Dirk Mueller
df11e96f83
* Add hdf5storage-pr134-numpy2.patch * gh#frejanordsiek/hdf5storage#134 (backported) - Make it noarch again OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-hdf5storage?expand=0&rev=12
227 lines
11 KiB
Diff
227 lines
11 KiB
Diff
From 9814bc28874a56757e16479186523b2b77d5c553 Mon Sep 17 00:00:00 2001
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From: Jesse R Codling <codling@umich.edu>
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Date: Wed, 14 Aug 2024 12:34:47 -0400
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Subject: [PATCH 2/3] Numpy 2.0: Remove all np.unicode_ for np.str_
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---
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doc/source/storage_format.rst | 6 ++--
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pyproject.toml | 2 +-
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hdf5storage/Marshallers.py | 20 +++++++------
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hdf5storage/__init__.py | 6 ++--
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hdf5storage/utilities.py | 40 ++++++++++++-------------
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tests/asserts.py | 14 ++++-----
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tests/make_randoms.py | 4 +--
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tests/test_dict_like_storage_methods.py | 6 ++--
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tests/test_str_conv_utils.py | 8 ++---
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tests/test_string_utf16_conversion.py | 4 +--
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tests/test_write_readback.py | 6 ++--
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11 files changed, 59 insertions(+), 57 deletions(-)
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Index: hdf5storage-0.1.19/tests/make_randoms.py
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===================================================================
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--- hdf5storage-0.1.19.orig/tests/make_randoms.py
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+++ hdf5storage-0.1.19/tests/make_randoms.py
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@@ -156,7 +156,7 @@ def random_numpy(shape, dtype, allow_nan
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chars = random_str_some_unicode(length)
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else:
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chars = random_str_ascii(length)
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- data[index] = np.unicode_(chars)
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+ data[index] = np.str_(chars)
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return data
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elif dtype == 'object':
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data = np.zeros(shape=shape, dtype='object')
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Index: hdf5storage-0.1.19/tests/test_string_utf16_conversion.py
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===================================================================
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--- hdf5storage-0.1.19.orig/tests/test_string_utf16_conversion.py
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+++ hdf5storage-0.1.19/tests/test_string_utf16_conversion.py
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@@ -44,12 +44,12 @@ import pytest
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# convert_numpy_str_to_utf16 option is set.
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#
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# * str
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-# * numpy.unicode_ scalars
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+# * numpy.str_ scalars
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if sys.hexversion < 0x3000000:
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- tps_tuple = (unicode, np.unicode_)
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+ tps_tuple = (unicode, np.str_)
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else:
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- tps_tuple = (str, np.unicode_)
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+ tps_tuple = (str, np.str_)
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@pytest.mark.parametrize("tp", tps_tuple)
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Index: hdf5storage-0.1.19/hdf5storage/Marshallers.py
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===================================================================
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--- hdf5storage-0.1.19.orig/hdf5storage/Marshallers.py
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+++ hdf5storage-0.1.19/hdf5storage/Marshallers.py
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@@ -480,7 +480,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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'MATLAB_int_decode',
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'MATLAB_fields'])
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# As np.str_ is the unicode type string in Python 3 and the bare
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- # bytes string in Python 2, we have to use np.unicode_ which is
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+ # bytes string in Python 2, we have to use np.str_ which is
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# or points to the unicode one in both versions.
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self.types = [np.ndarray, np.matrix,
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np.chararray, np.core.records.recarray,
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@@ -489,7 +489,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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np.int8, np.int16, np.int32, np.int64,
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np.float32, np.float64,
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np.complex64, np.complex128,
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- np.bytes_, np.unicode_, np.object_]
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+ np.bytes_, np.str_, np.object_]
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self._numpy_types = list(self.types)
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# Using Python 3 type strings.
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self.python_type_strings = ['numpy.ndarray', 'numpy.matrix',
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@@ -525,7 +525,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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np.complex64: 'single',
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np.complex128: 'double',
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np.bytes_: 'char',
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- np.unicode_: 'char',
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+ np.str_: 'char',
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np.object_: 'cell'}
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# Make a dict to look up the opposite direction (given a matlab
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@@ -542,7 +542,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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'int64': np.int64,
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'single': np.float32,
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'double': np.float64,
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- 'char': np.unicode_,
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+ 'char': np.str_,
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'cell': np.object_,
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'canonical empty': np.float64,
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'struct': np.object_}
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@@ -601,18 +601,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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raise NotImplementedError( \
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'Can''t write non-ASCII numpy.bytes_.')
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- # As of 2013-12-13, h5py cannot write numpy.str_ (UTF-32
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- # encoding) types (its numpy.unicode_ in Python 2, which is an
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- # alias for it in Python 3). If the option is set to try to
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- # convert them to UTF-16, then an attempt at the conversion is
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- # made. If no conversion is to be done, the conversion throws an
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- # exception (a UTF-32 character had no UTF-16 equivalent), or a
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- # UTF-32 character gets turned into a UTF-16 doublet (the
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- # increase in the number of columns will be by a factor more
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- # than the length of the strings); then it will be simply
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- # converted to uint32's byte for byte instead.
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-
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- if data.dtype.type == np.unicode_:
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+ if data.dtype.type == np.str_:
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new_data = None
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if options.convert_numpy_str_to_utf16:
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try:
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@@ -620,7 +609,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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data_to_store)
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except:
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pass
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- if new_data is None or (type(data_to_store) == np.unicode_ \
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+ if new_data is None or (type(data_to_store) == np.str_ \
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and len(data_to_store) != len(new_data)) \
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or (isinstance(data_to_store, np.ndarray) \
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and new_data.shape[-1] != data_to_store.shape[-1] \
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@@ -1049,7 +1038,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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str_attrs[attr_name] = value
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elif isinstance(value, bytes):
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str_attrs[attr_name] = value.decode()
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- elif isinstance(value, np.unicode_):
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+ elif isinstance(value, np.str_):
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str_attrs[attr_name] = str(value)
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elif isinstance(value, np.bytes_):
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str_attrs[attr_name] = value.decode()
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@@ -1313,7 +1302,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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elif underlying_type.startswith('str') \
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or matlab_class == 'char':
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if underlying_type == 'str':
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- data = np.unicode_('')
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+ data = np.str_('')
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elif underlying_type.startswith('str'):
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data = convert_to_numpy_str(data, \
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length=int(underlying_type[3:])//32)
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@@ -1344,7 +1333,7 @@ class NumpyScalarArrayMarshaller(TypeMar
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data = data.flatten()[0]
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elif underlying_type.startswith('str'):
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if python_empty == 1:
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- data = np.unicode_('')
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+ data = np.str_('')
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elif isinstance(data, np.ndarray):
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data = data.flatten()[0]
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else:
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@@ -1511,7 +1500,7 @@ class PythonStringMarshaller(NumpyScalar
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if (sys.hexversion >= 0x03000000 and isinstance(data, str)) \
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or (sys.hexversion < 0x03000000 \
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and isinstance(data, unicode)):
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- cdata = np.unicode_(data)
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+ cdata = np.str_(data)
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else:
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cdata = np.bytes_(data)
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Index: hdf5storage-0.1.19/hdf5storage/utilities.py
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===================================================================
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--- hdf5storage-0.1.19.orig/hdf5storage/utilities.py
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+++ hdf5storage-0.1.19/hdf5storage/utilities.py
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@@ -408,7 +408,7 @@ def convert_to_str(data):
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# assuming it is in UTF-8. Otherwise, data has to be returned as is.
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if isinstance(data, (np.ndarray, np.uint8, np.uint16, np.uint32,
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- np.bytes_, np.unicode_)):
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+ np.bytes_, np.str_)):
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if data.dtype.name == 'uint8':
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return numpy_to_bytes(data.flatten()).decode('UTF-8')
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elif data.dtype.name == 'uint16':
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@@ -477,7 +477,7 @@ def convert_to_numpy_str(data, length=No
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"""
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# The method of conversion depends on its type.
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- if isinstance(data, np.unicode_) or (isinstance(data, np.ndarray) \
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+ if isinstance(data, np.str_) or (isinstance(data, np.ndarray) \
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and data.dtype.char == 'U'):
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# It is already an np.str_ or array of them, so nothing needs to
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# be done.
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@@ -486,16 +486,16 @@ def convert_to_numpy_str(data, length=No
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or (sys.hexversion < 0x03000000 \
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and isinstance(data, unicode)):
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# Easily converted through constructor.
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- return np.unicode_(data)
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+ return np.str_(data)
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elif isinstance(data, (bytes, bytearray, np.bytes_)):
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# All of them can be decoded and then passed through the
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# constructor.
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- return np.unicode_(data.decode('UTF-8'))
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+ return np.str_(data.decode('UTF-8'))
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elif isinstance(data, (np.uint8, np.uint16)):
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# They are single UTF-8 or UTF-16 scalars, and are easily
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# converted to a UTF-8 string and then passed through the
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# constructor.
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- return np.unicode_(convert_to_str(data))
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+ return np.str_(convert_to_str(data))
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elif isinstance(data, np.uint32):
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# It is just the uint32 version of the character, so it just
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# needs to be have the dtype essentially changed by having its
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@@ -507,7 +507,7 @@ def convert_to_numpy_str(data, length=No
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new_data = np.zeros(shape=data.shape,
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dtype='U' + str(data.dtype.itemsize))
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for index, x in np.ndenumerate(data):
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- new_data[index] = np.unicode_(x.decode('UTF-8'))
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+ new_data[index] = np.str_(x.decode('UTF-8'))
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return new_data
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elif isinstance(data, np.ndarray) \
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and data.dtype.name in ('uint8', 'uint16', 'uint32'):
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@@ -559,7 +559,7 @@ def convert_to_numpy_str(data, length=No
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dtype=new_data.dtype,
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buffer=numpy_to_bytes(chunk))[()]
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else:
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- new_data[i] = np.unicode_(convert_to_str(chunk))
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+ new_data[i] = np.str_(convert_to_str(chunk))
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# Only thing is left is to reshape it.
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return new_data.reshape(tuple(new_shape))
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@@ -896,7 +896,7 @@ def get_attribute_string(target, name):
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return value
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elif isinstance(value, bytes):
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return value.decode()
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- elif isinstance(value, np.unicode_):
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+ elif isinstance(value, np.str_):
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return str(value)
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elif isinstance(value, np.bytes_):
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return value.decode()
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