package scipy

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type tag = [
  1. | `FortranFile
]
type t = [ `FortranFile | `Object ] Obj.t
val of_pyobject : Py.Object.t -> t
val to_pyobject : [> tag ] Obj.t -> Py.Object.t
val create : ?mode:[ `R | `W ] -> ?header_dtype:Np.Dtype.t -> filename:[ `File of Py.Object.t | `S of string ] -> unit -> t

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

val close : [> tag ] Obj.t -> Py.Object.t

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

val read_ints : ?dtype:Np.Dtype.t -> [> tag ] Obj.t -> [ `ArrayLike | `Ndarray | `Object ] Np.Obj.t

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 one-dimensional array object.

See Also -------- read_reals read_record

val read_reals : ?dtype:Np.Dtype.t -> [> tag ] Obj.t -> [ `ArrayLike | `Ndarray | `Object ] Np.Obj.t

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 one-dimensional array object.

See Also -------- read_ints read_record

val read_record : ?kwargs:(string * Py.Object.t) list -> Py.Object.t list -> [> tag ] Obj.t -> [ `ArrayLike | `Ndarray | `Object ] Np.Obj.t

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 one-dimensional 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 multi-dimensional 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 1D 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 = record0 # first number b = record1 # 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 = record0 b = record1.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

val write_record : Py.Object.t list -> [> tag ] Obj.t -> Py.Object.t

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.

val to_string : t -> string

Print the object to a human-readable representation.

val show : t -> string

Print the object to a human-readable representation.

val pp : Format.formatter -> t -> unit

Pretty-print the object to a formatter.

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