manyi/venv/Lib/site-packages/pandas/tests/indexes/multi/test_monotonic.py

# -*- coding: utf-8 -*-

import numpy as np
import pytest

import pandas as pd
from pandas import Index, IntervalIndex, MultiIndex
from pandas.api.types import is_scalar


def test_is_monotonic_increasing():
    i = MultiIndex.from_product([np.arange(10),
                                 np.arange(10)], names=['one', 'two'])
    assert i.is_monotonic is True
    assert i._is_strictly_monotonic_increasing is True
    assert Index(i.values).is_monotonic is True
    assert i._is_strictly_monotonic_increasing is True

    i = MultiIndex.from_product([np.arange(10, 0, -1),
                                 np.arange(10)], names=['one', 'two'])
    assert i.is_monotonic is False
    assert i._is_strictly_monotonic_increasing is False
    assert Index(i.values).is_monotonic is False
    assert Index(i.values)._is_strictly_monotonic_increasing is False

    i = MultiIndex.from_product([np.arange(10),
                                 np.arange(10, 0, -1)],
                                names=['one', 'two'])
    assert i.is_monotonic is False
    assert i._is_strictly_monotonic_increasing is False
    assert Index(i.values).is_monotonic is False
    assert Index(i.values)._is_strictly_monotonic_increasing is False

    i = MultiIndex.from_product([[1.0, np.nan, 2.0], ['a', 'b', 'c']])
    assert i.is_monotonic is False
    assert i._is_strictly_monotonic_increasing is False
    assert Index(i.values).is_monotonic is False
    assert Index(i.values)._is_strictly_monotonic_increasing is False

    # string ordering
    i = MultiIndex(levels=[['foo', 'bar', 'baz', 'qux'],
                           ['one', 'two', 'three']],
                   codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3],
                          [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
                   names=['first', 'second'])
    assert i.is_monotonic is False
    assert Index(i.values).is_monotonic is False
    assert i._is_strictly_monotonic_increasing is False
    assert Index(i.values)._is_strictly_monotonic_increasing is False

    i = MultiIndex(levels=[['bar', 'baz', 'foo', 'qux'],
                           ['mom', 'next', 'zenith']],
                   codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3],
                          [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
                   names=['first', 'second'])
    assert i.is_monotonic is True
    assert Index(i.values).is_monotonic is True
    assert i._is_strictly_monotonic_increasing is True
    assert Index(i.values)._is_strictly_monotonic_increasing is True

    # mixed levels, hits the TypeError
    i = MultiIndex(
        levels=[[1, 2, 3, 4], ['gb00b03mlx29', 'lu0197800237',
                               'nl0000289783',
                               'nl0000289965', 'nl0000301109']],
        codes=[[0, 1, 1, 2, 2, 2, 3], [4, 2, 0, 0, 1, 3, -1]],
        names=['household_id', 'asset_id'])

    assert i.is_monotonic is False
    assert i._is_strictly_monotonic_increasing is False

    # empty
    i = MultiIndex.from_arrays([[], []])
    assert i.is_monotonic is True
    assert Index(i.values).is_monotonic is True
    assert i._is_strictly_monotonic_increasing is True
    assert Index(i.values)._is_strictly_monotonic_increasing is True


def test_is_monotonic_decreasing():
    i = MultiIndex.from_product([np.arange(9, -1, -1),
                                 np.arange(9, -1, -1)],
                                names=['one', 'two'])
    assert i.is_monotonic_decreasing is True
    assert i._is_strictly_monotonic_decreasing is True
    assert Index(i.values).is_monotonic_decreasing is True
    assert i._is_strictly_monotonic_decreasing is True

    i = MultiIndex.from_product([np.arange(10),
                                 np.arange(10, 0, -1)],
                                names=['one', 'two'])
    assert i.is_monotonic_decreasing is False
    assert i._is_strictly_monotonic_decreasing is False
    assert Index(i.values).is_monotonic_decreasing is False
    assert Index(i.values)._is_strictly_monotonic_decreasing is False

    i = MultiIndex.from_product([np.arange(10, 0, -1),
                                 np.arange(10)], names=['one', 'two'])
    assert i.is_monotonic_decreasing is False
    assert i._is_strictly_monotonic_decreasing is False
    assert Index(i.values).is_monotonic_decreasing is False
    assert Index(i.values)._is_strictly_monotonic_decreasing is False

    i = MultiIndex.from_product([[2.0, np.nan, 1.0], ['c', 'b', 'a']])
    assert i.is_monotonic_decreasing is False
    assert i._is_strictly_monotonic_decreasing is False
    assert Index(i.values).is_monotonic_decreasing is False
    assert Index(i.values)._is_strictly_monotonic_decreasing is False

    # string ordering
    i = MultiIndex(levels=[['qux', 'foo', 'baz', 'bar'],
                           ['three', 'two', 'one']],
                   codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3],
                          [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
                   names=['first', 'second'])
    assert i.is_monotonic_decreasing is False
    assert Index(i.values).is_monotonic_decreasing is False
    assert i._is_strictly_monotonic_decreasing is False
    assert Index(i.values)._is_strictly_monotonic_decreasing is False

    i = MultiIndex(levels=[['qux', 'foo', 'baz', 'bar'],
                           ['zenith', 'next', 'mom']],
                   codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3],
                          [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
                   names=['first', 'second'])
    assert i.is_monotonic_decreasing is True
    assert Index(i.values).is_monotonic_decreasing is True
    assert i._is_strictly_monotonic_decreasing is True
    assert Index(i.values)._is_strictly_monotonic_decreasing is True

    # mixed levels, hits the TypeError
    i = MultiIndex(
        levels=[[4, 3, 2, 1], ['nl0000301109', 'nl0000289965',
                               'nl0000289783', 'lu0197800237',
                               'gb00b03mlx29']],
        codes=[[0, 1, 1, 2, 2, 2, 3], [4, 2, 0, 0, 1, 3, -1]],
        names=['household_id', 'asset_id'])

    assert i.is_monotonic_decreasing is False
    assert i._is_strictly_monotonic_decreasing is False

    # empty
    i = MultiIndex.from_arrays([[], []])
    assert i.is_monotonic_decreasing is True
    assert Index(i.values).is_monotonic_decreasing is True
    assert i._is_strictly_monotonic_decreasing is True
    assert Index(i.values)._is_strictly_monotonic_decreasing is True


def test_is_strictly_monotonic_increasing():
    idx = pd.MultiIndex(levels=[['bar', 'baz'], ['mom', 'next']],
                        codes=[[0, 0, 1, 1], [0, 0, 0, 1]])
    assert idx.is_monotonic_increasing is True
    assert idx._is_strictly_monotonic_increasing is False


def test_is_strictly_monotonic_decreasing():
    idx = pd.MultiIndex(levels=[['baz', 'bar'], ['next', 'mom']],
                        codes=[[0, 0, 1, 1], [0, 0, 0, 1]])
    assert idx.is_monotonic_decreasing is True
    assert idx._is_strictly_monotonic_decreasing is False


def test_searchsorted_monotonic(indices):
    # GH17271
    # not implemented for tuple searches in MultiIndex
    # or Intervals searches in IntervalIndex
    if isinstance(indices, (MultiIndex, IntervalIndex)):
        return

    # nothing to test if the index is empty
    if indices.empty:
        return
    value = indices[0]

    # determine the expected results (handle dupes for 'right')
    expected_left, expected_right = 0, (indices == value).argmin()
    if expected_right == 0:
        # all values are the same, expected_right should be length
        expected_right = len(indices)

    # test _searchsorted_monotonic in all cases
    # test searchsorted only for increasing
    if indices.is_monotonic_increasing:
        ssm_left = indices._searchsorted_monotonic(value, side='left')
        assert is_scalar(ssm_left)
        assert expected_left == ssm_left

        ssm_right = indices._searchsorted_monotonic(value, side='right')
        assert is_scalar(ssm_right)
        assert expected_right == ssm_right

        ss_left = indices.searchsorted(value, side='left')
        assert is_scalar(ss_left)
        assert expected_left == ss_left

        ss_right = indices.searchsorted(value, side='right')
        assert is_scalar(ss_right)
        assert expected_right == ss_right

    elif indices.is_monotonic_decreasing:
        ssm_left = indices._searchsorted_monotonic(value, side='left')
        assert is_scalar(ssm_left)
        assert expected_left == ssm_left

        ssm_right = indices._searchsorted_monotonic(value, side='right')
        assert is_scalar(ssm_right)
        assert expected_right == ssm_right

    else:
        # non-monotonic should raise.
        with pytest.raises(ValueError):
            indices._searchsorted_monotonic(value, side='left')