ai-content-maker/.venv/Lib/site-packages/scipy/io/arff/tests/test_arffread.py

422 lines
13 KiB
Python

import datetime
import os
import sys
from os.path import join as pjoin
from io import StringIO
import numpy as np
from numpy.testing import (assert_array_almost_equal,
assert_array_equal, assert_equal, assert_)
from pytest import raises as assert_raises
from scipy.io.arff import loadarff
from scipy.io.arff._arffread import read_header, ParseArffError
data_path = pjoin(os.path.dirname(__file__), 'data')
test1 = pjoin(data_path, 'test1.arff')
test2 = pjoin(data_path, 'test2.arff')
test3 = pjoin(data_path, 'test3.arff')
test4 = pjoin(data_path, 'test4.arff')
test5 = pjoin(data_path, 'test5.arff')
test6 = pjoin(data_path, 'test6.arff')
test7 = pjoin(data_path, 'test7.arff')
test8 = pjoin(data_path, 'test8.arff')
test9 = pjoin(data_path, 'test9.arff')
test10 = pjoin(data_path, 'test10.arff')
test11 = pjoin(data_path, 'test11.arff')
test_quoted_nominal = pjoin(data_path, 'quoted_nominal.arff')
test_quoted_nominal_spaces = pjoin(data_path, 'quoted_nominal_spaces.arff')
expect4_data = [(0.1, 0.2, 0.3, 0.4, 'class1'),
(-0.1, -0.2, -0.3, -0.4, 'class2'),
(1, 2, 3, 4, 'class3')]
expected_types = ['numeric', 'numeric', 'numeric', 'numeric', 'nominal']
missing = pjoin(data_path, 'missing.arff')
expect_missing_raw = np.array([[1, 5], [2, 4], [np.nan, np.nan]])
expect_missing = np.empty(3, [('yop', float), ('yap', float)])
expect_missing['yop'] = expect_missing_raw[:, 0]
expect_missing['yap'] = expect_missing_raw[:, 1]
class TestData:
def test1(self):
# Parsing trivial file with nothing.
self._test(test4)
def test2(self):
# Parsing trivial file with some comments in the data section.
self._test(test5)
def test3(self):
# Parsing trivial file with nominal attribute of 1 character.
self._test(test6)
def test4(self):
# Parsing trivial file with trailing spaces in attribute declaration.
self._test(test11)
def _test(self, test_file):
data, meta = loadarff(test_file)
for i in range(len(data)):
for j in range(4):
assert_array_almost_equal(expect4_data[i][j], data[i][j])
assert_equal(meta.types(), expected_types)
def test_filelike(self):
# Test reading from file-like object (StringIO)
with open(test1) as f1:
data1, meta1 = loadarff(f1)
with open(test1) as f2:
data2, meta2 = loadarff(StringIO(f2.read()))
assert_(data1 == data2)
assert_(repr(meta1) == repr(meta2))
def test_path(self):
# Test reading from `pathlib.Path` object
from pathlib import Path
with open(test1) as f1:
data1, meta1 = loadarff(f1)
data2, meta2 = loadarff(Path(test1))
assert_(data1 == data2)
assert_(repr(meta1) == repr(meta2))
class TestMissingData:
def test_missing(self):
data, meta = loadarff(missing)
for i in ['yop', 'yap']:
assert_array_almost_equal(data[i], expect_missing[i])
class TestNoData:
def test_nodata(self):
# The file nodata.arff has no data in the @DATA section.
# Reading it should result in an array with length 0.
nodata_filename = os.path.join(data_path, 'nodata.arff')
data, meta = loadarff(nodata_filename)
if sys.byteorder == 'big':
end = '>'
else:
end = '<'
expected_dtype = np.dtype([('sepallength', f'{end}f8'),
('sepalwidth', f'{end}f8'),
('petallength', f'{end}f8'),
('petalwidth', f'{end}f8'),
('class', 'S15')])
assert_equal(data.dtype, expected_dtype)
assert_equal(data.size, 0)
class TestHeader:
def test_type_parsing(self):
# Test parsing type of attribute from their value.
with open(test2) as ofile:
rel, attrs = read_header(ofile)
expected = ['numeric', 'numeric', 'numeric', 'numeric', 'numeric',
'numeric', 'string', 'string', 'nominal', 'nominal']
for i in range(len(attrs)):
assert_(attrs[i].type_name == expected[i])
def test_badtype_parsing(self):
# Test parsing wrong type of attribute from their value.
def badtype_read():
with open(test3) as ofile:
_, _ = read_header(ofile)
assert_raises(ParseArffError, badtype_read)
def test_fullheader1(self):
# Parsing trivial header with nothing.
with open(test1) as ofile:
rel, attrs = read_header(ofile)
# Test relation
assert_(rel == 'test1')
# Test numerical attributes
assert_(len(attrs) == 5)
for i in range(4):
assert_(attrs[i].name == 'attr%d' % i)
assert_(attrs[i].type_name == 'numeric')
# Test nominal attribute
assert_(attrs[4].name == 'class')
assert_(attrs[4].values == ('class0', 'class1', 'class2', 'class3'))
def test_dateheader(self):
with open(test7) as ofile:
rel, attrs = read_header(ofile)
assert_(rel == 'test7')
assert_(len(attrs) == 5)
assert_(attrs[0].name == 'attr_year')
assert_(attrs[0].date_format == '%Y')
assert_(attrs[1].name == 'attr_month')
assert_(attrs[1].date_format == '%Y-%m')
assert_(attrs[2].name == 'attr_date')
assert_(attrs[2].date_format == '%Y-%m-%d')
assert_(attrs[3].name == 'attr_datetime_local')
assert_(attrs[3].date_format == '%Y-%m-%d %H:%M')
assert_(attrs[4].name == 'attr_datetime_missing')
assert_(attrs[4].date_format == '%Y-%m-%d %H:%M')
def test_dateheader_unsupported(self):
def read_dateheader_unsupported():
with open(test8) as ofile:
_, _ = read_header(ofile)
assert_raises(ValueError, read_dateheader_unsupported)
class TestDateAttribute:
def setup_method(self):
self.data, self.meta = loadarff(test7)
def test_year_attribute(self):
expected = np.array([
'1999',
'2004',
'1817',
'2100',
'2013',
'1631'
], dtype='datetime64[Y]')
assert_array_equal(self.data["attr_year"], expected)
def test_month_attribute(self):
expected = np.array([
'1999-01',
'2004-12',
'1817-04',
'2100-09',
'2013-11',
'1631-10'
], dtype='datetime64[M]')
assert_array_equal(self.data["attr_month"], expected)
def test_date_attribute(self):
expected = np.array([
'1999-01-31',
'2004-12-01',
'1817-04-28',
'2100-09-10',
'2013-11-30',
'1631-10-15'
], dtype='datetime64[D]')
assert_array_equal(self.data["attr_date"], expected)
def test_datetime_local_attribute(self):
expected = np.array([
datetime.datetime(year=1999, month=1, day=31, hour=0, minute=1),
datetime.datetime(year=2004, month=12, day=1, hour=23, minute=59),
datetime.datetime(year=1817, month=4, day=28, hour=13, minute=0),
datetime.datetime(year=2100, month=9, day=10, hour=12, minute=0),
datetime.datetime(year=2013, month=11, day=30, hour=4, minute=55),
datetime.datetime(year=1631, month=10, day=15, hour=20, minute=4)
], dtype='datetime64[m]')
assert_array_equal(self.data["attr_datetime_local"], expected)
def test_datetime_missing(self):
expected = np.array([
'nat',
'2004-12-01T23:59',
'nat',
'nat',
'2013-11-30T04:55',
'1631-10-15T20:04'
], dtype='datetime64[m]')
assert_array_equal(self.data["attr_datetime_missing"], expected)
def test_datetime_timezone(self):
assert_raises(ParseArffError, loadarff, test8)
class TestRelationalAttribute:
def setup_method(self):
self.data, self.meta = loadarff(test9)
def test_attributes(self):
assert_equal(len(self.meta._attributes), 1)
relational = list(self.meta._attributes.values())[0]
assert_equal(relational.name, 'attr_date_number')
assert_equal(relational.type_name, 'relational')
assert_equal(len(relational.attributes), 2)
assert_equal(relational.attributes[0].name,
'attr_date')
assert_equal(relational.attributes[0].type_name,
'date')
assert_equal(relational.attributes[1].name,
'attr_number')
assert_equal(relational.attributes[1].type_name,
'numeric')
def test_data(self):
dtype_instance = [('attr_date', 'datetime64[D]'),
('attr_number', np.float64)]
expected = [
np.array([('1999-01-31', 1), ('1935-11-27', 10)],
dtype=dtype_instance),
np.array([('2004-12-01', 2), ('1942-08-13', 20)],
dtype=dtype_instance),
np.array([('1817-04-28', 3)],
dtype=dtype_instance),
np.array([('2100-09-10', 4), ('1957-04-17', 40),
('1721-01-14', 400)],
dtype=dtype_instance),
np.array([('2013-11-30', 5)],
dtype=dtype_instance),
np.array([('1631-10-15', 6)],
dtype=dtype_instance)
]
for i in range(len(self.data["attr_date_number"])):
assert_array_equal(self.data["attr_date_number"][i],
expected[i])
class TestRelationalAttributeLong:
def setup_method(self):
self.data, self.meta = loadarff(test10)
def test_attributes(self):
assert_equal(len(self.meta._attributes), 1)
relational = list(self.meta._attributes.values())[0]
assert_equal(relational.name, 'attr_relational')
assert_equal(relational.type_name, 'relational')
assert_equal(len(relational.attributes), 1)
assert_equal(relational.attributes[0].name,
'attr_number')
assert_equal(relational.attributes[0].type_name, 'numeric')
def test_data(self):
dtype_instance = [('attr_number', np.float64)]
expected = np.array([(n,) for n in range(30000)],
dtype=dtype_instance)
assert_array_equal(self.data["attr_relational"][0],
expected)
class TestQuotedNominal:
"""
Regression test for issue #10232:
Exception in loadarff with quoted nominal attributes.
"""
def setup_method(self):
self.data, self.meta = loadarff(test_quoted_nominal)
def test_attributes(self):
assert_equal(len(self.meta._attributes), 2)
age, smoker = self.meta._attributes.values()
assert_equal(age.name, 'age')
assert_equal(age.type_name, 'numeric')
assert_equal(smoker.name, 'smoker')
assert_equal(smoker.type_name, 'nominal')
assert_equal(smoker.values, ['yes', 'no'])
def test_data(self):
age_dtype_instance = np.float64
smoker_dtype_instance = '<S3'
age_expected = np.array([
18,
24,
44,
56,
89,
11,
], dtype=age_dtype_instance)
smoker_expected = np.array([
'no',
'yes',
'no',
'no',
'yes',
'no',
], dtype=smoker_dtype_instance)
assert_array_equal(self.data["age"], age_expected)
assert_array_equal(self.data["smoker"], smoker_expected)
class TestQuotedNominalSpaces:
"""
Regression test for issue #10232:
Exception in loadarff with quoted nominal attributes.
"""
def setup_method(self):
self.data, self.meta = loadarff(test_quoted_nominal_spaces)
def test_attributes(self):
assert_equal(len(self.meta._attributes), 2)
age, smoker = self.meta._attributes.values()
assert_equal(age.name, 'age')
assert_equal(age.type_name, 'numeric')
assert_equal(smoker.name, 'smoker')
assert_equal(smoker.type_name, 'nominal')
assert_equal(smoker.values, [' yes', 'no '])
def test_data(self):
age_dtype_instance = np.float64
smoker_dtype_instance = '<S5'
age_expected = np.array([
18,
24,
44,
56,
89,
11,
], dtype=age_dtype_instance)
smoker_expected = np.array([
'no ',
' yes',
'no ',
'no ',
' yes',
'no ',
], dtype=smoker_dtype_instance)
assert_array_equal(self.data["age"], age_expected)
assert_array_equal(self.data["smoker"], smoker_expected)