def testModel(self):
"""
First create a GaussianKernel object, then send it back and make sure we get
the right double value.
"""
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
build_model=True)
output2 = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
model_in=output['model_out'])
self.assertEqual(output2['model_bw_out'], 20.0)
def testArraylikeUmatrix(self):
"""
Test that we can pass an arraylike unsigned matrix.
"""
x = [[1, 2, 3, 4, 5],
[6, 7, 8, 9, 10],
[11, 12, 13, 14, 15]]
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
umatrix_in=x)
self.assertEqual(output['umatrix_out'].shape[0], 3)
self.assertEqual(output['umatrix_out'].shape[1], 4)
self.assertEqual(output['umatrix_out'].dtype, np.long)
self.assertEqual(output['umatrix_out'][0, 0], 1)
self.assertEqual(output['umatrix_out'][0, 1], 2)
self.assertEqual(output['umatrix_out'][0, 2], 6)
self.assertEqual(output['umatrix_out'][0, 3], 4)
self.assertEqual(output['umatrix_out'][1, 0], 6)
self.assertEqual(output['umatrix_out'][1, 1], 7)
self.assertEqual(output['umatrix_out'][1, 2], 16)
self.assertEqual(output['umatrix_out'][1, 3], 9)
self.assertEqual(output['umatrix_out'][2, 0], 11)
self.assertEqual(output['umatrix_out'][2, 1], 12)
self.assertEqual(output['umatrix_out'][2, 2], 26)
self.assertEqual(output['umatrix_out'][2, 3], 14)
def testRunBindingWrongInt(self):
"""
If we give the wrong int, we should get wrong results.
"""
output = test_python_binding(string_in='hello',
int_in=15,
double_in=4.0,
flag1=True)
self.assertNotEqual(output['int_out'], 13)
def testRunBindingWrongDouble(self):
"""
If we give the wrong double, we should get wrong results.
"""
output = test_python_binding(string_in='hello',
int_in=12,
double_in=2.0,
flag1=True)
self.assertNotEqual(output['double_out'], 5.0)
def testRunBindingWrongString(self):
"""
If we give the wrong string, we should get wrong results.
"""
output = test_python_binding(string_in='goodbye',
int_in=12,
double_in=4.0,
flag1=True)
self.assertNotEqual(output['string_out'], 'hello2')
def testRunBindingNoFlag(self):
"""
If we forget the mandatory flag, we should get wrong results.
"""
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0)
self.assertNotEqual(output['string_out'], 'hello2')
self.assertNotEqual(output['int_out'], 13)
self.assertNotEqual(output['double_out'], 5.0)
def testRunBadFlag(self):
"""
If we give the second flag, this should fail.
"""
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
flag2=True)
self.assertNotEqual(output['string_out'], 'hello2')
self.assertNotEqual(output['int_out'], 13)
self.assertNotEqual(output['double_out'], 5.0)
def testIntVector(self):
"""
Test that we can pass a vector of ints and get back that same vector but
with the last element removed.
"""
x = [1, 2, 3, 4, 5]
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
vector_in=x)
self.assertEqual(output['vector_out'], [1, 2, 3, 4])
def testRunBindingCorrectly(self):
"""
Test that when we run the binding correctly (with correct input parameters),
we get the expected output.
"""
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True)
self.assertEqual(output['string_out'], 'hello2')
self.assertEqual(output['int_out'], 13)
self.assertEqual(output['double_out'], 5.0)
def testStringVector(self):
"""
Test that we can pass a vector of strings and get back that same vector but
with the last element removed.
"""
x = ['one', 'two', 'three', 'four', 'five']
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
str_vector_in=x)
self.assertEqual(output['str_vector_out'],
['one', 'two', 'three', 'four'])
def testUcol(self):
"""
Test an unsigned column vector input parameter.
"""
x = np.random.randint(0, high=500, size=100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
ucol_in=x)
self.assertEqual(output['ucol_out'].shape[0], 100)
self.assertEqual(output['ucol_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['ucol_out'][i], x[i] * 2)
def testOneDimensionMatrixAndInfoPandasForceCopy(self):
"""
Test that we can pass a one dimension matrix with some categorical features.
"""
x = pd.DataFrame(np.random.rand(10))
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_and_info_in=x[0],
copy_all_inputs=True)
self.assertEqual(output['matrix_and_info_out'].shape[0], 10)
for j in range(10):
self.assertEqual(output['matrix_and_info_out'][j, 0], x[0][j] * 2)
def testUcol(self):
"""
Test an unsigned column vector input parameter.
"""
x = np.random.randint(0, high=500, size=100)
z = copy.deepcopy(x)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
ucol_in=z)
self.assertEqual(output['ucol_out'].shape[0], 100)
self.assertEqual(output['ucol_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['ucol_out'][i], x[i] * 2)
def testOneDimensionMatrixAndInfoPandas(self):
"""
Test that we can pass a one dimension matrix with some categorical features.
"""
x = pd.DataFrame(np.random.rand(10))
z = copy.copy(x)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_and_info_in=z[0])
self.assertEqual(output['matrix_and_info_out'].shape[0], 10)
for i in range(10):
self.assertEqual(output['matrix_and_info_out'][i, 0], z[0][i] * 2)
def testRow(self):
"""
Test a row vector input parameter.
"""
x = np.random.rand(100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
row_in=x)
self.assertEqual(output['row_out'].shape[0], 100)
self.assertEqual(output['row_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['row_out'][i], x[i] * 2)
def testTwoDimensionUcolForceCopy(self):
"""
Test that we pass Two Dimension unsigned column vector input parameter.
"""
x = np.random.randint(0, high=500, size=[100, 1])
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
ucol_in=x,
copy_all_inputs=True)
self.assertEqual(output['ucol_out'].shape[0], 100)
self.assertEqual(output['ucol_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['ucol_out'][i], x[i] * 2)
def testRow(self):
"""
Test a row vector input parameter.
"""
x = np.random.rand(100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
row_in=x)
self.assertEqual(output['row_out'].shape[0], 100)
self.assertEqual(output['row_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['row_out'][i], x[i] * 2)
def testUrow(self):
"""
Test an unsigned row vector input parameter.
"""
x = np.random.randint(0, high=500, size=100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
urow_in=x)
self.assertEqual(output['urow_out'].shape[0], 100)
self.assertEqual(output['urow_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['urow_out'][i], x[i] * 2)
def testOneDimensionNumpymatrixForceCopy(self):
"""
Test that we can pass one dimension matrix from matrix_in
"""
x = np.random.rand(100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
smatrix_in=x,
copy_all_inputs=True)
self.assertEqual(output['smatrix_out'].shape[0], 100)
self.assertEqual(output['smatrix_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['smatrix_out'][i, 0], x[i] * 2)
def testPandasSeriesMatrix(self):
"""
Test that we can pass pandas.Series as input parameter.
"""
x = pd.Series(np.random.rand(100))
z = copy.copy(x)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
smatrix_in=z)
self.assertEqual(output['smatrix_out'].shape[0], 100)
self.assertEqual(output['smatrix_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['smatrix_out'][i,0], z.iloc[i] * 2)
def testPandasSeriesUMatrixForceCopy(self):
"""
Test that we can pass pandas.Series as input parameter.
"""
x = pd.Series(np.random.randint(0, high=500, size=100))
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
s_umatrix_in=x,
copy_all_inputs=True)
self.assertEqual(output['s_umatrix_out'].shape[0], 100)
self.assertEqual(output['s_umatrix_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['s_umatrix_out'][i, 0], x.iloc[i] * 2)
def testPandasSeriesForceCopy(self):
"""
Test a Pandas Series input paramter
"""
x = pd.Series(np.random.rand(100))
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
col_in=x,
copy_all_inputs=True)
self.assertEqual(output['col_out'].shape[0], 100)
self.assertEqual(output['col_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['col_out'][i], x[i] * 2)
def testTwoDimensionUrowForceCopy(self):
"""
Test an unsigned two dimensional row vector input parameter.
"""
x = np.random.randint(5, high=500, size=[1, 101])
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
urow_in=x,
copy_all_inputs=True)
self.assertEqual(output['urow_out'].shape[0], 101)
self.assertEqual(output['urow_out'].dtype, np.long)
for i in range(101):
self.assertEqual(output['urow_out'][i], x[0][i] * 2)
def testTwoDimensionColForceCopy(self):
"""
Test that we pass Two Dimension column vetor as input paramter
"""
x = np.random.rand(100,1)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
col_in=x,
copy_all_inputs=True)
self.assertEqual(output['col_out'].shape[0], 100)
self.assertEqual(output['col_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['col_out'][i], x[i] * 2)
def testTwoDimensionUrow(self):
"""
Test an unsigned two dimensional row vector input parameter.
"""
x = np.random.randint(0, high=500, size=[100, 1])
z = copy.deepcopy(x)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
urow_in=z)
self.assertEqual(output['urow_out'].shape[0], 100)
self.assertEqual(output['urow_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['urow_out'][i], x[i] * 2)
def testMatrixAndInfoNumpy(self):
"""
Test that we can pass a matrix with all numeric features.
"""
x = np.random.rand(100, 10)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_and_info_in=x)
self.assertEqual(output['matrix_and_info_out'].shape[0], 100)
self.assertEqual(output['matrix_and_info_out'].shape[1], 10)
for i in range(10):
for j in range(100):
self.assertEqual(output['matrix_and_info_out'][j, i], x[j, i] * 2.0)
def testTwoDimensionRowForceCopy(self):
"""
Test a two dimensional row vector input parameter.
"""
x = np.random.rand(100,1)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
row_in=x,
copy_all_inputs=True)
self.assertEqual(output['row_out'].shape[0], 100)
self.assertEqual(output['row_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['row_out'][i], x[i] * 2)
def testOneDimensionNumpyUmatrixForceCopy(self):
"""
Same as testNumpyMatrix() but with an unsigned matrix and One Dimension Matrix.
"""
x = np.random.randint(0, high=500, size=100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
s_umatrix_in=x,
copy_all_inputs=True)
self.assertEqual(output['s_umatrix_out'].shape[0], 100)
self.assertEqual(output['s_umatrix_out'].dtype, np.long)
for i in range(100):
self.assertEqual(output['s_umatrix_out'][i, 0], x[i] * 2)
def testColForceCopy(self):
"""
Test a column vector input parameter.
"""
x = np.random.rand(100)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
col_in=x,
copy_all_inputs=True)
self.assertEqual(output['col_out'].shape[0], 100)
self.assertEqual(output['col_out'].dtype, np.double)
for i in range(100):
self.assertEqual(output['col_out'][i], x[i] * 2)
def testMatrixAndInfoNumpyForceCopy(self):
"""
Test that we can pass a matrix with all numeric features.
"""
x = np.random.rand(100, 10)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_and_info_in=x,
copy_all_inputs=True)
self.assertEqual(output['matrix_and_info_out'].shape[0], 100)
self.assertEqual(output['matrix_and_info_out'].shape[1], 10)
for i in range(10):
for j in range(100):
self.assertEqual(output['matrix_and_info_out'][j, i], x[j, i] * 2.0)
def testNumpyUmatrix(self):
"""
Same as testNumpyMatrix() but with an unsigned matrix.
"""
x = np.random.randint(0, high=500, size=[100, 5])
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
umatrix_in=x)
self.assertEqual(output['umatrix_out'].shape[0], 100)
self.assertEqual(output['umatrix_out'].shape[1], 4)
self.assertEqual(output['umatrix_out'].dtype, np.long)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x[j, i], output['umatrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x[j, 2], output['umatrix_out'][j, 2])
def testNumpyUmatrix(self):
"""
Same as testNumpyMatrix() but with an unsigned matrix.
"""
x = np.random.randint(0, high=500, size=[100, 5])
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
umatrix_in=x)
self.assertEqual(output['umatrix_out'].shape[0], 100)
self.assertEqual(output['umatrix_out'].shape[1], 4)
self.assertEqual(output['umatrix_out'].dtype, np.long)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x[j, i], output['umatrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x[j, 2], output['umatrix_out'][j, 2])
def testNumpyMatrix(self):
"""
The matrix we pass in, we should get back with the third dimension doubled
and the fifth forgotten.
"""
x = np.random.rand(100, 5);
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_in=x)
self.assertEqual(output['matrix_out'].shape[0], 100)
self.assertEqual(output['matrix_out'].shape[1], 4)
self.assertEqual(output['matrix_out'].dtype, np.double)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x[j, i], output['matrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x[j, 2], output['matrix_out'][j, 2])
def testNumpyMatrix(self):
"""
The matrix we pass in, we should get back with the third dimension doubled
and the fifth forgotten.
"""
x = np.random.rand(100, 5)
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_in=x)
self.assertEqual(output['matrix_out'].shape[0], 100)
self.assertEqual(output['matrix_out'].shape[1], 4)
self.assertEqual(output['matrix_out'].dtype, np.double)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x[j, i], output['matrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x[j, 2], output['matrix_out'][j, 2])
def testNumpyFContiguousMatrixForceCopy(self):
"""
The matrix with F_CONTIGUOUS set we pass in, we should get back with the third
dimension doubled and the fifth forgotten.
"""
x = np.array(np.random.rand(100, 5), order='F');
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_in=x,
copy_all_inputs=True)
self.assertEqual(output['matrix_out'].shape[0], 100)
self.assertEqual(output['matrix_out'].shape[1], 4)
self.assertEqual(output['matrix_out'].dtype, np.double)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x[j, i], output['matrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x[j, 2], output['matrix_out'][j, 2])
def testPandasDataFrameMatrixForceCopy(self):
"""
The matrix we pass in, we should get back with the third dimension doubled
and the fifth forgotten.
"""
x = pd.DataFrame(np.random.rand(100, 5))
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_in=x,
copy_all_inputs=True)
self.assertEqual(output['matrix_out'].shape[0], 100)
self.assertEqual(output['matrix_out'].shape[1], 4)
self.assertEqual(output['matrix_out'].dtype, np.double)
for i in [0, 1, 3]:
for j in range(100):
self.assertEqual(x.iloc[j, i], output['matrix_out'][j, i])
for j in range(100):
self.assertEqual(2 * x.iloc[j, 2], output['matrix_out'][j, 2])
def testMatrixAndInfoPandas(self):
"""
Test that we can pass a matrix with some categorical features.
"""
x = pd.DataFrame(np.random.rand(10, 4), columns=list('abcd'))
x['e'] = pd.Series(['a', 'b', 'c', 'd', 'a', 'b', 'e', 'c', 'a', 'b'],
dtype='category')
output = test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
matrix_and_info_in=x)
self.assertEqual(output['matrix_and_info_out'].shape[0], 10)
self.assertEqual(output['matrix_and_info_out'].shape[1], 5)
cols = list('abcde')
for i in range(4):
for j in range(10):
self.assertEqual(output['matrix_and_info_out'][j, i], x[cols[i]][j] * 2)
for j in range(10):
self.assertEqual(output['matrix_and_info_out'][j, 4], x[cols[4]][j])
def testThrownException(self):
"""
Test that we pass wrong type and get back TypeError
"""
self.assertRaises(TypeError,
lambda : test_python_binding(string_in=10,
int_in=12,
double_in=4.0,
flag1=True))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=10.0,
double_in=4.0,
flag1=True))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in='bad',
flag1=True))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
flag2=10))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
matrix_in= 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
matrix_in= 1))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
matrix_and_info_in = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
copy_all_inputs = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
col_in = 10))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
row_in = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
str_vector_in = 'bad'))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
urow_in = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
ucol_in = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
umatrix_in = 10.0))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
verbose = 10))
self.assertRaises(TypeError,
lambda : test_python_binding(string_in='hello',
int_in=12,
double_in=4.0,
flag1=True,
vector_in = 10.0))
