+      if: matrix.python-version == '3.14'
+      uses: actions/upload-artifact@main
+      with:
+        name: coverage-no-objects-group-${{ matrix.group }}
+        path: .coverage.*
+        include-hidden-files: true
+
+  # combine the three shards before uploading to codecov
+  coverage_no_objects:
+    needs: no_object_checks
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@main
+
+      - uses: actions/setup-python@main
+        with:
+          python-version: "3.14"
+          cache: pip
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install --editable . --group dev
+
+      - name: Download coverage shards
+        uses: actions/download-artifact@main
+        with:
+          pattern: coverage-no-objects-group-*
+          merge-multiple: true
+
+      - name: Combine and export coverage
+        run: |
+          coverage combine
+          coverage xml
+
+      - name: Upload to Codecov
+        uses: codecov/codecov-action@main
+        with:
+          flags: no_objects  # distinguishes this suite in the Codecov UI
+          token: ${{ secrets.CODECOV_TOKEN }}
 
   objects_check:
     needs: pre-commit
@@ -67,19 +111,31 @@ jobs:
         python-version: ["3.11", "3.12", "3.13", "3.14"]
 
     steps:
-    - uses: actions/checkout@v6
+    - uses: actions/checkout@main
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v6
+      uses: actions/setup-python@main
       with:
         python-version: ${{ matrix.python-version }}
         cache: pip
+
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
         pip install --editable . --group dev
-    - name: Test with pytest
+
+    - name: Test with pytest + coverage
+      if: matrix.python-version == '3.14'
       run: |
         coverage run --source=src/vip_hci/objects/ -m pytest tests/post_3_10
         coverage xml
-    - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v6
+
+    - name: Test with pytest
+      if: matrix.python-version != '3.14'
+      run: pytest tests/post_3_10
+
+    - name: Upload to Codecov
+      if: matrix.python-version == '3.14'
+      uses: codecov/codecov-action@main
+      with:
+        flags: objects
+        token: ${{ secrets.CODECOV_TOKEN }}
diff --git a/.test_durations b/.test_durations
index 4d1581d6f..f846beb46 100644
--- a/.test_durations
+++ b/.test_durations
@@ -1,396 +1,200 @@
 {
-    "tests/pre_3_10/test_conf.py::test_check_array": 0.0009448270002394565,
-    "tests/pre_3_10/test_conf.py::test_check_enough_memory": 0.001534232000267366,
-    "tests/pre_3_10/test_dataset.py::test_saveable_dataset": 0.026163340000493918,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[3D-1br-2]": 0.002074555000035616,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[3D-2br-2]": 0.002946827000414487,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[3D-2br-[1,2]]": 0.003803053999945405,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[4D-1br-2]": 0.002419510999970953,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[4D-2br-2]": 0.0031940179997036466,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_cube_inject_companions[4D-2br-[1,2]]": 0.005085348999273265,
-    "tests/pre_3_10/test_fm_fakecomp.py::test_normalize_psf_shapes": 0.13249760600047011,
-    "tests/pre_3_10/test_fm_fakedisk.py::test_cube_inject_fakedisk[3D]": 0.007264263001161453,
-    "tests/pre_3_10/test_fm_fakedisk.py::test_cube_inject_trace[3D]": 0.003873825999107794,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[median_sub-firstguess-None-False-sum-False-None]": 17.36409372700291,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[pca-firstguess-3-True-None-False-None]": 4805.008413951999,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[pca_annular-firstguess-3-False-stddev-False-None]": 276.1521137669988,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[pca_annulus-mcmc_negfc_sampling-3-False-stddev-False-gb]": 3189.4055685210005,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[pca_annulus-mcmc_negfc_sampling-3-True-None-True-ac]": 13.455389487999128,
-    "tests/pre_3_10/test_fm_negfc_3d.py::test_algos[pca_annulus-nested_negfc_sampling-3-False-sum-False-None]": 391.0898957319987,
-    "tests/pre_3_10/test_fm_negfc_4d.py::test_algos[pca_annulus-firstguess-4-False-sum]": 104.96475922899845,
-    "tests/pre_3_10/test_fm_negfc_4d.py::test_algos[pca_annulus-firstguess-4-True-None]": 107.45344228199974,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_HG_phase_function_and_print[0.4]": 0.1610931730010634,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_HG_phase_function_and_print[0.9]": 0.15798255700065056,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_HG_phase_function_and_print[0]": 0.15326452199951746,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_double_HG_phase_function[0.2]": 0.09817494099843316,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_double_HG_phase_function[0.4]": 0.09790049499861198,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_double_HG_phase_function[0.9]": 0.09735819299930881,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_dust_distribution[55]": 0.0018734090008365456,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_dust_distribution[60]": 0.0017114679976657499,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_dust_distribution[65]": 0.0011796740000136197,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_homemade_phase_function[10]": 0.07189100700270501,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_homemade_phase_function[20]": 0.07324782299838262,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_homemade_phase_function[60]": 0.07598692000101437,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_scattered_light_disk[0]": 0.35001708200070425,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_scattered_light_disk[30]": 0.35262140599843406,
-    "tests/pre_3_10/test_fm_scatteredlightdisk.py::test_scattered_light_disk[60]": 0.3456563069994445,
-    "tests/pre_3_10/test_metrics_completeness.py::test_completeness_curve": 95.78075984799943,
-    "tests/pre_3_10/test_metrics_completeness.py::test_completeness_map": 512.084328797002,
-    "tests/pre_3_10/test_metrics_contrcurve.py::test_contrast_curve": 31.345007147001525,
-    "tests/pre_3_10/test_metrics_detection.py::test_detection_dog": 0.06214700199961953,
-    "tests/pre_3_10/test_metrics_detection.py::test_detection_log": 3.536986305998653,
-    "tests/pre_3_10/test_metrics_detection.py::test_detection_lpeaks": 0.12510709000162024,
-    "tests/pre_3_10/test_metrics_detection.py::test_detection_snrmap": 1.3919314830018266,
-    "tests/pre_3_10/test_metrics_snr.py::test_frame_report": 0.040421667999908095,
-    "tests/pre_3_10/test_metrics_snr.py::test_snrmap_fast": 1.0066158919998998,
-    "tests/pre_3_10/test_metrics_snr.py::test_snrmap_masked": 10.020044711998707,
-    "tests/pre_3_10/test_metrics_snr.py::test_snrmap_sss": 13.025515498999084,
-    "tests/pre_3_10/test_metrics_stim.py::test_normstimmap": 2.6724075249985617,
-    "tests/pre_3_10/test_metrics_stim.py::test_stimmap": 2.82266785200045,
-    "tests/pre_3_10/test_pca_svd.py::test_svd_recons": 0.001310138999542687,
-    "tests/pre_3_10/test_pipeline_adi_paco.py::test_algos[fast_paco-None]": 290.063934429003,
-    "tests/pre_3_10/test_pipeline_adi_paco.py::test_algos[fast_paco_parallel-None]": 282.0075367540012,
-    "tests/pre_3_10/test_pipeline_adi_paco.py::test_algos[full_paco-None]": 344.7504089419999,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[nmf-snrmap_fast]": 19.862909896002748,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[nmf_annular_ardi-snrmap_fast]": 121.84820888100148,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[nmf_annular_rdi-snrmap_fast]": 306.5563052380003,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[pca-snrmap_fast]": 6.398729093001748,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[pca_annular_ardi-snrmap_fast]": 11.65438401099891,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[pca_annular_rdi-snrmap_fast]": 6.808081585000764,
-    "tests/pre_3_10/test_pipeline_rdi.py::test_algos[pca_mask-snrmap_fast]": 4.607050608998179,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[medsub-None]": 6.45876743000008,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[medsub_annular-None]": 0.016447748997961753,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[pca_annular-None]": 0.003346259998579626,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[pca_double-snrmap_fast]": 19.243675446999987,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[pca_double_left_eigv-snrmap_fast]": 19.254295025999454,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[pca_single-snrmap_fast]": 18.890561857999273,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[pca_single_left_eigv-snrmap_fast]": 20.894869393998306,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[xloci-snrmap_fast]": 149.57750667099754,
-    "tests/pre_3_10/test_pipeline_sdi.py::test_algos[xloci_double-snrmap_fast]": 127.04142911000235,
-    "tests/pre_3_10/test_preproc_badframes.py::test_badfr_corr": 0.01414775899866072,
-    "tests/pre_3_10/test_preproc_badframes.py::test_badfr_ellip": 0.0977754420000565,
-    "tests/pre_3_10/test_preproc_badframes.py::test_badfr_pxstat": 0.03702596400034963,
-    "tests/pre_3_10/test_preproc_badpix.py::test_badpix_ann": 1.1866403499971057,
-    "tests/pre_3_10/test_preproc_badpix.py::test_badpix_clump": 3.427470025002549,
-    "tests/pre_3_10/test_preproc_badpix.py::test_badpix_ifs1": 34.93476781699974,
-    "tests/pre_3_10/test_preproc_badpix.py::test_badpix_ifs2": 46.02538736400129,
-    "tests/pre_3_10/test_preproc_badpix.py::test_badpix_iso": 0.5979241429995454,
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-    "tests/pre_3_10/test_preproc_recentering.py::test_satspots": 0.33523571399928187,
-    "tests/pre_3_10/test_preproc_recentering.py::test_satspots_image": 1.477167074001045,
-    "tests/pre_3_10/test_preproc_recentering.py::test_speckle_recentering": 43.3803175990015,
-    "tests/pre_3_10/test_preproc_rescaling.py::test_check_scal_vector": 0.0023853809980209917,
-    "tests/pre_3_10/test_preproc_rescaling.py::test_cube_px_resampling[ndimage]": 0.09154982800100697,
-    "tests/pre_3_10/test_preproc_rescaling.py::test_cube_px_resampling[opencv]": 0.018606757999805268,
-    "tests/pre_3_10/test_preproc_rescaling.py::test_cube_px_resampling[vip-fft]": 0.03635872999984713,
-    "tests/pre_3_10/test_preproc_rescaling.py::test_cube_rescaling_wavelengths[ndimage-bicubic]": 26.69963105699935,
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-    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[vip-fft-True]": 0.008221808999223867,
-    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[opencv-lanczos4-edge-interp+noise]": 5.661295323998274,
-    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[skimage-bicubic-symmetric-interp+noise]": 6.528927044999364,
-    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[skimage-biquintic-wrap-noise]": 4.134889907998513,
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-    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[3-2-0-0-10-truth5]": 0.002260377001221059,
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-    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-gauss-subt]": 0.00338047699915478,
-    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-hann]": 0.0019868239996867487,
-    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-laplacian-conv]": 0.001754527000230155,
-    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-laplacian]": 0.0010262700016028248,
-    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-median-subt]": 0.0019242449998273514,
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+    "tests/pre_3_10/test_preproc_rescaling.py::test_find_indices_sdi[6-5-truth1]": 0.00037920899922028184,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[ndimage-False]": 0.007614458998432383,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[ndimage-True]": 0.01491445899955579,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[opencv-False]": 0.000615834000200266,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[opencv-True]": 0.002836666004441213,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[vip-fft-False]": 0.0022203750013432,
+    "tests/pre_3_10/test_preproc_rescaling.py::test_frame_px_resampling[vip-fft-True]": 0.001970166998944478,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[opencv-lanczos4-edge-interp+noise]": 0.577141624999058,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[skimage-bicubic-symmetric-interp+noise]": 0.6923712089992478,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[skimage-biquintic-wrap-noise]": 0.4302830839988019,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[vip-fft-None-constant-None]": 1.2019933329938794,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate[vip-fft-None-reflect-noise]": 1.3166242500010412,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate_mask[opencv-lanczos4-edge-interp-True]": 0.10779887600438087,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate_mask[skimage-biquintic-reflect-interp-True]": 0.13829249999980675,
+    "tests/pre_3_10/test_preproc_rotation.py::test_cube_derotate_mask[vip-fft-None-reflect-interp-True]": 0.36853250000058324,
+    "tests/pre_3_10/test_preproc_rotation.py::test_define_annuli": 0.00034383300226181746,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[0-None-0-0-10-truth0]": 0.00041020900243893266,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[1-None-0-0-10-truth1]": 0.0003111239966528956,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[2-None-0-0-10-truth2]": 0.00030833300115773454,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[3-2-0-0-10-truth5]": 0.0003419169988774229,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[3-None-0-0-10-truth3]": 0.0002863750014512334,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[3-None-0-1-3-truth6]": 0.0003439169995544944,
+    "tests/pre_3_10/test_preproc_rotation.py::test_find_indices_adi[3-None-1-0-10-truth4]": 0.00030883399813319556,
+    "tests/pre_3_10/test_var_filters.py::test_fft_ifft": 0.00022191499738255516,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-fourier-butter]": 0.0006010009965393692,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-gauss-subt]": 0.0013446670018311124,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-hann]": 0.0005333749977580737,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-laplacian-conv]": 0.0009427509976376314,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-laplacian]": 0.0007614580026711337,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[cube-median-subt]": 0.00048404100016341545,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-fourier-butter]": 0.0002546260002418421,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-gauss-subt]": 0.00038083399704191834,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-hann]": 0.0002619160004542209,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-laplacian-conv]": 0.0003153750039928127,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-laplacian]": 0.00023054200210026465,
+    "tests/pre_3_10/test_var_filters.py::test_highpass[frame-median-subt]": 0.00022912599888513796,
+    "tests/pre_3_10/test_var_filters.py::test_iuwt": 0.0012909159959235694,
+    "tests/pre_3_10/test_var_filters.py::test_lowpass[cube-gauss]": 0.0010617909974826034,
+    "tests/pre_3_10/test_var_filters.py::test_lowpass[cube-median]": 0.00038308299917844124,
+    "tests/pre_3_10/test_var_filters.py::test_lowpass[frame-gauss]": 0.0005109999983687885,
+    "tests/pre_3_10/test_var_filters.py::test_lowpass[frame-median]": 0.0002299999941897113,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-4-fr10-psf6]": 0.0010198329982813448,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-4-fr10-psf7]": 0.000800832003733376,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-4-fr11-psf6]": 0.000865165999130113,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-4-fr11-psf7]": 0.0007773340003041085,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-6-fr10-psf6]": 0.0008493330024066381,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-6-fr10-psf7]": 0.0007797500038577709,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-6-fr11-psf6]": 0.0008596250008849893,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-4-6-fr11-psf7]": 0.0007906660030130297,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-6-5-fr10-psf6]": 0.0008379589999094605,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-6-5-fr10-psf7]": 0.0007619170028192457,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-6-5-fr11-psf6]": 0.0008848750003380701,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[airy-6-5-fr11-psf7]": 0.0008495000001857989,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-4-fr10-psf6]": 0.00146929200127488,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-4-fr10-psf7]": 0.0009627929939597379,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-4-fr11-psf6]": 0.0011147500044899061,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-4-fr11-psf7]": 0.0009600410048733465,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-6-fr10-psf6]": 0.0010108330025104806,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-6-fr10-psf7]": 0.0009424580021004658,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-6-fr11-psf6]": 0.0010388760019850451,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-4-6-fr11-psf7]": 0.0009217079968948383,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-6-5-fr10-psf6]": 0.0009971239996957593,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-6-5-fr10-psf7]": 0.0009268329959013499,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-6-5-fr11-psf6]": 0.0010275419990648516,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[gauss-6-5-fr11-psf7]": 0.0009376659982081037,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-4-fr10-psf6]": 0.002715708003961481,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-4-fr10-psf7]": 0.002566749997640727,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-4-fr11-psf6]": 0.002805750002153218,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-4-fr11-psf7]": 0.002713583002332598,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-6-fr10-psf6]": 0.002582417000667192,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-6-fr10-psf7]": 0.002524874002119759,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-6-fr11-psf6]": 0.002638250000018161,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-4-6-fr11-psf7]": 0.002614291002828395,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-6-5-fr10-psf6]": 0.0025367490015923977,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-6-5-fr10-psf7]": 0.0025143740022031125,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-6-5-fr11-psf6]": 0.0025916660051734652,
+    "tests/pre_3_10/test_var_fit2d.py::test_fit2d[moff-6-5-fr11-psf7]": 0.0026012489979621023,
+    "tests/pre_3_10/test_var_shapes.py::test_dist": 0.00014854100299999118,
+    "tests/pre_3_10/test_var_shapes.py::test_frame_center": 0.0001620840048417449,
+    "tests/pre_3_10/test_var_shapes.py::test_get_annulus_segments": 0.0009169999975711107,
+    "tests/pre_3_10/test_var_shapes.py::test_get_circle": 0.00027645799855235964,
+    "tests/pre_3_10/test_var_shapes.py::test_get_ell_annulus": 0.00019904200235032476,
+    "tests/pre_3_10/test_var_shapes.py::test_get_ellipse": 0.00019787500423262827,
+    "tests/pre_3_10/test_var_shapes.py::test_get_square": 0.00035424899760982953,
+    "tests/pre_3_10/test_var_shapes.py::test_mask_circle": 0.00029487399660865776,
+    "tests/pre_3_10/test_var_shapes.py::test_mask_roi": 0.0010457510034029838,
+    "tests/pre_3_10/test_var_shapes.py::test_matrix_scaling": 0.001095624997105915,
+    "tests/pre_3_10/test_var_shapes.py::test_reshape_matrix": 0.00016995700207189657
 }
diff --git a/Makefile b/Makefile
index 0cee8a47d..6a0f908f9 100644
--- a/Makefile
+++ b/Makefile
@@ -56,7 +56,7 @@ test:
 	pre-commit install-hooks
 	pre-commit install
 	pre-commit run --files src/**/*.py
-	coverate run -m pytest
+	coverage run -m pytest
 	coverage xml
 	rm confi_hist.pdf
 	rm confi_hist_gaussfit.pdf
diff --git a/helpers/update_docs_rst_from_README.py b/helpers/update_docs_rst_from_README.py
index c06fbc1ff..06cf89460 100644
--- a/helpers/update_docs_rst_from_README.py
+++ b/helpers/update_docs_rst_from_README.py
@@ -6,14 +6,14 @@
 
 with open("../README.rst") as f_r:
     readme = f_r.readlines()
-str_titles = ['TL;DR', 
+str_titles = ['TL;DR',
               'Installation and dependencies',
               'Image conventions',
               'Contact',
               'Attribution',
               'THE END']
 titles_occ = [0,0,0,1,0,0]
-w_titles = ['TLDR', 
+w_titles = ['TLDR',
             'Installation-and-dependencies',
             'Image-conventions',
             'Contact',
@@ -37,6 +37,6 @@
                 stop_write=True
             else:
                 continue
-            
-            
+
+
 print("successfully converted README into documentation rst files.")
diff --git a/pyproject.toml b/pyproject.toml
index 1690d34c7..d0811fedf 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,5 +1,5 @@
 [build-system]
-requires = ["setuptools>=42", "wheel"]
+requires = ["setuptools>=64"]
 build-backend = "setuptools.build_meta"
 
 [project]
@@ -26,7 +26,6 @@ classifiers = [
   "Programming Language :: Python :: 3.14",
   "Topic :: Scientific/Engineering :: Astronomy",
 ]
-urls.Homepage = "https://github.com/vortex-exoplanet/VIP"
 dependencies = [
     "astropy>=5.0.0",
     "corner>=2.2.1",
@@ -45,6 +44,10 @@ dependencies = [
     "scikit-learn>=1.0.2",
 ]
 
+[project.urls]
+Homepage = "https://github.com/vortex-exoplanet/VIP"
+Issues = "https://github.com/vortex-exoplanet/VIP/issues"
+
 [dependency-groups]
 dev = [
     "coverage>=7.10.0",
@@ -67,3 +70,13 @@ dev = [
     "sphinx_rtd_theme",
     "jupyter_sphinx",
 ]
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[tool.setuptools.package-data]
+"vip_hci" = ["py.typed"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+addopts = "-v --tb=short"
diff --git a/src/vip_hci/config/paramenum.py b/src/vip_hci/config/paramenum.py
index 049edd198..3953d3aaa 100644
--- a/src/vip_hci/config/paramenum.py
+++ b/src/vip_hci/config/paramenum.py
@@ -316,13 +316,13 @@ class OptMethod(str, Enum):
 
     * ``LSQ``
 
-    * ``ROBUST``
+    * ``L1``
     """
 
     NO = "no"
     TOTAL = "total"
     LSQ = "lsq"
-    ROBUST = "robust"
+    L1 = "l1"
 
 
 class VarEstim(str, Enum):
diff --git a/src/vip_hci/fm/fakecomp.py b/src/vip_hci/fm/fakecomp.py
index 7f8d7cecb..dfee18bbb 100644
--- a/src/vip_hci/fm/fakecomp.py
+++ b/src/vip_hci/fm/fakecomp.py
@@ -97,7 +97,7 @@ def cube_inject_companions(array, psf_template, angle_list, flevel, rad_dists,
         Number of CPUs to use for multiprocessing. If None, will be
         automatically set to half the number of available CPUs.
     copy_array: bool, optional
-        Default is True. If False, ``array`` is not copied before injection. This is intended for 
+        Default is True. If False, ``array`` is not copied before injection. This is intended for
         computing performance when ``array`` can be modified.
 
     Returns
diff --git a/src/vip_hci/fm/fakedisk.py b/src/vip_hci/fm/fakedisk.py
index 250fe09fe..284315faf 100644
--- a/src/vip_hci/fm/fakedisk.py
+++ b/src/vip_hci/fm/fakedisk.py
@@ -61,6 +61,7 @@ def cube_inject_fakedisk(
     """
     if not fakedisk.ndim == 2:
         raise TypeError("Fakedisk is not a frame or a 2d array.")
+    angle_list = np.asarray(angle_list)
     if not angle_list.ndim == 1:
         raise TypeError("Input parallactic angle is not a 1d array")
 
diff --git a/src/vip_hci/fm/negfc_fmerit.py b/src/vip_hci/fm/negfc_fmerit.py
index 74dfe8aa6..b1d9668a3 100644
--- a/src/vip_hci/fm/negfc_fmerit.py
+++ b/src/vip_hci/fm/negfc_fmerit.py
@@ -251,7 +251,7 @@ def chisquare(
         imlib=imlib_sh,
         interpolation=interpolation,
         transmission=transmission,
-        radial_gradient=radial_gradient, 
+        radial_gradient=radial_gradient,
         verbose=False
     )
 
diff --git a/src/vip_hci/greedy/ipca_fullfr.py b/src/vip_hci/greedy/ipca_fullfr.py
index 0a7197b52..e2159138e 100644
--- a/src/vip_hci/greedy/ipca_fullfr.py
+++ b/src/vip_hci/greedy/ipca_fullfr.py
@@ -146,7 +146,7 @@ def ipca(*all_args: List, **all_kwargs: dict):
         but has no additional options for the extraction of circumstellar signal
         at each iteration (all signals > 0 are considered). Installation of the
         GreeDS package is required for this option.
-        - If 'Christiaens24': Same as 'Juillard23' but not in Torch, and with 
+        - If 'Christiaens24': Same as 'Juillard23' but not in Torch, and with
         the extra parameters ``thr`` and ``ncomp_step`` available.
     ncomp : int or tuple/list of 2 or 3 int, optional
         How many PCs are used as a lower-dimensional subspace to project the
@@ -154,12 +154,12 @@ def ipca(*all_args: List, **all_kwargs: dict):
         - if mode is None:
             * strategy in {'ADI', 'RDI', 'ARDI'} and no ``mask_rdi`` provided:
             an int must be provided, ``ncomp`` is the fixed number of PCs to use
-            
+
             * strategy in {'RADI' , 'RARDI'} and no ``mask_rdi`` is provided:
             an int or a tuple/list of 2 int is accepted. In the latter case, the
             first value is used for IPCA-RDI, and the second for IPCA-ADI for
             the remaining iterations after the former converged.
-            
+
             * strategy in {'ADI', 'RDI', 'ARDI} and ``mask_rdi`` is provided: an
             int or a tuple/list of 2 int can be provided. In the latter case,
             the first value is used for PCA-data imputation at the first
@@ -170,12 +170,12 @@ def ipca(*all_args: List, **all_kwargs: dict):
             the first value is used for PCA-data imputation at the first
             iteration, the second for IPCA-RDI，and the third for IPCA-ADI for
             the remaining iterations after the former converged.
-            
+
          - if mode is not None:
              ncomp should correspond to the maximum number of principal
              components to be tested. The first ncomp will be ``ncomp_start``
              and the increment will be ``ncomp_step``.
-             
+
     ncomp_start: int, opt
         For incremental versions of iterative PCA (i.e. if mode is 'Juillard23'
         or 'Christiaens24'), this is the number of principal components at the
@@ -188,10 +188,10 @@ def ipca(*all_args: List, **all_kwargs: dict):
         Number of iterations for the iterative PCA.
         - if mode is None:
             total number of iterations
-            
+
         - if mode is 'Juillard23', or 'Christiaens24':
             iterations per tested ncomp.
-            
+
     strategy: str {'ADI, 'RDI', 'ARDI', 'RADI', 'RARDI''}, opt
         Whether to do iterative ADI only ('ADI'), iterative RDI only ('RDI'),
         iterative ADI and RDI together ('ARDI', i.e. with a combined PCA
@@ -201,7 +201,7 @@ def ipca(*all_args: List, **all_kwargs: dict):
         'ARDI', 'RADI' and 'RARDI'.
     thr: float or 'auto', opt
         Minimum threshold used to identify significant signals in the PCA image
-        obtained at each iteration, according to ``thr_mode``. 
+        obtained at each iteration, according to ``thr_mode``.
     thr_mode: str {'STIM', 'abs'}, opt
         How the threshold is expressed: whether based on the STIM map ('STIM')
         or expressed as absolute pixel intensity threshold ('abs'). The optimal
@@ -615,9 +615,9 @@ def _blurring_3d(array, mask_center_sz, fwhm_sz=2):
         pca_params['ncomp'] = final_ncomp[0]
         pca_params['cube'] = cube_tmp
         pca_params['cube_ref'] = cube_ref_tmp
-        
+
         res = pca(**pca_params, **rot_options)
-        
+
         frame = res[0]
         residuals_cube = res[-2]
         residuals_cube_ = res[-1]
diff --git a/src/vip_hci/invprob/andromeda.py b/src/vip_hci/invprob/andromeda.py
index 45898f626..593b94f62 100644
--- a/src/vip_hci/invprob/andromeda.py
+++ b/src/vip_hci/invprob/andromeda.py
@@ -134,7 +134,7 @@ def andromeda(*all_args: List, **all_kwargs: dict):
         by ``roa * annuli_width``.
         ``roa`` is forced to ``1`` when ``opt_method="no"`` is chosen.
         IDL parameter: ``RATIO_OPT_AREA_INPUT``
-    opt_method : {'no', 'total', 'lsq', 'robust'}, optional
+    opt_method : {'no', 'total', 'lsq', 'l1'}, optional
         Method used to balance for the flux difference that exists between the
         two subtracted annuli in an optimal way during ADI.
         IDL parameter: ``OPT_METHOD_ANG_INPUT``
diff --git a/src/vip_hci/invprob/utils_andro.py b/src/vip_hci/invprob/utils_andro.py
index 0802d9321..c9a3131b1 100644
--- a/src/vip_hci/invprob/utils_andro.py
+++ b/src/vip_hci/invprob/utils_andro.py
@@ -8,6 +8,7 @@
 
 
 import numpy as np
+from astropy.stats import median_absolute_deviation
 
 
 def robust_std(x):
@@ -32,8 +33,8 @@ def robust_std(x):
     based on ``LibAndromeda/robust_stddev.pro`` v1.1 2016/02/16
 
     """
-    median_absolute_deviation = np.median(np.abs(x - np.median(x)))
-    return median_absolute_deviation / 0.6745
+    mad = median_absolute_deviation(x)
+    return mad / 0.6745
 
 
 def idl_round(x):
@@ -84,7 +85,7 @@ def idl_where(array_expression):
       returns ``[]``, which is more "pythonic".
 
     """
-    res = np.array([i for i, e in enumerate(array_expression.flatten()) if e])
+    res = np.flatnonzero(array_expression)
     return res
 
 
@@ -285,7 +286,7 @@ def calc_psf_shift_subpix(psf, precision):
 
     """
     n = psf.shape[0]
-    psf_cube = np.zeros((precision+1, precision+1, n, n))
+    psf_cube = np.empty((precision+1, precision+1, n, n))
 
     for i_column in range(precision+1):
         decalx = i_column/precision
diff --git a/src/vip_hci/preproc/badpixremoval.py b/src/vip_hci/preproc/badpixremoval.py
index 76652a010..acede68d2 100644
--- a/src/vip_hci/preproc/badpixremoval.py
+++ b/src/vip_hci/preproc/badpixremoval.py
@@ -172,7 +172,7 @@ def frame_fix_badpix_isolated(array, bpm_mask=None, correct_only=False,
         bpm_mask = bpm_mask.astype('bool')
 
     smoothed = median_filter(frame, size, mode='mirror')
-    frame[np.where(bpm_mask)] = smoothed[np.where(bpm_mask)]
+    frame[bpm_mask] = smoothed[bpm_mask]
     array_out = frame
     count_bp = np.sum(bpm_mask)
 
@@ -1927,12 +1927,9 @@ def _reject_outliers(data, test_value, m=5., stddev=None):
                 stddev = np.std(data)
 
             med = np.median(data)
-            d = data.copy()
-            d_flat = d.flatten()
-            for i in range(d_flat.shape[0]):
-                d_flat[i] = np.abs(data.flatten()[i] - med)
+            d_flat = np.abs(data.flatten() - med)
             mdev = np.median(d_flat)
-            if max(np.max(d), np.abs(test_value-med)) > stddev:
+            if max(np.max(data), np.abs(test_value-med)) > stddev:
                 test = np.abs((test_value-med)/mdev)
                 if test < m:
                     test_result = 0
diff --git a/src/vip_hci/preproc/cosmetics.py b/src/vip_hci/preproc/cosmetics.py
index 65dcf81f7..66e5faa2f 100644
--- a/src/vip_hci/preproc/cosmetics.py
+++ b/src/vip_hci/preproc/cosmetics.py
@@ -70,6 +70,14 @@ def cube_crop_frames(
     else:
         raise TypeError("`Array` is not a cube (3d or 4d numpy.ndarray)")
 
+    if temp_fr.shape[0] == size and temp_fr.shape[1] == size:
+        if verbose:
+            print("Frame size already matches crop size. No cropping needed.")
+        if full_output:
+            ceny, cenx = frame_center(temp_fr)
+            return array, cenx, ceny
+        return array
+
     if xy is not None:
         cenx, ceny = xy
     else:
@@ -130,6 +138,11 @@ def frame_crop(array, size, xy=None, force=False, verbose=True):
     if array.ndim != 2:
         raise TypeError("`Array` is not a frame or 2d array")
 
+    if array.shape[0] == size and array.shape[1] == size:
+        if verbose:
+            print("Frame size already matches crop size. No cropping needed.")
+        return array
+
     if not xy:
         ceny, cenx = frame_center(array)
     else:
diff --git a/src/vip_hci/preproc/rescaling.py b/src/vip_hci/preproc/rescaling.py
index d338f94f4..4720ffebd 100644
--- a/src/vip_hci/preproc/rescaling.py
+++ b/src/vip_hci/preproc/rescaling.py
@@ -409,7 +409,7 @@ def cube_rescaling_wavelengths(
                 values are used to pad the end and the end values are used to
                 pad the beginning
     nproc : int, optional
-        Number of processes to use for parallel frame rescaling. Default is 1. 
+        Number of processes to use for parallel frame rescaling. Default is 1.
         Set to None to use half the available CPUs.
 
     Returns
@@ -1215,10 +1215,3 @@ def scale_fft(array, scale, ori_dim=False):
         array_resc = scaled
 
     return array_resc
-
-
-
-
-
-
-
diff --git a/src/vip_hci/psfsub/medsub.py b/src/vip_hci/psfsub/medsub.py
index 14c939590..4aeedb22c 100644
--- a/src/vip_hci/psfsub/medsub.py
+++ b/src/vip_hci/psfsub/medsub.py
@@ -572,7 +572,7 @@ def _median_subt_fr_sdi(
                     scal, ann_center, j, fwhm, delta_sep_vec[ann], nframes
                 )
                 matrix_masked = matrix[indices_left]
-                ref_psf_opt = bn.nanmedian(matrix_masked, axis=0) 
+                ref_psf_opt = bn.nanmedian(matrix_masked, axis=0)
                 curr_wv = matrix[j]
                 subtracted = curr_wv - ref_psf_opt
                 cube_res[j, yy, xx] = subtracted
diff --git a/src/vip_hci/py.typed b/src/vip_hci/py.typed
new file mode 100644
index 000000000..e69de29bb