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"""
Test Parameters based on pandas
"""
import os
import re
import unittest
import param
import pytest
from .utils import check_defaults
try:
import pandas
except ImportError:
if os.getenv('PARAM_TEST_PANDAS','0') == '1':
raise ImportError("PARAM_TEST_PANDAS=1 but pandas not available.")
else:
raise unittest.SkipTest("pandas not available")
class TestDataFrame(unittest.TestCase):
def _check_defaults(self, p):
assert p.default is None
assert p.allow_None is True
assert p.instantiate is True
assert p.is_instance is True
assert p.rows is None
assert p.columns is None
assert p.ordered is None
assert p.class_ == pandas.DataFrame
def test_defaults_class(self):
class P(param.Parameterized):
s = param.DataFrame()
check_defaults(P.param.s, label='S', skip=['instantiate'])
self._check_defaults(P.param.s)
def test_defaults_inst(self):
class P(param.Parameterized):
s = param.DataFrame()
p = P()
check_defaults(p.param.s, label='S', skip=['instantiate'])
self._check_defaults(p.param.s)
def test_defaults_unbound(self):
s = param.DataFrame()
check_defaults(s, label=None, skip=['instantiate'])
self._check_defaults(s)
def test_dataframe_positional_argument(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]},
columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(valid_df)
def test_dataframe_allow_none(self):
class Test(param.Parameterized):
df = param.DataFrame(default=None, rows=3)
test = Test()
self.assertIs(test.df, None)
def test_dataframe_allow_none_constructor(self):
class Test(param.Parameterized):
df = param.DataFrame(allow_None=True, rows=3)
test = Test(df=None)
self.assertIs(test.df, None)
def test_dataframe_allow_none_set_value(self):
class Test(param.Parameterized):
df = param.DataFrame(allow_None=True, rows=3)
test = Test()
test.df = None
self.assertIs(test.df, None)
def test_empty_dataframe_param_invalid_set(self):
empty = pandas.DataFrame()
class Test(param.Parameterized):
df = param.DataFrame(default=empty)
test = Test()
exception = "DataFrame parameter 'Test.df' value must be an instance of DataFrame, not 3."
with self.assertRaisesRegex(ValueError, exception):
test.df = 3
def test_dataframe_unordered_column_set_valid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns={'a', 'b'})
def test_dataframe_unordered_column_set_invalid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'd':[4,5]}, columns=['b', 'a', 'd'])
invalid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns={'a', 'd'})
test = Test()
self.assertEqual(test.param['df'].ordered, False)
exception = re.escape("DataFrame parameter 'Test.df': provided columns ['b', 'a', 'c'] does not contain required columns ['a', 'd']")
with self.assertRaisesRegex(ValueError, exception):
test.df = invalid_df
def test_dataframe_ordered_column_list_valid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
test = param.DataFrame(default=valid_df, columns=['b', 'a', 'c'])
def test_dataframe_ordered_column_list_invalid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'd':[4,5]}, columns=['b', 'a', 'd'])
invalid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['a', 'b', 'd'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns=['b', 'a', 'd'])
test = Test()
self.assertEqual(test.param['df'].ordered, True)
exception = re.escape("DataFrame parameter 'Test.df': provided columns ['a', 'b', 'd'] must exactly match ['b', 'a', 'd']")
with self.assertRaisesRegex(ValueError, exception):
test.df = invalid_df
def test_dataframe_unordered_column_number_valid_df(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns=3)
def test_dataframe_unordered_column_number_invalid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
invalid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3]}, columns=['b', 'a'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns=3)
test = Test()
self.assertEqual(test.param['df'].ordered, None)
exception = "column length 2 does not match declared bounds of 3"
with self.assertRaisesRegex(ValueError, exception):
test.df = invalid_df
def test_dataframe_unordered_column_tuple_valid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, columns=(None,3))
def test_dataframe_unordered_column_tuple_invalid(self):
invalid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
exception = re.escape("DataFrame parameter 'df': columns length 3 does not match declared bounds of (None, 2)")
with self.assertRaisesRegex(ValueError, exception):
class Test(param.Parameterized):
df = param.DataFrame(default=invalid_df, columns=(None,2))
def test_dataframe_row_number_valid_df(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, rows=2)
def test_dataframe_row_number_invalid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3]}, columns=['b', 'a'])
invalid_df = pandas.DataFrame({'a':[1,2,4], 'b':[2,3,4]}, columns=['b', 'a'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, rows=2)
test = Test()
exception = re.escape("DataFrame parameter 'Test.df': row length 3 does not match declared bounds of 2")
with self.assertRaisesRegex(ValueError, exception):
test.df = invalid_df
def test_dataframe_unordered_row_tuple_valid(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
class Test(param.Parameterized):
df = param.DataFrame(default=valid_df, rows=(None,3))
def test_dataframe_unordered_row_tuple_invalid(self):
invalid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
exception = r"row length 2 does not match declared bounds of \(5, 7\)"
with self.assertRaisesRegex(ValueError, exception):
class Test(param.Parameterized):
df = param.DataFrame(default=invalid_df, rows=(5,7))
def test_dataframe_unordered_columns_as_set_error(self):
valid_df = pandas.DataFrame({'a':[1,2], 'b':[2,3], 'c':[4,5]}, columns=['b', 'a', 'c'])
with pytest.raises(
ValueError,
match=re.escape("DataFrame parameter 'df': columns cannot be ordered when specified as a set"),
):
df = param.DataFrame(default=valid_df, columns=set(['a', 'b']), ordered=True) # noqa
class TestSeries(unittest.TestCase):
def _check_defaults(self, p):
assert p.default is None
assert p.allow_None is True
assert p.instantiate is True
assert p.is_instance is True
assert p.rows is None
assert p.class_ == pandas.Series
def test_defaults_class(self):
class P(param.Parameterized):
s = param.Series()
check_defaults(P.param.s, label='S', skip=['instantiate'])
self._check_defaults(P.param.s)
def test_defaults_inst(self):
class P(param.Parameterized):
s = param.Series()
p = P()
check_defaults(p.param.s, label='S', skip=['instantiate'])
self._check_defaults(p.param.s)
def test_defaults_unbound(self):
s = param.Series()
check_defaults(s, label=None, skip=['instantiate'])
self._check_defaults(s)
def test_series_positional_argument(self):
valid_series = pandas.Series([1,2])
class Test(param.Parameterized):
series = param.Series(valid_series, rows=2)
def test_series_row_number_valid(self):
valid_series = pandas.Series([1,2])
class Test(param.Parameterized):
series = param.Series(default=valid_series, rows=2)
def test_series_row_number_invalid(self):
valid_series = pandas.Series([1,2])
invalid_series = pandas.Series([1,2,3])
class Test(param.Parameterized):
series = param.Series(default=valid_series, rows=2)
test = Test()
exception = re.escape("Series parameter 'Test.series': row length 3 does not match declared bounds of 2")
with self.assertRaisesRegex(ValueError, exception):
test.series = invalid_series
def test_series_unordered_row_tuple_valid(self):
valid_series = pandas.Series([1,2,3])
class Test(param.Parameterized):
series = param.Series(default=valid_series, rows=(None,3))
def test_series_unordered_row_tuple_invalid(self):
invalid_series = pandas.Series([1,2])
exception = re.escape("Series parameter 'series': row length 2 does not match declared bounds of (5, 7)")
with self.assertRaisesRegex(ValueError, exception):
class Test(param.Parameterized):
series = param.Series(default=invalid_series, rows=(5,7))
def test_series_allow_none(self):
class Test(param.Parameterized):
series = param.Series(default=None, rows=3)
test = Test()
self.assertIs(test.series, None)
def test_series_allow_none_constructor(self):
class Test(param.Parameterized):
series = param.Series(allow_None=True, rows=3)
test = Test(series=None)
self.assertIs(test.series, None)
def test_series_allow_none_set_value(self):
class Test(param.Parameterized):
series = param.Series(allow_None=True, rows=3)
test = Test()
test.series = None
self.assertIs(test.series, None)
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