fixed all tests

basaks · Apr 4, 2024 · 6b80d69 · 6b80d69
1 parent c3abef6
commit 6b80d69
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Showing 3 changed files with 8 additions and 7 deletions.
diff --git a/tests/test_models.py b/tests/test_models.py
@@ -7,7 +7,7 @@
 from uncoverml.models import (apply_masked,
                               apply_multiple_masked,
                               modelmaps)
-from uncoverml.optimise.models import transformed_modelmaps
+from uncoverml.optimise.models import transformed_modelmaps, no_test_support_classifiers
 
 models = {**transformed_modelmaps, **modelmaps}
 
@@ -101,7 +101,9 @@ def test_trasnsformed_model_attr(get_transformed_model):
                                       'multicubist',
                                       'decisiontree',
                                       'extratree',
-                                      'catboost'
+                                      'catboost',
+                                      'svrmulti',
+                                     * list(no_test_support_classifiers.keys())
                                      ]])
 def models_supported(request):
     return request.param

diff --git a/uncoverml/image.py b/uncoverml/image.py
@@ -3,7 +3,7 @@
 import logging
 
 from affine import Affine
-from uncoverml.geoio import RasterioImageSource
+# from uncoverml.geoio import RasterioImageSource
 
 log = logging.getLogger(__name__)
 
@@ -29,9 +29,9 @@ def construct_splits(npixels, nchunks, overlap=0):
 
 
 class Image:
-    def __init__(self, source: RasterioImageSource,
+    def __init__(self, source,
                  chunk_idx=0, nchunks=1, overlap=0,
-                 t_source: Optional[RasterioImageSource] = None,
+                 t_source=None,
                  ):
         assert chunk_idx >= 0 and chunk_idx < nchunks
 

diff --git a/uncoverml/optimise/models.py b/uncoverml/optimise/models.py
@@ -285,7 +285,6 @@ def __init__(self, fit_intercept=True, normalize=False, copy_X=True,
             target_transform = transforms.transforms[target_transform]()
         self.target_transform = target_transform
         super(TransformedOLS, self).__init__(fit_intercept=fit_intercept,
-                                             normalize=normalize,
                                              copy_X=copy_X,
                                              n_jobs=n_jobs)
 
@@ -308,7 +307,7 @@ def __init__(self, alpha=1.0, l1_ratio=0.5, fit_intercept=True,
 
         super(TransformedElasticNet, self).__init__(
             alpha=alpha, l1_ratio=l1_ratio, fit_intercept=fit_intercept,
-            normalize=normalize, precompute=precompute, max_iter=max_iter,
+            precompute=precompute, max_iter=max_iter,
             copy_X=copy_X, tol=tol, warm_start=warm_start, positive=positive,
             random_state=random_state, selection=selection
             )