Improve test coverage for sympy/tensor/array

Drop untested and/or inaccessible code, add some
trivial tests.

sympy/printing/str.py

@@ -505,8 +505,7 @@ def _print_MatPow(self, expr):
     def _print_ImmutableDenseNDimArray(self, expr):
         return str(expr)
 
-    def _print_ImmutableSparseNDimArray(self, expr):
-        return str(expr)
+    _print_ImmutableSparseNDimArray = _print_ImmutableDenseNDimArray
 
     def _print_Integer(self, expr):
         return str(expr.p)

sympy/tensor/array/dense_ndim_array.py

@@ -10,9 +10,6 @@
 
 class DenseNDimArray(NDimArray):
 
-    def __new__(cls, *args, **kwargs):
-        return ImmutableDenseNDimArray(*args, **kwargs)
-
     def __getitem__(self, index):
         """
         Allows to get items from N-dim array.
@@ -104,7 +101,7 @@ def reshape(self, *newshape):
         """
         new_total_size = functools.reduce(lambda x, y: x*y, newshape)
         if new_total_size != self._loop_size:
-            raise ValueError("Invalid reshape parameters " + newshape)
+            raise ValueError("Invalid reshape parameters " + str(newshape))
 
         # there is no `.func` as this class does not subtype `Basic`:
         return type(self)(self._array, newshape)

sympy/tensor/array/ndim_array.py

@@ -55,9 +55,6 @@ class NDimArray(object):
     [[-3, -3], [-3, -3]]
 
     """
-    def __new__(cls, *args, **kwargs):
-        from sympy.tensor.array import ImmutableDenseNDimArray
-        return ImmutableDenseNDimArray(*args, **kwargs)
 
     def _parse_index(self, index):
 
@@ -207,23 +204,6 @@ def f(sh, shape_left, i, j):
 
         return f(self._loop_size, self.shape, 0, self._loop_size)
 
-        out_str = ''
-
-        # forming output string
-        for i, el in enumerate(self):
-
-            out_str += str(el) + '  '
-            chidx = i+1
-            for sh in reversed(self.shape):
-                if chidx % sh == 0:
-                    out_str += '\n'
-                    chidx //= sh
-
-        return out_str
-
-    def __repr__(self):
-        return self.__str__()
-
     def tolist(self):
         """
         Conveting MutableDenseNDimArray to one-dim list

sympy/tensor/array/sparse_ndim_array.py

@@ -8,9 +8,6 @@
 
 class SparseNDimArray(NDimArray):
 
-    def __new__(cls, *args, **kwargs):
-        return ImmutableSparseNDimArray(*args, **kwargs)
-
     def __getitem__(self, index):
         """
         Get an element from a sparse N-dim array.
@@ -77,13 +74,6 @@ def iterator():
                 yield self[i]
         return iterator()
 
-    def reshape(self, *newshape):
-        new_total_size = functools.reduce(lambda x, y: x*y, newshape)
-        if new_total_size != self._loop_size:
-            raise ValueError("Invalid reshape parameters " + newshape)
-
-        return type(self)(*(newshape + (self._array,)))
-
 
 class ImmutableSparseNDimArray(SparseNDimArray, Expr):
 

sympy/tensor/array/tests/test_immutable_ndim_array.py

@@ -69,6 +69,8 @@ def test_reshape():
     assert array.rank() == 3
     assert len(array) == 50
 
+    pytest.raises(ValueError, lambda: array.reshape(1, 1))
+
 
 def test_iterator():
     array = ImmutableDenseNDimArray(range(4), (2, 2))
@@ -145,6 +147,9 @@ def test_ndim_array_converting():
     matrix = sparse_array.tomatrix()
     assert(isinstance(matrix, SparseMatrix))
 
+    pytest.raises(ValueError,
+                  lambda: ImmutableDenseNDimArray([1]*6, (2, 2, 2)).tomatrix())
+
     for i in range(len(sparse_array)):
         assert sparse_array[i] == matrix[i]
     assert matrix.shape == sparse_array.shape

sympy/tensor/array/tests/test_mutable_ndim_array.py

@@ -1,5 +1,7 @@
 from copy import copy
 
+import pytest
+
 from sympy.tensor.array.dense_ndim_array import MutableDenseNDimArray
 from sympy import Symbol, Rational, SparseMatrix
 from sympy.matrices import Matrix
@@ -145,6 +147,9 @@ def test_ndim_array_converting():
     matrix = sparse_array.tomatrix()
     assert(isinstance(matrix, SparseMatrix))
 
+    pytest.raises(ValueError,
+                  lambda: MutableSparseNDimArray([1]*6, (2, 2, 2)).tomatrix())
+
     for i in range(len(sparse_array)):
         assert sparse_array[i] == matrix[i]
     assert matrix.shape == sparse_array.shape