from pathlib import Path

import stroll

import wavemap

FILE_ROOT = Path(__file__).parent

from numpy.testing import assert_array_equal

import numpy as np

import unittest

import numpy as np

from numpy.testing import assert_array_equal

import wavemap

from wavemap import ReadMap

import inspect

import unittest

from wavemap import ReadMap

class TestDocs(unittest.TestCase):

def test_docs(self):

actual = inspect.getdoc(ReadMap.__new__)

expected = READMAP_DOC

if expected != actual:

print("expected", "------", "", *expected, sep="\n")

print

print()

print("actual", "------", "", *actual, sep="\n")

if True:

assert expected == actual

from . import files

import unittest

from pathlib import Path

import tdir

import unittest

import wavemap

from . import files

class TestExpected(unittest.TestCase):

@tdir

from . import files

import unittest

import wavemap

from . import files

class TestWaveMap(unittest.TestCase):

def test_snare(self):

from . import files

from numpy.testing import assert_array_equal

from pathlib import Path

import numpy as np

import os

import subprocess

import tdir

import unittest

from pathlib import Path

import numpy as np

import tdir

from numpy.testing import assert_array_equal

import wavemap

from . import files

IS_TRAVIS = os.getenv("TRAVIS", "").lower().startswith("t")

skip_if_travis = unittest.skipIf(IS_TRAVIS, "Test does not work in travis")

from . import files

from numpy.testing import assert_array_equal

from pathlib import Path

import struct

import tdir

import unittest

from pathlib import Path

import tdir

from numpy.testing import assert_array_equal

import wavemap

from . import files

class TestWaveWrite(unittest.TestCase):

def test_write1(self):

# Each sample in the file is scaled by half.

"""

from typing import Optional, Union

from collections.abc import Callable

import numpy as np

import xmod

from . import docs

from .convert import convert

from .raw import RawMap, warn

from .read import ReadMap as ReadMap

from .write import WriteMap as WriteMap

from typing import Callable, Optional, Union

import numpy as np

import xmod

__all__ = (

"wavemap",

# Read parameters

#

mode: str = "r",

order: Optional[str] = None,

order: str | None = None,

always_2d: bool = False,

#

# Write parameters

#

dtype: Optional[np.dtype] = None,

shape: Union[None, int, tuple] = None,

dtype: np.dtype | None = None,

shape: None | int | tuple = None,

sample_rate: int = 0,

roffset: int = 0,

#

# Read and write parameters

#

warn: Optional[Callable] = warn,

warn: Callable | None = warn,

):

"""

Memory map a WAVE file to a `numpy` array

from numpy.lib.stride_tricks import as_strided

from typing import Optional

import numpy as np

from numpy.lib.stride_tricks import as_strided

def convert(arr: np.ndarray, dtype: Optional[np.dtype], must_copy: bool = False):

def convert(arr: np.ndarray, dtype: np.dtype | None, must_copy: bool = False):

"""

Returns a copy of a numpy array or matrix that represents audio data in

another type, scaling and shifting as necessary.

from numpy.compat import os_fspath, contextlib_nullcontext, is_pathlib_path

from numpy.core.numeric import uint8, ndarray, dtype

from numpy.core.overrides import set_module

import numpy as np

from numpy.compat import contextlib_nullcontext, is_pathlib_path, os_fspath

from numpy.core.numeric import dtype, ndarray, uint8

from numpy.core.overrides import set_module

__all__ = ["memmap"]

self.base.flush()

def __array_wrap__(self, arr, context=None):

arr = super(memmap, self).__array_wrap__(arr, context)

arr = super().__array_wrap__(arr, context)

# Return a memmap if a memmap was given as the output of the

# ufunc. Leave the arr class unchanged if self is not a memmap

return arr.view(np.ndarray)

def __getitem__(self, index):

res = super(memmap, self).__getitem__(index)

res = super().__getitem__(index)

if type(res) is memmap and res._mmap is None:

return res.view(type=ndarray)

return res