fr/fr_env/lib/python3.8/site-packages/scipy/io/mmio.py

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"""
Matrix Market I/O in Python.
See http://math.nist.gov/MatrixMarket/formats.html
for information about the Matrix Market format.
"""
#
# Author: Pearu Peterson <pearu@cens.ioc.ee>
# Created: October, 2004
#
# References:
# http://math.nist.gov/MatrixMarket/
#
import os
import sys
from numpy import (asarray, real, imag, conj, zeros, ndarray, concatenate,
ones, can_cast)
from numpy.compat import asbytes, asstr
from scipy.sparse import coo_matrix, isspmatrix
__all__ = ['mminfo', 'mmread', 'mmwrite', 'MMFile']
# -----------------------------------------------------------------------------
def mminfo(source):
"""
Return size and storage parameters from Matrix Market file-like 'source'.
Parameters
----------
source : str or file-like
Matrix Market filename (extension .mtx) or open file-like object
Returns
-------
rows : int
Number of matrix rows.
cols : int
Number of matrix columns.
entries : int
Number of non-zero entries of a sparse matrix
or rows*cols for a dense matrix.
format : str
Either 'coordinate' or 'array'.
field : str
Either 'real', 'complex', 'pattern', or 'integer'.
symmetry : str
Either 'general', 'symmetric', 'skew-symmetric', or 'hermitian'.
"""
return MMFile.info(source)
# -----------------------------------------------------------------------------
def mmread(source):
"""
Reads the contents of a Matrix Market file-like 'source' into a matrix.
Parameters
----------
source : str or file-like
Matrix Market filename (extensions .mtx, .mtz.gz)
or open file-like object.
Returns
-------
a : ndarray or coo_matrix
Dense or sparse matrix depending on the matrix format in the
Matrix Market file.
"""
return MMFile().read(source)
# -----------------------------------------------------------------------------
def mmwrite(target, a, comment='', field=None, precision=None, symmetry=None):
"""
Writes the sparse or dense array `a` to Matrix Market file-like `target`.
Parameters
----------
target : str or file-like
Matrix Market filename (extension .mtx) or open file-like object.
a : array like
Sparse or dense 2-D array.
comment : str, optional
Comments to be prepended to the Matrix Market file.
field : None or str, optional
Either 'real', 'complex', 'pattern', or 'integer'.
precision : None or int, optional
Number of digits to display for real or complex values.
symmetry : None or str, optional
Either 'general', 'symmetric', 'skew-symmetric', or 'hermitian'.
If symmetry is None the symmetry type of 'a' is determined by its
values.
"""
MMFile().write(target, a, comment, field, precision, symmetry)
###############################################################################
class MMFile:
__slots__ = ('_rows',
'_cols',
'_entries',
'_format',
'_field',
'_symmetry')
@property
def rows(self):
return self._rows
@property
def cols(self):
return self._cols
@property
def entries(self):
return self._entries
@property
def format(self):
return self._format
@property
def field(self):
return self._field
@property
def symmetry(self):
return self._symmetry
@property
def has_symmetry(self):
return self._symmetry in (self.SYMMETRY_SYMMETRIC,
self.SYMMETRY_SKEW_SYMMETRIC,
self.SYMMETRY_HERMITIAN)
# format values
FORMAT_COORDINATE = 'coordinate'
FORMAT_ARRAY = 'array'
FORMAT_VALUES = (FORMAT_COORDINATE, FORMAT_ARRAY)
@classmethod
def _validate_format(self, format):
if format not in self.FORMAT_VALUES:
raise ValueError('unknown format type %s, must be one of %s' %
(format, self.FORMAT_VALUES))
# field values
FIELD_INTEGER = 'integer'
FIELD_UNSIGNED = 'unsigned-integer'
FIELD_REAL = 'real'
FIELD_COMPLEX = 'complex'
FIELD_PATTERN = 'pattern'
FIELD_VALUES = (FIELD_INTEGER, FIELD_UNSIGNED, FIELD_REAL, FIELD_COMPLEX, FIELD_PATTERN)
@classmethod
def _validate_field(self, field):
if field not in self.FIELD_VALUES:
raise ValueError('unknown field type %s, must be one of %s' %
(field, self.FIELD_VALUES))
# symmetry values
SYMMETRY_GENERAL = 'general'
SYMMETRY_SYMMETRIC = 'symmetric'
SYMMETRY_SKEW_SYMMETRIC = 'skew-symmetric'
SYMMETRY_HERMITIAN = 'hermitian'
SYMMETRY_VALUES = (SYMMETRY_GENERAL, SYMMETRY_SYMMETRIC,
SYMMETRY_SKEW_SYMMETRIC, SYMMETRY_HERMITIAN)
@classmethod
def _validate_symmetry(self, symmetry):
if symmetry not in self.SYMMETRY_VALUES:
raise ValueError('unknown symmetry type %s, must be one of %s' %
(symmetry, self.SYMMETRY_VALUES))
DTYPES_BY_FIELD = {FIELD_INTEGER: 'intp',
FIELD_UNSIGNED: 'uint64',
FIELD_REAL: 'd',
FIELD_COMPLEX: 'D',
FIELD_PATTERN: 'd'}
# -------------------------------------------------------------------------
@staticmethod
def reader():
pass
# -------------------------------------------------------------------------
@staticmethod
def writer():
pass
# -------------------------------------------------------------------------
@classmethod
def info(self, source):
"""
Return size, storage parameters from Matrix Market file-like 'source'.
Parameters
----------
source : str or file-like
Matrix Market filename (extension .mtx) or open file-like object
Returns
-------
rows : int
Number of matrix rows.
cols : int
Number of matrix columns.
entries : int
Number of non-zero entries of a sparse matrix
or rows*cols for a dense matrix.
format : str
Either 'coordinate' or 'array'.
field : str
Either 'real', 'complex', 'pattern', or 'integer'.
symmetry : str
Either 'general', 'symmetric', 'skew-symmetric', or 'hermitian'.
"""
stream, close_it = self._open(source)
try:
# read and validate header line
line = stream.readline()
mmid, matrix, format, field, symmetry = \
[asstr(part.strip()) for part in line.split()]
if not mmid.startswith('%%MatrixMarket'):
raise ValueError('source is not in Matrix Market format')
if not matrix.lower() == 'matrix':
raise ValueError("Problem reading file header: " + line)
# http://math.nist.gov/MatrixMarket/formats.html
if format.lower() == 'array':
format = self.FORMAT_ARRAY
elif format.lower() == 'coordinate':
format = self.FORMAT_COORDINATE
# skip comments
# line.startswith('%')
while line and line[0] in ['%', 37]:
line = stream.readline()
# skip empty lines
while not line.strip():
line = stream.readline()
split_line = line.split()
if format == self.FORMAT_ARRAY:
if not len(split_line) == 2:
raise ValueError("Header line not of length 2: " +
line.decode('ascii'))
rows, cols = map(int, split_line)
entries = rows * cols
else:
if not len(split_line) == 3:
raise ValueError("Header line not of length 3: " +
line.decode('ascii'))
rows, cols, entries = map(int, split_line)
return (rows, cols, entries, format, field.lower(),
symmetry.lower())
finally:
if close_it:
stream.close()
# -------------------------------------------------------------------------
@staticmethod
def _open(filespec, mode='rb'):
""" Return an open file stream for reading based on source.
If source is a file name, open it (after trying to find it with mtx and
gzipped mtx extensions). Otherwise, just return source.
Parameters
----------
filespec : str or file-like
String giving file name or file-like object
mode : str, optional
Mode with which to open file, if `filespec` is a file name.
Returns
-------
fobj : file-like
Open file-like object.
close_it : bool
True if the calling function should close this file when done,
false otherwise.
"""
# If 'filespec' is path-like (str, pathlib.Path, os.DirEntry, other class
# implementing a '__fspath__' method), try to convert it to str. If this
# fails by throwing a 'TypeError', assume it's an open file handle and
# return it as-is.
try:
filespec = os.fspath(filespec)
except TypeError:
return filespec, False
# 'filespec' is definitely a str now
# open for reading
if mode[0] == 'r':
# determine filename plus extension
if not os.path.isfile(filespec):
if os.path.isfile(filespec+'.mtx'):
filespec = filespec + '.mtx'
elif os.path.isfile(filespec+'.mtx.gz'):
filespec = filespec + '.mtx.gz'
elif os.path.isfile(filespec+'.mtx.bz2'):
filespec = filespec + '.mtx.bz2'
# open filename
if filespec.endswith('.gz'):
import gzip
stream = gzip.open(filespec, mode)
elif filespec.endswith('.bz2'):
import bz2
stream = bz2.BZ2File(filespec, 'rb')
else:
stream = open(filespec, mode)
# open for writing
else:
if filespec[-4:] != '.mtx':
filespec = filespec + '.mtx'
stream = open(filespec, mode)
return stream, True
# -------------------------------------------------------------------------
@staticmethod
def _get_symmetry(a):
m, n = a.shape
if m != n:
return MMFile.SYMMETRY_GENERAL
issymm = True
isskew = True
isherm = a.dtype.char in 'FD'
# sparse input
if isspmatrix(a):
# check if number of nonzero entries of lower and upper triangle
# matrix are equal
a = a.tocoo()
(row, col) = a.nonzero()
if (row < col).sum() != (row > col).sum():
return MMFile.SYMMETRY_GENERAL
# define iterator over symmetric pair entries
a = a.todok()
def symm_iterator():
for ((i, j), aij) in a.items():
if i > j:
aji = a[j, i]
yield (aij, aji)
# non-sparse input
else:
# define iterator over symmetric pair entries
def symm_iterator():
for j in range(n):
for i in range(j+1, n):
aij, aji = a[i][j], a[j][i]
yield (aij, aji)
# check for symmetry
for (aij, aji) in symm_iterator():
if issymm and aij != aji:
issymm = False
if isskew and aij != -aji:
isskew = False
if isherm and aij != conj(aji):
isherm = False
if not (issymm or isskew or isherm):
break
# return symmetry value
if issymm:
return MMFile.SYMMETRY_SYMMETRIC
if isskew:
return MMFile.SYMMETRY_SKEW_SYMMETRIC
if isherm:
return MMFile.SYMMETRY_HERMITIAN
return MMFile.SYMMETRY_GENERAL
# -------------------------------------------------------------------------
@staticmethod
def _field_template(field, precision):
return {MMFile.FIELD_REAL: '%%.%ie\n' % precision,
MMFile.FIELD_INTEGER: '%i\n',
MMFile.FIELD_UNSIGNED: '%u\n',
MMFile.FIELD_COMPLEX: '%%.%ie %%.%ie\n' %
(precision, precision)
}.get(field, None)
# -------------------------------------------------------------------------
def __init__(self, **kwargs):
self._init_attrs(**kwargs)
# -------------------------------------------------------------------------
def read(self, source):
"""
Reads the contents of a Matrix Market file-like 'source' into a matrix.
Parameters
----------
source : str or file-like
Matrix Market filename (extensions .mtx, .mtz.gz)
or open file object.
Returns
-------
a : ndarray or coo_matrix
Dense or sparse matrix depending on the matrix format in the
Matrix Market file.
"""
stream, close_it = self._open(source)
try:
self._parse_header(stream)
return self._parse_body(stream)
finally:
if close_it:
stream.close()
# -------------------------------------------------------------------------
def write(self, target, a, comment='', field=None, precision=None,
symmetry=None):
"""
Writes sparse or dense array `a` to Matrix Market file-like `target`.
Parameters
----------
target : str or file-like
Matrix Market filename (extension .mtx) or open file-like object.
a : array like
Sparse or dense 2-D array.
comment : str, optional
Comments to be prepended to the Matrix Market file.
field : None or str, optional
Either 'real', 'complex', 'pattern', or 'integer'.
precision : None or int, optional
Number of digits to display for real or complex values.
symmetry : None or str, optional
Either 'general', 'symmetric', 'skew-symmetric', or 'hermitian'.
If symmetry is None the symmetry type of 'a' is determined by its
values.
"""
stream, close_it = self._open(target, 'wb')
try:
self._write(stream, a, comment, field, precision, symmetry)
finally:
if close_it:
stream.close()
else:
stream.flush()
# -------------------------------------------------------------------------
def _init_attrs(self, **kwargs):
"""
Initialize each attributes with the corresponding keyword arg value
or a default of None
"""
attrs = self.__class__.__slots__
public_attrs = [attr[1:] for attr in attrs]
invalid_keys = set(kwargs.keys()) - set(public_attrs)
if invalid_keys:
raise ValueError('''found %s invalid keyword arguments, please only
use %s''' % (tuple(invalid_keys),
public_attrs))
for attr in attrs:
setattr(self, attr, kwargs.get(attr[1:], None))
# -------------------------------------------------------------------------
def _parse_header(self, stream):
rows, cols, entries, format, field, symmetry = \
self.__class__.info(stream)
self._init_attrs(rows=rows, cols=cols, entries=entries, format=format,
field=field, symmetry=symmetry)
# -------------------------------------------------------------------------
def _parse_body(self, stream):
rows, cols, entries, format, field, symm = (self.rows, self.cols,
self.entries, self.format,
self.field, self.symmetry)
try:
from scipy.sparse import coo_matrix
except ImportError:
coo_matrix = None
dtype = self.DTYPES_BY_FIELD.get(field, None)
has_symmetry = self.has_symmetry
is_integer = field == self.FIELD_INTEGER
is_unsigned_integer = field == self.FIELD_UNSIGNED
is_complex = field == self.FIELD_COMPLEX
is_skew = symm == self.SYMMETRY_SKEW_SYMMETRIC
is_herm = symm == self.SYMMETRY_HERMITIAN
is_pattern = field == self.FIELD_PATTERN
if format == self.FORMAT_ARRAY:
a = zeros((rows, cols), dtype=dtype)
line = 1
i, j = 0, 0
if is_skew:
a[i, j] = 0
if i < rows - 1:
i += 1
while line:
line = stream.readline()
# line.startswith('%')
if not line or line[0] in ['%', 37] or not line.strip():
continue
if is_integer:
aij = int(line)
elif is_unsigned_integer:
aij = int(line)
elif is_complex:
aij = complex(*map(float, line.split()))
else:
aij = float(line)
a[i, j] = aij
if has_symmetry and i != j:
if is_skew:
a[j, i] = -aij
elif is_herm:
a[j, i] = conj(aij)
else:
a[j, i] = aij
if i < rows-1:
i = i + 1
else:
j = j + 1
if not has_symmetry:
i = 0
else:
i = j
if is_skew:
a[i, j] = 0
if i < rows-1:
i += 1
if is_skew:
if not (i in [0, j] and j == cols - 1):
raise ValueError("Parse error, did not read all lines.")
else:
if not (i in [0, j] and j == cols):
raise ValueError("Parse error, did not read all lines.")
elif format == self.FORMAT_COORDINATE and coo_matrix is None:
# Read sparse matrix to dense when coo_matrix is not available.
a = zeros((rows, cols), dtype=dtype)
line = 1
k = 0
while line:
line = stream.readline()
# line.startswith('%')
if not line or line[0] in ['%', 37] or not line.strip():
continue
l = line.split()
i, j = map(int, l[:2])
i, j = i-1, j-1
if is_integer:
aij = int(l[2])
elif is_unsigned_integer:
aij = int(l[2])
elif is_complex:
aij = complex(*map(float, l[2:]))
else:
aij = float(l[2])
a[i, j] = aij
if has_symmetry and i != j:
if is_skew:
a[j, i] = -aij
elif is_herm:
a[j, i] = conj(aij)
else:
a[j, i] = aij
k = k + 1
if not k == entries:
ValueError("Did not read all entries")
elif format == self.FORMAT_COORDINATE:
# Read sparse COOrdinate format
if entries == 0:
# empty matrix
return coo_matrix((rows, cols), dtype=dtype)
I = zeros(entries, dtype='intc')
J = zeros(entries, dtype='intc')
if is_pattern:
V = ones(entries, dtype='int8')
elif is_integer:
V = zeros(entries, dtype='intp')
elif is_unsigned_integer:
V = zeros(entries, dtype='uint64')
elif is_complex:
V = zeros(entries, dtype='complex')
else:
V = zeros(entries, dtype='float')
entry_number = 0
for line in stream:
# line.startswith('%')
if not line or line[0] in ['%', 37] or not line.strip():
continue
if entry_number+1 > entries:
raise ValueError("'entries' in header is smaller than "
"number of entries")
l = line.split()
I[entry_number], J[entry_number] = map(int, l[:2])
if not is_pattern:
if is_integer:
V[entry_number] = int(l[2])
elif is_unsigned_integer:
V[entry_number] = int(l[2])
elif is_complex:
V[entry_number] = complex(*map(float, l[2:]))
else:
V[entry_number] = float(l[2])
entry_number += 1
if entry_number < entries:
raise ValueError("'entries' in header is larger than "
"number of entries")
I -= 1 # adjust indices (base 1 -> base 0)
J -= 1
if has_symmetry:
mask = (I != J) # off diagonal mask
od_I = I[mask]
od_J = J[mask]
od_V = V[mask]
I = concatenate((I, od_J))
J = concatenate((J, od_I))
if is_skew:
od_V *= -1
elif is_herm:
od_V = od_V.conjugate()
V = concatenate((V, od_V))
a = coo_matrix((V, (I, J)), shape=(rows, cols), dtype=dtype)
else:
raise NotImplementedError(format)
return a
# ------------------------------------------------------------------------
def _write(self, stream, a, comment='', field=None, precision=None,
symmetry=None):
if isinstance(a, list) or isinstance(a, ndarray) or \
isinstance(a, tuple) or hasattr(a, '__array__'):
rep = self.FORMAT_ARRAY
a = asarray(a)
if len(a.shape) != 2:
raise ValueError('Expected 2 dimensional array')
rows, cols = a.shape
if field is not None:
if field == self.FIELD_INTEGER:
if not can_cast(a.dtype, 'intp'):
raise OverflowError("mmwrite does not support integer "
"dtypes larger than native 'intp'.")
a = a.astype('intp')
elif field == self.FIELD_REAL:
if a.dtype.char not in 'fd':
a = a.astype('d')
elif field == self.FIELD_COMPLEX:
if a.dtype.char not in 'FD':
a = a.astype('D')
else:
if not isspmatrix(a):
raise ValueError('unknown matrix type: %s' % type(a))
rep = 'coordinate'
rows, cols = a.shape
typecode = a.dtype.char
if precision is None:
if typecode in 'fF':
precision = 8
else:
precision = 16
if field is None:
kind = a.dtype.kind
if kind == 'i':
if not can_cast(a.dtype, 'intp'):
raise OverflowError("mmwrite does not support integer "
"dtypes larger than native 'intp'.")
field = 'integer'
elif kind == 'f':
field = 'real'
elif kind == 'c':
field = 'complex'
elif kind == 'u':
field = 'unsigned-integer'
else:
raise TypeError('unexpected dtype kind ' + kind)
if symmetry is None:
symmetry = self._get_symmetry(a)
# validate rep, field, and symmetry
self.__class__._validate_format(rep)
self.__class__._validate_field(field)
self.__class__._validate_symmetry(symmetry)
# write initial header line
stream.write(asbytes('%%MatrixMarket matrix {0} {1} {2}\n'.format(rep,
field, symmetry)))
# write comments
for line in comment.split('\n'):
stream.write(asbytes('%%%s\n' % (line)))
template = self._field_template(field, precision)
# write dense format
if rep == self.FORMAT_ARRAY:
# write shape spec
stream.write(asbytes('%i %i\n' % (rows, cols)))
if field in (self.FIELD_INTEGER, self.FIELD_REAL, self.FIELD_UNSIGNED):
if symmetry == self.SYMMETRY_GENERAL:
for j in range(cols):
for i in range(rows):
stream.write(asbytes(template % a[i, j]))
elif symmetry == self.SYMMETRY_SKEW_SYMMETRIC:
for j in range(cols):
for i in range(j + 1, rows):
stream.write(asbytes(template % a[i, j]))
else:
for j in range(cols):
for i in range(j, rows):
stream.write(asbytes(template % a[i, j]))
elif field == self.FIELD_COMPLEX:
if symmetry == self.SYMMETRY_GENERAL:
for j in range(cols):
for i in range(rows):
aij = a[i, j]
stream.write(asbytes(template % (real(aij),
imag(aij))))
else:
for j in range(cols):
for i in range(j, rows):
aij = a[i, j]
stream.write(asbytes(template % (real(aij),
imag(aij))))
elif field == self.FIELD_PATTERN:
raise ValueError('pattern type inconsisted with dense format')
else:
raise TypeError('Unknown field type %s' % field)
# write sparse format
else:
coo = a.tocoo() # convert to COOrdinate format
# if symmetry format used, remove values above main diagonal
if symmetry != self.SYMMETRY_GENERAL:
lower_triangle_mask = coo.row >= coo.col
coo = coo_matrix((coo.data[lower_triangle_mask],
(coo.row[lower_triangle_mask],
coo.col[lower_triangle_mask])),
shape=coo.shape)
# write shape spec
stream.write(asbytes('%i %i %i\n' % (rows, cols, coo.nnz)))
template = self._field_template(field, precision-1)
if field == self.FIELD_PATTERN:
for r, c in zip(coo.row+1, coo.col+1):
stream.write(asbytes("%i %i\n" % (r, c)))
elif field in (self.FIELD_INTEGER, self.FIELD_REAL, self.FIELD_UNSIGNED):
for r, c, d in zip(coo.row+1, coo.col+1, coo.data):
stream.write(asbytes(("%i %i " % (r, c)) +
(template % d)))
elif field == self.FIELD_COMPLEX:
for r, c, d in zip(coo.row+1, coo.col+1, coo.data):
stream.write(asbytes(("%i %i " % (r, c)) +
(template % (d.real, d.imag))))
else:
raise TypeError('Unknown field type %s' % field)
def _is_fromfile_compatible(stream):
"""
Check whether `stream` is compatible with numpy.fromfile.
Passing a gzipped file object to ``fromfile/fromstring`` doesn't work with
Python 3.
"""
bad_cls = []
try:
import gzip
bad_cls.append(gzip.GzipFile)
except ImportError:
pass
try:
import bz2
bad_cls.append(bz2.BZ2File)
except ImportError:
pass
bad_cls = tuple(bad_cls)
return not isinstance(stream, bad_cls)
# -----------------------------------------------------------------------------
if __name__ == '__main__':
import time
for filename in sys.argv[1:]:
print('Reading', filename, '...', end=' ')
sys.stdout.flush()
t = time.time()
mmread(filename)
print('took %s seconds' % (time.time() - t))