diff --git a/TensorToolbox/import_data.py b/TensorToolbox/import_data.py
index 96fb2ce8..b0905bf0 100644
--- a/TensorToolbox/import_data.py
+++ b/TensorToolbox/import_data.py
@@ -24,7 +24,9 @@ def import_data(filename):
     
     if data_type == 'tensor':
     
-        assert False, f"{data_type} is not currently allowed"
+        shape = import_shape(fp)
+        data = import_array(fp, np.prod(shape))
+        return ttb.tensor().from_data(data, shape)
  
     elif data_type == 'sptensor':
     
@@ -35,26 +37,22 @@ def import_data(filename):
  
     elif data_type == 'matrix':         
 
-        assert False, f"{data_type} is not currently allowed"
+        shape = import_shape(fp)
+        mat = import_array(fp, np.prod(shape))
+        mat = np.reshape(mat, np.array(shape))
+        return mat
         
     elif data_type == 'ktensor':
 
         shape = import_shape(fp)
-        #print(f"shape: {shape}")
         r = import_rank(fp)
-        #print(f"rank: {r}")
-        weights = np.array(fp.readline().strip().split(' '),dtype="float")
-        #print(f"weights: {weights}")
+        weights = import_array(fp, r)
         factor_matrices = []
         for n in range(len(shape)):
              fac_type = fp.readline().strip()
-             #print(f"fac_type: {fac_type}")
              fac_shape = import_shape(fp)
-             #print(f"fac_shape: {fac_shape}")
-             fac = np.zeros(fac_shape, dtype="float")
-             for r in range(fac_shape[0]):
-                 fac[r,:] = fp.readline().strip().split(' ')
-                 #print(f"fac: {fac}")
+             fac = import_array(fp, np.prod(fac_shape))
+             fac = np.reshape(fac, np.array(fac_shape))
              factor_matrices.append(fac)
         return ttb.ktensor().from_data(weights, factor_matrices)
     
@@ -87,6 +85,10 @@ def import_sparse_array(fp, n, nz):
     vals = np.zeros((nz, 1))
     for k in range(nz):
         line = fp.readline().strip().split(' ')
-        subs[k,:] = line[:-1]
+        # 1-based indexing in file, 0-based indexing in package
+        subs[k,:] = [np.int64(i)-1 for i in line[:-1]]
         vals[k,0] = line[-1]
     return subs, vals
+
+def import_array(fp, n):
+    return np.fromfile(fp, count=n, sep=' ')
diff --git a/tests/test_import_export_data.py b/tests/test_import_export_data.py
new file mode 100644
index 00000000..db1f26b0
--- /dev/null
+++ b/tests/test_import_export_data.py
@@ -0,0 +1,108 @@
+# Copyright 2022 National Technology & Engineering Solutions of Sandia,
+# LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
+# U.S. Government retains certain rights in this software.
+
+import numpy as np
+import pytest
+import os
+import TensorToolbox as ttb
+
+@pytest.fixture()
+def sample_tensor_2way():
+    data = np.array([[1., 2., 3.], [4., 5., 6.]])
+    shape = (2, 3)
+    params = {'data':data, 'shape': shape}
+    tensorInstance = ttb.tensor().from_data(data, shape)
+    return params, tensorInstance
+
+@pytest.fixture()
+def sample_tensor_3way():
+    data = np.array([1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12.])
+    shape = (2, 3, 2)
+    params = {'data':np.reshape(data, np.array(shape), order='F'), 'shape': shape}
+    tensorInstance = ttb.tensor().from_data(data, shape)
+    return params, tensorInstance
+
+@pytest.fixture()
+def sample_tensor_4way():
+    data = np.arange(1, 82)
+    shape = (3, 3, 3, 3)
+    params = {'data':np.reshape(data, np.array(shape), order='F'), 'shape': shape}
+    tensorInstance = ttb.tensor().from_data(data, shape)
+    return params, tensorInstance
+
+@pytest.mark.indevelopment
+def test_import_data_tensor():
+    # truth data
+    T = ttb.tensor.from_data(np.ones((3,3,3)), (3,3,3))
+
+    # imported data
+    data_filename = os.path.join(os.path.dirname(__file__),'data','tensor.tns')
+    X = ttb.import_data(data_filename)
+
+    assert X.shape == (3, 3, 3)
+    assert T.isequal(X)
+ 
+@pytest.mark.indevelopment
+def test_import_data_sptensor():
+    # truth data
+    subs = np.array([[0, 0, 0],[0, 2, 2],[1, 1, 1],[1, 2, 0],[1, 2, 1],[1, 2, 2],
+                     [1, 3, 1],[2, 0, 0],[2, 0, 1],[2, 2, 0],[2, 2, 1],[2, 3, 0],
+                     [2, 3, 2],[3, 0, 0],[3, 0, 1],[3, 2, 0],[4, 0, 2],[4, 3, 2]])
+    vals = np.reshape(np.array(range(1,19)),(18,1))
+    shape = (5, 4, 3)
+    S = ttb.sptensor().from_data(subs, vals, shape)
+
+    # imported data
+    data_filename = os.path.join(os.path.dirname(__file__),'data','sptensor.tns')
+    X = ttb.import_data(data_filename)
+    
+    assert S.isequal(X)
+
+@pytest.mark.indevelopment
+def test_import_data_ktensor():
+    # truth data
+    weights = np.array([3, 2])
+    fm0 = np.array([[1., 5.], [2., 6.], [3., 7.], [4., 8.]])
+    fm1 = np.array([[ 2.,  7.], [ 3.,  8.], [ 4.,  9.], [ 5., 10.], [ 6., 11.]])
+    fm2 = np.array([[3., 6.], [4., 7.], [5., 8.]])
+    factor_matrices = [fm0, fm1, fm2]
+    K = ttb.ktensor.from_data(weights, factor_matrices)
+    
+    # imported data
+    data_filename = os.path.join(os.path.dirname(__file__),'data','ktensor.tns')
+    X = ttb.import_data(data_filename)
+    
+    assert K.isequal(X)
+
+@pytest.mark.indevelopment
+def test_import_data_array():
+    # truth data
+    M = np.array([[1., 5.], [2., 6.], [3., 7.], [4., 8.]])
+    print('\nM')
+    print(M)
+
+    # imported data
+    data_filename = os.path.join(os.path.dirname(__file__),'data','matrix.tns')
+    X = ttb.import_data(data_filename)
+    print('\nX')
+    print(X)
+    
+    assert (M == X).all()
+
+@pytest.mark.indevelopment
+def test_export_data_tensor():
+    pass
+
+@pytest.mark.indevelopment
+def test_export_data_sptensor():
+    pass
+
+@pytest.mark.indevelopment
+def test_export_data_ktensor():
+    pass
+
+@pytest.mark.indevelopment
+def test_export_data_array():
+    pass
+