Merge pull request #625 from markotoplak/fix-warn

[ENH] Implement equivalence of (some) spectral tranformations

conda/meta.yaml

@@ -24,15 +24,15 @@ requirements:
   run:
     - python >=3.8
     - numpy >=1.20.0
-    - orange3 >=3.32.0
-    - orange-canvas-core >=0.1.24
-    - orange-widget-base >=4.16.1
-    - scipy >=1.4.0
+    - orange3 >=3.34.0
+    - orange-canvas-core >=0.1.28
+    - orange-widget-base >=4.19.0
+    - scipy >=1.9.0
     - scikit-learn>=1.0.1
     - spectral >=0.22.3,!=0.23
     - serverfiles >=0.2
-    - AnyQt >=0.0.6
-    - pyqtgraph >=0.11.1,!=0.12.4
+    - AnyQt >=0.1.0
+    - pyqtgraph >=0.12.2,!=0.12.4
     - colorcet
     - h5py
     - extranormal3 >=0.0.3

orangecontrib/spectroscopy/preprocess/__init__.py

@@ -29,7 +29,7 @@
 
 
 class PCADenoisingFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _PCAReconstructCommon(CommonDomain):
@@ -79,7 +79,7 @@ def __call__(self, data):
 
 
 class GaussianFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _GaussianCommon(CommonDomainOrderUnknowns):
@@ -131,7 +131,7 @@ def __call__(self, data):
 
 
 class SavitzkyGolayFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _SavitzkyGolayCommon(CommonDomainOrderUnknowns):
@@ -147,6 +147,15 @@ def transformed(self, X, wavenumbers):
                              polyorder=self.polyorder,
                              deriv=self.deriv, mode="nearest")
 
+    def __eq__(self, other):
+        return super().__eq__(other) \
+               and self.window == other.window \
+               and self.polyorder == other.polyorder \
+               and self.deriv == other.deriv
+
+    def __hash__(self):
+        return hash((super().__hash__(), self.window, self.polyorder, self.deriv))
+
 
 class SavitzkyGolayFiltering(Preprocess):
     """
@@ -169,7 +178,7 @@ def __call__(self, data):
 
 
 class RubberbandBaselineFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _RubberbandBaselineCommon(CommonDomainOrder):
@@ -233,7 +242,7 @@ def __call__(self, data):
 
 
 class LinearBaselineFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _LinearBaselineCommon(CommonDomainOrderUnknowns):
@@ -276,7 +285,7 @@ def __call__(self, data):
 
 
 class NormalizeFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _NormalizeCommon(CommonDomain):
@@ -333,6 +342,18 @@ def transformed(self, data):
                 replace_infs(data.X)
         return data.X
 
+    def __eq__(self, other):
+        return super().__eq__(other) \
+               and self.method == other.method \
+               and self.lower == other.lower \
+               and self.upper == other.upper \
+               and self.int_method == other.int_method \
+               and self.attr == other.attr
+
+    def __hash__(self):
+        return hash((super().__hash__(), self.method, self.lower,
+                     self.upper, self.int_method, self.attr))
+
 
 class Normalize(Preprocess):
     # Normalization methods
@@ -412,7 +433,7 @@ def features_with_interpolation(points, kind="linear", domain=None, handle_nans=
 
 
 class InterpolatedFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _InterpolateCommon:
@@ -449,6 +470,18 @@ def __call__(self, data):
                 interpfn = interp1d_wo_unknowns_scipy
         return interpfn(x, ys, self.points, kind=self.kind)
 
+    def __eq__(self, other):
+        return type(self) is type(other) \
+               and np.all(self.points == other.points) \
+               and self.kind == other.kind \
+               and self.domain == other.domain \
+               and self.handle_nans == other.handle_nans \
+               and self.interpfn == other.interpfn
+
+    def __hash__(self):
+        return hash((type(self), tuple(self.points[:5]), self.kind,
+                     self.domain, self.handle_nans, self.interpfn))
+
 
 class Interpolate(Preprocess):
     """
@@ -512,7 +545,7 @@ def __call__(self, data):
 
 ######################################### XAS normalization ##########
 class XASnormalizationFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _XASnormalizationCommon(CommonDomainOrderUnknowns):
@@ -574,7 +607,7 @@ class NoEdgejumpProvidedException(PreprocessException):
 
 
 class ExtractEXAFSFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class EdgeJumpException(PreprocessException):
@@ -698,7 +731,7 @@ def __call__(self, data):
 
 
 class CurveShiftFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _CurveShiftCommon(CommonDomain):
@@ -726,7 +759,7 @@ def __call__(self, data):
 
 
 class DespikeFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _DespikeCommon(CommonDomainOrderUnknowns):
@@ -804,7 +837,7 @@ def __call__(self, data):
 
 
 class SpSubtractFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _SpSubtractCommon(CommonDomainRef):

orangecontrib/spectroscopy/preprocess/als/__init__.py

@@ -11,7 +11,7 @@
 
 
 class ALSFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class ALSCommon(CommonDomainOrderUnknowns):
@@ -54,7 +54,7 @@ def __call__(self, data):
 
 
 class ARPLSFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class ARPLSCommon(CommonDomainOrderUnknowns):
@@ -100,7 +100,7 @@ def __call__(self, data):
 
 
 class AIRPLSFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class AIRPLSCommon(CommonDomainOrderUnknowns):

orangecontrib/spectroscopy/preprocess/emsc.py

@@ -54,11 +54,11 @@ def weighted_wavenumbers(weights, wavenumbers):
 
 
 class EMSCFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class EMSCModel(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _EMSC(CommonDomainOrderUnknowns):

orangecontrib/spectroscopy/preprocess/integrate.py

@@ -72,17 +72,25 @@ def compute(self, data, common):
         x_s, y_s = self.extract_data(data, common)
         return self.compute_integral(x_s, y_s)
 
+    def __eq__(self, other):
+        return super().__eq__(other) \
+               and self.limits == other.limits
+
+    def __hash__(self):
+        return hash((super().__hash__(), tuple(self.limits)))
+
 
 class IntegrateFeatureEdgeBaseline(IntegrateFeature):
     """ A linear edge-to-edge baseline subtraction. """
 
     name = "Integral from baseline"
+    InheritEq = True
 
     @staticmethod
     def parameters():
         return (("Low limit", "Low limit for integration (inclusive)"),
                 ("High limit", "High limit for integration (inclusive)"),
-            )
+                )
 
     def compute_baseline(self, x, y):
         if np.any(np.isnan(y)):
@@ -105,6 +113,7 @@ def compute_draw_info(self, x, ys):
 class IntegrateFeatureSeparateBaseline(IntegrateFeature):
 
     name = "Integral from separate baseline"
+    InheritEq = True
 
     @staticmethod
     def parameters():
@@ -148,6 +157,7 @@ class IntegrateFeatureSimple(IntegrateFeatureEdgeBaseline):
     """ A simple y=0 integration on the provided data window. """
 
     name = "Integral from 0"
+    InheritEq = True
 
     def compute_baseline(self, x_s, y_s):
         return np.zeros(y_s.shape)
@@ -157,12 +167,13 @@ class IntegrateFeaturePeakEdgeBaseline(IntegrateFeature):
     """ The maximum baseline-subtracted peak height in the provided window. """
 
     name = "Peak from baseline"
+    InheritEq = True
 
     @staticmethod
     def parameters():
         return (("Low limit", "Low limit for integration (inclusive)"),
                 ("High limit", "High limit for integration (inclusive)"),
-            )
+                )
 
     def compute_baseline(self, x, y):
         return edge_baseline(x, y)
@@ -186,6 +197,7 @@ class IntegrateFeaturePeakSimple(IntegrateFeaturePeakEdgeBaseline):
     """ The maximum peak height in the provided data window. """
 
     name = "Peak from 0"
+    InheritEq = True
 
     def compute_baseline(self, x_s, y_s):
         return np.zeros(y_s.shape)
@@ -195,12 +207,13 @@ class IntegrateFeaturePeakXEdgeBaseline(IntegrateFeature):
     """ The X-value of the maximum baseline-subtracted peak height in the provided window. """
 
     name = "X-value of maximum from baseline"
+    InheritEq = True
 
     @staticmethod
     def parameters():
         return (("Low limit", "Low limit for integration (inclusive)"),
                 ("High limit", "High limit for integration (inclusive)"),
-            )
+                )
 
     def compute_baseline(self, x, y):
         return edge_baseline(x, y)
@@ -231,6 +244,7 @@ class IntegrateFeaturePeakXSimple(IntegrateFeaturePeakXEdgeBaseline):
     """ The X-value of the maximum peak height in the provided data window. """
 
     name = "X-value of maximum from 0"
+    InheritEq = True
 
     def compute_baseline(self, x_s, y_s):
         return np.zeros(y_s.shape)
@@ -240,11 +254,12 @@ class IntegrateFeatureAtPeak(IntegrateFeature):
     """ Find the closest x and return the value there. """
 
     name = "Closest value"
+    InheritEq = True
 
     @staticmethod
     def parameters():
         return (("Closest to", "Nearest value"),
-            )
+                )
 
     def extract_data(self, data, common):
         data, x, x_sorter = common
@@ -275,6 +290,14 @@ def transformed(self, data):
         x_sorter = np.argsort(x)
         return data, x, x_sorter
 
+    def __eq__(self, other):
+        # pylint: disable=useless-parent-delegation
+        return super().__eq__(other)
+
+    def __hash__(self):
+        # pylint: disable=useless-parent-delegation
+        return super().__hash__()
+
 
 class Integrate(Preprocess):
 

orangecontrib/spectroscopy/preprocess/me_emsc.py

@@ -88,11 +88,11 @@ def cal_ncomp(reference, wavenumbers,  explainedVarLim, alpha0, gamma):
 
 
 class ME_EMSCFeature(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class ME_EMSCModel(SelectColumn):
-    pass
+    InheritEq = True
 
 
 class _ME_EMSC(CommonDomainOrderUnknowns):