1423 lines
48 KiB
Python
1423 lines
48 KiB
Python
from datetime import (
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date,
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datetime,
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)
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import itertools
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import re
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import numpy as np
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import pytest
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from pandas._libs.internals import BlockPlacement
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from pandas.compat import IS64
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import pandas.util._test_decorators as td
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from pandas.core.dtypes.common import is_scalar
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import pandas as pd
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from pandas import (
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Categorical,
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DataFrame,
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DatetimeIndex,
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Index,
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IntervalIndex,
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Series,
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Timedelta,
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Timestamp,
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period_range,
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)
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import pandas._testing as tm
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import pandas.core.algorithms as algos
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from pandas.core.arrays import (
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DatetimeArray,
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SparseArray,
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TimedeltaArray,
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)
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from pandas.core.internals import (
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BlockManager,
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SingleBlockManager,
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make_block,
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)
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from pandas.core.internals.blocks import (
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ensure_block_shape,
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maybe_coerce_values,
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new_block,
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)
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# this file contains BlockManager specific tests
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# TODO(ArrayManager) factor out interleave_dtype tests
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pytestmark = td.skip_array_manager_invalid_test
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@pytest.fixture(params=[new_block, make_block])
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def block_maker(request):
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"""
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Fixture to test both the internal new_block and pseudo-public make_block.
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"""
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return request.param
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@pytest.fixture
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def mgr():
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return create_mgr(
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"a: f8; b: object; c: f8; d: object; e: f8;"
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"f: bool; g: i8; h: complex; i: datetime-1; j: datetime-2;"
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"k: M8[ns, US/Eastern]; l: M8[ns, CET];"
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)
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def assert_block_equal(left, right):
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tm.assert_numpy_array_equal(left.values, right.values)
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assert left.dtype == right.dtype
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assert isinstance(left.mgr_locs, BlockPlacement)
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assert isinstance(right.mgr_locs, BlockPlacement)
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tm.assert_numpy_array_equal(left.mgr_locs.as_array, right.mgr_locs.as_array)
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def get_numeric_mat(shape):
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arr = np.arange(shape[0])
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return np.lib.stride_tricks.as_strided(
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x=arr, shape=shape, strides=(arr.itemsize,) + (0,) * (len(shape) - 1)
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).copy()
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N = 10
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def create_block(typestr, placement, item_shape=None, num_offset=0, maker=new_block):
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"""
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Supported typestr:
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* float, f8, f4, f2
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* int, i8, i4, i2, i1
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* uint, u8, u4, u2, u1
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* complex, c16, c8
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* bool
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* object, string, O
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* datetime, dt, M8[ns], M8[ns, tz]
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* timedelta, td, m8[ns]
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* sparse (SparseArray with fill_value=0.0)
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* sparse_na (SparseArray with fill_value=np.nan)
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* category, category2
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"""
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placement = BlockPlacement(placement)
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num_items = len(placement)
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if item_shape is None:
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item_shape = (N,)
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shape = (num_items,) + item_shape
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mat = get_numeric_mat(shape)
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if typestr in (
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"float",
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"f8",
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"f4",
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"f2",
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"int",
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"i8",
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"i4",
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"i2",
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"i1",
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"uint",
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"u8",
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"u4",
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"u2",
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"u1",
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):
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values = mat.astype(typestr) + num_offset
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elif typestr in ("complex", "c16", "c8"):
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values = 1.0j * (mat.astype(typestr) + num_offset)
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elif typestr in ("object", "string", "O"):
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values = np.reshape([f"A{i:d}" for i in mat.ravel() + num_offset], shape)
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elif typestr in ("b", "bool"):
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values = np.ones(shape, dtype=np.bool_)
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elif typestr in ("datetime", "dt", "M8[ns]"):
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values = (mat * 1e9).astype("M8[ns]")
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elif typestr.startswith("M8[ns"):
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# datetime with tz
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m = re.search(r"M8\[ns,\s*(\w+\/?\w*)\]", typestr)
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assert m is not None, f"incompatible typestr -> {typestr}"
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tz = m.groups()[0]
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assert num_items == 1, "must have only 1 num items for a tz-aware"
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values = DatetimeIndex(np.arange(N) * 10**9, tz=tz)._data
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values = ensure_block_shape(values, ndim=len(shape))
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elif typestr in ("timedelta", "td", "m8[ns]"):
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values = (mat * 1).astype("m8[ns]")
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elif typestr in ("category",):
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values = Categorical([1, 1, 2, 2, 3, 3, 3, 3, 4, 4])
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elif typestr in ("category2",):
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values = Categorical(["a", "a", "a", "a", "b", "b", "c", "c", "c", "d"])
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elif typestr in ("sparse", "sparse_na"):
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if shape[-1] != 10:
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# We also are implicitly assuming this in the category cases above
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raise NotImplementedError
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assert all(s == 1 for s in shape[:-1])
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if typestr.endswith("_na"):
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fill_value = np.nan
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else:
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fill_value = 0.0
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values = SparseArray(
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[fill_value, fill_value, 1, 2, 3, fill_value, 4, 5, fill_value, 6],
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fill_value=fill_value,
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)
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arr = values.sp_values.view()
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arr += num_offset - 1
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else:
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raise ValueError(f'Unsupported typestr: "{typestr}"')
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values = maybe_coerce_values(values)
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return maker(values, placement=placement, ndim=len(shape))
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def create_single_mgr(typestr, num_rows=None):
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if num_rows is None:
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num_rows = N
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return SingleBlockManager(
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create_block(typestr, placement=slice(0, num_rows), item_shape=()),
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Index(np.arange(num_rows)),
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)
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def create_mgr(descr, item_shape=None):
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"""
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Construct BlockManager from string description.
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String description syntax looks similar to np.matrix initializer. It looks
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like this::
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a,b,c: f8; d,e,f: i8
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Rules are rather simple:
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* see list of supported datatypes in `create_block` method
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* components are semicolon-separated
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* each component is `NAME,NAME,NAME: DTYPE_ID`
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* whitespace around colons & semicolons are removed
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* components with same DTYPE_ID are combined into single block
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* to force multiple blocks with same dtype, use '-SUFFIX'::
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'a:f8-1; b:f8-2; c:f8-foobar'
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"""
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if item_shape is None:
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item_shape = (N,)
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offset = 0
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mgr_items = []
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block_placements = {}
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for d in descr.split(";"):
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d = d.strip()
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if not len(d):
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continue
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names, blockstr = d.partition(":")[::2]
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blockstr = blockstr.strip()
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names = names.strip().split(",")
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mgr_items.extend(names)
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placement = list(np.arange(len(names)) + offset)
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try:
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block_placements[blockstr].extend(placement)
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except KeyError:
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block_placements[blockstr] = placement
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offset += len(names)
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mgr_items = Index(mgr_items)
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blocks = []
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num_offset = 0
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for blockstr, placement in block_placements.items():
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typestr = blockstr.split("-")[0]
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blocks.append(
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create_block(
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typestr, placement, item_shape=item_shape, num_offset=num_offset
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)
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)
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num_offset += len(placement)
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sblocks = sorted(blocks, key=lambda b: b.mgr_locs[0])
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return BlockManager(
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tuple(sblocks),
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[mgr_items] + [Index(np.arange(n)) for n in item_shape],
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)
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@pytest.fixture
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def fblock():
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return create_block("float", [0, 2, 4])
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class TestBlock:
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def test_constructor(self):
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int32block = create_block("i4", [0])
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assert int32block.dtype == np.int32
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@pytest.mark.parametrize(
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"typ, data",
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[
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["float", [0, 2, 4]],
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["complex", [7]],
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["object", [1, 3]],
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["bool", [5]],
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],
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)
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def test_pickle(self, typ, data):
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blk = create_block(typ, data)
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assert_block_equal(tm.round_trip_pickle(blk), blk)
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def test_mgr_locs(self, fblock):
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assert isinstance(fblock.mgr_locs, BlockPlacement)
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tm.assert_numpy_array_equal(
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fblock.mgr_locs.as_array, np.array([0, 2, 4], dtype=np.intp)
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)
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def test_attrs(self, fblock):
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assert fblock.shape == fblock.values.shape
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assert fblock.dtype == fblock.values.dtype
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assert len(fblock) == len(fblock.values)
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def test_copy(self, fblock):
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cop = fblock.copy()
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assert cop is not fblock
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assert_block_equal(fblock, cop)
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def test_delete(self, fblock):
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newb = fblock.copy()
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locs = newb.mgr_locs
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nb = newb.delete(0)[0]
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assert newb.mgr_locs is locs
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assert nb is not newb
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tm.assert_numpy_array_equal(
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nb.mgr_locs.as_array, np.array([2, 4], dtype=np.intp)
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)
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assert not (newb.values[0] == 1).all()
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assert (nb.values[0] == 1).all()
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newb = fblock.copy()
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locs = newb.mgr_locs
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nb = newb.delete(1)
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assert len(nb) == 2
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assert newb.mgr_locs is locs
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tm.assert_numpy_array_equal(
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nb[0].mgr_locs.as_array, np.array([0], dtype=np.intp)
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)
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tm.assert_numpy_array_equal(
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nb[1].mgr_locs.as_array, np.array([4], dtype=np.intp)
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)
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assert not (newb.values[1] == 2).all()
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assert (nb[1].values[0] == 2).all()
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newb = fblock.copy()
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nb = newb.delete(2)
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assert len(nb) == 1
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tm.assert_numpy_array_equal(
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nb[0].mgr_locs.as_array, np.array([0, 2], dtype=np.intp)
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)
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assert (nb[0].values[1] == 1).all()
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newb = fblock.copy()
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with pytest.raises(IndexError, match=None):
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newb.delete(3)
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def test_delete_datetimelike(self):
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# dont use np.delete on values, as that will coerce from DTA/TDA to ndarray
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arr = np.arange(20, dtype="i8").reshape(5, 4).view("m8[ns]")
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df = DataFrame(arr)
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blk = df._mgr.blocks[0]
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assert isinstance(blk.values, TimedeltaArray)
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nb = blk.delete(1)
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assert len(nb) == 2
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assert isinstance(nb[0].values, TimedeltaArray)
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assert isinstance(nb[1].values, TimedeltaArray)
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df = DataFrame(arr.view("M8[ns]"))
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blk = df._mgr.blocks[0]
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assert isinstance(blk.values, DatetimeArray)
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nb = blk.delete([1, 3])
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assert len(nb) == 2
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assert isinstance(nb[0].values, DatetimeArray)
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assert isinstance(nb[1].values, DatetimeArray)
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def test_split(self):
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# GH#37799
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values = np.random.default_rng(2).standard_normal((3, 4))
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blk = new_block(values, placement=BlockPlacement([3, 1, 6]), ndim=2)
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result = blk._split()
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# check that we get views, not copies
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values[:] = -9999
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assert (blk.values == -9999).all()
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assert len(result) == 3
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expected = [
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new_block(values[[0]], placement=BlockPlacement([3]), ndim=2),
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new_block(values[[1]], placement=BlockPlacement([1]), ndim=2),
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new_block(values[[2]], placement=BlockPlacement([6]), ndim=2),
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]
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for res, exp in zip(result, expected):
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assert_block_equal(res, exp)
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class TestBlockManager:
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def test_attrs(self):
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mgr = create_mgr("a,b,c: f8-1; d,e,f: f8-2")
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assert mgr.nblocks == 2
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assert len(mgr) == 6
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def test_duplicate_ref_loc_failure(self):
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tmp_mgr = create_mgr("a:bool; a: f8")
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axes, blocks = tmp_mgr.axes, tmp_mgr.blocks
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blocks[0].mgr_locs = BlockPlacement(np.array([0]))
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blocks[1].mgr_locs = BlockPlacement(np.array([0]))
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# test trying to create block manager with overlapping ref locs
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msg = "Gaps in blk ref_locs"
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with pytest.raises(AssertionError, match=msg):
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mgr = BlockManager(blocks, axes)
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mgr._rebuild_blknos_and_blklocs()
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blocks[0].mgr_locs = BlockPlacement(np.array([0]))
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blocks[1].mgr_locs = BlockPlacement(np.array([1]))
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mgr = BlockManager(blocks, axes)
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mgr.iget(1)
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def test_pickle(self, mgr):
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mgr2 = tm.round_trip_pickle(mgr)
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tm.assert_frame_equal(
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DataFrame._from_mgr(mgr, axes=mgr.axes),
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DataFrame._from_mgr(mgr2, axes=mgr2.axes),
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)
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# GH2431
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assert hasattr(mgr2, "_is_consolidated")
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assert hasattr(mgr2, "_known_consolidated")
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# reset to False on load
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assert not mgr2._is_consolidated
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assert not mgr2._known_consolidated
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@pytest.mark.parametrize("mgr_string", ["a,a,a:f8", "a: f8; a: i8"])
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def test_non_unique_pickle(self, mgr_string):
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mgr = create_mgr(mgr_string)
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mgr2 = tm.round_trip_pickle(mgr)
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tm.assert_frame_equal(
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DataFrame._from_mgr(mgr, axes=mgr.axes),
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DataFrame._from_mgr(mgr2, axes=mgr2.axes),
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)
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def test_categorical_block_pickle(self):
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mgr = create_mgr("a: category")
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mgr2 = tm.round_trip_pickle(mgr)
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tm.assert_frame_equal(
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DataFrame._from_mgr(mgr, axes=mgr.axes),
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DataFrame._from_mgr(mgr2, axes=mgr2.axes),
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)
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smgr = create_single_mgr("category")
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smgr2 = tm.round_trip_pickle(smgr)
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tm.assert_series_equal(
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Series()._constructor_from_mgr(smgr, axes=smgr.axes),
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Series()._constructor_from_mgr(smgr2, axes=smgr2.axes),
|
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)
|
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def test_iget(self):
|
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cols = Index(list("abc"))
|
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values = np.random.default_rng(2).random((3, 3))
|
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block = new_block(
|
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values=values.copy(),
|
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placement=BlockPlacement(np.arange(3, dtype=np.intp)),
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ndim=values.ndim,
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)
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mgr = BlockManager(blocks=(block,), axes=[cols, Index(np.arange(3))])
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tm.assert_almost_equal(mgr.iget(0).internal_values(), values[0])
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tm.assert_almost_equal(mgr.iget(1).internal_values(), values[1])
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tm.assert_almost_equal(mgr.iget(2).internal_values(), values[2])
|
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|
|
def test_set(self):
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mgr = create_mgr("a,b,c: int", item_shape=(3,))
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mgr.insert(len(mgr.items), "d", np.array(["foo"] * 3))
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mgr.iset(1, np.array(["bar"] * 3))
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tm.assert_numpy_array_equal(mgr.iget(0).internal_values(), np.array([0] * 3))
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tm.assert_numpy_array_equal(
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mgr.iget(1).internal_values(), np.array(["bar"] * 3, dtype=np.object_)
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)
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tm.assert_numpy_array_equal(mgr.iget(2).internal_values(), np.array([2] * 3))
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tm.assert_numpy_array_equal(
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mgr.iget(3).internal_values(), np.array(["foo"] * 3, dtype=np.object_)
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)
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def test_set_change_dtype(self, mgr):
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mgr.insert(len(mgr.items), "baz", np.zeros(N, dtype=bool))
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mgr.iset(mgr.items.get_loc("baz"), np.repeat("foo", N))
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idx = mgr.items.get_loc("baz")
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assert mgr.iget(idx).dtype == np.object_
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mgr2 = mgr.consolidate()
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mgr2.iset(mgr2.items.get_loc("baz"), np.repeat("foo", N))
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idx = mgr2.items.get_loc("baz")
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assert mgr2.iget(idx).dtype == np.object_
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|
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mgr2.insert(
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len(mgr2.items),
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"quux",
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np.random.default_rng(2).standard_normal(N).astype(int),
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)
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idx = mgr2.items.get_loc("quux")
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assert mgr2.iget(idx).dtype == np.dtype(int)
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mgr2.iset(
|
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mgr2.items.get_loc("quux"), np.random.default_rng(2).standard_normal(N)
|
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)
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assert mgr2.iget(idx).dtype == np.float64
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|
|
|
def test_copy(self, mgr):
|
|
cp = mgr.copy(deep=False)
|
|
for blk, cp_blk in zip(mgr.blocks, cp.blocks):
|
|
# view assertion
|
|
tm.assert_equal(cp_blk.values, blk.values)
|
|
if isinstance(blk.values, np.ndarray):
|
|
assert cp_blk.values.base is blk.values.base
|
|
else:
|
|
# DatetimeTZBlock has DatetimeIndex values
|
|
assert cp_blk.values._ndarray.base is blk.values._ndarray.base
|
|
|
|
# copy(deep=True) consolidates, so the block-wise assertions will
|
|
# fail is mgr is not consolidated
|
|
mgr._consolidate_inplace()
|
|
cp = mgr.copy(deep=True)
|
|
for blk, cp_blk in zip(mgr.blocks, cp.blocks):
|
|
bvals = blk.values
|
|
cpvals = cp_blk.values
|
|
|
|
tm.assert_equal(cpvals, bvals)
|
|
|
|
if isinstance(cpvals, np.ndarray):
|
|
lbase = cpvals.base
|
|
rbase = bvals.base
|
|
else:
|
|
lbase = cpvals._ndarray.base
|
|
rbase = bvals._ndarray.base
|
|
|
|
# copy assertion we either have a None for a base or in case of
|
|
# some blocks it is an array (e.g. datetimetz), but was copied
|
|
if isinstance(cpvals, DatetimeArray):
|
|
assert (lbase is None and rbase is None) or (lbase is not rbase)
|
|
elif not isinstance(cpvals, np.ndarray):
|
|
assert lbase is not rbase
|
|
else:
|
|
assert lbase is None and rbase is None
|
|
|
|
def test_sparse(self):
|
|
mgr = create_mgr("a: sparse-1; b: sparse-2")
|
|
assert mgr.as_array().dtype == np.float64
|
|
|
|
def test_sparse_mixed(self):
|
|
mgr = create_mgr("a: sparse-1; b: sparse-2; c: f8")
|
|
assert len(mgr.blocks) == 3
|
|
assert isinstance(mgr, BlockManager)
|
|
|
|
@pytest.mark.parametrize(
|
|
"mgr_string, dtype",
|
|
[("c: f4; d: f2", np.float32), ("c: f4; d: f2; e: f8", np.float64)],
|
|
)
|
|
def test_as_array_float(self, mgr_string, dtype):
|
|
mgr = create_mgr(mgr_string)
|
|
assert mgr.as_array().dtype == dtype
|
|
|
|
@pytest.mark.parametrize(
|
|
"mgr_string, dtype",
|
|
[
|
|
("a: bool-1; b: bool-2", np.bool_),
|
|
("a: i8-1; b: i8-2; c: i4; d: i2; e: u1", np.int64),
|
|
("c: i4; d: i2; e: u1", np.int32),
|
|
],
|
|
)
|
|
def test_as_array_int_bool(self, mgr_string, dtype):
|
|
mgr = create_mgr(mgr_string)
|
|
assert mgr.as_array().dtype == dtype
|
|
|
|
def test_as_array_datetime(self):
|
|
mgr = create_mgr("h: datetime-1; g: datetime-2")
|
|
assert mgr.as_array().dtype == "M8[ns]"
|
|
|
|
def test_as_array_datetime_tz(self):
|
|
mgr = create_mgr("h: M8[ns, US/Eastern]; g: M8[ns, CET]")
|
|
assert mgr.iget(0).dtype == "datetime64[ns, US/Eastern]"
|
|
assert mgr.iget(1).dtype == "datetime64[ns, CET]"
|
|
assert mgr.as_array().dtype == "object"
|
|
|
|
@pytest.mark.parametrize("t", ["float16", "float32", "float64", "int32", "int64"])
|
|
def test_astype(self, t):
|
|
# coerce all
|
|
mgr = create_mgr("c: f4; d: f2; e: f8")
|
|
|
|
t = np.dtype(t)
|
|
tmgr = mgr.astype(t)
|
|
assert tmgr.iget(0).dtype.type == t
|
|
assert tmgr.iget(1).dtype.type == t
|
|
assert tmgr.iget(2).dtype.type == t
|
|
|
|
# mixed
|
|
mgr = create_mgr("a,b: object; c: bool; d: datetime; e: f4; f: f2; g: f8")
|
|
|
|
t = np.dtype(t)
|
|
tmgr = mgr.astype(t, errors="ignore")
|
|
assert tmgr.iget(2).dtype.type == t
|
|
assert tmgr.iget(4).dtype.type == t
|
|
assert tmgr.iget(5).dtype.type == t
|
|
assert tmgr.iget(6).dtype.type == t
|
|
|
|
assert tmgr.iget(0).dtype.type == np.object_
|
|
assert tmgr.iget(1).dtype.type == np.object_
|
|
if t != np.int64:
|
|
assert tmgr.iget(3).dtype.type == np.datetime64
|
|
else:
|
|
assert tmgr.iget(3).dtype.type == t
|
|
|
|
def test_convert(self, using_infer_string):
|
|
def _compare(old_mgr, new_mgr):
|
|
"""compare the blocks, numeric compare ==, object don't"""
|
|
old_blocks = set(old_mgr.blocks)
|
|
new_blocks = set(new_mgr.blocks)
|
|
assert len(old_blocks) == len(new_blocks)
|
|
|
|
# compare non-numeric
|
|
for b in old_blocks:
|
|
found = False
|
|
for nb in new_blocks:
|
|
if (b.values == nb.values).all():
|
|
found = True
|
|
break
|
|
assert found
|
|
|
|
for b in new_blocks:
|
|
found = False
|
|
for ob in old_blocks:
|
|
if (b.values == ob.values).all():
|
|
found = True
|
|
break
|
|
assert found
|
|
|
|
# noops
|
|
mgr = create_mgr("f: i8; g: f8")
|
|
new_mgr = mgr.convert(copy=True)
|
|
_compare(mgr, new_mgr)
|
|
|
|
# convert
|
|
mgr = create_mgr("a,b,foo: object; f: i8; g: f8")
|
|
mgr.iset(0, np.array(["1"] * N, dtype=np.object_))
|
|
mgr.iset(1, np.array(["2."] * N, dtype=np.object_))
|
|
mgr.iset(2, np.array(["foo."] * N, dtype=np.object_))
|
|
new_mgr = mgr.convert(copy=True)
|
|
dtype = "string[pyarrow_numpy]" if using_infer_string else np.object_
|
|
assert new_mgr.iget(0).dtype == dtype
|
|
assert new_mgr.iget(1).dtype == dtype
|
|
assert new_mgr.iget(2).dtype == dtype
|
|
assert new_mgr.iget(3).dtype == np.int64
|
|
assert new_mgr.iget(4).dtype == np.float64
|
|
|
|
mgr = create_mgr(
|
|
"a,b,foo: object; f: i4; bool: bool; dt: datetime; i: i8; g: f8; h: f2"
|
|
)
|
|
mgr.iset(0, np.array(["1"] * N, dtype=np.object_))
|
|
mgr.iset(1, np.array(["2."] * N, dtype=np.object_))
|
|
mgr.iset(2, np.array(["foo."] * N, dtype=np.object_))
|
|
new_mgr = mgr.convert(copy=True)
|
|
assert new_mgr.iget(0).dtype == dtype
|
|
assert new_mgr.iget(1).dtype == dtype
|
|
assert new_mgr.iget(2).dtype == dtype
|
|
assert new_mgr.iget(3).dtype == np.int32
|
|
assert new_mgr.iget(4).dtype == np.bool_
|
|
assert new_mgr.iget(5).dtype.type, np.datetime64
|
|
assert new_mgr.iget(6).dtype == np.int64
|
|
assert new_mgr.iget(7).dtype == np.float64
|
|
assert new_mgr.iget(8).dtype == np.float16
|
|
|
|
def test_interleave(self):
|
|
# self
|
|
for dtype in ["f8", "i8", "object", "bool", "complex", "M8[ns]", "m8[ns]"]:
|
|
mgr = create_mgr(f"a: {dtype}")
|
|
assert mgr.as_array().dtype == dtype
|
|
mgr = create_mgr(f"a: {dtype}; b: {dtype}")
|
|
assert mgr.as_array().dtype == dtype
|
|
|
|
@pytest.mark.parametrize(
|
|
"mgr_string, dtype",
|
|
[
|
|
("a: category", "i8"),
|
|
("a: category; b: category", "i8"),
|
|
("a: category; b: category2", "object"),
|
|
("a: category2", "object"),
|
|
("a: category2; b: category2", "object"),
|
|
("a: f8", "f8"),
|
|
("a: f8; b: i8", "f8"),
|
|
("a: f4; b: i8", "f8"),
|
|
("a: f4; b: i8; d: object", "object"),
|
|
("a: bool; b: i8", "object"),
|
|
("a: complex", "complex"),
|
|
("a: f8; b: category", "object"),
|
|
("a: M8[ns]; b: category", "object"),
|
|
("a: M8[ns]; b: bool", "object"),
|
|
("a: M8[ns]; b: i8", "object"),
|
|
("a: m8[ns]; b: bool", "object"),
|
|
("a: m8[ns]; b: i8", "object"),
|
|
("a: M8[ns]; b: m8[ns]", "object"),
|
|
],
|
|
)
|
|
def test_interleave_dtype(self, mgr_string, dtype):
|
|
# will be converted according the actual dtype of the underlying
|
|
mgr = create_mgr("a: category")
|
|
assert mgr.as_array().dtype == "i8"
|
|
mgr = create_mgr("a: category; b: category2")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: category2")
|
|
assert mgr.as_array().dtype == "object"
|
|
|
|
# combinations
|
|
mgr = create_mgr("a: f8")
|
|
assert mgr.as_array().dtype == "f8"
|
|
mgr = create_mgr("a: f8; b: i8")
|
|
assert mgr.as_array().dtype == "f8"
|
|
mgr = create_mgr("a: f4; b: i8")
|
|
assert mgr.as_array().dtype == "f8"
|
|
mgr = create_mgr("a: f4; b: i8; d: object")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: bool; b: i8")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: complex")
|
|
assert mgr.as_array().dtype == "complex"
|
|
mgr = create_mgr("a: f8; b: category")
|
|
assert mgr.as_array().dtype == "f8"
|
|
mgr = create_mgr("a: M8[ns]; b: category")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: M8[ns]; b: bool")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: M8[ns]; b: i8")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: m8[ns]; b: bool")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: m8[ns]; b: i8")
|
|
assert mgr.as_array().dtype == "object"
|
|
mgr = create_mgr("a: M8[ns]; b: m8[ns]")
|
|
assert mgr.as_array().dtype == "object"
|
|
|
|
def test_consolidate_ordering_issues(self, mgr):
|
|
mgr.iset(mgr.items.get_loc("f"), np.random.default_rng(2).standard_normal(N))
|
|
mgr.iset(mgr.items.get_loc("d"), np.random.default_rng(2).standard_normal(N))
|
|
mgr.iset(mgr.items.get_loc("b"), np.random.default_rng(2).standard_normal(N))
|
|
mgr.iset(mgr.items.get_loc("g"), np.random.default_rng(2).standard_normal(N))
|
|
mgr.iset(mgr.items.get_loc("h"), np.random.default_rng(2).standard_normal(N))
|
|
|
|
# we have datetime/tz blocks in mgr
|
|
cons = mgr.consolidate()
|
|
assert cons.nblocks == 4
|
|
cons = mgr.consolidate().get_numeric_data()
|
|
assert cons.nblocks == 1
|
|
assert isinstance(cons.blocks[0].mgr_locs, BlockPlacement)
|
|
tm.assert_numpy_array_equal(
|
|
cons.blocks[0].mgr_locs.as_array, np.arange(len(cons.items), dtype=np.intp)
|
|
)
|
|
|
|
def test_reindex_items(self):
|
|
# mgr is not consolidated, f8 & f8-2 blocks
|
|
mgr = create_mgr("a: f8; b: i8; c: f8; d: i8; e: f8; f: bool; g: f8-2")
|
|
|
|
reindexed = mgr.reindex_axis(["g", "c", "a", "d"], axis=0)
|
|
# reindex_axis does not consolidate_inplace, as that risks failing to
|
|
# invalidate _item_cache
|
|
assert not reindexed.is_consolidated()
|
|
|
|
tm.assert_index_equal(reindexed.items, Index(["g", "c", "a", "d"]))
|
|
tm.assert_almost_equal(
|
|
mgr.iget(6).internal_values(), reindexed.iget(0).internal_values()
|
|
)
|
|
tm.assert_almost_equal(
|
|
mgr.iget(2).internal_values(), reindexed.iget(1).internal_values()
|
|
)
|
|
tm.assert_almost_equal(
|
|
mgr.iget(0).internal_values(), reindexed.iget(2).internal_values()
|
|
)
|
|
tm.assert_almost_equal(
|
|
mgr.iget(3).internal_values(), reindexed.iget(3).internal_values()
|
|
)
|
|
|
|
def test_get_numeric_data(self, using_copy_on_write):
|
|
mgr = create_mgr(
|
|
"int: int; float: float; complex: complex;"
|
|
"str: object; bool: bool; obj: object; dt: datetime",
|
|
item_shape=(3,),
|
|
)
|
|
mgr.iset(5, np.array([1, 2, 3], dtype=np.object_))
|
|
|
|
numeric = mgr.get_numeric_data()
|
|
tm.assert_index_equal(numeric.items, Index(["int", "float", "complex", "bool"]))
|
|
tm.assert_almost_equal(
|
|
mgr.iget(mgr.items.get_loc("float")).internal_values(),
|
|
numeric.iget(numeric.items.get_loc("float")).internal_values(),
|
|
)
|
|
|
|
# Check sharing
|
|
numeric.iset(
|
|
numeric.items.get_loc("float"),
|
|
np.array([100.0, 200.0, 300.0]),
|
|
inplace=True,
|
|
)
|
|
if using_copy_on_write:
|
|
tm.assert_almost_equal(
|
|
mgr.iget(mgr.items.get_loc("float")).internal_values(),
|
|
np.array([1.0, 1.0, 1.0]),
|
|
)
|
|
else:
|
|
tm.assert_almost_equal(
|
|
mgr.iget(mgr.items.get_loc("float")).internal_values(),
|
|
np.array([100.0, 200.0, 300.0]),
|
|
)
|
|
|
|
def test_get_bool_data(self, using_copy_on_write):
|
|
mgr = create_mgr(
|
|
"int: int; float: float; complex: complex;"
|
|
"str: object; bool: bool; obj: object; dt: datetime",
|
|
item_shape=(3,),
|
|
)
|
|
mgr.iset(6, np.array([True, False, True], dtype=np.object_))
|
|
|
|
bools = mgr.get_bool_data()
|
|
tm.assert_index_equal(bools.items, Index(["bool"]))
|
|
tm.assert_almost_equal(
|
|
mgr.iget(mgr.items.get_loc("bool")).internal_values(),
|
|
bools.iget(bools.items.get_loc("bool")).internal_values(),
|
|
)
|
|
|
|
bools.iset(0, np.array([True, False, True]), inplace=True)
|
|
if using_copy_on_write:
|
|
tm.assert_numpy_array_equal(
|
|
mgr.iget(mgr.items.get_loc("bool")).internal_values(),
|
|
np.array([True, True, True]),
|
|
)
|
|
else:
|
|
tm.assert_numpy_array_equal(
|
|
mgr.iget(mgr.items.get_loc("bool")).internal_values(),
|
|
np.array([True, False, True]),
|
|
)
|
|
|
|
def test_unicode_repr_doesnt_raise(self):
|
|
repr(create_mgr("b,\u05d0: object"))
|
|
|
|
@pytest.mark.parametrize(
|
|
"mgr_string", ["a,b,c: i8-1; d,e,f: i8-2", "a,a,a: i8-1; b,b,b: i8-2"]
|
|
)
|
|
def test_equals(self, mgr_string):
|
|
# unique items
|
|
bm1 = create_mgr(mgr_string)
|
|
bm2 = BlockManager(bm1.blocks[::-1], bm1.axes)
|
|
assert bm1.equals(bm2)
|
|
|
|
@pytest.mark.parametrize(
|
|
"mgr_string",
|
|
[
|
|
"a:i8;b:f8", # basic case
|
|
"a:i8;b:f8;c:c8;d:b", # many types
|
|
"a:i8;e:dt;f:td;g:string", # more types
|
|
"a:i8;b:category;c:category2", # categories
|
|
"c:sparse;d:sparse_na;b:f8", # sparse
|
|
],
|
|
)
|
|
def test_equals_block_order_different_dtypes(self, mgr_string):
|
|
# GH 9330
|
|
bm = create_mgr(mgr_string)
|
|
block_perms = itertools.permutations(bm.blocks)
|
|
for bm_perm in block_perms:
|
|
bm_this = BlockManager(tuple(bm_perm), bm.axes)
|
|
assert bm.equals(bm_this)
|
|
assert bm_this.equals(bm)
|
|
|
|
def test_single_mgr_ctor(self):
|
|
mgr = create_single_mgr("f8", num_rows=5)
|
|
assert mgr.external_values().tolist() == [0.0, 1.0, 2.0, 3.0, 4.0]
|
|
|
|
@pytest.mark.parametrize("value", [1, "True", [1, 2, 3], 5.0])
|
|
def test_validate_bool_args(self, value):
|
|
bm1 = create_mgr("a,b,c: i8-1; d,e,f: i8-2")
|
|
|
|
msg = (
|
|
'For argument "inplace" expected type bool, '
|
|
f"received type {type(value).__name__}."
|
|
)
|
|
with pytest.raises(ValueError, match=msg):
|
|
bm1.replace_list([1], [2], inplace=value)
|
|
|
|
def test_iset_split_block(self):
|
|
bm = create_mgr("a,b,c: i8; d: f8")
|
|
bm._iset_split_block(0, np.array([0]))
|
|
tm.assert_numpy_array_equal(
|
|
bm.blklocs, np.array([0, 0, 1, 0], dtype="int64" if IS64 else "int32")
|
|
)
|
|
# First indexer currently does not have a block associated with it in case
|
|
tm.assert_numpy_array_equal(
|
|
bm.blknos, np.array([0, 0, 0, 1], dtype="int64" if IS64 else "int32")
|
|
)
|
|
assert len(bm.blocks) == 2
|
|
|
|
def test_iset_split_block_values(self):
|
|
bm = create_mgr("a,b,c: i8; d: f8")
|
|
bm._iset_split_block(0, np.array([0]), np.array([list(range(10))]))
|
|
tm.assert_numpy_array_equal(
|
|
bm.blklocs, np.array([0, 0, 1, 0], dtype="int64" if IS64 else "int32")
|
|
)
|
|
# First indexer currently does not have a block associated with it in case
|
|
tm.assert_numpy_array_equal(
|
|
bm.blknos, np.array([0, 2, 2, 1], dtype="int64" if IS64 else "int32")
|
|
)
|
|
assert len(bm.blocks) == 3
|
|
|
|
|
|
def _as_array(mgr):
|
|
if mgr.ndim == 1:
|
|
return mgr.external_values()
|
|
return mgr.as_array().T
|
|
|
|
|
|
class TestIndexing:
|
|
# Nosetests-style data-driven tests.
|
|
#
|
|
# This test applies different indexing routines to block managers and
|
|
# compares the outcome to the result of same operations on np.ndarray.
|
|
#
|
|
# NOTE: sparse (SparseBlock with fill_value != np.nan) fail a lot of tests
|
|
# and are disabled.
|
|
|
|
MANAGERS = [
|
|
create_single_mgr("f8", N),
|
|
create_single_mgr("i8", N),
|
|
# 2-dim
|
|
create_mgr("a,b,c,d,e,f: f8", item_shape=(N,)),
|
|
create_mgr("a,b,c,d,e,f: i8", item_shape=(N,)),
|
|
create_mgr("a,b: f8; c,d: i8; e,f: string", item_shape=(N,)),
|
|
create_mgr("a,b: f8; c,d: i8; e,f: f8", item_shape=(N,)),
|
|
]
|
|
|
|
@pytest.mark.parametrize("mgr", MANAGERS)
|
|
def test_get_slice(self, mgr):
|
|
def assert_slice_ok(mgr, axis, slobj):
|
|
mat = _as_array(mgr)
|
|
|
|
# we maybe using an ndarray to test slicing and
|
|
# might not be the full length of the axis
|
|
if isinstance(slobj, np.ndarray):
|
|
ax = mgr.axes[axis]
|
|
if len(ax) and len(slobj) and len(slobj) != len(ax):
|
|
slobj = np.concatenate(
|
|
[slobj, np.zeros(len(ax) - len(slobj), dtype=bool)]
|
|
)
|
|
|
|
if isinstance(slobj, slice):
|
|
sliced = mgr.get_slice(slobj, axis=axis)
|
|
elif (
|
|
mgr.ndim == 1
|
|
and axis == 0
|
|
and isinstance(slobj, np.ndarray)
|
|
and slobj.dtype == bool
|
|
):
|
|
sliced = mgr.get_rows_with_mask(slobj)
|
|
else:
|
|
# BlockManager doesn't support non-slice, SingleBlockManager
|
|
# doesn't support axis > 0
|
|
raise TypeError(slobj)
|
|
|
|
mat_slobj = (slice(None),) * axis + (slobj,)
|
|
tm.assert_numpy_array_equal(
|
|
mat[mat_slobj], _as_array(sliced), check_dtype=False
|
|
)
|
|
tm.assert_index_equal(mgr.axes[axis][slobj], sliced.axes[axis])
|
|
|
|
assert mgr.ndim <= 2, mgr.ndim
|
|
for ax in range(mgr.ndim):
|
|
# slice
|
|
assert_slice_ok(mgr, ax, slice(None))
|
|
assert_slice_ok(mgr, ax, slice(3))
|
|
assert_slice_ok(mgr, ax, slice(100))
|
|
assert_slice_ok(mgr, ax, slice(1, 4))
|
|
assert_slice_ok(mgr, ax, slice(3, 0, -2))
|
|
|
|
if mgr.ndim < 2:
|
|
# 2D only support slice objects
|
|
|
|
# boolean mask
|
|
assert_slice_ok(mgr, ax, np.ones(mgr.shape[ax], dtype=np.bool_))
|
|
assert_slice_ok(mgr, ax, np.zeros(mgr.shape[ax], dtype=np.bool_))
|
|
|
|
if mgr.shape[ax] >= 3:
|
|
assert_slice_ok(mgr, ax, np.arange(mgr.shape[ax]) % 3 == 0)
|
|
assert_slice_ok(
|
|
mgr, ax, np.array([True, True, False], dtype=np.bool_)
|
|
)
|
|
|
|
@pytest.mark.parametrize("mgr", MANAGERS)
|
|
def test_take(self, mgr):
|
|
def assert_take_ok(mgr, axis, indexer):
|
|
mat = _as_array(mgr)
|
|
taken = mgr.take(indexer, axis)
|
|
tm.assert_numpy_array_equal(
|
|
np.take(mat, indexer, axis), _as_array(taken), check_dtype=False
|
|
)
|
|
tm.assert_index_equal(mgr.axes[axis].take(indexer), taken.axes[axis])
|
|
|
|
for ax in range(mgr.ndim):
|
|
# take/fancy indexer
|
|
assert_take_ok(mgr, ax, indexer=np.array([], dtype=np.intp))
|
|
assert_take_ok(mgr, ax, indexer=np.array([0, 0, 0], dtype=np.intp))
|
|
assert_take_ok(
|
|
mgr, ax, indexer=np.array(list(range(mgr.shape[ax])), dtype=np.intp)
|
|
)
|
|
|
|
if mgr.shape[ax] >= 3:
|
|
assert_take_ok(mgr, ax, indexer=np.array([0, 1, 2], dtype=np.intp))
|
|
assert_take_ok(mgr, ax, indexer=np.array([-1, -2, -3], dtype=np.intp))
|
|
|
|
@pytest.mark.parametrize("mgr", MANAGERS)
|
|
@pytest.mark.parametrize("fill_value", [None, np.nan, 100.0])
|
|
def test_reindex_axis(self, fill_value, mgr):
|
|
def assert_reindex_axis_is_ok(mgr, axis, new_labels, fill_value):
|
|
mat = _as_array(mgr)
|
|
indexer = mgr.axes[axis].get_indexer_for(new_labels)
|
|
|
|
reindexed = mgr.reindex_axis(new_labels, axis, fill_value=fill_value)
|
|
tm.assert_numpy_array_equal(
|
|
algos.take_nd(mat, indexer, axis, fill_value=fill_value),
|
|
_as_array(reindexed),
|
|
check_dtype=False,
|
|
)
|
|
tm.assert_index_equal(reindexed.axes[axis], new_labels)
|
|
|
|
for ax in range(mgr.ndim):
|
|
assert_reindex_axis_is_ok(mgr, ax, Index([]), fill_value)
|
|
assert_reindex_axis_is_ok(mgr, ax, mgr.axes[ax], fill_value)
|
|
assert_reindex_axis_is_ok(mgr, ax, mgr.axes[ax][[0, 0, 0]], fill_value)
|
|
assert_reindex_axis_is_ok(mgr, ax, Index(["foo", "bar", "baz"]), fill_value)
|
|
assert_reindex_axis_is_ok(
|
|
mgr, ax, Index(["foo", mgr.axes[ax][0], "baz"]), fill_value
|
|
)
|
|
|
|
if mgr.shape[ax] >= 3:
|
|
assert_reindex_axis_is_ok(mgr, ax, mgr.axes[ax][:-3], fill_value)
|
|
assert_reindex_axis_is_ok(mgr, ax, mgr.axes[ax][-3::-1], fill_value)
|
|
assert_reindex_axis_is_ok(
|
|
mgr, ax, mgr.axes[ax][[0, 1, 2, 0, 1, 2]], fill_value
|
|
)
|
|
|
|
@pytest.mark.parametrize("mgr", MANAGERS)
|
|
@pytest.mark.parametrize("fill_value", [None, np.nan, 100.0])
|
|
def test_reindex_indexer(self, fill_value, mgr):
|
|
def assert_reindex_indexer_is_ok(mgr, axis, new_labels, indexer, fill_value):
|
|
mat = _as_array(mgr)
|
|
reindexed_mat = algos.take_nd(mat, indexer, axis, fill_value=fill_value)
|
|
reindexed = mgr.reindex_indexer(
|
|
new_labels, indexer, axis, fill_value=fill_value
|
|
)
|
|
tm.assert_numpy_array_equal(
|
|
reindexed_mat, _as_array(reindexed), check_dtype=False
|
|
)
|
|
tm.assert_index_equal(reindexed.axes[axis], new_labels)
|
|
|
|
for ax in range(mgr.ndim):
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, Index([]), np.array([], dtype=np.intp), fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, mgr.axes[ax], np.arange(mgr.shape[ax]), fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr,
|
|
ax,
|
|
Index(["foo"] * mgr.shape[ax]),
|
|
np.arange(mgr.shape[ax]),
|
|
fill_value,
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, mgr.axes[ax][::-1], np.arange(mgr.shape[ax]), fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, mgr.axes[ax], np.arange(mgr.shape[ax])[::-1], fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, Index(["foo", "bar", "baz"]), np.array([0, 0, 0]), fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr, ax, Index(["foo", "bar", "baz"]), np.array([-1, 0, -1]), fill_value
|
|
)
|
|
assert_reindex_indexer_is_ok(
|
|
mgr,
|
|
ax,
|
|
Index(["foo", mgr.axes[ax][0], "baz"]),
|
|
np.array([-1, -1, -1]),
|
|
fill_value,
|
|
)
|
|
|
|
if mgr.shape[ax] >= 3:
|
|
assert_reindex_indexer_is_ok(
|
|
mgr,
|
|
ax,
|
|
Index(["foo", "bar", "baz"]),
|
|
np.array([0, 1, 2]),
|
|
fill_value,
|
|
)
|
|
|
|
|
|
class TestBlockPlacement:
|
|
@pytest.mark.parametrize(
|
|
"slc, expected",
|
|
[
|
|
(slice(0, 4), 4),
|
|
(slice(0, 4, 2), 2),
|
|
(slice(0, 3, 2), 2),
|
|
(slice(0, 1, 2), 1),
|
|
(slice(1, 0, -1), 1),
|
|
],
|
|
)
|
|
def test_slice_len(self, slc, expected):
|
|
assert len(BlockPlacement(slc)) == expected
|
|
|
|
@pytest.mark.parametrize("slc", [slice(1, 1, 0), slice(1, 2, 0)])
|
|
def test_zero_step_raises(self, slc):
|
|
msg = "slice step cannot be zero"
|
|
with pytest.raises(ValueError, match=msg):
|
|
BlockPlacement(slc)
|
|
|
|
def test_slice_canonize_negative_stop(self):
|
|
# GH#37524 negative stop is OK with negative step and positive start
|
|
slc = slice(3, -1, -2)
|
|
|
|
bp = BlockPlacement(slc)
|
|
assert bp.indexer == slice(3, None, -2)
|
|
|
|
@pytest.mark.parametrize(
|
|
"slc",
|
|
[
|
|
slice(None, None),
|
|
slice(10, None),
|
|
slice(None, None, -1),
|
|
slice(None, 10, -1),
|
|
# These are "unbounded" because negative index will
|
|
# change depending on container shape.
|
|
slice(-1, None),
|
|
slice(None, -1),
|
|
slice(-1, -1),
|
|
slice(-1, None, -1),
|
|
slice(None, -1, -1),
|
|
slice(-1, -1, -1),
|
|
],
|
|
)
|
|
def test_unbounded_slice_raises(self, slc):
|
|
msg = "unbounded slice"
|
|
with pytest.raises(ValueError, match=msg):
|
|
BlockPlacement(slc)
|
|
|
|
@pytest.mark.parametrize(
|
|
"slc",
|
|
[
|
|
slice(0, 0),
|
|
slice(100, 0),
|
|
slice(100, 100),
|
|
slice(100, 100, -1),
|
|
slice(0, 100, -1),
|
|
],
|
|
)
|
|
def test_not_slice_like_slices(self, slc):
|
|
assert not BlockPlacement(slc).is_slice_like
|
|
|
|
@pytest.mark.parametrize(
|
|
"arr, slc",
|
|
[
|
|
([0], slice(0, 1, 1)),
|
|
([100], slice(100, 101, 1)),
|
|
([0, 1, 2], slice(0, 3, 1)),
|
|
([0, 5, 10], slice(0, 15, 5)),
|
|
([0, 100], slice(0, 200, 100)),
|
|
([2, 1], slice(2, 0, -1)),
|
|
],
|
|
)
|
|
def test_array_to_slice_conversion(self, arr, slc):
|
|
assert BlockPlacement(arr).as_slice == slc
|
|
|
|
@pytest.mark.parametrize(
|
|
"arr",
|
|
[
|
|
[],
|
|
[-1],
|
|
[-1, -2, -3],
|
|
[-10],
|
|
[-1],
|
|
[-1, 0, 1, 2],
|
|
[-2, 0, 2, 4],
|
|
[1, 0, -1],
|
|
[1, 1, 1],
|
|
],
|
|
)
|
|
def test_not_slice_like_arrays(self, arr):
|
|
assert not BlockPlacement(arr).is_slice_like
|
|
|
|
@pytest.mark.parametrize(
|
|
"slc, expected",
|
|
[(slice(0, 3), [0, 1, 2]), (slice(0, 0), []), (slice(3, 0), [])],
|
|
)
|
|
def test_slice_iter(self, slc, expected):
|
|
assert list(BlockPlacement(slc)) == expected
|
|
|
|
@pytest.mark.parametrize(
|
|
"slc, arr",
|
|
[
|
|
(slice(0, 3), [0, 1, 2]),
|
|
(slice(0, 0), []),
|
|
(slice(3, 0), []),
|
|
(slice(3, 0, -1), [3, 2, 1]),
|
|
],
|
|
)
|
|
def test_slice_to_array_conversion(self, slc, arr):
|
|
tm.assert_numpy_array_equal(
|
|
BlockPlacement(slc).as_array, np.asarray(arr, dtype=np.intp)
|
|
)
|
|
|
|
def test_blockplacement_add(self):
|
|
bpl = BlockPlacement(slice(0, 5))
|
|
assert bpl.add(1).as_slice == slice(1, 6, 1)
|
|
assert bpl.add(np.arange(5)).as_slice == slice(0, 10, 2)
|
|
assert list(bpl.add(np.arange(5, 0, -1))) == [5, 5, 5, 5, 5]
|
|
|
|
@pytest.mark.parametrize(
|
|
"val, inc, expected",
|
|
[
|
|
(slice(0, 0), 0, []),
|
|
(slice(1, 4), 0, [1, 2, 3]),
|
|
(slice(3, 0, -1), 0, [3, 2, 1]),
|
|
([1, 2, 4], 0, [1, 2, 4]),
|
|
(slice(0, 0), 10, []),
|
|
(slice(1, 4), 10, [11, 12, 13]),
|
|
(slice(3, 0, -1), 10, [13, 12, 11]),
|
|
([1, 2, 4], 10, [11, 12, 14]),
|
|
(slice(0, 0), -1, []),
|
|
(slice(1, 4), -1, [0, 1, 2]),
|
|
([1, 2, 4], -1, [0, 1, 3]),
|
|
],
|
|
)
|
|
def test_blockplacement_add_int(self, val, inc, expected):
|
|
assert list(BlockPlacement(val).add(inc)) == expected
|
|
|
|
@pytest.mark.parametrize("val", [slice(1, 4), [1, 2, 4]])
|
|
def test_blockplacement_add_int_raises(self, val):
|
|
msg = "iadd causes length change"
|
|
with pytest.raises(ValueError, match=msg):
|
|
BlockPlacement(val).add(-10)
|
|
|
|
|
|
class TestCanHoldElement:
|
|
@pytest.fixture(
|
|
params=[
|
|
lambda x: x,
|
|
lambda x: x.to_series(),
|
|
lambda x: x._data,
|
|
lambda x: list(x),
|
|
lambda x: x.astype(object),
|
|
lambda x: np.asarray(x),
|
|
lambda x: x[0],
|
|
lambda x: x[:0],
|
|
]
|
|
)
|
|
def element(self, request):
|
|
"""
|
|
Functions that take an Index and return an element that should have
|
|
blk._can_hold_element(element) for a Block with this index's dtype.
|
|
"""
|
|
return request.param
|
|
|
|
def test_datetime_block_can_hold_element(self):
|
|
block = create_block("datetime", [0])
|
|
|
|
assert block._can_hold_element([])
|
|
|
|
# We will check that block._can_hold_element iff arr.__setitem__ works
|
|
arr = pd.array(block.values.ravel())
|
|
|
|
# coerce None
|
|
assert block._can_hold_element(None)
|
|
arr[0] = None
|
|
assert arr[0] is pd.NaT
|
|
|
|
# coerce different types of datetime objects
|
|
vals = [np.datetime64("2010-10-10"), datetime(2010, 10, 10)]
|
|
for val in vals:
|
|
assert block._can_hold_element(val)
|
|
arr[0] = val
|
|
|
|
val = date(2010, 10, 10)
|
|
assert not block._can_hold_element(val)
|
|
|
|
msg = (
|
|
"value should be a 'Timestamp', 'NaT', "
|
|
"or array of those. Got 'date' instead."
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
arr[0] = val
|
|
|
|
@pytest.mark.parametrize("dtype", [np.int64, np.uint64, np.float64])
|
|
def test_interval_can_hold_element_emptylist(self, dtype, element):
|
|
arr = np.array([1, 3, 4], dtype=dtype)
|
|
ii = IntervalIndex.from_breaks(arr)
|
|
blk = new_block(ii._data, BlockPlacement([1]), ndim=2)
|
|
|
|
assert blk._can_hold_element([])
|
|
# TODO: check this holds for all blocks
|
|
|
|
@pytest.mark.parametrize("dtype", [np.int64, np.uint64, np.float64])
|
|
def test_interval_can_hold_element(self, dtype, element):
|
|
arr = np.array([1, 3, 4, 9], dtype=dtype)
|
|
ii = IntervalIndex.from_breaks(arr)
|
|
blk = new_block(ii._data, BlockPlacement([1]), ndim=2)
|
|
|
|
elem = element(ii)
|
|
self.check_series_setitem(elem, ii, True)
|
|
assert blk._can_hold_element(elem)
|
|
|
|
# Careful: to get the expected Series-inplace behavior we need
|
|
# `elem` to not have the same length as `arr`
|
|
ii2 = IntervalIndex.from_breaks(arr[:-1], closed="neither")
|
|
elem = element(ii2)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
self.check_series_setitem(elem, ii, False)
|
|
assert not blk._can_hold_element(elem)
|
|
|
|
ii3 = IntervalIndex.from_breaks([Timestamp(1), Timestamp(3), Timestamp(4)])
|
|
elem = element(ii3)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
self.check_series_setitem(elem, ii, False)
|
|
assert not blk._can_hold_element(elem)
|
|
|
|
ii4 = IntervalIndex.from_breaks([Timedelta(1), Timedelta(3), Timedelta(4)])
|
|
elem = element(ii4)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
self.check_series_setitem(elem, ii, False)
|
|
assert not blk._can_hold_element(elem)
|
|
|
|
def test_period_can_hold_element_emptylist(self):
|
|
pi = period_range("2016", periods=3, freq="Y")
|
|
blk = new_block(pi._data.reshape(1, 3), BlockPlacement([1]), ndim=2)
|
|
|
|
assert blk._can_hold_element([])
|
|
|
|
def test_period_can_hold_element(self, element):
|
|
pi = period_range("2016", periods=3, freq="Y")
|
|
|
|
elem = element(pi)
|
|
self.check_series_setitem(elem, pi, True)
|
|
|
|
# Careful: to get the expected Series-inplace behavior we need
|
|
# `elem` to not have the same length as `arr`
|
|
pi2 = pi.asfreq("D")[:-1]
|
|
elem = element(pi2)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
self.check_series_setitem(elem, pi, False)
|
|
|
|
dti = pi.to_timestamp("s")[:-1]
|
|
elem = element(dti)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
self.check_series_setitem(elem, pi, False)
|
|
|
|
def check_can_hold_element(self, obj, elem, inplace: bool):
|
|
blk = obj._mgr.blocks[0]
|
|
if inplace:
|
|
assert blk._can_hold_element(elem)
|
|
else:
|
|
assert not blk._can_hold_element(elem)
|
|
|
|
def check_series_setitem(self, elem, index: Index, inplace: bool):
|
|
arr = index._data.copy()
|
|
ser = Series(arr, copy=False)
|
|
|
|
self.check_can_hold_element(ser, elem, inplace)
|
|
|
|
if is_scalar(elem):
|
|
ser[0] = elem
|
|
else:
|
|
ser[: len(elem)] = elem
|
|
|
|
if inplace:
|
|
assert ser.array is arr # i.e. setting was done inplace
|
|
else:
|
|
assert ser.dtype == object
|
|
|
|
|
|
class TestShouldStore:
|
|
def test_should_store_categorical(self):
|
|
cat = Categorical(["A", "B", "C"])
|
|
df = DataFrame(cat)
|
|
blk = df._mgr.blocks[0]
|
|
|
|
# matching dtype
|
|
assert blk.should_store(cat)
|
|
assert blk.should_store(cat[:-1])
|
|
|
|
# different dtype
|
|
assert not blk.should_store(cat.as_ordered())
|
|
|
|
# ndarray instead of Categorical
|
|
assert not blk.should_store(np.asarray(cat))
|
|
|
|
|
|
def test_validate_ndim():
|
|
values = np.array([1.0, 2.0])
|
|
placement = BlockPlacement(slice(2))
|
|
msg = r"Wrong number of dimensions. values.ndim != ndim \[1 != 2\]"
|
|
|
|
with pytest.raises(ValueError, match=msg):
|
|
make_block(values, placement, ndim=2)
|
|
|
|
|
|
def test_block_shape():
|
|
idx = Index([0, 1, 2, 3, 4])
|
|
a = Series([1, 2, 3]).reindex(idx)
|
|
b = Series(Categorical([1, 2, 3])).reindex(idx)
|
|
|
|
assert a._mgr.blocks[0].mgr_locs.indexer == b._mgr.blocks[0].mgr_locs.indexer
|
|
|
|
|
|
def test_make_block_no_pandas_array(block_maker):
|
|
# https://github.com/pandas-dev/pandas/pull/24866
|
|
arr = pd.arrays.NumpyExtensionArray(np.array([1, 2]))
|
|
|
|
# NumpyExtensionArray, no dtype
|
|
result = block_maker(arr, BlockPlacement(slice(len(arr))), ndim=arr.ndim)
|
|
assert result.dtype.kind in ["i", "u"]
|
|
|
|
if block_maker is make_block:
|
|
# new_block requires caller to unwrap NumpyExtensionArray
|
|
assert result.is_extension is False
|
|
|
|
# NumpyExtensionArray, NumpyEADtype
|
|
result = block_maker(arr, slice(len(arr)), dtype=arr.dtype, ndim=arr.ndim)
|
|
assert result.dtype.kind in ["i", "u"]
|
|
assert result.is_extension is False
|
|
|
|
# new_block no longer taked dtype keyword
|
|
# ndarray, NumpyEADtype
|
|
result = block_maker(
|
|
arr.to_numpy(), slice(len(arr)), dtype=arr.dtype, ndim=arr.ndim
|
|
)
|
|
assert result.dtype.kind in ["i", "u"]
|
|
assert result.is_extension is False
|