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# Test methods with long descriptive names can omit docstrings
# pylint: disable=missing-docstring
import unittest
import os
from functools import wraps
from tempfile import mkstemp
from typing import Callable
import numpy as np
from Orange.data import io, ContinuousVariable, DiscreteVariable, Table
def get_dataset(name):
return os.path.join(os.path.dirname(__file__), "xlsx_files", name)
def get_xlsx_reader(name: str) -> io.ExcelReader:
return io.ExcelReader(get_dataset(name + ".xlsx"))
def get_xls_reader(name: str) -> io.XlsReader:
return io.XlsReader(get_dataset(name + ".xls"))
def read_file(reader: Callable, name: str) -> Table:
return reader(name).read()
def test_xlsx_xls(f):
@wraps(f)
def wrapper(self):
f(self, get_xlsx_reader)
f(self, get_xls_reader)
return wrapper
class TestExcelReader(unittest.TestCase):
def test_read_round_floats(self):
table = read_file(get_xlsx_reader, "round_floats")
domain = table.domain
self.assertIsNone(domain.class_var)
self.assertEqual(len(domain.metas), 0)
self.assertEqual(len(domain.attributes), 3)
self.assertIsInstance(domain[0], ContinuousVariable)
self.assertIsInstance(domain[1], ContinuousVariable)
self.assertEqual(domain[2].values, ("1", "2"))
def test_write_file(self):
fd, filename = mkstemp(suffix=".xlsx")
os.close(fd)
data = Table("zoo")
io.ExcelReader.write_file(filename, data, with_annotations=True)
reader = io.ExcelReader(filename)
read_data = reader.read()
domain1 = data.domain
domain2 = read_data.domain
self.assertEqual(len(domain1.attributes), len(domain2.attributes))
self.assertEqual(len(domain1.class_vars), len(domain2.class_vars))
self.assertEqual(len(domain1.metas), len(domain2.metas))
for var1, var2 in zip(domain1.variables + domain1.metas,
domain2.variables + domain2.metas):
self.assertEqual(type(var1), type(var2))
self.assertEqual(var1.name, var2.name)
if var1.is_discrete:
self.assertEqual(var1.values, var2.values)
np.testing.assert_array_equal(data.X, read_data.X)
np.testing.assert_array_equal(data.Y, read_data.Y)
np.testing.assert_array_equal(data.metas, read_data.metas)
np.testing.assert_array_equal(data.W, read_data.W)
os.unlink(filename)
class TestExcelHeader0(unittest.TestCase):
@test_xlsx_xls
def test_read(self, reader: Callable[[str], io.FileFormat]):
table = read_file(reader, "header_0")
domain = table.domain
self.assertIsNone(domain.class_var)
self.assertEqual(len(domain.metas), 0)
self.assertEqual(len(domain.attributes), 4)
for i, var in enumerate(domain.attributes):
self.assertIsInstance(var, ContinuousVariable)
self.assertEqual(var.name, "Feature {}".format(i + 1))
np.testing.assert_almost_equal(table.X,
np.array([[0.1, 0.5, 0.1, 21],
[0.2, 0.1, 2.5, 123],
[0, 0, 0, 0]]))
self.assertEqual(table.name, 'header_0')
class TextExcelSheets(unittest.TestCase):
@test_xlsx_xls
def test_sheets(self, reader: Callable[[str], io.FileFormat]):
reader = reader("header_0_sheet")
self.assertSequenceEqual(reader.sheets,
["Sheet1", "my_sheet", "Sheet3"])
@test_xlsx_xls
def test_named_sheet(self, reader: Callable[[str], io.FileFormat]):
reader = reader("header_0_sheet")
reader.select_sheet("my_sheet")
table = reader.read()
self.assertEqual(len(table.domain.attributes), 4)
self.assertEqual(table.name, 'header_0_sheet-my_sheet')
def test_named_sheet_table_xlsx(self):
table = Table.from_file(get_dataset("header_0_sheet.xlsx"),
sheet="my_sheet")
self.assertEqual(len(table.domain.attributes), 4)
self.assertEqual(table.name, 'header_0_sheet-my_sheet')
def test_named_sheet_table_xls(self):
table = Table.from_file(get_dataset("header_0_sheet.xls"),
sheet="my_sheet")
self.assertEqual(len(table.domain.attributes), 4)
self.assertEqual(table.name, 'header_0_sheet-my_sheet')
class TestExcelHeader1(unittest.TestCase):
@test_xlsx_xls
def test_no_flags(self, reader: Callable[[str], io.FileFormat]):
table = read_file(reader, "header_1_no_flags")
domain = table.domain
self.assertEqual(len(domain.metas), 0)
self.assertEqual(len(domain.attributes), 4)
self.assertIsInstance(domain[0], DiscreteVariable)
self.assertIsInstance(domain[1], ContinuousVariable)
self.assertIsInstance(domain[2], DiscreteVariable)
self.assertIsInstance(domain[3], ContinuousVariable)
for i, var in enumerate(domain.variables):
self.assertEqual(var.name, chr(97 + i))
self.assertEqual(domain[0].values, ("green", "red"))
np.testing.assert_almost_equal(table.X,
np.array([[1, 0.5, 0, 21],
[1, 0.1, 0, 123],
[0, 0, np.nan, 0]]))
np.testing.assert_equal(table.Y, np.array([]).reshape(3, 0))
def test_hash(self):
table = Table.from_file(get_dataset("header_1_hash.xlsx"))
domain = table.domain
self.assertEqual(len(domain.metas), 0)
self.assertEqual(len(domain.attributes), 3)
self.assertEqual(len(domain.class_vars), 1)
self.assertIsInstance(domain[0], DiscreteVariable)
self.assertIsInstance(domain[1], ContinuousVariable)
self.assertIsInstance(domain[2], ContinuousVariable)
self.assertIsInstance(domain[3], DiscreteVariable)
self.assertEqual([v.name for v in domain.variables],
["#", "b#", "d", "Feature 1"])
self.assertEqual(domain[0].values, ("green", "red"))
np.testing.assert_almost_equal(table.X, np.array([[1, 0.5, 21],
[1, 0.1, 123],
[0, 0, 0]]))
np.testing.assert_equal(table.Y, [0, 0, np.nan])
@test_xlsx_xls
def test_flags(self, reader: Callable[[str], io.FileFormat]):
table = read_file(reader, "header_1_flags")
domain = table.domain
self.assertEqual(len(domain.attributes), 1)
attr = domain.attributes[0]
self.assertEqual(attr.name, "d")
self.assertIsInstance(attr, ContinuousVariable)
np.testing.assert_almost_equal(table.X, np.arange(23).reshape(23, 1))
self.assertEqual(len(domain.class_vars), 1)
class_ = domain.class_var
self.assertEqual(class_.name, "b")
self.assertIsInstance(class_, ContinuousVariable)
np.testing.assert_almost_equal(
table.Y, np.array([.5, .1, 0, 0] * 5 + [.5, .1, 0]))
self.assertEqual(len(domain.metas), 3)
for n, var in zip("acf", domain.metas):
self.assertEqual(var.name, n)
self.assertIsInstance(domain.metas[0], DiscreteVariable)
self.assertEqual(domain.metas[0].values, ("green", "red"))
self.assertIsInstance(domain.metas[1], ContinuousVariable)
np.testing.assert_almost_equal(
table.metas[:, 0], np.array([1, 1, 0] * 7 + [1, 1]))
np.testing.assert_almost_equal(
table.metas[:, 1], np.array([0, 1, 2, 3] * 5 + [0, 1, 2]))
class TestExcelHeader3(unittest.TestCase):
@test_xlsx_xls
def test_read(self, reader: Callable[[str], io.FileFormat]):
table = read_file(reader, "header_3")
domain = table.domain
self.assertEqual(len(domain.attributes), 2)
attr = domain.attributes[0]
self.assertEqual(attr.name, "d")
self.assertIsInstance(attr, ContinuousVariable)
np.testing.assert_almost_equal(table.X[:, 0], np.arange(23))
attr = domain.attributes[1]
self.assertEqual(attr.name, "g")
self.assertIsInstance(attr, DiscreteVariable)
np.testing.assert_almost_equal(table.X[:, 1],
np.array([1, 0] + [float("nan")] * 21))
self.assertEqual(len(domain.class_vars), 1)
class_ = domain.class_var
self.assertEqual(class_.name, "b")
self.assertIsInstance(class_, ContinuousVariable)
np.testing.assert_almost_equal(
table.Y, np.array([.5, .1, 0, 0] * 5 + [.5, .1, 0]))
self.assertEqual(len(domain.metas), 3)
for n, var in zip("acf", domain.metas):
self.assertEqual(var.name, n)
self.assertIsInstance(domain.metas[0], DiscreteVariable)
self.assertEqual(domain.metas[0].values, ("green", "red"))
self.assertIsInstance(domain.metas[1], ContinuousVariable)
np.testing.assert_almost_equal(
table.metas[:, 0], np.array([1, 1, 0] * 7 + [1, 1]))
np.testing.assert_almost_equal(
table.metas[:, 1], np.array([0, 1, 2, 3] * 5 + [0, 1, 2]))
np.testing.assert_equal(
table.metas[:, 2], np.array(list("abcdefghijklmnopqrstuvw")))
class TestMissingValues(unittest.TestCase):
@test_xlsx_xls
def test_read_errors(self, reader: Callable[[str], io.FileFormat]):
table = read_file(reader, "missing")
values = table.get_column("C")
self.assertTrue(np.isnan(values).all())
if __name__ == "__main__":
unittest.main()
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