8000 Revert the use of attributes in check_is_fitted · fatiando/verde@d87ffd7 · GitHub
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Revert the use of attributes in check_is_fitted
Rollback the changes in #217 because scikit-learn reverted the deprecation of attributes in check_is_fitted. See scikit-learn/scikit-learn#15947
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6 files changed

+7
-11
lines changed

6 files changed

+7
-11
lines changed

‎verde/base/base_classes.py

Lines changed: 2 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -54,16 +54,12 @@ class BaseGridder(BaseEstimator):
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... if self.multiplier <= 0:
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... raise ValueError('Invalid multiplier {}'
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... .format(self.multiplier))
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... # Use a trailing underscore on the mean so we could
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... # know if the gridder is already fitted before predicting
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... self.mean_ = data.mean()*self.multiplier
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... # fit should return self so that we can chain operations
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... return self
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... def predict(self, coordinates):
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... # We know the gridder has been fitted if it has the mean_
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... # attribute (or if the gridder has any attribute with a
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... # trailing underscore)
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... check_is_fitted(self)
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... # We know the gridder has been fitted if it has the mean
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... check_is_fitted(self, ['mean_'])
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... return np.ones_like(coordinates[0])*self.mean_
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>>> # Try it on some synthetic data
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>>> synthetic = vd.datasets.CheckerBoard(region=(0, 5, -10, 8))

‎verde/chain.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -118,7 +118,7 @@ def predict(self, coordinates):
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The data values predicted on the given points.
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"""
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check_is_fitted(self)
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check_is_fitted(self, ["region_"])
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result = None
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for _, step in self.steps:
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if hasattr(step, "predict"):

‎verde/scipygridder.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -131,6 +131,6 @@ def predict(self, coordinates):
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The data values interpolated on the given points.
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"""
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check_is_fitted(self)
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check_is_fitted(self, ["interpolator_"])
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easting, northing = coordinates[:2]
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return self.interpolator_((easting, northing))

‎verde/spline.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -231,7 +231,7 @@ def predict(self, coordinates):
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The data values evaluated on the given points.
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"""
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check_is_fitted(self)
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check_is_fitted(self, ["_best"])
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return self._best.predict(coordinates)
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‎verde/trend.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -149,7 +149,7 @@ def predict(self, coordinates):
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The trend values evaluated on the given points.
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"""
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check_is_fitted(self)
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check_is_fitted(self, ["coef_"])
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easting, northing = n_1d_arrays(coordinates, 2)
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shape = np.broadcast(*coordinates[:2]).shape
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data = np.zeros(easting.size, dtype=easting.dtype)

‎verde/vector.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -138,7 +138,7 @@ def predict(self, coordinates):
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:meth:`~verde.Vector.fit`.
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"""
141-
check_is_fitted(self)
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check_is_fitted(self, ["region_"])
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return tuple(comp.predict(coordinates) for comp in self.components)
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