354 lines
11 KiB
Python
354 lines
11 KiB
Python
|
"""
|
||
|
|
Module to read / write Fortran unformatted sequential files.
|
||
|
|
|
||
|
|
This is in the spirit of code written by Neil Martinsen-Burrell and Joe Zuntz.
|
||
|
|
|
||
|
|
"""
|
||
|
|
import warnings
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
__all__ = ['FortranFile', 'FortranEOFError', 'FortranFormattingError']
|
||
|
|
|
||
|
|
|
||
|
|
class FortranEOFError(TypeError, IOError):
|
||
|
|
"""Indicates that the file ended properly.
|
||
|
|
|
||
|
|
This error descends from TypeError because the code used to raise
|
||
|
|
TypeError (and this was the only way to know that the file had
|
||
|
|
ended) so users might have ``except TypeError:``.
|
||
|
|
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
|
||
|
|
class FortranFormattingError(TypeError, IOError):
|
||
|
|
"""Indicates that the file ended mid-record.
|
||
|
|
|
||
|
|
Descends from TypeError for backward compatibility.
|
||
|
|
|
||
|
|
"""
|
||
|
|
pass
|
||
|
|
|
||
|
|
|
||
|
|
class FortranFile(object):
|
||
|
|
"""
|
||
|
|
A file object for unformatted sequential files from Fortran code.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
filename : file or str
|
||
|
|
Open file object or filename.
|
||
|
|
mode : {'r', 'w'}, optional
|
||
|
|
Read-write mode, default is 'r'.
|
||
|
|
header_dtype : dtype, optional
|
||
|
|
Data type of the header. Size and endiness must match the input/output file.
|
||
|
|
|
||
|
|
Notes
|
||
|
|
-----
|
||
|
|
These files are broken up into records of unspecified types. The size of
|
||
|
|
each record is given at the start (although the size of this header is not
|
||
|
|
standard) and the data is written onto disk without any formatting. Fortran
|
||
|
|
compilers supporting the BACKSPACE statement will write a second copy of
|
||
|
|
the size to facilitate backwards seeking.
|
||
|
|
|
||
|
|
This class only supports files written with both sizes for the record.
|
||
|
|
It also does not support the subrecords used in Intel and gfortran compilers
|
||
|
|
for records which are greater than 2GB with a 4-byte header.
|
||
|
|
|
||
|
|
An example of an unformatted sequential file in Fortran would be written as::
|
||
|
|
|
||
|
|
OPEN(1, FILE=myfilename, FORM='unformatted')
|
||
|
|
|
||
|
|
WRITE(1) myvariable
|
||
|
|
|
||
|
|
Since this is a non-standard file format, whose contents depend on the
|
||
|
|
compiler and the endianness of the machine, caution is advised. Files from
|
||
|
|
gfortran 4.8.0 and gfortran 4.1.2 on x86_64 are known to work.
|
||
|
|
|
||
|
|
Consider using Fortran direct-access files or files from the newer Stream
|
||
|
|
I/O, which can be easily read by `numpy.fromfile`.
|
||
|
|
|
||
|
|
Examples
|
||
|
|
--------
|
||
|
|
To create an unformatted sequential Fortran file:
|
||
|
|
|
||
|
|
>>> from scipy.io import FortranFile
|
||
|
|
>>> f = FortranFile('test.unf', 'w')
|
||
|
|
>>> f.write_record(np.array([1,2,3,4,5], dtype=np.int32))
|
||
|
|
>>> f.write_record(np.linspace(0,1,20).reshape((5,4)).T)
|
||
|
|
>>> f.close()
|
||
|
|
|
||
|
|
To read this file:
|
||
|
|
|
||
|
|
>>> f = FortranFile('test.unf', 'r')
|
||
|
|
>>> print(f.read_ints(np.int32))
|
||
|
|
[1 2 3 4 5]
|
||
|
|
>>> print(f.read_reals(float).reshape((5,4), order="F"))
|
||
|
|
[[0. 0.05263158 0.10526316 0.15789474]
|
||
|
|
[0.21052632 0.26315789 0.31578947 0.36842105]
|
||
|
|
[0.42105263 0.47368421 0.52631579 0.57894737]
|
||
|
|
[0.63157895 0.68421053 0.73684211 0.78947368]
|
||
|
|
[0.84210526 0.89473684 0.94736842 1. ]]
|
||
|
|
>>> f.close()
|
||
|
|
|
||
|
|
Or, in Fortran::
|
||
|
|
|
||
|
|
integer :: a(5), i
|
||
|
|
double precision :: b(5,4)
|
||
|
|
open(1, file='test.unf', form='unformatted')
|
||
|
|
read(1) a
|
||
|
|
read(1) b
|
||
|
|
close(1)
|
||
|
|
write(*,*) a
|
||
|
|
do i = 1, 5
|
||
|
|
write(*,*) b(i,:)
|
||
|
|
end do
|
||
|
|
|
||
|
|
"""
|
||
|
|
def __init__(self, filename, mode='r', header_dtype=np.uint32):
|
||
|
|
if header_dtype is None:
|
||
|
|
raise ValueError('Must specify dtype')
|
||
|
|
|
||
|
|
header_dtype = np.dtype(header_dtype)
|
||
|
|
if header_dtype.kind != 'u':
|
||
|
|
warnings.warn("Given a dtype which is not unsigned.")
|
||
|
|
|
||
|
|
if mode not in 'rw' or len(mode) != 1:
|
||
|
|
raise ValueError('mode must be either r or w')
|
||
|
|
|
||
|
|
if hasattr(filename, 'seek'):
|
||
|
|
self._fp = filename
|
||
|
|
else:
|
||
|
|
self._fp = open(filename, '%sb' % mode)
|
||
|
|
|
||
|
|
self._header_dtype = header_dtype
|
||
|
|
|
||
|
|
def _read_size(self, eof_ok=False):
|
||
|
|
n = self._header_dtype.itemsize
|
||
|
|
b = self._fp.read(n)
|
||
|
|
if (not b) and eof_ok:
|
||
|
|
raise FortranEOFError("End of file occurred at end of record")
|
||
|
|
elif len(b) < n:
|
||
|
|
raise FortranFormattingError(
|
||
|
|
"End of file in the middle of the record size")
|
||
|
|
return int(np.frombuffer(b, dtype=self._header_dtype, count=1))
|
||
|
|
|
||
|
|
def write_record(self, *items):
|
||
|
|
"""
|
||
|
|
Write a record (including sizes) to the file.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
*items : array_like
|
||
|
|
The data arrays to write.
|
||
|
|
|
||
|
|
Notes
|
||
|
|
-----
|
||
|
|
Writes data items to a file::
|
||
|
|
|
||
|
|
write_record(a.T, b.T, c.T, ...)
|
||
|
|
|
||
|
|
write(1) a, b, c, ...
|
||
|
|
|
||
|
|
Note that data in multidimensional arrays is written in
|
||
|
|
row-major order --- to make them read correctly by Fortran
|
||
|
|
programs, you need to transpose the arrays yourself when
|
||
|
|
writing them.
|
||
|
|
|
||
|
|
"""
|
||
|
|
items = tuple(np.asarray(item) for item in items)
|
||
|
|
total_size = sum(item.nbytes for item in items)
|
||
|
|
|
||
|
|
nb = np.array([total_size], dtype=self._header_dtype)
|
||
|
|
|
||
|
|
nb.tofile(self._fp)
|
||
|
|
for item in items:
|
||
|
|
item.tofile(self._fp)
|
||
|
|
nb.tofile(self._fp)
|
||
|
|
|
||
|
|
def read_record(self, *dtypes, **kwargs):
|
||
|
|
"""
|
||
|
|
Reads a record of a given type from the file.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
*dtypes : dtypes, optional
|
||
|
|
Data type(s) specifying the size and endiness of the data.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
data : ndarray
|
||
|
|
A 1-D array object.
|
||
|
|
|
||
|
|
Raises
|
||
|
|
------
|
||
|
|
FortranEOFError
|
||
|
|
To signal that no further records are available
|
||
|
|
FortranFormattingError
|
||
|
|
To signal that the end of the file was encountered
|
||
|
|
part-way through a record
|
||
|
|
|
||
|
|
Notes
|
||
|
|
-----
|
||
|
|
If the record contains a multidimensional array, you can specify
|
||
|
|
the size in the dtype. For example::
|
||
|
|
|
||
|
|
INTEGER var(5,4)
|
||
|
|
|
||
|
|
can be read with::
|
||
|
|
|
||
|
|
read_record('(4,5)i4').T
|
||
|
|
|
||
|
|
Note that this function does **not** assume the file data is in Fortran
|
||
|
|
column major order, so you need to (i) swap the order of dimensions
|
||
|
|
when reading and (ii) transpose the resulting array.
|
||
|
|
|
||
|
|
Alternatively, you can read the data as a 1-D array and handle the
|
||
|
|
ordering yourself. For example::
|
||
|
|
|
||
|
|
read_record('i4').reshape(5, 4, order='F')
|
||
|
|
|
||
|
|
For records that contain several variables or mixed types (as opposed
|
||
|
|
to single scalar or array types), give them as separate arguments::
|
||
|
|
|
||
|
|
double precision :: a
|
||
|
|
integer :: b
|
||
|
|
write(1) a, b
|
||
|
|
|
||
|
|
record = f.read_record('<f4', '<i4')
|
||
|
|
a = record[0] # first number
|
||
|
|
b = record[1] # second number
|
||
|
|
|
||
|
|
and if any of the variables are arrays, the shape can be specified as
|
||
|
|
the third item in the relevant dtype::
|
||
|
|
|
||
|
|
double precision :: a
|
||
|
|
integer :: b(3,4)
|
||
|
|
write(1) a, b
|
||
|
|
|
||
|
|
record = f.read_record('<f4', np.dtype(('<i4', (4, 3))))
|
||
|
|
a = record[0]
|
||
|
|
b = record[1].T
|
||
|
|
|
||
|
|
NumPy also supports a short syntax for this kind of type::
|
||
|
|
|
||
|
|
record = f.read_record('<f4', '(3,3)<i4')
|
||
|
|
|
||
|
|
See Also
|
||
|
|
--------
|
||
|
|
read_reals
|
||
|
|
read_ints
|
||
|
|
|
||
|
|
"""
|
||
|
|
dtype = kwargs.pop('dtype', None)
|
||
|
|
if kwargs:
|
||
|
|
raise ValueError("Unknown keyword arguments {}".format(tuple(kwargs.keys())))
|
||
|
|
|
||
|
|
if dtype is not None:
|
||
|
|
dtypes = dtypes + (dtype,)
|
||
|
|
elif not dtypes:
|
||
|
|
raise ValueError('Must specify at least one dtype')
|
||
|
|
|
||
|
|
first_size = self._read_size(eof_ok=True)
|
||
|
|
|
||
|
|
dtypes = tuple(np.dtype(dtype) for dtype in dtypes)
|
||
|
|
block_size = sum(dtype.itemsize for dtype in dtypes)
|
||
|
|
|
||
|
|
num_blocks, remainder = divmod(first_size, block_size)
|
||
|
|
if remainder != 0:
|
||
|
|
raise ValueError('Size obtained ({0}) is not a multiple of the '
|
||
|
|
'dtypes given ({1}).'.format(first_size, block_size))
|
||
|
|
|
||
|
|
if len(dtypes) != 1 and first_size != block_size:
|
||
|
|
# Fortran does not write mixed type array items in interleaved order,
|
||
|
|
# and it's not possible to guess the sizes of the arrays that were written.
|
||
|
|
# The user must specify the exact sizes of each of the arrays.
|
||
|
|
raise ValueError('Size obtained ({0}) does not match with the expected '
|
||
|
|
'size ({1}) of multi-item record'.format(first_size, block_size))
|
||
|
|
|
||
|
|
data = []
|
||
|
|
for dtype in dtypes:
|
||
|
|
r = np.fromfile(self._fp, dtype=dtype, count=num_blocks)
|
||
|
|
if len(r) != num_blocks:
|
||
|
|
raise FortranFormattingError(
|
||
|
|
"End of file in the middle of a record")
|
||
|
|
if dtype.shape != ():
|
||
|
|
# Squeeze outmost block dimension for array items
|
||
|
|
if num_blocks == 1:
|
||
|
|
assert r.shape == (1,) + dtype.shape
|
||
|
|
r = r[0]
|
||
|
|
|
||
|
|
data.append(r)
|
||
|
|
|
||
|
|
second_size = self._read_size()
|
||
|
|
if first_size != second_size:
|
||
|
|
raise IOError('Sizes do not agree in the header and footer for '
|
||
|
|
'this record - check header dtype')
|
||
|
|
|
||
|
|
# Unpack result
|
||
|
|
if len(dtypes) == 1:
|
||
|
|
return data[0]
|
||
|
|
else:
|
||
|
|
return tuple(data)
|
||
|
|
|
||
|
|
def read_ints(self, dtype='i4'):
|
||
|
|
"""
|
||
|
|
Reads a record of a given type from the file, defaulting to an integer
|
||
|
|
type (``INTEGER*4`` in Fortran).
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
dtype : dtype, optional
|
||
|
|
Data type specifying the size and endiness of the data.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
data : ndarray
|
||
|
|
A 1-D array object.
|
||
|
|
|
||
|
|
See Also
|
||
|
|
--------
|
||
|
|
read_reals
|
||
|
|
read_record
|
||
|
|
|
||
|
|
"""
|
||
|
|
return self.read_record(dtype)
|
||
|
|
|
||
|
|
def read_reals(self, dtype='f8'):
|
||
|
|
"""
|
||
|
|
Reads a record of a given type from the file, defaulting to a floating
|
||
|
|
point number (``real*8`` in Fortran).
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
dtype : dtype, optional
|
||
|
|
Data type specifying the size and endiness of the data.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
data : ndarray
|
||
|
|
A 1-D array object.
|
||
|
|
|
||
|
|
See Also
|
||
|
|
--------
|
||
|
|
read_ints
|
||
|
|
read_record
|
||
|
|
|
||
|
|
"""
|
||
|
|
return self.read_record(dtype)
|
||
|
|
|
||
|
|
def close(self):
|
||
|
|
"""
|
||
|
|
Closes the file. It is unsupported to call any other methods off this
|
||
|
|
object after closing it. Note that this class supports the 'with'
|
||
|
|
statement in modern versions of Python, to call this automatically
|
||
|
|
|
||
|
|
"""
|
||
|
|
self._fp.close()
|
||
|
|
|
||
|
|
def __enter__(self):
|
||
|
|
return self
|
||
|
|
|
||
|
|
def __exit__(self, type, value, tb):
|
||
|
|
self.close()
|