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