Linting

doc/source/background.md

@@ -130,4 +130,4 @@ And finally:
 - **Reproducibility:** all code should be version-controlled and release-based, to ensure consistency of dependent
   packages and works;
 
-- **Open-source:** all code should be accessible and re-usable to anyone in the community, for transparency and open governance.
+- **Open-source:** all code should be accessible and reusable to anyone in the community, for transparency and open governance.

doc/source/code/comparison_plot_local_hypsometric_interpolation.py

@@ -1,4 +1,5 @@
 """Plot an example of local hypsometric interpolation at Scott Turnerbreen, Svalbard."""
+
 import geoutils as gu
 import matplotlib.pyplot as plt
 import numpy as np

doc/source/code/comparison_plot_regional_hypsometric_interpolation.py

@@ -1,4 +1,5 @@
 """Plot an example of regional hypsometric interpolation in central Svalbard."""
+
 import geoutils as gu
 import matplotlib.pyplot as plt
 import numpy as np

doc/source/code/comparison_plot_spatial_interpolation.py

@@ -1,4 +1,5 @@
 """Plot an example of spatial interpolation of randomly generated errors."""
+
 import geoutils as gu
 import matplotlib.pyplot as plt
 import numpy as np

doc/source/code/intricacies_datatypes.py

@@ -1,4 +1,5 @@
 """Plot example of elevation data types for guide page."""
+
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np

doc/source/code/robust_mean_std.py

@@ -1,4 +1,5 @@
 """Plot example of NMAD/median as robust estimators for guide page."""
+
 import matplotlib.pyplot as plt
 import numpy as np
 

doc/source/code/robust_vario.py

@@ -1,4 +1,5 @@
 """Plot example of Dowd variogram as robust estimator for guide page."""
+
 import matplotlib.pyplot as plt
 import numpy as np
 from skgstat import OrdinaryKriging, Variogram

doc/source/code/spatialstats_heterosc_slope.py

@@ -1,4 +1,5 @@
 """Code example for spatial statistics"""
+
 import geoutils as gu
 import numpy as np
 

doc/source/code/spatialstats_standardizing.py

@@ -1,4 +1,5 @@
 """Documentation plot illustrating standardization of a distribution"""
+
 import matplotlib.pyplot as plt
 import numpy as np
 

doc/source/code/spatialstats_stationarity_assumption.py

@@ -1,4 +1,5 @@
 """Documentation plot illustrating stationarity of mean and variance"""
+
 import matplotlib.pyplot as plt
 import numpy as np
 

doc/source/code/spatialstats_variogram_covariance.py

@@ -1,4 +1,5 @@
 """Documentation plot illustrating the link between variogram and covariance"""
+
 import matplotlib.pyplot as plt
 import numpy as np
 from skgstat.models import exponential

doc/source/sphinxext.py

@@ -1,4 +1,6 @@
 """Functions for documentation configuration only, importable by sphinx"""
+
+
 # To reset resolution setting for each sphinx-gallery example
 def reset_mpl(gallery_conf, fname):
     # To get a good resolution for displayed figures

examples/advanced/plot_blockwise_coreg.py

@@ -16,6 +16,7 @@
 5. Warp the DEM to apply the X/Y/Z shifts.
 
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 2

examples/advanced/plot_deramp.py

@@ -7,6 +7,7 @@
 
 See also the :ref:`deramp` section in feature pages.
 """
+
 import geoutils as gu
 import numpy as np
 

examples/advanced/plot_heterosc_estimation_modelling.py

@@ -19,6 +19,7 @@
 
 **Reference:** `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 8

examples/advanced/plot_norm_regional_hypso.py

@@ -27,6 +27,7 @@
 
 The consequence is a much more accurate interpolation approach that can be used in a multitude of glacierized settings.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 2

examples/advanced/plot_slope_methods.py

@@ -9,6 +9,7 @@
 
 **References:** `Horn (1981) <https://ieeexplore.ieee.org/document/1456186>`_, `Zevenbergen and Thorne (1987) <http://dx.doi.org/10.1002/esp.3290120107>`_.
 """
+
 import matplotlib.pyplot as plt
 import numpy as np
 

examples/advanced/plot_standardization.py

@@ -13,6 +13,7 @@
 
 **Reference**: `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 4

examples/advanced/plot_variogram_estimation_modelling.py

@@ -20,6 +20,7 @@
 
 **References:** `Rolstad et al. (2009) <http://dx.doi.org/10.3189/002214309789470950>`_, `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 6

examples/basic/plot_dem_subtraction.py

@@ -10,6 +10,7 @@
 Before DEMs can be compared, they need to be reprojected to the same grid and have the same 3D CRSs. The :func:`~xdem.DEM.reproject` and :func:`~xdem.DEM.to_vcrs` methods are used for this.
 
 """
+
 import geoutils as gu
 
 import xdem

examples/basic/plot_icp_coregistration.py

@@ -10,6 +10,7 @@
 
 **References**: `Besl and McKay (1992) <https://doi.org/10.1117/12.57955>`_.
 """
+
 # sphinx_gallery_thumbnail_number = 2
 import matplotlib.pyplot as plt
 import numpy as np

examples/basic/plot_infer_heterosc.py

@@ -9,6 +9,7 @@
 
 **Reference:** `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 1

examples/basic/plot_infer_spatial_correlation.py

@@ -8,6 +8,7 @@
 
 **References:** `Rolstad et al. (2009) <http://dx.doi.org/10.3189/002214309789470950>`_, `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 
 # sphinx_gallery_thumbnail_number = 1

examples/basic/plot_nuth_kaab.py

@@ -10,6 +10,7 @@
 
 **Reference:** `Nuth and Kääb (2011) <https:https://doi.org/10.5194/tc-5-271-2011>`_.
 """
+
 import geoutils as gu
 import numpy as np
 

examples/basic/plot_spatial_error_propagation.py

@@ -9,6 +9,7 @@
 
 **References:** `Rolstad et al. (2009) <http://dx.doi.org/10.3189/002214309789470950>`_, `Hugonnet et al. (2022) <https://doi.org/10.1109/jstars.2022.3188922>`_.
 """
+
 import geoutils as gu
 import matplotlib.pyplot as plt
 

examples/basic/plot_terrain_attributes.py

@@ -12,6 +12,7 @@
 `Riley et al. (1999) <http://download.osgeo.org/qgis/doc/reference-docs/Terrain_Ruggedness_Index.pdf>`_ (terrain
 ruggedness index), `Jenness (2004) <https://doi.org/10.2193/0091-7648(2004)032%5B0829:CLSAFD%5D2.0.CO;2>`_ (rugosity).
 """
+
 # sphinx_gallery_thumbnail_number = 1
 import matplotlib.pyplot as plt
 

setup.py

@@ -1,4 +1,5 @@
 """This file now only serves for backward-compatibility for routines explicitly calling python setup.py"""
+
 from setuptools import setup
 
 setup()

tests/test_coreg/test_affine.py

@@ -1,4 +1,5 @@
 """Functions to test the affine coregistrations."""
+
 from __future__ import annotations
 
 import warnings
@@ -409,7 +410,7 @@ def test_coreg_rigid__synthetic(self, fit_args, shifts_rotations, coreg_method)
         matrix[:3, 3] = shifts
 
         # Pass a centroid
-        centroid = [ref.bounds.left, ref.bounds.bottom, np.nanmean(ref)]
+        centroid = (ref.bounds.left, ref.bounds.bottom, np.nanmean(ref))
         ref_shifted_rotated = coreg.apply_matrix(ref, matrix=matrix, centroid=centroid)
 
         # Convert to point cloud if input was point cloud

tests/test_coreg/test_base.py

@@ -49,7 +49,7 @@ def assert_coreg_meta_equal(input1: Any, input2: Any) -> bool:
     """Short test function to check equality of coreg dictionary values."""
 
     # Different equality check based on input: number, callable, array, dataframe
-    if type(input1) != type(input2):
+    if not isinstance(input1, type(input2)):
         return False
     elif isinstance(input1, (str, float, int, np.floating, np.integer, tuple, list)) or callable(input1):
         return input1 == input2
@@ -466,12 +466,16 @@ def test_fit_and_apply__pipeline(self) -> None:
         assert aligned_and.raster_equal(aligned_then, warn_failure_reason=True)
         assert list(coreg_fit_and_apply.pipeline[0].meta.keys()) == list(coreg_fit_then_apply.pipeline[0].meta.keys())
         assert all(
-            assert_coreg_meta_equal(coreg_fit_and_apply.pipeline[0].meta[k], coreg_fit_then_apply.pipeline[0].meta[k])
+            assert_coreg_meta_equal(
+                coreg_fit_and_apply.pipeline[0].meta[k], coreg_fit_then_apply.pipeline[0].meta[k]  # type: ignore
+            )
             for k in coreg_fit_and_apply.pipeline[0].meta.keys()
         )
         assert list(coreg_fit_and_apply.pipeline[1].meta.keys()) == list(coreg_fit_then_apply.pipeline[1].meta.keys())
         assert all(
-            assert_coreg_meta_equal(coreg_fit_and_apply.pipeline[1].meta[k], coreg_fit_then_apply.pipeline[1].meta[k])
+            assert_coreg_meta_equal(
+                coreg_fit_and_apply.pipeline[1].meta[k], coreg_fit_then_apply.pipeline[1].meta[k]  # type: ignore
+            )
             for k in coreg_fit_and_apply.pipeline[1].meta.keys()
         )
 
@@ -702,9 +706,7 @@ def test_pipeline_combinations__biasvar(
         """Test pipelines with all combinations of coregistration subclasses with bias variables"""
 
         # Create a pipeline from one affine and one biascorr methods
-        pipeline = coreg.CoregPipeline([coreg1(), coreg.BiasCorr(**coreg2_init_kwargs)])
-        print(pipeline.pipeline[0].meta["inputs"]["random"]["subsample"])
-        print(pipeline.pipeline[1].meta["inputs"]["random"]["subsample"])
+        pipeline = coreg.CoregPipeline([coreg1(), coreg.BiasCorr(**coreg2_init_kwargs)])  # type: ignore
         bias_vars = {"slope": xdem.terrain.slope(self.ref), "aspect": xdem.terrain.aspect(self.ref)}
         pipeline.fit(**self.fit_params, bias_vars=bias_vars, subsample=5000, random_state=42)
 

tests/test_coreg/test_biascorr.py

@@ -1,4 +1,5 @@
 """Tests for the biascorr module (non-rigid coregistrations)."""
+
 from __future__ import annotations
 
 import re

tests/test_coreg/test_workflows.py

@@ -1,4 +1,5 @@
 """Functions to test the coregistration workflows."""
+
 from __future__ import annotations
 
 import os

tests/test_dem.py

@@ -1,4 +1,5 @@
 """ Functions to test the DEM tools."""
+
 from __future__ import annotations
 
 import os

tests/test_demcollection.py

@@ -1,4 +1,5 @@
 """Functions to test the DEM collection tools."""
+
 import datetime
 import warnings
 

tests/test_doc.py

@@ -1,4 +1,5 @@
 """Functions to test the documentation."""
+
 import logging
 import os
 import platform

tests/test_examples.py

@@ -1,4 +1,5 @@
 """Functions to test the example data."""
+
 from __future__ import annotations
 
 import geoutils as gu

tests/test_filters.py

@@ -1,4 +1,5 @@
 """Functions to test the filtering tools."""
+
 from __future__ import annotations
 
 import geoutils as gu

tests/test_fit.py

@@ -1,6 +1,7 @@
 """
 Functions to test the fitting tools.
 """
+
 import platform
 import warnings
 

tests/test_misc.py

@@ -1,4 +1,5 @@
 """Test the xdem.misc functions."""
+
 from __future__ import annotations
 
 import os

tests/test_spatialstats.py

@@ -1,4 +1,5 @@
 """Functions to test the spatial statistics."""
+
 from __future__ import annotations
 
 import os

tests/test_terrain.py

@@ -377,7 +377,7 @@ def test_raster_argument(self) -> None:
 
         assert slope != aspect
 
-        assert type(slope) == type(aspect)
+        assert isinstance(slope, type(aspect))
         assert all(isinstance(r, gu.Raster) for r in (aspect, slope, self.dem))
 
         assert slope.transform == self.dem.transform == aspect.transform

tests/test_vcrs.py

@@ -1,4 +1,5 @@
 """Tests for vertical CRS transformation tools."""
+
 from __future__ import annotations
 
 import pathlib

xdem/coreg/affine.py

@@ -205,8 +205,8 @@ def sub_dh_interpolator(shift_x: float, shift_y: float) -> NDArrayf:
     else:
 
         # Identify which dataset is point or raster
-        pts_elev = ref_elev if isinstance(ref_elev, gpd.GeoDataFrame) else tba_elev
-        rst_elev = ref_elev if not isinstance(ref_elev, gpd.GeoDataFrame) else tba_elev
+        pts_elev: gpd.GeoDataFrame = ref_elev if isinstance(ref_elev, gpd.GeoDataFrame) else tba_elev
+        rst_elev: NDArrayf = ref_elev if not isinstance(ref_elev, gpd.GeoDataFrame) else tba_elev
         # Check which input is reference, to compute the dh always in the same direction (ref minus tba) further below
         ref = "point" if isinstance(ref_elev, gpd.GeoDataFrame) else "raster"