#
# * The source code in this file is based on the soure code of CuPy.
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import nlcpy
from nlcpy.wrapper.numpy_wrap import numpy_wrap
class NpzFile(object):
def __init__(self, npz_file):
self.npz_file = npz_file
self.files = npz_file.files
def __enter__(self):
self.npz_file.__enter__()
return self
def __exit__(self, typ, val, traceback):
self.npz_file.__exit__(typ, val, traceback)
def __getitem__(self, key):
arr = self.npz_file[key]
return nlcpy.array(arr)
def close(self):
self.npz_file.close()
[ドキュメント]@numpy_wrap
def load(file, mmap_mode=None, allow_pickle=False, fix_imports=True, encoding='ASCII'):
"""Loads arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
.. Warning::
Loading files that contain object arrays uses the ``pickle`` module, which is
not secure against erroneous or maliciously constructed data. Consider passing
``allow_pickle=False`` to load data that is known not to contain object arrays
for the safer handling of untrusted sources.
Parameters
----------
file : file-like object, string, or pathlib.Path
The file to read. File-like objects must support the ``seek()`` and ``read()``
methods. Pickled files require that the file-like object support the
``readline()`` method as well.
mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional
If not None, memory-map the file to construct an intermediate
:obj:`numpy.ndarray` object and create :obj:`nlcpy.ndarray` from it.
allow_pickle : bool, optional
Allow loading pickled object arrays stored in npy files. Reasons for
disallowing pickles include security, as loading pickled data can execute
arbitrary code. If pickles are disallowed, loading object arrays will fail.
Default: False
fix_imports : bool, optional
Only useful when loading Python 2 generated pickled files on Python 3, which
includes npy/npz files containing object arrays. If *fix_imports* is True,
pickle will try to map the old Python 2 names to the new names used in Python
3.
encoding : str, optional
What encoding to use when reading Python 2 strings. Only useful when loading
Python 2 generated pickled files in Python 3, which includes npy/npz files
containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes'
are not allowed, as they can corrupt numerical data. Default: 'ASCII'
Returns
-------
result : ndarray, tuple, dict, etc.
Data stored in the file. For ``.npz`` files, the returned instance of NpzFile
class must be closed to avoid leaking file descriptors.
Note
----
- If the file contains pickle data, then whatever object is stored in the pickle
is returned.
- If the file is a ``.npy`` file, then a single array is returned.
- If the file is a ``.npz`` file, then a dictionary-like object is returned,
containing {filename: array} key-value pairs, one for each file in the archive.
- If the file is a ``.npz`` file, the returned value supports the context manager
protocol in a similar fashion to the open function::
with load('foo.npz') as data:
a = data['a']
The underlying file descriptor is closed when exiting the 'with' block.
See Also
--------
loadtxt : Loads data from a text file.
Examples
--------
Store data to disk, and load it again:
>>> import nlcpy as vp
>>> vp.save('/tmp/123', vp.array([[1, 2, 3], [4, 5, 6]]))
>>> vp.load('/tmp/123.npy')
array([[1, 2, 3],
[4, 5, 6]])
Store compressed data to disk, and load it again:
>>> a=vp.array([[1, 2, 3], [4, 5, 6]])
>>> b=vp.array([1, 2])
>>> vp.savez('/tmp/123.npz', a=a, b=b)
>>> data = vp.load('/tmp/123.npz')
>>> data['a']
array([[1, 2, 3],
[4, 5, 6]])
>>> data['b']
array([1, 2])
>>> data.close()
"""
# use numpy_wrap
raise NotImplementedError('load is not implemented yet.')
[ドキュメント]@numpy_wrap
def save(file, arr, allow_pickle=True, fix_imports=True):
"""Saves an array to a binary file in NumPy ``.npy`` format.
Parameters
----------
file : file, str, or pathlib.Path
File or filename to which the data is saved. If file is a file-object,
then the filename is unchanged. If file is a string or Path, a ``.npy``
extension will be appended to the file name if it does not already have one.
arr : array_like
Array data to be saved.
allow_pickle : bool, optional
Allow saving object arrays using Python pickles. Reasons for disallowing pickles
include security (loading pickled data can execute arbitrary code) and
portability (pickled objects may not be loadable on different Python
installations, for example if the stored objects require libraries that are not
available, and not all pickled data is compatible between Python 2 and
Python 3). Default: True
fix_imports : bool, optional
Only useful in forcing objects in object arrays on Python 3 to be pickled in a
Python 2 compatible way. If fix_imports is True, pickle will try to map the new
Python 3 names to the old module names used in Python 2, so that the pickle data
stream is readable with Python 2.
See Also
--------
savez : Saves several arrays into a single file in uncompressed ``.npz`` format.
savetxt : Saves an array to a text file.
load : Loads arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
Note
----
For a description of the ``.npy`` format, see `numpy.lib.format.
<https://numpy.org/doc/1.17/reference/generated/numpy.lib.format.html#module-numpy.lib.format>`_
Examples
--------
>>> import nlcpy as vp
>>> from tempfile import TemporaryFile
>>> outfile = TemporaryFile()
>>> x = vp.arange(10)
>>> vp.save(outfile, x)
>>> _ = outfile.seek(0) # Only needed here to simulate closing & reopening file
>>> vp.load(outfile)
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
"""
# use numpy_wrap
raise NotImplementedError('save is not implemented yet.')
@numpy_wrap
def savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='n', header='', footer='',
comments='# ', encoding=None):
"""Saves an array to a text file.
Parameters
----------
fname : filename or file handle
If the filename ends in ``.gz``, the file is automatically saved in compressed
gzip format. loadtxt understands gzipped files transparently.
x : 1D or 2D array_like
Data to be saved to a text file.
fmt : str or sequence of strs, optional
A single format (%10.5f), a sequence of formats, or a multi-format string, e.g.
'Iteration %d – %10.5f', in which case *delimiter* is ignored.
For complex *X*, the legal options for *fmt* are:
- a single specifier, *fmt='%.4e'*, resulting in numbers formatted like
*'(%s+%sj)' % (fmt, fmt)*
- a full string specifying every real and imaginary part,
e.g. *'%.4e %+.4ej %.4e %+.4ej %.4e %+.4ej'* for 3 columns
- a list of specifiers, one per column - in this case, the real and imaginary
part must have separate specifiers, e.g. *['%.3e + %.3ej', '(%.15e%+.15ej)']*
for 2 columns
delimiter : str, optional
String or character separating columns.
newline : str, optional
String or character separating lines.
header : str, optional
String that will be written at the beginning of the file.
footer : str, optional
String that will be written at the end of the file.
comments : str, optional
String that will be prepended to the ``header`` and ``footer`` strings,
to mark them as comments. Default: '# ', as expected by e.g. ``numpy.loadtxt``.
encoding : {None, str}, optional
Encoding used to encode the outputfile. Does not apply to output streams.
If the encoding is something other than 'bytes' or 'latin1' you will not be
able to load the file in NumPy versions < 1.14. Default is 'latin1'.
See Also
--------
save : Saves an array to a binary file in NumPy ``.npy`` format.
savez : Saves several arrays into a single file in uncompressed ``.npz`` format.
savez_compressed : Saves several arrays into a single file in compressed
``.npz`` format.
Note
----
Further explanation of the fmt parameter (``%[flag]width[.precision]specifier``):
**flags:**
``-`` : left justify
``+`` : Forces to precede result with + or -.
``0`` : Left pad the number with zeros instead of space (see width).
**width:**
Minimum number of characters to be printed.
The value is not truncated if it has more characters.
**precision:**
- For integer specifiers (eg. ``d,i,o,x``), the minimum number of digits.
- For ``e, E`` and ``f`` specifiers, the number of digits to print after
the decimal point.
- For ``g`` and ``G``, the maximum number of significant digits.
- For ``s``, the maximum number of characters.
**specifiers:**
``c`` : character
``d`` or ``i`` : signed decimal integer
``e`` or ``E`` : scientific notation with ``e`` or ``E``.
``f`` : decimal floating point
``g,G`` : use the shorter of e,E or f
``o`` : signed octal
``s`` : string of characters
``u`` : unsigned decimal integer
``x,X`` : unsigned hexadecimal integer
This explanation of ``fmt`` is not complete, for an exhaustive specification
see `Format Specification Mini-Language
<https://docs.python.org/3/library/string.html#format-specification-mini-language>`_
, Python Documentation.
Examples
--------
>>> import nlcpy as vp
>>> x = y = z = vp.arange(0.0, 5.0, 1.0)
>>> vp.savetxt('test.out', x, delimiter=',') # X is an array
>>> vp.savetxt('test.out', (x, y, z)) # x,y,z equal sized 1D arrays
>>> vp.savetxt('test.out', x, fmt='%1.4e') # use exponential notation
"""
# use numpy_wrap
raise NotImplementedError('savetxt is not implemented yet.')
[ドキュメント]@numpy_wrap
def savez(file, *args, **kwds):
"""Saves several arrays into a single file in uncompressed ``.npz`` format.
If arguments are passed in with no keywords, the corresponding variable names,
in the ``.npz`` file, are 'arr_0', 'arr_1', etc. If keyword arguments are given,
the corresponding variable names, in the ``.npz`` file will match the keyword names.
Parameters
----------
file : str or file
Either the file name (string) or an open file (file-like object) where the data
will be saved. If file is a string or a Path, the ``.npz`` extension will be
appended to the file name if it is not already there.
args : Arguments, optional
Arrays to save to the file. Since it is not possible for Python to know the
names of the arrays outside savez, the arrays will be saved with names "arr_0",
"arr_1", and so on. These arguments can be any expression.
kwds : keyword arguments, optional
Arrays to save to the file.
Arrays will be saved in the file with the keyword names.
See Also
--------
save : Saves an array to a binary file in NumPy ``.npy`` format.
savetxt : Saves an array to a text file.
savez_compressed : Saves several arrays into a single file in compressed
``.npz`` format.
Note
----
The ``.npz`` file format is a zipped archive of files named after the variables
they contain. The archive is not compressed and each file in the archive contains
one variable in ``.npy`` format. For a description of the ``.npy`` format,
see `numpy.lib.format.
<https://numpy.org/doc/1.17/reference/generated/numpy.lib.format.html#module-numpy.lib.format>`_
When opening the saved ``.npz`` file with :func:`load` a *NpzFile* object is
returned.
This is a dictionary-like object which can be queried for its list of arrays (with
the ``.files`` attribute), and for the arrays themselves.
Examples
--------
>>> import nlcpy as vp
>>> from tempfile import TemporaryFile
>>> outfile = TemporaryFile()
>>> x = vp.arange(10)
>>> y = vp.sin(x)
Using savez with \\*args, the arrays are saved with default names.
>>> vp.savez(outfile, x, y)
>>> _ = outfile.seek(0) # Only needed here to simulate closing & reopening file
>>> npzfile = vp.load(outfile)
>>> npzfile.files
['arr_0', 'arr_1']
>>> npzfile['arr_0']
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
Using savez with \\**kwds, the arrays are saved with the keyword names.
>>> outfile = TemporaryFile()
>>> vp.savez(outfile, x=x, y=y)
>>> _ = outfile.seek(0)
>>> npzfile = vp.load(outfile)
>>> sorted(npzfile.files)
['x', 'y']
>>> npzfile['x']
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
"""
# use numpy_wrap
raise NotImplementedError('savez is not implemented yet.')
[ドキュメント]@numpy_wrap
def savez_compressed(file, *args, **kwds):
""" Saves several arrays into a single file in compressed ``.npz`` format.
If keyword arguments are given, then filenames are taken from the keywords.
If arguments are passed in with no keywords, then stored file names are arr_0,
arr_1, etc.
Parameters
----------
file : str or file
Either the file name (string) or an open file (file-like object) where the data
will be saved. If file is a string or a Path, the ``.npz`` extension will be
appended to the file name if it is not already there.
args : Arguments, optional
Arrays to save to the file. Since it is not possible for Python to know the
names of the arrays outside :func:`savez`, the arrays will be saved with
names "arr_0", "arr_1", and so on. These arguments can be any expression.
kwds : keyword arguments
Arrays to save to the file.
Arrays will be saved in the file with the keyword names.
See Also
--------
save : Saves an array to a binary file in NumPy ``.npy`` format.
savetxt : Saves an array to a text file.
savez : Saves several arrays into a single file in uncompressed ``.npz`` format.
load : Loads arrays or pickled objects from ``.npy``, ``.npz`` or pickled files.
Note
----
The ``.npz`` file format is a zipped archive of files named after the variables
they contain. The archive is compressed with ``zipfile.ZIP_DEFLATED`` and each file
in the archive contains one variable in ``.npy`` format. For a description of the
``.npy`` format, see `numpy.lib.format.
<https://numpy.org/doc/1.17/reference/generated/numpy.lib.format.html#module-numpy.lib.format>`_
When opening the saved ``.npz`` file with :func:`load` a *NpzFile* object is
returned.
This is a dictionary-like object which can be queried for its list of arrays (with
the ``.files`` attribute), and for the arrays themselves.
Examples
--------
>>> import nlcpy as vp
>>> from nlcpy import testing
>>> test_array = vp.random.rand(3, 2)
>>> test_vector = vp.random.rand(4)
>>> vp.savez_compressed('/tmp/123', a=test_array, b=test_vector)
>>> loaded = vp.load('/tmp/123.npz')
>>> vp.testing.assert_array_equal(test_array, loaded['a'])
>>> vp.testing.assert_array_equal(test_vector, loaded['b'])
"""
# use numpy_wrap
raise NotImplementedError('savez_compressed is not implemented yet.')