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"""Tests for silx.uitls.number module"""

__authors__ = ["V. Valls"]
__license__ = "MIT"
__date__ = "05/06/2018"

import logging
import numpy
from packaging.version import Version
from silx.utils import number
from silx.utils import testutils

_logger = logging.getLogger(__name__)


class TestConversionTypes(testutils.ParametricTestCase):
    def testEmptyFail(self):
        self.assertRaises(ValueError, number.min_numerical_convertible_type, "")

    def testStringFail(self):
        self.assertRaises(ValueError, number.min_numerical_convertible_type, "a")

    def testInteger(self):
        dtype = number.min_numerical_convertible_type("1456")
        self.assertTrue(numpy.issubdtype(dtype, numpy.unsignedinteger))

    def testTrailledInteger(self):
        dtype = number.min_numerical_convertible_type(" \t\n\r1456\t\n\r")
        self.assertTrue(numpy.issubdtype(dtype, numpy.unsignedinteger))

    def testPositiveInteger(self):
        dtype = number.min_numerical_convertible_type("+1456")
        self.assertTrue(numpy.issubdtype(dtype, numpy.unsignedinteger))

    def testNegativeInteger(self):
        dtype = number.min_numerical_convertible_type("-1456")
        self.assertTrue(numpy.issubdtype(dtype, numpy.signedinteger))

    def testIntegerExponential(self):
        dtype = number.min_numerical_convertible_type("14e10")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testIntegerPositiveExponential(self):
        dtype = number.min_numerical_convertible_type("14e+10")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testIntegerNegativeExponential(self):
        dtype = number.min_numerical_convertible_type("14e-10")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testNumberDecimal(self):
        dtype = number.min_numerical_convertible_type("14.5")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testPositiveNumberDecimal(self):
        dtype = number.min_numerical_convertible_type("+14.5")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testNegativeNumberDecimal(self):
        dtype = number.min_numerical_convertible_type("-14.5")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testDecimal(self):
        dtype = number.min_numerical_convertible_type(".50")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testPositiveDecimal(self):
        dtype = number.min_numerical_convertible_type("+.5")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testNegativeDecimal(self):
        dtype = number.min_numerical_convertible_type("-.5")
        self.assertTrue(numpy.issubdtype(dtype, numpy.floating))

    def testMantissa16(self):
        dtype = number.min_numerical_convertible_type("1.50")
        self.assertEqual(dtype, numpy.float16)

    def testFloat32(self):
        dtype = number.min_numerical_convertible_type("-23.172")
        self.assertEqual(dtype, numpy.float32)

    def testMantissa32(self):
        dtype = number.min_numerical_convertible_type("1400.50")
        self.assertEqual(dtype, numpy.float32)

    def testMantissa64(self):
        dtype = number.min_numerical_convertible_type("10000.000010")
        self.assertEqual(dtype, numpy.float64)

    def testMantissa80(self):
        self.skipIfFloat80NotSupported()
        dtype = number.min_numerical_convertible_type("1000000000.00001013")

        if Version(numpy.version.version) <= Version("1.10.4"):
            # numpy 1.8.2 -> Debian 8
            # Checking a float128 precision with numpy 1.8.2 using abs(diff) is not working.
            # It looks like the difference is done using float64 (diff == 0.0)
            expected = (numpy.longdouble, numpy.float64)
        else:
            expected = (numpy.longdouble,)
        self.assertIn(dtype, expected)

    def testExponent32(self):
        dtype = number.min_numerical_convertible_type("14.0e30")
        self.assertEqual(dtype, numpy.float32)

    def testExponent64(self):
        dtype = number.min_numerical_convertible_type("14.0e300")
        self.assertEqual(dtype, numpy.float64)

    def testExponent80(self):
        self.skipIfFloat80NotSupported()
        dtype = number.min_numerical_convertible_type("14.0e3000")
        self.assertEqual(dtype, numpy.longdouble)

    def testFloat32ToString(self):
        value = str(numpy.float32(numpy.pi))
        dtype = number.min_numerical_convertible_type(value)
        self.assertIn(dtype, (numpy.float32, numpy.float64))

    def skipIfFloat80NotSupported(self):
        if number.is_longdouble_64bits():
            self.skipTest("float-80bits not supported")

    def testLosePrecisionUsingFloat80(self):
        self.skipIfFloat80NotSupported()
        if Version(numpy.version.version) <= Version("1.10.4"):
            self.skipTest("numpy > 1.10.4 expected")
        # value does not fit even in a 128 bits mantissa
        value = "1.0340282366920938463463374607431768211456"
        func = testutils.validate_logging(number._logger.name, warning=1)
        func = func(number.min_numerical_convertible_type)
        dtype = func(value)
        self.assertIn(dtype, (numpy.longdouble,))

    def testMillisecondEpochTime(self):
        datetimes = [
            "1465803236.495412",
            "1465803236.999362",
            "1465803237.504311",
            "1465803238.009261",
            "1465803238.512211",
            "1465803239.016160",
            "1465803239.520110",
            "1465803240.026059",
            "1465803240.529009",
        ]
        for datetime in datetimes:
            with self.subTest(datetime=datetime):
                dtype = number.min_numerical_convertible_type(datetime)
                self.assertEqual(dtype, numpy.float64)
