Inzynierka/Lib/site-packages/scipy/io/_harwell_boeing/hb.py

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2023-06-02 12:51:02 +02:00
"""
Implementation of Harwell-Boeing read/write.
At the moment not the full Harwell-Boeing format is supported. Supported
features are:
- assembled, non-symmetric, real matrices
- integer for pointer/indices
- exponential format for float values, and int format
"""
# TODO:
# - Add more support (symmetric/complex matrices, non-assembled matrices ?)
# XXX: reading is reasonably efficient (>= 85 % is in numpy.fromstring), but
# takes a lot of memory. Being faster would require compiled code.
# write is not efficient. Although not a terribly exciting task,
# having reusable facilities to efficiently read/write fortran-formatted files
# would be useful outside this module.
import warnings
import numpy as np
from scipy.sparse import csc_matrix
from ._fortran_format_parser import FortranFormatParser, IntFormat, ExpFormat
__all__ = ["MalformedHeader", "hb_read", "hb_write", "HBInfo", "HBFile",
"HBMatrixType"]
class MalformedHeader(Exception):
pass
class LineOverflow(Warning):
pass
def _nbytes_full(fmt, nlines):
"""Return the number of bytes to read to get every full lines for the
given parsed fortran format."""
return (fmt.repeat * fmt.width + 1) * (nlines - 1)
class HBInfo:
@classmethod
def from_data(cls, m, title="Default title", key="0", mxtype=None, fmt=None):
"""Create a HBInfo instance from an existing sparse matrix.
Parameters
----------
m : sparse matrix
the HBInfo instance will derive its parameters from m
title : str
Title to put in the HB header
key : str
Key
mxtype : HBMatrixType
type of the input matrix
fmt : dict
not implemented
Returns
-------
hb_info : HBInfo instance
"""
m = m.tocsc(copy=False)
pointer = m.indptr
indices = m.indices
values = m.data
nrows, ncols = m.shape
nnon_zeros = m.nnz
if fmt is None:
# +1 because HB use one-based indexing (Fortran), and we will write
# the indices /pointer as such
pointer_fmt = IntFormat.from_number(np.max(pointer+1))
indices_fmt = IntFormat.from_number(np.max(indices+1))
if values.dtype.kind in np.typecodes["AllFloat"]:
values_fmt = ExpFormat.from_number(-np.max(np.abs(values)))
elif values.dtype.kind in np.typecodes["AllInteger"]:
values_fmt = IntFormat.from_number(-np.max(np.abs(values)))
else:
raise NotImplementedError("type %s not implemented yet" % values.dtype.kind)
else:
raise NotImplementedError("fmt argument not supported yet.")
if mxtype is None:
if not np.isrealobj(values):
raise ValueError("Complex values not supported yet")
if values.dtype.kind in np.typecodes["AllInteger"]:
tp = "integer"
elif values.dtype.kind in np.typecodes["AllFloat"]:
tp = "real"
else:
raise NotImplementedError("type %s for values not implemented"
% values.dtype)
mxtype = HBMatrixType(tp, "unsymmetric", "assembled")
else:
raise ValueError("mxtype argument not handled yet.")
def _nlines(fmt, size):
nlines = size // fmt.repeat
if nlines * fmt.repeat != size:
nlines += 1
return nlines
pointer_nlines = _nlines(pointer_fmt, pointer.size)
indices_nlines = _nlines(indices_fmt, indices.size)
values_nlines = _nlines(values_fmt, values.size)
total_nlines = pointer_nlines + indices_nlines + values_nlines
return cls(title, key,
total_nlines, pointer_nlines, indices_nlines, values_nlines,
mxtype, nrows, ncols, nnon_zeros,
pointer_fmt.fortran_format, indices_fmt.fortran_format,
values_fmt.fortran_format)
@classmethod
def from_file(cls, fid):
"""Create a HBInfo instance from a file object containing a matrix in the
HB format.
Parameters
----------
fid : file-like matrix
File or file-like object containing a matrix in the HB format.
Returns
-------
hb_info : HBInfo instance
"""
# First line
line = fid.readline().strip("\n")
if not len(line) > 72:
raise ValueError("Expected at least 72 characters for first line, "
"got: \n%s" % line)
title = line[:72]
key = line[72:]
# Second line
line = fid.readline().strip("\n")
if not len(line.rstrip()) >= 56:
raise ValueError("Expected at least 56 characters for second line, "
"got: \n%s" % line)
total_nlines = _expect_int(line[:14])
pointer_nlines = _expect_int(line[14:28])
indices_nlines = _expect_int(line[28:42])
values_nlines = _expect_int(line[42:56])
rhs_nlines = line[56:72].strip()
if rhs_nlines == '':
rhs_nlines = 0
else:
rhs_nlines = _expect_int(rhs_nlines)
if not rhs_nlines == 0:
raise ValueError("Only files without right hand side supported for "
"now.")
# Third line
line = fid.readline().strip("\n")
if not len(line) >= 70:
raise ValueError("Expected at least 72 character for third line, got:\n"
"%s" % line)
mxtype_s = line[:3].upper()
if not len(mxtype_s) == 3:
raise ValueError("mxtype expected to be 3 characters long")
mxtype = HBMatrixType.from_fortran(mxtype_s)
if mxtype.value_type not in ["real", "integer"]:
raise ValueError("Only real or integer matrices supported for "
"now (detected %s)" % mxtype)
if not mxtype.structure == "unsymmetric":
raise ValueError("Only unsymmetric matrices supported for "
"now (detected %s)" % mxtype)
if not mxtype.storage == "assembled":
raise ValueError("Only assembled matrices supported for now")
if not line[3:14] == " " * 11:
raise ValueError("Malformed data for third line: %s" % line)
nrows = _expect_int(line[14:28])
ncols = _expect_int(line[28:42])
nnon_zeros = _expect_int(line[42:56])
nelementals = _expect_int(line[56:70])
if not nelementals == 0:
raise ValueError("Unexpected value %d for nltvl (last entry of line 3)"
% nelementals)
# Fourth line
line = fid.readline().strip("\n")
ct = line.split()
if not len(ct) == 3:
raise ValueError("Expected 3 formats, got %s" % ct)
return cls(title, key,
total_nlines, pointer_nlines, indices_nlines, values_nlines,
mxtype, nrows, ncols, nnon_zeros,
ct[0], ct[1], ct[2],
rhs_nlines, nelementals)
def __init__(self, title, key,
total_nlines, pointer_nlines, indices_nlines, values_nlines,
mxtype, nrows, ncols, nnon_zeros,
pointer_format_str, indices_format_str, values_format_str,
right_hand_sides_nlines=0, nelementals=0):
"""Do not use this directly, but the class ctrs (from_* functions)."""
self.title = title
self.key = key
if title is None:
title = "No Title"
if len(title) > 72:
raise ValueError("title cannot be > 72 characters")
if key is None:
key = "|No Key"
if len(key) > 8:
warnings.warn("key is > 8 characters (key is %s)" % key, LineOverflow)
self.total_nlines = total_nlines
self.pointer_nlines = pointer_nlines
self.indices_nlines = indices_nlines
self.values_nlines = values_nlines
parser = FortranFormatParser()
pointer_format = parser.parse(pointer_format_str)
if not isinstance(pointer_format, IntFormat):
raise ValueError("Expected int format for pointer format, got %s"
% pointer_format)
indices_format = parser.parse(indices_format_str)
if not isinstance(indices_format, IntFormat):
raise ValueError("Expected int format for indices format, got %s" %
indices_format)
values_format = parser.parse(values_format_str)
if isinstance(values_format, ExpFormat):
if mxtype.value_type not in ["real", "complex"]:
raise ValueError("Inconsistency between matrix type %s and "
"value type %s" % (mxtype, values_format))
values_dtype = np.float64
elif isinstance(values_format, IntFormat):
if mxtype.value_type not in ["integer"]:
raise ValueError("Inconsistency between matrix type %s and "
"value type %s" % (mxtype, values_format))
# XXX: fortran int -> dtype association ?
values_dtype = int
else:
raise ValueError("Unsupported format for values %r" % (values_format,))
self.pointer_format = pointer_format
self.indices_format = indices_format
self.values_format = values_format
self.pointer_dtype = np.int32
self.indices_dtype = np.int32
self.values_dtype = values_dtype
self.pointer_nlines = pointer_nlines
self.pointer_nbytes_full = _nbytes_full(pointer_format, pointer_nlines)
self.indices_nlines = indices_nlines
self.indices_nbytes_full = _nbytes_full(indices_format, indices_nlines)
self.values_nlines = values_nlines
self.values_nbytes_full = _nbytes_full(values_format, values_nlines)
self.nrows = nrows
self.ncols = ncols
self.nnon_zeros = nnon_zeros
self.nelementals = nelementals
self.mxtype = mxtype
def dump(self):
"""Gives the header corresponding to this instance as a string."""
header = [self.title.ljust(72) + self.key.ljust(8)]
header.append("%14d%14d%14d%14d" %
(self.total_nlines, self.pointer_nlines,
self.indices_nlines, self.values_nlines))
header.append("%14s%14d%14d%14d%14d" %
(self.mxtype.fortran_format.ljust(14), self.nrows,
self.ncols, self.nnon_zeros, 0))
pffmt = self.pointer_format.fortran_format
iffmt = self.indices_format.fortran_format
vffmt = self.values_format.fortran_format
header.append("%16s%16s%20s" %
(pffmt.ljust(16), iffmt.ljust(16), vffmt.ljust(20)))
return "\n".join(header)
def _expect_int(value, msg=None):
try:
return int(value)
except ValueError as e:
if msg is None:
msg = "Expected an int, got %s"
raise ValueError(msg % value) from e
def _read_hb_data(content, header):
# XXX: look at a way to reduce memory here (big string creation)
ptr_string = "".join([content.read(header.pointer_nbytes_full),
content.readline()])
ptr = np.fromstring(ptr_string,
dtype=int, sep=' ')
ind_string = "".join([content.read(header.indices_nbytes_full),
content.readline()])
ind = np.fromstring(ind_string,
dtype=int, sep=' ')
val_string = "".join([content.read(header.values_nbytes_full),
content.readline()])
val = np.fromstring(val_string,
dtype=header.values_dtype, sep=' ')
try:
return csc_matrix((val, ind-1, ptr-1),
shape=(header.nrows, header.ncols))
except ValueError as e:
raise e
def _write_data(m, fid, header):
m = m.tocsc(copy=False)
def write_array(f, ar, nlines, fmt):
# ar_nlines is the number of full lines, n is the number of items per
# line, ffmt the fortran format
pyfmt = fmt.python_format
pyfmt_full = pyfmt * fmt.repeat
# for each array to write, we first write the full lines, and special
# case for partial line
full = ar[:(nlines - 1) * fmt.repeat]
for row in full.reshape((nlines-1, fmt.repeat)):
f.write(pyfmt_full % tuple(row) + "\n")
nremain = ar.size - full.size
if nremain > 0:
f.write((pyfmt * nremain) % tuple(ar[ar.size - nremain:]) + "\n")
fid.write(header.dump())
fid.write("\n")
# +1 is for Fortran one-based indexing
write_array(fid, m.indptr+1, header.pointer_nlines,
header.pointer_format)
write_array(fid, m.indices+1, header.indices_nlines,
header.indices_format)
write_array(fid, m.data, header.values_nlines,
header.values_format)
class HBMatrixType:
"""Class to hold the matrix type."""
# q2f* translates qualified names to Fortran character
_q2f_type = {
"real": "R",
"complex": "C",
"pattern": "P",
"integer": "I",
}
_q2f_structure = {
"symmetric": "S",
"unsymmetric": "U",
"hermitian": "H",
"skewsymmetric": "Z",
"rectangular": "R"
}
_q2f_storage = {
"assembled": "A",
"elemental": "E",
}
_f2q_type = dict([(j, i) for i, j in _q2f_type.items()])
_f2q_structure = dict([(j, i) for i, j in _q2f_structure.items()])
_f2q_storage = dict([(j, i) for i, j in _q2f_storage.items()])
@classmethod
def from_fortran(cls, fmt):
if not len(fmt) == 3:
raise ValueError("Fortran format for matrix type should be 3 "
"characters long")
try:
value_type = cls._f2q_type[fmt[0]]
structure = cls._f2q_structure[fmt[1]]
storage = cls._f2q_storage[fmt[2]]
return cls(value_type, structure, storage)
except KeyError as e:
raise ValueError("Unrecognized format %s" % fmt) from e
def __init__(self, value_type, structure, storage="assembled"):
self.value_type = value_type
self.structure = structure
self.storage = storage
if value_type not in self._q2f_type:
raise ValueError("Unrecognized type %s" % value_type)
if structure not in self._q2f_structure:
raise ValueError("Unrecognized structure %s" % structure)
if storage not in self._q2f_storage:
raise ValueError("Unrecognized storage %s" % storage)
@property
def fortran_format(self):
return self._q2f_type[self.value_type] + \
self._q2f_structure[self.structure] + \
self._q2f_storage[self.storage]
def __repr__(self):
return "HBMatrixType(%s, %s, %s)" % \
(self.value_type, self.structure, self.storage)
class HBFile:
def __init__(self, file, hb_info=None):
"""Create a HBFile instance.
Parameters
----------
file : file-object
StringIO work as well
hb_info : HBInfo, optional
Should be given as an argument for writing, in which case the file
should be writable.
"""
self._fid = file
if hb_info is None:
self._hb_info = HBInfo.from_file(file)
else:
#raise OSError("file %s is not writable, and hb_info "
# "was given." % file)
self._hb_info = hb_info
@property
def title(self):
return self._hb_info.title
@property
def key(self):
return self._hb_info.key
@property
def type(self):
return self._hb_info.mxtype.value_type
@property
def structure(self):
return self._hb_info.mxtype.structure
@property
def storage(self):
return self._hb_info.mxtype.storage
def read_matrix(self):
return _read_hb_data(self._fid, self._hb_info)
def write_matrix(self, m):
return _write_data(m, self._fid, self._hb_info)
def hb_read(path_or_open_file):
"""Read HB-format file.
Parameters
----------
path_or_open_file : path-like or file-like
If a file-like object, it is used as-is. Otherwise, it is opened
before reading.
Returns
-------
data : scipy.sparse.csc_matrix instance
The data read from the HB file as a sparse matrix.
Notes
-----
At the moment not the full Harwell-Boeing format is supported. Supported
features are:
- assembled, non-symmetric, real matrices
- integer for pointer/indices
- exponential format for float values, and int format
Examples
--------
We can read and write a harwell-boeing format file:
>>> from scipy.io import hb_read, hb_write
>>> from scipy.sparse import csr_matrix, eye
>>> data = csr_matrix(eye(3)) # create a sparse matrix
>>> hb_write("data.hb", data) # write a hb file
>>> print(hb_read("data.hb")) # read a hb file
(0, 0) 1.0
(1, 1) 1.0
(2, 2) 1.0
"""
def _get_matrix(fid):
hb = HBFile(fid)
return hb.read_matrix()
if hasattr(path_or_open_file, 'read'):
return _get_matrix(path_or_open_file)
else:
with open(path_or_open_file) as f:
return _get_matrix(f)
def hb_write(path_or_open_file, m, hb_info=None):
"""Write HB-format file.
Parameters
----------
path_or_open_file : path-like or file-like
If a file-like object, it is used as-is. Otherwise, it is opened
before writing.
m : sparse-matrix
the sparse matrix to write
hb_info : HBInfo
contains the meta-data for write
Returns
-------
None
Notes
-----
At the moment not the full Harwell-Boeing format is supported. Supported
features are:
- assembled, non-symmetric, real matrices
- integer for pointer/indices
- exponential format for float values, and int format
Examples
--------
We can read and write a harwell-boeing format file:
>>> from scipy.io import hb_read, hb_write
>>> from scipy.sparse import csr_matrix, eye
>>> data = csr_matrix(eye(3)) # create a sparse matrix
>>> hb_write("data.hb", data) # write a hb file
>>> print(hb_read("data.hb")) # read a hb file
(0, 0) 1.0
(1, 1) 1.0
(2, 2) 1.0
"""
m = m.tocsc(copy=False)
if hb_info is None:
hb_info = HBInfo.from_data(m)
def _set_matrix(fid):
hb = HBFile(fid, hb_info)
return hb.write_matrix(m)
if hasattr(path_or_open_file, 'write'):
return _set_matrix(path_or_open_file)
else:
with open(path_or_open_file, 'w') as f:
return _set_matrix(f)