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ai-content-maker/.venv/Lib/site-packages/numpy/lib/tests/test_io.py

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import sys
import gc
import gzip
import os
import threading
import time
import warnings
import io
import re
import pytest
from pathlib import Path
from tempfile import NamedTemporaryFile
from io import BytesIO, StringIO
from datetime import datetime
import locale
from multiprocessing import Value, get_context
from ctypes import c_bool
import numpy as np
import numpy.ma as ma
from numpy.lib._iotools import ConverterError, ConversionWarning
from numpy.compat import asbytes
from numpy.ma.testutils import assert_equal
from numpy.testing import (
assert_warns, assert_, assert_raises_regex, assert_raises,
assert_allclose, assert_array_equal, temppath, tempdir, IS_PYPY,
HAS_REFCOUNT, suppress_warnings, assert_no_gc_cycles, assert_no_warnings,
break_cycles, IS_WASM
)
from numpy.testing._private.utils import requires_memory
class TextIO(BytesIO):
"""Helper IO class.
Writes encode strings to bytes if needed, reads return bytes.
This makes it easier to emulate files opened in binary mode
without needing to explicitly convert strings to bytes in
setting up the test data.
"""
def __init__(self, s=""):
BytesIO.__init__(self, asbytes(s))
def write(self, s):
BytesIO.write(self, asbytes(s))
def writelines(self, lines):
BytesIO.writelines(self, [asbytes(s) for s in lines])
IS_64BIT = sys.maxsize > 2**32
try:
import bz2
HAS_BZ2 = True
except ImportError:
HAS_BZ2 = False
try:
import lzma
HAS_LZMA = True
except ImportError:
HAS_LZMA = False
def strptime(s, fmt=None):
"""
This function is available in the datetime module only from Python >=
2.5.
"""
if type(s) == bytes:
s = s.decode("latin1")
return datetime(*time.strptime(s, fmt)[:3])
class RoundtripTest:
def roundtrip(self, save_func, *args, **kwargs):
"""
save_func : callable
Function used to save arrays to file.
file_on_disk : bool
If true, store the file on disk, instead of in a
string buffer.
save_kwds : dict
Parameters passed to `save_func`.
load_kwds : dict
Parameters passed to `numpy.load`.
args : tuple of arrays
Arrays stored to file.
"""
save_kwds = kwargs.get('save_kwds', {})
load_kwds = kwargs.get('load_kwds', {"allow_pickle": True})
file_on_disk = kwargs.get('file_on_disk', False)
if file_on_disk:
target_file = NamedTemporaryFile(delete=False)
load_file = target_file.name
else:
target_file = BytesIO()
load_file = target_file
try:
arr = args
save_func(target_file, *arr, **save_kwds)
target_file.flush()
target_file.seek(0)
if sys.platform == 'win32' and not isinstance(target_file, BytesIO):
target_file.close()
arr_reloaded = np.load(load_file, **load_kwds)
self.arr = arr
self.arr_reloaded = arr_reloaded
finally:
if not isinstance(target_file, BytesIO):
target_file.close()
# holds an open file descriptor so it can't be deleted on win
if 'arr_reloaded' in locals():
if not isinstance(arr_reloaded, np.lib.npyio.NpzFile):
os.remove(target_file.name)
def check_roundtrips(self, a):
self.roundtrip(a)
self.roundtrip(a, file_on_disk=True)
self.roundtrip(np.asfortranarray(a))
self.roundtrip(np.asfortranarray(a), file_on_disk=True)
if a.shape[0] > 1:
# neither C nor Fortran contiguous for 2D arrays or more
self.roundtrip(np.asfortranarray(a)[1:])
self.roundtrip(np.asfortranarray(a)[1:], file_on_disk=True)
def test_array(self):
a = np.array([], float)
self.check_roundtrips(a)
a = np.array([[1, 2], [3, 4]], float)
self.check_roundtrips(a)
a = np.array([[1, 2], [3, 4]], int)
self.check_roundtrips(a)
a = np.array([[1 + 5j, 2 + 6j], [3 + 7j, 4 + 8j]], dtype=np.csingle)
self.check_roundtrips(a)
a = np.array([[1 + 5j, 2 + 6j], [3 + 7j, 4 + 8j]], dtype=np.cdouble)
self.check_roundtrips(a)
def test_array_object(self):
a = np.array([], object)
self.check_roundtrips(a)
a = np.array([[1, 2], [3, 4]], object)
self.check_roundtrips(a)
def test_1D(self):
a = np.array([1, 2, 3, 4], int)
self.roundtrip(a)
@pytest.mark.skipif(sys.platform == 'win32', reason="Fails on Win32")
def test_mmap(self):
a = np.array([[1, 2.5], [4, 7.3]])
self.roundtrip(a, file_on_disk=True, load_kwds={'mmap_mode': 'r'})
a = np.asfortranarray([[1, 2.5], [4, 7.3]])
self.roundtrip(a, file_on_disk=True, load_kwds={'mmap_mode': 'r'})
def test_record(self):
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
self.check_roundtrips(a)
@pytest.mark.slow
def test_format_2_0(self):
dt = [(("%d" % i) * 100, float) for i in range(500)]
a = np.ones(1000, dtype=dt)
with warnings.catch_warnings(record=True):
warnings.filterwarnings('always', '', UserWarning)
self.check_roundtrips(a)
class TestSaveLoad(RoundtripTest):
def roundtrip(self, *args, **kwargs):
RoundtripTest.roundtrip(self, np.save, *args, **kwargs)
assert_equal(self.arr[0], self.arr_reloaded)
assert_equal(self.arr[0].dtype, self.arr_reloaded.dtype)
assert_equal(self.arr[0].flags.fnc, self.arr_reloaded.flags.fnc)
class TestSavezLoad(RoundtripTest):
def roundtrip(self, *args, **kwargs):
RoundtripTest.roundtrip(self, np.savez, *args, **kwargs)
try:
for n, arr in enumerate(self.arr):
reloaded = self.arr_reloaded['arr_%d' % n]
assert_equal(arr, reloaded)
assert_equal(arr.dtype, reloaded.dtype)
assert_equal(arr.flags.fnc, reloaded.flags.fnc)
finally:
# delete tempfile, must be done here on windows
if self.arr_reloaded.fid:
self.arr_reloaded.fid.close()
os.remove(self.arr_reloaded.fid.name)
@pytest.mark.skipif(IS_PYPY, reason="Hangs on PyPy")
@pytest.mark.skipif(not IS_64BIT, reason="Needs 64bit platform")
@pytest.mark.slow
def test_big_arrays(self):
L = (1 << 31) + 100000
a = np.empty(L, dtype=np.uint8)
with temppath(prefix="numpy_test_big_arrays_", suffix=".npz") as tmp:
np.savez(tmp, a=a)
del a
npfile = np.load(tmp)
a = npfile['a'] # Should succeed
npfile.close()
del a # Avoid pyflakes unused variable warning.
def test_multiple_arrays(self):
a = np.array([[1, 2], [3, 4]], float)
b = np.array([[1 + 2j, 2 + 7j], [3 - 6j, 4 + 12j]], complex)
self.roundtrip(a, b)
def test_named_arrays(self):
a = np.array([[1, 2], [3, 4]], float)
b = np.array([[1 + 2j, 2 + 7j], [3 - 6j, 4 + 12j]], complex)
c = BytesIO()
np.savez(c, file_a=a, file_b=b)
c.seek(0)
l = np.load(c)
assert_equal(a, l['file_a'])
assert_equal(b, l['file_b'])
def test_tuple_getitem_raises(self):
# gh-23748
a = np.array([1, 2, 3])
f = BytesIO()
np.savez(f, a=a)
f.seek(0)
l = np.load(f)
with pytest.raises(KeyError, match="(1, 2)"):
l[1, 2]
def test_BagObj(self):
a = np.array([[1, 2], [3, 4]], float)
b = np.array([[1 + 2j, 2 + 7j], [3 - 6j, 4 + 12j]], complex)
c = BytesIO()
np.savez(c, file_a=a, file_b=b)
c.seek(0)
l = np.load(c)
assert_equal(sorted(dir(l.f)), ['file_a','file_b'])
assert_equal(a, l.f.file_a)
assert_equal(b, l.f.file_b)
@pytest.mark.skipif(IS_WASM, reason="Cannot start thread")
def test_savez_filename_clashes(self):
# Test that issue #852 is fixed
# and savez functions in multithreaded environment
def writer(error_list):
with temppath(suffix='.npz') as tmp:
arr = np.random.randn(500, 500)
try:
np.savez(tmp, arr=arr)
except OSError as err:
error_list.append(err)
errors = []
threads = [threading.Thread(target=writer, args=(errors,))
for j in range(3)]
for t in threads:
t.start()
for t in threads:
t.join()
if errors:
raise AssertionError(errors)
def test_not_closing_opened_fid(self):
# Test that issue #2178 is fixed:
# verify could seek on 'loaded' file
with temppath(suffix='.npz') as tmp:
with open(tmp, 'wb') as fp:
np.savez(fp, data='LOVELY LOAD')
with open(tmp, 'rb', 10000) as fp:
fp.seek(0)
assert_(not fp.closed)
np.load(fp)['data']
# fp must not get closed by .load
assert_(not fp.closed)
fp.seek(0)
assert_(not fp.closed)
@pytest.mark.slow_pypy
def test_closing_fid(self):
# Test that issue #1517 (too many opened files) remains closed
# It might be a "weak" test since failed to get triggered on
# e.g. Debian sid of 2012 Jul 05 but was reported to
# trigger the failure on Ubuntu 10.04:
# http://projects.scipy.org/numpy/ticket/1517#comment:2
with temppath(suffix='.npz') as tmp:
np.savez(tmp, data='LOVELY LOAD')
# We need to check if the garbage collector can properly close
# numpy npz file returned by np.load when their reference count
# goes to zero. Python 3 running in debug mode raises a
# ResourceWarning when file closing is left to the garbage
# collector, so we catch the warnings.
with suppress_warnings() as sup:
sup.filter(ResourceWarning) # TODO: specify exact message
for i in range(1, 1025):
try:
np.load(tmp)["data"]
except Exception as e:
msg = "Failed to load data from a file: %s" % e
raise AssertionError(msg)
finally:
if IS_PYPY:
gc.collect()
def test_closing_zipfile_after_load(self):
# Check that zipfile owns file and can close it. This needs to
# pass a file name to load for the test. On windows failure will
# cause a second error will be raised when the attempt to remove
# the open file is made.
prefix = 'numpy_test_closing_zipfile_after_load_'
with temppath(suffix='.npz', prefix=prefix) as tmp:
np.savez(tmp, lab='place holder')
data = np.load(tmp)
fp = data.zip.fp
data.close()
assert_(fp.closed)
@pytest.mark.parametrize("count, expected_repr", [
(1, "NpzFile {fname!r} with keys: arr_0"),
(5, "NpzFile {fname!r} with keys: arr_0, arr_1, arr_2, arr_3, arr_4"),
# _MAX_REPR_ARRAY_COUNT is 5, so files with more than 5 keys are
# expected to end in '...'
(6, "NpzFile {fname!r} with keys: arr_0, arr_1, arr_2, arr_3, arr_4..."),
])
def test_repr_lists_keys(self, count, expected_repr):
a = np.array([[1, 2], [3, 4]], float)
with temppath(suffix='.npz') as tmp:
np.savez(tmp, *[a]*count)
l = np.load(tmp)
assert repr(l) == expected_repr.format(fname=tmp)
l.close()
class TestSaveTxt:
def test_array(self):
a = np.array([[1, 2], [3, 4]], float)
fmt = "%.18e"
c = BytesIO()
np.savetxt(c, a, fmt=fmt)
c.seek(0)
assert_equal(c.readlines(),
[asbytes((fmt + ' ' + fmt + '\n') % (1, 2)),
asbytes((fmt + ' ' + fmt + '\n') % (3, 4))])
a = np.array([[1, 2], [3, 4]], int)
c = BytesIO()
np.savetxt(c, a, fmt='%d')
c.seek(0)
assert_equal(c.readlines(), [b'1 2\n', b'3 4\n'])
def test_1D(self):
a = np.array([1, 2, 3, 4], int)
c = BytesIO()
np.savetxt(c, a, fmt='%d')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'1\n', b'2\n', b'3\n', b'4\n'])
def test_0D_3D(self):
c = BytesIO()
assert_raises(ValueError, np.savetxt, c, np.array(1))
assert_raises(ValueError, np.savetxt, c, np.array([[[1], [2]]]))
def test_structured(self):
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
c = BytesIO()
np.savetxt(c, a, fmt='%d')
c.seek(0)
assert_equal(c.readlines(), [b'1 2\n', b'3 4\n'])
def test_structured_padded(self):
# gh-13297
a = np.array([(1, 2, 3),(4, 5, 6)], dtype=[
('foo', 'i4'), ('bar', 'i4'), ('baz', 'i4')
])
c = BytesIO()
np.savetxt(c, a[['foo', 'baz']], fmt='%d')
c.seek(0)
assert_equal(c.readlines(), [b'1 3\n', b'4 6\n'])
def test_multifield_view(self):
a = np.ones(1, dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'f4')])
v = a[['x', 'z']]
with temppath(suffix='.npy') as path:
path = Path(path)
np.save(path, v)
data = np.load(path)
assert_array_equal(data, v)
def test_delimiter(self):
a = np.array([[1., 2.], [3., 4.]])
c = BytesIO()
np.savetxt(c, a, delimiter=',', fmt='%d')
c.seek(0)
assert_equal(c.readlines(), [b'1,2\n', b'3,4\n'])
def test_format(self):
a = np.array([(1, 2), (3, 4)])
c = BytesIO()
# Sequence of formats
np.savetxt(c, a, fmt=['%02d', '%3.1f'])
c.seek(0)
assert_equal(c.readlines(), [b'01 2.0\n', b'03 4.0\n'])
# A single multiformat string
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Specify delimiter, should be overridden
c = BytesIO()
np.savetxt(c, a, fmt='%02d : %3.1f', delimiter=',')
c.seek(0)
lines = c.readlines()
assert_equal(lines, [b'01 : 2.0\n', b'03 : 4.0\n'])
# Bad fmt, should raise a ValueError
c = BytesIO()
assert_raises(ValueError, np.savetxt, c, a, fmt=99)
def test_header_footer(self):
# Test the functionality of the header and footer keyword argument.
c = BytesIO()
a = np.array([(1, 2), (3, 4)], dtype=int)
test_header_footer = 'Test header / footer'
# Test the header keyword argument
np.savetxt(c, a, fmt='%1d', header=test_header_footer)
c.seek(0)
assert_equal(c.read(),
asbytes('# ' + test_header_footer + '\n1 2\n3 4\n'))
# Test the footer keyword argument
c = BytesIO()
np.savetxt(c, a, fmt='%1d', footer=test_header_footer)
c.seek(0)
assert_equal(c.read(),
asbytes('1 2\n3 4\n# ' + test_header_footer + '\n'))
# Test the commentstr keyword argument used on the header
c = BytesIO()
commentstr = '% '
np.savetxt(c, a, fmt='%1d',
header=test_header_footer, comments=commentstr)
c.seek(0)
assert_equal(c.read(),
asbytes(commentstr + test_header_footer + '\n' + '1 2\n3 4\n'))
# Test the commentstr keyword argument used on the footer
c = BytesIO()
commentstr = '% '
np.savetxt(c, a, fmt='%1d',
footer=test_header_footer, comments=commentstr)
c.seek(0)
assert_equal(c.read(),
asbytes('1 2\n3 4\n' + commentstr + test_header_footer + '\n'))
def test_file_roundtrip(self):
with temppath() as name:
a = np.array([(1, 2), (3, 4)])
np.savetxt(name, a)
b = np.loadtxt(name)
assert_array_equal(a, b)
def test_complex_arrays(self):
ncols = 2
nrows = 2
a = np.zeros((ncols, nrows), dtype=np.complex128)
re = np.pi
im = np.e
a[:] = re + 1.0j * im
# One format only
c = BytesIO()
np.savetxt(c, a, fmt=' %+.3e')
c.seek(0)
lines = c.readlines()
assert_equal(
lines,
[b' ( +3.142e+00+ +2.718e+00j) ( +3.142e+00+ +2.718e+00j)\n',
b' ( +3.142e+00+ +2.718e+00j) ( +3.142e+00+ +2.718e+00j)\n'])
# One format for each real and imaginary part
c = BytesIO()
np.savetxt(c, a, fmt=' %+.3e' * 2 * ncols)
c.seek(0)
lines = c.readlines()
assert_equal(
lines,
[b' +3.142e+00 +2.718e+00 +3.142e+00 +2.718e+00\n',
b' +3.142e+00 +2.718e+00 +3.142e+00 +2.718e+00\n'])
# One format for each complex number
c = BytesIO()
np.savetxt(c, a, fmt=['(%.3e%+.3ej)'] * ncols)
c.seek(0)
lines = c.readlines()
assert_equal(
lines,
[b'(3.142e+00+2.718e+00j) (3.142e+00+2.718e+00j)\n',
b'(3.142e+00+2.718e+00j) (3.142e+00+2.718e+00j)\n'])
def test_complex_negative_exponent(self):
# Previous to 1.15, some formats generated x+-yj, gh 7895
ncols = 2
nrows = 2
a = np.zeros((ncols, nrows), dtype=np.complex128)
re = np.pi
im = np.e
a[:] = re - 1.0j * im
c = BytesIO()
np.savetxt(c, a, fmt='%.3e')
c.seek(0)
lines = c.readlines()
assert_equal(
lines,
[b' (3.142e+00-2.718e+00j) (3.142e+00-2.718e+00j)\n',
b' (3.142e+00-2.718e+00j) (3.142e+00-2.718e+00j)\n'])
def test_custom_writer(self):
class CustomWriter(list):
def write(self, text):
self.extend(text.split(b'\n'))
w = CustomWriter()
a = np.array([(1, 2), (3, 4)])
np.savetxt(w, a)
b = np.loadtxt(w)
assert_array_equal(a, b)
def test_unicode(self):
utf8 = b'\xcf\x96'.decode('UTF-8')
a = np.array([utf8], dtype=np.str_)
with tempdir() as tmpdir:
# set encoding as on windows it may not be unicode even on py3
np.savetxt(os.path.join(tmpdir, 'test.csv'), a, fmt=['%s'],
encoding='UTF-8')
def test_unicode_roundtrip(self):
utf8 = b'\xcf\x96'.decode('UTF-8')
a = np.array([utf8], dtype=np.str_)
# our gz wrapper support encoding
suffixes = ['', '.gz']
if HAS_BZ2:
suffixes.append('.bz2')
if HAS_LZMA:
suffixes.extend(['.xz', '.lzma'])
with tempdir() as tmpdir:
for suffix in suffixes:
np.savetxt(os.path.join(tmpdir, 'test.csv' + suffix), a,
fmt=['%s'], encoding='UTF-16-LE')
b = np.loadtxt(os.path.join(tmpdir, 'test.csv' + suffix),
encoding='UTF-16-LE', dtype=np.str_)
assert_array_equal(a, b)
def test_unicode_bytestream(self):
utf8 = b'\xcf\x96'.decode('UTF-8')
a = np.array([utf8], dtype=np.str_)
s = BytesIO()
np.savetxt(s, a, fmt=['%s'], encoding='UTF-8')
s.seek(0)
assert_equal(s.read().decode('UTF-8'), utf8 + '\n')
def test_unicode_stringstream(self):
utf8 = b'\xcf\x96'.decode('UTF-8')
a = np.array([utf8], dtype=np.str_)
s = StringIO()
np.savetxt(s, a, fmt=['%s'], encoding='UTF-8')
s.seek(0)
assert_equal(s.read(), utf8 + '\n')
@pytest.mark.parametrize("fmt", ["%f", b"%f"])
@pytest.mark.parametrize("iotype", [StringIO, BytesIO])
def test_unicode_and_bytes_fmt(self, fmt, iotype):
# string type of fmt should not matter, see also gh-4053
a = np.array([1.])
s = iotype()
np.savetxt(s, a, fmt=fmt)
s.seek(0)
if iotype is StringIO:
assert_equal(s.read(), "%f\n" % 1.)
else:
assert_equal(s.read(), b"%f\n" % 1.)
@pytest.mark.skipif(sys.platform=='win32', reason="files>4GB may not work")
@pytest.mark.slow
@requires_memory(free_bytes=7e9)
def test_large_zip(self):
def check_large_zip(memoryerror_raised):
memoryerror_raised.value = False
try:
# The test takes at least 6GB of memory, writes a file larger
# than 4GB. This tests the ``allowZip64`` kwarg to ``zipfile``
test_data = np.asarray([np.random.rand(
np.random.randint(50,100),4)
for i in range(800000)], dtype=object)
with tempdir() as tmpdir:
np.savez(os.path.join(tmpdir, 'test.npz'),
test_data=test_data)
except MemoryError:
memoryerror_raised.value = True
raise
# run in a subprocess to ensure memory is released on PyPy, see gh-15775
# Use an object in shared memory to re-raise the MemoryError exception
# in our process if needed, see gh-16889
memoryerror_raised = Value(c_bool)
# Since Python 3.8, the default start method for multiprocessing has
# been changed from 'fork' to 'spawn' on macOS, causing inconsistency
# on memory sharing model, lead to failed test for check_large_zip
ctx = get_context('fork')
p = ctx.Process(target=check_large_zip, args=(memoryerror_raised,))
p.start()
p.join()
if memoryerror_raised.value:
raise MemoryError("Child process raised a MemoryError exception")
# -9 indicates a SIGKILL, probably an OOM.
if p.exitcode == -9:
pytest.xfail("subprocess got a SIGKILL, apparently free memory was not sufficient")
assert p.exitcode == 0
class LoadTxtBase:
def check_compressed(self, fopen, suffixes):
# Test that we can load data from a compressed file
wanted = np.arange(6).reshape((2, 3))
linesep = ('\n', '\r\n', '\r')
for sep in linesep:
data = '0 1 2' + sep + '3 4 5'
for suffix in suffixes:
with temppath(suffix=suffix) as name:
with fopen(name, mode='wt', encoding='UTF-32-LE') as f:
f.write(data)
res = self.loadfunc(name, encoding='UTF-32-LE')
assert_array_equal(res, wanted)
with fopen(name, "rt", encoding='UTF-32-LE') as f:
res = self.loadfunc(f)
assert_array_equal(res, wanted)
def test_compressed_gzip(self):
self.check_compressed(gzip.open, ('.gz',))
@pytest.mark.skipif(not HAS_BZ2, reason="Needs bz2")
def test_compressed_bz2(self):
self.check_compressed(bz2.open, ('.bz2',))
@pytest.mark.skipif(not HAS_LZMA, reason="Needs lzma")
def test_compressed_lzma(self):
self.check_compressed(lzma.open, ('.xz', '.lzma'))
def test_encoding(self):
with temppath() as path:
with open(path, "wb") as f:
f.write('0.\n1.\n2.'.encode("UTF-16"))
x = self.loadfunc(path, encoding="UTF-16")
assert_array_equal(x, [0., 1., 2.])
def test_stringload(self):
# umlaute
nonascii = b'\xc3\xb6\xc3\xbc\xc3\xb6'.decode("UTF-8")
with temppath() as path:
with open(path, "wb") as f:
f.write(nonascii.encode("UTF-16"))
x = self.loadfunc(path, encoding="UTF-16", dtype=np.str_)
assert_array_equal(x, nonascii)
def test_binary_decode(self):
utf16 = b'\xff\xfeh\x04 \x00i\x04 \x00j\x04'
v = self.loadfunc(BytesIO(utf16), dtype=np.str_, encoding='UTF-16')
assert_array_equal(v, np.array(utf16.decode('UTF-16').split()))
def test_converters_decode(self):
# test converters that decode strings
c = TextIO()
c.write(b'\xcf\x96')
c.seek(0)
x = self.loadfunc(c, dtype=np.str_,
converters={0: lambda x: x.decode('UTF-8')})
a = np.array([b'\xcf\x96'.decode('UTF-8')])
assert_array_equal(x, a)
def test_converters_nodecode(self):
# test native string converters enabled by setting an encoding
utf8 = b'\xcf\x96'.decode('UTF-8')
with temppath() as path:
with io.open(path, 'wt', encoding='UTF-8') as f:
f.write(utf8)
x = self.loadfunc(path, dtype=np.str_,
converters={0: lambda x: x + 't'},
encoding='UTF-8')
a = np.array([utf8 + 't'])
assert_array_equal(x, a)
class TestLoadTxt(LoadTxtBase):
loadfunc = staticmethod(np.loadtxt)
def setup_method(self):
# lower chunksize for testing
self.orig_chunk = np.lib.npyio._loadtxt_chunksize
np.lib.npyio._loadtxt_chunksize = 1
def teardown_method(self):
np.lib.npyio._loadtxt_chunksize = self.orig_chunk
def test_record(self):
c = TextIO()
c.write('1 2\n3 4')
c.seek(0)
x = np.loadtxt(c, dtype=[('x', np.int32), ('y', np.int32)])
a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
assert_array_equal(x, a)
d = TextIO()
d.write('M 64 75.0\nF 25 60.0')
d.seek(0)
mydescriptor = {'names': ('gender', 'age', 'weight'),
'formats': ('S1', 'i4', 'f4')}
b = np.array([('M', 64.0, 75.0),
('F', 25.0, 60.0)], dtype=mydescriptor)
y = np.loadtxt(d, dtype=mydescriptor)
assert_array_equal(y, b)
def test_array(self):
c = TextIO()
c.write('1 2\n3 4')
c.seek(0)
x = np.loadtxt(c, dtype=int)
a = np.array([[1, 2], [3, 4]], int)
assert_array_equal(x, a)
c.seek(0)
x = np.loadtxt(c, dtype=float)
a = np.array([[1, 2], [3, 4]], float)
assert_array_equal(x, a)
def test_1D(self):
c = TextIO()
c.write('1\n2\n3\n4\n')
c.seek(0)
x = np.loadtxt(c, dtype=int)
a = np.array([1, 2, 3, 4], int)
assert_array_equal(x, a)
c = TextIO()
c.write('1,2,3,4\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',')
a = np.array([1, 2, 3, 4], int)
assert_array_equal(x, a)
def test_missing(self):
c = TextIO()
c.write('1,2,3,,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
converters={3: lambda s: int(s or - 999)})
a = np.array([1, 2, 3, -999, 5], int)
assert_array_equal(x, a)
def test_converters_with_usecols(self):
c = TextIO()
c.write('1,2,3,,5\n6,7,8,9,10\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
converters={3: lambda s: int(s or - 999)},
usecols=(1, 3,))
a = np.array([[2, -999], [7, 9]], int)
assert_array_equal(x, a)
def test_comments_unicode(self):
c = TextIO()
c.write('# comment\n1,2,3,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
comments='#')
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
def test_comments_byte(self):
c = TextIO()
c.write('# comment\n1,2,3,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
comments=b'#')
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
def test_comments_multiple(self):
c = TextIO()
c.write('# comment\n1,2,3\n@ comment2\n4,5,6 // comment3')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
comments=['#', '@', '//'])
a = np.array([[1, 2, 3], [4, 5, 6]], int)
assert_array_equal(x, a)
@pytest.mark.skipif(IS_PYPY and sys.implementation.version <= (7, 3, 8),
reason="PyPy bug in error formatting")
def test_comments_multi_chars(self):
c = TextIO()
c.write('/* comment\n1,2,3,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
comments='/*')
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
# Check that '/*' is not transformed to ['/', '*']
c = TextIO()
c.write('*/ comment\n1,2,3,5\n')
c.seek(0)
assert_raises(ValueError, np.loadtxt, c, dtype=int, delimiter=',',
comments='/*')
def test_skiprows(self):
c = TextIO()
c.write('comment\n1,2,3,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
skiprows=1)
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
c = TextIO()
c.write('# comment\n1,2,3,5\n')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
skiprows=1)
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
def test_usecols(self):
a = np.array([[1, 2], [3, 4]], float)
c = BytesIO()
np.savetxt(c, a)
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=(1,))
assert_array_equal(x, a[:, 1])
a = np.array([[1, 2, 3], [3, 4, 5]], float)
c = BytesIO()
np.savetxt(c, a)
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=(1, 2))
assert_array_equal(x, a[:, 1:])
# Testing with arrays instead of tuples.
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=np.array([1, 2]))
assert_array_equal(x, a[:, 1:])
# Testing with an integer instead of a sequence
for int_type in [int, np.int8, np.int16,
np.int32, np.int64, np.uint8, np.uint16,
np.uint32, np.uint64]:
to_read = int_type(1)
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=to_read)
assert_array_equal(x, a[:, 1])
# Testing with some crazy custom integer type
class CrazyInt:
def __index__(self):
return 1
crazy_int = CrazyInt()
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=crazy_int)
assert_array_equal(x, a[:, 1])
c.seek(0)
x = np.loadtxt(c, dtype=float, usecols=(crazy_int,))
assert_array_equal(x, a[:, 1])
# Checking with dtypes defined converters.
data = '''JOE 70.1 25.3
BOB 60.5 27.9
'''
c = TextIO(data)
names = ['stid', 'temp']
dtypes = ['S4', 'f8']
arr = np.loadtxt(c, usecols=(0, 2), dtype=list(zip(names, dtypes)))
assert_equal(arr['stid'], [b"JOE", b"BOB"])
assert_equal(arr['temp'], [25.3, 27.9])
# Testing non-ints in usecols
c.seek(0)
bogus_idx = 1.5
assert_raises_regex(
TypeError,
'^usecols must be.*%s' % type(bogus_idx).__name__,
np.loadtxt, c, usecols=bogus_idx
)
assert_raises_regex(
TypeError,
'^usecols must be.*%s' % type(bogus_idx).__name__,
np.loadtxt, c, usecols=[0, bogus_idx, 0]
)
def test_bad_usecols(self):
with pytest.raises(OverflowError):
np.loadtxt(["1\n"], usecols=[2**64], delimiter=",")
with pytest.raises((ValueError, OverflowError)):
# Overflow error on 32bit platforms
np.loadtxt(["1\n"], usecols=[2**62], delimiter=",")
with pytest.raises(TypeError,
match="If a structured dtype .*. But 1 usecols were given and "
"the number of fields is 3."):
np.loadtxt(["1,1\n"], dtype="i,(2)i", usecols=[0], delimiter=",")
def test_fancy_dtype(self):
c = TextIO()
c.write('1,2,3.0\n4,5,6.0\n')
c.seek(0)
dt = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
x = np.loadtxt(c, dtype=dt, delimiter=',')
a = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dt)
assert_array_equal(x, a)
def test_shaped_dtype(self):
c = TextIO("aaaa 1.0 8.0 1 2 3 4 5 6")
dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
('block', int, (2, 3))])
x = np.loadtxt(c, dtype=dt)
a = np.array([('aaaa', 1.0, 8.0, [[1, 2, 3], [4, 5, 6]])],
dtype=dt)
assert_array_equal(x, a)
def test_3d_shaped_dtype(self):
c = TextIO("aaaa 1.0 8.0 1 2 3 4 5 6 7 8 9 10 11 12")
dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
('block', int, (2, 2, 3))])
x = np.loadtxt(c, dtype=dt)
a = np.array([('aaaa', 1.0, 8.0,
[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])],
dtype=dt)
assert_array_equal(x, a)
def test_str_dtype(self):
# see gh-8033
c = ["str1", "str2"]
for dt in (str, np.bytes_):
a = np.array(["str1", "str2"], dtype=dt)
x = np.loadtxt(c, dtype=dt)
assert_array_equal(x, a)
def test_empty_file(self):
with pytest.warns(UserWarning, match="input contained no data"):
c = TextIO()
x = np.loadtxt(c)
assert_equal(x.shape, (0,))
x = np.loadtxt(c, dtype=np.int64)
assert_equal(x.shape, (0,))
assert_(x.dtype == np.int64)
def test_unused_converter(self):
c = TextIO()
c.writelines(['1 21\n', '3 42\n'])
c.seek(0)
data = np.loadtxt(c, usecols=(1,),
converters={0: lambda s: int(s, 16)})
assert_array_equal(data, [21, 42])
c.seek(0)
data = np.loadtxt(c, usecols=(1,),
converters={1: lambda s: int(s, 16)})
assert_array_equal(data, [33, 66])
def test_dtype_with_object(self):
# Test using an explicit dtype with an object
data = """ 1; 2001-01-01
2; 2002-01-31 """
ndtype = [('idx', int), ('code', object)]
func = lambda s: strptime(s.strip(), "%Y-%m-%d")
converters = {1: func}
test = np.loadtxt(TextIO(data), delimiter=";", dtype=ndtype,
converters=converters)
control = np.array(
[(1, datetime(2001, 1, 1)), (2, datetime(2002, 1, 31))],
dtype=ndtype)
assert_equal(test, control)
def test_uint64_type(self):
tgt = (9223372043271415339, 9223372043271415853)
c = TextIO()
c.write("%s %s" % tgt)
c.seek(0)
res = np.loadtxt(c, dtype=np.uint64)
assert_equal(res, tgt)
def test_int64_type(self):
tgt = (-9223372036854775807, 9223372036854775807)
c = TextIO()
c.write("%s %s" % tgt)
c.seek(0)
res = np.loadtxt(c, dtype=np.int64)
assert_equal(res, tgt)
def test_from_float_hex(self):
# IEEE doubles and floats only, otherwise the float32
# conversion may fail.
tgt = np.logspace(-10, 10, 5).astype(np.float32)
tgt = np.hstack((tgt, -tgt)).astype(float)
inp = '\n'.join(map(float.hex, tgt))
c = TextIO()
c.write(inp)
for dt in [float, np.float32]:
c.seek(0)
res = np.loadtxt(
c, dtype=dt, converters=float.fromhex, encoding="latin1")
assert_equal(res, tgt, err_msg="%s" % dt)
@pytest.mark.skipif(IS_PYPY and sys.implementation.version <= (7, 3, 8),
reason="PyPy bug in error formatting")
def test_default_float_converter_no_default_hex_conversion(self):
"""
Ensure that fromhex is only used for values with the correct prefix and
is not called by default. Regression test related to gh-19598.
"""
c = TextIO("a b c")
with pytest.raises(ValueError,
match=".*convert string 'a' to float64 at row 0, column 1"):
np.loadtxt(c)
@pytest.mark.skipif(IS_PYPY and sys.implementation.version <= (7, 3, 8),
reason="PyPy bug in error formatting")
def test_default_float_converter_exception(self):
"""
Ensure that the exception message raised during failed floating point
conversion is correct. Regression test related to gh-19598.
"""
c = TextIO("qrs tuv") # Invalid values for default float converter
with pytest.raises(ValueError,
match="could not convert string 'qrs' to float64"):
np.loadtxt(c)
def test_from_complex(self):
tgt = (complex(1, 1), complex(1, -1))
c = TextIO()
c.write("%s %s" % tgt)
c.seek(0)
res = np.loadtxt(c, dtype=complex)
assert_equal(res, tgt)
def test_complex_misformatted(self):
# test for backward compatibility
# some complex formats used to generate x+-yj
a = np.zeros((2, 2), dtype=np.complex128)
re = np.pi
im = np.e
a[:] = re - 1.0j * im
c = BytesIO()
np.savetxt(c, a, fmt='%.16e')
c.seek(0)
txt = c.read()
c.seek(0)
# misformat the sign on the imaginary part, gh 7895
txt_bad = txt.replace(b'e+00-', b'e00+-')
assert_(txt_bad != txt)
c.write(txt_bad)
c.seek(0)
res = np.loadtxt(c, dtype=complex)
assert_equal(res, a)
def test_universal_newline(self):
with temppath() as name:
with open(name, 'w') as f:
f.write('1 21\r3 42\r')
data = np.loadtxt(name)
assert_array_equal(data, [[1, 21], [3, 42]])
def test_empty_field_after_tab(self):
c = TextIO()
c.write('1 \t2 \t3\tstart \n4\t5\t6\t \n7\t8\t9.5\t')
c.seek(0)
dt = {'names': ('x', 'y', 'z', 'comment'),
'formats': ('<i4', '<i4', '<f4', '|S8')}
x = np.loadtxt(c, dtype=dt, delimiter='\t')
a = np.array([b'start ', b' ', b''])
assert_array_equal(x['comment'], a)
def test_unpack_structured(self):
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('|S1', '<i4', '<f4')}
a, b, c = np.loadtxt(txt, dtype=dt, unpack=True)
assert_(a.dtype.str == '|S1')
assert_(b.dtype.str == '<i4')
assert_(c.dtype.str == '<f4')
assert_array_equal(a, np.array([b'M', b'F']))
assert_array_equal(b, np.array([21, 35]))
assert_array_equal(c, np.array([72., 58.]))
def test_ndmin_keyword(self):
c = TextIO()
c.write('1,2,3\n4,5,6')
c.seek(0)
assert_raises(ValueError, np.loadtxt, c, ndmin=3)
c.seek(0)
assert_raises(ValueError, np.loadtxt, c, ndmin=1.5)
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',', ndmin=1)
a = np.array([[1, 2, 3], [4, 5, 6]])
assert_array_equal(x, a)
d = TextIO()
d.write('0,1,2')
d.seek(0)
x = np.loadtxt(d, dtype=int, delimiter=',', ndmin=2)
assert_(x.shape == (1, 3))
d.seek(0)
x = np.loadtxt(d, dtype=int, delimiter=',', ndmin=1)
assert_(x.shape == (3,))
d.seek(0)
x = np.loadtxt(d, dtype=int, delimiter=',', ndmin=0)
assert_(x.shape == (3,))
e = TextIO()
e.write('0\n1\n2')
e.seek(0)
x = np.loadtxt(e, dtype=int, delimiter=',', ndmin=2)
assert_(x.shape == (3, 1))
e.seek(0)
x = np.loadtxt(e, dtype=int, delimiter=',', ndmin=1)
assert_(x.shape == (3,))
e.seek(0)
x = np.loadtxt(e, dtype=int, delimiter=',', ndmin=0)
assert_(x.shape == (3,))
# Test ndmin kw with empty file.
with pytest.warns(UserWarning, match="input contained no data"):
f = TextIO()
assert_(np.loadtxt(f, ndmin=2).shape == (0, 1,))
assert_(np.loadtxt(f, ndmin=1).shape == (0,))
def test_generator_source(self):
def count():
for i in range(10):
yield "%d" % i
res = np.loadtxt(count())
assert_array_equal(res, np.arange(10))
def test_bad_line(self):
c = TextIO()
c.write('1 2 3\n4 5 6\n2 3')
c.seek(0)
# Check for exception and that exception contains line number
assert_raises_regex(ValueError, "3", np.loadtxt, c)
def test_none_as_string(self):
# gh-5155, None should work as string when format demands it
c = TextIO()
c.write('100,foo,200\n300,None,400')
c.seek(0)
dt = np.dtype([('x', int), ('a', 'S10'), ('y', int)])
np.loadtxt(c, delimiter=',', dtype=dt, comments=None) # Should succeed
@pytest.mark.skipif(locale.getpreferredencoding() == 'ANSI_X3.4-1968',
reason="Wrong preferred encoding")
def test_binary_load(self):
butf8 = b"5,6,7,\xc3\x95scarscar\r\n15,2,3,hello\r\n"\
b"20,2,3,\xc3\x95scar\r\n"
sutf8 = butf8.decode("UTF-8").replace("\r", "").splitlines()
with temppath() as path:
with open(path, "wb") as f:
f.write(butf8)
with open(path, "rb") as f:
x = np.loadtxt(f, encoding="UTF-8", dtype=np.str_)
assert_array_equal(x, sutf8)
# test broken latin1 conversion people now rely on
with open(path, "rb") as f:
x = np.loadtxt(f, encoding="UTF-8", dtype="S")
x = [b'5,6,7,\xc3\x95scarscar', b'15,2,3,hello', b'20,2,3,\xc3\x95scar']
assert_array_equal(x, np.array(x, dtype="S"))
def test_max_rows(self):
c = TextIO()
c.write('1,2,3,5\n4,5,7,8\n2,1,4,5')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
max_rows=1)
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
def test_max_rows_with_skiprows(self):
c = TextIO()
c.write('comments\n1,2,3,5\n4,5,7,8\n2,1,4,5')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
skiprows=1, max_rows=1)
a = np.array([1, 2, 3, 5], int)
assert_array_equal(x, a)
c = TextIO()
c.write('comment\n1,2,3,5\n4,5,7,8\n2,1,4,5')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
skiprows=1, max_rows=2)
a = np.array([[1, 2, 3, 5], [4, 5, 7, 8]], int)
assert_array_equal(x, a)
def test_max_rows_with_read_continuation(self):
c = TextIO()
c.write('1,2,3,5\n4,5,7,8\n2,1,4,5')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
max_rows=2)
a = np.array([[1, 2, 3, 5], [4, 5, 7, 8]], int)
assert_array_equal(x, a)
# test continuation
x = np.loadtxt(c, dtype=int, delimiter=',')
a = np.array([2,1,4,5], int)
assert_array_equal(x, a)
def test_max_rows_larger(self):
#test max_rows > num rows
c = TextIO()
c.write('comment\n1,2,3,5\n4,5,7,8\n2,1,4,5')
c.seek(0)
x = np.loadtxt(c, dtype=int, delimiter=',',
skiprows=1, max_rows=6)
a = np.array([[1, 2, 3, 5], [4, 5, 7, 8], [2, 1, 4, 5]], int)
assert_array_equal(x, a)
@pytest.mark.parametrize(["skip", "data"], [
(1, ["ignored\n", "1,2\n", "\n", "3,4\n"]),
# "Bad" lines that do not end in newlines:
(1, ["ignored", "1,2", "", "3,4"]),
(1, StringIO("ignored\n1,2\n\n3,4")),
# Same as above, but do not skip any lines:
(0, ["-1,0\n", "1,2\n", "\n", "3,4\n"]),
(0, ["-1,0", "1,2", "", "3,4"]),
(0, StringIO("-1,0\n1,2\n\n3,4"))])
def test_max_rows_empty_lines(self, skip, data):
with pytest.warns(UserWarning,
match=f"Input line 3.*max_rows={3-skip}"):
res = np.loadtxt(data, dtype=int, skiprows=skip, delimiter=",",
max_rows=3-skip)
assert_array_equal(res, [[-1, 0], [1, 2], [3, 4]][skip:])
if isinstance(data, StringIO):
data.seek(0)
with warnings.catch_warnings():
warnings.simplefilter("error", UserWarning)
with pytest.raises(UserWarning):
np.loadtxt(data, dtype=int, skiprows=skip, delimiter=",",
max_rows=3-skip)
class Testfromregex:
def test_record(self):
c = TextIO()
c.write('1.312 foo\n1.534 bar\n4.444 qux')
c.seek(0)
dt = [('num', np.float64), ('val', 'S3')]
x = np.fromregex(c, r"([0-9.]+)\s+(...)", dt)
a = np.array([(1.312, 'foo'), (1.534, 'bar'), (4.444, 'qux')],
dtype=dt)
assert_array_equal(x, a)
def test_record_2(self):
c = TextIO()
c.write('1312 foo\n1534 bar\n4444 qux')
c.seek(0)
dt = [('num', np.int32), ('val', 'S3')]
x = np.fromregex(c, r"(\d+)\s+(...)", dt)
a = np.array([(1312, 'foo'), (1534, 'bar'), (4444, 'qux')],
dtype=dt)
assert_array_equal(x, a)
def test_record_3(self):
c = TextIO()
c.write('1312 foo\n1534 bar\n4444 qux')
c.seek(0)
dt = [('num', np.float64)]
x = np.fromregex(c, r"(\d+)\s+...", dt)
a = np.array([(1312,), (1534,), (4444,)], dtype=dt)
assert_array_equal(x, a)
@pytest.mark.parametrize("path_type", [str, Path])
def test_record_unicode(self, path_type):
utf8 = b'\xcf\x96'
with temppath() as str_path:
path = path_type(str_path)
with open(path, 'wb') as f:
f.write(b'1.312 foo' + utf8 + b' \n1.534 bar\n4.444 qux')
dt = [('num', np.float64), ('val', 'U4')]
x = np.fromregex(path, r"(?u)([0-9.]+)\s+(\w+)", dt, encoding='UTF-8')
a = np.array([(1.312, 'foo' + utf8.decode('UTF-8')), (1.534, 'bar'),
(4.444, 'qux')], dtype=dt)
assert_array_equal(x, a)
regexp = re.compile(r"([0-9.]+)\s+(\w+)", re.UNICODE)
x = np.fromregex(path, regexp, dt, encoding='UTF-8')
assert_array_equal(x, a)
def test_compiled_bytes(self):
regexp = re.compile(b'(\\d)')
c = BytesIO(b'123')
dt = [('num', np.float64)]
a = np.array([1, 2, 3], dtype=dt)
x = np.fromregex(c, regexp, dt)
assert_array_equal(x, a)
def test_bad_dtype_not_structured(self):
regexp = re.compile(b'(\\d)')
c = BytesIO(b'123')
with pytest.raises(TypeError, match='structured datatype'):
np.fromregex(c, regexp, dtype=np.float64)
#####--------------------------------------------------------------------------
class TestFromTxt(LoadTxtBase):
loadfunc = staticmethod(np.genfromtxt)
def test_record(self):
# Test w/ explicit dtype
data = TextIO('1 2\n3 4')
test = np.genfromtxt(data, dtype=[('x', np.int32), ('y', np.int32)])
control = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
assert_equal(test, control)
#
data = TextIO('M 64.0 75.0\nF 25.0 60.0')
descriptor = {'names': ('gender', 'age', 'weight'),
'formats': ('S1', 'i4', 'f4')}
control = np.array([('M', 64.0, 75.0), ('F', 25.0, 60.0)],
dtype=descriptor)
test = np.genfromtxt(data, dtype=descriptor)
assert_equal(test, control)
def test_array(self):
# Test outputting a standard ndarray
data = TextIO('1 2\n3 4')
control = np.array([[1, 2], [3, 4]], dtype=int)
test = np.genfromtxt(data, dtype=int)
assert_array_equal(test, control)
#
data.seek(0)
control = np.array([[1, 2], [3, 4]], dtype=float)
test = np.loadtxt(data, dtype=float)
assert_array_equal(test, control)
def test_1D(self):
# Test squeezing to 1D
control = np.array([1, 2, 3, 4], int)
#
data = TextIO('1\n2\n3\n4\n')
test = np.genfromtxt(data, dtype=int)
assert_array_equal(test, control)
#
data = TextIO('1,2,3,4\n')
test = np.genfromtxt(data, dtype=int, delimiter=',')
assert_array_equal(test, control)
def test_comments(self):
# Test the stripping of comments
control = np.array([1, 2, 3, 5], int)
# Comment on its own line
data = TextIO('# comment\n1,2,3,5\n')
test = np.genfromtxt(data, dtype=int, delimiter=',', comments='#')
assert_equal(test, control)
# Comment at the end of a line
data = TextIO('1,2,3,5# comment\n')
test = np.genfromtxt(data, dtype=int, delimiter=',', comments='#')
assert_equal(test, control)
def test_skiprows(self):
# Test row skipping
control = np.array([1, 2, 3, 5], int)
kwargs = dict(dtype=int, delimiter=',')
#
data = TextIO('comment\n1,2,3,5\n')
test = np.genfromtxt(data, skip_header=1, **kwargs)
assert_equal(test, control)
#
data = TextIO('# comment\n1,2,3,5\n')
test = np.loadtxt(data, skiprows=1, **kwargs)
assert_equal(test, control)
def test_skip_footer(self):
data = ["# %i" % i for i in range(1, 6)]
data.append("A, B, C")
data.extend(["%i,%3.1f,%03s" % (i, i, i) for i in range(51)])
data[-1] = "99,99"
kwargs = dict(delimiter=",", names=True, skip_header=5, skip_footer=10)
test = np.genfromtxt(TextIO("\n".join(data)), **kwargs)
ctrl = np.array([("%f" % i, "%f" % i, "%f" % i) for i in range(41)],
dtype=[(_, float) for _ in "ABC"])
assert_equal(test, ctrl)
def test_skip_footer_with_invalid(self):
with suppress_warnings() as sup:
sup.filter(ConversionWarning)
basestr = '1 1\n2 2\n3 3\n4 4\n5 \n6 \n7 \n'
# Footer too small to get rid of all invalid values
assert_raises(ValueError, np.genfromtxt,
TextIO(basestr), skip_footer=1)
# except ValueError:
# pass
a = np.genfromtxt(
TextIO(basestr), skip_footer=1, invalid_raise=False)
assert_equal(a, np.array([[1., 1.], [2., 2.], [3., 3.], [4., 4.]]))
#
a = np.genfromtxt(TextIO(basestr), skip_footer=3)
assert_equal(a, np.array([[1., 1.], [2., 2.], [3., 3.], [4., 4.]]))
#
basestr = '1 1\n2 \n3 3\n4 4\n5 \n6 6\n7 7\n'
a = np.genfromtxt(
TextIO(basestr), skip_footer=1, invalid_raise=False)
assert_equal(a, np.array([[1., 1.], [3., 3.], [4., 4.], [6., 6.]]))
a = np.genfromtxt(
TextIO(basestr), skip_footer=3, invalid_raise=False)
assert_equal(a, np.array([[1., 1.], [3., 3.], [4., 4.]]))
def test_header(self):
# Test retrieving a header
data = TextIO('gender age weight\nM 64.0 75.0\nF 25.0 60.0')
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, dtype=None, names=True)
assert_(w[0].category is np.VisibleDeprecationWarning)
control = {'gender': np.array([b'M', b'F']),
'age': np.array([64.0, 25.0]),
'weight': np.array([75.0, 60.0])}
assert_equal(test['gender'], control['gender'])
assert_equal(test['age'], control['age'])
assert_equal(test['weight'], control['weight'])
def test_auto_dtype(self):
# Test the automatic definition of the output dtype
data = TextIO('A 64 75.0 3+4j True\nBCD 25 60.0 5+6j False')
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, dtype=None)
assert_(w[0].category is np.VisibleDeprecationWarning)
control = [np.array([b'A', b'BCD']),
np.array([64, 25]),
np.array([75.0, 60.0]),
np.array([3 + 4j, 5 + 6j]),
np.array([True, False]), ]
assert_equal(test.dtype.names, ['f0', 'f1', 'f2', 'f3', 'f4'])
for (i, ctrl) in enumerate(control):
assert_equal(test['f%i' % i], ctrl)
def test_auto_dtype_uniform(self):
# Tests whether the output dtype can be uniformized
data = TextIO('1 2 3 4\n5 6 7 8\n')
test = np.genfromtxt(data, dtype=None)
control = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
assert_equal(test, control)
def test_fancy_dtype(self):
# Check that a nested dtype isn't MIA
data = TextIO('1,2,3.0\n4,5,6.0\n')
fancydtype = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
test = np.genfromtxt(data, dtype=fancydtype, delimiter=',')
control = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=fancydtype)
assert_equal(test, control)
def test_names_overwrite(self):
# Test overwriting the names of the dtype
descriptor = {'names': ('g', 'a', 'w'),
'formats': ('S1', 'i4', 'f4')}
data = TextIO(b'M 64.0 75.0\nF 25.0 60.0')
names = ('gender', 'age', 'weight')
test = np.genfromtxt(data, dtype=descriptor, names=names)
descriptor['names'] = names
control = np.array([('M', 64.0, 75.0),
('F', 25.0, 60.0)], dtype=descriptor)
assert_equal(test, control)
def test_bad_fname(self):
with pytest.raises(TypeError, match='fname must be a string,'):
np.genfromtxt(123)
def test_commented_header(self):
# Check that names can be retrieved even if the line is commented out.
data = TextIO("""
#gender age weight
M 21 72.100000
F 35 58.330000
M 33 21.99
""")
# The # is part of the first name and should be deleted automatically.
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, names=True, dtype=None)
assert_(w[0].category is np.VisibleDeprecationWarning)
ctrl = np.array([('M', 21, 72.1), ('F', 35, 58.33), ('M', 33, 21.99)],
dtype=[('gender', '|S1'), ('age', int), ('weight', float)])
assert_equal(test, ctrl)
# Ditto, but we should get rid of the first element
data = TextIO(b"""
# gender age weight
M 21 72.100000
F 35 58.330000
M 33 21.99
""")
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, names=True, dtype=None)
assert_(w[0].category is np.VisibleDeprecationWarning)
assert_equal(test, ctrl)
def test_names_and_comments_none(self):
# Tests case when names is true but comments is None (gh-10780)
data = TextIO('col1 col2\n 1 2\n 3 4')
test = np.genfromtxt(data, dtype=(int, int), comments=None, names=True)
control = np.array([(1, 2), (3, 4)], dtype=[('col1', int), ('col2', int)])
assert_equal(test, control)
def test_file_is_closed_on_error(self):
# gh-13200
with tempdir() as tmpdir:
fpath = os.path.join(tmpdir, "test.csv")
with open(fpath, "wb") as f:
f.write('\N{GREEK PI SYMBOL}'.encode())
# ResourceWarnings are emitted from a destructor, so won't be
# detected by regular propagation to errors.
with assert_no_warnings():
with pytest.raises(UnicodeDecodeError):
np.genfromtxt(fpath, encoding="ascii")
def test_autonames_and_usecols(self):
# Tests names and usecols
data = TextIO('A B C D\n aaaa 121 45 9.1')
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, usecols=('A', 'C', 'D'),
names=True, dtype=None)
assert_(w[0].category is np.VisibleDeprecationWarning)
control = np.array(('aaaa', 45, 9.1),
dtype=[('A', '|S4'), ('C', int), ('D', float)])
assert_equal(test, control)
def test_converters_with_usecols(self):
# Test the combination user-defined converters and usecol
data = TextIO('1,2,3,,5\n6,7,8,9,10\n')
test = np.genfromtxt(data, dtype=int, delimiter=',',
converters={3: lambda s: int(s or - 999)},
usecols=(1, 3,))
control = np.array([[2, -999], [7, 9]], int)
assert_equal(test, control)
def test_converters_with_usecols_and_names(self):
# Tests names and usecols
data = TextIO('A B C D\n aaaa 121 45 9.1')
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(data, usecols=('A', 'C', 'D'), names=True,
dtype=None,
converters={'C': lambda s: 2 * int(s)})
assert_(w[0].category is np.VisibleDeprecationWarning)
control = np.array(('aaaa', 90, 9.1),
dtype=[('A', '|S4'), ('C', int), ('D', float)])
assert_equal(test, control)
def test_converters_cornercases(self):
# Test the conversion to datetime.
converter = {
'date': lambda s: strptime(s, '%Y-%m-%d %H:%M:%SZ')}
data = TextIO('2009-02-03 12:00:00Z, 72214.0')
test = np.genfromtxt(data, delimiter=',', dtype=None,
names=['date', 'stid'], converters=converter)
control = np.array((datetime(2009, 2, 3), 72214.),
dtype=[('date', np.object_), ('stid', float)])
assert_equal(test, control)
def test_converters_cornercases2(self):
# Test the conversion to datetime64.
converter = {
'date': lambda s: np.datetime64(strptime(s, '%Y-%m-%d %H:%M:%SZ'))}
data = TextIO('2009-02-03 12:00:00Z, 72214.0')
test = np.genfromtxt(data, delimiter=',', dtype=None,
names=['date', 'stid'], converters=converter)
control = np.array((datetime(2009, 2, 3), 72214.),
dtype=[('date', 'datetime64[us]'), ('stid', float)])
assert_equal(test, control)
def test_unused_converter(self):
# Test whether unused converters are forgotten
data = TextIO("1 21\n 3 42\n")
test = np.genfromtxt(data, usecols=(1,),
converters={0: lambda s: int(s, 16)})
assert_equal(test, [21, 42])
#
data.seek(0)
test = np.genfromtxt(data, usecols=(1,),
converters={1: lambda s: int(s, 16)})
assert_equal(test, [33, 66])
def test_invalid_converter(self):
strip_rand = lambda x: float((b'r' in x.lower() and x.split()[-1]) or
(b'r' not in x.lower() and x.strip() or 0.0))
strip_per = lambda x: float((b'%' in x.lower() and x.split()[0]) or
(b'%' not in x.lower() and x.strip() or 0.0))
s = TextIO("D01N01,10/1/2003 ,1 %,R 75,400,600\r\n"
"L24U05,12/5/2003, 2 %,1,300, 150.5\r\n"
"D02N03,10/10/2004,R 1,,7,145.55")
kwargs = dict(
converters={2: strip_per, 3: strip_rand}, delimiter=",",
dtype=None)
assert_raises(ConverterError, np.genfromtxt, s, **kwargs)
def test_tricky_converter_bug1666(self):
# Test some corner cases
s = TextIO('q1,2\nq3,4')
cnv = lambda s: float(s[1:])
test = np.genfromtxt(s, delimiter=',', converters={0: cnv})
control = np.array([[1., 2.], [3., 4.]])
assert_equal(test, control)
def test_dtype_with_converters(self):
dstr = "2009; 23; 46"
test = np.genfromtxt(TextIO(dstr,),
delimiter=";", dtype=float, converters={0: bytes})
control = np.array([('2009', 23., 46)],
dtype=[('f0', '|S4'), ('f1', float), ('f2', float)])
assert_equal(test, control)
test = np.genfromtxt(TextIO(dstr,),
delimiter=";", dtype=float, converters={0: float})
control = np.array([2009., 23., 46],)
assert_equal(test, control)
def test_dtype_with_converters_and_usecols(self):
dstr = "1,5,-1,1:1\n2,8,-1,1:n\n3,3,-2,m:n\n"
dmap = {'1:1':0, '1:n':1, 'm:1':2, 'm:n':3}
dtyp = [('e1','i4'),('e2','i4'),('e3','i2'),('n', 'i1')]
conv = {0: int, 1: int, 2: int, 3: lambda r: dmap[r.decode()]}
test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
names=None, converters=conv)
control = np.rec.array([(1,5,-1,0), (2,8,-1,1), (3,3,-2,3)], dtype=dtyp)
assert_equal(test, control)
dtyp = [('e1','i4'),('e2','i4'),('n', 'i1')]
test = np.recfromcsv(TextIO(dstr,), dtype=dtyp, delimiter=',',
usecols=(0,1,3), names=None, converters=conv)
control = np.rec.array([(1,5,0), (2,8,1), (3,3,3)], dtype=dtyp)
assert_equal(test, control)
def test_dtype_with_object(self):
# Test using an explicit dtype with an object
data = """ 1; 2001-01-01
2; 2002-01-31 """
ndtype = [('idx', int), ('code', object)]
func = lambda s: strptime(s.strip(), "%Y-%m-%d")
converters = {1: func}
test = np.genfromtxt(TextIO(data), delimiter=";", dtype=ndtype,
converters=converters)
control = np.array(
[(1, datetime(2001, 1, 1)), (2, datetime(2002, 1, 31))],
dtype=ndtype)
assert_equal(test, control)
ndtype = [('nest', [('idx', int), ('code', object)])]
with assert_raises_regex(NotImplementedError,
'Nested fields.* not supported.*'):
test = np.genfromtxt(TextIO(data), delimiter=";",
dtype=ndtype, converters=converters)
# nested but empty fields also aren't supported
ndtype = [('idx', int), ('code', object), ('nest', [])]
with assert_raises_regex(NotImplementedError,
'Nested fields.* not supported.*'):
test = np.genfromtxt(TextIO(data), delimiter=";",
dtype=ndtype, converters=converters)
def test_dtype_with_object_no_converter(self):
# Object without a converter uses bytes:
parsed = np.genfromtxt(TextIO("1"), dtype=object)
assert parsed[()] == b"1"
parsed = np.genfromtxt(TextIO("string"), dtype=object)
assert parsed[()] == b"string"
def test_userconverters_with_explicit_dtype(self):
# Test user_converters w/ explicit (standard) dtype
data = TextIO('skip,skip,2001-01-01,1.0,skip')
test = np.genfromtxt(data, delimiter=",", names=None, dtype=float,
usecols=(2, 3), converters={2: bytes})
control = np.array([('2001-01-01', 1.)],
dtype=[('', '|S10'), ('', float)])
assert_equal(test, control)
def test_utf8_userconverters_with_explicit_dtype(self):
utf8 = b'\xcf\x96'
with temppath() as path:
with open(path, 'wb') as f:
f.write(b'skip,skip,2001-01-01' + utf8 + b',1.0,skip')
test = np.genfromtxt(path, delimiter=",", names=None, dtype=float,
usecols=(2, 3), converters={2: np.compat.unicode},
encoding='UTF-8')
control = np.array([('2001-01-01' + utf8.decode('UTF-8'), 1.)],
dtype=[('', '|U11'), ('', float)])
assert_equal(test, control)
def test_spacedelimiter(self):
# Test space delimiter
data = TextIO("1 2 3 4 5\n6 7 8 9 10")
test = np.genfromtxt(data)
control = np.array([[1., 2., 3., 4., 5.],
[6., 7., 8., 9., 10.]])
assert_equal(test, control)
def test_integer_delimiter(self):
# Test using an integer for delimiter
data = " 1 2 3\n 4 5 67\n890123 4"
test = np.genfromtxt(TextIO(data), delimiter=3)
control = np.array([[1, 2, 3], [4, 5, 67], [890, 123, 4]])
assert_equal(test, control)
def test_missing(self):
data = TextIO('1,2,3,,5\n')
test = np.genfromtxt(data, dtype=int, delimiter=',',
converters={3: lambda s: int(s or - 999)})
control = np.array([1, 2, 3, -999, 5], int)
assert_equal(test, control)
def test_missing_with_tabs(self):
# Test w/ a delimiter tab
txt = "1\t2\t3\n\t2\t\n1\t\t3"
test = np.genfromtxt(TextIO(txt), delimiter="\t",
usemask=True,)
ctrl_d = np.array([(1, 2, 3), (np.nan, 2, np.nan), (1, np.nan, 3)],)
ctrl_m = np.array([(0, 0, 0), (1, 0, 1), (0, 1, 0)], dtype=bool)
assert_equal(test.data, ctrl_d)
assert_equal(test.mask, ctrl_m)
def test_usecols(self):
# Test the selection of columns
# Select 1 column
control = np.array([[1, 2], [3, 4]], float)
data = TextIO()
np.savetxt(data, control)
data.seek(0)
test = np.genfromtxt(data, dtype=float, usecols=(1,))
assert_equal(test, control[:, 1])
#
control = np.array([[1, 2, 3], [3, 4, 5]], float)
data = TextIO()
np.savetxt(data, control)
data.seek(0)
test = np.genfromtxt(data, dtype=float, usecols=(1, 2))
assert_equal(test, control[:, 1:])
# Testing with arrays instead of tuples.
data.seek(0)
test = np.genfromtxt(data, dtype=float, usecols=np.array([1, 2]))
assert_equal(test, control[:, 1:])
def test_usecols_as_css(self):
# Test giving usecols with a comma-separated string
data = "1 2 3\n4 5 6"
test = np.genfromtxt(TextIO(data),
names="a, b, c", usecols="a, c")
ctrl = np.array([(1, 3), (4, 6)], dtype=[(_, float) for _ in "ac"])
assert_equal(test, ctrl)
def test_usecols_with_structured_dtype(self):
# Test usecols with an explicit structured dtype
data = TextIO("JOE 70.1 25.3\nBOB 60.5 27.9")
names = ['stid', 'temp']
dtypes = ['S4', 'f8']
test = np.genfromtxt(
data, usecols=(0, 2), dtype=list(zip(names, dtypes)))
assert_equal(test['stid'], [b"JOE", b"BOB"])
assert_equal(test['temp'], [25.3, 27.9])
def test_usecols_with_integer(self):
# Test usecols with an integer
test = np.genfromtxt(TextIO(b"1 2 3\n4 5 6"), usecols=0)
assert_equal(test, np.array([1., 4.]))
def test_usecols_with_named_columns(self):
# Test usecols with named columns
ctrl = np.array([(1, 3), (4, 6)], dtype=[('a', float), ('c', float)])
data = "1 2 3\n4 5 6"
kwargs = dict(names="a, b, c")
test = np.genfromtxt(TextIO(data), usecols=(0, -1), **kwargs)
assert_equal(test, ctrl)
test = np.genfromtxt(TextIO(data),
usecols=('a', 'c'), **kwargs)
assert_equal(test, ctrl)
def test_empty_file(self):
# Test that an empty file raises the proper warning.
with suppress_warnings() as sup:
sup.filter(message="genfromtxt: Empty input file:")
data = TextIO()
test = np.genfromtxt(data)
assert_equal(test, np.array([]))
# when skip_header > 0
test = np.genfromtxt(data, skip_header=1)
assert_equal(test, np.array([]))
def test_fancy_dtype_alt(self):
# Check that a nested dtype isn't MIA
data = TextIO('1,2,3.0\n4,5,6.0\n')
fancydtype = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
test = np.genfromtxt(data, dtype=fancydtype, delimiter=',', usemask=True)
control = ma.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=fancydtype)
assert_equal(test, control)
def test_shaped_dtype(self):
c = TextIO("aaaa 1.0 8.0 1 2 3 4 5 6")
dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
('block', int, (2, 3))])
x = np.genfromtxt(c, dtype=dt)
a = np.array([('aaaa', 1.0, 8.0, [[1, 2, 3], [4, 5, 6]])],
dtype=dt)
assert_array_equal(x, a)
def test_withmissing(self):
data = TextIO('A,B\n0,1\n2,N/A')
kwargs = dict(delimiter=",", missing_values="N/A", names=True)
test = np.genfromtxt(data, dtype=None, usemask=True, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', int), ('B', int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
#
data.seek(0)
test = np.genfromtxt(data, usemask=True, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', float), ('B', float)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
def test_user_missing_values(self):
data = "A, B, C\n0, 0., 0j\n1, N/A, 1j\n-9, 2.2, N/A\n3, -99, 3j"
basekwargs = dict(dtype=None, delimiter=",", names=True,)
mdtype = [('A', int), ('B', float), ('C', complex)]
#
test = np.genfromtxt(TextIO(data), missing_values="N/A",
**basekwargs)
control = ma.array([(0, 0.0, 0j), (1, -999, 1j),
(-9, 2.2, -999j), (3, -99, 3j)],
mask=[(0, 0, 0), (0, 1, 0), (0, 0, 1), (0, 0, 0)],
dtype=mdtype)
assert_equal(test, control)
#
basekwargs['dtype'] = mdtype
test = np.genfromtxt(TextIO(data),
missing_values={0: -9, 1: -99, 2: -999j}, usemask=True, **basekwargs)
control = ma.array([(0, 0.0, 0j), (1, -999, 1j),
(-9, 2.2, -999j), (3, -99, 3j)],
mask=[(0, 0, 0), (0, 1, 0), (1, 0, 1), (0, 1, 0)],
dtype=mdtype)
assert_equal(test, control)
#
test = np.genfromtxt(TextIO(data),
missing_values={0: -9, 'B': -99, 'C': -999j},
usemask=True,
**basekwargs)
control = ma.array([(0, 0.0, 0j), (1, -999, 1j),
(-9, 2.2, -999j), (3, -99, 3j)],
mask=[(0, 0, 0), (0, 1, 0), (1, 0, 1), (0, 1, 0)],
dtype=mdtype)
assert_equal(test, control)
def test_user_filling_values(self):
# Test with missing and filling values
ctrl = np.array([(0, 3), (4, -999)], dtype=[('a', int), ('b', int)])
data = "N/A, 2, 3\n4, ,???"
kwargs = dict(delimiter=",",
dtype=int,
names="a,b,c",
missing_values={0: "N/A", 'b': " ", 2: "???"},
filling_values={0: 0, 'b': 0, 2: -999})
test = np.genfromtxt(TextIO(data), **kwargs)
ctrl = np.array([(0, 2, 3), (4, 0, -999)],
dtype=[(_, int) for _ in "abc"])
assert_equal(test, ctrl)
#
test = np.genfromtxt(TextIO(data), usecols=(0, -1), **kwargs)
ctrl = np.array([(0, 3), (4, -999)], dtype=[(_, int) for _ in "ac"])
assert_equal(test, ctrl)
data2 = "1,2,*,4\n5,*,7,8\n"
test = np.genfromtxt(TextIO(data2), delimiter=',', dtype=int,
missing_values="*", filling_values=0)
ctrl = np.array([[1, 2, 0, 4], [5, 0, 7, 8]])
assert_equal(test, ctrl)
test = np.genfromtxt(TextIO(data2), delimiter=',', dtype=int,
missing_values="*", filling_values=-1)
ctrl = np.array([[1, 2, -1, 4], [5, -1, 7, 8]])
assert_equal(test, ctrl)
def test_withmissing_float(self):
data = TextIO('A,B\n0,1.5\n2,-999.00')
test = np.genfromtxt(data, dtype=None, delimiter=',',
missing_values='-999.0', names=True, usemask=True)
control = ma.array([(0, 1.5), (2, -1.)],
mask=[(False, False), (False, True)],
dtype=[('A', int), ('B', float)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
def test_with_masked_column_uniform(self):
# Test masked column
data = TextIO('1 2 3\n4 5 6\n')
test = np.genfromtxt(data, dtype=None,
missing_values='2,5', usemask=True)
control = ma.array([[1, 2, 3], [4, 5, 6]], mask=[[0, 1, 0], [0, 1, 0]])
assert_equal(test, control)
def test_with_masked_column_various(self):
# Test masked column
data = TextIO('True 2 3\nFalse 5 6\n')
test = np.genfromtxt(data, dtype=None,
missing_values='2,5', usemask=True)
control = ma.array([(1, 2, 3), (0, 5, 6)],
mask=[(0, 1, 0), (0, 1, 0)],
dtype=[('f0', bool), ('f1', bool), ('f2', int)])
assert_equal(test, control)
def test_invalid_raise(self):
# Test invalid raise
data = ["1, 1, 1, 1, 1"] * 50
for i in range(5):
data[10 * i] = "2, 2, 2, 2 2"
data.insert(0, "a, b, c, d, e")
mdata = TextIO("\n".join(data))
kwargs = dict(delimiter=",", dtype=None, names=True)
def f():
return np.genfromtxt(mdata, invalid_raise=False, **kwargs)
mtest = assert_warns(ConversionWarning, f)
assert_equal(len(mtest), 45)
assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
#
mdata.seek(0)
assert_raises(ValueError, np.genfromtxt, mdata,
delimiter=",", names=True)
def test_invalid_raise_with_usecols(self):
# Test invalid_raise with usecols
data = ["1, 1, 1, 1, 1"] * 50
for i in range(5):
data[10 * i] = "2, 2, 2, 2 2"
data.insert(0, "a, b, c, d, e")
mdata = TextIO("\n".join(data))
kwargs = dict(delimiter=",", dtype=None, names=True,
invalid_raise=False)
def f():
return np.genfromtxt(mdata, usecols=(0, 4), **kwargs)
mtest = assert_warns(ConversionWarning, f)
assert_equal(len(mtest), 45)
assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'ae']))
#
mdata.seek(0)
mtest = np.genfromtxt(mdata, usecols=(0, 1), **kwargs)
assert_equal(len(mtest), 50)
control = np.ones(50, dtype=[(_, int) for _ in 'ab'])
control[[10 * _ for _ in range(5)]] = (2, 2)
assert_equal(mtest, control)
def test_inconsistent_dtype(self):
# Test inconsistent dtype
data = ["1, 1, 1, 1, -1.1"] * 50
mdata = TextIO("\n".join(data))
converters = {4: lambda x: "(%s)" % x.decode()}
kwargs = dict(delimiter=",", converters=converters,
dtype=[(_, int) for _ in 'abcde'],)
assert_raises(ValueError, np.genfromtxt, mdata, **kwargs)
def test_default_field_format(self):
# Test default format
data = "0, 1, 2.3\n4, 5, 6.7"
mtest = np.genfromtxt(TextIO(data),
delimiter=",", dtype=None, defaultfmt="f%02i")
ctrl = np.array([(0, 1, 2.3), (4, 5, 6.7)],
dtype=[("f00", int), ("f01", int), ("f02", float)])
assert_equal(mtest, ctrl)
def test_single_dtype_wo_names(self):
# Test single dtype w/o names
data = "0, 1, 2.3\n4, 5, 6.7"
mtest = np.genfromtxt(TextIO(data),
delimiter=",", dtype=float, defaultfmt="f%02i")
ctrl = np.array([[0., 1., 2.3], [4., 5., 6.7]], dtype=float)
assert_equal(mtest, ctrl)
def test_single_dtype_w_explicit_names(self):
# Test single dtype w explicit names
data = "0, 1, 2.3\n4, 5, 6.7"
mtest = np.genfromtxt(TextIO(data),
delimiter=",", dtype=float, names="a, b, c")
ctrl = np.array([(0., 1., 2.3), (4., 5., 6.7)],
dtype=[(_, float) for _ in "abc"])
assert_equal(mtest, ctrl)
def test_single_dtype_w_implicit_names(self):
# Test single dtype w implicit names
data = "a, b, c\n0, 1, 2.3\n4, 5, 6.7"
mtest = np.genfromtxt(TextIO(data),
delimiter=",", dtype=float, names=True)
ctrl = np.array([(0., 1., 2.3), (4., 5., 6.7)],
dtype=[(_, float) for _ in "abc"])
assert_equal(mtest, ctrl)
def test_easy_structured_dtype(self):
# Test easy structured dtype
data = "0, 1, 2.3\n4, 5, 6.7"
mtest = np.genfromtxt(TextIO(data), delimiter=",",
dtype=(int, float, float), defaultfmt="f_%02i")
ctrl = np.array([(0, 1., 2.3), (4, 5., 6.7)],
dtype=[("f_00", int), ("f_01", float), ("f_02", float)])
assert_equal(mtest, ctrl)
def test_autostrip(self):
# Test autostrip
data = "01/01/2003 , 1.3, abcde"
kwargs = dict(delimiter=",", dtype=None)
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
mtest = np.genfromtxt(TextIO(data), **kwargs)
assert_(w[0].category is np.VisibleDeprecationWarning)
ctrl = np.array([('01/01/2003 ', 1.3, ' abcde')],
dtype=[('f0', '|S12'), ('f1', float), ('f2', '|S8')])
assert_equal(mtest, ctrl)
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
mtest = np.genfromtxt(TextIO(data), autostrip=True, **kwargs)
assert_(w[0].category is np.VisibleDeprecationWarning)
ctrl = np.array([('01/01/2003', 1.3, 'abcde')],
dtype=[('f0', '|S10'), ('f1', float), ('f2', '|S5')])
assert_equal(mtest, ctrl)
def test_replace_space(self):
# Test the 'replace_space' option
txt = "A.A, B (B), C:C\n1, 2, 3.14"
# Test default: replace ' ' by '_' and delete non-alphanum chars
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None)
ctrl_dtype = [("AA", int), ("B_B", int), ("CC", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no replace, no delete
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None,
replace_space='', deletechars='')
ctrl_dtype = [("A.A", int), ("B (B)", int), ("C:C", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no delete (spaces are replaced by _)
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=None,
deletechars='')
ctrl_dtype = [("A.A", int), ("B_(B)", int), ("C:C", float)]
ctrl = np.array((1, 2, 3.14), dtype=ctrl_dtype)
assert_equal(test, ctrl)
def test_replace_space_known_dtype(self):
# Test the 'replace_space' (and related) options when dtype != None
txt = "A.A, B (B), C:C\n1, 2, 3"
# Test default: replace ' ' by '_' and delete non-alphanum chars
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int)
ctrl_dtype = [("AA", int), ("B_B", int), ("CC", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no replace, no delete
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int,
replace_space='', deletechars='')
ctrl_dtype = [("A.A", int), ("B (B)", int), ("C:C", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
# Test: no delete (spaces are replaced by _)
test = np.genfromtxt(TextIO(txt),
delimiter=",", names=True, dtype=int,
deletechars='')
ctrl_dtype = [("A.A", int), ("B_(B)", int), ("C:C", int)]
ctrl = np.array((1, 2, 3), dtype=ctrl_dtype)
assert_equal(test, ctrl)
def test_incomplete_names(self):
# Test w/ incomplete names
data = "A,,C\n0,1,2\n3,4,5"
kwargs = dict(delimiter=",", names=True)
# w/ dtype=None
ctrl = np.array([(0, 1, 2), (3, 4, 5)],
dtype=[(_, int) for _ in ('A', 'f0', 'C')])
test = np.genfromtxt(TextIO(data), dtype=None, **kwargs)
assert_equal(test, ctrl)
# w/ default dtype
ctrl = np.array([(0, 1, 2), (3, 4, 5)],
dtype=[(_, float) for _ in ('A', 'f0', 'C')])
test = np.genfromtxt(TextIO(data), **kwargs)
def test_names_auto_completion(self):
# Make sure that names are properly completed
data = "1 2 3\n 4 5 6"
test = np.genfromtxt(TextIO(data),
dtype=(int, float, int), names="a")
ctrl = np.array([(1, 2, 3), (4, 5, 6)],
dtype=[('a', int), ('f0', float), ('f1', int)])
assert_equal(test, ctrl)
def test_names_with_usecols_bug1636(self):
# Make sure we pick up the right names w/ usecols
data = "A,B,C,D,E\n0,1,2,3,4\n0,1,2,3,4\n0,1,2,3,4"
ctrl_names = ("A", "C", "E")
test = np.genfromtxt(TextIO(data),
dtype=(int, int, int), delimiter=",",
usecols=(0, 2, 4), names=True)
assert_equal(test.dtype.names, ctrl_names)
#
test = np.genfromtxt(TextIO(data),
dtype=(int, int, int), delimiter=",",
usecols=("A", "C", "E"), names=True)
assert_equal(test.dtype.names, ctrl_names)
#
test = np.genfromtxt(TextIO(data),
dtype=int, delimiter=",",
usecols=("A", "C", "E"), names=True)
assert_equal(test.dtype.names, ctrl_names)
def test_fixed_width_names(self):
# Test fix-width w/ names
data = " A B C\n 0 1 2.3\n 45 67 9."
kwargs = dict(delimiter=(5, 5, 4), names=True, dtype=None)
ctrl = np.array([(0, 1, 2.3), (45, 67, 9.)],
dtype=[('A', int), ('B', int), ('C', float)])
test = np.genfromtxt(TextIO(data), **kwargs)
assert_equal(test, ctrl)
#
kwargs = dict(delimiter=5, names=True, dtype=None)
ctrl = np.array([(0, 1, 2.3), (45, 67, 9.)],
dtype=[('A', int), ('B', int), ('C', float)])
test = np.genfromtxt(TextIO(data), **kwargs)
assert_equal(test, ctrl)
def test_filling_values(self):
# Test missing values
data = b"1, 2, 3\n1, , 5\n0, 6, \n"
kwargs = dict(delimiter=",", dtype=None, filling_values=-999)
ctrl = np.array([[1, 2, 3], [1, -999, 5], [0, 6, -999]], dtype=int)
test = np.genfromtxt(TextIO(data), **kwargs)
assert_equal(test, ctrl)
def test_comments_is_none(self):
# Github issue 329 (None was previously being converted to 'None').
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(TextIO("test1,testNonetherestofthedata"),
dtype=None, comments=None, delimiter=',')
assert_(w[0].category is np.VisibleDeprecationWarning)
assert_equal(test[1], b'testNonetherestofthedata')
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(TextIO("test1, testNonetherestofthedata"),
dtype=None, comments=None, delimiter=',')
assert_(w[0].category is np.VisibleDeprecationWarning)
assert_equal(test[1], b' testNonetherestofthedata')
def test_latin1(self):
latin1 = b'\xf6\xfc\xf6'
norm = b"norm1,norm2,norm3\n"
enc = b"test1,testNonethe" + latin1 + b",test3\n"
s = norm + enc + norm
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(TextIO(s),
dtype=None, comments=None, delimiter=',')
assert_(w[0].category is np.VisibleDeprecationWarning)
assert_equal(test[1, 0], b"test1")
assert_equal(test[1, 1], b"testNonethe" + latin1)
assert_equal(test[1, 2], b"test3")
test = np.genfromtxt(TextIO(s),
dtype=None, comments=None, delimiter=',',
encoding='latin1')
assert_equal(test[1, 0], "test1")
assert_equal(test[1, 1], "testNonethe" + latin1.decode('latin1'))
assert_equal(test[1, 2], "test3")
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(TextIO(b"0,testNonethe" + latin1),
dtype=None, comments=None, delimiter=',')
assert_(w[0].category is np.VisibleDeprecationWarning)
assert_equal(test['f0'], 0)
assert_equal(test['f1'], b"testNonethe" + latin1)
def test_binary_decode_autodtype(self):
utf16 = b'\xff\xfeh\x04 \x00i\x04 \x00j\x04'
v = self.loadfunc(BytesIO(utf16), dtype=None, encoding='UTF-16')
assert_array_equal(v, np.array(utf16.decode('UTF-16').split()))
def test_utf8_byte_encoding(self):
utf8 = b"\xcf\x96"
norm = b"norm1,norm2,norm3\n"
enc = b"test1,testNonethe" + utf8 + b",test3\n"
s = norm + enc + norm
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '', np.VisibleDeprecationWarning)
test = np.genfromtxt(TextIO(s),
dtype=None, comments=None, delimiter=',')
assert_(w[0].category is np.VisibleDeprecationWarning)
ctl = np.array([
[b'norm1', b'norm2', b'norm3'],
[b'test1', b'testNonethe' + utf8, b'test3'],
[b'norm1', b'norm2', b'norm3']])
assert_array_equal(test, ctl)
def test_utf8_file(self):
utf8 = b"\xcf\x96"
with temppath() as path:
with open(path, "wb") as f:
f.write((b"test1,testNonethe" + utf8 + b",test3\n") * 2)
test = np.genfromtxt(path, dtype=None, comments=None,
delimiter=',', encoding="UTF-8")
ctl = np.array([
["test1", "testNonethe" + utf8.decode("UTF-8"), "test3"],
["test1", "testNonethe" + utf8.decode("UTF-8"), "test3"]],
dtype=np.str_)
assert_array_equal(test, ctl)
# test a mixed dtype
with open(path, "wb") as f:
f.write(b"0,testNonethe" + utf8)
test = np.genfromtxt(path, dtype=None, comments=None,
delimiter=',', encoding="UTF-8")
assert_equal(test['f0'], 0)
assert_equal(test['f1'], "testNonethe" + utf8.decode("UTF-8"))
def test_utf8_file_nodtype_unicode(self):
# bytes encoding with non-latin1 -> unicode upcast
utf8 = '\u03d6'
latin1 = '\xf6\xfc\xf6'
# skip test if cannot encode utf8 test string with preferred
# encoding. The preferred encoding is assumed to be the default
# encoding of io.open. Will need to change this for PyTest, maybe
# using pytest.mark.xfail(raises=***).
try:
encoding = locale.getpreferredencoding()
utf8.encode(encoding)
except (UnicodeError, ImportError):
pytest.skip('Skipping test_utf8_file_nodtype_unicode, '
'unable to encode utf8 in preferred encoding')
with temppath() as path:
with io.open(path, "wt") as f:
f.write("norm1,norm2,norm3\n")
f.write("norm1," + latin1 + ",norm3\n")
f.write("test1,testNonethe" + utf8 + ",test3\n")
with warnings.catch_warnings(record=True) as w:
warnings.filterwarnings('always', '',
np.VisibleDeprecationWarning)
test = np.genfromtxt(path, dtype=None, comments=None,
delimiter=',')
# Check for warning when encoding not specified.
assert_(w[0].category is np.VisibleDeprecationWarning)
ctl = np.array([
["norm1", "norm2", "norm3"],
["norm1", latin1, "norm3"],
["test1", "testNonethe" + utf8, "test3"]],
dtype=np.str_)
assert_array_equal(test, ctl)
def test_recfromtxt(self):
#
data = TextIO('A,B\n0,1\n2,3')
kwargs = dict(delimiter=",", missing_values="N/A", names=True)
test = np.recfromtxt(data, **kwargs)
control = np.array([(0, 1), (2, 3)],
dtype=[('A', int), ('B', int)])
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
#
data = TextIO('A,B\n0,1\n2,N/A')
test = np.recfromtxt(data, dtype=None, usemask=True, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', int), ('B', int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
assert_equal(test.A, [0, 2])
def test_recfromcsv(self):
#
data = TextIO('A,B\n0,1\n2,3')
kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
test = np.recfromcsv(data, dtype=None, **kwargs)
control = np.array([(0, 1), (2, 3)],
dtype=[('A', int), ('B', int)])
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
#
data = TextIO('A,B\n0,1\n2,N/A')
test = np.recfromcsv(data, dtype=None, usemask=True, **kwargs)
control = ma.array([(0, 1), (2, -1)],
mask=[(False, False), (False, True)],
dtype=[('A', int), ('B', int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
assert_equal(test.A, [0, 2])
#
data = TextIO('A,B\n0,1\n2,3')
test = np.recfromcsv(data, missing_values='N/A',)
control = np.array([(0, 1), (2, 3)],
dtype=[('a', int), ('b', int)])
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
#
data = TextIO('A,B\n0,1\n2,3')
dtype = [('a', int), ('b', float)]
test = np.recfromcsv(data, missing_values='N/A', dtype=dtype)
control = np.array([(0, 1), (2, 3)],
dtype=dtype)
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
#gh-10394
data = TextIO('color\n"red"\n"blue"')
test = np.recfromcsv(data, converters={0: lambda x: x.strip(b'\"')})
control = np.array([('red',), ('blue',)], dtype=[('color', (bytes, 4))])
assert_equal(test.dtype, control.dtype)
assert_equal(test, control)
def test_max_rows(self):
# Test the `max_rows` keyword argument.
data = '1 2\n3 4\n5 6\n7 8\n9 10\n'
txt = TextIO(data)
a1 = np.genfromtxt(txt, max_rows=3)
a2 = np.genfromtxt(txt)
assert_equal(a1, [[1, 2], [3, 4], [5, 6]])
assert_equal(a2, [[7, 8], [9, 10]])
# max_rows must be at least 1.
assert_raises(ValueError, np.genfromtxt, TextIO(data), max_rows=0)
# An input with several invalid rows.
data = '1 1\n2 2\n0 \n3 3\n4 4\n5 \n6 \n7 \n'
test = np.genfromtxt(TextIO(data), max_rows=2)
control = np.array([[1., 1.], [2., 2.]])
assert_equal(test, control)
# Test keywords conflict
assert_raises(ValueError, np.genfromtxt, TextIO(data), skip_footer=1,
max_rows=4)
# Test with invalid value
assert_raises(ValueError, np.genfromtxt, TextIO(data), max_rows=4)
# Test with invalid not raise
with suppress_warnings() as sup:
sup.filter(ConversionWarning)
test = np.genfromtxt(TextIO(data), max_rows=4, invalid_raise=False)
control = np.array([[1., 1.], [2., 2.], [3., 3.], [4., 4.]])
assert_equal(test, control)
test = np.genfromtxt(TextIO(data), max_rows=5, invalid_raise=False)
control = np.array([[1., 1.], [2., 2.], [3., 3.], [4., 4.]])
assert_equal(test, control)
# Structured array with field names.
data = 'a b\n#c d\n1 1\n2 2\n#0 \n3 3\n4 4\n5 5\n'
# Test with header, names and comments
txt = TextIO(data)
test = np.genfromtxt(txt, skip_header=1, max_rows=3, names=True)
control = np.array([(1.0, 1.0), (2.0, 2.0), (3.0, 3.0)],
dtype=[('c', '<f8'), ('d', '<f8')])
assert_equal(test, control)
# To continue reading the same "file", don't use skip_header or
# names, and use the previously determined dtype.
test = np.genfromtxt(txt, max_rows=None, dtype=test.dtype)
control = np.array([(4.0, 4.0), (5.0, 5.0)],
dtype=[('c', '<f8'), ('d', '<f8')])
assert_equal(test, control)
def test_gft_using_filename(self):
# Test that we can load data from a filename as well as a file
# object
tgt = np.arange(6).reshape((2, 3))
linesep = ('\n', '\r\n', '\r')
for sep in linesep:
data = '0 1 2' + sep + '3 4 5'
with temppath() as name:
with open(name, 'w') as f:
f.write(data)
res = np.genfromtxt(name)
assert_array_equal(res, tgt)
def test_gft_from_gzip(self):
# Test that we can load data from a gzipped file
wanted = np.arange(6).reshape((2, 3))
linesep = ('\n', '\r\n', '\r')
for sep in linesep:
data = '0 1 2' + sep + '3 4 5'
s = BytesIO()
with gzip.GzipFile(fileobj=s, mode='w') as g:
g.write(asbytes(data))
with temppath(suffix='.gz2') as name:
with open(name, 'w') as f:
f.write(data)
assert_array_equal(np.genfromtxt(name), wanted)
def test_gft_using_generator(self):
# gft doesn't work with unicode.
def count():
for i in range(10):
yield asbytes("%d" % i)
res = np.genfromtxt(count())
assert_array_equal(res, np.arange(10))
def test_auto_dtype_largeint(self):
# Regression test for numpy/numpy#5635 whereby large integers could
# cause OverflowErrors.
# Test the automatic definition of the output dtype
#
# 2**66 = 73786976294838206464 => should convert to float
# 2**34 = 17179869184 => should convert to int64
# 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
# int64 on 64-bit systems)
data = TextIO('73786976294838206464 17179869184 1024')
test = np.genfromtxt(data, dtype=None)
assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])
assert_(test.dtype['f0'] == float)
assert_(test.dtype['f1'] == np.int64)
assert_(test.dtype['f2'] == np.int_)
assert_allclose(test['f0'], 73786976294838206464.)
assert_equal(test['f1'], 17179869184)
assert_equal(test['f2'], 1024)
def test_unpack_float_data(self):
txt = TextIO("1,2,3\n4,5,6\n7,8,9\n0.0,1.0,2.0")
a, b, c = np.loadtxt(txt, delimiter=",", unpack=True)
assert_array_equal(a, np.array([1.0, 4.0, 7.0, 0.0]))
assert_array_equal(b, np.array([2.0, 5.0, 8.0, 1.0]))
assert_array_equal(c, np.array([3.0, 6.0, 9.0, 2.0]))
def test_unpack_structured(self):
# Regression test for gh-4341
# Unpacking should work on structured arrays
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('S1', 'i4', 'f4')}
a, b, c = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_equal(a.dtype, np.dtype('S1'))
assert_equal(b.dtype, np.dtype('i4'))
assert_equal(c.dtype, np.dtype('f4'))
assert_array_equal(a, np.array([b'M', b'F']))
assert_array_equal(b, np.array([21, 35]))
assert_array_equal(c, np.array([72., 58.]))
def test_unpack_auto_dtype(self):
# Regression test for gh-4341
# Unpacking should work when dtype=None
txt = TextIO("M 21 72.\nF 35 58.")
expected = (np.array(["M", "F"]), np.array([21, 35]), np.array([72., 58.]))
test = np.genfromtxt(txt, dtype=None, unpack=True, encoding="utf-8")
for arr, result in zip(expected, test):
assert_array_equal(arr, result)
assert_equal(arr.dtype, result.dtype)
def test_unpack_single_name(self):
# Regression test for gh-4341
# Unpacking should work when structured dtype has only one field
txt = TextIO("21\n35")
dt = {'names': ('a',), 'formats': ('i4',)}
expected = np.array([21, 35], dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal(expected.dtype, test.dtype)
def test_squeeze_scalar(self):
# Regression test for gh-4341
# Unpacking a scalar should give zero-dim output,
# even if dtype is structured
txt = TextIO("1")
dt = {'names': ('a',), 'formats': ('i4',)}
expected = np.array((1,), dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal((), test.shape)
assert_equal(expected.dtype, test.dtype)
@pytest.mark.parametrize("ndim", [0, 1, 2])
def test_ndmin_keyword(self, ndim: int):
# lets have the same behaviour of ndmin as loadtxt
# as they should be the same for non-missing values
txt = "42"
a = np.loadtxt(StringIO(txt), ndmin=ndim)
b = np.genfromtxt(StringIO(txt), ndmin=ndim)
assert_array_equal(a, b)
class TestPathUsage:
# Test that pathlib.Path can be used
def test_loadtxt(self):
with temppath(suffix='.txt') as path:
path = Path(path)
a = np.array([[1.1, 2], [3, 4]])
np.savetxt(path, a)
x = np.loadtxt(path)
assert_array_equal(x, a)
def test_save_load(self):
# Test that pathlib.Path instances can be used with save.
with temppath(suffix='.npy') as path:
path = Path(path)
a = np.array([[1, 2], [3, 4]], int)
np.save(path, a)
data = np.load(path)
assert_array_equal(data, a)
def test_save_load_memmap(self):
# Test that pathlib.Path instances can be loaded mem-mapped.
with temppath(suffix='.npy') as path:
path = Path(path)
a = np.array([[1, 2], [3, 4]], int)
np.save(path, a)
data = np.load(path, mmap_mode='r')
assert_array_equal(data, a)
# close the mem-mapped file
del data
if IS_PYPY:
break_cycles()
break_cycles()
@pytest.mark.xfail(IS_WASM, reason="memmap doesn't work correctly")
def test_save_load_memmap_readwrite(self):
# Test that pathlib.Path instances can be written mem-mapped.
with temppath(suffix='.npy') as path:
path = Path(path)
a = np.array([[1, 2], [3, 4]], int)
np.save(path, a)
b = np.load(path, mmap_mode='r+')
a[0][0] = 5
b[0][0] = 5
del b # closes the file
if IS_PYPY:
break_cycles()
break_cycles()
data = np.load(path)
assert_array_equal(data, a)
def test_savez_load(self):
# Test that pathlib.Path instances can be used with savez.
with temppath(suffix='.npz') as path:
path = Path(path)
np.savez(path, lab='place holder')
with np.load(path) as data:
assert_array_equal(data['lab'], 'place holder')
def test_savez_compressed_load(self):
# Test that pathlib.Path instances can be used with savez.
with temppath(suffix='.npz') as path:
path = Path(path)
np.savez_compressed(path, lab='place holder')
data = np.load(path)
assert_array_equal(data['lab'], 'place holder')
data.close()
def test_genfromtxt(self):
with temppath(suffix='.txt') as path:
path = Path(path)
a = np.array([(1, 2), (3, 4)])
np.savetxt(path, a)
data = np.genfromtxt(path)
assert_array_equal(a, data)
def test_recfromtxt(self):
with temppath(suffix='.txt') as path:
path = Path(path)
with path.open('w') as f:
f.write('A,B\n0,1\n2,3')
kwargs = dict(delimiter=",", missing_values="N/A", names=True)
test = np.recfromtxt(path, **kwargs)
control = np.array([(0, 1), (2, 3)],
dtype=[('A', int), ('B', int)])
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
def test_recfromcsv(self):
with temppath(suffix='.txt') as path:
path = Path(path)
with path.open('w') as f:
f.write('A,B\n0,1\n2,3')
kwargs = dict(missing_values="N/A", names=True, case_sensitive=True)
test = np.recfromcsv(path, dtype=None, **kwargs)
control = np.array([(0, 1), (2, 3)],
dtype=[('A', int), ('B', int)])
assert_(isinstance(test, np.recarray))
assert_equal(test, control)
def test_gzip_load():
a = np.random.random((5, 5))
s = BytesIO()
f = gzip.GzipFile(fileobj=s, mode="w")
np.save(f, a)
f.close()
s.seek(0)
f = gzip.GzipFile(fileobj=s, mode="r")
assert_array_equal(np.load(f), a)
# These next two classes encode the minimal API needed to save()/load() arrays.
# The `test_ducktyping` ensures they work correctly
class JustWriter:
def __init__(self, base):
self.base = base
def write(self, s):
return self.base.write(s)
def flush(self):
return self.base.flush()
class JustReader:
def __init__(self, base):
self.base = base
def read(self, n):
return self.base.read(n)
def seek(self, off, whence=0):
return self.base.seek(off, whence)
def test_ducktyping():
a = np.random.random((5, 5))
s = BytesIO()
f = JustWriter(s)
np.save(f, a)
f.flush()
s.seek(0)
f = JustReader(s)
assert_array_equal(np.load(f), a)
def test_gzip_loadtxt():
# Thanks to another windows brokenness, we can't use
# NamedTemporaryFile: a file created from this function cannot be
# reopened by another open call. So we first put the gzipped string
# of the test reference array, write it to a securely opened file,
# which is then read from by the loadtxt function
s = BytesIO()
g = gzip.GzipFile(fileobj=s, mode='w')
g.write(b'1 2 3\n')
g.close()
s.seek(0)
with temppath(suffix='.gz') as name:
with open(name, 'wb') as f:
f.write(s.read())
res = np.loadtxt(name)
s.close()
assert_array_equal(res, [1, 2, 3])
def test_gzip_loadtxt_from_string():
s = BytesIO()
f = gzip.GzipFile(fileobj=s, mode="w")
f.write(b'1 2 3\n')
f.close()
s.seek(0)
f = gzip.GzipFile(fileobj=s, mode="r")
assert_array_equal(np.loadtxt(f), [1, 2, 3])
def test_npzfile_dict():
s = BytesIO()
x = np.zeros((3, 3))
y = np.zeros((3, 3))
np.savez(s, x=x, y=y)
s.seek(0)
z = np.load(s)
assert_('x' in z)
assert_('y' in z)
assert_('x' in z.keys())
assert_('y' in z.keys())
for f, a in z.items():
assert_(f in ['x', 'y'])
assert_equal(a.shape, (3, 3))
assert_(len(z.items()) == 2)
for f in z:
assert_(f in ['x', 'y'])
assert_('x' in z.keys())
@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
def test_load_refcount():
# Check that objects returned by np.load are directly freed based on
# their refcount, rather than needing the gc to collect them.
f = BytesIO()
np.savez(f, [1, 2, 3])
f.seek(0)
with assert_no_gc_cycles():
np.load(f)
f.seek(0)
dt = [("a", 'u1', 2), ("b", 'u1', 2)]
with assert_no_gc_cycles():
x = np.loadtxt(TextIO("0 1 2 3"), dtype=dt)
assert_equal(x, np.array([((0, 1), (2, 3))], dtype=dt))
def test_load_multiple_arrays_until_eof():
f = BytesIO()
np.save(f, 1)
np.save(f, 2)
f.seek(0)
assert np.load(f) == 1
assert np.load(f) == 2
with pytest.raises(EOFError):
np.load(f)
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