Merge pull request #4867 from janezd/table-numpy-convert-to-csr

Table.numpy: Convert non-csr/csc matrices to csr

Orange/data/table.py

@@ -1751,6 +1751,8 @@ def ninstances(array):
                              % (ninstances(array), shape_1))
 
         if sp.issparse(array):
+            if not (sp.isspmatrix_csr(array) or sp.isspmatrix_csc(array)):
+                array = array.tocsr()
             array.data = np.asarray(array.data)
             has_inf = _check_inf(array.data)
         else:

Orange/data/tests/test_table.py

@@ -1,6 +1,7 @@
 import unittest
 
 import numpy as np
+import scipy.sparse as sp
 
 from Orange.data import (
     ContinuousVariable, DiscreteVariable, StringVariable,
@@ -85,6 +86,28 @@ def test_from_numpy(self):
             self.assertRaises(ValueError, func, dom, X, Y, metas[:4])
             self.assertRaises(ValueError, func, dom, X, Y[:4])
 
+    def test_from_numpy_sparse(self):
+        domain = Domain([ContinuousVariable(c) for c in "abc"])
+        x = np.arange(12).reshape(4, 3)
+
+        t = Table.from_numpy(domain, x, None, None)
+        self.assertFalse(sp.issparse(t.X))
+
+        t = Table.from_numpy(domain, sp.csr_matrix(x))
+        self.assertTrue(sp.isspmatrix_csr(t.X))
+
+        t = Table.from_numpy(domain, sp.csc_matrix(x))
+        self.assertTrue(sp.isspmatrix_csc(t.X))
+
+        t = Table.from_numpy(domain, sp.coo_matrix(x))
+        self.assertTrue(sp.isspmatrix_csr(t.X))
+
+        t = Table.from_numpy(domain, sp.lil_matrix(x))
+        self.assertTrue(sp.isspmatrix_csr(t.X))
+
+        t = Table.from_numpy(domain, sp.bsr_matrix(x))
+        self.assertTrue(sp.isspmatrix_csr(t.X))
+
 
 class TestTableFilters(unittest.TestCase):
     def setUp(self):